Multi-objective optimization design of rear seat for a passenger car based on GARS and NSGA-III

Xuan Zhou, Hengliang Jiang, J. Long
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Abstract

A collaborative multi-objective optimization design is conducted for the rear seat of a passenger car. This study introduces a combined optimization strategy that integrates both the multi-objective optimization problem and multi-criteria decision-making approaches. Firstly, a finite element model of the rear seat luggage compartment crash is established, and its accuracy is validated. Secondly, the thickness and material type of the primary stress components of the backrest framework for the rear seat are considered as design variables. The safety test point displacement, material cost, and weight are defined as the optimization objectives, while regulatory standards are taken as constraints to construct a multi-objective optimization problem. Once more, the Pareto frontier solution sets are achieved by constructing the genetic aggregation response surface surrogate model combined with the non-dominated sorting genetic algorithm-III optimization algorithm through experimental design. Finally, the Pareto frontier solution sets are ranked to determine the best compromise solution using the multi-criteria decision-making method, which involves the optimal combination weight and the technique for order preference by similarity to an ideal solution based on the Kullback-Leibler distance. The safety performance, lightweight, and cost-effectiveness of the optimized rear car seat are improved. Specifically, the displacement of the headrest skeleton and backrest skeleton is reduced by 5.96% and 4.47% respectively, the material cost is decreased by 7.1%, and the weight is reduced by 5.54%.
基于 GARS 和 NSGA-III 的乘用车后排座椅多目标优化设计
针对乘用车后排座椅进行了多目标协同优化设计。该研究引入了一种综合优化策略,将多目标优化问题和多标准决策方法融为一体。首先,建立了后座行李箱碰撞的有限元模型,并验证了其准确性。其次,将后座靠背框架主要受力部件的厚度和材料类型作为设计变量。以安全测试点位移、材料成本和重量为优化目标,以法规标准为约束条件,构建多目标优化问题。再次,通过试验设计,构建遗传聚集响应面代用模型,结合非支配排序遗传算法-III 优化算法,实现帕累托前沿解集。最后,利用多标准决策法对帕累托前沿解集进行排序,以确定最佳折中方案。多标准决策法包括最优组合权重和基于库尔贝克-莱伯勒距离的理想方案相似度排序偏好技术。优化后的后排汽车座椅在安全性能、轻量化和成本效益方面都得到了改善。具体而言,头枕骨架和靠背骨架的位移分别减少了 5.96% 和 4.47%,材料成本降低了 7.1%,重量减轻了 5.54%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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