一种改进的同步磁阻电机无模型预测电流控制*

doi:10.11985/2023.02.001

电气工程学报 ›› 2023, Vol. 18 ›› Issue (2): 1-8.doi: 10.11985/2023.02.001

• 电机与电器 • 下一篇

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一种改进的同步磁阻电机无模型预测电流控制^*

石国航¹(), 张永昌²(), 杨海涛¹()

1.电力电子与电气传动北京市工程研究中心(北方工业大学) 北京 100144
2.华北电力大学电气与电子工程学院北京 102206

收稿日期:2021-12-27 修回日期:2022-04-15 出版日期:2023-06-25 发布日期:2023-07-12
作者简介:石国航，女，1997年生，硕士研究生。主要研究方向为同步磁阻电机控制。E-mail：hope9456@163.com
张永昌，男，1982年生，教授，博士研究生导师。主要研究方向为模型预测控制在电力电子与电机控制中的应用。E-mail：zhangdavid37@gmail.com
杨海涛，男，1987年生，副教授，硕士研究生导师。主要研究方向为异步电机模型预测控制。E-mail：yhtseaky@gmail.com
基金资助:
国家自然科学基金资助项目(52077002)

An Improved Model-free Predictive Current Control for Synchronous Reluctance Motor Drives

SHI Guohang¹(), ZHANG Yongchang²(), YANG Haitao¹()

1. Power Electronics and Motor Drive Engineering Research Center of Beijing (North China University of Technology), Beijing 100144
2. School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206

Received:2021-12-27 Revised:2022-04-15 Online:2023-06-25 Published:2023-07-12

摘要/Abstract

摘要：

无模型预测电流控制(Model-free predictive current control, MFPCC)由于本质上对系统内外扰动具有鲁棒性，在电机驱动领域得到广泛的研究，能够实现同步磁阻电机(Synchronous reluctance motor, SynRM)的高性能控制。传统的MFPCC方法把各时刻电压矢量对应的电流差分存储在查找表(Lookup table, LUT)中，进而预测下一时刻的最优电压矢量，但存在电流差分更新停滞和稳态性能不理想的问题。针对这些问题，提出一种改进的MFPCC方法，将电机模型用超局部模型表示，通过在线估计增益项和扰动项来及时更新LUT，解决了电流差分更新停滞的问题。另外利用扩展的有限状态集，得到更精确的电压矢量，改善了系统稳态性能。最后将所提方法与传统的MFPCC方法进行对比，仿真和试验结果表明该方法可以有效解决电流更新停滞的问题，并在全速范围内具有良好的动静态性能。

关键词: 同步磁阻电机, 无模型预测控制, 超局部模型, 扩展有限状态集

Abstract:

Model-free predictive current control(MFPCC) has been widely studied in the field of motor drive because of its intrinsic robustness to internal and external disturbances of the system, and can achieve high performance control of synchronous reluctance motor(SynRM). The traditional MFPCC method stores the current difference corresponding to the voltage vector at each time in the lookup table(LUT), and then predicts the optimal voltage vector at the next time, but there are problems of current difference update stagnation and unsatisfactory steady-state performance. To solve these problems, an improved MFPCC method is proposed. The motor model is expressed as an ultra-local model, and the LUT is updated timely by estimating the gain term and disturbance term online, which solves the current differential update stagnation problem. In addition, a more accurate voltage vector is obtained by using the extended finite state set to improve the steady-state performance. Finally, the proposed method is compared with the traditional MFPCC method, and the simulation and experimental results show that the proposed method effectively solves the problem of current update stagnation, and has good dynamic and static performance in the full speed range.

Key words: Synchronous reluctance motor, model-free predictive control, ultra-local model, extended finite state set

中图分类号:

TM352

石国航, 张永昌, 杨海涛. 一种改进的同步磁阻电机无模型预测电流控制^*[J]. 电气工程学报, 2023, 18(2): 1-8.

SHI Guohang, ZHANG Yongchang, YANG Haitao. An Improved Model-free Predictive Current Control for Synchronous Reluctance Motor Drives[J]. Journal of Electrical Engineering, 2023, 18(2): 1-8.

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参数	数值
直流母线电压U_dc/V	540
额定功率P_n/kW	2.2
额定电压U_n/V	380
额定频率f_n/Hz	50
极对数N_p	2
d轴电感L_d/mH	196.2
q轴电感L_q/mH	89.25
定子电阻R_s/Ω	2.532
额定转矩T_n/(N·m)	14

一种改进的同步磁阻电机无模型预测电流控制^*

An Improved Model-free Predictive Current Control for Synchronous Reluctance Motor Drives

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