Vold-Kalman Filtering Order Tracking Based Rotor Flux Linkage Monitoring in PMSM

Abstract

Monitoring permanent magnet (PM) flux linkage is important to maintain a stable permanent magnet synchronous motor (PMSM) operation. In this paper, V old-Kalman filtering order tracking (VKF-OT) and dynamic Bayesian network (DBN) are used to investigate the application of torque ripple in real-time PM flux monitoring. Firstly, a torque ripple model of PMSM considering electromagnetic noise is proposed, and the torque variation is studied. In this model, the torque is analyzed and processed by wavelet transform to eliminate the effects of the electromagnetic disturbances. Secondly, VKF-OT is introduced to track the order of torque ripple of PMSM running in unsteady state. Therefore, torque ripple characteristics can be used as a feature to reflect changes in PM flux linkage. Thirdly, this method is feasible for PMSM by applying DBN to the training data to estimate the flux linkage during motor operation. The proposed flux monitoring method is validated on a laboratory PMSM. The results demonstrate that this method can monitor the flux variation over a wide speed range at different load levels.