Aerodynamic drag reduction in a vehicle based on efficient global optimisation
| Autor: | Liangsheng Deng, Chenguang Lai, Chengping Yan, Qingyu Wang, Bo Hu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Optimal design
numerical analysis Computer science optimisation computational fluid dynamics numerical simulation technology 020209 energy Energy Engineering and Power Technology four-dimensional aerodynamic drag reduction design 02 engineering and technology computational fluid dynamics Computational fluid dynamics design engineering drag reduction Reduction (complexity) 0203 mechanical engineering statistical analysis Control theory Black box EGO algorithm low efficiency 0202 electrical engineering electronic engineering information engineering Aerodynamic drag vehicle drag reduction method design variables engine hood inclination minimum function evaluations search problems Computer simulation business.industry global optimisation algorithm vehicle dynamics General Engineering data mining technologies 020302 automobile design & engineering Aerodynamics data mining computationally expensive black box problem original vehicle tail upturn angle Drag lcsh:TA1-2040 vehicle aerodynamic shape optimisation business lcsh:Engineering (General). Civil engineering (General) aerodynamics global optimum Software global optimisation process |
| Zdroj: | The Journal of Engineering (2018) |
| DOI: | 10.1049/joe.2018.8954 |
| Popis: | Vehicle aerodynamic shape optimisation is a typical non-linear and computationally expensive black box problem, which is severely limited by time and cost of the objective function evaluations during the global optimisation process. To solve the shortcomings of low efficiency and high cost of the existing vehicle drag reduction method, an improved efficient global optimisation (EGO) algorithm is used to optimise a four-dimensional aerodynamic drag reduction design of a vehicle combined with computational fluid dynamics numerical simulation technology. Moreover, data mining technologies are used to reveal the influence mechanisms of design variables on aerodynamic drag and to analyse the relationship between the variables. It is demonstrated that the improved EGO algorithm, based on the kriging response surface and expected improvement function, can achieve the global optimum with minimum function evaluations. The aerodynamic drag of the optimal design is 1.56% lower than that of the original vehicle. The data mining results showed that the engine hood inclination and the tail upturn angle play a leading role in the vehicle's aerodynamic drag, and the hood inclination has the greatest impact. |
| Databáze: | OpenAIRE |
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