Numerical Investigations of the DrivAer Car Model using
Opensource CFD Solver OpenFOAM
Gopal Shinde1, email@example.com, Aniruddha Joshi, firstname.lastname@example.org and Kishor Nikam,
A lot of the investigations in automotive aerodynamics are still based on strongly
simplified generic bodies such as the Ahmed Body or the SAE body. To close the
gap between these strongly simplified models and highly complex production cars
the new generic DrivAer body model is introduced by the Institute of Aerodynamics
and Fluid Mechanics, Technische Universitat Munchen (TUM). This current study is
focused on three different DrivAer body models namely Fastback, Estateback, and
Notchback and two different underbody types for each model, smooth and detailed.
Hence, total 6 different models are simulated using open source CFD solver
OpenFOAM at two different ground conditions, with ground and without ground effect
(WGS and WoGS). All the models used in simulations are 2.5 scaled down models
as compared with the actual car dimensions. The vehicle velocity considered for this
numerical study is 40 m/s, Reynolds number is 4.87M and turbulence model used is
k-w-SST. The mesh is generated using SnappyHexMesh (SHM) tool of OpenFOAM
and it is around 11 million volume cells for the smooth underbody and 14 million
volume cells for the detailed underbody. The coefficients of drag (Cd) values are
within 0.5% to 12% error band as compared against the experimental values
published by the TUM. The coefficients of pressure (Cp) plots are comparable with
experimental results and also the contribution of individual body part in overall Cd
values is obtained in this study. All the simulations are carried out using OpenFOAM
2.1.1 on Tata Consultancy Services (TCS) High Performance Computing facility.
Keywords : DrivAer body, External Aerodynamics, OpenFOAM, SnappyHexMesh,
CFD, HPC, TCS.
1Author for correspondence, Gopal Shinde, email@example.com, Tata
Consultancy Services, Pune, India
Nowadays with the help of Computational Fluid Dynamics (CFD) and High
Performance Computing (HPC) Technology, vehicle aerodynamics engineers are
reducing the wind tunnel experiments and accelerating the vehicle design cycle. A lot
of the investigations in automotive aerodynamics are still based on strongly
simplified generic bodies such as the Ahmed Body. In an experimental work, Ahmed
et al.  set a bluff body, called the Ahmed Model, in the Gottingen open section
wind tunnel and analysed the time averaged flow behaviour for different slant angle
variations. Gilli´eron et al.  performed computational simulation and compared
against the experimental ones for the reference Ahmed model. Lienhart et al. 
performed experiments for two slant angles, 250 and 350, with slightly lower velocity
40 m/s but of the same order, with Re = 2.8E06. Later, Kapadia et al. ,
Hinterberger et al. , Sinisa Krajnovic and Lars Davidson  and Ehab Fares 
also contributed to understand the Ahmed body flow physics better. Recently, Ronak
Pandya et al.  and Angelina Heft et al.  also contributed numerical observations
on Ahmed body.
These simple car models like Ahmed Body or SAE body make it easy to relate the
observed phenomena to specific areas and thus help to understand basic flow
structures. At the same time, more complex flow phenomena, e.g. at the underbody,
wheels/wheelhouses and around the rear view mirrors etc., cannot be reproduced
due to the over simplification of these geometries. On the other hand, it is usually not
feasible to investigate these phenomena on a specific production vehicle, as, due to
its short life span and restricted access, typically little validation data is available.
Recognizing the need for a model combining the strengths of both approaches,
various more or less generic models, such as the VW reference car and the MIRA
reference car, have been proposed . However, while these reference cars mark a
step in the right direction, these models are still too generic to completely understand
the complex phenomena occurring at realistic vehicles.
To close this gap, the Institute of Aerodynamics and Fluid Mechanics of the
Technische Universitat Munchen (TUM), in cooperation with two major car
companies, the Audi AG and the BMW Group, has proposed a new realistic generic
car model called “DrivAer Model” . The body is based on two typical medium
class vehicles (Audi A4 and BMW3 series) and includes three interchangeable tops
and two different underbody geometries to allow for a high universality. To
encourage the use of the DrivAer model in independent research projects, TUM
research group is open to share the geometry and a comprehensive experimental
database is published in different papers [12, 13].
The aim of the current work is to use different DrivAer body models and their
experimental results to validate the opensource CFD solver OpenFOAM.
This current study is focused on three different DrivAer body models namely
Fastback, Estateback, and Notchback and two different underbody types for each
model, smooth and detailed as shown in Figure 1. Hence, total 6 different models
are simulated using open source CFD solver OpenFOAM at two different ground
conditions, with ground and without ground effect (WGS and WoGS). In case of
WGS, car wheels are rotating anticlockwise and road is moving in the direction of air
and in case of WoGS both car wheels and road are stationary. All the models used
in simulations are 2.5 scaled down models as compared with the actual car
dimensions. Figure 2 show a sketch and main dimensions of the fastback
configuration of the 1:2.5 DrivAer model. Different parts of the Fastback model
considered for the simulation study are as shown in Figure 3. The individual drag
contribution of these components is also calculated along with the total car drag.
The vehicle velocity considered for this numerical study is 40 m/s, Reynolds number
is 4.87E106 and turbulence model used is k-w-SST.
Figure 1: DrivAer body models and different underbody types
Computational Domain and Mesh Generation
To capture the flow around the car model the computational domain is created
around the car which often called as numerical wind tunnel as shown in Figure 4.
This computational domain is like physical wind tunnel test section. The length of the
computational domain is 28 m, width is 10 m and height is 7 m. While the length of
Figure 2: Typical dimensions of the Fastback model
Figure 3: Different parts of the Fastback model
physical wind tunnel test section is 4.8 m, width is 2.4 m and height is 1.8 m. The
blockage ratio used in computational domain is 0.57% while in physical wind tunnel it
To capture flow physics around the car more accurately the mesh size kept near the
car is fine and becomes coarse when go away from the car as shown in Figure 5. To
achieve this variable mesh size distribution various refinement boxes are created
with different dimensions as shown in Figure 4. To capture the boundary layer
around the car, multiple layers of very fine and fine element sizes are kept around
full car and along the road which is shown in Figure 6. The y+ obtained is 30 which is
supposed to be good for incompressible simulations using OpenFoam.
SnappyHexMesh (SHM) tool was used in parallel mode for the grid generation. The
meshing was carried out on 4 cores of 32 GB workstation. The mesh generated on
smooth underbody models is about 11 million volume cells and 14 million volume
cells for the detailed underbody.
Figure 4: Different boxes of refinement around the Fastback model
Figure 5: Z-Cut plane of the grid around the Fastback model
Boundary Conditions and Solver Settings
Boundary conditions are implemented on the computational domain, car body, car
wheels and road. Velocity was specified at the inlet and pressure was specified at
outlet. Road was given translation speed 40 m/s in the direction of flow in simulations
with ground effect and considered stationary for without ground simulations. Car
wheels are rotating at 320 rad/s anticlockwise in simulations with ground effect and
considered stationery for without ground simulations. All other car parts are defined
as stationary walls.
“simpleFoam” solver from OpenFoam has been used for simulations.
“potentialFoam” solver is used to set pressure field in the domain. Post-processing
has been carried out using the in-built utilities sampleDict, streamlines, and
cuttingPlane. The models considered here are with wheels and mirrors and were
simulated for 10,000 iterations each. The convergence achieved was 5 decades fall
for flow variables P and U and 6 decades fall for turbulence quantities omega and k.
Convergence of drag force is also monitored and achieved upto 15 counts in last 100
Some of the solver’s important settings are given below.
Time stepping = Steady state
Gradient scheme = Second order
Divergence scheme = Upwind (First order)
Laplacian scheme = Linear (Second order)
Interpolation scheme = Linear (Second order)
Turbulence model = K-omega-SST
Pressure solver = GAMG
Figure 6: Zoomed view of the grid cut plane around the Fastback model
Velocity solver = GaussSiedel
Non-orthogonal correctors = 2
The total drag values obtained for the three models with smooth underbody
considering with and without ground effect are given in the Table 1. Table 2 shows
the drag values obtained for the three models with detailed underbody considering
with and without ground effect. Percentage error found out in the simulated drag
values is in the range of 0.5% to 12% as compared to the experimental drag values.
Simulated drag value is taken as the average of drag values of last 100 iterations.
The component wise drag plot for all configurations is as shown in Figures 7 and 8.
This plot shows the drag produced by each component, which gives us the important
insight where we should look for design changes in order to reduce the drag.
Reduction of drag directly contributes towards increase of fuel efficiency. These
component wise drag values are not readily available from experiments; however, it
is easily possible in simulations. Cp plots for the top surface of the models at y=0 are
plotted against the experimental Cp distribution as shown in Figure 9 and 10. We
have observed deviation in the simulated Cp distribution at the center of the model.
In experimental setup, at center of the model a vertical strut is mounted.
Table 1: Total drag values for Smooth Underbody models
Table 2: Total drag values for Detailed Underbody models
Figure 7: Component wise drag contribution plot for Smooth Underbody models
Figure 8: Component wise drag contribution plot for Detailed Underbody models
Figure 9: Coefficient of pressure (Cp) plot for Fastback model, WoGS
Figure 10: Coefficient of pressure (Cp) plot for Fastback model, WGS
This current study is focused on 3 different models of DrivAer body namely
FastBack, EstateBack, and NotchBack and 2 different underbodies, smooth and
detailed underbody. Hence, total 6 different configurations are simulated using open
source software OpenFOAM at two different conditions with ground and without
ground effect. The coefficients of drag (Cd) values are within 0.5% to 12% error band
as compared against the experimental values published by the TUM. The
coefficients of pressure (Cp) plots are comparable with experimental results and also
the contribution of individual body part in overall Cd values is obtained in this study.
There are huge flow separation / recirculation zones on the back-side of the models.
In order to capture the flow features more accurately, we need to refine the grid in
these zones. Since the flow features in these zones keep on changing with respect
to time, current steady state simulations may not mimic the exact flow situation.
Unsteady state flow simulations with region-wise refined grid and with more stringent
convergence criterions may give more insights.
In this current work, steady state simulations using k-w-SST turbulence model are
carried out. We would like to investigate this further for few more turbulence models
and also with transient calculations. Grid refinement may be necessary at the back
side of the models to capture the flow separation / recirculation zones more
accurately, which needs to be investigated.
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time averaged ground vehicle wake. SAE paper no. 840300.
2. P. Gilli´eron and F. Chometon, 1999. Modelling of stationary three-
separated air flows around an Ahmed reference model. In ESAIMproc.,
volume 7, pages 173-182.
3. H. Lienhart, C. Stoots, and S. Becker, 2000. Flow and turbulence structures in
the wake of a simplified car model (Ahmed Model). In DGLR Fach Symp. der
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reference Ahmed car model. AIAA paper no. 2003-0857
5. M. Hinterberger, M. Garcia-Villalba, and W. Rodi, 2004. Large Eddy
Simulation of flow around the Ahmed body. Lecture notes in Applied and
Computational Mechanics, The Aerodynamics of heavy vehicles: Trucks,
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Computational Study on the Drag Breakdown of Ahmed Body, IUTAM
Symposium on Bluff Body Flows, December 12-16, 2011, IIT Kanpur, India.
9. A. I. Heft, T. Indingery, and N. A. Adams, Investigation of Unsteady Flow
Structures in the Wake of a Realistic Generic Car Model, 29th AIAA Applied
Aerodynamics Conference, 27 - 30 June 2011, Honolulu, Hawaii
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Automotive Aerodynamics, SAE Technical Paper 2004-01-1308, 2004, doi:
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New Realistic Generic Car Model for Aerodynamic Investigations, SAE
12. Mack, S., Indinger, T., Adams, N. A., and Unterlechner, P., “The Ground-
Simulation Upgrade of the TUM Wind Tunnel,” SAE Technical Paper 2012-01-
0299, 2012, doi:10.4271/2012-01-0299.
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Experimental Investigation of Unsteady Vehicle Aerodynamics under Time
Dependent Flow Conditions - Part 2, SAE 2011 World Congress, April 12-14,
2011, Detroit, Michigan, USA, Paper 2011-01-0164
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around the Ahmed body using RANS and URANS with various turbulence
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The authors are thankful to Angelina I. Heft et al. (Institute of Aerodynamics and
Fluid Mechanics, Technische Universitat Munchen, Germany) for sharing the DrivAer
body CAD files and for valuable suggestions during this course of work. Authors
would like to thank the TCS-HPC team for their continuous support to carry out this
exercise. Authors also acknowledge the encouragement and support extended by
Mr. Rajaravisankar Shanmugam and EIS leadership team in pursuing this initiative.