Parameter identification of permanent magnet synchronous motors in automotive K&C test benches

In the test bench for the motion characteristics and flexibility (K&C) characteristics of automotive suspension, the permanent magnet synchronous motor (PMSM) serves as the power device of the suspension loading system. The control performance of the motor determines the performance of the test bench. However, during the actual operation of PMSM, the motor parameters will change, conflicting with the initial motor parameters in the controller design process, affecting the system stability and control accuracy. Therefore, in the process of identifying inductors and permanent magnet magnetic links of PMSM using the model reference adaptive systems (MRAS) method in this paper, the extended kalman filter algorithm is added. EKF) Identify the resistor. The research results show that, compared with the single EKF algorithm, when using the MRAS-EKF method, the resistance identification error is reduced by 7.41%. The inductance identification error has been reduced by 5.18%. The magnetic link identification error has been reduced by 8.23%. On the basis of maintaining the raptness of the EKF algorithm, the MRAS-EKF algorithm can effectively improve the accuracy of PMSM parameter identification.