High Efficiency Sensorless Control of SynRM with Inductance Identification Based on Adaptive Alternate EKF

To improve the efficiency and stability of synchronous reluctance motor (SynRM) under sensorless control strategy, a novel parameter identification method based on an adaptive alternate extended Kalman filter (AAEKF) is proposed in this paper. The core idea is to design two EKFs based on different state variables, which executed alternately. The first EKF is employed to estimate rotor speed and d-axis inductance simultaneously, the other is used to estimate rotor speed and q- axis inductance. Meanwhile, the estimated inductances are used to achieve online maximum torque per ampere (MTPA) control. Furthermore, to improve the estimation accuracy under different working conditions, an adaptive system noise covariance matrix based on innovation sequence is incorporated into EKFs, which reduce the number of parameters to be adjusted at the same time. The proposed control method is validated by simulation and experiment.