中文摘要：

应用新近开发的基于混合元模型的优化方法（Hybrid and adaptive metamodeling method,HAM）,对某款车的后车架系统进行轻量化分析。在保证后车架系统刚度的前提下,为进一步减小系统的质量,提高结果的精度,提出局部搜索策略。局部搜索策略使用元模型在设计空间内部构造的较小子空间内搜索,应用局部搜索策略的子空间是以HAM方法得到的样本点为中心上下偏移一定距离构成的。HAM将三种各具特点的元模型-克里金（Kriging）、径向基函数（Radial basis function,RBF）和二次多项式响应面（Fuadratic function,QF）有机结合,根据不同问题,自动选择最适合的元模型进行寻优。三种元模型能够在搜索过程中自适应地更新、重建,逐渐提高关注区域的精度。在使用HAM方法优化结束后,应用此策略在HAM方法得到的样本点构造的子空间内继续搜索来进一步提高结果的精度,减小系统的质量。在对后车架系统的轻量化设计中,局部搜索策略的应用,使此系统的质量在满足刚度要求下比仅使用HAM方法多减小了2.18 kg。

英文摘要：

The newly developed hybrid and adaptive metamodeling method（HAM） is applied in lightweight design of one car rear frame.To reduce more weight of the system under the premise of the system stiffness,local search scheme is proposed,which is searched in a small subspace constructed by HAM sample point offsetting a small distance beside design space using the metamodels.HAM integrated three different metamodels which are Kriging,radial basis function（RBF） and uadratic function（QF） metamodel in optimization process.In addition,the appropriate metamodel can be selected automatically from the alternative metamodels in solving unknown problems.The employed three metamodels can be adaptively updated in the optimization process and the accuracy in the focused area will be gradually increased.When the optimization by HAM method is done,the local search scheme will be applied in the constructed subspaces for more mass reduction.Application of local search scheme makes the rear frame system reduce more by another 2.18 kg than that just by HAM method.