永磁同步电机扩展卡尔曼滤波器电流观测方法
Current Estimation for Permanent Magnet Synchronous Motor Based on Extended Kalman Filter
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摘要: 为提高前置电感电容LC滤波器永磁同步电机系统性能, 提出一种基于扩展卡尔曼滤波器(extended Kalman filter, EKF)的电机电流观测控制方法。该方法采集逆变器侧电流, 通过新型EKF观测器获得实际电机电流, 并将估计的电机电流用于电流环反馈控制。论文给出了新型EKF电流观测器的结构和参数设计过程, 并利用Lyapunov稳定性定理证明了该方法的稳定性。仿真结果表明, 与传统Luenberger观测器相比, 新型EKF观测方法的电流估计误差更小, 电机电流跟踪性能更好, 电磁转矩脉动及其谐波明显降低。Abstract: To improve the system performance of permanent magnet synchronous motor (PMSM) with LC filter, a new motor current estimation and control method based on the extended Kalman filter (EKF) is proposed in this paper. In the EKF method, the inverter side current was sampled, the actual motor current was obtained through the new EKF observer, and the estimated motor current was used for current loop feedback. The structure and parameter design of the new EKF current observer were given, and the system stability was proved by Lyapunov stability theorem. The simulation results show that, compared with the traditional Luenberger observer, the new EKF observation method has smaller current estimation error and better motor current tracking performance. The torque ripple and the harmonics can also be effectively reduced.