摘要
为提高车门刚度并考虑轻量化的要求,提出以拼焊板车门下沉刚度和质量为优化目标,基于车门下沉刚度和窗框刚度两种工况,采用最优拉丁方试验设计方法进行样本数据设计,使用kriging模型拟合下沉刚度、窗框刚度、塑性变形量响应的近似模型,使用响应面模型拟合质量的近似模型.利用NSGA-II遗传算法进行寻优,得到车门质量和下沉刚度的pareto优化解集,并对优化解进行验证,最终得到理想的优化结果.
In order to improve the door stiffness and simultaneously achieve the lightweight goal , the sinking rigidity and mass of the tailed-weld bank door were proposed as optimization objectives based on the door sinking stiffness conditions and window frame stiffness conditions, sampling points were obtained by using optimal latin hypercube, and the approximated system, including the door sinking stiffness, window frame stiffness and plastic deformation, was constructed by kriging model while the mass was fitted by response surface model. Nondominated sorting genetic algorithm-II （NSGA-II） genetic algorithm was used for multi- objective optimization, a pareto optimal solution set is gained, to verify this optimization solution, and eventually get the ideal optimization results.
作者
高云凯
申振宇
冯兆玄
李应军
GAO Yunkai SHEN Zhenyu FENG Zhaoxuan LI Yingjun(School of Automotive Studies, Shanghai Key Lab of Vehicle Aerodynamics and Vehicle Thermal Management Systems, Tongji University, Shanghai 201804, China Commercial Vehicle Technical Center of SAICMOTOR, Shanghai 200438, China)
出处
《同济大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2017年第2期275-280,308,共7页
Journal of Tongji University:Natural Science
基金
国家自然科学基金(No:51575399)
关键词
车门刚度
轻量化
塑形变形
多目标优化
vehicle door stiffness
lightweight
plastic deformation
multi-objective optimization
