Rotor Position Estimation of PMSM With Noise Suppression Using Steady-State Linear Kalman Filter and High Frequency Square Wave Injection

In this paper, a new square wave injection sensorless control algorithm based on steady-state linear Kalman filter (SSLKF) is proposed for standstill and low-speed operation of permanent magnet synchronous motors (PMSM). Usually, in the square wave injection method, phase-locked loop (PLL) is used to extract the rotor position and speed information from the excited current. However, due to the measurement noise in the current signal, there will be large errors in the estimated speed and position values, which will affect the system performance. Compared with traditional methods, the proposed algorithm is more robust to noise and has higher estimation accuracy even under very high noise. In addition, an additional acceleration feedforward term is introduced into the SSLKF, which improves the response speed of the system. The performance of the proposed algorithm is evaluated in simulations. The root mean square error (RMSE) of velocity estimation is reduced from 180 RPM to 30 RPM, and RMSE of position estimation is reduced from 10° to 5°.