Energies (May 2022)

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,
  • Chenyang Zhang

DOI
https://doi.org/10.3390/en15103759
Journal volume & issue
Vol. 15, no. 10
p. 3759

Abstract

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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