Rotor Position Estimation Method for Permanent Magnet Synchronous Motor Based on High-Order Extended Kalman Filter

To address the issue of decreased rotor position estimation accuracy in permanent magnet synchronous motors (PMSMs) caused by linearization rounding errors in the extended Kalman filter (EKF), this paper proposes a rotor position estimation method for PMSMs based on higher-order extended Kalman filtering. This method relies on the state-space equations of a PMSM in a stationary coordinate system and establishes a higher-order Taylor series expansion based on the least squares approach. It constructs a prediction and update model for the state variables using the higher-order Taylor series expansion and designs an algorithm for estimating the rotor position of PMSMs based on higher-order extended Kalman filtering. The simulation results indicate that, compared to the EKF, the proposed method reduces the root-mean-square error by 10%.