摘要
为提升乘员约束系统安全性能,本文中将近似模型参数优化技术应用于约束系统可靠性优化设计中。首先建立某车型驾驶员侧约束系统仿真模型,并基于实车碰撞试验结果对仿真模型进行验证,然后采用灰狼优化(GWO)算法优化克里金(KRG)模型的相关参数,得到高精度的GWO-KRG近似模型。最后,基于GWO-KRG近似模型和可靠性优化方法对约束系统进行优化设计。结果表明:GWO-KRG近似模型能提供更准确的预测响应值;经可靠性优化后的约束系统安全性能得到提高的同时可靠性也得到保证。
In order to enhance the safety performance of the occupant restraint system,the parameter optimization technology for surrogate model is applied to the reliability optimization design of the restraint system in this paper.Firstly,a simulation model for the driver-side restraint system of a vehicle is established and verified by real vehicle crash test.Then,the grey wolf optimization(GWO)algorithm is used to optimize the correlation parameters of Kriging(KRG)model,so a high-accuracy GWO-KRG surrogate model is obtained.Finally,based on GWOKRG surrogate model,a reliability optimization is conducted on the restraint system.The results show that GWOKRG surrogate model can provide more accurate predicted response,and after reliability optimization the safety performance of the restraint system is improved with its reliability also guaranteed.
作者
谷先广
高梦琳
王笑乐
黄岳竹
Gu Xianguang;Gao Menglin;Wang Xiaole;Huang Yuezhu(School of Automotive and Traffic Engineering,Hefei University of Technology,Hefei 230009;Intelligent Manufacturing Institute,Hefei University of Technology,Hefei 230009;Taihang Changqing Automobile Safety System(Suzhou)Co.,Ltd.,Suzhou 215100)
出处
《汽车工程》
EI
CSCD
北大核心
2021年第6期870-876,884,共8页
Automotive Engineering
基金
中国博士后科学基金(2018M640524)
中国博士后特别资助基金(2019T120460)资助。
关键词
乘员约束系统
灰狼优化
克里金近似模型
可靠性优化设计
occupant restraint system
grey wolf optimization
Kriging surrogate model
reliability optimization design
