[关键词]
[摘要]
针对在转速估算研究中采用常数矩阵不能准确描述永磁同步电机(PMSM)在不同运行条件下系统噪声的问题,提出了一种基于新息序列和状态残差的自适应扩展卡尔曼滤波算法(AEKF)。同时,对AEKF的稳定性进行理论上的探究。经仿真验证,与传统扩展卡尔曼滤波算法相比,AEKF在收敛速度和收敛精度上更优,参数鲁棒性更好。
[Key word]
[Abstract]
In order to accurately describe the system noise of permanent magnet synchronous motor (PMSM) under different operating conditions, the variable matrix was used to estimate the system noise based on the innovation sequence and state residual. An adaptive extended Kalman filter (AEKF) algorithm based on the variable matrix was adopted to estimate the speed. At the same time, the research on the stability of AEKF was conducted. The simulation proves that compared with the traditional extended Kalman filter algorithm, the AEKF is better in convergence speed and convergence precision and has better robustness.
[中图分类号]
TM 341
[基金项目]
国家自然科学基金创新研究群体基金项目(51621004);国家自然科学基金联合基金项目(U1864207);国家重点研发计划课题项目(2016YFB0100903-2);广西科技大学汽车零部件与车辆技术重点实验室开放项目(2017GKLACVTKF01)