Abstract
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.
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Acknowledgements
The project is supported by the National Natural Science Foundation of China (Grant No. U20A20285 and Grant No. 11772123), the National Key Research and Development Program (Grant No. 2020YFA0710904), the Key research and technology plan of Hunan Province (Grant No. 2020GK2094), the National Natural Science Foundation of China (Grant No. 52005054), and the Open Fund of State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body (Grant No. 32015012).
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The detailed information of the modeling method and the software employed in this paper can be found in the corresponding sections, and the optimization algorithm presented in this work is the reproduction of an already published and developed method. The necessary data of modeled structures and the corresponding coefficient of the method applied can be found in the corresponding text and tables of this paper.
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Tan, H., He, Z., Li, E. et al. Crashworthiness design and multi-objective optimization of a novel auxetic hierarchical honeycomb crash box. Struct Multidisc Optim 64, 2009–2024 (2021). https://doi.org/10.1007/s00158-021-02961-9
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DOI: https://doi.org/10.1007/s00158-021-02961-9