The Simulation of Reduced Scale Automotive Mock-up Applied to Drag Reduction Solutions

Σ-Sigmatech R&I
Yoann EULALIE
Philippe GILOTTE
LES simulation of reduced scale
automotive mock-up applied to
drag reduction solutions
PARIS 01.10.2015
2015 – European Altair Technology Conference

AUTO EXTERIOR DIVISION All Right Reserved 2015 – EUROPEAN ALTAIR TECHNOLOGY CONFERENCEDate : 1st October Z015
LES simulation for automotive drag reduction
2
o Outlines
oContext : aerodynamic contribution for automotive CO2 reduction
oProblem definition : transient simulation and flow control target
oAnalysis : wake analysis on square back mockup
oDiscussion : interests on optimization technic
oValue of the work for the company : identification of flow control solution
oConclusion : toward full scale vehicle CFD analysis

A division of Plastic Omnium
2014 Sales:2014 Sales:2014 Sales:2014 Sales: €€€€ 5.35.35.35.3 BnBnBnBn
AUTOMOTIVEAUTOMOTIVEAUTOMOTIVEAUTOMOTIVE ENVIRONMENTENVIRONMENTENVIRONMENTENVIRONMENT
AUTO INERGYAUTO INERGYAUTO INERGYAUTO INERGYAUTO EXTERIORAUTO EXTERIORAUTO EXTERIORAUTO EXTERIOR
100%100%100%100%100%100%100%100%
Body panels and modules
Composite solutions
No.1No.1No.1No.1 WorldwideWorldwideWorldwideWorldwide
Waste equipment and data
management systems
ENVIRONMENTENVIRONMENTENVIRONMENTENVIRONMENT
100%100%100%100%
Plastic Fuel systems
and Emission reduction
related fluid systems
€€€€ 4.9m4.9m4.9m4.9m €€€€ .4m.4m.4m.4m
3
oPlastic Omnium Group

4
o Product lines Air duct
Front spoiler
active shutter
Top spoiler side
deflector

5
o Vehicle current design : vertical tailgate examples
143
114
94949494 89898989
Eco2 or blue motion versions
Target : SUV aerodynamic optimization
EU 2020 targetEU 2020 targetEU 2020 targetEU 2020 target
C0C0C0C02222emission[g/km]emission[g/km]emission[g/km]emission[g/km]

6
o Aerodynamic contribution on WLTP cycle
Mechanical energy lossMechanical energy lossMechanical energy lossMechanical energy loss
without frictionwithout frictionwithout frictionwithout friction
Aerodynamic contributionAerodynamic contributionAerodynamic contributionAerodynamic contributionLight weight contributionLight weight contributionLight weight contributionLight weight contribution
~50%~50%~50%~50%~50%~50%~50%~50%
10 kg of weight reduction :
1g/km C02
3 % of drag reduction :
1g /km C02
WLTP cycle time [s]
Vehiclespeed[m/s]
0
50
100
150
0 500 1000 1500 2000
vehicle speed

o Wake influence on SUV or Monospace :
o 60 % of the Cd drag due to the wake zone
o Research of flow control solutions for drag reduction
SUV >32°
α=45°
* Hucho et al. [1993]
Drag coefficient according to slant angle of the rear window *
Minivan 90°
7

o Wake flow analysis of Ahmed body :
o LES computation at reduced scale
o Test of flow control solution at 90° and 45°
Full detachmentSquare back
Ahmed et al. [1984]
8

o Wind tunnel and mock up characteristics :
Q=230L/min
U∞=30m.s-1
ReH= 412 000
9

o Time scale for flow control solution with periodic jet :
o Computation time step : ∆t=1,25.10-4s f=8000Hz
o Computational final time T=1,5s 12000 solved time steps
o 8 time steps for periodic jet description at 500 Hz (shear layer frequency)
o Minimum frequency = 4 Hz with a precision of 1 Hz for cross correlation
o Sampling output at 1000 Hz - Averaging on 1000 instantaneous field
Periodic actuation
θθθθ
Frequency [Hz]
Crossspectra[-]
20Hz
Shear layer
frequencies
H
H/2
H/2
10

o Meshing characteristics for LES simulation :
o Implicit resolved scheme : ∆t= 20.CFLmin
o 1 mm cell size in the wake - 120 millions cells
Smagorinsky model Δ ² 2
11

o Dissipative scale and cut-off frequency for LES simulation :
o Minimum vortex diameter 2 mm
o Dissipative scale = 1mm
o Dissipative frequency = 2500 Hz
kDI = 6500m-1
LDI = 0,96 mm
kEI = 0,14m-1
LEI = 43 mm
FDI = 2500 Hz
I
II
Time average Q criteria
Power spectral density of
velocity in shear layer
12

o LES computation with AcuSolve :
o Finite element solver with Galerkin Least Square method
o Variational formulation in Sobolev space
0 . . !
"
#Ω . % #Γ
'
( )*
. + ) ! #Ω
,-
./01
Minimum residual term computed on
each element, thanks to a least square
discontinuous Galerkin method
) ≡ 3 ∙ 5 ∙ 6 ∙ ) !⇒
With
Variational
Formulation
13

o LES computational result :
o Pulsed jet measurement done at PRISME Wind tunnel at Orleans
o Close Cd value between experiments and computations
o Square back pressure corresponds to 60% of the Cd
Drag comparison in [%]
measurement / computation
Square back Cp comparison
computation (top) and
experiment (bottom)
14

o Active flow control on a square back bluff body
o 9.1 % of Cd Gain on a Ahmed bluff body with synthetic jet
o Gain to be confirmed on a full scale vehicle
Vortex structures of jets
15
V∞
Iso contour of Q criteria colored
by longitudinal velocity
V∞
Controlled flow with synthetic jets
∆∆∆∆Cx = - 9,1%
Uncontrolled flow
V∞

o Active flow control on a square back 45° :
o 2% of gain with the same parameter
o Boundary layer and volume transition issue (periodic jet refinement)
16
Cp [-]
Uncontrolled Flow Controlled flow with periodic jet
∆Cx= - 2.5%

o Toward flow control optimization : model free control loop
o Test on a D shape of a extremum seeking algorithm (Pastoor*)
o Research of a jet velocity amplitude reduction (Cµ reduction)
Control law :
D shape geometry with
1,5 million of cell
Simulation time steps
have to be related to
control pulsation
17
*Pastoor et al. ‘’Feedback shear layer control for bluff body drag reduction’’, J. Fluid Mech. (2008), vol. 608, pp. 161–196.).

ou
o Toward flow control optimization : model based control loop
o System description
o Sensibility method
18

avec
et
o System description
o Adjoint equation
19

o Optimal problem
o Optimal system
20

o Example of Adjoint method coupled with a RANS or DES model solved with
OpenFoam : jet boundary conditions and shape optimization (C.Othmer*)
*Pictures from Carsten Othmer. “Adjoint methods for car aerodynamic”. Journal of Mathematics in Industry (2014).
21

o Toward flow control optimization on SUV vehicle shape :
o Development of optimal system coupled with LES AcuSolve solver
o Coupling with DOE for global minimum search
o First applications to perform on a reduced scale vehicle geometry
PSA 3008
VW Golf Van
BMW 2 Active Tourer
RSA Captur
PSA 308 (new)
VW Golf
Opel Astra
Picture from Carsten Othmer. “Adjoint methods
for car aerodynamic”. Journal of Mathematics
in Industry (2014).
Example of shape optimization
22

o Full scale vehicle LES simulation trial on square back bluff body
oFirst computation done on a full scale vehicle generic model
oLarge scale computed until 1600 Hz with mesh cells of 6 mm (mesh with 120 millions cells)
oTime-average ring pressure in the wake close to the Ahmed body computational results
oSpectral density and Cd value to be improved with finer mesh and smaller time step
23
Cp [-]
Reduced scale
Cp=0,26
Full scale generic model
Time-average Q criteria (use of API) with
Cp=0,26

o Full scale vehicle LES simulation
o Cell size in the wake of 1,5 mm at full scale leading to numerical model of 600 million cells
o Meshing and post-processing limitation for finite element simulation with AcuSolve ?
o Use of Lattice-Boltzmann method at full scaled for DOE ?
Reduced scale Full scale
24
Scaling
factor : x6
1mm
smallest cell
= dissipative limit scale
6mm
smallest cell
=4x(dissipative limit scale)
Full scale
Reduced scale

o Full scale LES computational result :
o At least 600 million cells
o 10 days of CPU with 46 processors, 500 Go of storage for reduced scale
o 30 days of CPU time and 3T of data storage at full scale ?
o Performance of HyperMesh and HyperView
o Routine to divide 1 tetrahedron in 8 to 13 smaller tetrahedrons
o Lattice Boltzmann simulation ?
2 elements on each edge + 1 at center
- 13 elements split
- Cell size divided by 2 (roughly)
Reduced scale
- 120 million cell mesh
- Min cell size in wake : ∆x = 1.0 mm
Full scale
- 1.5 billion cell mesh
- Min cell size in wake : ∆x = 3.0 mm
25
Scale factor x6

26
o Conclusions
o Validation of LES simulation on reduced scale square back mock up
o Identification of flow control solution to be confirmed on 47° slant angle mock up
o Introduction of optimization technic
o Limitation for full scale LES simulation to be solved

The Simulation of Reduced Scale Automotive Mock-up Applied to Drag Reduction Solutions

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