Multi-Objective Optimization of Structural Design for Lightweight Vehicle Chassis
Abstract
This study presents a systematic optimization of a lightweight vehicle chassis design using Design of Experiments (DoE), Finite Element Analysis (FEA), and Analysis of Variance (ANOVA) to enhance structural performance while balancing mass efficiency and safety factor. Material selection and wall thickness variations were considered to achieve a compromise between minimal mass and a safety factor of at least 1.5. Pareto front analysis, combined with the Taguchi method, identified the optimal solution, Cycle Design 11, which achieved a safety factor of 1.9489, representing an increase of 0.7681 compared to the baseline design. The total mass of 3.5742 kg reflects a 32.13% increase from the baseline. ANOVA results confirmed that both material and wall thickness significantly influence safety factor and mass, providing critical guidance for design decisions. This multi-objective optimization approach demonstrates that integrating FEA with experimental design enables superior chassis designs compared to traditional single-objective methods, offering a practical strategy for developing lightweight, safe, and energy-efficient vehicles.
Keywords
Design optimization; Lightweight chassis; Design of Experiments (DOE); Finite Element Analysis (FEA); Pareto optimal frontReferences
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