Lightweight design of multi-material body structure based on material selection method and implicit parametric modeling

Abstract

Multi-material automotive structures enable precise material selection in each structure, leading to enhanced product performance at a reduced cost and achieving lightweight design objectives. This paper introduces an innovative method for material selection in the context of designing multi-material lightweight automotive bodies. The proposed approach integrates topology optimization, Entropy Weight (EW), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to apply optimal materials in specific locations strategically. The investigation centers on the body of a compact electric vehicle, leveraging topology optimization to ascertain load transfer paths and material distribution within the structure. The EW-TOPSIS method introduces a comprehensive mechanical property ranking method for materials, organizing scoring criteria across various materials. By combining this information with element density via topology optimization, a matching criterion and a corresponding relationship between vehicle body performance and material characteristics are established. Subsequently, the SFE-CONCEPT software is employed to generate an implicit parametric model of the body structure based on material distribution characteristics. The steps of the vehicle body structure reliability optimization design involve establishing a multi-objective optimization model, defining and screening design variables, analyzing the approximate model and errors, and conducting reliability optimization based on a second-generation genetic algorithm. After optimization, the body structure is reconstructed, resulting in a 3.49% reduction in mass, a 38.8% increase in bending stiffness, a 6.47% increase in torsional stiffness, and significantly enhanced collision safety performance.