Multi-Response Optimisation of Automotive Door Using Grey Relational Analysis with Entropy Weights

被引:0
|
作者
Chen, Hao [1 ]
Lu, Chihua [1 ,2 ]
Liu, Zhien [1 ,2 ]
Shen, Cunrui [1 ]
Sun, Menglei [1 ]
机构
[1] Wuhan Univ Technol, Hubei Key Lab Adv Technol Automot Components, Wuhan 430070, Peoples R China
[2] Foshan Xianhu Lab Adv Energy Sci & Technol Guangd, Xianhu Hydrogen Valley 528200, Foshan, Peoples R China
基金
中国国家自然科学基金;
关键词
automotive door; lightweight; Taguchi; grey relational analysis; entropy method; multi-response optimisation; OPTIMAL-DESIGN;
D O I
10.3390/ma15155339
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Tail-welded blanks (TWBs) are widely used in automotive bodies to improve the structural performance and reduce weight. The stiffness and modal lightweight design optimisation of TWBs for automotive doors was performed in this study. The finite element model was validated through physical experiments. An L27 (3(12)) Taguchi orthogonal array was used to collect the sample points. The multi-objective optimisation problem was transformed into a single-objective optimisation problem based on the grey relational degree. The optimal combination of structural design parameters was obtained for a tail-welded door using the proposed method, and the weight of the door structure was reduced by 2.83 kg. The proposed optimisation method has fewer iterations and a lower computational cost, enabling the design of lightweight TWBs.
引用
收藏
页数:13
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