基于新型权重解析法的永磁电机预测转矩控制

颜黎明; 郭鑫; 赵冬冬

doi:10.7527/S1000-6893.2022.27785

航空学报 >

2022 , Vol. 43 >Issue 12: 327785 - 327785

DOI: https://doi.org/10.7527/S1000-6893.2022.27785

电子电气工程与控制

基于新型权重解析法的永磁电机预测转矩控制

颜黎明 ,
郭鑫 ,
赵冬冬

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1. 长安大学汽车学院, 西安 710064;
2. 西北工业大学自动化学院, 西安 710072

收稿日期: 2022-07-11

修回日期: 2022-08-04

网络出版日期: 2022-09-22

基金资助

国家自然科学基金（52107036）；中国博士后科学基金（2022T150071）

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Model predictive torque control of permanent magnet synchronous motor using novel analytic weighting factor assignment

YAN Liming ,
GUO Xin ,
ZHAO Dongdong

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1. School of Automobile, Chang'an University, Xi'an 710064, China;
2. School of Automation, Northwest Polytechnic University, Xi'an 710072, China

Received date: 2022-07-11

Revised date: 2022-08-04

Online published: 2022-09-22

Supported by

National Natural Science Foundation of China (52107036);China Postdoctoral Science Foundation (2022T150071)

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摘要

在永磁同步电机有限集预测转矩控制中，多控制目标的最优协同调控依赖于权重因子的配置。由于目前缺乏理论指导，权重因子的设计通常采用额定值法或试凑法，无法实现多工况下永磁同步电机电磁转矩和定子磁链幅值的协同控制。针对此问题，提出了基于新型解析权重因子配置的永磁同步电机模型预测转矩控制。基于仿真法研究了代价函数中权重因子对电驱系统控制性能的影响规律，详细阐述了解析权重因子的推导过程及其数学表达式。考虑到解析权重及预测模型均依赖于电机参数，本文方法融合了在线电机参数辨识技术。与传统预测转矩控制相比，本文方法具有更好的动态、稳态及鲁棒性能。

关键词： 模型预测控制; 永磁同步电机; 预测转矩控制; 权重因子; 最优控制

本文引用格式

颜黎明 , 郭鑫 , 赵冬冬 . 基于新型权重解析法的永磁电机预测转矩控制[J]. 航空学报, 2022 , 43(12) : 327785 -327785 . DOI: 10.7527/S1000-6893.2022.27785

Abstract

In finite control set-predictive torque control of Permanent Magnet Synchronous Motor (PMSM), the optimal coordinated regulation of multiple control objectives depends on the allocation of weighting factors. Due to the lack of theoretical guidance, the design of weighting factor usually adopts the rated value method or cut-and-trial method, which cannot realize the coordinated control of electromagnetic torque and stator flux amplitude of PMSM under multiple operating conditions. To solve this problem, a model predictive torque control of PMSM with novel analytical weighting factor configuration is proposed in this paper. Firstly, the influence of weighting factor in the cost function on the control performances of electric drive system is studied by the simulation method. Secondly, the derivation process and mathematical expression of analytical weighting factors are described. Considering that the analytical weighting factor and the prediction model depend on the motor parameters, this paper integrates the online motor parameter identification technologies. Compared with traditional predictive torque control, the proposed method has better dynamic and steady-state and robustness performances.

Key words： model predictive control; permanent magnet synchronous machine; predictive torque control; weighting factor; optimal control

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