An adaptive multi-objective optimization method for structure-connection-performance design of commercial vehicle cab
A variable screening-approximate model-adaptive multi-optimization algorithm integrated method is proposed to solve the high-dimensional nonlinear problems for lightweight optimization of cabs. Firstly, a full-parametric body-in-white model of the cab is established using implicit parameterization technology, and the simulation analysis of the bending and torsional stiffness, natural modal characteristics, and passive safety are established. Then, considering the structure and connection process parameters, the design variables are screened based on a gray relational analysis-TOPSIS (GRA-TOPSIS). Finally, integrated multi-objective optimization of cab structure-connection-performance is carried out by an adaptive RBF neural network optimization method, and the optimal solution is determined by the GRA-TOPSIS method. Compared with the initial model, the mass of cab is reduced by 3.28% after optimization design. It provides guidance for the lightweight design of body.
Authors
- Chong Xie (ORCID: https://orcid.org/0009-0003-1000-3440)
- Yong Xiang (ORCID: https://orcid.org/0000-0003-3545-7863)
- Hongwei Zhang (ORCID: https://orcid.org/0000-0001-8394-3925)
- Feng Zhao (ORCID: https://orcid.org/0000-0001-6767-8105)
- Changqing Du
- Sijun Kong
Institutions
- Wuhan University of Technology (CN)
- Dongfeng Motor Group (China) (CN)
Publication Details
- Journal
- Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering
- Published
- 2024-09-20
- DOI
- https://doi.org/10.1177/09544070241273803
- Citations
- 5
- Primary Topic
- Mechanical Engineering and Vibrations Research
- Type
- article
- Field-Weighted Citation Impact
- 1.06
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China
- Fundamental Research Funds for the Central Universities