Abstract
In this paper, the improved EGO global optimization algorithm, based on the Kriging response surface and EI function, was used to complete the aerodynamic drag reduction in the design space of a vehicle combined with data mining technology. The EGO algorithm can usually achieve the global optimum with minimum function evaluations. Data mining technologies provide a method to uncover the influence mechanisms of design variables on aerodynamic drag and to analyze the relationship between variables. Aerodynamic drag of the optimal design is 1.56% lower than that of the original model. The data mining results show that the engine hood inclination and the tail angle play a leading role in the vehicle’s aerodynamic drag, and the hood inclination has the greatest impact. The method can efficiently solve the computationally expensive black box problems such as vehicle aerodynamic design optimization.
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