Optimization design of carbon fiber reinforced polymer anti-collision beam crashworthiness by grey relational analysis with entropy method

To improve the vehicle lightweight and crashworthiness, a design strategy for the characteristics of carbon fiber reinforced polymer composite anti-collision beam structure was proposed based on grey relational analysis with the entropy weight method. A numerical simplified model considering the actual working condition of the whole vehicle was established. The mechanical properties of the material were determined by the mechanical properties test of carbon fiber reinforced plastics, which provides accurate material property for the carbon fiber bumper anti-collision beam model under collision conditions. The Hammersley experimental design method can generate 60 sample points to establish the relationship between design variables and responses based on the frontal collision simulation model. The entropy weight method was used to determine the weight of each response index, and the crashworthiness and lightweight of the composite anti-collision beam were optimized by the grey relational analysis method. The optimal size parameter combination of the anti-collision beam structure was obtained and the optimization scheme was determined. The results show that the optimal model peak energy absorption is increased by 11.4%, the peak force is reduced by 48%, and the mass is reduced by 56.5% compared with the initial model. The method achieves lightweight optimization design for the vehide under the premise that the safety index is satisfied.