Application of improved RSM in the optimization design of automotive frontal crashworthiness

To increase the frontal crashworthiness of automobiles, an improved response surface method (RSM) which has accurate convergence characteristics at the current design is presented, and the methodology is firstly used with optimal Latin hypercube sampling (LHS) to build the surrogate model of B-pillar acceleration peak value in full frontal crash. Many structure parameters are optimized using sequential quadratic program (SQP) based on the surrogate model. The results show that the improved RSM has high accuracy, and the acceleration peak value of B-pillar decreases nearly 18.2% after optimization. The research provides a facilitating approach for the optimization design of automotive frontal crashworthiness.