Robust fuzzy stability control optimization by multi-objective for modular vehicle

被引:32
|
作者
Silva, Fabricio Leonardo [1 ]
Silva, Ludmila C. A. [1 ]
Eckert, Jony Javorski [1 ]
Lourenco, Maria A. M. [1 ]
机构
[1] Univ Campinas UNICAMP, BR-13083860 Campinas, SP, Brazil
关键词
Modular vehicle; Fuzzy logic control; Genetic algorithm; Multi-objective optimization; Electronic differential; MODEL-PREDICTIVE CONTROL; ELECTRIC VEHICLES; WHEEL MOTORS; SYSTEM;
D O I
10.1016/j.mechmachtheory.2021.104554
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Modular design becomes a trend in the automotive industry to increase competitiveness with vehicle platforms that combine multiple modules to provide different applications. This paper presents an optimized Fuzzy Logic Control (FLC) applied to modular all-wheel-drive vehicles, focusing on Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEV) powered configurations. The vehicle behavior is determined by dynamic model simulation, in which the Magic Formula is applied to define the tire slip, associated with the load transfer during curves or drive/break situations. The controller acts as an electronic differential and changes the in-wheel motor torques to correct the vehicle trajectory during a standard maneuver. A multi-objective optimization based on the genetic algorithm determines the FLC configuration. The vehicle parameters (EV and HEV) have been modified to analyze the optimized FLC and, in all cases, the control showed an improvement in behavior to the vehicle without control. Finally, the FLC was implemented in a simple microcontroller and a hardware-in-the-loop simulation was developed to simulate a real vehicle operating condition and analyze this performance.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] Stability Control for Vehicle Dynamic Management with Multi-Objective Fuzzy Continuous Damping Control
    Zhang, Xu
    Song, Chuanxue
    Song, Shixin
    Cao, Jingwei
    Peng, Silun
    Qi, Chunyang
    Xiao, Feng
    Wang, Da
    APPLIED SCIENCES-BASEL, 2020, 10 (21): : 1 - 22
  • [2] Robust Fuzzy Clustering as a Multi-Objective Optimization Procedure
    Banerjee, Amit
    2009 ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY, 2009, : 80 - 85
  • [3] Robust Fuzzy Control for Uncertain Nonlinear System based on Multi-objective Optimization
    Hao Wan-Jun
    Qiao Yan-Hui
    Zhu Xue-Li
    Wu Yong Zhi
    Li Ze
    PROCEEDINGS OF THE 2012 24TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2012, : 1297 - 1300
  • [4] Robust Routes for the Fuzzy Multi-objective Vehicle Routing Problem
    Bahri, Oumayma
    Ben Amer, Nahla
    Talbi, El-Ghazali
    IFAC PAPERSONLINE, 2016, 49 (12): : 769 - 774
  • [5] Multi-objective robust design of vehicle structure based on multi-objective particle swarm optimization
    Liu, Haichao
    Jin, Xiangjie
    Zhang, Fagui
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2020, 39 (06) : 9063 - 9071
  • [6] Robust Dynamic Multi-Objective Vehicle Routing Optimization Method
    Guo, Yi-Nan
    Cheng, Jian
    Luo, Sha
    Gong, Dunwei
    Xue, Yu
    IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2018, 15 (06) : 1891 - 1903
  • [7] Multi-objective topology optimization for the control arm of vehicle suspension
    Zhu, Xiaoyuan
    Fang, Zongde
    Shen, Shanshan
    Qi, Yuxuan
    Qiche Gongcheng/Automotive Engineering, 2011, 33 (02): : 138 - 141
  • [8] Multi-Objective Optimization of Active Vehicle Suspension System Control
    Jing, Dong
    Sun, Jian-Qiao
    Ren, Chuan-Bo
    Zhang, Xiu-hua
    NONLINEAR DYNAMICS AND CONTROL, VOL II: PROCEEDINGS OF THE FIRST INTERNATIONAL NONLINEAR DYNAMICS CONFERENCE (NODYCON 2019), 2020, : 137 - 145
  • [9] A Robust Volt/Var Control Via Multi-Objective Optimization
    Vitor, Tiago Soares
    Vieira, Jose Carlos M.
    2018 13TH IEEE INTERNATIONAL CONFERENCE ON INDUSTRY APPLICATIONS (INDUSCON), 2018, : 672 - 678
  • [10] Multi-objective Constrained Robust Variable Gain Control for Supercavitating Vehicle
    Han, Yuntao
    He, Yulin
    Guo, Hao
    PROCEEDINGS OF THE 39TH CHINESE CONTROL CONFERENCE, 2020, : 322 - 327