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Electrical Vehicle vs ICE Vehicle

Electrical vehicles are the new technology emerging (with potential and willingness) to replace fossil fuel based internal combustion engine (ICE) driven vehicles. A short and preliminary comparison of the two technology can be summarized as follows.

Electrical Vehicle vs ICE Vehicle

The application of CFD in EV will still be at large scale except the fact that the combustion phenomena will not be there. Some of the applications are:
  • Cooling of electric drive motors: the hot gas can be used in a gas-to-gas heat exchanger for heating of passenger cabin.
  • Thermal comfort in cabin - same as conventional internal combustion engine based vehicle
  • Battery Thermal Management System: needs to be heated under cold condition and cooled under hot conditions.
  • Cooling of brakes - same as conventional vehicle, regenerating braking can be used as electrical circuits are present everywhere. Brake force still hydraulic but actuation can be electrical.

Ventilation of an Electric Motor
Electrical Motor Ventilation

Recyclability of Battery Component - LAB (Lead Acid Batteries)
Lead Acid Battery

Recyclability of Battery Component - LIB (Li-Ion Batteries)
As of now, now known and scalable (technically as well as commercially) method exists. The cells used in mobile phones are still being dumped as solid waste.

Application of Numerical Simulations


There are wide range of applications of numerical methods such as CFD in automotive domain ranging from system level External and Underhood aerodynamics to brake cooling to the simulation of combustion phenomena inside engine cylinders. At the same time, the implementation of 3D simulation with 1D tools such as AVL-Boost, Ricardo-Wave and GT-Power suites significantly enhances the capabilities of each other. […]

CFD can be used to iterate the designs without actual prototyping. For example, the flow uniformity though the various runners of an intake manifold can be ensured at the early stage of development.
Flow in runners of Intake Manifold


The flow over bluff bodies has applications ranging from electrical high tension wires to cars to aeroplanes

Simplifications and Stages of Numerical Methods

Engine Combustion

Combustion is a complex phenomena involving fluid flow, all three modes of heat transfer, structural severity, lubrication, emissions and very short duration phenomena. Typically, such simulations are performed in specialized programs such as KIVA. However, to gain deeper insight into the physics, CFD tools have now been widely and successfully exploited in a staged manner.
Stages of In-cylinder Simulations

In-cylinder Simulations

HVAC System

Heating Unit HVAC Velocity Vector HVAC

Oil Filter - Flow through Porous Domain

The performance of oil filter (pressure drop and flow uniformity across filter) can be optimized using numerical fluid dynamic calculations. The filter can be used as porous domain whose porosity can be varied as the particulate matters get trapped during actual use.
Automotive Oil Filter

Component Level Appliations

There always exist a scope of improvement in the performance of individual components. The power of numerical simulations can be exploited without costly prototypes. For example, the location on inlet and outlets of a radiator is constrained by performance requirement as well as layout inside the engine compartments. The flow distribution inside the radiator tubes can be improved for different location of the inlet and outlet as well as shape and size of headers.

CFD: Automotive Applications

Fundamentals: Working Principle and Design Ratios

The conversion of rotating motion to translating motion using a slider-crank mechanism is explained in the following figure. The locus of some of the points which is translating as well as rotating is also shown. Slider Crank Mechanism

  • Length of the stroke = diameter of the crank pin = DCP. Piston travel per revolution = 2 * DCP. Distance traveled by crank pin per revolution = π * DCP. Hence, the ratio of average piston velocity to that of crankshaft pin = 2 * DCP / π * DCP = 2/π.

Slider Crank Mechanism Animation
The video can be accessed here: Slider Crank at YouTube. The Octave script used to create this animation is as follows:
clc; clear;
% Define constants - use consistent units: mm, rad, s
  N 	=   5;               % [rpm] - crankshaft rotation speed
  R     =   0.075;           % [m] - Crank Radius
  L     =   0.200;           % [m] - connecting rod length
  w     =  2*pi*N/60;        % [rad/s] - angular speed
  tau   =  2*pi/w;           % Time for one complete rotation of crankshaft
  dq    =  pi/30;
  Lp    =  0.010;            % Piston Length
  Db    =  0.020;            % Bore diameter = piston diameter
% Define parameters, calculate functions and plot  
  x(1)  = 0.0;
  y(1)  = 0.0;
  xMax  = L + 2*R + Lp; 	xMin = -2*R;  yMin = -2*R; yMax  = 2*R;
  figure;     axis([xMin xMax yMin yMax]);     hold on;     daspect([1 1 1]);
  plot(x(1), y(1), 'o');
  for q =  [0: dq : 2*pi]
    x(2)  = R * cos(q);
    y(2)  = R * sin(q);
  % Location of piston centre with crank angle q.
    x(3)  = R * cos(q) + sqrt(L^2 - R^2 * sin(q) * sin(q));
	y(3)  = 0;
	x(4)  = x(3) - Lp/2.0; y(4) = 0.0;
	x(5)  = x(4);          y(5) = -Db/2.0;
	x(6)  = x(3) + Lp;     y(6) = y(5);
	x(7)  = x(6);          y(7) = y(6) + Db;
	x(8)  = x(4);          y(8) = y(7);
	x(9)  = x(4);          y(9) = 0;
  % Time derivative of x - excluding q_dot term
    n     = L/R;
    xp    = -R * sin(q) - R * sin(2 * q) / sqrt(n^2 - sin(q) * sin(q) );
  % Piston velocity
    V     =  xp * w;
    plot(x(2), y(2), 'o'); plot(x(3), y(3), 'o');
    plot(x, y, "linestyle", "-", "linewidth", 2, "color", 'k'); 
    xlabel('x'); ylabel('y'); 
    %grid on;  % should be placed only after the plot command
    xtick = get (gca, "xtick"); 
    xticklabel = strsplit (sprintf ("%.2f\n", xtick), "\n", true);
    set (gca, "xticklabel", xticklabel)   

    ytick = get (gca, "ytick"); 
    yticklabel = strsplit (sprintf ("%.2f\n", ytick), "\n", true); 
    set (gca, "yticklabel", yticklabel);
    pause (0.0001); cla;  plot(x(1), y(1), 'o');  
    axis([xMin xMax yMin yMax]); daspect([1 1 1]);
  plot(x, y, "linestyle", "-", "linewidth", 2, "color", 'k');
  plot(x(2), y(2), 'o'); plot(x(3), y(3), 'o');

Combustion is on the most complex thermo-chemical phenomena known to us. This is much more than fluid mechanics and heat transfer and hence a typical method of CFD simulations does not fulfill the requirements. The complexity of combustion is described by following slides.

Types of Combustion

Combustion: Types

Non-Premixed Combustion

Non-Premixed Combustion

Premixed Combustion

Premixed Combustion

Partially Premixed Combustion

Partially Premixed Combustion

Combustion Phenomena in Engines

Combustion Phenomena in Engines

Combustion: CI vs. SI Engines

Combustion: CI vs. SI Engines

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