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.

考虑到分层蜂窝结构和拉胀结构优异的吸能能力，提出了一种由拉胀分层填充芯和外方形薄壁管组装而成的新型拉胀分层碰撞盒。系统地研究了拉胀分级碰撞盒的破碎性能。对拉胀分级碰撞盒、泡沫铝填充碰撞盒和传统碰撞盒的吸能能力进行了比较。此外，基于具有更高精度的代理模型进行多目标优化设计。分别采用非支配排序遗传算法（NSGA-II）和基于档案的微遗传算法（AMGA）来获得帕累托集。结果表明，采用AMGA的最优解具有较小的相对误差，多目标优化成功提高了拉胀分级碰撞箱的破碎性能。拉胀分级碰撞盒的应用显着提高了电动汽车的耐撞性。本文的结论可为碰撞盒的设计提供新的解决方案。