This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Aerodynamic Design and Analysis of a Formula SAE Drag Reduction System (DRS)
Technical Paper
2020-01-0685
ISSN: 0148-7191, e-ISSN: 2688-3627
This content contains downloadable datasets
Annotation ability available
Sector:
Language:
English
Abstract
Formula SAE vehicles, like many other vehicles within motorsport, often employ rear mounted aerodynamic devices to improve cornering performance, these devices can however have a significant amount of aerodynamic drag. Additional speed can be gained by reducing the impact of the rear wing on the straightaways of the track through the use the aptly named Drag Reduction System (DRS), which works by reducing the angle of attack of the rear wing flap(s).
A DRS can however introduce other performance losses, including the losses from having a gap between the rear wing flaps and endplate to prevent friction, the potential to stall the rear wing from improper opening angles of the flaps, and from the wake of the DRS actuator if positioned in front of the airfoils. An additional concern is the time it takes for the rear wing performance to return upon DRS deactivation, which will affect how long before corner entry the driver must disable the system.
Insight into each of these problems as well as the optimum opening angles was found through the use of CFD using Siemens’ STAR-CCM+ 2019.1. Simplified geometry came from UMSAE Polar Bear Racing’s car, PBR20, out of the University of Manitoba. All steady state simulations were done using RANS, while the DRS deactivation study was done using a novel method using Detached Eddy Simulation (DES), where dynamic overset meshes were used to model the transient motion of the flaps. As a result of the deactivation study, new insight was gained into the dynamic behaviour of drag reduction systems.
Authors
Topic
Citation
Penner, D., "Aerodynamic Design and Analysis of a Formula SAE Drag Reduction System (DRS)," SAE Technical Paper 2020-01-0685, 2020, https://doi.org/10.4271/2020-01-0685.Data Sets - Support Documents
Title | Description | Download |
---|---|---|
Unnamed Dataset 1 | ||
Unnamed Dataset 2 | ||
Unnamed Dataset 3 | ||
Unnamed Dataset 4 | ||
Unnamed Dataset 5 | ||
Unnamed Dataset 6 | ||
Unnamed Dataset 7 | ||
Unnamed Dataset 8 |
Also In
References
- Merkel , J.P. 54 60 2013
- Siemens PLM 2019
- Ashton , N. , West , A. , Lardeau , S. , and Revell , A. Assessment of RANS and DES Methods for Realistic Automotive Models Computers and Fluids 128 1 15 2016
- Addad , Y. , Gaitonde , U. , Laurence , D. , and Rolfo , S. Optimal Unstructured Meshing for Large Eddy Simulations Quality and Reliability of Large Eddy Simulations 93 103 2008