Aerodynamic modeling optimization of bus under crosswind condition based on improved Gaussian process
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％.
bussteady state crosswindaerodynamic shapeGaussian process regressionGenetic algorithm
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