重庆理工大学学报2024，Vol.38Issue(7)：15-23,9.DOI:10.3969/j.issn.1674-8425(z).2024.04.003
改进高斯过程的客车侧风工况下气动造型优化研究
Aerodynamic modeling optimization of bus under crosswind condition based on improved Gaussian process
摘要
Abstract
The driving safety of high-speed buses is greatly affected by crosswind.To improve the aerodynamic characteristics and driving stability of high-speed buses, this paper proposes an improved Gaussian process regression model to optimize the buses' aerodynamic modeling.In this model, an automatic kernel construction algorithm is employed to automatically build the kernel function according to the data characteristics, and an adaptive genetic algorithm based on the gravitational acceleration mechanism is adopted to optimize the hyperparameters.It addresses the problem of low accuracy of the traditional approximate model.Our results show the predicted values of the improved Gaussian process regression model are all high in accuracy,with all in the 95％ confidence interval.In its applications, it reduces both the number of simulations and experiments with huge potential in engineering field.Finally,based on collaborative optimization, the aerodynamic shape of the bus is optimized with its aerodynamic lift coefficient down by 22.56％, its lateral force coefficient down by 18.53％, and its aerodynamic drag coefficient down by 4.51％.关键词
客车/稳态侧风/气动造型/高斯过程回归/遗传算法Key words
bus/steady state crosswind/aerodynamic shape/Gaussian process regression/Genetic algorithm分类
交通工程引用本文复制引用
王婷婷,姚铭宽,邵旭,秦东晨,陈江义..改进高斯过程的客车侧风工况下气动造型优化研究[J].重庆理工大学学报,2024,38(7):15-23,9.基金项目
国家自然科学基金项目(51705468) （51705468）
