Multi-objective optimization design of automotive crashworthiness based on collaborative optimization method

Based on the combination of Latin hypercubic sampling method and response surface method (RSM), the acceleration indexes of three key positions were adopted as the subjects to investigate the automotive full frontal crashworthiness and their models were mathematically expressed. Then these three indexes were coordinated using collaborative optimization (CO). Optimization results show that all three performance indicators are improved in varying degrees and the frontal crashworthiness are increased. In addition, the results also show that the collaborative optimization method combined with approximate technology and finite element method is an effective method to solve multi-objective design optimization problem of the automotive crashworthiness, which can effectively avoid the difficulty in solving the issue of highly nonlinear problems by using traditional optimization method.