为了提升整车路噪、平顺性以及疲劳耐久综合性能,本文构造了序列近似多目标优化方法,结合虚拟试验场技术对轮胎参数进行了优化设计。采用径向基函数代理模型建立了CDTire轮胎模型关键物理参数与整车多学科性能VPG仿真输出响应的显式数学关系,基于多目标粒子群优化算法与自适应补点方法持续更新代理模型迭代求解逐步逼近真实Pareto前沿。通过设计变量分类建立2步法优化模型,求解匹配轮胎模型参数后,车辆关键测点的全频段噪声均方根、最大振动加速度均值及疲劳损伤均值分别降低了1.6%,10.4%及3.8%,优化效果显著。
Abstract
In order to improve the road noise, ride comfort and fatigue durability performance of vehicle, optimization design for tire parameters is studied in this paper by a sequential approximate multi-objective optimization method combined the Virtual Proving Ground technique. The radial basis function metamodel is used to establish the explicit mathematical relationship between the key physical parameters of CDTire model and the output responses of vehicle multidisciplinary performance from VPG simulation results. The optimization problem is iteratively solved by the adaptive sampling approach based multi-objective particle swarm optimization algorithm, the real Pareto frontier will thus be approached gradually.The two-step optimization model is established through the classification of design variables, which is thus solved to match tire model parameters. After optimization, the root mean square value of noise over full-frequency range, the mean value of maximum vibration acceleration and the mean value of fatigue damage from key measurement channel of the vehicle have been reduced by 1.6%, 10.4% and 3.8% respectively, demonstrating the significant optimization effect.
关键词
轮胎优化设计 /
路噪 /
平顺性 /
疲劳耐久 /
虚拟试验场
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Key words
tire optimization design /
road noise /
ride comfort /
fatigue durability /
Virtual Proving Ground
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参考文献
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