Human-in-the-loop optimization for vehicle body lightweight design

• Published in: Advanced engineering informatics Vol. 62; p. 102887
• Main Authors: Hao, Jia, Deng, Ruofan, Jia, Liangyue, Li, Zuoxuan, Alizadeh, Reza, Soltanisehat, Leili, Liu, Bingyi, Sun, Zhibin, Shao, Yiping
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.10.2024
• Subjects: Human-in-the-loop; Interaction interface; Lightweight vehicle body; Optimization design; Interaction interface; Lightweight vehicle body; Optimization design; Human-in-the-loop
• ISSN: 1474-0346
• DOI: 10.1016/j.aei.2024.102887

Automatic optimization algorithms are crucial for vehicle body lightweight design; however, existing methods remain inefficient leading to excessive iterations that increase both time and costs. Current interactive optimization strategies partially mitigate this issue but lack a broad range of manipulation points and auxiliary information models. As such, we introduce a novel approach, “Human-in-the-Loop based method for Vehicle Body Lightweight Design” (HIL-VBLD). This method integrates human decision-making with optimization algorithms to reduce unproductive iterations. HIL-VBLD comprises two key components: (1) an innovative interaction mode that provides multiple manipulation points including constraint modification, algorithm switching, and selection of solutions of interest (SOI); (2) A comprehensive auxiliary information model that supports decision-making for designers. Our analysis demonstrates HIL-VBLD’s efficacy, showing a 54.5 % reduction in iteration cycles for genetic algorithm using SOI selection. Algorithm switching led to a 4.5 % mass reduction, mitigating local optimum pitfalls associated with gradient algorithms. Additionally, the auxiliary information model achieved a further 1.25 % mass reduction, enhancing optimization robustness. Compared to conventional automatic algorithm switching strategies, HIL-VBLD maintains equivalent accuracy with 23.9 % fewer iterations.