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Drag reduction simulation of generic vehicle model by adding vortex generators for battery electric car in India.

Authors :
Shrivastava, Ambar
Jaurker, Anandrao
Source :
AIP Conference Proceedings. 2023, Vol. 2821 Issue 1, p1-9. 9p.
Publication Year :
2023

Abstract

Vehicular exhaust emission is the most prominent cause of air pollution in India. Air pollution reduction to its minimum level is possible by switching from gasoline to electric vehicles. Since battery power consumption is a crucial aspect of a battery-electric car, lowering the aerodynamic drag force can decrease its consumption. In this study, a generic vehicle model named Ahmed body with a 35° rear slant angle was taken as a baseline model. FLUENT, a fluid flow component system of ANSYS, was used to simulate this baseline model at zero yawing angles via the k-epsilon turbulence model at velocities 20, 30, and 40 m/s. The result of the baseline model was validated from literature with a minimum difference of 0.35%. Drag reduction analysis was carried out to find the optimized model by placing an array of cylindrical vortex generators on top of the validated baseline model with diameters that varied in the range of 6mm to 12mm each at corresponding heights of 6mm to 18mm. The velocity contours and streamlines were studied to examine the wake region, and a maximum of 6.51% of drag reduction was found under investigation. Drag coefficient results of baseline and optimized model were applied to the real car under two road conditions. Flat road and 5% uphill were considered for calculating the percentage battery consumption reduction, and the best results were found as 3.97% and 2.25%, respectively. This drag reduction study in automobile engineering, especially for battery electric vehicles, can help reduce fossil fuel dependency. Thus, minimizing air pollution. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0094243X
Volume :
2821
Issue :
1
Database :
Academic Search Index
Journal :
AIP Conference Proceedings
Publication Type :
Conference
Accession number :
173743705
Full Text :
https://doi.org/10.1063/5.0164122