The automotive industry is increasingly focused on developing lightweight, fuel-efficient, and structurally robust components to meet stringent performance and sustainability requirements. Additively manufactured lattice structures have emerged as a promising solution due to their high strength-to-weight ratio, energy absorption capability, and geometric flexibility; however, achieving an optimal balance among competing objectives such as mass reduction, mechanical stiffness, strength, and manufacturability remains a significant challenge. This study proposes a multi-objective topology optimization framework for the design of 3D-printed lattice-based automotive components. The framework integrates density-based topology optimization with lattice parameterization and a multi-objective evolutionary optimization algorithm to simultaneously minimize structural mass and maximize mechanical performance under realistic automotive loading conditions. Finite element analysis is employed to evaluate stress distribution, displacement, and compliance, while additive manufacturing constraints—including minimum feature size and printability—are explicitly embedded within the optimization process to ensure fabrication feasibility. The resulting lattice-optimized configurations are assessed through extensive numerical simulations and comparative performance analysis. Simulation results demonstrate that the proposed approach achieves an average weight reduction of approximately 35% while maintaining or improving structural stiffness and strength compared to conventional solid and uniform lattice designs. The generated Pareto-optimal solutions provide designers with flexibility to select optimal trade-offs tailored to specific automotive applications. Overall, the proposed framework significantly outperforms traditional single-objective optimization approaches in terms of material efficiency and mechanical performance. This research presents a scalable and manufacturable design methodology that bridges the gap between theoretical topology optimization and industrially viable lightweight automotive components, supporting the broader adoption of additive manufacturing in sustainable vehicle design.
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