基于多元线性回归模型的永磁同步电机参数辨识的新方法

系统仿真学报 ›› 2015, Vol. 27 ›› Issue (8): 1687-1696.

• 建模与仿真理论及方法 • 上一篇下一篇

基于多元线性回归模型的永磁同步电机参数辨识的新方法

时振伟^1,2, 纪志成¹

1.江南大学物联网工程学院,无锡 214122;
2.无锡机电高等职业技术学校,无锡 214122

收稿日期:2015-05-03 修回日期:2015-07-02 出版日期:2015-08-08 发布日期:2020-08-03

Novel Method to Identify PMSM Parameters Based on Multiple Linear Regressive Models

Shi Zhenwei^1,2, Ji Zhicheng¹

1. School of Internet of Things, Jiangnan University, Wuxi, 214122;
2. Wuxi Electrical and Higher Vocational Schools Wuxi 214122

Received:2015-05-03 Revised:2015-07-02 Online:2015-08-08 Published:2020-08-03
About author:Shi Zhenwei(1978-) Wuxi, China, doctoral student, his research interest: nonlinear system modeling theory and parameter estimation; Ji Zhicheng(1959-), Hangzhou, China, professor, his research interest: complex system modeling and the applications in wind power field.
Supported by:
National Natural Science Foundation of China (61174032); the Public Scientific Research Project of State Administration of Grain ( 201313012)

摘要/Abstract

摘要： 根据推导出的简单和实用的永磁同步电机(PMSM)多元线性回归辨识模型,提出了一种新的耦合带遗忘因子的递归最小二乘(C-FF-RLS)永磁同步电机参数辨识算法,与传统的多变量带遗忘因子递归最小二乘算法M-FF-RLS相比,因为C-FF-RLS算法在增益矩阵中避免了矩阵求逆运算,所以C-FF-RLS算法具有较高的计算效率和快速的收敛速度。所提出的辨识算法被应用于一个永磁同步电机的仿真系统。在仿真系统中,C-FF-RLS算法获得的辨识结果与M-FF-RLS算法得到的永磁同步电机参数进行了比较。比较表明,C-FF-RLS算法优于M-FF-RLS算法在辨识永磁同步电机参数时。

关键词: 永磁同步电机, 多模型, 仿真, 参数辨识, RLS

Abstract: A New Coupled Recursive Least Squares (C-FF-RLS) Algorithm with a forgetting factor was proposed for the Parameters Identification of Permanent Magnet Synchronous Motors (PMSMs). The deduced multiple linear regressive models of PMSM were proposed that were simple and appropriate for parameter identification. The C-FF-RLS identification algorithm had a high computational efficiency and a fast convergence speed because which Avoided the Matrix Inversion Operation in the Gain Matrix Compared with the Traditional Multivariable Recursive Least Squares (M-FF-RLS) Algorithm with a Forgetting Factor. The Proposed Identification Algorithm was applied on a simulation system of PMSM. The identification results achieved by the C-FF-RLS Algorithm comparing with the PMSM parameters obtained by the M-FF-RLS Algorithm. The comparisons show that the C-FF-RLS Algorithm performs better than the M-FF-RLS Algorithm for the parameters identification of PMSM.

Key words: PMSM, multiple models, simulation, parameter identification, RLS

中图分类号:

TM301.6

时振伟, 纪志成. 基于多元线性回归模型的永磁同步电机参数辨识的新方法[J]. 系统仿真学报, 2015, 27(8): 1687-1696.

Shi Zhenwei, Ji Zhicheng. Novel Method to Identify PMSM Parameters Based on Multiple Linear Regressive Models[J]. Journal of System Simulation, 2015, 27(8): 1687-1696.

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基于多元线性回归模型的永磁同步电机参数辨识的新方法

Novel Method to Identify PMSM Parameters Based on Multiple Linear Regressive Models

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