Title: Research on parameter optimisation of tracked vehicle transmission system based on genetic algorithm

Authors: Lingjun Wei; Haiou Liu; Huiyan Chen; Yi Xu; Ziye Zhao

Addresses: School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 10081, China ' School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 10081, China ' School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 10081, China ' China North Vehicle Research Institute, 4 Huaishuling, Changxindian, Fengtai District, Beijing 100072, China ' School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 10081, China

Abstract: Based on the theoretical analysis of optimisation parameters and evaluation objectives, this paper applies computer simulation technology and objective optimisation theory to the parameter optimisation design of tracked vehicle power transmission system by using the basic idea of genetic algorithm. The transmission ratio and main deceleration ratio of transmission are taken as design variables to ensure trafficability, and fuel consumption is taken as a measure of tracked vehicle. The objective function of fuel economy is to establish the mathematical model of target optimisation of tracked vehicle transmission system with acceleration time and climbing slope as constraints. Compared with the original scheme, the traction characteristics and fuel economy of the optimised scheme are greatly improved. It is proved that the genetic algorithm can greatly improve the optimal design method of transmission system.

Keywords: genetic algorithm; tracked vehicle; transmission system; parameter optimisation.

DOI: 10.1504/IJAL.2021.10034472

International Journal of Automation and Logistics, 2021 Vol.3 No.2, pp.169 - 178

Accepted: 04 Feb 2020
Published online: 14 Jan 2021 *

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