Preference-based topology optimization for vehicle concept design with concurrent static and crash load cases

Abstract

In the simulation-based design process of automotive structures, an increasing amount of multi-disciplinary requirements have to be considered. Methods of topology optimization can be used to devise structural concepts early in the design process to obtain the best possible structural layout as starting point for further development steps. Especially relevant for the vehicle design process is the concurrent consideration of static load requirements representing normal operating conditions and energy absorption requirements targeting passive safety in crash events. When the disciplines are considered separately, the heuristic Hybrid Cellular Automaton topology optimization is a suitable method. However, in practical applications, both disciplines are usually addressed sequentially. This complicates the overall process and may reduce the quality of the final optimization result, since optimization objectives may be conflicting. We propose a preference-based Scaled Energy Weighting approach to address the topology optimization of both disciplines concurrently. The main idea is to decouple the user preference from the scaling of the different magnitudes of energies. This enables a multi-objective optimization and ultimately the selection of the desired trade-off solution. We first validate the capability of the method to provide structures optimized for stiffness and energy absorption objectives on beam examples. Finally, the method is applied to optimize a concept structure of an industrial vehicle body, demonstrating its practical feasibility.