Research and Experimental Verification of an Efficient Subframe Lightweighting Method Integrating SIMP Topology and Size Optimization

Under the context of the dual-carbon policy, reducing energy consumption and emissions in automobiles has garnered significant attention, with automotive lightweighting being particularly important. This paper focuses on the lightweight design of automotive subframes, aiming to minimize weight while meeting performance requirements. Research has revealed that the original subframe allows further room for lightweighting and performance optimization. A topology optimization model was established using the Solid Isotropic Material with Penalization (SIMP) method and solved using the Method of Moving Asymptotes (MMA) algorithm. Integration of the SIMP method was achieved on the Abaqus-Matlab (2022x) platform via Python (3.11.0) and Matlab (R2022a) coding, forming an effective optimization framework. The optimization results provided clear load transfer paths, offering a theoretical basis for geometric model conversion. The subframe model was subsequently reconstructed in CATIA. Material redundancy was identified in the reconstructed subframe model, prompting secondary optimization. Multi-objective size optimization was conducted in OptiStruct, reducing the subframe’s mass from 33.73 kg to 17.84 kg, achieving a 47.1% weight reduction. Static stiffness and modal analyses performed in HyperMesh confirmed that results met all relevant standards. Modal testing revealed a minimal deviation of only −2.7% from the simulation results, validating the feasibility and reliability of the optimized design. This research demonstrates that combining topology optimization with size optimization can significantly reduce weight and enhance subframe performance, providing valuable support for future automotive component design.