Uncertain design optimization of automobile structures: A survey

Author:

Xu Xiang1,Huang Chuanqiang1,Li Chongchong1,Zhao Gang1,Li Xiaojie1,Ma Chao2

Affiliation:

1. School of Engineering, Anhui Agriculture University, Hefei 230036, China

2. School of Intelligent Manufacturing, Jiangsu Vocational Institute of Architectural Technology, Xuzhou 221116, China

Abstract

<abstract> <p>In real life, there are a lot of uncertainties in engineering structure design, and the potential uncertainties will have an important impact on the structural performance responses. Therefore, it is of great significance to consider the uncertainty in the initial stage of structural design to improve product performance. The consensus can be reached that the mechanical structure obtained by the reliability and robustness design optimization method considering uncertainty not only has low failure risk but also has highly stable performance. As a large mechanical system, the uncertainty design optimization of key vehicle structural performances is particularly important. This survey mainly discusses the current situation of the uncertain design optimization framework of automobile structures, and successively summarizes the uncertain design optimization of key automobile structures, uncertainty analysis methods, and multi-objective iterative optimization models. The uncertainty analysis method in the design optimization framework needs to consider the existing limited knowledge and limited test data. The importance of the interval model as a non-probabilistic model in the uncertainty analysis and optimization process is discussed. However, it should be noted that the interval model ignores the actual uncertainty distribution rule, which makes the design scheme still have some limitations. With the further improvement of design requirements, the efficiency, accuracy, and calculation cost of the entire design optimization framework of automobile structures need to be further improved iteratively. This survey will provide useful theoretical guidance for engineers and researchers in the automotive engineering field at the early stage of product development.</p> </abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

General Mathematics

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