Extended-Kalman-Filter-Based Magnet Flux Linkage and Inductance Estimation for PMSM Considering Magnetic Saturation

During the operation of permanent magnet synchronous motor (PMSM), accurate parameter identification plays an important role in high-performance motor control, especially in a situation where the parameters can vary nonlinearly significantly. This paper proposes an estimation method that combines extended Kalman filtering (EKF) and least squares method to identify the parameters of PMSM under the influence of magnetic saturation. This paper improves the PMSM model by establishing an inductance model considering magnetic saturation at first. Thereafter, EKF and least squares based method is proposed to estimate the magnetic flux and variation of inductances. The proposed method can accurately identify the machine parameters especially under the condition of magnetic saturation situation. The effectiveness of the proposed method is verified by simulation on the improved PMSM model.