【摘要】 为提高汽车前纵梁结构的耐撞性和轻量化水平，文章对其进行多目标优化设计。基于动态落锤冲击试验，建立并验证了前纵梁有限元模型的准确性以及建模方法的可靠性。结合试验设计、粒子群优化（PSO）算法改进的支持向量机回归模型（SVR）和非支配排序遗传算法Ⅱ（NSGA-Ⅱ），以减轻前纵梁质量和增加其比吸能为优化目标，对前纵梁的结构进行确定性优化和可靠性优化。结果表明，优化后的前纵梁结构耐撞性和轻量化水平都有了提升，同时也保证了设计的可靠性。更多还原

【Abstract】 In order to improve the crashworthiness and lightweight level of automobile front rail structure, multi-objective optimization design is carried out in this paper. Based on the dynamic drop hammer impact test, the accuracy of the finite element model of the front rail and the reliability of the modeling method are established and verified. Combined with experimental design,particle swarm optimization(PSO) algorithm improved support vector regression(SVR) model and non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ), In order to reduce the weight of the front rail and increase its specific absorption energy, the deterministic optimization and reliability optimization of the front rail were carried out. The results show that the crashworthiness and lightweight level of the optimized front rail structure are improved, and the reliability of the design is also guaranteed.更多还原