Speed Sensor Fault Detection and Tolerant Control for New Energy Vehicle Drive System

被引:0
作者
Xiao L. [1 ]
Gao F. [2 ]
Hou S. [1 ]
Yu L. [1 ]
Zhang H. [1 ]
Liu B. [1 ]
机构
[1] School of Information Engineering, Tianjin University of Commerce, Tianjin
[2] Shenhua Tianjin Coal Terminal Co. Ltd, Tianjin
来源
Diangong Jishu Xuebao/Transactions of China Electrotechnical Society | 2020年 / 35卷 / 24期
关键词
Fault detection; New energy vehicle; Sliding mode observer; Speed sensor; Tolerant control;
D O I
10.19595/j.cnki.1000-6753.tces.191391
中图分类号
学科分类号
摘要
For the failure of speed sensor of the new energy vehicle drive system, this paper proposes a fault detection and tolerant control method for permanent magnet synchronous motor drive system in vehicles based on an improved high-order sliding mode observer. Firstly, the super-spin algorithm is used to optimize the design of high-order sliding mode observer to improve the convergence and speed tracking accuracy under different types of interference. Secondly, the new sliding mode observer is used to calculate the speed observation value, and the difference between the actual speed and the estimated speed is selected as the fault feature quantity, and then the fault detection and tolerant control method are proposed. Finally, the simulation analysis and experimental verification corresponding with the constant-speed driving mode and the variable-load driving mode of vehicles are carried out. The results show that regardless of driving conditions the proposed system can detect the fault accurately and timely, and has good fault-tolerant performance. Compared with the drive system with the traditional high-order sliding mode observer, the proposed method has higher speed tracking accuracy and better fault-tolerant control effect. © 2020, Electrical Technology Press Co. Ltd. All right reserved.
引用
收藏
页码:5075 / 5086
页数:11
相关论文
共 17 条
  • [1] Hu Sideng, Liang Zipeng, Zhang Wei, Et al., Research on the integration of hybrid energy storage system and dual three-phase PMSM drive in EV, IEEE Transactions on Industrial Electronics, 65, 8, pp. 6602-6611, (2018)
  • [2] Chaoui H, Khayamy M, Okezie O., Adaptive RBF network based direct voltage control for interior PMSM based vehicles, IEEE Transactions on Vehicular Technology, 67, 7, pp. 5740-5749, (2018)
  • [3] Xiao Li, Fan Shurui, Wang Bowen, Fault detection method of power converter for switched reluctance motor based on analysis of current, Electric Machines and Control, 22, 4, pp. 67-74, (2018)
  • [4] Li Haoyuan, Zhang Xing, Yang Shuying, Et al., Review on sensorless control of permanent magnet synchronous motor based on high-frequency signal injection, Transactions of China Electrotechnical Society, 33, 12, pp. 2653-2664, (2018)
  • [5] Guo Lei, Yang Zhongping, Lin Fei, A sensorless control strategy for high frequency signal injection permanent magnet synchronous motor with error compensation, Transactions of China Electro-technical Society, 34, 21, pp. 4458-4466, (2019)
  • [6] Xu Zhongyang, Guo Xizheng, Zou Fangshuo, Et al., Research on digital discretization method of speed sensorless control for permanent magnet synchronous motor, Transactions of China Electrotechnical Society, 34, S1, pp. 52-61, (2019)
  • [7] Dong Lianghui, Liu Jinglin, Research on the fault tolerant control and its dynamic performance of brushless permanent magnet motor with faults in hall sensor, Proceedings of the CSEE, 37, 12, pp. 3602-3611, (2017)
  • [8] Lu Degang, Du Zeyuan, Li Song, Fault-tolerant of brushless permanent magnet motor drives with Hall sensors, Electric Machines and Control, 23, 2, pp. 44-52, (2019)
  • [9] Bai Hongfen, Zhu Jingwei, Qin Junfeng, Et al., Estimation algorithm of rotor position for dual-winding fault tolerant permanent magnet motor drive based on SMO-MRAS, Control and Decision, 33, 1, pp. 27-36, (2018)
  • [10] Zhang Liwei, Li Hang, Song Peipei, Et al., Sensorless vector control using a new sliding mode observer for permanent magnet synchronous motor speed control system, Transactions of China Electrotechnical Society, 34, S1, pp. 70-78, (2019)