Optimization Methodology for Innovative Automotive Crash Absorbers

Abstract

The simulation of vehicle crash impacts requires accurate and computationally expensive Finite Element analysis. An effective procedure consists in considering and establishing which improvement can be made on an equivalent sub-model of the full vehicle. In this way, all the analysis can be performed on smaller models, thus saving computational time. A full vehicle simulation is required only at the end of the design process to validate the results of the sub-model analysis. A software based on a genetic optimization algorithm has been developed in order to optimize the geometrical parameters of a variable-thickness crash absorber. A numerical study on the folding of thin-walled aluminum tubes with variable-thickness has been performed in order to achieve the maximum energy absorption-to-mass ratio. Moreover, the performance in terms of folding length and crush load peaks have been considered. Different optimization strategies have been implemented to find out which solution guarantees the achievement of the optimization target with the lowest computational cost. The results show how the approach proposed by the authors allows an efficient variable-thickness crash absorber to be obtained. In fact it performs better in term of crash behavior and energy dissipation-to-mass ratio, with respect to the original constant_thickness model.