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CLC number: TN386.2; TP183

On-line Access: 2010-06-02

Received: 2009-07-22

Revision Accepted: 2010-01-24

Crosschecked: 2010-05-11

Cited: 1

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Journal of Zhejiang University SCIENCE C 2010 Vol.11 No.6 P.435-443

http://doi.org/10.1631/jzus.C0910442


Application of artificial neural network for switching loss modeling in power IGBTs


Author(s):  Yan Deng, Xiang-ning He, Jing Zhao, Yan Xiong, Yan-qun Shen, Jian Jiang

Affiliation(s):  School of Electrical Engineering, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   dengyan@zju.edu.cn

Key Words:  Insulated gate bipolar transistor (IGBT), Switching loss, Modeling, Artificial neural network (ANN)


Yan Deng, Xiang-ning He, Jing Zhao, Yan Xiong, Yan-qun Shen, Jian Jiang. Application of artificial neural network for switching loss modeling in power IGBTs[J]. Journal of Zhejiang University Science C, 2010, 11(6): 435-443.

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author="Yan Deng, Xiang-ning He, Jing Zhao, Yan Xiong, Yan-qun Shen, Jian Jiang",
journal="Journal of Zhejiang University Science C",
volume="11",
number="6",
pages="435-443",
year="2010",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.C0910442"
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%T Application of artificial neural network for switching loss modeling in power IGBTs
%A Yan Deng
%A Xiang-ning He
%A Jing Zhao
%A Yan Xiong
%A Yan-qun Shen
%A Jian Jiang
%J Journal of Zhejiang University SCIENCE C
%V 11
%N 6
%P 435-443
%@ 1869-1951
%D 2010
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C0910442

TY - JOUR
T1 - Application of artificial neural network for switching loss modeling in power IGBTs
A1 - Yan Deng
A1 - Xiang-ning He
A1 - Jing Zhao
A1 - Yan Xiong
A1 - Yan-qun Shen
A1 - Jian Jiang
J0 - Journal of Zhejiang University Science C
VL - 11
IS - 6
SP - 435
EP - 443
%@ 1869-1951
Y1 - 2010
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C0910442


Abstract: 
The modeling of switching loss in semiconductor power devices is important in practice for the prediction and evaluation of thermal safety and system reliability. Both simulation-based behavioral models and data processing-based empirical models are difficult and have limited applications. Although the artificial neural network (ANN) algorithm has often been used for modeling, it has never been used for modeling insulated gate bipolar transistor (IGBT) transient loss. In this paper, we attempt to use the ANN method for this purpose, using a customized switching loss test bench. We compare its performance with two conventional curve-fitting models and verify the results by experiment. Our model is generally superior in calculation speed, accuracy, and data requirement, and is also able to be extended to loss modeling for all kinds of semiconductor power devices.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

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