This content is not included in your SAE MOBILUS subscription, or you are not logged in.
CFD drag analysis of autonomous vehicles in different arrays
ISSN: 0148-7191, e-ISSN: 2688-3627
Published September 03, 2018 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
Autonomous vehicles, which are defined as capable of sensing environment and navigating without any human input, are the top trend of the automobilist industry in terms of technology. The computers responsible for the control are able to set the vehicle to optimum operation point. With the advent of Computational Fluid Dynamics -CFD software, it is possible to study drag reduction proposals when the vehicles drive at the velocity, which contributes to increase fuel economy. In this context, based on a sedan virtual drag model, several simulations cases were developed considering different vehicle arrays and changing the distance between each one. The study aims to demonstrate, using virtual simulations, the potential drag coefficient reduction when vehicles are moving in a constant speed and which configuration leads to better performance increment. Taking the isolated vehicle as the baseline value, all the vehicles in the different arrays were analyzed. Results show that the vehicles staying behind the first vehicle in the arrays have better drag coefficient performance. Considering the presented results, it is possible to apply this methodology to others types of vehicles and optimize the driving of autonomous vehicles.
CitationBuscariolo, F., Magazoni, F., Volpe, L., Maruyama, F. et al., "CFD drag analysis of autonomous vehicles in different arrays," SAE Technical Paper 2018-36-0184, 2018, https://doi.org/10.4271/2018-36-0184.
Data Sets - Support Documents
|[Unnamed Dataset 1]|
|[Unnamed Dataset 2]|
- Buscariolo, F.F.; Karbon, K.J., “Comparative CFD Analysis Between Rotating and Static Cases of Different Wheels Opening Designs over a Performance Sedan”, SAE Paper, N° 2011-36-0271, Society of Automotive Engineers, 2011.
- Buscariolo, F.F.; Magazoni, F., Wolf, M., Maruyama F., Alves, J. C. L., Volpe, L. D., “Analysis of Turbulence Models Applied to CFD Drag Simulations of a Small Hatchback Vehicle”, SAE Paper, N° 2016-36-0201, Society of Automotive Engineers, 2016.
- Ferziger, P.; Peric, M., “Computational Methods for Fluid Dynamics”, Computational Methods for Fluid Dynamics, Springer-Verland, Germany 1999.
- FLUENT 15, “User's Guide”, Fluent Inc., 2013.
- Forrest, A., Konca, M., “Autonomous Cars and Soceity”, Worcester Polytechnic Institute, USA, 2007.
- Kelly, K. B.; Provencher, L. G.; Schenkel, F. K., The General Motors Engineering Staff Aerodynamics Laboratory – A full Scale Automotive Wind Tunnel, SAE Paper, N° 820371, Society of Automotive Engineers, 1982.
- Le Vine, S., Zolfaghari, A., Polak, J., “Autonomous cars: The tension between occupant experience and intersection capacity”, Transportation Research Part C 52 (2015) 1–14, Elsevier, 2015
- Maruyama, F., Alves, J. C. L., Volpe, L. D., Magazoni, F., Buscariolo, F. F., “Wheel Design Sensitive Analysis on Drag of Small Sedan Vehicle”, SAE Paper, N° 2015-36-0168, Society of Automotive Engineers, 2015.
- Pahle, J., Berger, D., Venti, M., Duggan, C., Faber, J., Cardinal, K., “An Initial Flight Investigation of Formation Flight for Drag Reduction on the C-17 Aircraft”, AIAA Paper N° AIAA 2012-4802, AIAA Atmospheric Flight Mechanics Conference, Minnesota, USA, 2012.
- Tennekes, H.; Lumley, J. L., ”A First Course in Turbulence”, MIT Press, Cambridge, MA, 1972.
- Torre, I., Íñiguez, J., ”Aerodynamics of a cycling team in a time trial: does the cyclist at the front benefit?”, EUROPEAN JOURNAL OF PHYSICS vol. 30, (1365-1369), IOP Publishing, 2009
- Trenchard, H., “Peloton phase oscillations”, Chaos, Solitons & Fractals vol. 56, (194-201), Elsevier, 2013.
- grabcad.com, https://grabcad.com/
- https://www.sae.org/standards/content/j3016_201401/ - Taxonomy and Definitions for Terms Related to On-Road Motor Vehicle Automated Driving Systems