failure mechanisms of insulated gate bipolar … failure mechanisms of insulated gate bipolar...

30
Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Nathan Valentine, Dr. Diganta Das, and Prof. Michael Pecht www.calce.umd.edu Center for Advanced Life Cycle Engineering (CALCE) 2015 NREL Photovoltaic Reliability Workshop [email protected] TM University of Maryland Prognostics and Health Management Consortium 1 calce Copyright © 2015 CALCE

Upload: hadien

Post on 17-Mar-2018

260 views

Category:

Documents


7 download

TRANSCRIPT

Page 1: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)

Nathan Valentine Dr Diganta Das and Prof Michael Pecht wwwcalceumdedu

Center for Advanced Life Cycle Engineering (CALCE) 2015 NREL Photovoltaic Reliability Workshop

digantaumdedu

TM University of MarylandPrognostics and Health Management Consortium 11calce Copyright copy 2015 CALCE

   

CALCE Introduction

bull The Center for Advanced Life Cycle Engineering (CALCE) formally started in 1984 as a NSF Center of Excellence in systems reliability

bull One of the worldrsquos most advanced and comprehensive testing and failure analysis laboratories

bull Funded at $6M by over 150 of the worldrsquos leading companies bull Supported by over 100 faculty visiting scientists and research

assistants bull Received NSF Innovation Award and NDIA Systems Engineering

Excellence Award in 2009 and IEEE Standards Education Award in 2013

TM University of MarylandPrognostics and Health Management Consortium 22calce Copyright copy 2015 CALCE

IGBT Applications bull Need for more compact power converters achieved through faster device

switching bull IGBTs are the ideal choice with switching frequencies of 1kHz-150kHz and

current handling of up to 1500A

Electric Trains TM University of MarylandPrognostics and Health Management Consortium 33calce Copyright copy 2015 CALCE

Electric CarsInduction Heating Units Power Converters

Uninterruptible Power Supplies Wind Turbines

IGBT Technologies

Source Infineon

TM University of MarylandPrognostics and Health Management Consortium 44calce Copyright copy 2015 CALCE

University of Maryland Copyright copy 2015 CALCE

5 calceTM 5 Prognostics and Health Management Consortium

Failed Wind Turbine IGBT Module

Unused IGBT Failed IGBT which experienced a thermal runaway burning the module

University of Maryland Copyright copy 2015 CALCE

6 calceTM 6 Prognostics and Health Management Consortium

Steps in Reliability Evaluation

bull  Quantify the life cycle conditions bull  Failure Modes Mechanisms and Effects Analysis

(FMMEA) gt reliability analysis assess design tradeoffs and reviseupdate design

bull  Part material and supplier selection bull  Virtual qualification (VQ) including stress and

thermal analysis

University of Maryland Copyright copy 2015 CALCE

7 calceTM 7 Prognostics and Health Management Consortium

FMMEA Methodology

Identify life cycle profile

Identify potential failure modes

Identify potential failure mechanisms

Identify failure models

Define system and identify elements and functions to be analyzed

Identify potential failure causes

Prioritize failure mechanisms

Document the process

University of Maryland Copyright copy 2015 CALCE

8 calceTM 8 Prognostics and Health Management Consortium

IGBT Failure Modes and Mechanisms

bull  Failure modes in an IGBT are simple at top level ndash  Short circuit ndash  Open circuit ndash  Parameter drift

bull  Parameter drift occurs as a part degrades and the electrical characteristics such as VCE(ON) or ICE drift from the acceptable operating range due to the accumulation of damage within a device or module

University of Maryland Copyright copy 2015 CALCE

9 calceTM 9 Prognostics and Health Management Consortium

Failure Modes and Mechanisms Potential Failure Modes (Sites)

Short circuit loss of gate control increased leakage current (Oxide)

Potential Failure Causes

High temperature high electric field overvoltage

Potential Failure Mechanisms (Parameters

affected)

Time dependent dielectric breakdown (Vth gm)

High leakage currents (Oxide OxideSubstrate

Interface)

Overvoltage high current densities Hot electrons (Vth gm)

Loss of gate control device burn-out (Silicon die)

High electric field overvoltage ionizing

radiation Latch-up (VCE(ON))

Open Circuit (Bond Wire)

High temperature high current densities Bond Wire Cracking

Lift Off (VCE(ON))

Open Circuit (Die Attach)

Voiding Delamination of Die

Attach (VCE(ON))

High temperature high current densities

University of Maryland Copyright copy 2015 CALCE

10 calceTM 10 Prognostics and Health Management Consortium

Examples of Failure Models Failure Mechanism Failure Sites Failure Causes Failure Models

Fatigue

Die attach WirebondTAB Solder leads Bond pads

Traces ViasPTHs Interfaces

Cyclic Deformations

(Δ T Δ H Δ V)

Nonlinear Power Law (Coffin-Manson)

Corrosion Metallizations M ΔV T chemical Eyring (Howard)

Electromigration Metallizations T J Eyring (Black)

Conductive Filament Formation

Between Metallizations M ΛV Power Law (Rudra)

Stress Driven Diffusion Voiding

Metal Traces σ T Eyring (Okabayashi)

Time Dependent Dielectric Breakdown

Dielectric layers V T Arrhenius (Fowler-Nordheim)

Δ Cyclic range V Voltage Λ gradient M Moisture T Temperature J Current density H Humidity σ Stress

University of Maryland Copyright copy 2015 CALCE

11 calceTM 11 Prognostics and Health Management Consortium

Thermal Analysis Vibrational Analysis

Shock Analysis Failure Analysis

calcePWA Circuit Card Assemblies

Failure Analysis

calceEP Device andPackage

calceFAST Failure Assessment

Software Toolkit

httpwwwcalceumdedusoftware

CALCE Simulation Assisted Reliability Assessment (SARAreg) Software

Conductor II

Conductor I

Whisker

Spacing (ls)

calceTinWhisker FailureRiskCalculator

University of Maryland Copyright copy 2015 CALCE

12 calceTM 12 Prognostics and Health Management Consortium

Thermally-Induced Stresses in IGBT

Material13 CTE (10-6 K-1)13 Conductivity (W m-1 K-1)13

A12O3 13 68 13 2413 AlN 13 4713 17013

Si3N413 2713 6013 BeO13 913 25013 Al13 23513 23713 Cu13 17513 39413 Mo13 5113 13813 Si13 2613 14813

AlSiC13 7513 20013 - Bond Wire Fatigue - Solder Joint Fatigue

University of Maryland Copyright copy 2015 CALCE

13 calceTM 13 Prognostics and Health Management Consortium

IGBT Power Cycling Experiment

bull  IGBT samples were power cycled between specified temperatures TMin and TMax The devices were switched at 1 or 5 kHz Cooling was carried out passively by exposure to ambient temperature

bull  This lsquopowerrsquo (thermal) cycling was repeated until failure occurred by latchup or by failure to ldquoturn onrdquo

TMax

TMin

Switching at 1 or 5 kHz

Heating

Cooling

Time Power cycling illustration

University of Maryland Copyright copy 2015 CALCE

14 calceTM 14 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Internal PNP Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

15 calceTM 15 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Parasitic NPN Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

16 calceTM 16 Prognostics and Health Management Consortium

Die Attach Acoustic Scan Images

New IGBT sample Failure to turn on after 3126 power cycles ΔT = 75degC Die attach shows delamination

Delaminated surface

Failure by latchup after 1010 power cycles ΔT = 100degC Melting T of die attach = 233degC

Specification sheet for Sn65Ag25Sb10 solder from Indium Corp Indalloy 209

Melted die attach

University of Maryland Copyright copy 2015 CALCE

17 calceTM 17 Prognostics and Health Management Consortium

Bond Wire Failures

Bond Wire Cracking Bond Wire Liftoff

University of Maryland Copyright copy 2015 CALCE

18 calceTM 18 Prognostics and Health Management Consortium

Lifetime Statistics of Experimental Results

150-200C Data β = 226 η = 7134 ρ = 096

125-225C Data β = 260 η = 1191 ρ = 096

1 kHz 5 kHz

60 duty cycle

2P-Weibull with 95 confidence bounds

MTTF = 6320

MTTF = 1058

ANOVA p-value = 76E-6 there4 Different distributions

University of Maryland Copyright copy 2015 CALCE

19 calceTM 19 Prognostics and Health Management Consortium

Prediction of Other Reliability Metrics Temperature Range MTTF (Cycles) [B5Life B95Life]

(Cycles) 150-200degC 6320 cycles [1922 11582] 125-225degC 1058 cycles [381 1815]

MTTF varies with loading conditions and from part to part Predicting service life of an IGBT based on a population MTTF results in a high uncertainty

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 2: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

   

CALCE Introduction

bull The Center for Advanced Life Cycle Engineering (CALCE) formally started in 1984 as a NSF Center of Excellence in systems reliability

bull One of the worldrsquos most advanced and comprehensive testing and failure analysis laboratories

bull Funded at $6M by over 150 of the worldrsquos leading companies bull Supported by over 100 faculty visiting scientists and research

assistants bull Received NSF Innovation Award and NDIA Systems Engineering

Excellence Award in 2009 and IEEE Standards Education Award in 2013

TM University of MarylandPrognostics and Health Management Consortium 22calce Copyright copy 2015 CALCE

IGBT Applications bull Need for more compact power converters achieved through faster device

switching bull IGBTs are the ideal choice with switching frequencies of 1kHz-150kHz and

current handling of up to 1500A

Electric Trains TM University of MarylandPrognostics and Health Management Consortium 33calce Copyright copy 2015 CALCE

Electric CarsInduction Heating Units Power Converters

Uninterruptible Power Supplies Wind Turbines

IGBT Technologies

Source Infineon

TM University of MarylandPrognostics and Health Management Consortium 44calce Copyright copy 2015 CALCE

University of Maryland Copyright copy 2015 CALCE

5 calceTM 5 Prognostics and Health Management Consortium

Failed Wind Turbine IGBT Module

Unused IGBT Failed IGBT which experienced a thermal runaway burning the module

University of Maryland Copyright copy 2015 CALCE

6 calceTM 6 Prognostics and Health Management Consortium

Steps in Reliability Evaluation

bull  Quantify the life cycle conditions bull  Failure Modes Mechanisms and Effects Analysis

(FMMEA) gt reliability analysis assess design tradeoffs and reviseupdate design

bull  Part material and supplier selection bull  Virtual qualification (VQ) including stress and

thermal analysis

University of Maryland Copyright copy 2015 CALCE

7 calceTM 7 Prognostics and Health Management Consortium

FMMEA Methodology

Identify life cycle profile

Identify potential failure modes

Identify potential failure mechanisms

Identify failure models

Define system and identify elements and functions to be analyzed

Identify potential failure causes

Prioritize failure mechanisms

Document the process

University of Maryland Copyright copy 2015 CALCE

8 calceTM 8 Prognostics and Health Management Consortium

IGBT Failure Modes and Mechanisms

bull  Failure modes in an IGBT are simple at top level ndash  Short circuit ndash  Open circuit ndash  Parameter drift

bull  Parameter drift occurs as a part degrades and the electrical characteristics such as VCE(ON) or ICE drift from the acceptable operating range due to the accumulation of damage within a device or module

University of Maryland Copyright copy 2015 CALCE

9 calceTM 9 Prognostics and Health Management Consortium

Failure Modes and Mechanisms Potential Failure Modes (Sites)

Short circuit loss of gate control increased leakage current (Oxide)

Potential Failure Causes

High temperature high electric field overvoltage

Potential Failure Mechanisms (Parameters

affected)

Time dependent dielectric breakdown (Vth gm)

High leakage currents (Oxide OxideSubstrate

Interface)

Overvoltage high current densities Hot electrons (Vth gm)

Loss of gate control device burn-out (Silicon die)

High electric field overvoltage ionizing

radiation Latch-up (VCE(ON))

Open Circuit (Bond Wire)

High temperature high current densities Bond Wire Cracking

Lift Off (VCE(ON))

Open Circuit (Die Attach)

Voiding Delamination of Die

Attach (VCE(ON))

High temperature high current densities

University of Maryland Copyright copy 2015 CALCE

10 calceTM 10 Prognostics and Health Management Consortium

Examples of Failure Models Failure Mechanism Failure Sites Failure Causes Failure Models

Fatigue

Die attach WirebondTAB Solder leads Bond pads

Traces ViasPTHs Interfaces

Cyclic Deformations

(Δ T Δ H Δ V)

Nonlinear Power Law (Coffin-Manson)

Corrosion Metallizations M ΔV T chemical Eyring (Howard)

Electromigration Metallizations T J Eyring (Black)

Conductive Filament Formation

Between Metallizations M ΛV Power Law (Rudra)

Stress Driven Diffusion Voiding

Metal Traces σ T Eyring (Okabayashi)

Time Dependent Dielectric Breakdown

Dielectric layers V T Arrhenius (Fowler-Nordheim)

Δ Cyclic range V Voltage Λ gradient M Moisture T Temperature J Current density H Humidity σ Stress

University of Maryland Copyright copy 2015 CALCE

11 calceTM 11 Prognostics and Health Management Consortium

Thermal Analysis Vibrational Analysis

Shock Analysis Failure Analysis

calcePWA Circuit Card Assemblies

Failure Analysis

calceEP Device andPackage

calceFAST Failure Assessment

Software Toolkit

httpwwwcalceumdedusoftware

CALCE Simulation Assisted Reliability Assessment (SARAreg) Software

Conductor II

Conductor I

Whisker

Spacing (ls)

calceTinWhisker FailureRiskCalculator

University of Maryland Copyright copy 2015 CALCE

12 calceTM 12 Prognostics and Health Management Consortium

Thermally-Induced Stresses in IGBT

Material13 CTE (10-6 K-1)13 Conductivity (W m-1 K-1)13

A12O3 13 68 13 2413 AlN 13 4713 17013

Si3N413 2713 6013 BeO13 913 25013 Al13 23513 23713 Cu13 17513 39413 Mo13 5113 13813 Si13 2613 14813

AlSiC13 7513 20013 - Bond Wire Fatigue - Solder Joint Fatigue

University of Maryland Copyright copy 2015 CALCE

13 calceTM 13 Prognostics and Health Management Consortium

IGBT Power Cycling Experiment

bull  IGBT samples were power cycled between specified temperatures TMin and TMax The devices were switched at 1 or 5 kHz Cooling was carried out passively by exposure to ambient temperature

bull  This lsquopowerrsquo (thermal) cycling was repeated until failure occurred by latchup or by failure to ldquoturn onrdquo

TMax

TMin

Switching at 1 or 5 kHz

Heating

Cooling

Time Power cycling illustration

University of Maryland Copyright copy 2015 CALCE

14 calceTM 14 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Internal PNP Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

15 calceTM 15 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Parasitic NPN Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

16 calceTM 16 Prognostics and Health Management Consortium

Die Attach Acoustic Scan Images

New IGBT sample Failure to turn on after 3126 power cycles ΔT = 75degC Die attach shows delamination

Delaminated surface

Failure by latchup after 1010 power cycles ΔT = 100degC Melting T of die attach = 233degC

Specification sheet for Sn65Ag25Sb10 solder from Indium Corp Indalloy 209

Melted die attach

University of Maryland Copyright copy 2015 CALCE

17 calceTM 17 Prognostics and Health Management Consortium

Bond Wire Failures

Bond Wire Cracking Bond Wire Liftoff

University of Maryland Copyright copy 2015 CALCE

18 calceTM 18 Prognostics and Health Management Consortium

Lifetime Statistics of Experimental Results

150-200C Data β = 226 η = 7134 ρ = 096

125-225C Data β = 260 η = 1191 ρ = 096

1 kHz 5 kHz

60 duty cycle

2P-Weibull with 95 confidence bounds

MTTF = 6320

MTTF = 1058

ANOVA p-value = 76E-6 there4 Different distributions

University of Maryland Copyright copy 2015 CALCE

19 calceTM 19 Prognostics and Health Management Consortium

Prediction of Other Reliability Metrics Temperature Range MTTF (Cycles) [B5Life B95Life]

(Cycles) 150-200degC 6320 cycles [1922 11582] 125-225degC 1058 cycles [381 1815]

MTTF varies with loading conditions and from part to part Predicting service life of an IGBT based on a population MTTF results in a high uncertainty

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 3: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

IGBT Applications bull Need for more compact power converters achieved through faster device

switching bull IGBTs are the ideal choice with switching frequencies of 1kHz-150kHz and

current handling of up to 1500A

Electric Trains TM University of MarylandPrognostics and Health Management Consortium 33calce Copyright copy 2015 CALCE

Electric CarsInduction Heating Units Power Converters

Uninterruptible Power Supplies Wind Turbines

IGBT Technologies

Source Infineon

TM University of MarylandPrognostics and Health Management Consortium 44calce Copyright copy 2015 CALCE

University of Maryland Copyright copy 2015 CALCE

5 calceTM 5 Prognostics and Health Management Consortium

Failed Wind Turbine IGBT Module

Unused IGBT Failed IGBT which experienced a thermal runaway burning the module

University of Maryland Copyright copy 2015 CALCE

6 calceTM 6 Prognostics and Health Management Consortium

Steps in Reliability Evaluation

bull  Quantify the life cycle conditions bull  Failure Modes Mechanisms and Effects Analysis

(FMMEA) gt reliability analysis assess design tradeoffs and reviseupdate design

bull  Part material and supplier selection bull  Virtual qualification (VQ) including stress and

thermal analysis

University of Maryland Copyright copy 2015 CALCE

7 calceTM 7 Prognostics and Health Management Consortium

FMMEA Methodology

Identify life cycle profile

Identify potential failure modes

Identify potential failure mechanisms

Identify failure models

Define system and identify elements and functions to be analyzed

Identify potential failure causes

Prioritize failure mechanisms

Document the process

University of Maryland Copyright copy 2015 CALCE

8 calceTM 8 Prognostics and Health Management Consortium

IGBT Failure Modes and Mechanisms

bull  Failure modes in an IGBT are simple at top level ndash  Short circuit ndash  Open circuit ndash  Parameter drift

bull  Parameter drift occurs as a part degrades and the electrical characteristics such as VCE(ON) or ICE drift from the acceptable operating range due to the accumulation of damage within a device or module

University of Maryland Copyright copy 2015 CALCE

9 calceTM 9 Prognostics and Health Management Consortium

Failure Modes and Mechanisms Potential Failure Modes (Sites)

Short circuit loss of gate control increased leakage current (Oxide)

Potential Failure Causes

High temperature high electric field overvoltage

Potential Failure Mechanisms (Parameters

affected)

Time dependent dielectric breakdown (Vth gm)

High leakage currents (Oxide OxideSubstrate

Interface)

Overvoltage high current densities Hot electrons (Vth gm)

Loss of gate control device burn-out (Silicon die)

High electric field overvoltage ionizing

radiation Latch-up (VCE(ON))

Open Circuit (Bond Wire)

High temperature high current densities Bond Wire Cracking

Lift Off (VCE(ON))

Open Circuit (Die Attach)

Voiding Delamination of Die

Attach (VCE(ON))

High temperature high current densities

University of Maryland Copyright copy 2015 CALCE

10 calceTM 10 Prognostics and Health Management Consortium

Examples of Failure Models Failure Mechanism Failure Sites Failure Causes Failure Models

Fatigue

Die attach WirebondTAB Solder leads Bond pads

Traces ViasPTHs Interfaces

Cyclic Deformations

(Δ T Δ H Δ V)

Nonlinear Power Law (Coffin-Manson)

Corrosion Metallizations M ΔV T chemical Eyring (Howard)

Electromigration Metallizations T J Eyring (Black)

Conductive Filament Formation

Between Metallizations M ΛV Power Law (Rudra)

Stress Driven Diffusion Voiding

Metal Traces σ T Eyring (Okabayashi)

Time Dependent Dielectric Breakdown

Dielectric layers V T Arrhenius (Fowler-Nordheim)

Δ Cyclic range V Voltage Λ gradient M Moisture T Temperature J Current density H Humidity σ Stress

University of Maryland Copyright copy 2015 CALCE

11 calceTM 11 Prognostics and Health Management Consortium

Thermal Analysis Vibrational Analysis

Shock Analysis Failure Analysis

calcePWA Circuit Card Assemblies

Failure Analysis

calceEP Device andPackage

calceFAST Failure Assessment

Software Toolkit

httpwwwcalceumdedusoftware

CALCE Simulation Assisted Reliability Assessment (SARAreg) Software

Conductor II

Conductor I

Whisker

Spacing (ls)

calceTinWhisker FailureRiskCalculator

University of Maryland Copyright copy 2015 CALCE

12 calceTM 12 Prognostics and Health Management Consortium

Thermally-Induced Stresses in IGBT

Material13 CTE (10-6 K-1)13 Conductivity (W m-1 K-1)13

A12O3 13 68 13 2413 AlN 13 4713 17013

Si3N413 2713 6013 BeO13 913 25013 Al13 23513 23713 Cu13 17513 39413 Mo13 5113 13813 Si13 2613 14813

AlSiC13 7513 20013 - Bond Wire Fatigue - Solder Joint Fatigue

University of Maryland Copyright copy 2015 CALCE

13 calceTM 13 Prognostics and Health Management Consortium

IGBT Power Cycling Experiment

bull  IGBT samples were power cycled between specified temperatures TMin and TMax The devices were switched at 1 or 5 kHz Cooling was carried out passively by exposure to ambient temperature

bull  This lsquopowerrsquo (thermal) cycling was repeated until failure occurred by latchup or by failure to ldquoturn onrdquo

TMax

TMin

Switching at 1 or 5 kHz

Heating

Cooling

Time Power cycling illustration

University of Maryland Copyright copy 2015 CALCE

14 calceTM 14 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Internal PNP Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

15 calceTM 15 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Parasitic NPN Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

16 calceTM 16 Prognostics and Health Management Consortium

Die Attach Acoustic Scan Images

New IGBT sample Failure to turn on after 3126 power cycles ΔT = 75degC Die attach shows delamination

Delaminated surface

Failure by latchup after 1010 power cycles ΔT = 100degC Melting T of die attach = 233degC

Specification sheet for Sn65Ag25Sb10 solder from Indium Corp Indalloy 209

Melted die attach

University of Maryland Copyright copy 2015 CALCE

17 calceTM 17 Prognostics and Health Management Consortium

Bond Wire Failures

Bond Wire Cracking Bond Wire Liftoff

University of Maryland Copyright copy 2015 CALCE

18 calceTM 18 Prognostics and Health Management Consortium

Lifetime Statistics of Experimental Results

150-200C Data β = 226 η = 7134 ρ = 096

125-225C Data β = 260 η = 1191 ρ = 096

1 kHz 5 kHz

60 duty cycle

2P-Weibull with 95 confidence bounds

MTTF = 6320

MTTF = 1058

ANOVA p-value = 76E-6 there4 Different distributions

University of Maryland Copyright copy 2015 CALCE

19 calceTM 19 Prognostics and Health Management Consortium

Prediction of Other Reliability Metrics Temperature Range MTTF (Cycles) [B5Life B95Life]

(Cycles) 150-200degC 6320 cycles [1922 11582] 125-225degC 1058 cycles [381 1815]

MTTF varies with loading conditions and from part to part Predicting service life of an IGBT based on a population MTTF results in a high uncertainty

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 4: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

IGBT Technologies

Source Infineon

TM University of MarylandPrognostics and Health Management Consortium 44calce Copyright copy 2015 CALCE

University of Maryland Copyright copy 2015 CALCE

5 calceTM 5 Prognostics and Health Management Consortium

Failed Wind Turbine IGBT Module

Unused IGBT Failed IGBT which experienced a thermal runaway burning the module

University of Maryland Copyright copy 2015 CALCE

6 calceTM 6 Prognostics and Health Management Consortium

Steps in Reliability Evaluation

bull  Quantify the life cycle conditions bull  Failure Modes Mechanisms and Effects Analysis

(FMMEA) gt reliability analysis assess design tradeoffs and reviseupdate design

bull  Part material and supplier selection bull  Virtual qualification (VQ) including stress and

thermal analysis

University of Maryland Copyright copy 2015 CALCE

7 calceTM 7 Prognostics and Health Management Consortium

FMMEA Methodology

Identify life cycle profile

Identify potential failure modes

Identify potential failure mechanisms

Identify failure models

Define system and identify elements and functions to be analyzed

Identify potential failure causes

Prioritize failure mechanisms

Document the process

University of Maryland Copyright copy 2015 CALCE

8 calceTM 8 Prognostics and Health Management Consortium

IGBT Failure Modes and Mechanisms

bull  Failure modes in an IGBT are simple at top level ndash  Short circuit ndash  Open circuit ndash  Parameter drift

bull  Parameter drift occurs as a part degrades and the electrical characteristics such as VCE(ON) or ICE drift from the acceptable operating range due to the accumulation of damage within a device or module

University of Maryland Copyright copy 2015 CALCE

9 calceTM 9 Prognostics and Health Management Consortium

Failure Modes and Mechanisms Potential Failure Modes (Sites)

Short circuit loss of gate control increased leakage current (Oxide)

Potential Failure Causes

High temperature high electric field overvoltage

Potential Failure Mechanisms (Parameters

affected)

Time dependent dielectric breakdown (Vth gm)

High leakage currents (Oxide OxideSubstrate

Interface)

Overvoltage high current densities Hot electrons (Vth gm)

Loss of gate control device burn-out (Silicon die)

High electric field overvoltage ionizing

radiation Latch-up (VCE(ON))

Open Circuit (Bond Wire)

High temperature high current densities Bond Wire Cracking

Lift Off (VCE(ON))

Open Circuit (Die Attach)

Voiding Delamination of Die

Attach (VCE(ON))

High temperature high current densities

University of Maryland Copyright copy 2015 CALCE

10 calceTM 10 Prognostics and Health Management Consortium

Examples of Failure Models Failure Mechanism Failure Sites Failure Causes Failure Models

Fatigue

Die attach WirebondTAB Solder leads Bond pads

Traces ViasPTHs Interfaces

Cyclic Deformations

(Δ T Δ H Δ V)

Nonlinear Power Law (Coffin-Manson)

Corrosion Metallizations M ΔV T chemical Eyring (Howard)

Electromigration Metallizations T J Eyring (Black)

Conductive Filament Formation

Between Metallizations M ΛV Power Law (Rudra)

Stress Driven Diffusion Voiding

Metal Traces σ T Eyring (Okabayashi)

Time Dependent Dielectric Breakdown

Dielectric layers V T Arrhenius (Fowler-Nordheim)

Δ Cyclic range V Voltage Λ gradient M Moisture T Temperature J Current density H Humidity σ Stress

University of Maryland Copyright copy 2015 CALCE

11 calceTM 11 Prognostics and Health Management Consortium

Thermal Analysis Vibrational Analysis

Shock Analysis Failure Analysis

calcePWA Circuit Card Assemblies

Failure Analysis

calceEP Device andPackage

calceFAST Failure Assessment

Software Toolkit

httpwwwcalceumdedusoftware

CALCE Simulation Assisted Reliability Assessment (SARAreg) Software

Conductor II

Conductor I

Whisker

Spacing (ls)

calceTinWhisker FailureRiskCalculator

University of Maryland Copyright copy 2015 CALCE

12 calceTM 12 Prognostics and Health Management Consortium

Thermally-Induced Stresses in IGBT

Material13 CTE (10-6 K-1)13 Conductivity (W m-1 K-1)13

A12O3 13 68 13 2413 AlN 13 4713 17013

Si3N413 2713 6013 BeO13 913 25013 Al13 23513 23713 Cu13 17513 39413 Mo13 5113 13813 Si13 2613 14813

AlSiC13 7513 20013 - Bond Wire Fatigue - Solder Joint Fatigue

University of Maryland Copyright copy 2015 CALCE

13 calceTM 13 Prognostics and Health Management Consortium

IGBT Power Cycling Experiment

bull  IGBT samples were power cycled between specified temperatures TMin and TMax The devices were switched at 1 or 5 kHz Cooling was carried out passively by exposure to ambient temperature

bull  This lsquopowerrsquo (thermal) cycling was repeated until failure occurred by latchup or by failure to ldquoturn onrdquo

TMax

TMin

Switching at 1 or 5 kHz

Heating

Cooling

Time Power cycling illustration

University of Maryland Copyright copy 2015 CALCE

14 calceTM 14 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Internal PNP Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

15 calceTM 15 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Parasitic NPN Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

16 calceTM 16 Prognostics and Health Management Consortium

Die Attach Acoustic Scan Images

New IGBT sample Failure to turn on after 3126 power cycles ΔT = 75degC Die attach shows delamination

Delaminated surface

Failure by latchup after 1010 power cycles ΔT = 100degC Melting T of die attach = 233degC

Specification sheet for Sn65Ag25Sb10 solder from Indium Corp Indalloy 209

Melted die attach

University of Maryland Copyright copy 2015 CALCE

17 calceTM 17 Prognostics and Health Management Consortium

Bond Wire Failures

Bond Wire Cracking Bond Wire Liftoff

University of Maryland Copyright copy 2015 CALCE

18 calceTM 18 Prognostics and Health Management Consortium

Lifetime Statistics of Experimental Results

150-200C Data β = 226 η = 7134 ρ = 096

125-225C Data β = 260 η = 1191 ρ = 096

1 kHz 5 kHz

60 duty cycle

2P-Weibull with 95 confidence bounds

MTTF = 6320

MTTF = 1058

ANOVA p-value = 76E-6 there4 Different distributions

University of Maryland Copyright copy 2015 CALCE

19 calceTM 19 Prognostics and Health Management Consortium

Prediction of Other Reliability Metrics Temperature Range MTTF (Cycles) [B5Life B95Life]

(Cycles) 150-200degC 6320 cycles [1922 11582] 125-225degC 1058 cycles [381 1815]

MTTF varies with loading conditions and from part to part Predicting service life of an IGBT based on a population MTTF results in a high uncertainty

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 5: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

5 calceTM 5 Prognostics and Health Management Consortium

Failed Wind Turbine IGBT Module

Unused IGBT Failed IGBT which experienced a thermal runaway burning the module

University of Maryland Copyright copy 2015 CALCE

6 calceTM 6 Prognostics and Health Management Consortium

Steps in Reliability Evaluation

bull  Quantify the life cycle conditions bull  Failure Modes Mechanisms and Effects Analysis

(FMMEA) gt reliability analysis assess design tradeoffs and reviseupdate design

bull  Part material and supplier selection bull  Virtual qualification (VQ) including stress and

thermal analysis

University of Maryland Copyright copy 2015 CALCE

7 calceTM 7 Prognostics and Health Management Consortium

FMMEA Methodology

Identify life cycle profile

Identify potential failure modes

Identify potential failure mechanisms

Identify failure models

Define system and identify elements and functions to be analyzed

Identify potential failure causes

Prioritize failure mechanisms

Document the process

University of Maryland Copyright copy 2015 CALCE

8 calceTM 8 Prognostics and Health Management Consortium

IGBT Failure Modes and Mechanisms

bull  Failure modes in an IGBT are simple at top level ndash  Short circuit ndash  Open circuit ndash  Parameter drift

bull  Parameter drift occurs as a part degrades and the electrical characteristics such as VCE(ON) or ICE drift from the acceptable operating range due to the accumulation of damage within a device or module

University of Maryland Copyright copy 2015 CALCE

9 calceTM 9 Prognostics and Health Management Consortium

Failure Modes and Mechanisms Potential Failure Modes (Sites)

Short circuit loss of gate control increased leakage current (Oxide)

Potential Failure Causes

High temperature high electric field overvoltage

Potential Failure Mechanisms (Parameters

affected)

Time dependent dielectric breakdown (Vth gm)

High leakage currents (Oxide OxideSubstrate

Interface)

Overvoltage high current densities Hot electrons (Vth gm)

Loss of gate control device burn-out (Silicon die)

High electric field overvoltage ionizing

radiation Latch-up (VCE(ON))

Open Circuit (Bond Wire)

High temperature high current densities Bond Wire Cracking

Lift Off (VCE(ON))

Open Circuit (Die Attach)

Voiding Delamination of Die

Attach (VCE(ON))

High temperature high current densities

University of Maryland Copyright copy 2015 CALCE

10 calceTM 10 Prognostics and Health Management Consortium

Examples of Failure Models Failure Mechanism Failure Sites Failure Causes Failure Models

Fatigue

Die attach WirebondTAB Solder leads Bond pads

Traces ViasPTHs Interfaces

Cyclic Deformations

(Δ T Δ H Δ V)

Nonlinear Power Law (Coffin-Manson)

Corrosion Metallizations M ΔV T chemical Eyring (Howard)

Electromigration Metallizations T J Eyring (Black)

Conductive Filament Formation

Between Metallizations M ΛV Power Law (Rudra)

Stress Driven Diffusion Voiding

Metal Traces σ T Eyring (Okabayashi)

Time Dependent Dielectric Breakdown

Dielectric layers V T Arrhenius (Fowler-Nordheim)

Δ Cyclic range V Voltage Λ gradient M Moisture T Temperature J Current density H Humidity σ Stress

University of Maryland Copyright copy 2015 CALCE

11 calceTM 11 Prognostics and Health Management Consortium

Thermal Analysis Vibrational Analysis

Shock Analysis Failure Analysis

calcePWA Circuit Card Assemblies

Failure Analysis

calceEP Device andPackage

calceFAST Failure Assessment

Software Toolkit

httpwwwcalceumdedusoftware

CALCE Simulation Assisted Reliability Assessment (SARAreg) Software

Conductor II

Conductor I

Whisker

Spacing (ls)

calceTinWhisker FailureRiskCalculator

University of Maryland Copyright copy 2015 CALCE

12 calceTM 12 Prognostics and Health Management Consortium

Thermally-Induced Stresses in IGBT

Material13 CTE (10-6 K-1)13 Conductivity (W m-1 K-1)13

A12O3 13 68 13 2413 AlN 13 4713 17013

Si3N413 2713 6013 BeO13 913 25013 Al13 23513 23713 Cu13 17513 39413 Mo13 5113 13813 Si13 2613 14813

AlSiC13 7513 20013 - Bond Wire Fatigue - Solder Joint Fatigue

University of Maryland Copyright copy 2015 CALCE

13 calceTM 13 Prognostics and Health Management Consortium

IGBT Power Cycling Experiment

bull  IGBT samples were power cycled between specified temperatures TMin and TMax The devices were switched at 1 or 5 kHz Cooling was carried out passively by exposure to ambient temperature

bull  This lsquopowerrsquo (thermal) cycling was repeated until failure occurred by latchup or by failure to ldquoturn onrdquo

TMax

TMin

Switching at 1 or 5 kHz

Heating

Cooling

Time Power cycling illustration

University of Maryland Copyright copy 2015 CALCE

14 calceTM 14 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Internal PNP Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

15 calceTM 15 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Parasitic NPN Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

16 calceTM 16 Prognostics and Health Management Consortium

Die Attach Acoustic Scan Images

New IGBT sample Failure to turn on after 3126 power cycles ΔT = 75degC Die attach shows delamination

Delaminated surface

Failure by latchup after 1010 power cycles ΔT = 100degC Melting T of die attach = 233degC

Specification sheet for Sn65Ag25Sb10 solder from Indium Corp Indalloy 209

Melted die attach

University of Maryland Copyright copy 2015 CALCE

17 calceTM 17 Prognostics and Health Management Consortium

Bond Wire Failures

Bond Wire Cracking Bond Wire Liftoff

University of Maryland Copyright copy 2015 CALCE

18 calceTM 18 Prognostics and Health Management Consortium

Lifetime Statistics of Experimental Results

150-200C Data β = 226 η = 7134 ρ = 096

125-225C Data β = 260 η = 1191 ρ = 096

1 kHz 5 kHz

60 duty cycle

2P-Weibull with 95 confidence bounds

MTTF = 6320

MTTF = 1058

ANOVA p-value = 76E-6 there4 Different distributions

University of Maryland Copyright copy 2015 CALCE

19 calceTM 19 Prognostics and Health Management Consortium

Prediction of Other Reliability Metrics Temperature Range MTTF (Cycles) [B5Life B95Life]

(Cycles) 150-200degC 6320 cycles [1922 11582] 125-225degC 1058 cycles [381 1815]

MTTF varies with loading conditions and from part to part Predicting service life of an IGBT based on a population MTTF results in a high uncertainty

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 6: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

6 calceTM 6 Prognostics and Health Management Consortium

Steps in Reliability Evaluation

bull  Quantify the life cycle conditions bull  Failure Modes Mechanisms and Effects Analysis

(FMMEA) gt reliability analysis assess design tradeoffs and reviseupdate design

bull  Part material and supplier selection bull  Virtual qualification (VQ) including stress and

thermal analysis

University of Maryland Copyright copy 2015 CALCE

7 calceTM 7 Prognostics and Health Management Consortium

FMMEA Methodology

Identify life cycle profile

Identify potential failure modes

Identify potential failure mechanisms

Identify failure models

Define system and identify elements and functions to be analyzed

Identify potential failure causes

Prioritize failure mechanisms

Document the process

University of Maryland Copyright copy 2015 CALCE

8 calceTM 8 Prognostics and Health Management Consortium

IGBT Failure Modes and Mechanisms

bull  Failure modes in an IGBT are simple at top level ndash  Short circuit ndash  Open circuit ndash  Parameter drift

bull  Parameter drift occurs as a part degrades and the electrical characteristics such as VCE(ON) or ICE drift from the acceptable operating range due to the accumulation of damage within a device or module

University of Maryland Copyright copy 2015 CALCE

9 calceTM 9 Prognostics and Health Management Consortium

Failure Modes and Mechanisms Potential Failure Modes (Sites)

Short circuit loss of gate control increased leakage current (Oxide)

Potential Failure Causes

High temperature high electric field overvoltage

Potential Failure Mechanisms (Parameters

affected)

Time dependent dielectric breakdown (Vth gm)

High leakage currents (Oxide OxideSubstrate

Interface)

Overvoltage high current densities Hot electrons (Vth gm)

Loss of gate control device burn-out (Silicon die)

High electric field overvoltage ionizing

radiation Latch-up (VCE(ON))

Open Circuit (Bond Wire)

High temperature high current densities Bond Wire Cracking

Lift Off (VCE(ON))

Open Circuit (Die Attach)

Voiding Delamination of Die

Attach (VCE(ON))

High temperature high current densities

University of Maryland Copyright copy 2015 CALCE

10 calceTM 10 Prognostics and Health Management Consortium

Examples of Failure Models Failure Mechanism Failure Sites Failure Causes Failure Models

Fatigue

Die attach WirebondTAB Solder leads Bond pads

Traces ViasPTHs Interfaces

Cyclic Deformations

(Δ T Δ H Δ V)

Nonlinear Power Law (Coffin-Manson)

Corrosion Metallizations M ΔV T chemical Eyring (Howard)

Electromigration Metallizations T J Eyring (Black)

Conductive Filament Formation

Between Metallizations M ΛV Power Law (Rudra)

Stress Driven Diffusion Voiding

Metal Traces σ T Eyring (Okabayashi)

Time Dependent Dielectric Breakdown

Dielectric layers V T Arrhenius (Fowler-Nordheim)

Δ Cyclic range V Voltage Λ gradient M Moisture T Temperature J Current density H Humidity σ Stress

University of Maryland Copyright copy 2015 CALCE

11 calceTM 11 Prognostics and Health Management Consortium

Thermal Analysis Vibrational Analysis

Shock Analysis Failure Analysis

calcePWA Circuit Card Assemblies

Failure Analysis

calceEP Device andPackage

calceFAST Failure Assessment

Software Toolkit

httpwwwcalceumdedusoftware

CALCE Simulation Assisted Reliability Assessment (SARAreg) Software

Conductor II

Conductor I

Whisker

Spacing (ls)

calceTinWhisker FailureRiskCalculator

University of Maryland Copyright copy 2015 CALCE

12 calceTM 12 Prognostics and Health Management Consortium

Thermally-Induced Stresses in IGBT

Material13 CTE (10-6 K-1)13 Conductivity (W m-1 K-1)13

A12O3 13 68 13 2413 AlN 13 4713 17013

Si3N413 2713 6013 BeO13 913 25013 Al13 23513 23713 Cu13 17513 39413 Mo13 5113 13813 Si13 2613 14813

AlSiC13 7513 20013 - Bond Wire Fatigue - Solder Joint Fatigue

University of Maryland Copyright copy 2015 CALCE

13 calceTM 13 Prognostics and Health Management Consortium

IGBT Power Cycling Experiment

bull  IGBT samples were power cycled between specified temperatures TMin and TMax The devices were switched at 1 or 5 kHz Cooling was carried out passively by exposure to ambient temperature

bull  This lsquopowerrsquo (thermal) cycling was repeated until failure occurred by latchup or by failure to ldquoturn onrdquo

TMax

TMin

Switching at 1 or 5 kHz

Heating

Cooling

Time Power cycling illustration

University of Maryland Copyright copy 2015 CALCE

14 calceTM 14 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Internal PNP Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

15 calceTM 15 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Parasitic NPN Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

16 calceTM 16 Prognostics and Health Management Consortium

Die Attach Acoustic Scan Images

New IGBT sample Failure to turn on after 3126 power cycles ΔT = 75degC Die attach shows delamination

Delaminated surface

Failure by latchup after 1010 power cycles ΔT = 100degC Melting T of die attach = 233degC

Specification sheet for Sn65Ag25Sb10 solder from Indium Corp Indalloy 209

Melted die attach

University of Maryland Copyright copy 2015 CALCE

17 calceTM 17 Prognostics and Health Management Consortium

Bond Wire Failures

Bond Wire Cracking Bond Wire Liftoff

University of Maryland Copyright copy 2015 CALCE

18 calceTM 18 Prognostics and Health Management Consortium

Lifetime Statistics of Experimental Results

150-200C Data β = 226 η = 7134 ρ = 096

125-225C Data β = 260 η = 1191 ρ = 096

1 kHz 5 kHz

60 duty cycle

2P-Weibull with 95 confidence bounds

MTTF = 6320

MTTF = 1058

ANOVA p-value = 76E-6 there4 Different distributions

University of Maryland Copyright copy 2015 CALCE

19 calceTM 19 Prognostics and Health Management Consortium

Prediction of Other Reliability Metrics Temperature Range MTTF (Cycles) [B5Life B95Life]

(Cycles) 150-200degC 6320 cycles [1922 11582] 125-225degC 1058 cycles [381 1815]

MTTF varies with loading conditions and from part to part Predicting service life of an IGBT based on a population MTTF results in a high uncertainty

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 7: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

7 calceTM 7 Prognostics and Health Management Consortium

FMMEA Methodology

Identify life cycle profile

Identify potential failure modes

Identify potential failure mechanisms

Identify failure models

Define system and identify elements and functions to be analyzed

Identify potential failure causes

Prioritize failure mechanisms

Document the process

University of Maryland Copyright copy 2015 CALCE

8 calceTM 8 Prognostics and Health Management Consortium

IGBT Failure Modes and Mechanisms

bull  Failure modes in an IGBT are simple at top level ndash  Short circuit ndash  Open circuit ndash  Parameter drift

bull  Parameter drift occurs as a part degrades and the electrical characteristics such as VCE(ON) or ICE drift from the acceptable operating range due to the accumulation of damage within a device or module

University of Maryland Copyright copy 2015 CALCE

9 calceTM 9 Prognostics and Health Management Consortium

Failure Modes and Mechanisms Potential Failure Modes (Sites)

Short circuit loss of gate control increased leakage current (Oxide)

Potential Failure Causes

High temperature high electric field overvoltage

Potential Failure Mechanisms (Parameters

affected)

Time dependent dielectric breakdown (Vth gm)

High leakage currents (Oxide OxideSubstrate

Interface)

Overvoltage high current densities Hot electrons (Vth gm)

Loss of gate control device burn-out (Silicon die)

High electric field overvoltage ionizing

radiation Latch-up (VCE(ON))

Open Circuit (Bond Wire)

High temperature high current densities Bond Wire Cracking

Lift Off (VCE(ON))

Open Circuit (Die Attach)

Voiding Delamination of Die

Attach (VCE(ON))

High temperature high current densities

University of Maryland Copyright copy 2015 CALCE

10 calceTM 10 Prognostics and Health Management Consortium

Examples of Failure Models Failure Mechanism Failure Sites Failure Causes Failure Models

Fatigue

Die attach WirebondTAB Solder leads Bond pads

Traces ViasPTHs Interfaces

Cyclic Deformations

(Δ T Δ H Δ V)

Nonlinear Power Law (Coffin-Manson)

Corrosion Metallizations M ΔV T chemical Eyring (Howard)

Electromigration Metallizations T J Eyring (Black)

Conductive Filament Formation

Between Metallizations M ΛV Power Law (Rudra)

Stress Driven Diffusion Voiding

Metal Traces σ T Eyring (Okabayashi)

Time Dependent Dielectric Breakdown

Dielectric layers V T Arrhenius (Fowler-Nordheim)

Δ Cyclic range V Voltage Λ gradient M Moisture T Temperature J Current density H Humidity σ Stress

University of Maryland Copyright copy 2015 CALCE

11 calceTM 11 Prognostics and Health Management Consortium

Thermal Analysis Vibrational Analysis

Shock Analysis Failure Analysis

calcePWA Circuit Card Assemblies

Failure Analysis

calceEP Device andPackage

calceFAST Failure Assessment

Software Toolkit

httpwwwcalceumdedusoftware

CALCE Simulation Assisted Reliability Assessment (SARAreg) Software

Conductor II

Conductor I

Whisker

Spacing (ls)

calceTinWhisker FailureRiskCalculator

University of Maryland Copyright copy 2015 CALCE

12 calceTM 12 Prognostics and Health Management Consortium

Thermally-Induced Stresses in IGBT

Material13 CTE (10-6 K-1)13 Conductivity (W m-1 K-1)13

A12O3 13 68 13 2413 AlN 13 4713 17013

Si3N413 2713 6013 BeO13 913 25013 Al13 23513 23713 Cu13 17513 39413 Mo13 5113 13813 Si13 2613 14813

AlSiC13 7513 20013 - Bond Wire Fatigue - Solder Joint Fatigue

University of Maryland Copyright copy 2015 CALCE

13 calceTM 13 Prognostics and Health Management Consortium

IGBT Power Cycling Experiment

bull  IGBT samples were power cycled between specified temperatures TMin and TMax The devices were switched at 1 or 5 kHz Cooling was carried out passively by exposure to ambient temperature

bull  This lsquopowerrsquo (thermal) cycling was repeated until failure occurred by latchup or by failure to ldquoturn onrdquo

TMax

TMin

Switching at 1 or 5 kHz

Heating

Cooling

Time Power cycling illustration

University of Maryland Copyright copy 2015 CALCE

14 calceTM 14 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Internal PNP Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

15 calceTM 15 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Parasitic NPN Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

16 calceTM 16 Prognostics and Health Management Consortium

Die Attach Acoustic Scan Images

New IGBT sample Failure to turn on after 3126 power cycles ΔT = 75degC Die attach shows delamination

Delaminated surface

Failure by latchup after 1010 power cycles ΔT = 100degC Melting T of die attach = 233degC

Specification sheet for Sn65Ag25Sb10 solder from Indium Corp Indalloy 209

Melted die attach

University of Maryland Copyright copy 2015 CALCE

17 calceTM 17 Prognostics and Health Management Consortium

Bond Wire Failures

Bond Wire Cracking Bond Wire Liftoff

University of Maryland Copyright copy 2015 CALCE

18 calceTM 18 Prognostics and Health Management Consortium

Lifetime Statistics of Experimental Results

150-200C Data β = 226 η = 7134 ρ = 096

125-225C Data β = 260 η = 1191 ρ = 096

1 kHz 5 kHz

60 duty cycle

2P-Weibull with 95 confidence bounds

MTTF = 6320

MTTF = 1058

ANOVA p-value = 76E-6 there4 Different distributions

University of Maryland Copyright copy 2015 CALCE

19 calceTM 19 Prognostics and Health Management Consortium

Prediction of Other Reliability Metrics Temperature Range MTTF (Cycles) [B5Life B95Life]

(Cycles) 150-200degC 6320 cycles [1922 11582] 125-225degC 1058 cycles [381 1815]

MTTF varies with loading conditions and from part to part Predicting service life of an IGBT based on a population MTTF results in a high uncertainty

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 8: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

8 calceTM 8 Prognostics and Health Management Consortium

IGBT Failure Modes and Mechanisms

bull  Failure modes in an IGBT are simple at top level ndash  Short circuit ndash  Open circuit ndash  Parameter drift

bull  Parameter drift occurs as a part degrades and the electrical characteristics such as VCE(ON) or ICE drift from the acceptable operating range due to the accumulation of damage within a device or module

University of Maryland Copyright copy 2015 CALCE

9 calceTM 9 Prognostics and Health Management Consortium

Failure Modes and Mechanisms Potential Failure Modes (Sites)

Short circuit loss of gate control increased leakage current (Oxide)

Potential Failure Causes

High temperature high electric field overvoltage

Potential Failure Mechanisms (Parameters

affected)

Time dependent dielectric breakdown (Vth gm)

High leakage currents (Oxide OxideSubstrate

Interface)

Overvoltage high current densities Hot electrons (Vth gm)

Loss of gate control device burn-out (Silicon die)

High electric field overvoltage ionizing

radiation Latch-up (VCE(ON))

Open Circuit (Bond Wire)

High temperature high current densities Bond Wire Cracking

Lift Off (VCE(ON))

Open Circuit (Die Attach)

Voiding Delamination of Die

Attach (VCE(ON))

High temperature high current densities

University of Maryland Copyright copy 2015 CALCE

10 calceTM 10 Prognostics and Health Management Consortium

Examples of Failure Models Failure Mechanism Failure Sites Failure Causes Failure Models

Fatigue

Die attach WirebondTAB Solder leads Bond pads

Traces ViasPTHs Interfaces

Cyclic Deformations

(Δ T Δ H Δ V)

Nonlinear Power Law (Coffin-Manson)

Corrosion Metallizations M ΔV T chemical Eyring (Howard)

Electromigration Metallizations T J Eyring (Black)

Conductive Filament Formation

Between Metallizations M ΛV Power Law (Rudra)

Stress Driven Diffusion Voiding

Metal Traces σ T Eyring (Okabayashi)

Time Dependent Dielectric Breakdown

Dielectric layers V T Arrhenius (Fowler-Nordheim)

Δ Cyclic range V Voltage Λ gradient M Moisture T Temperature J Current density H Humidity σ Stress

University of Maryland Copyright copy 2015 CALCE

11 calceTM 11 Prognostics and Health Management Consortium

Thermal Analysis Vibrational Analysis

Shock Analysis Failure Analysis

calcePWA Circuit Card Assemblies

Failure Analysis

calceEP Device andPackage

calceFAST Failure Assessment

Software Toolkit

httpwwwcalceumdedusoftware

CALCE Simulation Assisted Reliability Assessment (SARAreg) Software

Conductor II

Conductor I

Whisker

Spacing (ls)

calceTinWhisker FailureRiskCalculator

University of Maryland Copyright copy 2015 CALCE

12 calceTM 12 Prognostics and Health Management Consortium

Thermally-Induced Stresses in IGBT

Material13 CTE (10-6 K-1)13 Conductivity (W m-1 K-1)13

A12O3 13 68 13 2413 AlN 13 4713 17013

Si3N413 2713 6013 BeO13 913 25013 Al13 23513 23713 Cu13 17513 39413 Mo13 5113 13813 Si13 2613 14813

AlSiC13 7513 20013 - Bond Wire Fatigue - Solder Joint Fatigue

University of Maryland Copyright copy 2015 CALCE

13 calceTM 13 Prognostics and Health Management Consortium

IGBT Power Cycling Experiment

bull  IGBT samples were power cycled between specified temperatures TMin and TMax The devices were switched at 1 or 5 kHz Cooling was carried out passively by exposure to ambient temperature

bull  This lsquopowerrsquo (thermal) cycling was repeated until failure occurred by latchup or by failure to ldquoturn onrdquo

TMax

TMin

Switching at 1 or 5 kHz

Heating

Cooling

Time Power cycling illustration

University of Maryland Copyright copy 2015 CALCE

14 calceTM 14 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Internal PNP Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

15 calceTM 15 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Parasitic NPN Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

16 calceTM 16 Prognostics and Health Management Consortium

Die Attach Acoustic Scan Images

New IGBT sample Failure to turn on after 3126 power cycles ΔT = 75degC Die attach shows delamination

Delaminated surface

Failure by latchup after 1010 power cycles ΔT = 100degC Melting T of die attach = 233degC

Specification sheet for Sn65Ag25Sb10 solder from Indium Corp Indalloy 209

Melted die attach

University of Maryland Copyright copy 2015 CALCE

17 calceTM 17 Prognostics and Health Management Consortium

Bond Wire Failures

Bond Wire Cracking Bond Wire Liftoff

University of Maryland Copyright copy 2015 CALCE

18 calceTM 18 Prognostics and Health Management Consortium

Lifetime Statistics of Experimental Results

150-200C Data β = 226 η = 7134 ρ = 096

125-225C Data β = 260 η = 1191 ρ = 096

1 kHz 5 kHz

60 duty cycle

2P-Weibull with 95 confidence bounds

MTTF = 6320

MTTF = 1058

ANOVA p-value = 76E-6 there4 Different distributions

University of Maryland Copyright copy 2015 CALCE

19 calceTM 19 Prognostics and Health Management Consortium

Prediction of Other Reliability Metrics Temperature Range MTTF (Cycles) [B5Life B95Life]

(Cycles) 150-200degC 6320 cycles [1922 11582] 125-225degC 1058 cycles [381 1815]

MTTF varies with loading conditions and from part to part Predicting service life of an IGBT based on a population MTTF results in a high uncertainty

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 9: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

9 calceTM 9 Prognostics and Health Management Consortium

Failure Modes and Mechanisms Potential Failure Modes (Sites)

Short circuit loss of gate control increased leakage current (Oxide)

Potential Failure Causes

High temperature high electric field overvoltage

Potential Failure Mechanisms (Parameters

affected)

Time dependent dielectric breakdown (Vth gm)

High leakage currents (Oxide OxideSubstrate

Interface)

Overvoltage high current densities Hot electrons (Vth gm)

Loss of gate control device burn-out (Silicon die)

High electric field overvoltage ionizing

radiation Latch-up (VCE(ON))

Open Circuit (Bond Wire)

High temperature high current densities Bond Wire Cracking

Lift Off (VCE(ON))

Open Circuit (Die Attach)

Voiding Delamination of Die

Attach (VCE(ON))

High temperature high current densities

University of Maryland Copyright copy 2015 CALCE

10 calceTM 10 Prognostics and Health Management Consortium

Examples of Failure Models Failure Mechanism Failure Sites Failure Causes Failure Models

Fatigue

Die attach WirebondTAB Solder leads Bond pads

Traces ViasPTHs Interfaces

Cyclic Deformations

(Δ T Δ H Δ V)

Nonlinear Power Law (Coffin-Manson)

Corrosion Metallizations M ΔV T chemical Eyring (Howard)

Electromigration Metallizations T J Eyring (Black)

Conductive Filament Formation

Between Metallizations M ΛV Power Law (Rudra)

Stress Driven Diffusion Voiding

Metal Traces σ T Eyring (Okabayashi)

Time Dependent Dielectric Breakdown

Dielectric layers V T Arrhenius (Fowler-Nordheim)

Δ Cyclic range V Voltage Λ gradient M Moisture T Temperature J Current density H Humidity σ Stress

University of Maryland Copyright copy 2015 CALCE

11 calceTM 11 Prognostics and Health Management Consortium

Thermal Analysis Vibrational Analysis

Shock Analysis Failure Analysis

calcePWA Circuit Card Assemblies

Failure Analysis

calceEP Device andPackage

calceFAST Failure Assessment

Software Toolkit

httpwwwcalceumdedusoftware

CALCE Simulation Assisted Reliability Assessment (SARAreg) Software

Conductor II

Conductor I

Whisker

Spacing (ls)

calceTinWhisker FailureRiskCalculator

University of Maryland Copyright copy 2015 CALCE

12 calceTM 12 Prognostics and Health Management Consortium

Thermally-Induced Stresses in IGBT

Material13 CTE (10-6 K-1)13 Conductivity (W m-1 K-1)13

A12O3 13 68 13 2413 AlN 13 4713 17013

Si3N413 2713 6013 BeO13 913 25013 Al13 23513 23713 Cu13 17513 39413 Mo13 5113 13813 Si13 2613 14813

AlSiC13 7513 20013 - Bond Wire Fatigue - Solder Joint Fatigue

University of Maryland Copyright copy 2015 CALCE

13 calceTM 13 Prognostics and Health Management Consortium

IGBT Power Cycling Experiment

bull  IGBT samples were power cycled between specified temperatures TMin and TMax The devices were switched at 1 or 5 kHz Cooling was carried out passively by exposure to ambient temperature

bull  This lsquopowerrsquo (thermal) cycling was repeated until failure occurred by latchup or by failure to ldquoturn onrdquo

TMax

TMin

Switching at 1 or 5 kHz

Heating

Cooling

Time Power cycling illustration

University of Maryland Copyright copy 2015 CALCE

14 calceTM 14 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Internal PNP Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

15 calceTM 15 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Parasitic NPN Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

16 calceTM 16 Prognostics and Health Management Consortium

Die Attach Acoustic Scan Images

New IGBT sample Failure to turn on after 3126 power cycles ΔT = 75degC Die attach shows delamination

Delaminated surface

Failure by latchup after 1010 power cycles ΔT = 100degC Melting T of die attach = 233degC

Specification sheet for Sn65Ag25Sb10 solder from Indium Corp Indalloy 209

Melted die attach

University of Maryland Copyright copy 2015 CALCE

17 calceTM 17 Prognostics and Health Management Consortium

Bond Wire Failures

Bond Wire Cracking Bond Wire Liftoff

University of Maryland Copyright copy 2015 CALCE

18 calceTM 18 Prognostics and Health Management Consortium

Lifetime Statistics of Experimental Results

150-200C Data β = 226 η = 7134 ρ = 096

125-225C Data β = 260 η = 1191 ρ = 096

1 kHz 5 kHz

60 duty cycle

2P-Weibull with 95 confidence bounds

MTTF = 6320

MTTF = 1058

ANOVA p-value = 76E-6 there4 Different distributions

University of Maryland Copyright copy 2015 CALCE

19 calceTM 19 Prognostics and Health Management Consortium

Prediction of Other Reliability Metrics Temperature Range MTTF (Cycles) [B5Life B95Life]

(Cycles) 150-200degC 6320 cycles [1922 11582] 125-225degC 1058 cycles [381 1815]

MTTF varies with loading conditions and from part to part Predicting service life of an IGBT based on a population MTTF results in a high uncertainty

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 10: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

10 calceTM 10 Prognostics and Health Management Consortium

Examples of Failure Models Failure Mechanism Failure Sites Failure Causes Failure Models

Fatigue

Die attach WirebondTAB Solder leads Bond pads

Traces ViasPTHs Interfaces

Cyclic Deformations

(Δ T Δ H Δ V)

Nonlinear Power Law (Coffin-Manson)

Corrosion Metallizations M ΔV T chemical Eyring (Howard)

Electromigration Metallizations T J Eyring (Black)

Conductive Filament Formation

Between Metallizations M ΛV Power Law (Rudra)

Stress Driven Diffusion Voiding

Metal Traces σ T Eyring (Okabayashi)

Time Dependent Dielectric Breakdown

Dielectric layers V T Arrhenius (Fowler-Nordheim)

Δ Cyclic range V Voltage Λ gradient M Moisture T Temperature J Current density H Humidity σ Stress

University of Maryland Copyright copy 2015 CALCE

11 calceTM 11 Prognostics and Health Management Consortium

Thermal Analysis Vibrational Analysis

Shock Analysis Failure Analysis

calcePWA Circuit Card Assemblies

Failure Analysis

calceEP Device andPackage

calceFAST Failure Assessment

Software Toolkit

httpwwwcalceumdedusoftware

CALCE Simulation Assisted Reliability Assessment (SARAreg) Software

Conductor II

Conductor I

Whisker

Spacing (ls)

calceTinWhisker FailureRiskCalculator

University of Maryland Copyright copy 2015 CALCE

12 calceTM 12 Prognostics and Health Management Consortium

Thermally-Induced Stresses in IGBT

Material13 CTE (10-6 K-1)13 Conductivity (W m-1 K-1)13

A12O3 13 68 13 2413 AlN 13 4713 17013

Si3N413 2713 6013 BeO13 913 25013 Al13 23513 23713 Cu13 17513 39413 Mo13 5113 13813 Si13 2613 14813

AlSiC13 7513 20013 - Bond Wire Fatigue - Solder Joint Fatigue

University of Maryland Copyright copy 2015 CALCE

13 calceTM 13 Prognostics and Health Management Consortium

IGBT Power Cycling Experiment

bull  IGBT samples were power cycled between specified temperatures TMin and TMax The devices were switched at 1 or 5 kHz Cooling was carried out passively by exposure to ambient temperature

bull  This lsquopowerrsquo (thermal) cycling was repeated until failure occurred by latchup or by failure to ldquoturn onrdquo

TMax

TMin

Switching at 1 or 5 kHz

Heating

Cooling

Time Power cycling illustration

University of Maryland Copyright copy 2015 CALCE

14 calceTM 14 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Internal PNP Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

15 calceTM 15 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Parasitic NPN Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

16 calceTM 16 Prognostics and Health Management Consortium

Die Attach Acoustic Scan Images

New IGBT sample Failure to turn on after 3126 power cycles ΔT = 75degC Die attach shows delamination

Delaminated surface

Failure by latchup after 1010 power cycles ΔT = 100degC Melting T of die attach = 233degC

Specification sheet for Sn65Ag25Sb10 solder from Indium Corp Indalloy 209

Melted die attach

University of Maryland Copyright copy 2015 CALCE

17 calceTM 17 Prognostics and Health Management Consortium

Bond Wire Failures

Bond Wire Cracking Bond Wire Liftoff

University of Maryland Copyright copy 2015 CALCE

18 calceTM 18 Prognostics and Health Management Consortium

Lifetime Statistics of Experimental Results

150-200C Data β = 226 η = 7134 ρ = 096

125-225C Data β = 260 η = 1191 ρ = 096

1 kHz 5 kHz

60 duty cycle

2P-Weibull with 95 confidence bounds

MTTF = 6320

MTTF = 1058

ANOVA p-value = 76E-6 there4 Different distributions

University of Maryland Copyright copy 2015 CALCE

19 calceTM 19 Prognostics and Health Management Consortium

Prediction of Other Reliability Metrics Temperature Range MTTF (Cycles) [B5Life B95Life]

(Cycles) 150-200degC 6320 cycles [1922 11582] 125-225degC 1058 cycles [381 1815]

MTTF varies with loading conditions and from part to part Predicting service life of an IGBT based on a population MTTF results in a high uncertainty

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 11: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

11 calceTM 11 Prognostics and Health Management Consortium

Thermal Analysis Vibrational Analysis

Shock Analysis Failure Analysis

calcePWA Circuit Card Assemblies

Failure Analysis

calceEP Device andPackage

calceFAST Failure Assessment

Software Toolkit

httpwwwcalceumdedusoftware

CALCE Simulation Assisted Reliability Assessment (SARAreg) Software

Conductor II

Conductor I

Whisker

Spacing (ls)

calceTinWhisker FailureRiskCalculator

University of Maryland Copyright copy 2015 CALCE

12 calceTM 12 Prognostics and Health Management Consortium

Thermally-Induced Stresses in IGBT

Material13 CTE (10-6 K-1)13 Conductivity (W m-1 K-1)13

A12O3 13 68 13 2413 AlN 13 4713 17013

Si3N413 2713 6013 BeO13 913 25013 Al13 23513 23713 Cu13 17513 39413 Mo13 5113 13813 Si13 2613 14813

AlSiC13 7513 20013 - Bond Wire Fatigue - Solder Joint Fatigue

University of Maryland Copyright copy 2015 CALCE

13 calceTM 13 Prognostics and Health Management Consortium

IGBT Power Cycling Experiment

bull  IGBT samples were power cycled between specified temperatures TMin and TMax The devices were switched at 1 or 5 kHz Cooling was carried out passively by exposure to ambient temperature

bull  This lsquopowerrsquo (thermal) cycling was repeated until failure occurred by latchup or by failure to ldquoturn onrdquo

TMax

TMin

Switching at 1 or 5 kHz

Heating

Cooling

Time Power cycling illustration

University of Maryland Copyright copy 2015 CALCE

14 calceTM 14 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Internal PNP Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

15 calceTM 15 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Parasitic NPN Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

16 calceTM 16 Prognostics and Health Management Consortium

Die Attach Acoustic Scan Images

New IGBT sample Failure to turn on after 3126 power cycles ΔT = 75degC Die attach shows delamination

Delaminated surface

Failure by latchup after 1010 power cycles ΔT = 100degC Melting T of die attach = 233degC

Specification sheet for Sn65Ag25Sb10 solder from Indium Corp Indalloy 209

Melted die attach

University of Maryland Copyright copy 2015 CALCE

17 calceTM 17 Prognostics and Health Management Consortium

Bond Wire Failures

Bond Wire Cracking Bond Wire Liftoff

University of Maryland Copyright copy 2015 CALCE

18 calceTM 18 Prognostics and Health Management Consortium

Lifetime Statistics of Experimental Results

150-200C Data β = 226 η = 7134 ρ = 096

125-225C Data β = 260 η = 1191 ρ = 096

1 kHz 5 kHz

60 duty cycle

2P-Weibull with 95 confidence bounds

MTTF = 6320

MTTF = 1058

ANOVA p-value = 76E-6 there4 Different distributions

University of Maryland Copyright copy 2015 CALCE

19 calceTM 19 Prognostics and Health Management Consortium

Prediction of Other Reliability Metrics Temperature Range MTTF (Cycles) [B5Life B95Life]

(Cycles) 150-200degC 6320 cycles [1922 11582] 125-225degC 1058 cycles [381 1815]

MTTF varies with loading conditions and from part to part Predicting service life of an IGBT based on a population MTTF results in a high uncertainty

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 12: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

12 calceTM 12 Prognostics and Health Management Consortium

Thermally-Induced Stresses in IGBT

Material13 CTE (10-6 K-1)13 Conductivity (W m-1 K-1)13

A12O3 13 68 13 2413 AlN 13 4713 17013

Si3N413 2713 6013 BeO13 913 25013 Al13 23513 23713 Cu13 17513 39413 Mo13 5113 13813 Si13 2613 14813

AlSiC13 7513 20013 - Bond Wire Fatigue - Solder Joint Fatigue

University of Maryland Copyright copy 2015 CALCE

13 calceTM 13 Prognostics and Health Management Consortium

IGBT Power Cycling Experiment

bull  IGBT samples were power cycled between specified temperatures TMin and TMax The devices were switched at 1 or 5 kHz Cooling was carried out passively by exposure to ambient temperature

bull  This lsquopowerrsquo (thermal) cycling was repeated until failure occurred by latchup or by failure to ldquoturn onrdquo

TMax

TMin

Switching at 1 or 5 kHz

Heating

Cooling

Time Power cycling illustration

University of Maryland Copyright copy 2015 CALCE

14 calceTM 14 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Internal PNP Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

15 calceTM 15 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Parasitic NPN Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

16 calceTM 16 Prognostics and Health Management Consortium

Die Attach Acoustic Scan Images

New IGBT sample Failure to turn on after 3126 power cycles ΔT = 75degC Die attach shows delamination

Delaminated surface

Failure by latchup after 1010 power cycles ΔT = 100degC Melting T of die attach = 233degC

Specification sheet for Sn65Ag25Sb10 solder from Indium Corp Indalloy 209

Melted die attach

University of Maryland Copyright copy 2015 CALCE

17 calceTM 17 Prognostics and Health Management Consortium

Bond Wire Failures

Bond Wire Cracking Bond Wire Liftoff

University of Maryland Copyright copy 2015 CALCE

18 calceTM 18 Prognostics and Health Management Consortium

Lifetime Statistics of Experimental Results

150-200C Data β = 226 η = 7134 ρ = 096

125-225C Data β = 260 η = 1191 ρ = 096

1 kHz 5 kHz

60 duty cycle

2P-Weibull with 95 confidence bounds

MTTF = 6320

MTTF = 1058

ANOVA p-value = 76E-6 there4 Different distributions

University of Maryland Copyright copy 2015 CALCE

19 calceTM 19 Prognostics and Health Management Consortium

Prediction of Other Reliability Metrics Temperature Range MTTF (Cycles) [B5Life B95Life]

(Cycles) 150-200degC 6320 cycles [1922 11582] 125-225degC 1058 cycles [381 1815]

MTTF varies with loading conditions and from part to part Predicting service life of an IGBT based on a population MTTF results in a high uncertainty

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 13: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

13 calceTM 13 Prognostics and Health Management Consortium

IGBT Power Cycling Experiment

bull  IGBT samples were power cycled between specified temperatures TMin and TMax The devices were switched at 1 or 5 kHz Cooling was carried out passively by exposure to ambient temperature

bull  This lsquopowerrsquo (thermal) cycling was repeated until failure occurred by latchup or by failure to ldquoturn onrdquo

TMax

TMin

Switching at 1 or 5 kHz

Heating

Cooling

Time Power cycling illustration

University of Maryland Copyright copy 2015 CALCE

14 calceTM 14 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Internal PNP Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

15 calceTM 15 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Parasitic NPN Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

16 calceTM 16 Prognostics and Health Management Consortium

Die Attach Acoustic Scan Images

New IGBT sample Failure to turn on after 3126 power cycles ΔT = 75degC Die attach shows delamination

Delaminated surface

Failure by latchup after 1010 power cycles ΔT = 100degC Melting T of die attach = 233degC

Specification sheet for Sn65Ag25Sb10 solder from Indium Corp Indalloy 209

Melted die attach

University of Maryland Copyright copy 2015 CALCE

17 calceTM 17 Prognostics and Health Management Consortium

Bond Wire Failures

Bond Wire Cracking Bond Wire Liftoff

University of Maryland Copyright copy 2015 CALCE

18 calceTM 18 Prognostics and Health Management Consortium

Lifetime Statistics of Experimental Results

150-200C Data β = 226 η = 7134 ρ = 096

125-225C Data β = 260 η = 1191 ρ = 096

1 kHz 5 kHz

60 duty cycle

2P-Weibull with 95 confidence bounds

MTTF = 6320

MTTF = 1058

ANOVA p-value = 76E-6 there4 Different distributions

University of Maryland Copyright copy 2015 CALCE

19 calceTM 19 Prognostics and Health Management Consortium

Prediction of Other Reliability Metrics Temperature Range MTTF (Cycles) [B5Life B95Life]

(Cycles) 150-200degC 6320 cycles [1922 11582] 125-225degC 1058 cycles [381 1815]

MTTF varies with loading conditions and from part to part Predicting service life of an IGBT based on a population MTTF results in a high uncertainty

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 14: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

14 calceTM 14 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Internal PNP Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

15 calceTM 15 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Parasitic NPN Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

16 calceTM 16 Prognostics and Health Management Consortium

Die Attach Acoustic Scan Images

New IGBT sample Failure to turn on after 3126 power cycles ΔT = 75degC Die attach shows delamination

Delaminated surface

Failure by latchup after 1010 power cycles ΔT = 100degC Melting T of die attach = 233degC

Specification sheet for Sn65Ag25Sb10 solder from Indium Corp Indalloy 209

Melted die attach

University of Maryland Copyright copy 2015 CALCE

17 calceTM 17 Prognostics and Health Management Consortium

Bond Wire Failures

Bond Wire Cracking Bond Wire Liftoff

University of Maryland Copyright copy 2015 CALCE

18 calceTM 18 Prognostics and Health Management Consortium

Lifetime Statistics of Experimental Results

150-200C Data β = 226 η = 7134 ρ = 096

125-225C Data β = 260 η = 1191 ρ = 096

1 kHz 5 kHz

60 duty cycle

2P-Weibull with 95 confidence bounds

MTTF = 6320

MTTF = 1058

ANOVA p-value = 76E-6 there4 Different distributions

University of Maryland Copyright copy 2015 CALCE

19 calceTM 19 Prognostics and Health Management Consortium

Prediction of Other Reliability Metrics Temperature Range MTTF (Cycles) [B5Life B95Life]

(Cycles) 150-200degC 6320 cycles [1922 11582] 125-225degC 1058 cycles [381 1815]

MTTF varies with loading conditions and from part to part Predicting service life of an IGBT based on a population MTTF results in a high uncertainty

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 15: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

15 calceTM 15 Prognostics and Health Management Consortium

Parasitic Thyristor in IGBT Structure

Parasitic NPN Bipolar Transistor

University of Maryland Copyright copy 2015 CALCE

16 calceTM 16 Prognostics and Health Management Consortium

Die Attach Acoustic Scan Images

New IGBT sample Failure to turn on after 3126 power cycles ΔT = 75degC Die attach shows delamination

Delaminated surface

Failure by latchup after 1010 power cycles ΔT = 100degC Melting T of die attach = 233degC

Specification sheet for Sn65Ag25Sb10 solder from Indium Corp Indalloy 209

Melted die attach

University of Maryland Copyright copy 2015 CALCE

17 calceTM 17 Prognostics and Health Management Consortium

Bond Wire Failures

Bond Wire Cracking Bond Wire Liftoff

University of Maryland Copyright copy 2015 CALCE

18 calceTM 18 Prognostics and Health Management Consortium

Lifetime Statistics of Experimental Results

150-200C Data β = 226 η = 7134 ρ = 096

125-225C Data β = 260 η = 1191 ρ = 096

1 kHz 5 kHz

60 duty cycle

2P-Weibull with 95 confidence bounds

MTTF = 6320

MTTF = 1058

ANOVA p-value = 76E-6 there4 Different distributions

University of Maryland Copyright copy 2015 CALCE

19 calceTM 19 Prognostics and Health Management Consortium

Prediction of Other Reliability Metrics Temperature Range MTTF (Cycles) [B5Life B95Life]

(Cycles) 150-200degC 6320 cycles [1922 11582] 125-225degC 1058 cycles [381 1815]

MTTF varies with loading conditions and from part to part Predicting service life of an IGBT based on a population MTTF results in a high uncertainty

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 16: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

16 calceTM 16 Prognostics and Health Management Consortium

Die Attach Acoustic Scan Images

New IGBT sample Failure to turn on after 3126 power cycles ΔT = 75degC Die attach shows delamination

Delaminated surface

Failure by latchup after 1010 power cycles ΔT = 100degC Melting T of die attach = 233degC

Specification sheet for Sn65Ag25Sb10 solder from Indium Corp Indalloy 209

Melted die attach

University of Maryland Copyright copy 2015 CALCE

17 calceTM 17 Prognostics and Health Management Consortium

Bond Wire Failures

Bond Wire Cracking Bond Wire Liftoff

University of Maryland Copyright copy 2015 CALCE

18 calceTM 18 Prognostics and Health Management Consortium

Lifetime Statistics of Experimental Results

150-200C Data β = 226 η = 7134 ρ = 096

125-225C Data β = 260 η = 1191 ρ = 096

1 kHz 5 kHz

60 duty cycle

2P-Weibull with 95 confidence bounds

MTTF = 6320

MTTF = 1058

ANOVA p-value = 76E-6 there4 Different distributions

University of Maryland Copyright copy 2015 CALCE

19 calceTM 19 Prognostics and Health Management Consortium

Prediction of Other Reliability Metrics Temperature Range MTTF (Cycles) [B5Life B95Life]

(Cycles) 150-200degC 6320 cycles [1922 11582] 125-225degC 1058 cycles [381 1815]

MTTF varies with loading conditions and from part to part Predicting service life of an IGBT based on a population MTTF results in a high uncertainty

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 17: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

17 calceTM 17 Prognostics and Health Management Consortium

Bond Wire Failures

Bond Wire Cracking Bond Wire Liftoff

University of Maryland Copyright copy 2015 CALCE

18 calceTM 18 Prognostics and Health Management Consortium

Lifetime Statistics of Experimental Results

150-200C Data β = 226 η = 7134 ρ = 096

125-225C Data β = 260 η = 1191 ρ = 096

1 kHz 5 kHz

60 duty cycle

2P-Weibull with 95 confidence bounds

MTTF = 6320

MTTF = 1058

ANOVA p-value = 76E-6 there4 Different distributions

University of Maryland Copyright copy 2015 CALCE

19 calceTM 19 Prognostics and Health Management Consortium

Prediction of Other Reliability Metrics Temperature Range MTTF (Cycles) [B5Life B95Life]

(Cycles) 150-200degC 6320 cycles [1922 11582] 125-225degC 1058 cycles [381 1815]

MTTF varies with loading conditions and from part to part Predicting service life of an IGBT based on a population MTTF results in a high uncertainty

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 18: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

18 calceTM 18 Prognostics and Health Management Consortium

Lifetime Statistics of Experimental Results

150-200C Data β = 226 η = 7134 ρ = 096

125-225C Data β = 260 η = 1191 ρ = 096

1 kHz 5 kHz

60 duty cycle

2P-Weibull with 95 confidence bounds

MTTF = 6320

MTTF = 1058

ANOVA p-value = 76E-6 there4 Different distributions

University of Maryland Copyright copy 2015 CALCE

19 calceTM 19 Prognostics and Health Management Consortium

Prediction of Other Reliability Metrics Temperature Range MTTF (Cycles) [B5Life B95Life]

(Cycles) 150-200degC 6320 cycles [1922 11582] 125-225degC 1058 cycles [381 1815]

MTTF varies with loading conditions and from part to part Predicting service life of an IGBT based on a population MTTF results in a high uncertainty

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 19: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

19 calceTM 19 Prognostics and Health Management Consortium

Prediction of Other Reliability Metrics Temperature Range MTTF (Cycles) [B5Life B95Life]

(Cycles) 150-200degC 6320 cycles [1922 11582] 125-225degC 1058 cycles [381 1815]

MTTF varies with loading conditions and from part to part Predicting service life of an IGBT based on a population MTTF results in a high uncertainty

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 20: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

20 calceTM 20 Prognostics and Health Management Consortium

Physics of Failure Based Lifetime Prediction

bull  Thermo-mechanical fatigue due to variations of power dissipation has been identified as a failure mechanism of IGBT

bull  Die attach fatigue failure model was used in the CalceFAST software The model was based on the Suhirrsquos interface stress equation coupled with the Coffin Manson equation ndash  Model inputs were ∆T cycling period materials and dimensions ndash  Failure criteria were based on separation of die attach material

bull  This model does not represent latchup failures and the actual degradation involves intermetallic growth which changes the crack propagation due to brittle fracture

Temperature PoF Lifetime Prediction Experiment MTTF 150-200degC 15300 cycles 6320 cycles 125-225degC 10800 cycles 1058 cycles

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 21: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

21 calceTM 21 Prognostics and Health Management Consortium

Limitations of the Die Attach Method bull  Die attach area reduction may not be linear as assumed since

thermal stress is highest in the perimeter and reduces as cracks move toward the center of the die Crack growth in the brittle intermetallic is not the same as the original material

bull  Power dissipation changes with time as efficiency degrades bull  The latchup Tj is not always 255C due to difference in current

density between operating conditions metallization degradation and chip manufacturing variations

bull  The developed thermal stack model does not represent the actual thermal resistance network due to unknown spreading resistance dissipation through the encapsulant and bond wires and changing conductivity through the growing intermetallic

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 22: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

22 calceTM 22 Prognostics and Health Management Consortium

MIL-217 Handbook Reliability Prediction of Electronic Equipment

bull  MIL217 Handbook provides formulas to estimate failure rate of military electronic equipment Constant failure rate is assumed

bull  No formula was provided for IGBT therefore a MOSFET and Bipolar Junction Transistor (BJT) was modeled in series to represent an IGBT

bull  Failure rate is calculated by multiplying a base failure rate with several conditional factors For example

where λP = part failure rate

λb = base failure rate πT = temperature factor λA = application factor λQ = quality factor πE = environment factor

Temperature factor does not account for temperature cycling input

p b T A Q Eλ λ π π π π= failures106 hours

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 23: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

23 calceTM 23 Prognostics and Health Management Consortium

Comparison of MTTFs Temperature

Profile MIL-

HDBK-217 Die Attach

Fatigue Model Experimental Data

2P-Weibull 150-200degC 115843 hours 15300 cycles 187 hours (6320 cycles) 125-225degC 96327 hours 10800 cycles 122 hours (1058 cycles)

bull  MIL-HDBK-217 method does not account for temperature cycling loading and other relevant loading conditions

bull  Die attach fatigue model provides a better estimate than the handbook Improvement to the model includes obtaining material fatigue properties incorporating intermetallic growth into the crack propagation and estimation of junction temperature

bull  Predicting lifetime using a population MTTF cannot account for variability from part to part

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 24: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

24 calceTM 24 Prognostics and Health Management Consortium

Motivation for Health Monitoring Approach (for IGBT and System)

bull  Using MTTF to predict IGBT lifetime is not sufficient to avoid unexpected failures in the field due to the variability in prediction

bull  Handbook approach ignores relevant loading conditions device characteristics and failure mechanisms leading to erroneous lifetime predictions

bull  Physics-based lifetime prediction cannot avoid unexpected failures in the field due to variations from part to part and field loading conditions

bull  An alternative approach to avoid failures is to monitor IGBT health individually under operation by using a data-driven method to analyze the operating data and detect for faulty conditions before failure occurs

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 25: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

25 calceTM 25 Prognostics and Health Management Consortium

What We Need to Do bull  Relevant material properties for the critical failure

mechanisms bull  Ability to update the failure models quickly bull  Modeling platforms for the units and components

bull  Life cycle condition information from monitoring bull  Use of data for determination of anomaly at the level

of interest bull  Remaining useful life assessment ability

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 26: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

26 calceTM 26 Prognostics and Health Management Consortium

IGBT Prognostics bull  Patil et al [9] IGBTs were monitored for VCE and ICE during continuous

power cycling Proposed a method to predict remaining useful life (RUL) of IGBT under power cycling by extrapolating VCE curve to a failure threshold using particle filter

bull  Sutrisno et al [10] generated a K-Nearest Neighbor algorithm for fault detection of IGBTs under continuous power cycling conditions using monitored electrical characteristics such as VCE and ICE

[9] N Patil ldquoPrognostics of Insulated Gate Bipolar Transistorsrdquo Ph D dissertation Dept Mech Eng University of Maryland College Park MD 2011

[10] E Sutrisno ldquoFault Detection and Prognostics of Insulated Gate Bipolar Transistor (IGBT) Using K-Nearest Neighbor Classification Algoritihmrdquo MS dissertation Dept Mech Eng University of Maryland College Park MD 2013

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 27: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

27 calceTM 27 Prognostics and Health Management Consortium

IGBT Prognostics bull  Xiong et al [11] proposed an online diagnostic and prognostic system to

predict the potential failure of an automotive IGBT power module A prognostic check-up routine was implemented that would be activated at a preset frequency and current during vehicle turn-on and turn-off

bull  Ginart et al [12] developed an online ringing characterization technique to diagnose IGBT faults in power drives Analysis of the damping characteristic allowed the authors to identify failure mechanisms

[11] Y Xiong Xu Cheng Z Shen C Mi H Wu and V Garg ―Prognostic and Warning System for Power-Electronic Modules in Electric Hybrid Electric and Fuel-Cell Vehiclesǁ IEEE Transactions on Industrial Electronics Vol 55 No 6 pp 2268-2276 2008 [12] A Ginart D Brown P Kalgren and M Roemer ―Online Ringing Characterization as a Diagnostic Technique for IGBTs in Power Drivesǁ IEEE Transactions on Instrumentation and Measurement Vol58 No7 pp2290-2299 2009

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 28: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

28 calceTM 28 Prognostics and Health Management Consortium

Unclamped Inductive Switching (UIS) Current Imbalance

bull  IGBTs operated with inductive loads can experience voltages well above their breakdown rating if no voltage clamp is implemented

bull  Voiding and delamination caused by either aging or voiding leads to current imbalance within the IGBT cells causing local heating

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 29: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

29 calceTM 29 Prognostics and Health Management Consortium

Heating within IGBT under UIS Conditions

Unstable behavior observed on die at nominal current localized heating [13] [13] M Riccio A Irace G Breglio P Spirito E Napoli and Y Mizuno ldquoElectro-thermal instability in multi-cellular Trench-IGBTs in avalanche condition Experiments and simulationsrdquo in Proc IEEE 23rd Int Symp Power Semiconductor Devices and ICs (ISPSD) May 23ndash26 2011 pp 124ndash127

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off
Page 30: Failure Mechanisms of Insulated Gate Bipolar … Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs) Author Diganta Das Subject

University of Maryland Copyright copy 2015 CALCE

30 calceTM 30 Prognostics and Health Management Consortium

Dynamic Avalanche at Turn-off bull  Similar to UIS conditions dynamic avalanche can cause

current imbalance between the cells of the IGBT bull  Dynamic Avalanche can be self-induced if the gate resistance

is too low causing high gate currents

Burned emitter contact pad for discrete IGBT

  • Failure Mechanisms of Insulated Gate Bipolar Transistors (IGBTs)
  • CALCE Introduction
  • IGBT Applications
  • IGBT Technologies
  • Failed Wind Turbine IGBT Module
  • Steps in Reliability Evaluation
  • FMMEA Methodology
  • IGBT Failure Modes and Mechanisms
  • Failure Modes and Mechanisms
  • Examples of Failure Models
  • CALCE Simulation Assisted ReliabilityAssessment (SARAreg) Software
  • Thermally-Induced Stresses in IGBT
  • IGBT Power Cycling Experiment
  • Parasitic Thyristor in IGBT Structure
  • Parasitic Thyristor in IGBT Structure
  • Die Attach Acoustic Scan Images
  • Bond Wire Failures
  • Lifetime Statistics of Experimental Results
  • Prediction of Other Reliability Metrics
  • Physics of Failure Based Lifetime Prediction
  • Limitations of the Die Attach Method
  • MIL-217 Handbook Reliability Prediction of Electronic Equipment
  • Comparison of MTTFs
  • Motivation for Health Monitoring Approach (for IGBT and System)
  • What We Need to Do
  • IGBT Prognostics
  • IGBT Prognostics
  • Unclamped Inductive Switching (UIS) Current Imbalance
  • Heating within IGBT under UIS Conditions
  • Dynamic Avalanche at Turn-off