Speed and load torque estimation of SPMSM based on Kalman filter

This paper presents a kalman filter algorithm for speed estimation of surface permanent magnet synchronous motor (SPMSM) with load torque estimation at the same time based on the mechanical kinemic equations of the motor. Unlike sensorless control, this approach is an optimal information fusion of the optical encoder speed measurement and kinemic model based speed estimation on sense of minimum mean square error. Further more it requires less motor parameters than common sensorless EKF speed estimation. Simulation results show that the novel method can achieve high estimation precision and consistency errors over the entire speed range. Load torque estimation at the same time ensures the robustness with the torque interference.