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汽车安全与节能学报

汽车安全与节能学报 ›› 2021, Vol. 12 ›› Issue (3): 386-394.DOI: 10.3969/j.issn.1674-8484.2021.03.014

• 汽车节能与环保 • 上一篇    下一篇

基于改进GWO算法的永磁同步电机滑模MRAS控制

王泽霖(), 胡启国*()   

  1. 重庆交通大学 机电与车辆工程学院,重庆 400074,中国
  • 收稿日期:2021-01-17 出版日期:2021-09-30 发布日期:2021-10-09
  • 通讯作者: 胡启国
  • 作者简介:* 胡启国,教授。E-mail: swpihqg@163.com。
    王泽霖（1997—）,男（汉族）,甘肃,硕士研究生。E-mail: 1942027030@qq.com。

Sliding mode MRAS control for permanent magnet synchronous motor based on an improved GWO algorithm

WANG Zelin(), HU Qiguo*()   

  1. School of Mechanical-electronic and Vehicle Engineering, Chongqing Jiaotong University, Chongqing 400074,China
  • Received:2021-01-17 Online:2021-09-30 Published:2021-10-09
  • Contact: HU Qiguo

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摘要：

设计了一种改进的新型滑模模型参考自适应系统(MRAS),以提高传统的永磁同步电机(PMSM)滑模MRAS控制性能。在传统滑模MRAS中的积分滑模面基础上引入非奇异快速终端滑模面,构成一种积分型非奇异快速终端滑模面,以提高收敛性能。用非线性指数函数来代替传统滑模MRAS中的开关函数,用改进的灰狼优化(GWO)算法,对滑模面参数进行全局寻优,以提升控制精度。进行了Matlab/Simulink软件的仿真。结果表明:相比传统的滑模MRAS,改进后的滑模MRAS将系统转矩脉动幅度降低75%,实际转速抖动幅度降低80%,超调控制在2.3%以内,调节时间控制在10 ms以内,转子位置观测误差减小60%。

关键词: 永磁同步电机(PMSM), 模型参考自适应系统(MRAS), 滑模MRAS, 灰狼优化(GWO), 非奇异快速终端滑模面, 非线性指数函数

Abstract:

An improved sliding mode model reference adaptive system (MRAS) was designed to improve the control performance of traditional permanent magnet synchronous motor (PMSM) sliding mode MRAS. Based on the integral sliding mode surface of traditional sliding mode MRAS, the non-singular fast terminal sliding mode surface was introduced, which constitutes an integral non-singular fast terminal sliding mode surface to improve the convergence performance. A nonlinear exponential function was used to replace the switching function in the traditional sliding mode MRAS, and an improved gray wolf optimization (GWO) algorithm was used to optimize the sliding mode surface parameters globally to improve the control precision. The simulation results of MATLAB/Simulink software show that compare with the traditional sliding mode MRAS, the improved sliding mode MRAS can reduce the torque ripple amplitude by 75%, reduce the actual speed jitter amplitude by 80%, control the actual speed overshot within 2.3%, control the adjustment time within 10 ms, and reduce the observation error of rotor position by 60%.

Key words: permanent magnet synchronous motor (PMSM), model reference adaptive system (MRAS), sliding model MRAS, grey wolf optimization (GWO), non-singular fast terminal sliding surface, nonlinear exponential function

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