Structure design and multi-objective optimization of a novel crash box based on biomimetic structure

Abstract

In order to improve the crashworthiness and energy absorption performance, this paper introduces the structural bionics to the structural design of crash box and proposes a novel structure. Taking the human tibia as a bionic object, the novel crash box is composed of a concave structure shell and an inner core filled with negative Poisson's ratio (NPR) structure material. In view of the gradient characteristics of the cancellous bone structure of the tibia, the NPR inner core is designed as a functional gradient distribution structure along the longitudinal direction of the crash box. Based on this, by combining the optimal Latin hypercube design and response surface methodology, a multi-objective optimization design is conducted for the novel crash box based on archive-based micro genetic algorithm (AMGA) and improved non-dominated sorting genetic algorithm (NSGA-II). Simulation results show that the novel crash box optimized by NSGA-II algorithm can improve the energy absorption characteristics and comprehensive crashworthiness more effectively, and make the collision process controllable and stable. The results of this paper can provide some reference for the design and optimization of the crash box.