Crashworthiness optimization of crash box with 3D-printed lattice structures

Crash boxes are important energy-absorbing components to ensure the passive safety of automobile vehicles during crashworthiness. The current study presents an investigation of a novel crash box, which consists of Al shell and 3D-printed lattice core. In view of obtaining a good lightweight and energy absorption, the lattice structures are fabricated by fused filament fabrication (FFF) technology using carbon fiber reinforced polyamide 6 (PA6/CF) composites. First, the correlations between fiber content and elastic modulus, maximum tensile stress are established by a least squares method. Four different lattice structures including hexagonal, kagome, re-entrant and triangular honeycombs are additive-manufactured. The results reveal that the experimental data from compression test is in good agreement with the simulation analysis, and the kagome achieves the maximum specific energy absorption (SEA) values through numerical analysis. Then, an integrated "material-structure" model is constructed in an Isight environment to analyze the sensitivity of the material property (elastic modulus (E), tensile strength (Sigma) and fracture strain (epsilon)) and geometric parameters (thickness (t) and unit size (r) on the crashworthiness performance. A multi-objective optimization strategy with maximum SEA and minimum mass as objectives for the novel crash box is established using response surface model approach and optimal Latin hy-percube. Simulation results show that the crash box optimized by non-dominated sorting genetic algorithm (NSGA-II) algorithm can improve the energy absorption with mass reduction, which provides some reference for the structural design and optimization of the crash box.