cfd analysis of aerodynamic design of tata indica car · analysis of car models has in reducing the...

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International Journal of Mechanical Engineering and Technology (IJMET) Volume 8, Issue 3, March 2017, pp. 344–355 Article ID: IJMET_08_03_038

Available online at http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=8&IType=3

ISSN Print: 0976-6340 and ISSN Online: 0976-6359

© IAEME Publication Scopus Indexed

CFD ANALYSIS OF AERODYNAMIC DESIGN

OF TATA INDICA CAR

Abdul Razzaque Ansari

Department of Mechanical Engineering,

Cambridge Institute of Technology, Ranchi-835103, India

ABSTRACT

Now a day the choice of car by the customer depends on the basis of fuel efficiency,

mileage, cost and comfortable. Fuel efficiency is the most important factor that is

responsible for the overall popularity of car. The fuel efficiency is depends upon the

performance of internal combustion engine and also on the aerodynamic design body

of the car. Aerodynamic styling of car is one of the most crucial aspects of the car

design. The shape of frontal area of the car is main factor of Drag reduction and

essential for reducing the fuel consumption. Designing a vehicle with a minimized drag

resistance provides economical and performance of many advantages. The drag force

is produced by relative motion between air and vehicle Aerodynamic. Analysis of car

models has in reducing the drag force acting on the cars body. The design of Tata Indica

car has been done on Pro-e 5.0 and the same is used for analysis in Ansys-(fluent). The

main intention behind this project is to reduce the drag co-efficient & drag force of car

body by improving the aerodynamic shape by using CFD software. The analysis is done

for finding drag co efficient and drag force. The aerodynamic analysis of the design

parameter of car will be performed by using a suitable turbulence model and to compare

the drag coefficient of design of car model by using CFD software result and

experimentally result and the results will be validated by CFD analysis/experimental

studies. The result of software analysis has agreed excellently with field experimentally

results.

Key words: CAD, CFD, Pro-E, Ansys, Drag coefficient, Drag Force, Aerodynamic.

Cite this Article: Abdul Razzaque Ansari, CFD Analysis of Aerodynamic Design of

Tata Indica Car, International Journal of Mechanical Engineering and Technology,

8(3), 2017, pp.344–355.

http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=8&IType=3

1. INTRODUCTION

All The choice of car is often mode on the basis of fuel efficiency cost & comfort. However for

general purpose fuel efficiency is the most important factor that is responsible for the overall

popularity of a car of any make fuel efficiency is depend upon the performance of internal

combustion engine & also on the aerodynamic design body of the car. [1][2]



Aerodynamically design car may offer better stability at high speed air while moving past

car exist two different Aerodynamic stylish of a car is one of the most crucial accept of car

design. It includes task of integration of advanced engineering and computer analysis.

Aerodynamically design car required least power in overcoming drag exerted by air and

exhibits higher performance with fuel consumption. [3][4]

1.1. Force on the Car Surface

1. Tangential force induced by share stress due to viscosity and velocity gradient at boundary

surface.

2. The forces normal to the car surface resulting from pressure intensity varying along the surface

due to dynamic effect.sum of the two forces over complete surface is know is resulting

force.[5][6]

Component of these force in the direction of relative velocity past car body is define as

aerodynamic drag. Aerodynamic is crucial factor in judging the performance of car. It highly

influences fuel consumption of car at high speed. Streamlined aerodynamically design of car

may have cd value from (.3) to (.5) drag in the surface vehicle aerodynamic is a major of

aerodynamic force where resist the forward motion of vehicle. Implied that vehicle body can

moved easily through the surrounding air with minimum air resistance. Where as negative lift

co efficient indicates more stability and less charge of skidding.[7][8][9]

Aerodynamically design car may offer better stability at high speed air while moving past

car exist two different Aerodynamic stylish of a car is one of the most crucial accept of car

design. It includes task of integration of advanced engineering and computer analysis.

Aerodynamically design car required least power in overcoming drag exerted by air and

exhibits higher performance with fuel consumption. [14][15]

1.2. Aerodynamics Forces and Moments

Among the most important results obtained from wind tunnel experiments supporting design

programs are the aerodynamic forces and moment ts acting on the test vehicle in a controlled

and repeatable environment. Force and moment measurements are important for all ground

vehicles. for some the principal interest is on drag because of its reflection on energy

requirements. for others such as performance cars racing cars and motorcycles, the moments

,lift, and side force are at least as important as drag because of their impact on controllability

and safety.[16][13]

The drag and lift forces generated on a high-speed train, for instance, are fundamental in

determining its safety, the maximum cruise speed, and all the consequent issues(e.g.,the time

of travel and the fuel efficiency)that eventually affect ticket prices. in the case of motorcycles

the moments and forces generated in straight-line motion and upon exposure to side winds have

a dominant effect on the performance of the vehicle and the safety of the rider. Drag is often

that receives the greatest attention as it has a dominant effect on fuel consumption at a given

speed and on the top speed attainable. [10][11][12]

The lift forces is of extreme importance in determining controllability for performance cars

and race cars, becoming more critical as the speed increases .lift is often considered in terms of

front lift and real lift. This is equivalent to considering total lift and pitching moment.[17] Other

aerodynamic force and moment components also play major roles in the controllability of

ground vehicles at high speeds. Side force, yawing moment, and rolling moment under side-

wind conditioned or due to passing of another vehicle are important determinants of the safety

and comfort of a passenger vehicle or the capability of a race car in competition.[20][18][19]

CFD Analysis of Aerodynamic Design of Tata Indica Car


1.3. Objectives

• To make a 3-D car model of Tata Indica car

• Analysis of 3-D car model to find the aerodynamic design parameters from Computational fluid

dynamics (CFD)

• validated by field/experimental studies

2. DETAILS OF EXPERIMENTAL STUDIES

The suitable testing spot was selected near the Ring road of Central Institute of Psychiatry in

the capital Ranchi of Jharkhand. In the experimental study determine of drag coefficient Cd,

drag force Fd, distance, time and velocity, it was required to arrange the cars of Tata Indica. and

to determine the distance travelled by the car where car is running when the engine is stopped

without the application of the applied brake and also the precaution of any road unwanted

gradients such as pits, cracks, stones, bumpers etc were taken into account which means for the

successful completion of the testing the road must be smooth and neat. Atmospheric

temperature was recorded with the help of Phycho meter as D.B.T- 26 degree Celsius and

W.B.T. as 21 degree Celsius and the wind flow was almost negligible. The road test began with

three people sitting inside the car. The precaution of window pan to be closed for each test was

taken so that the air effect does not enter inside the vehicle through these window pans. The

distance completely travelled by the vehicles at the speed of 20, 30, 40, 50, 60, 70 and 80 km/hr

after the engine is stopped for vehicle was determined with the help of distance measurement

reader available in the vehicle near the speedometer. For the uniform distance travelled at 20,

30, 40, 50, 60, 70 and 80 km/hr it was required to first allow the vehicle travel uniformly at 30,

40, 50, 60, 70, 80 and 90 km/hr and the accelerator pedal was released. As the speed

comes down to the required speed then the vehicle was allowed at least to travel constantly at

that speed for minimum 7 seconds. The road test of the vehicle took place in the N-S direction.

After the completion of the test the weight of the three cars was successfully taken as, Tata

Indica – 1140 kg

Figure 1 Tata Indica Car



2. EXPERIMENTAL STUDY

2.1. Estimation of Drag Coefficient and Drag Force on the Base of Field Study

X= distance travelled after switching off the engine

m=mass of vehicle in kg.

v=velocity at which the engine was switched off

(In m/s)

Cd=coefficient of drag

p=density of air

A= projected area

The force F opposes the motion of the vehicle

For skew of simplicity we assume the distinction of F is positive in direction of velocity

V.

Rolling resistance and gradient resistance for a given vehicle and gradient respectively, are

constant.

Rolling resistance +Gradient resistance =b

Drag force =C (��/2) A

=a�� Where a=Cd ρA/2

Force F=(a��+b)

F =m �� =m

�� × ��

��

F=mv�� =mvdv

� � �� =� ��

� /F

� � �� = � ��

� /(a��+b)

� � �� = � ��

�(��)

��

Let �� = �

� � �

�= � ��

�(�� + �)�

�

By integration we have got the value of distance travelled by the vehicle after switching off

the engine.

X = �� !" #

(��#) Where;

K = constant value = ��

V= velocity of the car, m/s

m = mass of the car in kg

a=Cd ρA/2

F= (a��+b)

After the success full experimental testing of the car model then use of this above formula

and find out the Drag Coefficient (Cd) and Drag Force (Fd)



Table 1 Experimental reading of the Tata Indica car: Mass-1140 kg, Area-2.11 m2

3. SIMULATION OF VEHICLE AERODYNAMIC

3.1. Mathematical Modeling of Vehicle aerodynamics

CFD has become a useful tool to study vehicle aerodynamics by excluding the need of

experimental studies ((Gibson and Launder (1978)). This chapter presents a numerical study

using automated CFD tools to study vehicle aerodynamics. In this work a CFD analysis of

vehicle aerodynamics has been done using FLUENT software. K-e RNG model has been used

to analyses the air flow field. Computational domain using structured and unstructured grid

schemes was used for different models of vehicles. It was observed that flow fields obtained

from CFD analysis using Fluent are comparable to experimental and numerical results available

in literature.

Computational Fluid Dynamics (CFD) has become a useful tool to understand the complex

flow structures and aerodynamics of vehicles by excluding the need of experimental studies.

Turbulent flows are associated with fluctuating velocity fields in time and space that cause

mixing and fluctuation of transported quantities like momentum, energy, and dust

concentration.

3.2. Turbulence Models

A simulation of a small scale and high frequency fluctuation requires complex mathematical

analysis. The approach for handling such fluctuations is to manipulate the instantaneous

governing equations by transforming them to time-averaged or ensemble-averaged form for

ease of computation. Several turbulence models have been proposed to determine the unknown

variables in the modified governing equations.

Reynolds-averaging (time-averaging) may be applied to the Navier-Stokes equations for

turbulence modeling of cyclone flow field. Reynolds averaging implies that the solution

variables in the instantaneous (exact) Navier-Stokes equations are decomposed into the mean

(ensemble-averaged or time-averaged) and fluctuating components. In the case of velocity

components:

ui = u i + u i (1)

The time averaging of the incompressible of instantaneous Navier Stokes equations (1) and

(2) lead to the Transient Reynolds Average Navier Stokes ((TRANS) or Unsteady Reynolds

Average Navier Stokes (URANS)) equations as given below:

( ) 0uit xi

ρρ

∂ ∂+ =

∂ ∂

Sl no. Speed(km/h) Distance(m) Time(s) Drag Coefficient

Cd

Drag Force Fd

1 20 400 55 0.25 18

2 30 500 73 0.134 12

3 40 400 56 0.682 108

4 50 400 60 0.825 204

5 60 400 77 0.798 283

6 70 500 76 0.74 360

7 80 510 79 0.758 638



2( ) ( ) [ ( )] ( ' ')

3

i j i

i j

j j j i i j

i ij i j i

i

p u u uu uu u u g

t x x x x x x xρ ρ µ δ ρ ρ

∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂+ =− + + − + − +

∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂

In the above equations, the symbols have the usual meaning. Kronecker delta ijδ ( ijδ =1 if

i=j and ijδ =0 if i =0.) accounts for the dissipation becoming zero for non-isotropic terms.

The term ' 'i ju uρ

Represents Reynolds stresses. When using the Reynolds stress model, besides the continuity

and momentum equations, the Reynolds stress transport equations are considered.

Turbulence modeling is the construction and use of a model to predict the effects of

turbulence. Averaging is often used to simplify the solution of the governing equations of

turbulence, but models are needed to represent scales of the flow that are not resolved.[1] The

turbulent models used for CFD analysis of aerodynamics by earlier research workers were

based on steady state solutions because of limited spatial resolution available at that time

There are several transport Model that close the Reynolds-averaged Navier-Stokes

equations by solving transport equations for the Reynolds stresses, together with an equation

for the dissipation rate. The exact form of the Reynolds stress transport equations are derived

by taking moments of the exact momentum equation.

A brief description of some closure turbulent models is given below:

k–ε (Standard) model: This model involves the solution of transport equations for the

kinetic energy of turbulence and its dissipation rate and the calculation of turbulent contribution

to the viscosity at each computational cell. Its main advantages are short computation time.

k–ε RNG model: A modified version of the k–ε model, with improved results for swirling

flows and flow separation for vehicle aerodynamics k-e RNG model may be used for accurate

flow analysis

k–ε Realizable model: Another modified version of the k–ε model.

Algebraic Stress Model: Boysan et al (1986) presented the theory of a 3D modified

algebraic stress turbulence model.

3.3. Simulation Steps Adopted For the Vehicles Aerodynamic

There are three steps involved in a typical CFD simulation. The three steps are:

a. Pre-Processing Stage

b. CFD Solving Stage

c. Post-Processing Stage

3.3. Pre-Processing Stage

In the pre-processing stage, CFD users are needed to provide sufficient input to the computer

in order to obtain the desired output. The pre-processing stage is divided into several steps:

A Geometry Generation

B Mesh Generation

C Input for Boundary Condition

D Flow Type (Steady/Unsteady)

E Discretization Scheme Input

F Turbulence and Near Wall Model Input



A: Geometry Generation - pro/Engineer wildfire 5.0

In the Pre Processing stage the models of the vehicles were create using the Pro-e software.

Pro/ENGINEER Wildfire 5.0 is unmatched for developing and communicating stunning

product concepts. It's a truly open solution you can use to share ideas—or refine concepts using

freeform surfacing and reverse engineering tools. Designs can be sent directly to a rapid

prototyping machine, or transferred to downstream Pro/ENGINEER applications.

• Easy-to-use tools, blending 2D or 3D, curves and surfaces, and imported sketches for

concept exploration and industrial design

• Advanced also to-rendering to create photorealistic images

• Interoperable with other CAD systems

Figure 2 Tata indica designed in pro/E software

B: Mesh Generation

Ansys workbench 2.0 framework version 12.0.1

The Ansys Workbench, in its present form, meshes solid geometry parts using a number of 3-

D elements for thermal and structural analysis. These elements include:

• 10-node tetrahedral

• 20-node hexahedral

• 13-node pyramids

• 15-node wedge elements

• 4-node quadrilateral shells

• 3-node triangle shells

Figure 3 Tata Indica car meshed in ansys work bench

The default shape checking acceptance criterion that is used by the ANSYS Workbench

was produced by an extensive and thorough study that correlated different element shape

metrics to the quality of the solution achieved with a distorted mesh. The study concluded that



the ANSYS program, which supports many different types element formulations (such as p-

elements), must enforce stricter shape parameter values than the ANSYS Workbench, which

only needed to support the solid and shell elements for the aforementioned analyses. One

particular shape metric predicted whether the quality of the element would affect the numerical

solution time and again the results obtained after the successful meshing procedure of Tata

Indica car in the Ansys Workbench are as follows:

Total Number of Nodes – 263039

Total Number of Elements – 1374209

Type of Meshing-Mixed Triangular Mesh

Table 2 Total grid size of Tata Indica Car

4. BOUNDARY CONDITION INPUT VARIOUS PARAMETERS

Table 3 Boundary Condition of Tata Indica Car

Table 4 Boundary Condition of Tata Indica Car

Parameters

Near

wall

Treatme

nt

Densit

y

kg/m3

Viscosity

Operatin

g

pressure

(pascal)

Speciation

Method

Turbulen

ce

intensity

Turbulent

viscosity

ratio

standard

wall

function

1.225 1.7894e-

05 kg/m-s

101325

intensity

length scale

2%

0.0014 (1%

height of the

vehicles )

4.1. CFD Solving Stage

In the CFD solving stage it was required to export the Mesh file, which was obtained in the

Ansys V12 in workbench. Then the meshed model was run on Fluent 6.3.26 software by

considering different boundary conditions. After the input boundary condition running the

fluent software different parameters on contour, vectors, velocity magnitude iteration and path

line were plotted.

In the contours, different parameter profile for a car have been plotted which are shown in

the figures.

4.2. Velocity magnitude

Velocity is a physical vector quantity; both magnitude and direction are needed to define it. The

scalar absolute value (magnitude) of velocity is called "speed", being a coherent derived unit

whose quantity is measured in the SI (metric) system as metres per second (m/s)

Car Level Cells Faces Nodes

Indica 0 711958 14644302 140628

Parameters Mass Area solver formulation velocity model k-epsilon model

1140kg 2.11m2 pressure

based

implicit 19.44 m/s K-epsilon realizable



Graph 1 velocity magnitude profile interior zone of Tata Indica obtained from contour

Graph 2 velocity magnitude profile of Tata Indica obtained from vectors

Table 5 The value of Velocity Magnitude profile from contours and vectors from graph with the help

of color code of Tata Indica car

Car Maximum

value in m/s

Minimum

value in m/s

Observe

value m/s

Drag

coefficient Cd

Drag force

Fd

Tata Indica 38.0 7.75 19.4 0.841 411

4.3. Turbulence Intensity

Turbulence Intensity is a scale characterizing turbulence expressed as a percent. An idealized

flow of air with absolutely no fluctuations in air speed or direction would have a Turbulence

Intensity value of 0% Here we have find out the value of color code taken by the graph



Graph 3 Turbulent Intensity of Tata Indica obtained from contours

Table 6-Estimate the turbulent intensity

Car Maximum value in % Minimum value in % Mean Value in

%

Turbulance Intensity

(%).

indica 123 29 76 1.97 %

4.4. Post Processing

In this stage the model of Tata Indica car which were modeled using the Pro-E 5.0 software

were exported in Ansys workbench V12 for the purpose of meshing. After successful meshing

it was then exported to Fluent 6.3.26 software. After giving the input conditions, for the purpose

of Iteration. The iterating time took around 32 hrs around no.of iteration 925

Graph 4 iteration of Indica car

5. RESULTS AND DISCUSSIONS

After the successfully completion of the computer software simulation and Experimental

calculation for Analysis of Aerodynamic design of Indica car to find out the drag coefficient

and drag force



Table 7 Result obtained from software simulation and experimental value

Differences 0.243

6. CONCLUSION

The drag coefficients found theoretically and experimentally are very near. The results vary by

only 0.243 values; this shows the accuracy of the results obtained by us during the thesis. If the

present design will be implemented for the model generation of the car we will obtain the exact

values of the drag coefficient and drag force, which were already measured

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