Publication

Abstract : The Permanent Magnet Synchronous Motors (PMSM) are widely used in Electric Vehicles (EVs) because of their high- power density and efficiency. The motor should be reliable when the vehicle travels in different terrains. The motors are prone to both electrical and mechanical faults. Nearly 40% of electrical faults are due to winding faults, which may be due to Open Circuit (OC) or Short Circuit (SC) of phase windings. Among these winding faults, the most frequent fault is the interturn short circuit fault and it is very dangerous if this fault is not treated immediately because of high currents. Prolonged interturn short circuit faults may lead to short circuit faults. During such fault conditions, the motor should be resilient for a sustainable transportation system. Hence, it is necessary to measure interturn short circuit fault currents. This paper focuses on the early estimation of interturn short circuit fault currents in PMSM motors used in electric vehicle applications. An estimator is needed for estimating fault currents. An Extended Kalman Filter (EKF) observer is designed and implemented using the state space model of PMSM and the covariance matrices. The fault is varied for 0 to 100% of short-circuiting of windings for different phases. Faults in 'a' phase winding will have an impact on direct axis current and 'b' phase faults impact will be more on quadrature axis currents. The fault currents and torques are extremely large. By using the proposed EKF observer, the fault current state estimation is possible. Once the fault current magnitudes are estimated in advance, necessary precautions can be taken. The proposed algorithm is implemented in the MATLAB/Simulink platform.