电流传感器故障状态下内嵌式永磁同步电机的无位置传感器容错控制算法研究
Research on sensorless fault-tolerant control algorithm for interior permanent magnet synchronous machine under sensor fault conditions
房钰超 1王博 1王元奎 2王云冲 1黄彰浩 1沈建新1
作者信息
- 1. 浙江大学 电气工程学院,浙江 杭州310027
- 2. 浙江大学 海洋学院,浙江 舟山316021
- 折叠
摘要
为了解决在永磁同步电机(PMSM)驱动控制中,电流传感器可能出现故障导致系统失控的问题,提出一种变参数的相电流重构方法,对定子电流进行精确观测,实现PMSM在无位置传感器控制下的电流传感器容错控制.研究了电机参数扰动和无位置传感器控制观测误差等非理想因素对直接搭建龙贝格观测器精度的影响.分析了观测电流的幅值误差和角度误差特性,通过引入2个自适应变化参数以调整重构电流的幅值,消除非理想因素对重构电流精度的影响.搭建仿真和实验平台验证算法有效性.实验结果表明,电流传感器故障后,电角度观测误差仅增加1°,dq轴电流波动峰峰值仅增加0.1 A.该算法能够实现电机的转速、位置及电流信息的准确观测,使得系统具有良好的稳态精度和动态性能.
Abstract
In order to solve the problem that the current sensors may malfunction in permanent magnet synchronous machine ( PMSM) drives,a phase current reconstruction algorithm with variable parameters was proposed to accurately estimate the stator current and realize fault-tolerant control of the current sen-sor under the position sensorless control of PMSM.The influence of non-ideal factors such as motor pa-rameter variation and sensorless control strategy estimated error on the accuracy of directly constructed Luenberger observer was studied.The amplitude error and angle error characteristics of the estimated cur-rent were analyzed.Two adaptive parameters were introduced to adjust the amplitude of the reconstructed current,and the influence on non-ideal factors on the accuracy of the reconstructed current can be elimi-nated.A simulation and experimental platform were built to verify effectiveness of this algorithm.The ex-perimental results show that after the current sensor malfunctions,the estimated error of electric angle is only increased by 1°,and the peak-to-peak value of dq axis current ripple is only increased by 0.1 A.The algorithm can accurately estimate the speed,position and current information of the motor,and the system has good steady-state accuracy and dynamic performance.
关键词
永磁同步电机/无位置传感器控制/电流传感器/容错运行/电流状态观测器/相电流重构Key words
permanent magnet synchronous machine/sensorless control/current sensor/fault-tolerant control/current state observer/phase current reconstruction引用本文复制引用
基金项目
国家重点研发计划(2022YFB3403100)
出版年
2024
NETL
NSTL
万方数据