Speed Sensorless Control Method of Synchronous Reluctance Motor Based on Resonant Kalman Filter
Fengtao Gao, Zhonggang Yin, Cong Bai, Dongsheng Yuan, Jing Liu
Abstract
When estimating the active back electromotive force (AEMF) of synchronous reluctance motor (SynRM) at medium and high speed, the traditional Kalman filter (KF) will produce large phase delay due to the low-pass filter characteristics. A novel speed sensorless control scheme of SynRM based on resonant Kalman filter (RKF) is proposed in this article. First, the AEMF observer based on KF is designed and the bandwidth performance is analyzed. To solve the phase delay problem caused by KF, a generalized integral resonance perturbation estimator (GIRPE) is introduced to the framework of KF and the proposed RKF is formed. The estimation error of AEMF is compensated through GIRPE in the current error feedback loop of KF observer. In this way, the high-precision position estimation at high speed range is obtained. Finally, an improved dynamic position compensator is proposed to enhance the position estimation performance under dynamic case. The effectiveness of proposed scheme is validated at a 1.5-kW SynRM drive, and the computational burden of the proposed method is assessed quantitatively.