组合机床与自动化加工技术2024,Issue(11) :122-124,129.DOI:10.13462/j.cnki.mmtamt.2024.11.023

基于EKF的PMSM无位置传感器控制

Position Sensor-Less Control of PMSM Based on EKF

任永强 侯陈义 王淑旺 蒋曜骏
组合机床与自动化加工技术2024,Issue(11) :122-124,129.DOI:10.13462/j.cnki.mmtamt.2024.11.023

基于EKF的PMSM无位置传感器控制

Position Sensor-Less Control of PMSM Based on EKF

任永强 1侯陈义 1王淑旺 2蒋曜骏1
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作者信息

  • 1. 合肥工业大学机械工程学院,合肥 230009
  • 2. 安徽巨一科技股份有限公司,合肥 230041
  • 折叠

摘要

为了获得永磁同步电机转子的位置信息,提出了一种五阶扩展卡尔曼滤波器(EKF)的算法;在传统的四阶EKF中引入对负载转矩的估算,并将其前馈至电流环以解决速度环对外界负载扰动响应慢的问题;通过设计改进的递推最小二乘法实时辨识电机的转动惯量,优化了系统的观测性能和鲁棒性,基于Simulink搭建仿真模型,结果表明该观测器性能优秀且提高了系统的抗扰动性能;最后,通过硬件实验实现了电机位置误差仅在0.02 rad以内,且负载转矩观测误差在4%以内,有效改善了系统在有负载波动时的动态特性.

Abstract

In order to obtain the position information of the rotor of permanent magnet synchronous motor,an extended Kalman filter ( EKF) algorithm is proposed;Introducing the estimation of load torque in the traditional fourth-order EKF and feedforward it to the current loop to solve the problem of slow response of the speed loop to external load disturbances;By designing an improved recursive least squares method for real-time identification of the motor's moment of inertia,the observation performance and robustness of the system were optimized. Building a simulation model based on Simulink,the results show that the observer has excellent performance and improves the system's disturbance resistance. Finally,hardware experiments were conducted to achieve a motor position error of only 0.02 rad and a load torque observation error of less than 4%,effectively improving the dynamic characteristics of the system under load fluctuations.

关键词

永磁同步电机/扩展卡尔曼滤波器/无位置传感器/负载转矩观测/最小二乘法

Key words

PMSM/extended Kalman filter/position sensor-less/load torque observation/least square method

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出版年

2024
组合机床与自动化加工技术
大连组合机床研究所 中国机械工程学会生产工程分会

组合机床与自动化加工技术

CSTPCD北大核心
影响因子:0.671
ISSN:1001-2265
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