Hybrid Type-2 Fuzzy Logic–Extended Kalman Filter Approach for ITSC Fault Detection in PMSM Drives for Electric Vehicles

Abstract The detection of Inter-Turn Short Circuit (ITSC) in electrical machines is a critical operation, particularly in electric vehicle (EV) motor drives. In this paper, a hybrid approach of type-2 fuzzy logic (T2-FL) and extended Kalman filter (EKF) is proposed in order to detect ITSC fault in the permanent magnet synchronous motor (PMSM) released by MATLAB/SIMULINK. The PMSM stator resistance is estimated through T2-FL, while the motor current, rotor speed and rotor angular are estimated by the EKF, taking advantage of its dynamic features. The results under high value and poor visibility of the ITSC resistance fault show that the root mean square error (RMSE) of the fault current is 0.2303. Moreover, comparison of the type-2 fuzzy logic and extended Kalman filter (T2-FL–EKF) strategy with the conventional EKF and fuzzy logic–extended Kalman filter (FL–EKF) approaches showed a significant optimisation in both speed control and ITSC fault detection.