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

Lingjun Wei*, Haiou Liu, Huiyan Chen, Ziye Zhao, Yi Xu, Hongyan Zhang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationCyber Security Intelligence and Analytics
EditorsKim-Kwang Raymond Choo, Mohammad Hammoudeh, Reza Parizi, Zheng Xu, Ali Dehghantanha
PublisherSpringer Verlag
Pages487-495
Number of pages9
ISBN (Print)9783030152345
DOIs
Publication statusPublished - 2020
EventInternational Conference on Cyber Security Intelligence and Analytics, CSIA 2019 - Shenyang, China
Duration: 21 Feb 201922 Feb 2019

Publication series

NameAdvances in Intelligent Systems and Computing
Volume928
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

ConferenceInternational Conference on Cyber Security Intelligence and Analytics, CSIA 2019
Country/TerritoryChina
CityShenyang
Period21/02/1922/02/19

Keywords

  • Drive system
  • Genetic algorithm
  • Parameter optimization
  • Tracked vehicle

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