In recent years, China's electric vehicle industry has developed rapidly. The fractional slot permanent magnet machine (FS-PMM) winding using the star-delta (Y-△) connection method can reduce the harmonic content. And it is easy to realize in motor processing, which can be well applied to the new energy vehicle industry.

However, FS-PMM with Y-△ connection has two sets of winding structures, which are more complex. The circulating current on the inner △ connection winding will reduce the three-phase asymmetry of machine in the inter-turn short circuit fault state to a certain extent. It will result its fault characteristics different from those of the traditional machine. Aiming at the inter turn short circuit fault of FS-PMM with Y-△ connection method, a fault diagnosis method based on parameter optimization variational mode decomposition algorithm is proposed.

In this paper, the equivalent circuit model of turn to turn short circuit of Y-connected and △ connected windings in Y-△ connected FS-PMM is established, and the short-circuit current at fault is derived. Secondly, the whale optimization algorithm is improved. The improved whale optimization algorithm is used to optimize the parameters of the variational mode decomposition algorithm, so as to process the current signal; Then, the multi-scale fuzzy entropy is selected as the signal feature, and the support vector machine is used to diagnose the partial inter-turn short circuit fault of Y connection method or △ connection method.

The fault diagnosis accuracy of this method is more than 95%, and it can effectively distinguish the turn to turn short circuit fault of Y-connection and △ connection.

支持基金：

National Natural Foundation of China (51907052)

论文链接：

http://www.motor-abc.cn/djykzyy/article/abstract/20240604

推荐引用格式：

CHEN Zhenfei, LING Zhihao, Ll Zhixin, BAO Miao. Fault Diagnosis of Inter-Turn Short Circuit Fault in Star-Delta Connection FS-PMM Based on Parameter Optimization VMD and Multi-Scale Fuzzy Entropy[J].  Electric Machines & Control Application, 2024, 51(6): 31-43.

Dr. Zhenfei Chen, assistant professor and master's supervisor of School of Electrical and Power Engineering of Hohai University. Her research interests include fault diagnosis of power equipment, electromagnetic analysis and design of power equipment, etc. She has published over 40 papers so far, including more than 30 SCI/EI indexed papers. She has applied for 16 invention patents and granted 9 authorizations. As the person in charge, she has led over 8 projects including the National Youth Fund, Jiangsu Provincial Youth Fund, and China Postdoctoral Fund, and participated in research on multiple national and provincial level projects, including the National Key Basic Research Development Plan, the National Natural Science Foundation Key Project, the Tianjin Science and Technology Support Plan Key Project, and the State Grid Jiangsu Electric Power Co., Ltd. Science and Technology Project. She has won the third prize for scientific and technological progress in Jiangsu Province. Email: chenzhenfei@hhu.edu.cn

Ling Zhihao is a master's student at the School of Electrical and Power Engineering, Hohai University, with a research focus on electromagnetic analysis and fault diagnosis of permanent magnet machine. Email: lzh_link@163.com