文献类型：期刊文献

中文题名：一种基于简化MRAS无速度传感器的永磁电机EKF磁链辨识

英文题名：Flux Identification of SPMSM Based on Simplified MRAS Senseless Control System

作者：刘梦佳[1];孙自强[1];卿湘运[1]

机构：[1]华东理工大学化工过程先进控制和优化技术教育部重点实验室,上海200237

年份：2015

卷号：41

期号：2

起止页码：222

中文期刊名：华东理工大学学报（自然科学版）

外文期刊名：Journal of East China University of Science and Technology

收录：CSTPCD;;Scopus;北大核心:【北大核心2014】；CSCD:【CSCD2015_2016】；

基金：上海市重点学科建设基金(B504)

语种：中文

中文关键词：表面式永磁同步电机;扩展的卡尔曼滤波;模型参考自适应观测器;无速度传感器系统

外文关键词：surface-mounted permanent magnet synchronous machine; extended Kalman filter; model reference adaptive system; sensorless control system

摘要：表面式永磁同步电机因其结构简单、功率密度高、效率高等优势,被广泛应用于高性能伺服系统以及其他工业场合中。由于电机控制性能受温度和磁饱和等现象影响,电机参数的在线辨识则显得至关重要。针对由于永磁电机数学模型阶数低造成无法由一个估计器同时辨识转速和电机参数的问题,本文提出了一种结合EKF和MRAS辨识的优点,在MRAS无速度传感器系统估计转速的基础上通过EKF观测器估计永磁体磁链的解决方法,并与精确MRAS算法作了比较,对自适应PI参数的选择进行了讨论。Simulink仿真研究验证了该方法的有效性和准确性,能满足电机运行速度快且动态要求高的场合需要。
Surface-mounted permanent magnet synchronous machine （SPMSM） has been widely applied in the servo drives and other industrial fields, due to its simpler structure, higher power/torque density, and better control performance. However, the change of temperature and flux saturation may seriously affect the control performance of motor. So it is significant to identify the parameters of motor online. Due to the low-0rder state model of permanent magnet motor, the speed and parameters can not be simultaneously identified by using only one observer. Hence, this paper presents a method to cope with the above problem by combining EKF and MRAS to estimate magnet flux and rotor speed respectively. Meanwhile, the comparison with the accurate MRAS model is made and some discussions on the selection of adaptive PI parameters are also given. Simulation results illustrate the feasibility and effectiveness of the proposed methods.