摘要
文中基于区间数规划法研究了汽车乘员约束系统的不确定优化问题。首先,利用MADYMO软件建立了乘员约束系统的仿真模型,并通过试验验证。接着确定以加权伤害准则为目标,安全带刚度、安全带上挂点位置和限力器的撕裂力与撕裂伸长等为设计变量,座椅和膝盖挡板的刚度为不确定量,并基于区间数规划法将不确定优化问题转化为确定性优化问题。通过拉丁超立方试验设计,建立目标函数和约束函数的近似模型,再利用序列二次规划算法和遗传算法分别作为内外层的求解器进行优化。最终,获得乘员约束系统参数的近似最优解。
The uncertainty optimization of vehicle occupant restraint system is studied in this paper based on interval number programming.Firstly a simulation model for occupant restraint system is set up using MADYMO software with the model verified by tests.Then,a weighted injury criterion is taken as objective,and the stiffness and upper anchor position of seat belt,as well as the tearing force and stretch length of force limiter etc are selected as design variables with the stiffnesses of seat and knee bolster as uncertain variables,and the uncertainty optimization is transformed into certainty optimization by using interval number programming.Next,the surrogate models for objective and constraint functions are built with Latin hypercube experiment design,and by utilizing sequential quadratic programming and genetic algorithms as the solvers for inner and outer layers respectively,an optimization is performed.Finally the approximately optimum solutions of the parameters of occupant restraint system are obtained.
出处
《汽车工程》
EI
CSCD
北大核心
2011年第1期6-10,共5页
Automotive Engineering
基金
囯家杰出青年科学基金(50625519)
教育部长江学者和创新团队发展计划
湖南大学汽车车身先进设计制造国家重点实验室自主研究课题(60870005)资助
关键词
乘员约束系统
拉丁超立方试验设计
近似模型
区间数规划
不确定优化
occupant restraint system
Latin hypercube experiment design
surrogate model
interval number programming
uncertainty optimization