摘要
文章针对汽车结构的轻量化设计,在传统确定性多目标优化方法的基础上考虑了不确定性因素的影响,加入了可靠性设计以提高设计方案的可靠性。基于实验设计数据建立克里格近似模型,并用高效的多目标粒子群算法进行优化,得到确定性优化方案;考虑到制造工艺、环境等对设计变量的影响,引入6Sigma可靠性优化设计方法,对确定性优化方案进行可靠性优化并与优化前结果进行了对比。结果表明:经过可靠性优化的不确定性优化方案的6Sigma质量水平和可靠性能得到大幅提高,满足实际生产需求;优化后整车吸能提高了3.1kJ,零件质量和减小了3.8kg,降幅为7.45%,达到了优化目的。
Aiming at the lightweight design of automobile structure,based on the traditional deterministic multi-objective optimization method and considering the influence of uncertainty factors,the reliability design is added to improve the reliability of the design scheme.A Kriging approximation model is established based on the experimental design data,and an optimized multi-objective particle swarm optimization(PSO)algorithm is used to obtain the deterministic optimization scheme.Considering the influence of manufacturing process and environment on design variables,6 Sigma reliability optimization design method is introduced.The reliability optimization of the deterministic optimization scheme is carried out and the results before and after optimization are compared.It is shown that the6 Sigma quality and reliability can be greatly improved by the reliability optimization scheme,which can meet the requirements of actual production conditions.After optimization,the energy absorption of the whole vehicle increases by 3.1 kJ,the mass of optimized parts is reduced by 3.8 kg,achieving a decrease of 7.45%,so the optimization goals are met.
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