Crashworthiness design and multi-objective optimization of a novel auxetic hierarchical honeycomb crash box

This paper takes into consideration the excellent energy absorption ability of hierarchical honeycombs and auxetic structures and proposes a novel auxetic hierarchical crash box assembled by the auxetic hierarchical filling cores and the outer square thin-walled tube. The crushing performance of the auxetic hierarchical crash box is systematically investigated. The comparisons of energy absorption ability are made among the auxetic hierarchical crash box, aluminum foam-filled crash box, and the traditional crash box. In addition, a multi-objective optimization design is conducted based on the surrogate model with higher accuracy. The non-dominated sorting genetic algorithm (NSGA-II) and archive-based micro genetic algorithm (AMGA) are, respectively, employed to obtain the pareto sets. The results show that the optimum solution with AMGA has a smaller relative error, and the multi-objective optimization successfully improves the crushing performance of the auxetic hierarchical crash box. The electric vehicle crashworthiness is remarkably improved by the application of the auxetic hierarchical crash box. The conclusions of this paper can provide a new solution for the design of the crash box.

Automated summary

This paper introduces a novel auxetic hierarchical crash box and shows that multi-objective optimization can effectively improve its performance. The application of this crash box significantly enhances the crashworthiness of electric vehicles.