Simulation of Inter-Turn Short-Circuit Detection Algorithm of Electric Vehicle Permanent Magnet Synchronous Motor

When the motor has inter turn short circuit fault, the internal resistance of the motor will be greatly reduced and the current will suddenly increase, resulting in excessive power of other components. If the fault motor cannot be monitored in time, it will cause secondary damage. However, due to the transient nature of short-circuit fault, it is difficult to obtain its characteristics. Therefore, a fault detection method for inter turn short circuit of permanent magnet synchronous motor of electric vehicle is proposed. The model of permanent magnet synchronous motor (PMSM) driving automobile is constructed. According to the principle that the restriction relationship between fundamental current and positive sequence current fails when the PMSM model is in the state of inter turn short circuit fault, the characteristics of inter turn short circuit fault are extracted. Based on this, particle swarm optimization least squares support vector machine (PSO-LSSVM) is used to obtain the fault detection results, so as to realize the detection of turn to turn short circuit fault of electric vehicle permanent magnet synchronous motor. The experimental results show that the load torque detected by the research method at any time is consistent with the actual value, and the output residual energy of the motor has high reliability, which shows that the method has strong applicability.