Automobile aerodynamic drag reduction based on the bionic dorsal fin

Airflow separation at the rear area of the automobile is the main source of automobile aerodynamic drag. To suppress the airflow separation, minimize the aerodynamic drag of the automobile, realize energy saving and emission reduction, a bionic drag reduction device was designed based on the dorsal...

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Bibliographic Details
Published in:Physics of Fluids
Main Authors: Zhao, Jian, Su, Chuqi, Liu, Xun, Yuan, Xiaohong, Li, Wenjie, Wang, Yiping
Other Authors: Hubei Province Supports Enterprise Technology Innovation and Development Project, Major Science and Technology Project of Hubei Province
Format: Article in Journal/Newspaper
Language:English
Published: AIP Publishing 2024
Subjects:
Online Access:http://dx.doi.org/10.1063/5.0223511
https://pubs.aip.org/aip/pof/article-pdf/doi/10.1063/5.0223511/20148374/095116_1_5.0223511.pdf
Description
Summary:Airflow separation at the rear area of the automobile is the main source of automobile aerodynamic drag. To suppress the airflow separation, minimize the aerodynamic drag of the automobile, realize energy saving and emission reduction, a bionic drag reduction device was designed based on the dorsal fin of the orca with low drag characteristics. A numerical computation method was established to maximize the drag reduction performance of the bionic device, and the parametric modeling of the bionic drag reduction device was carried out. The design of experiments, the Kriging surrogate model, and an optimization algorithm were used to optimize the bionic drag reduction device. The validity of the optimization design was validated by the wind tunnel test. Finally, the mechanism and effectiveness of the bionic device in reducing aerodynamic drag were investigated through the comparison of flow field. The results show that the optimized bionic drag reduction device can delay the airflow separation and effectively reduce turbulence intensity of the automobile. According to the wind tunnel test, the aerodynamic drag coefficient of the optimized model is reduced by 6.16% compared with the original model.