Active Safety Control Strategy of Electric Vehicles Considering CAN-Induced Time Delay

被引：0

作者：

Wei H. ^{[1
,2
]}

Wang H. ^{[3
]}

Zhao W. ^{[1
]}

Ai Q. ^{[1
,2
]}

Lai C. ^{[4
]}

Zhang Y. ^{[1
,2
]}

Zou X. ^{[4
]}

机构：

[1] School of Mechanical Engineering, Beijing Institute of Technology, Beijing

[2] Key Lab of Low Emission Vehicle (Beijing), Beijing

[3] China Automotive Engineering Research Institute Co., Ltd, Chongqing

[4] School of Vehicle Engineering, Chongqing University of Technology, Chongqing

来源：

Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology | 2022年 / 42卷 / 08期

关键词：

active safety; electric vehicles; network delay; robust model predictive control;

D O I：

10.15918/j.tbit1001-0645.2021.322

中图分类号：

学科分类号：

摘要：

The message processing and data packet loss of the automotive CAN network would cause the time delay effect of the automotive control system, thereby affecting the accuracy of the vehicle dynamics control. In order to solve this problem, a vehicle yaw stability control strategy was proposed based on robust model predictive control. First, the message delay characteristics of CAN network was analyzed, and a multicellular time-delay model was built to describe the parametric uncertainty. A robust model predictive controller containing uncertain parameters was designed to improve the anti-interference ability of the active safety controller. In addition, the comprehensive solution scheme of the variable time-domain robust optimal control law was also studied based on the asymptotically stable invariant ellipse set to improve the online solution efficiency, and meanwhile to balance the robustness and optimality of the system control. The results show that the proposed control strategy can resist the parameter uncertainty induced by the CAN network, alleviate the conservativeness of the robust control algorithm, and improve the active safety performance of the vehicle. © 2022 Beijing Institute of Technology. All rights reserved.

引用

页码：798 / 808

页数：10

共 14 条

[1] WANG Zhenpo, XUE Xue, WANG Yachao, State parameter estimation of distributed drive electric vehicle based on adaptive unscented Kalman filter[J], Transactions of Beijing Institute of Technology, 38, 7, (2018)
[2] MENG Xiang, CAO Wanke, LIN Cheng, Et al., Research on performance and scheduling strategy of TTCAN system for independent driving electric vehicle[J], Transactions of Beijing Institute of Technology, 31, 6, (2011)
[3] LIN Cheng, XU Zhifeng, ZHOU Fengjun, Et al., Stability hierarchical control strategy for distributed-driving electric vehicle[J], Transactions of Beijing Institute of Technology, 35, 5, (2015)
[4] GAO Z, ZHANG D, ZHU S, Et al., Distributed active disturbance rejection control for Ackermann steering of a four-in-wheel motor drive vehicle with deception attacks on controller area networks, Information Sciences, 540, pp. 370-389, (2020)
[5] SHUAI Z B, ZHANG H, WANG J M, Et al., Combined AFS and DYC control of four-wheel-independent-drive electric vehicles over CAN network with time-varying delays[J], IEEE Transactions on Vehicular Technology, 63, 2, (2013)
[6] ZHU X Y, ZHANG H, WANG J, Et al., Robust lateral motion control of electric ground vehicles with random network-induced delays[J], IEEE Transactions on Vehicular Technology, 64, 11, (2015)
[7] DING Xiaolin, WANG Zhenpo, ZHANG Lei, Powertrain sizing for four-wheel-independent-actuated electric vehicles based on multi-objective optimization[J], Journal of Mechanical Engineering, 57, 8, (2021)
[8] QIAO Chen, Time dealy analysis and control of distributed drive electric vehicle network, (2016)
[9] YANG Zhihao, Research on the stability of distributed drive electric vehicle based on the vehicle bus, (2015)
[10] MING Yao, Analysis and lateral dynamics control of distributed drive electric vehicle with network-induced induced delays, (2017)

← 1 2 →