Optimization of Energy-absorbing Characteristics for Bio-inspired Thin-walled Structures Using an Improved PSO Method

This study focuses on optimizing the energy-absorbing characteristics of bio-inspired thin-walled structures (BTS) based on naturally inspired structural features. Three design parameters are investigated: wall thickness t, inner diameter d, and number of diaphragms n. A combined approach was employed: first, the Taguchi method with nine experiments was conducted to collect initial data; subsequently, an improved Particle Swarm Optimization (PSO) algorithm was applied to determine the influence of parameters on specific energy absorption (SEA) while simultaneously searching for the optimal parameter set. The results show that the influences of parameters t, d, and n on SEA are 66%, 32.5%, and 1.5%, respectively. The optimization process using the improved PSO algorithm ultimately identified an optimal parameter set of t=1 mm, d=40.87 mm, and n=8, yielding the best SEA value of 15 kJ/kg. Validation simulations in Abaqus resulted in an SEA of 15.19 kJ/kg (1.299% deviation), which is 15.2% higher than the non-optimized configuration. The improved PSO optimization algorithm is highly effective in simplifying and solving parameter optimization problems for new energy-absorbing structures. Notably, wall thickness t is the most dominant factor, and increasing t from 1 mm to 2 mm reduces SEA by 61.5% while increasing peak force by 78.2%. Compared with a conventional circular tube of equal mass, the optimized HICT improves SEA by 55%, confirming its potential for lightweight automotive applications.