Project 1
Description:
Project 1 deals with the development of a forward energy-based fuel consumption model of a conventional vehicle.
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.
In this project, a typical midsize car with a 1.9L engine and a 4-speed automatic transmission is considered. Data is taken from ADVISOR data base developed by NREL, USA. Transmission shift map and controller is taken from Matlab/Simulink example database.
The model developed has the capability to simulate the vehicle on different drive cycles like UDDS, HWFET, FTP, NEDC, etc.
“Project1_InitFile.m” is a Matlab script used to load all the variables required for running the Simulink model and for post-processing. The drive cycle selection is also done here. Before running the Simulink
vehicle model, run this initialization script.
“Project1_VehicleModel.slx” is the Simulink model of the vehicle. It is modeled using a ‘Driver’ block, which is a basic PI controller that generates accelerator and brake pedal outputs to match the desired
and actual vehicle speeds. The ‘Controller’ block is the brains of the vehicle, representing the electronic controls units. Based on the driver inputs, it generates desired engine torque, desired transmission gear
and desired brake torque. These inputs are fed to the ‘Powertrain’ block which represents the drivetrain of the vehicle. It consists of an ‘Engine’ connected to the ‘Automatic Transmission’ through a ‘Torque
Converter’. The output of the transmission is connected to the ’Differential’, which powers the ‘Wheels’, that provides the tractive force for vehicle acceleration. The longitudinal dynamics of the vehicle along with the road load is represented in the ‘Vehicle Dynamics’ block. The solver selected is ode3 with a fixed step size of 0.01 sec.
After running this Simulink model, data from the model will be loaded in the Matlab workspace.
“Project1_ProcessingFile.m” is the Matlab script used to analyze this data and to generate plots. This script needs to be executed after the Simulink model data has been loaded into the workspace. Here we
rename the variables loaded from the model (if desired), do some basic post-process calculations and generate results and plots.
Task:
The task of this project is to compute the fuel economy numbers for the given vehicle (kmpl) on the urban cycle (UDDS) and highway cycle (HWFET). Also, to analyze and understand the vehicle operating
points in terms of engine speed, torque, transmission speeds, pedal positions, gear, distance traveled, etc.
To do that, the following steps need to be followed:
1) Load the Project1 folder as the Current Folder in Matlab.
2) Run the “Project1_InitFile.m” Matlab script.
3) The provided vehicle Simulink model “Project1_VehicleModel.slx” is incomplete. The engine and vehicle dynamics block contents have been deleted. Build the Simulink blocks by referring to the course lecture and example block images provided. You can run the model and analyze the results using a ‘Scope’ for debugging.
4) Add additional ‘To Workspace’ blocks for transferring the desired Simulink vehicle data into the Matlab workspace.
5) Modify the “Project1_ProcessingFile.m” as per the desired plots and required calculations.
6) Write a project report that contains the following:
a. Tabulate the fuel economy numbers (kmpl) for UDDS and HWFET cycle. This forms the baseline numbers for comparing with the future hybrid version.
b. Plot the time trace for engine, transmission input, transmission output and wheel speed on one plot.
c. Plot engine torque, engine power, fuel rate and fuel consumption using subplots.
d. Plot accelerator and brake pedal, gear command, vehicle desired and actual speed, vehicle distance using subplots.
e. Plot the engine operating points on the engine fuel map.
f. Write down appropriate brief comments on each of these plots, describing the vehicle behavior throughout the drive cycle.
g. Generate the plots for both drive cycles
UDDS Cycle:
The EPA Urban Dynamometer Driving Schedule (UDDS) is commonly called the "LA4" or "the city test" and represents city driving conditions. It is used for light duty vehicle testing. The UN/ECE Regulation 53 refers to the EPA UDDS as the "Test Equivalent to the Type 1 Test (verifying emissions after a cold start)."
HWFET Cycle:
The Highway Fuel Economy Driving Schedule (HWFET) represents highway driving conditions under 60 mph.
Vehicle Model
Initialization/Pre-Processing
- A MATLAB script has been created to load all the variables needed to run and post-process the Simulink model. Drive cycle selection is also done from here. Before running the Simulink vehicle model, the script is initialised at MATLAB to load all the variables in the workspace.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Skill-Lync -> Hybrid Drives Development
% Project 1 - Conventional Vehicle Model
% By - Aksharat Jain
% 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);- The Drive Cycle can be selected from this MATLAB Script, By changing the variable Drive_Cycle_Select to,
| 1 | UDDS |
| 2 | HWFET |
| 3 | FTP |
| 4 | US06 |
| 5 | NEDC |
| 6 | WLTP |
- Here, we have selected the value of Drive_Cycle_Select = 1 (i.e for UDDS Cycle).
- Here, we have selected the value of Drive_Cycle_Select = 2 (i.e for HWFET Cycle).
Model:
Engine Block
Vehicle Dynamics Block
Processing File
- A MATLAB script is created to analyse data and to generate plots. Here we rename the variables loaded from the model, do some basic post-process calculations and generate results and plots.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Skill-Lync -> Hybrid Drives Development
% Project 1 - Conventional Vehicle Model
% By - Aksharat Jain
% 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_rate = out.Eng_Fuel_Rate; % Engine Fuel Rate [gkW]
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]
WheelSpd = out.WheelSpd*30/pi; % Wheel speed [rpm]
%% 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 fuel economy numbers (Fuel Consumption vs Fuel Rate)
figure(1)
hold on
grid on
plot(Time,Eng_Fuel_Consump,'linewidth',2); % Engin Fuel Consumption
plot(Time,Eng_Fuel_rate,'linewidth',2,'Color','#D95319'); % Engine Fuel Rate
xlabel('Fuel Consumption');
ylabel('Fuel Rate');
xlim([0, Time(end)]);
legend('Fuel Consumption','Fuel Rate');
%% Plotting vehicle characteristics time trace for engine, transmission input, transmission output and wheel speed in one plot
figure(2)
hold on
grid on
plot (Time,Eng_Spd,'linewidth',2,'Color', '#0072BD'); % Engine Speed
plot (Time,Trans_In_Spd,'linewidth',2,'Color', '#D95319'); % Transmission Input Speed
plot (Time,Trans_Out_Spd,'linewidth',2, 'Color', '#EDB120'); % Transmission Output Speed
plot (Time,WheelSpd,'linewidth',2,'Color','#7E2F8E'); % Wheel Speed
xlabel ('Time (s)');
ylabel('Speed (rpm)')
xlim([0, Time(end)]);
legend('Engine Speed','Transmission Input','Transmission Output','Wheel Speed');
%% Plot engine torque, engine power, fuel rate and fuel consumption using subplots
% Engine Torque
figure (3)
subplot (2,2,1)
hold on
grid on
plot (Time,Eng_Trq,'linewidth',2,'Color','#4DBEEE'); % Engine Torque
xlabel ('Time (s)');
ylabel ('Torque (Nm)');
legend ('Torque');
% Engine Power
subplot (2,2,2)
hold on
grid on
plot (Time,Eng_Pwr,'linewidth',2,'Color','#4DBEEE'); % Engine Power
xlabel ('Time (s)');
ylabel ('Power (kW)');
legend ('Power');
% Engine Fuel Rate
subplot (2,2,3)
hold on
grid on
plot (Time,Eng_Fuel_rate,'linewidth',2,'Color','#4DBEEE'); % Engine Fuel Rate
xlabel ('Time (s)');
ylabel ('Fuel Rate (%)');
legend ('Fuel Rate');
% Engine Fuel Consumption
subplot (2,2,4)
hold on
grid on
plot (Time,Eng_Fuel_Consump,'linewidth',2,'Color','#4DBEEE'); % Engine Torque
xlabel ('Time (s)');
ylabel ('Fuel Consumption (kmpl)');
legend ('Fuel Consumption');
%% Plot accelerator and brake pedal, gear command, vehicle desired and actual speed, vehicle distance using subplots.
% Accelerator and brake pedal
figure (4)
subplot(3,2,1)
hold on
grid on
plot(Time, Acc_Pdl, 'linewidth', 2,'Color', '#0072BD'); % Accelerator pedal
plot(Time, Brk_Pdl, 'linewidth', 2,'Color', '#EDB120'); % Brake Pedal
ylabel('Pedal (%)')
xlim([0, Time(end)]);
legend('Accel','Brake');
% Gear Command
subplot(3,2,2)
hold on
grid on
plot(Time, Gear_Cmd, 'linewidth', 2,'Color','r'); % Gear Command
xlim([0, Time(end)]);
xlabel('Time (s)');
ylabel('Gear');
legend('Gear Command');
% Vehicle Speed
subplot(3,2,3)
hold on
grid on
plot(Time, Veh_Spd, 'linewidth', 2,'Color','black'); % Vehicle Speed
xlim([0, Time(end)]);
xlabel('Time (s)');
ylabel('Actual Speed (kmph)');
legend('Vehicle Speed');
% Vehicle Distance
subplot(3,2,4)
hold on
grid on
plot(Time, Veh_Dist, 'linewidth', 2,'Color','g'); % Vehicle Distance
xlim([0, Time(end)]);
xlabel('Time (s)');
ylabel('Distance (km)');
legend('Distance');
%% Plotting Drive Cycle
figure(5)
hold on
grid on
plot(cyc_time, cyc_vel, 'linewidth', 1, 'Color', 'black');
xlabel('Time (s)')
ylabel('Velocity (Mph)')
title('Drive Cycle')
%% 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)]);
UDDS Cycle:
a. Fuel economy numbers (kmpl)
UDDS drive cycle:
Fuel Economy = 13.6312 Kmpl
HWFET drive cycle:
Fuel Economy = 16.3072 Kmpl
As we can see, HWFET has better fuel efficiency than UDDS because there is more traffic in cities, stops are made for shorter periods of time, and gasoline is used more initially. Because there is no traffic and the vehicle is moving without excessive braking in HWFET, the fuel economy number will be higher.
b. Plot the time trace for engine, transmission input, transmission output and wheel speed on one plot.
UDDS drive cycle:
HWFET drive cycle:
- We can see that the UDDS fluctuations on the graph are greater than the HWFET cycle fluctuations.
- When compared to HWFET, UDDS has more braking because of the traffic peak.
c. Plot engine torque, engine power, fuel rate and fuel consumption using subplots.
UDDS drive cycle:
HWFET drive cycle:
- Due to the excessive number of starts and pauses compared to the HWFET cycle, the car used more power during the UDDS cycle.
- Because the vehicle needs extra torque to overcome static friction when starting from rest, engine torque is likewise high in UDDS.
- Because the vehicle will be moving continuously and consume more fuel, the fuel rate is high in HWFET.
- When compared to UDDS, where there are numerous stops and starts and more fuel is used when the car is idle, HWFET will have higher fuel efficiency.
d. Plot accelerator and brake pedal, gear command, vehicle desired and actual speed, vehicle distance using subplots.
UDDS drive cycle:
HWFET drive cycle:
- Due to the frequent starts and pauses, UDDS causes significant variations on the accelerator and braking pedals. However, because there won't be any frequent stops, the brake pedal fluctuations in HWFET are almost close to the zero line.
- As it cannot reach high speeds in that traffic, the UDDS cycle mostly employs the first and second gears and uses the third and fourth gears only very seldom. Since the vehicle will be moving at a high speed during the HWFET cycle, those gears are used the majority of the time. When braking is necessary, it commonly shifts into first and second gears.
- In comparison to UDDS, the vehicle speeds in HWFET will be higher. Due to its frequent braking, UDDS also experiences greater speed variations.
- Due to the traffic barrier in UDDS, the distance travelled in the allotted time will be shorter in HWFET than in UDDS.
e. Plot the engine operating points on the engine fuel map.
UDDS drive cycle:
HWFET drive cycle:
- By this, it is clear that as torque decreases speed increases.
- The engine operating points are plotted on the fuel map and the operating point is under the maximum torque curve.
Conclusion:
- In UDDS than in HWFET, there is a higher rate of fuel consumption.
- The UDDS drive cycle works well for normalising assessments of vehicle fuel consumption and pollutant emissions.
- In HWEFT, greater distance is covered than in UDDS.
- We can see that in UDDS, braking and shifting gears causes a loss in engine efficiency and fuel consumption.
- Thus, using MATLAB and Simulink, the forward energy-based fuel consumption model of a standard car has been successfully simulated.
- On the basis of engine speed, torque, transmission speed, pedal locations, gear, and distance travelled, analyses and understandings of vehicle operating points were carried out.
- The necessary graphs were successfully plotted using post-process computations.
- Vehicle fuel efficiency values (kmpl) for the given city cycle (UDDS) and highway cycle (HWFET) have been calculated successfully.