On-line Parameter Identification of Permanent Magnet Synchronous Motor based on Extended Kalman Filter

Abstract

Accurate motor parameters are the basic requirements for realizing high-performance control technology of permanent magnet synchronous motors (PMSM). To maintain high performance in different operation mode, it is necessary to adjust the control with different conditions. However, on-line parameter identification is hardly to have better precision. A parameter identification method for surface-mounted permanent magnet synchronous motor (SPMSM) based on extended Kalman filter is proposed to solve this problem. By using this scheme, the accuracy and speed of parameter identification can be effectively improved. In this paper, the stator resistance, rotor flux, inductance, moment of inertia and load torque of SPMSM are identified, and the anti-interference of the algorithm is also analyzed. Simulation results verify the correctness and effectiveness of the method, and show that the parameter identification results can converge quickly and the error is limited within a small range.