Research on Diagnosis and Prediction Method of Stator Interturn Short-Circuit Fault of Traction Motor

Jianqiang Liu, Hu Tan, Yunming Shi, Yu Ai, Shaoyong Chen and Chenyang Zhang
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Jianqiang Liu: School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
Hu Tan: School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
Yunming Shi: School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
Yu Ai: School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
Shaoyong Chen: School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
Chenyang Zhang: School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China

Energies, 2022, vol. 15, issue 10, 1-17

Abstract: The traction motor (TM) is an essential part of the high-speed train, the health condition of which determines the quality and safety of the vehicle. Hence, this study proposed a novel approach to diagnosing and predicting the TM stator interturn short-circuit fault (SISCF). Based on the Park vector (PV) of the stator current, this method could overcome the interference of current sensor errors, null shift, and motor frequency fluctuations in the actual conditions. More specifically, Park’s transformation was used to obtain the PV of the stator current. Then, the PV was fitted to obtain the elliptical trajectory and its parameters from which the negative sequence component of the stator current could be calculated. Finally, the SISCF diagnosis and prediction method were realized by the magnitude and trend of the negative current as well as the inclination of the trajectory ellipse. Furthermore, the performance of the proposed method was validated by a simulation model and a series of experiments. The simulation results were consistent with the experimental results, supporting the validity and correctness of the method proposed in this study.

Keywords: fault diagnosis; fault prediction; Park vector; stator interturn short-circuit fault; track fitting; traction motors (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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