北华大学学报（自然科学版）2024，Vol.25Issue(3)：405-413,9.DOI:10.11713/j.issn.1009-4822.2024.03.019
基于平方根容积卡尔曼滤波的永磁同步电机状态估计
State Estimation of Permanent Magnet Synchronous Motor Based on Square-Root Cubature Kalman Filter
摘要
Abstract
A modified square-root cubature kalman filter (SRCKF) is introduced to address the issues of large errors and slow computation speed in complex nonlinear state estimation by using Cubature Kalman Filter (CKF) algorithm.A linearized model of the nonlinear system and a mathematical model of the motor are established,and SRCKF is introduced to achieve state estimation of speed and rotor position,the SRCKF and CKF algorithms are simulated in the Matlab/Simulink.The simulation results show that the square-root volume Kalman filter greatly reduces the operating speed and estimation error of the motor during state estimation,improves estimation accuracy,and makes the system more stable.关键词
永磁同步电机/非线性/平方根容积卡尔曼滤波Key words
permanent magnet synchronous motor/nonlinear/square-root cubature kalman filter分类
信息技术与安全科学引用本文复制引用
刘业成,李亚鹏,杨苹,柳成..基于平方根容积卡尔曼滤波的永磁同步电机状态估计[J].北华大学学报（自然科学版）,2024,25(3):405-413,9.基金项目
北华大学研究生创新计划项目(2022046). （2022046）
