To read this content please select one of the options below:

Toward structure optimization for the mobile vehicle system based on multiconstraints

Xin Zhao (College of Engineering, South China Agricultural University, Guangzhou, China)
Jie Li (College of Engineering, South China Agricultural University, Guangzhou, China)
Shunli Sun (College of Engineering, South China Agricultural University, Guangzhou, China)
Chongyang Han (College of Engineering, South China Agricultural University, Guangzhou, China)
Wenbo Zhu (College of Engineering, South China Agricultural University, Guangzhou, China)
Zhaokai He (College of Engineering, South China Agricultural University, Guangzhou, China)
Luxin Tang (Guangdong Industrial Robot Integration and Application Engineering Technology Research Center, Guangzhou Institute of Science and Technology, Guangzhou, China)
Weibin Wu (College of Engineering, South China Agricultural University, Guangzhou, China)
Jiehao Li (College of Engineering, South China Agricultural University, Guangzhou, China)

Robotic Intelligence and Automation

ISSN: 2754-6969

Article publication date: 21 March 2023

Issue publication date: 28 March 2023

86

Abstract

Purpose

Vehicle lightweight design has positive implications for reducing energy consumption and abating greenhouse gas emissions. The traditional trailer axle design mainly focuses on the overall performance of the trailer axle. Only when the local performance does not meet the requirements will local performance optimization be done, such as local heat treatment to improve local strength. Such a design results in an uneven distribution of axle performance and excess performance in some local structures. The purpose of this study is to investigate the weight reduction on the premise of ensuring the structural dimensions of the outer surface of the axle remain unchanged and the reliability of the axle.

Design/methodology/approach

The axle is parameterized by computer aided design, and the optimized axle finite element model based on computer aided engineering is established and verified by taking the eight dimensions of the axle cavity structure which affect the performance as parameters. A genetic algorithm is used to optimize the axle cavity structure size and axle weight based on multiobjective optimization, and eight optimized size parameters of axle cavity structure are obtained.

Findings

The total weight of the optimized axle of TM1314 is reduced by 10.2 kg, and the weight reduction ratio reaches 10.7%. According to the optimized structural size of the axle, the specimen was trial-manufactured, and the bench tests of stiffness, strength and fatigue life were carried out according to the test requirements of the trailer axle standard (JT/T 475-2002). The test results show that the maximum deformation of the specimen is 2.46 mm, the strength safety factor of the specimen body and the steel plate spring seat are 6.71 and 6.86 and bear the alternating load more than 1.05 × 106 times, which meets the standard of the trailer axle and is better than the original design requirements of the trailer axle.

Originality/value

In this study, the multiobjective optimization model of the axle is established, the response surface is constructed by the Latin hypercube sampling design method and the optimal solution set is obtained by the multiobjective genetic algorithm. It has been verified by bench tests that it can achieve a weight reduction of 10.7% under the premise of the same structure and size of the outer surface of the axle. The lightweight method based on multiobjective optimization proposed in this paper can provide a reference for the lightweight design of other key vehicle components.

Keywords

Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grant 62203176, and the Key Technologies Research and Development Program of Guangdong Province under Grant 2020B090926004.

Citation

Zhao, X., Li, J., Sun, S., Han, C., Zhu, W., He, Z., Tang, L., Wu, W. and Li, J. (2023), "Toward structure optimization for the mobile vehicle system based on multiconstraints", Robotic Intelligence and Automation, Vol. 43 No. 1, pp. 75-84. https://doi.org/10.1108/RIA-08-2022-0213

Publisher

:

Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

Related articles