Enhanced crash performance of multi-cell crash box for electric vehicle battery pack design

Abstract

This paper is dedicated to enhancing the crash performance of a PA6 GF30 multicell crash box used for the crashworthiness and safety of the battery pack system used in electric vehicles. In this paper, a new hybrid optimization algorithm (HSFOA) combining the starfish optimization algorithm, dynamic oppositional-based learning, and a piecewise chaotic map is proposed, and a novel PA6 GF30 composite multicell crash box is developed to protect the electric vehicle battery pack. The performance of HSFOA is validated by applying it to piston rod design, car collision study, welded beam design, and truss structure optimization. After validation, the HSFOA is used to optimize a multicell energy absorber to evaluate its effectiveness in enhancing energy dissipation during collisions of electric vehicle battery pack. The developed crash box design, via finite element analysis and hybrid starfish optimization method, is manufactured by 3D printing and subjected to dynamic impact tests to validate crash performance. The results revealed that the developed design exhibited the highest crash performances, which are comparable to each other. Additionally, the PA6-Gf30 material for the developed multicell crash box, and HSFOA perform well in terms of efficiency, convergence, and stability in polymer-based electric vehicle battery pack design.