Sensorless control of permanent magnet motor based on two-stage Kalman filtering

Although the conventional sensorless algorithm based on Kalman filtering (KF) can eliminate the impact of model error and measurement error on the estimated state variables to a certain extent, heavy computation load and high cost may simultaneously occur. In order to solve this problem and keep the advantages of the original algorithm, a novel sensorless control strategy based on the optimal two-stage Kalman filtering is proposed in stationary two-phase coordinates for permanent magnet synchronous motor. In this new strategy, stator currents in the stationary reference frame are taken as the full-order states and the back-electromotive-force is taken as the augmented system state. In order to improve the parameter identification precision, software phase-locked loop is adopted in the control strategy to estimate the rotor speed. Experimental results show that the proposed strategy is mathematically equivalent to the traditional Kalman filtering, with an operation time reduction of 24.49%.