基于EKF的PMSM无传感器控制及滤波参数选取

摘要

Compared with the methods to achieve sensorless system via PMSM at present, Kalman Filter algorithm was widely used for its adaptive capacity, strong anti-interference and easy implementation with software.With the model of PMSM, the EKF theory was analyzed.In order to choose initial parameter for EKF, the paper provided the selection of initial parameter in detail.It is convenient for how to choose filter parameters of EKF.Simulation shows that the PMSM sensorless control system based on EKF runs steadily and has good dynamic and static performance.It also proves the rationality of the selection opinion used in this paper.%目前实现永磁同步电动机(PMSM)无速度传感器的方法有多种,卡尔曼滤波法因其具有自适应能力、抗干扰性强,易于软件实现等优点而广泛应用,针对 PMSM 数学模型,详细分析了扩展卡尔曼滤波(EKF)原理,并针对EKF 初始滤波参数如何选取这一问题,进行了研究,给出此参数的选取思路,为 EKF 参数选取工作提供了方便.仿真结果表明,基于 EKF 的 PMSM 无传感器控制系统运行稳定,动、静态性能良好,且验证了所采用的 EKF 参数选取方法的合理性.