Multi-objective optimization of an automobile seat frame based on collision condition and gray fuzzy decision

Abstract

This study established 50% dummy front collision (FC) and 50% dummy rear collision (RC) simulation analysis working conditions to address the optimization problem of automobile seat skeletons, improve the overall performance of automobile seat skeleton structures, and avoid the problems of instability of multi-criteria decision results, non-uniform results of different multi-criteria methods. The gray relation analysis and fuzzy logic system were used to optimize the design of the automobile seat under FC and RC conditions, and the fuzzy logic decision system was adopted to make decisions on the optimal design solutions for the sample points under FC and RC conditions. Then, the two design solutions were rationally recombined to form the final optimal design solution. The final optimized design scheme reduced the quality by 19.2% and the cost by 25.7%. Afterward, this study compared the fuzzy decision method with TOPSIS decision methods and proved that the proposed fuzzy decision-making method is simple, efficient, convenient, and fast.