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汽车安全与节能学报 ›› 2022, Vol. 13 ›› Issue (3): 560-570.DOI: 10.3969/j.issn.1674-8484.2022.03.018

• 汽车节能与环保 • 上一篇    下一篇

基于改进模型参考自适应的永磁轮毂电机无位置传感器控制

李勇1,2(), 胡晗1, 秦贞超4, 吴浩1, 王文军3   

  1. 1.江苏大学汽车工程研究院,镇江 212013,中国
    2.清华大学苏州汽车研究院(吴江),苏州 215200,中国
    3.清华大学,汽车安全与节能国家重点实验室,北京 100084,中国
    4.北京特种机械研究所,北京 100143,中国
  • 收稿日期:2021-09-26 修回日期:2022-03-24 出版日期:2022-09-30 发布日期:2022-10-04
  • 作者简介:李勇(1986—),男(汉),山东,副教授。E-mail: liyongthinkpad@outlook.com
  • 基金资助:
    国家自然科学基金资助项目(51705213);汽车安全与节能国家重点实验室开放基金资助项目(KF2004)

Sensorless control of permanent magnet in-wheel motor based on improved model reference adaptive strategy

LI Yong1,2(), HU Han1, QIN Zhenchao4, WU Hao1, WANG Wenjun3   

  1. 1. Automotive Engineering Research Institute, Zhenjiang 212013, China
    2. Suzhou Automotive Research Institute, Tsinghua University, Suzhou 215200, China
    3. State Key Lab of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
    4. Beijing Specialized Machinery Institute, Beijing 100143, China
  • Received:2021-09-26 Revised:2022-03-24 Online:2022-09-30 Published:2022-10-04

摘要:

为了提高分布式驱动电动汽车用永磁轮毂电机在变负载、宽转速范围内无位置传感器控制算法的可靠性,本文提出了一种基于改进模型参考自适应( IMRAS)的永磁轮毂电机无位置传感器控制方法。在传统模型参考自适应(MRAS)算法中固定增益自适应律设计基础上,结合自抗扰控制算法(ADRC)中的非线性变增益模块设计方法,利用fal函数构建了具有变增益非线性特性的自适应律,实现了对轮毂电机转子位置与转速的准确估算,并对所提出的控制方法进行了仿真及台架测试。结果表明:改进后的无位置传感器控制方法具有较强的鲁棒性和抗干扰特性,尤其在宽转速范围、负载突变等工况下具有较好的自适应能力。

关键词: 轮毂电机, 无位置传感器控制, 改进模型参考自适应( IMRAS), 非线性自适应律

Abstract:

An improved model reference adaptive system (IMRAS) sensorless control method for permanent magnet in-wheel motor was proposed to improve the operational reliability of the sensorless control algorithm for in-wheel motor drive electric vehicles under variable load and wide rotation speed range operating conditions. Based on the fixed-gain adaptive law design in the traditional model reference adaptive system (MRAS), the nonlinear variable-gain design with active disturbance rejection controller (ADRC) was considered. The fal function was employed to establish the adaptive law with variable-gain nonlinear characteristics, which achieved the accurate estimation of the rotor position and rotation speed of the in-wheel motor. The proposed IMRAS method was verified through simulation and experiments. The results show that the sensorless control algorithm with the proposed IMRAS has strong robustness and high capability of anti-interference and adaption ability, especially in the wide speed range and under conditions of sudden change load.

Key words: in-wheel motor, sensorless control, improved model reference adaptive system (IMRAS), nonlinear adaptive law

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