Modeling of a Switched Reluctance Motor Under Stator Winding Fault Condition

被引：11

作者：

Chen, H. ^{[1
]}

Han, G. ^{[1
]}

Yan, W. ^{[1
]}

Lu, S. ^{[2
]}

Chen, Z. ^{[3
]}

机构：

[1] China Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou 221116, Peoples R China

[2] Nanjing Inst Elect, Nanjing 210007, Jiangsu, Peoples R China

[3] Aalborg Univ, Dept Energy Technol, DK-9220 Aalborg, Denmark

来源：

IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY | 2016年 / 26卷 / 04期

基金：

中国国家自然科学基金;

关键词：

Artificial neural network; flux linkage; motor fault; switched reluctance motor; DIAGNOSIS;

D O I：

10.1109/TASC.2016.2539678

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A new method for modeling stator winding fault with one shorted coil in a switched reluctance motor (SRM) is presented in this paper. The method is based on artificial neural network (ANN), incorporated with a simple analytical model in electromagnetic analysis to estimate the flux-linkage characteristics of SRM under the stator winding fault. The magnetic equivalent circuit method with ANN is applied to calculate the nonlinear flux-linkage characteristics under stator winding fault condition. A stator winding fault 12/8 SRM prototype system is developed to verify the effectiveness of the proposed method. The results for a stator winding fault with one shorted coil are obtained from the proposed method and from the experimental work on a developed prototype. It is shown that the simulation results are close to the test results.

引用

页数：6

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