ansys chu y chicago modeling and simulation of brushless dc motor drive system

Ansys Convergence Conference - Chicago

Modeling and Simulation of Permanent Magnet

Brushless Motor Drives

Piyush Desai, Ph. D.

PD Consulting Inc.

+1 312 505 7805

[email protected]

Presented at the 2014 ANSYS Regional Conference Chicago May 23, 2014


Services:

•Design & development of inverters

•Design and virtual prototyping of electric machines

•Analyses, modeling, and simulations of electro-mechanical systems

•Development of control algorithms for motor drives and servo systems

•System design and layout of large utility scale PV solar plants

About PD Consulting

20+ years of experience in R & D, project management, and

product development

May 23, 2014 © PD Consulting 2


History of Motors

1819: Danish scientist Orsted

observed that a current-carrying

wire produces a magnetic field

M. Faraday devised an

experiment to demonstrate this

1883: Nikola Tesla

invented a practical AC

motor

1832: William Sturgeon

invented commutator 1831: Joseph Henry’s

improved version



PM Brushless Motor: BLDC, PMAC, PMSM

PM on the Rotor

Laminated Stator with Windings Position Sensor

Encapsulated Design

http://www.danahermotion.com/education/learn_about_mc/servohandbook/motor/comparison/brush_vs_brushless.php



Choices to Make


• Motor: BDC, BLDC, PMAC

• Controls: Trapezoidal, sinusoidal, field oriented

• Switching: Hysteresis, PWM (sine triangle,

space vector)

• Modeling approach: o Simple model: motor as 2nd order ODE; inverter as gain

o Detailed model: 3-phase motor as 5th order ODE; switching

inverter; detailed modeling of the controls

o Multi-physics simulation: co-simulation of FEA motor model and circuit based inverter

Objective: converge to an optimal design


Torque-Speed Curve

Torque

Speed

Motor capabilities for requirement verification Motor capabilities for requirement verification

An important metrics for relative comparison An important metrics for relative comparison


Ansys Convergence Conference - Chicago © PD Consulting

PM Machine Theory

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May 23, 2014 7


Options for BLDC Machine Model

Purely Analytical RMxprt

Maxwell FEA © PD Consulting 8


When RMxprt / Maxwell?

RMxprt Maxwell FEA

Fast Motor Design &

Model Generation

Design Studies

Fast Circuit Simulations

High Fidelity Simulations

Calculating Losses

Accounting for Saturation

© PD Consulting 9


Simple Model

Electrical System Mechanical

System

Electrical/Mechanical Constants

Simplorer Implementation



Simple Model Simulation Results

Motor Speed

DC Current

Simple “average – DC” model and reflects 2nd order nature of motor model

Does not take in to account commutation and inverter switching

Insensitive to number of pole pairs

Torque vs. Speed



Detailed BLDC Drive Model



Comparison: Torque-Speed Curves

More than 10% reduction in Capability Curve

Simple Model

Detailed Model



Phase Current

Phase A Current

Phase ABC Current

Current Ripple due to

Commutation



Output Torque

Commutation Current Ripple Torque Ripple



Quantitative Analysis of Torque

Commutation Ripple

Frequency in Hz

Torque in Nm

DC (Average) Torque Switching Ripple May 23, 2014 © PD Consulting 16


Comparison of 4 and 6 Pole Motors

Torque vs. Speed

4-pole Motor with Simple Model (Red)

6-pole Motor with Simple Motor (Blue)

4-pole Motor with Detailed Model (Green)

6-pole Motor with Detailed Model (Magenta)

High Speed Motor



4-pole Motor with Simple Model (Red)

6-pole Motor with Simple Model (Blue)

4-pole Motor with Detailed Model (Green)

6-pole Motor with Detailed Model (Magenta)

Torque vs. Speed

Industrial Motor


Comparison of 4 and 6 Pole Motors


Summary of both the Modeling Approaches

Simple Model:

• Simple, quick, good enough for basic understanding

• Commutation and # of poles not accounted for

• Needs ample margin in the design

Circuit simulations:

• Longer simulation time, more accurate (capability curve, current and torque ripples, efficiency estimation, # of poles, etc.)

• Can capture the system dynamics and transients: filter delay, digital sampling, IGBT/MOSFET switching

• Commutation effects reduction in the capability curve; current and torque ripple



Baseline Model

• Results must show typical/generic ‘real-world’ responses

• Should be easily adaptable/configurable

• Validated and verified o Validation: ‘tweak’ the model to match with one set of

experimental data

o Verification: match the simulation results with another set of experimental data

Now you have a good model that can be used for optimization



Optimization Case Study

Requirements:

• Efficiency at an operating point

• Torque ripple

• No load speed


SPM Lower Inductance higher current ripple higher torque ripple


Optimization Step – 1



Optimization Step -2


BLDC (Red)

FOC with Sine PWM (Blue)

FOC with SVM (Magenta)

Torque vs. Speed

FOC-SVM with Inductor: Needs Little more No Load Speed

(SPM Field Weakening is Not Efficient)


Optimization Step-3


Optimize Inductor Size & Switching Frequency


Thank you !!

Questions?


ansys chu y chicago modeling and simulation of brushless dc motor drive system

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