Project 1

Aim - Develope a vehicle model in simulink including Engine, Transmission, Differential, Wheels, Vehicle dynamics and run on different drive cycles like udds, hwfet, ftp or wltp etc.

Goal- The main goal of this project is to get familiar with the modeling process, writing scripts in Matlab, modeling in Simulink, analyzing data and generating plots.

Objectives -

• Tabulate the fuel economy numbers (kmpl) for UDDS and HWFET cycle. This forms the baseline numbers for comparing with the future hybrid version
• Plot the time trace for engine, transmission input, transmission output and wheel speed on one plot.
• Plot engine torque, engine power, fuel rate and fuel consumption using subplots
• Plot accelerator and brake pedal, gear command, vehicle desired and actual speed, vehicle distance using subplots.
• Plot the engine operating points on the engine fuel map
• Writing down appropriate brief comments on each of these plots, describing the vehicle behavior throughout the drive cycle.
• Generate the plots for both drive cycles.

Coventional Vehicle - conventional vehicles use an internal combustion engine fueled by gasoline or diesel to power the wheels. Electricity is used for some accessories, but is not used to move the vehicle.

Basically coventional vehicle consist of following subsystems

• Controller unit - Engine control, Transmission control, Brake control unit.
• Powertrain - Engine, Transmission, Differential, Wheels and vehicle dynamics
• Driver unit

Develope a script for matlab and design every unit in simulink to understand results,

Matlab Script1  file name - initial_file

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Skill-Lync -> Hybrid Drives Development
% Project 1 - Conventional Vehicle Model
% By - Vijaysinh Salunke 

% 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);

Now have a look at every unit we have built in simulink

Conventional Vehicle Model

Driver Model

Controller unit

Powertrain Unit

Engine Unit

• 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 Unit

If we take tractive force as 10000N then our outpt plot is as follows

Transmission

Differential

Wheel

Tractive force on wheels

Now the model is ready to run lets run the model for 2000 seconds. we got the following output as engine torque

Matlab Scipt2   File name Final_file

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Skill-Lync -> Hybrid Drives Development
% Project 1 - Conventional Vehicle Model
% By - VijaySinh Salunke
% 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_Spd = out.Eng_Spd*30/pi; % Engine speed [rpm]
Eng_Fuel_Rt= out.Eng_Fuel_Rate;
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;
Wheel_Spd=out.Wheel_Speed;
Veh_Speed = Veh_Spd*18/5;
% Eng_Spd=0.1;
Eng_Trq= out.Eng_Trq1;
%% 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(1)
subplot(3,1,1)
hold on
grid on
plot(Eng_Speed, 'linewidth', 1, 'Color', 'red');
xlabel('time (s)')
ylabel('Engine Speed [rpm]')
xlim([0, Time(end)]);

subplot(3,1,2)
hold on
grid on
plot(Time, Trans_In_Spd, 'linewidth', 1, 'Color', 'G');
plot(Time,Trans_Out_Spd, 'linewidth', 1, 'Color', 'Red');
xlim([0, Time(end)]);
legend('Transmission input','transmission output')
xlabel('Time [s]');
ylabel('Trans Speed');
subplot(3,1,3)
hold on
grid on
plot(Wheel_Spd, 'linewidth', 1, 'Color', 'red');
xlim([0, Time(end)]);
xlabel('Time [s]');
ylabel('Wheel Speed');
%% Plotting Engine an Fuel characteristics time trace
figure(2)
subplot(4,1,1)
hold on
grid on
plot(Eng_Trq, 'linewidth', 1, 'Color', 'b');
ylabel('Engine Torque')
xlim([0, Time(end)]);

subplot(4,1,2)
hold on
grid on
plot(Eng_Pwr, 'linewidth', 1, 'Color', 'black');
ylabel('Engine power')

subplot(4,1,3)
hold on
grid on
plot(Eng_Fuel_Consump, 'linewidth', 1, 'Color','Red');
xlim([0, Time(end)]);
xlabel('Time [s]');
ylabel('Fuel Consumption');
subplot(4,1,4)
hold on
grid on
plot(Eng_Fuel_Rt, 'linewidth', 1, 'Color','Red');
xlim([0, Time(end)]);
xlabel('Time [s]');
ylabel('Fuel Rate');
%% Plotting vehicle characteristics time trace
figure(3)
subplot(4,1,1)
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(4,1,2)
hold on
grid on
plot(Time, Gear_Cmd, 'linewidth', 1, 'Color', 'black');
xlim([0, Time(end)]);
xlabel('Time [s]');
ylabel('Gear');
subplot(4,1,3)
hold on
grid on
plot(Veh_Spd, 'linewidth', 1, 'Color', 'black');
xlim([0, Time(end)]);
xlabel('Time [s]');
ylabel('Vehicle speed');
subplot(4,1,4)
hold on
grid on
plot(Veh_Dist, 'linewidth', 1, 'Color', 'red');
xlim([0, Time(end)]);
xlabel('Time [s]');
ylabel('Vehicle Distance');
%% Plotting engine operating points on engine fuel map
figure(4)
title('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)]);

Procedure to run above model and script

• Make the project folder as cureent folder
• now run the intial_file.m matlab script
• Now run the Project_VehicleModel.slx simulink model
• now run the Final_file.m matlab script.

Note - Model is drawn in Matlab And Simulink R2021a

Fuel Economy Number

For UDDS cycle

For HWFET cycle

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

Outputs for UDDS cycle

Plot of Engine speed, Transmission In-Out Speed, Wheel Speed

Plot of Engine torque, Engine Power, Fuel Rate, Fuel Consumption

Engine Operating points

Plot for acceleration, brake pedal,gear commands, vehicle speed, vehicle distance

HWFET Cycle

Plot of Engine speed, Transmission In-Out Speed, Wheel Speed

Plot of Engine torque, Engine Power, Fuel Rate, Fuel Consumption

Engine Operating points

Plot for acceleration, brake pedal,gear commands, vehicle speed, vehicle distance

Observation

• 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 staticfriction.
• 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.
• 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.