汽车乘员约束系统多目标不确定性优化

摘要

With consideration of the influence of uncertain parameters of occupant restraint system on occu-pant safety, a multi-objective uncertainty optimization technique for occupant restraint system is proposed based on the combination of nonlinear interval number programming ( NINP ) and approximate model with locally-refined mesh. The numerical model for occupant restraint system is corrected according to the results of real vehicle frontal crash tests, and the uncertainty optimization problem is converted into a deterministic optimization problem by using interval order relations. Intergeneration projection genetic algorithm ( IP-GA) and micro multi-objective genetic algo-rithm (μMOGA) are adopted to seek for Pareto solution set meeting the protection performance requirements of oc-cupant restraint system. The results demonstrate that the proposed method can effectively obtain the optimal matching parameters of occupant restraint system with consideration of the effects of uncertainty and hence ensure the safety of vehicle occupants, having an extensive prospect of engineering application in the field of vehicle safety.%计及乘员约束系统不确定性参数对乘员安全性的影响,在非线性区间数规划(NINP)和局部加密近似模型相结合的基础上提出一种乘员约束系统多目标不确定性优化方法.根据实车前碰撞试验结果对乘员约束系统的数值模型进行校正,并利用区间序关系将乘员约束系统不确定性优化问题转换为确定性优化问题;采用隔代映射遗传算法(IP-GA)和微型多目标遗传算法(μMOGA)来求解满足乘员约束系统防护性能的非支配解集.结果表明:该方法能获得考虑不确定性影响的乘员约束系统最佳匹配参数,从而确保汽车乘员的安全性,在汽车安全领域具有广泛的工程应用前景.