基于响应面的白车身轻量化多目标优化设计
Multi-Objective Optimization Design of Body-in-White Lightweight Based on Response Surface
DOI: 10.12677/MOS.2023.124346, PDF,   
作者: 张 健, 吕俞祥, 李家俊, 刘会霞*:江苏大学机械工程学院,江苏 镇江;娄万里:上海埃立曼科技有限公司,上海
关键词: 白车身轻量化多目标优化GRSM响应面法Body-in-White Lightweight Multi-Objective Optimization GRSM Response Surface Method
摘要: 针对某车型的轻量化需求,本文结合灵敏度分析法和代理模型法实现白车身在扭转刚度和模态约束下的多目标优化。首先建立某车型白车身有限元模型,对模态、弯曲刚度、扭转刚度进行数值分析,掌握结构的基础性能。接着以车身板件厚度为设计变量,进行弯曲刚度、扭转刚度及模态频率的综合性能灵敏度分析。然后根据灵敏度分析结果,筛选出15个板件厚度作为变量,通过哈默斯雷采样法采样150个,并由此构建响应面模型。最后采用GRSM响应面优化法对白车身进行多目标优化,并获得Pareto最优解集。根据轻量化目的选取最优结果,结果显示:在刚度、模态等性能参数满足要求的同时,实现白车身减重3.7%,实现了轻量化目的。
Abstract: Aiming at the lightweight requirements of a certain model, this paper combines the sensitivity analysis method and the proxy model method to realize the multi-objective optimization of the body-in-white under torsional stiffness and modal constraints. Firstly, the finite element model of a certain model body-in-white is established, and the modal, bending stiffness and torsional stiffness are numerically analyzed to grasp the basic performance of the structure. Then, taking the thick-ness of the body panels as the design variable, the comprehensive performance sensitivity analysis of bending stiffness, torsional stiffness and modal frequency was carried out. Then, according to the sensitivity analysis results, 15 plate thicknesses were screened out as variables, and 150 were sampled by Hamersray sampling method, and the response surface model was constructed. Finally, the GRSM response surface optimization method is used to perform multi-objective optimization of the body-in-white, and the Pareto optimal solution set is obtained. According to the optimal results for the purpose of lightweighting, the results show that while the performance parameters such as stiffness and mode meet the requirements, the weight of the body-in-white is reduced by 3.7%, and the purpose of lightweight is achieved.
文章引用:张健, 吕俞祥, 李家俊, 娄万里, 刘会霞. 基于响应面的白车身轻量化多目标优化设计[J]. 建模与仿真, 2023, 12(4): 3781-3793. https://doi.org/10.12677/MOS.2023.124346

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