关键词: 永磁同步电机, 参数估计, 无传感器控制, 二阶扩展卡尔曼滤波

Abstract: The extended Kalman filter ( EKF ) is typically employed in sensorless control of permanent magnet synchronous motors ( PMSM) to estimate the rotor position and speed. The system state model was often linearized using the first-order Taylor expansion. Omitting second-order or higher terms during linearization could result in significant modeling errors. In response to the issue, an EKF method based on second-order approximation was proposed, which preserved second-order partial derivatived and improved the accuracy of the system model. Simulation experiments showed that the method could obtain more accurate estimation results than traditional methods.

Key words: permanent magnet synchronous motor ( PMSM), parameter estimation, sensorless control, second-order extended Kalman filtering( EKF)