modeling of induction hardening process part 1: induction heating dr. jiankun yuan prof. yiming...

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MODELING OF INDUCTION HARDENING PROCESS PART 1: INDUCTION HEATING Dr. Jiankun Yuan Prof. Yiming (Kevin) Rong http://me.wpi.edu/~camlab Acknowledgement: This project is partially supported by Delphi and CHTE at WPI. Dr. Q. Lu was involved in the early work of the project.

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Page 1: MODELING OF INDUCTION HARDENING PROCESS PART 1: INDUCTION HEATING Dr. Jiankun Yuan Prof. Yiming (Kevin) Rong camlab Acknowledgement:

MODELING OF INDUCTION HARDENING PROCESS

PART 1: INDUCTION HEATING

Dr. Jiankun Yuan

Prof. Yiming (Kevin) Rong

http://me.wpi.edu/~camlab

Acknowledgement: This project is partially supported by Delphi and CHTE at WPI. Dr. Q. Lu was involved in the early work of the project.

Page 2: MODELING OF INDUCTION HARDENING PROCESS PART 1: INDUCTION HEATING Dr. Jiankun Yuan Prof. Yiming (Kevin) Rong camlab Acknowledgement:

Induction: Why Induction Heat Treatment?

Greatly shortened

heat treatment cycle Highly

selective Highly energy

efficiency Less-pollution

process

Advantages

Practical Problems • Lack of systematic heating time and temperature distribution control inside WP.

• Nonlinear effect of material properties.

• Lack phase transformation data inside WP for hardness and residual stress determination.

• Evaluate combination effect of AC power density, frequency and gap on final hardness pattern.

• Trial and error, cost and design period.

Numerical modeling may provide better prediction

Research content: FEM based electromagnetic/thermal analysis + quenching analysis + hardening analysis

Research objective: (1) Provide T field, time history inside WP(2) Determine formed content of martensite, pearlite and bainite.(3) Determine hardness distribution in WP. (4) Guidance for induction system design.

Page 3: MODELING OF INDUCTION HARDENING PROCESS PART 1: INDUCTION HEATING Dr. Jiankun Yuan Prof. Yiming (Kevin) Rong camlab Acknowledgement:

•Martensite content determines the hardness

Introduction: Induction Hardening Process

• Induction heating: metal parts heated to austenite Phase

•Fast quenching process transforms austenite to martensite phase

•Martensitic structure is the most hardest microstructure

workpiece Inductor/coil

Heating process

Electromagnetic field

Inductioncoil

High freq. AC power

Joule heat byeddy current

Page 4: MODELING OF INDUCTION HARDENING PROCESS PART 1: INDUCTION HEATING Dr. Jiankun Yuan Prof. Yiming (Kevin) Rong camlab Acknowledgement:

Principle: Electromagnetic and Thermal Analysis

Calculation ofmagnetic vector potential (A)

Calculation ofmagnetic flux density (B)

Calculation ofmagnetic field intensity (H)

Calculation ofelectric field intensity (E)

Calculation ofelectric field density (D)

Calculation ofcurrent density (J)

Calculation ofInducting heat (Qinduction)

B = A

H = B /

D = E

Qinduction = E J = J2/

Output: Heat generation Qinduction in WP

(Gauss’ Law for magnetic field)

(Ampere’s Circuital Law)

C r

dlIA

40

t

BE

(Faraday’s Law)

Jt

DH

Input AC power to coil

Electromagnetic Analysis

CoilWP

QCQE

t

QN

QW

QS

QBQE

QN

QR+ QCV

QS

(Outside)

(a) WP geometry (b) FEA model

(c) Interior element (d) Surface element

Thermal Analysis with finite element model

inductionQTkt

Tc

2

airairinduction TThATTFAQTkt

Tc

442

Induced Joule heat Heat radiation Heat convection

Heat conduction

Page 5: MODELING OF INDUCTION HARDENING PROCESS PART 1: INDUCTION HEATING Dr. Jiankun Yuan Prof. Yiming (Kevin) Rong camlab Acknowledgement:

Case Study: Complex Surface Hardening

concave

convex

Geometry Model

Automotive parts from Delphi Inc., Sandusky,Ohio

Material: Carbon Steel, AISI 1070

Real spindle to be hardened

FEA model and B.C. Mesh generated by ANSYS

•Concave and convex on surface of workpiece make the heating process not easy to control.

•ANSYS system is employed for the analysis.

•Mesh should be much finer at locations of convex and concave in both coil and workpiece.

Page 6: MODELING OF INDUCTION HARDENING PROCESS PART 1: INDUCTION HEATING Dr. Jiankun Yuan Prof. Yiming (Kevin) Rong camlab Acknowledgement:

Case Study: Material Properties -- AISI 1070

Emissivity

conductivity

WP relative permeability

ElectricalResistivity

Specific heat

Convection coefficient

(a) Electromagnetic Properties

(b) Thermal Properties

Page 7: MODELING OF INDUCTION HARDENING PROCESS PART 1: INDUCTION HEATING Dr. Jiankun Yuan Prof. Yiming (Kevin) Rong camlab Acknowledgement:

Case Study: Magnetic Field Intensity Distribution

Page 8: MODELING OF INDUCTION HARDENING PROCESS PART 1: INDUCTION HEATING Dr. Jiankun Yuan Prof. Yiming (Kevin) Rong camlab Acknowledgement:

Effect of current density distribution

• Constant current distribution in coil can not result in good heating pattern, especially at concaves of workpiece

• Better hardened pattern resulted from modification of Finer coil mesh and enhanced coil current density at area neighboring to surface concaves of workpiece.

• Enhanced coil current density suggests utilization of magnetic controller at those area in coil design process. Physically this can be fulfilled by magnetic controller.

(a1) Constant current distribution in coil (a2) heated pattern

(b1) Adjusted current distribution in coil (b2) heated pattern

Page 9: MODELING OF INDUCTION HARDENING PROCESS PART 1: INDUCTION HEATING Dr. Jiankun Yuan Prof. Yiming (Kevin) Rong camlab Acknowledgement:

Case Study:Temperature Variation with Time in Induction Heating Process

Total heating time th = 7.05s

t=0.5s

f=9600Hz s=1.27mm J=1.256e6 A/m2

t=2s

t=4s

Page 10: MODELING OF INDUCTION HARDENING PROCESS PART 1: INDUCTION HEATING Dr. Jiankun Yuan Prof. Yiming (Kevin) Rong camlab Acknowledgement:

Case Study: Heating Curves

Summary • A finite element method based modeling system is developed to analyze the

coupled electromagnetic/thermal process in induction heating and implemented in ANSYS package, with following capabilities.

• Provide electrical and magnetic field strength distribution.

• Provide instantaneous temperature field data in workpiece.

• Provide Temperature history at any location in heating process.

• Provide guidance for inductor/coil design based on adjustment of current density distribution and desired heating patterns.