Research on Parameter Optimization of Tracked Vehicle Transmission System Based on Genetic Algorithm

被引:0
作者
Wei, Lingjun [1 ,2 ]
Liu, Haiou [1 ]
Chen, Huiyan [1 ]
Zhao, Ziye [1 ]
Xu, Yi [3 ]
Zhang, Hongyan [3 ]
机构
[1] Beijing Inst Technol, Sch Mech Engn, Beijing 10081, Peoples R China
[2] Beijing Vocat Coll Transportat, Beijing 102618, Peoples R China
[3] China North Vehicle Res Inst, Beijing 100072, Peoples R China
来源
CYBER SECURITY INTELLIGENCE AND ANALYTICS | 2020年 / 928卷
关键词
Genetic algorithm; Tracked vehicle; Drive system; Parameter optimization;
D O I
10.1007/978-3-030-15235-2_71
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The transmission system of tracked vehicle has great influence on the fuel economy and power performance of the whole vehicle. Its drivetrain parameter design is a multi parameter, multi-objective and nonlinear optimization problem, which is an important part of vehicle design. Based on the theoretical analysis of the optimization parameters and evaluation target, established the Smulink simulation model and normalization of tracked vehicle transmission system, according to the basic principle of genetic algorithm, computer simulation technology and optimization theory is applied to vehicle power transmission system parameter optimization design, the transmission ratio and the main reduction ratio as design variables, to guarantee the basis of fuel consumption as the target function to measure the tracked vehicle fuel economy, to the acceleration time and gradient optimization mathematical model of vehicle transmission system with a target shoe as constraint conditions. By comparing the optimization scheme and the original scheme, the traction characteristics and fuel economy are greatly improved. In the scheme, the objective function is greatly improved by improving the transmission ratio parameters of tracked vehicles, which proves that the optimization design method of tracked vehicles transmission system using genetic algorithm has been greatly improved.
引用
收藏
页码:487 / 495
页数:9
相关论文
共 18 条
  • [1] [Anonymous], 2010, J HEFEI U TECHNOL NA, V33, P341
  • [2] [Anonymous], 2015, J LIT LANGUAGE LINGU
  • [3] Experimental and numerical investigation of combined isotropic-kinematic hardening behavior of sheet metals
    Cao, Jian
    Lee, Wonoh
    Cheng, Hang Shawn
    Seniw, Mark
    Wang, Hui-Ping
    Chung, Kwansoo
    [J]. INTERNATIONAL JOURNAL OF PLASTICITY, 2009, 25 (05) : 942 - 972
  • [4] Chen Q. S., 2007, ADV ELECT VEHICLE TE
  • [5] A fast and elitist multiobjective genetic algorithm: NSGA-II
    Deb, K
    Pratap, A
    Agarwal, S
    Meyarivan, T
    [J]. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (02) : 182 - 197
  • [6] Li Z., 2020, MULTIOBJECTIVE OPTIM
  • [7] Mu Z, 2010, LOCOMOTIVE ROLLING S, V30, P19
  • [8] Qian L, 2005, J FARMING MECH, V36, P5
  • [9] Scott DW, 2015, WILEY SER PROBAB ST, P1, DOI 10.1002/9781118575574
  • [10] Sun J, 2005, PROENGINEERWILDFIRE