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Aerodynamic Analysis on under Body Drag and Vehicle Performance of Active Front Spoiler for High CG Vehicles
Technical Paper
2019-28-0025
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Vehicle aerodynamic drag reduction is the effective technique to enhance the fuel economy, performance and top speed of a vehicle. Out of the total drag, the underbody drag contributes about 40-50% by the parts like wheel arch, wheel housing, and the wheels. This further increases in the case of vehicles with higher CG. Thus, it seems logical to focus attention on the underbody aerodynamic drag reduction. In this study, an active spoiler is placed towards the front end of the vehicle which will divert the air flow from the front towards the radiator. The active spoiler revolves according to the signals received from the radar sensors placed at the lower end to detect obstacles which will prevent it from damage. The aim of the study is to examine the effect of the air flow diversion on underbody drag. The effect of air flow diversion on fuel consumption, radiator effectiveness and top speed is numerically evaluated. An SUV model is considered for the study as a base model designed in DS Solid works 2014 (pre-processor) and analyzed in STAR-CCM+ (post-processor). The different spoiler angle configurations have been analyzed to obtain the optimum spoiler angle and the performance is compared with the base model. The spoiler efficiency is obtained in terms of drag values from the STAR-CCM+. The results show that at 60o angle the spoiler is most effective in reducing overall aerodynamic drag by 9% from the base value. Furthermore, the obtained results show that for the 600 spoiler angle offers the vehicle top speed is increased by 3.28%, improved radiator effectiveness of 6.25% and 9.23% in the reduction of fuel consumption.
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Citation
Chaudhary, S., Krishnasamy, P., Kothari, R., and Rajamurugan, G., "Aerodynamic Analysis on under Body Drag and Vehicle Performance of Active Front Spoiler for High CG Vehicles," SAE Technical Paper 2019-28-0025, 2019, https://doi.org/10.4271/2019-28-0025.Data Sets - Support Documents
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References
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