基于优化EKF的永磁同步电机转速估计

广西师范大学学报（自然科学版） ›› 2014, Vol. 32 ›› Issue (4): 11-17.

基于优化EKF的永磁同步电机转速估计

王剑¹, 黄植功¹, 许金海²

1.广西师范大学电子工程学院,广西桂林541004;
2.桂林电子科技大学电子工程与自动化学院,广西桂林541004

收稿日期:2014-09-03 发布日期:2018-09-26
通讯作者: 黄植功(1970-),男,广西田东人,广西师范大学副教授。E-mail:hbypolly@mailbox.gxnu.edu.cn
基金资助:
国家重点基础研究发展计划项目(973计划)资助课题 (2006CB200303,2006CB2003056)

Speed Estimation of Permanent Magnet Synchronous Motor Based on Optimized EKF

WANG Jian¹, HUANG Zhi-gong¹, XU Jin-hai²

1.Electronic Engineering, Guangxi Normal University, Guilin Guangxi 541004, China;
2. Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin Guangxi 541004, China

Received:2014-09-03 Published:2018-09-26

摘要/Abstract

摘要： 为了解决在永磁同步电机无速度传感器直接转矩控制系统中,扩展卡尔曼滤波器在转速估计时系统噪声矩阵和测量噪声矩阵难以较准确获得的问题,提出了一种基于改进粒子群优化的扩展卡尔曼滤波器转速估计方法,该方法融合了粒子群算法与遗传算法的优点,经过实验仿真表明,当将此方法应用于卡尔曼滤波器系统噪声矩阵和测量噪声矩阵寻优时,与遗传算法、标准粒子群算法相比,改进粒子群优化的卡尔曼滤波器能更加迅速地找到较优解。

关键词: 永磁同步电机, 直接转矩控制, 无速度传感器, 扩展卡尔曼滤波, 改进粒子群算法

Abstract: An extended Kalman filter(EKF) speed estimation method based on improved Particle Swarm Optimization(IPSO) is proposed to solve the problem that the estimation of system noise matrix and measurement noise matrix are difficult to obtain accurately when EKF is used to estimate the speed in the sensorless speed direct torque control(DTC) system of permanent magnet synchronous motors(PMSM). This method combines the advantages of Particle Swarm Optimization and Genetic Algorithms. Simulation results show that the IPSO Kalman filter can find the optimum solution more quickly when it is applied to the optimization of Kalman filter system noise matrix and measurement noise matrix comparing with genetic algorithms and standard particle swarm optimization.

Key words: PMSM, direct torque control, speed sensorless, extended Kalman filter, improved particle swarm optimization

中图分类号:

TM341

王剑, 黄植功, 许金海. 基于优化EKF的永磁同步电机转速估计[J]. 广西师范大学学报（自然科学版）, 2014, 32(4): 11-17.

WANG Jian, HUANG Zhi-gong, XU Jin-hai. Speed Estimation of Permanent Magnet Synchronous Motor Based on Optimized EKF[J]. Journal of Guangxi Normal University(Natural Science Edition), 2014, 32(4): 11-17.

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