Correlation Coefficients Method of Power Converters Fault Diagnosis for Switched Reluctance Motors in Electric Vehicle
Switched reluctance,fault diagnosis
Energy Science and Technology > 8. Energy Management of New Energy Vehicles and Internet of Vehicles Technology
Draft Paper Accepted
Hao Chen / China University of Mining and Technology
Ruimin Duan / China University of Mining and Technology
Xianqiang Shi / China University of Mining and Technology
Mohamed Orabi / Aswan
Daqing Zou / Jiangsu Alternative Energy Vehicle Research Institute
The power converter plays a very important role in switched reluctance motor (SRM) systems which is recommended as a key technique for electric vehicles （EV）. But the power converter is also a vulnerable part most prone to be faulted. Therefore, this paper proposes a novel on-line fault diagnostic algorithm of power converters for switched reluctance motor drives based on correlation analysis. In order to obtain the fault signatures from the phase currents, two main fault types of the power transistors in an asymmetric bridge power converter are described and analyzed. The principle of the proposed method is to diagnose faults by comparing the faulty and healthy phase current waveforms. First, the phase currents are shifted into the same phase, then the correlation coefficients of phase-shift currents in the turn-off and reference region are computed as the feature coefficients to detect the faulty phase and to localize the short-circuit faulty device, respectively. The proposed scheme only uses the phase currents that are available from the main control system, and it is suitable for variable speed and load operation, and variable angle modulation system. Simulation and experimental results show the effectiveness and practicality of the proposed fault diagnostic method.