Optimization of Vehicle Aerodynamic Drag Based on EGO
| Autor: | Bao Lv, Chengping Yan, Chenguang Lai, Yuting Zhou, Boqi Ren |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Optimal design
Computer science 02 engineering and technology Aerodynamics Function (mathematics) 01 natural sciences 010305 fluids & plasmas 020303 mechanical engineering & transports 0203 mechanical engineering Kriging Control theory Black box 0103 physical sciences Aerodynamic drag Reduction (mathematics) Global optimization |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783319709895 |
| DOI: | 10.1007/978-3-319-70990-1_56 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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