Parameter Identification of Permanent Magnet Synchronous Motor Based on Improved Recursive Least Squares

Permanent magnet synchronous motor is widely used because of its reliable operation and high efficiency. The accuracy of parameter identification has an important impact on the operating performance and control methods of PMSM. Most of the current parameter identification methods fail to consider the effect of temperature on parameters, resulting in low parameter identification accuracy and poor control performance. Therefore, this paper proposes a mathematical model of permanent magnet synchronous motor considering the temperature change, and combines with the dynamic forgetting factor recursive least squares parameter identification method on this basis. The simulation results show that the proposed method can effectively monitor and identify the motor parameters, improve the accuracy of parameter identification and reduce the identification error.