Project 1

Title:-

Deals with the development of a forward energy-based fuel consumption model of a conventional vehicle.

Aim:-

1] Build Simulink model using blocks and complete the vehicle model.

2] Writting scripts in MATLAB to load all the variables required for running the Simulink model.

3] Tabulate the fuel economy numbers (kmpl) for UDDS and HWFET cycle.

4] Plot the time trace for engine, transmission input, transmission output and wheel speed on one plot.

5] Plot engine torque, engine power, fuel rate and fuel consumption using subplots.

6] Plot accelerator and brake pedal, gear command, vehicle desired and actual speed, vehicle distance using subplots.

7] Plot the engine operating points on the engine fuel map.

8] Generate the plots for both drive cycles.

9] Study of Conventional vehicle simulink model and creates graphs.

Conventional Vehicle:-

Conventional vehicles use an internal combustion engine fueled by gasoline or diesel to power the wheels. In this the heat engine uses the principle of heat release through combustion of a fuel with an oxidizer in a combustion chamber to create expanding gases which pushes against a piston creating forcce and torque output.

In this vehicle engine converts chemical energy stored in the fuel into heat which is used to produce useful work. Typically use fossil fuels like petroleum (petrol and diesel).

The most popular type of engine is used in this system is 4 stroke reciprocating engine. Engine in cyclinder process can be represented by ideal thermodynamic cycles such as Otto cycle, Diesel cycle. Otto cycle is a ideal cycle thet describes the cycle process for spark ignited SI engine. and the Diesel cycle is the ideal cycle thet describes the cycle process for a compression ignited CI engine.

Energy and performance of vehicle:-

In this system trge power demand on the wheel need to instant supplied by the powertrain. In otyher word the power coming from the powertrain dictates the power demand on the wheels (as per performance viz, acceleration, speed etc is determined by it.

In tis vehicle the powertrain is consists of an engine connected to the wheels through a transmission therefore the power comes from the engine through the transmission.

Conventional powwertrain efficiency:-

The engine generates power by converting chemical energy stored into the mechanical energy by the process of combustion. This process of energy conversion also has an efficiency and the energy input is in the form of fuel consumption.

- Instantaneous fuel consumption is given as

m.f=Peηe⋅ηt⋅QLHV">.mf=Peηe⋅ηt⋅QLHVm.f=Peηe⋅ηt⋅QLHV

Where,

mf = mass flow rate in [kg]

pe = Power of engine

pt = power of transmission

nt = efficiency of transmission

ne = efficiency of engine

QLHV = it is th ecalorific value/ lower heating value of fuel.

In this system of IC engine if tge power at the wheels is zero the engine is idling and still consumes some fuel to overcome the engine drag loss and keep it spinning this is the idling fuel consumption and know as idling process. Above mentioned formula is applicable only when the wheel power is strictly power. When the wheel power is negative either th engine is disengaged and idling or the engiune is engaged and providing some engine braking due to the engine drag losses.

The engine is consuming fuel when it is idling but even for engine braking the engine might be consuming some fuel.

The fuel consumption not only depend on the power requirement at the wheels but also is required to generate power to run the various engine and vehicle accessory loads

System Dynamics:-

It deals with the modeling of multi domain systems through the use of a unified approach based on a ordinary differential and algebraic equation describing the static and dynamic effects.

Each systems has are two generalised variables-

1] Efforts:- It is generalised force variable. ex- torque, force, voltage, heating value.

2] Flow:- It is the generalised flow/velocity variable. ex:- velocity, current, mass flow rate.

3] Power:- It is the product of the effort and flow variable. It is interchangeable between energy domains.

Energy based models- Element models

To models the internal physical properties of the element and the losses there are basically two kinds of approach.

1] Map based models:- Elements are modeled using maps which characterized the relationship between the input and output , output and losses etc.

2] Analytical models:- Elements are modeled using physical equation that represent the internal dynamics. These are the two extremes most models are a combination of the two with some dynamics models analytically and for some using maps.

In this model We use Forward Model:-

It also known as dynamic simulation. Dynamic models are used for detailed simulations. In this model force/torque/power is the input and the vehicle state variable velocity and acceleration are outputs. The models and simulatios are more realistic due to phhysical casualty hence appropriate for control development. There is feedback loop to meet the desired vehicle state. It is mainly used to simulate a vehicle on a driving cycle to analyse the dynamic behaviour of the system helps significantly in control development.

Procedure:
Load the Project1 folder as the Current Folder in Matlab.
Run the “Project1_InitFile.m” Matlab script for drive cycle 1 i.e. UDDS
Code of the 'Project1_IntiFile':

clear all
close all
clc
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Skill-Lync -> Hybrid Drives Development
% Project 1 - Conventional Vehicle Model
% By - Ullekh Gambhira

% Description:

%% Initialization File
% Initialization file for loading the variables for the Conventional vehicle simulation model

%% Vehicle Parameters
M = 1500; % Vehicle weight [kg]
Cr = 0.015; % Rolling resistance coefficient
Rw = 0.35; % Rolling radius [m]
Cd = 0.33; % Drag coefficient
Af = 2; % Frontal area [m2]
rhoa = 1.225; % Air density [kg/m3]
Vwind = 0; % Wind velocity [kmph]
g = 9.81; % Gravitational acceleration [m/s2]
theta = 0; % Slope [deg]
myu_road_tire = 1; % Coefficient of friction between tire - road interface

%% Powertrain Parameters
FDR = 3.73; % Final Drive Ratio / Diff Ratio
DiffEff = 0.99; % Differential efficiency (assumed independent of operating conditions)

NumGear = 4; % Number of gears in transmission
TransGear = [1:NumGear]; % Transmission Gears
TransRatio = [3.06, 1.62, 1, 0.7]; % Corresponding Transmission ratios
TransEff = 0.90; % Transmission efficiency (assumed independent of operating conditions)

TC_SR = [0, .5, .6, .7, .8, .87, .92, .94, .96, .97, 1]; % Torque Converter Speed Ratio (Matlab default) -> TurbSpd/PumpSpd
TC_TR = [2.232, 1.5462, 1.4058, 1.2746, 1.1528, 1.0732, 1.0192, 1, 1, 1, 1]; % Torque Converter Torque Ratio (Matlab default) -> TurbTrq/PumpTrq
TC_Cf = 1e-4 * [.72558, .66322, .63463, .59042, .51331, .4144, .29287, .22444, .12186, .04386, 0]; % Torque Converter Capacity Factor (Matlab default) -> PumpTrq/PumpSpd^2 [Nm/rpm^2]

load Vehicle_Data/Engine_data_1_9L_Saturn_95kW
load Vehicle_Data/Trans_Shift_map

%% Driver Parameters
Kp = 10; % P gain for driver PI model
Ki = 1; % I gain for driver PI model
Drive_Cycle_Select = 1; % Drive cycle selection

% Drive cycle values in m/s

if Drive_Cycle_Select == 1
load DriveCycles/UDDS;

elseif Drive_Cycle_Select == 2
load DriveCycles/HWFET;

elseif Drive_Cycle_Select == 3
load DriveCycles/FTP;

elseif Drive_Cycle_Select == 4
load DriveCycles/US06;

elseif Drive_Cycle_Select == 5
load DriveCycles/NEDC;

elseif Drive_Cycle_Select == 6
load DriveCycles/WLTP;

end

time_end = cyc_time(end);
vel_end = cyc_vel(end);

Vehicle Model:

Driver:

Controller:

Power Train:

Engine:

Now, the Vehicle dynamics block is developed using the equations
Equations for aerodynamic drag, rolling resistance, and gradient are created and summed up to get the road load
Road load is subtracted from the tractive force to get the force
This force is then divided by the mass to get the acceleration component
Integrator is used to integrate the acceleration and get the velocity component
Road load and velocity are multiplied to get the power required for the vehicle
Power is then multiplied by the total time to get the energy required
All the blocks of velocity, acceleration, road load, the power required, and energy required are attached to the 'scope' block to
see the output variations with respect to the time.

Vehicle Dynamics:

Transmission:

Differential:

Wheels:

Code of 'Project1_ProcessingFile':

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Skill-Lync -> Hybrid Drives Development
% Project 1 - Conventional Vehicle Model
% By - Ullekh Gambhira

% Description:
% The following file is to used with the Initialization file and Simulink
% results for post-processing of the data.
% The file is incomplete, has some examples of how the data is imported
% into a readable format, data analysis and plotting examples.
% Based on the project task, use commands in a similar format as given
% below, to analyse the data and generate required plots.
% You can change variable names if desired

%% Post-Processing File
% File for post-processing the Conventional vehicle simulation model data

%% Renaming variables
Time = out.tout;
Acc_Pdl = out.Acc_Pdl; % Accelerator pedal [%]
Brk_Pdl = out.Brk_Pdl; % Brake pedal [%]
Gear_Cmd = out.Gear_Cmd; % Transmission gear
Trans_In_Spd = out.Trans_In_Spd*30/pi; % Transmission input speed [rpm]
Trans_Out_Spd = out.Trans_Out_Spd*30/pi;% Transmission output speed [rpm]
Eng_Trq = out.Eng_Trq; % Engine brake torque [Nm]
Eng_Spd = out.Eng_Spd*30/pi; % Engine speed [rpm]
Eng_Fuel_Consump = out.Eng_Fuel_Consumption; % Engine fuel consumption [g]
Veh_Dist = out.Veh_Dist/1000; % Distance traveled by vehicle [km]
Veh_Spd = out.Veh_Spd*18/5; % Vehicle speed [kmph]

Eng_Speed = Eng_Spd*30/pi;
Veh_Distance = Veh_Dist/1000;
Veh_Speed = Veh_Spd*18/5;
Eng_Spd=0.1;
Eng_Trq=10;
%% Data Analysis
Eng_Pwr = Eng_Spd*pi/30*Eng_Trq/1000; % Engine brake power [kW]
rho_petrol = 0.7197; % Density of petrol [kg/L]
kmpl = Veh_Dist(end)/(Eng_Fuel_Consump(end)/1000/rho_petrol); % Fuel economy [kmpl]

%% Plotting vehicle characteristics time trace
figure()
subplot(3,1,1)
hold on
grid on
plot(Time, Acc_Pdl, 'linewidth', 1, 'Color', 'black');
plot(Time, Brk_Pdl, 'linewidth', 1, 'Color', 'red');
ylabel('Pedal [%]')
xlim([0, Time(end)]);
legend('Accel','Brake');
subplot(3,1,2)
hold on
grid on
plot(Time, Trans_In_Spd, 'linewidth', 1, 'Color', 'black');
plot(Time, Trans_Out_Spd, 'linewidth', 1, 'Color', 'red');
ylabel('Speed [rpm]')
xlim([0, Time(end)]);
ylim([0, 6000]);
legend('Trans Input','Trans Output');
subplot(3,1,3)
hold on
grid on
plot(Time, Gear_Cmd, 'linewidth', 1, 'Color', 'black');
xlim([0, Time(end)]);
xlabel('Time [s]');
ylabel('Gear');

%% Plotting engine operating points on engine fuel map
figure('Name','Engine Operating Points');
hold on
grid on
title('Engine Operating Points','fontsize',12);
p1=plot(Eng_map_spd*30/pi,Eng_max_trq,'linewidth',2,'color','r');
p2=line([Eng_map_spd(end)*30/pi Eng_map_spd(end)*30/pi],[0 Eng_max_trq(end)]);
set(p2,'linewidth',1,'linestyle','--','color','k');
p3=line([Eng_map_spd(1)*30/pi Eng_map_spd(1)*30/pi],[0 Eng_max_trq(1)]);
set(p3,'linewidth',1,'linestyle','--','color','k');
[c,h] = contour(Eng_map_spd'*30/pi,Eng_map_trq,Eng_fuel_map');
clabel(c,h);
xlabel('Engine Speed [rpm]');
ylabel('Engine Torque [Nm]');
title('Engine Fuel Consumption Map [g/s]');
p4 = plot(Eng_Spd,Eng_Trq,'.','color','k');
legend([p1 p4],{'Max Curve','Operating Points'});
axis([Eng_map_spd(1)*30/pi Eng_map_spd(end)*30/pi 0 Eng_map_trq(end)]);

Fuel economy number (kmpl) is found out from that program using formula
Engine, transmission input, transmission output, and wheel speed are plotted on one graph with respect to the time
Engine torque, engine power, fuel rate, and fuel consumption are plotted wrt the time using subplots
Accelerator and brake pedal, gear command, vehicle speed, and vehicle distance are plotted wrt the time using subplots
The engine operating points are plotted on the engine fuel map
A similar procedure is followed by changing the drive cycle to 2 i.e. HWFET

Results:

Fuel economy numbers:

As we see, the fuel economy is high in HWFET compared to UDDS, it is because, in urban driving, the vehicle encounters more
traffic and it has to stop for fewer distances and it consumes more fuel at the starting. In HWFET, the vehicle encounters no
traffic and it moves without use of too much braking, so it will have more fuel economy number

Engine, transmission input, transmission output and wheel speed plot

UDDS drive cycle:

HWFET drive cycle:

We can see that the graph has more fluctuations in UDDS compared to the HWFET cycle because UDDS has more starts and
stops but HWFET does not have too many starts and stops
Braking is high in UDDS when compared to HWFET due to traffic
Peak engine power reached in UDDS is nearly 4800 RPM and that in HWFET is 3800 RPM at the start, because, in UDDS, the vehicle requires more power to start from the initial condition.

Engine torque, engine power, fuel rate, and fuel consumption plot:

UDDS drive cycle:

HWFET drive cycle:

Vehicle consumed more power in the UDDS compared to HWFET cycle because it has too many starts and stops compared to
HWFET. When starting from the initial condition vehicle requires more power
Engine torque is also high in UDDS because while starting from rest, the vehicle requires more torque to overcome the static
friction
The fuel rate is high in HWFET because the vehicle will be in continuous movement, it consumes more fuel
But, fuel economy will be high in HWFET compared to UDDS because there are many stops and starts in UDDS and more fuel is consumed when the vehicle is in an idle position.

Accelerator and brake pedal, gear command, vehicle speed, vehicle distance plot
UDDS drive cycle:

HWFET drive cycle:
For UDDS, the accelerator and the brake pedal have more fluctuations because of frequent starts and stops. But in HWFET, the
brake pedal fluctuations are almost near to the zero line as there will be no frequent stops
UDDS cycle mostly runs on 1st, 2nd gears, and uses 3rd, 4th gears very rarely as it does not achieve high speeds in that traffic. In the HWFET cycle, the vehicle mostly runs on 3rd, 4th gears as it will be moving at high speeds. It uses 1st, 2nd gears very frequently when braking is required
Obviously, the vehicle speeds will be high in HWFET compared to UDDS. UDDS also has more fluctuations in the speed due to
frequent braking
The distance travelled in the given time will be high in HWFET than UDDS because of the traffic barrier in UDDS

Engine operating points on the engine fuel map
UDDS drive cycle: