Methodology and Research of Intelligent New Energy Vehicle Motion Control System based on Fuzzy Adaptive

被引:0
|
作者
Ji D. [1 ]
Li H. [1 ]
Liu W. [2 ]
机构
[1] School of Automotive Engg, Liuzhou Vocational & Technical College, Liuzhou
[2] School of Electromechanical and Automotive Engg, Liuzhou City Vocational College, Liuzhou
关键词
Driving system; Fuzzy adaptive; Motion control; New energy;
D O I
10.4273/ijvss.15.3.16
中图分类号
学科分类号
摘要
To resolve the difficult control issue of intelligent new energy automobile in the process of vehicle control, the study starts from the vehicle motion mode and splits the vehicle control into two parts, transverse control and longitudinal control. Among them, the longitudinal speed control is controlled by an improved adaptive PID model, while the lateral angle control is dominated by an indistinct adaptive PID model, afterwards longitudinal speed control is combined with the lateral angle control for joint control. Finally, the study uses the actual lane simulation to verify the three perspectives of transverse control, longitudinal control and joint control respectively. It shows that the longitudinal control and lateral control are well realized with the improved adaptive PID model control effect at 8km, 15km and 20km per hour. Meanwhile, maximum trajectory error of the combined direction and transverse dominate is always lower than 0.5m at vehicle speeds of 8km/h, 16km/h and 20km/h in the integrated road environment and the combined longitudinal speed and transverse angle control performance is good in the curves. This shows that the model designed by the research can realize adaptive real-time precision control. © 2023. Carbon Magics Ltd.
引用
收藏
页码:372 / 379
页数:7
相关论文
共 50 条
  • [31] Intelligent adaptive control of the vehicle-span/track system
    Dyniewicz, Bartlomiej
    Konowrocki, Robert
    Bajer, Czeslaw I.
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2015, 58-59 : 1 - 14
  • [32] Adaptive algorithm to vehicle following control in Intelligent Transportation System
    Ren, Dianbo
    Zhang, Jiye
    2008 INTERNATIONAL SYMPOSIUM ON INFORMATION PROCESSING AND 2008 INTERNATIONAL PACIFIC WORKSHOP ON WEB MINING AND WEB-BASED APPLICATION, 2008, : 46 - 50
  • [33] Intelligent Vehicle Control System Based on LED
    Zhang, JiePing
    Cui, ShiGang
    Chen, LiYun
    Chen, ZhiLiang
    Tian, LiGuo
    Wang, YongLiang
    MANUFACTURING PROCESS AND EQUIPMENT, PTS 1-4, 2013, 694-697 : 2149 - 2152
  • [34] Vision guided lateral control of agricultural vehicle based on adaptive neural fuzzy control system
    Lv, Zhaoqin (lzqsdau2003@126.com), 1600, Asian Association for Agricultural Engineering (25):
  • [35] Research on Canal System Automation Control Based on Adaptive Parameters Fuzzy
    Lan, Dunchen
    MECHATRONICS, ROBOTICS AND AUTOMATION, PTS 1-3, 2013, 373-375 : 1529 - 1532
  • [36] System Identification Methodology Preliminary Research on Maneuvering Motion of a New Type Unmanned Surface Vehicle
    Ma, Tianyu
    Wang, Taotao
    Li, Jun
    Yang, Songlin
    PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS RESEARCH AND MECHATRONICS ENGINEERING, 2015, 121 : 1645 - 1649
  • [37] Based on the fuzzy control of intelligent constant pressure water supply system research
    Qi, Xiangdong
    Yuan, Xize
    Yu, Shaojuan
    INFORMATION TECHNOLOGY APPLICATIONS IN INDUSTRY, PTS 1-4, 2013, 263-266 : 557 - 562
  • [38] Intelligent vehicle's path tracking based on fuzzy control
    Xiong, Bo
    Qu, Shiru
    Journal of Transportation Systems Engineering and Information Technology, 2010, 10 (02) : 70 - 75
  • [39] Longitudinal motion control of intelligent vehicle
    Li, Yibin
    Ruan, Jiuhong
    Li, Caihong
    Fu, Mengyin
    Jixie Gongcheng Xuebao/Chinese Journal of Mechanical Engineering, 2006, 42 (11): : 94 - 102
  • [40] Application of Adaptive Fuzzy Controller in Intelligent Greenhouse Control System
    Li, Shihua
    Liu, Shiyan
    Ju, Limei
    2008 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS, VOLS 1-6, 2008, : 1708 - 1712