吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (5): 1527-1534.doi: 10.13229/j.cnki.jdxbgxb201505022

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电动车用永磁电机新型观测器设计

张永博1, 2, 易伯瑜1, 康龙云1   

  1. 1.华南理工大学 机械与汽车工程学院, 广州 510640;
    2.华南农业大学 工程学院 广州 510642
  • 收稿日期:2014-03-04 出版日期:2015-09-01 发布日期:2015-09-01
  • 通讯作者: 康龙云(1961-),男,教授,博士生导师.研究方向:可再生能源,新能源变换控制技术,新能源汽车电机驱动技术.E-mail:lykang@scut.edu.cn
  • 作者简介:张永博(1968--）,男,讲师,博士研究生.研究方向:增程式电动车.E-mail:ybzhang@scau.edu.cn
  • 基金资助:
    国家自然科学基金项目(51377058)

Novel observer design of permanent magnet synchronous motor for electric vehicles

ZHANG Yong-bo1, 2, YI Bo-yu1, KANG Long-yun1   

  1. 1.School of Mechanical and Automobile Engineering, South China University of Technology, Guangzhou 510640, China;
    2.College of Engineering,South China Agriculture University,Guangzhou 510642,China
  • Received:2014-03-04 Online:2015-09-01 Published:2015-09-01

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摘要： 在电动汽车永磁同步电机的无传感器控制中,转子磁链值的参数摄动对转子速度和角度的辨识效果影响较大。为此,可以把转子磁链作为变量加入到扩展卡尔曼滤波器中进行辨识,但这会增加运算矩阵的阶数,造成实际系统运算量偏大。为解决这一问题,通过坐标变换的方法将高阶的扩展卡尔曼滤波器分解成为两个并行的低阶卡尔曼滤波器,提出一种用于永磁电机无传感器控制的非线性两段扩展卡尔曼滤波器,并在理论上分析了滤波器所需的乘法加法运算次数。仿真及实验结果表明:与原有传统卡尔曼滤波器相比,该算法减少了一定的运算量并保持了良好的辨识效果。

关键词: 自动控制技术, 无传感器控制, 转子磁链, 非线性两段扩展卡尔曼滤波器

Abstract: The conventional sensorless algorithm for electric vehicle based on Extended Kalman Filter (EKF) can be influenced by the error of the rotor flux and shows considerable steady-state speed and position deviations. To take rotor flux as a variable in the EKF may increase the order of the operational matrix and the computation load of the real system. To solve this problem and still keep the advantage of the original algorithm, a novel Kalman control strategy using Nonlinear Two-stage EKF (NTSEKF) is proposed. The main idea is to decouple the Kalman filter into two parallel low order filters using coordinate transformation. In theory, the total number of multiplication and addition operations for EKF and NTSEKF is calculated respectively. Simulation and experimental results show that the novel strategy can reduce the number of arithmetic operations compared to EKF meanwhile still keep good identification performance.

Key words: automatic control technology, sensorless control, rotor flux, nonlinear two-stage extended Kalman filter

中图分类号: 

  • TP29
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