基于改进开关磁阻电机模型的无位置传感器检测研究  

Research on Sensorless Position Detection Based on Improved Switched Reluctance Motor Model

作　　者：赵永生 刘鹤 柳健 范云生 ZHAO Yongsheng;LIU He;LIU Jian;FAN Yunsheng(College of Electrical Engineering,Dalian Maritime University,Dalian 116026,China)

机构地区：[1]大连海事大学船舶电气工程学院,辽宁大连116026

出　　处：《火力与指挥控制》2022年第12期39-47,共9页Fire Control & Command Control

基　　金：国家自然科学基金(51609033);辽宁省自然科学基金资助项目(20180520005)。

摘　　要：在简化磁链法中建立精确而小规模的开关磁阻电机(SRM)磁链模型,是实现SRM系统中无位置传感器控制的关键。采用堵转实验获取的磁链信息作为样本数据,构建电机磁链信息的最小二乘支持向量机(LSSVM)磁链特性模型;采用粒子群算法对建立的电机磁链模型的参数进行优化,将优化后的磁链特性模型应用于磁链法关断角位置处数据表中,实现开关磁阻电机驱动系统的正常运行,进而实现对转子位置的预测。实例仿真结果表明:优化后的磁链模型参数寻优耗时下降,预测磁链精度提高,转子位置前后误差缩小,应用于SRM无位置传感器控制策略中具有可行性。Establishing an accurate and small-scale SRM flux linkage model in the simplified flux linkage method is the key to realizing the position sensorless control in the SRD system.Firstly,the flux linkage information obtained by the locked rotor experiment is used as sample data to construct the least square support vector machine(LSSVM)flux linkage characteristic model of the motor flux linkage information.Then the particle swarm algorithm is used to optimize the parameters of the established motor flux model,and the optimized flux characteristic model is applied to the data table at the turn-off angle position of the flux linkage method to achieve the normal operation of the SRD system,and then to realize the rotor Location prediction.The simulation results of the example show that the optimized flux model parameter optimization takes less time,the accuracy of the predicted flux linkage is improved,and the front and back error of the rotor position is reduced.It is feasible to be applied to the SRM position sensorless control strategy.

关 键 词：开关磁阻电机 最小二乘支持向量机 粒子群算法 无位置传感器控制 磁链模型 

分 类 号：TM352[电气工程—电机] TM341