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SIMULINK中PMSM模型的改进及在参数辨识中的应用
引用本文:王莉娜,杨宗军.SIMULINK中PMSM模型的改进及在参数辨识中的应用[J].电机与控制学报,2012,16(7):77-82.
作者姓名:王莉娜  杨宗军
作者单位:北京航空航天大学自动化科学与电气工程学院,北京,100191
基金项目:国家自然科学基金,北京市科技新星计划,电力系统国家重点实验室资助
摘    要:Matlab\SIMULINK中集成的永磁同步电机模型在调速系统仿真中应用广泛,但存在电机参数不可动态修改,坐标定义不符合常规逻辑等不足,给研究工作带来不便.在分析永磁同步电机数学模型的基础上,针对原电机模型的不足提出了两种改进方案,并给出具体操作步骤和使用方法.一是根据需求直接对库模型做修改,二是自定义永磁同步电机仿真模型,这两种方法简单有效,各有其优点.仿真通过对比验证了改进模型的正确性,并结合模型参考自适应算法将自定义永磁同步电机模型应用在电机参数辨识中.结果显示,改进后的永磁同步电机模型弥补了原有模型的不足,在变参数变结构的动态仿真中具有实用性,拓展了永磁同步电机模型的应用范围.

关 键 词:SIMULINK  永磁同步电机  参数动态修改  坐标变换  非线性PI  模型参考自适应辨识

PMSM model's reform in SIMULINK and application in parameters' identification
WANG Li-na , YANG Zong-jun.PMSM model's reform in SIMULINK and application in parameters' identification[J].Electric Machines and Control,2012,16(7):77-82.
Authors:WANG Li-na  YANG Zong-jun
Affiliation:(School of Automation Science and Electrical Engineering,Beihang University,Beijing 100191,China)
Abstract:Although permanent magnet synchronous motor(PMSM) in SIMULINK is widely used in the simulation of speed regulation,its disadvantages such as the motor parameters not being dynamically modified and the coordinates transformation not being consistent with conventional logic bring researchers a lot of troubles.Based on the analysis of the PMSM mathematical model,this paper put forward two improved methods and provided the operated procedure and method in detail.The first was to modify the library file according to the demands and the second was to customize the PMSM model.Both of them were simple and effective with their advantages.The two methods were proved correct by simulation and the second was applied successfully in the simulation of parameter identification with model reference adaptive identification(MRAI) algorithm.Simulation results show that,with great practicality for variable structures and parameters systems in the dynamic simulation,the improved models cover the shortages of original PMSM model,and extend the application of PMSM model.
Keywords:SIMULINK  permanent magnet synchronous motors  parameters’ dynamic modifying  coordinate transformation  nonlinear PI  model reference adaptive identification
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