Project 1

OBJECTIVE:

• To compute the fuel economy numbers for the given vehicle (kmpl) on the urban cycle (UDDS) and highway cycle (HWFET).
• To analyze and understand the vehicle operating points in terms of engine speed, torque, transmission speeds, pedal positions, gear, distance traveled, etc.
• To build the Simulink blocks for Engine and Vehicle Dynamics and add additional ‘To Workspace’ blocks for transferring the desired Simulink vehicle data into the Matlab workspace.
• To tabulate the fuel economy numbers (kmpl) for UDDS and HWFET cycle.
• To plot various plots as per the requirement for both the drive cycles.

SOLUTION:

DESCRIPTION:

• This Project deals with the development of a forward energy-based fuel consumption model of 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).
• To analyze and understand the vehicle operating points in terms of engine speed, torque, transmission speeds, pedal positions, gear, distance traveled, etc.

STEPS TO BE FOLLOWED:

• Load the Project1 folder as the Current Folder in Matlab.
• Run the “Project1_InitFile.m” Matlab script.
• The provided vehicle Simulink model “Project1_VehicleModel.slx” is incomplete.
• To build the Simulink blocks for the Engine and the Vehicle Dynamics and run the model and analyze the results using a ‘Scope’ for debugging.
• Add additional ‘To Workspace’ blocks for transferring the desired Simulink vehicle data into the Matlab workspace.
• Modify the “Project1_ProcessingFile.m” as per the desired plots and required calculation.

SIMULINK MODEL:

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Skill-Lync -> Hybrid Drives Development
% Project 1 - Conventional Vehicle Model
% By - Dazzle 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,

lets see the simulink model of conventional vehicle,

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.

Now,

lets see the simulink model of conventional vehicle,

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.

Driver Model:-

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. In this we use drive cycles fro the based on these results of fuel consumption and emissions the vehicle gets certified and it also forms a basis of uniform asessment. It is based on time, velocity then its all integrate and creates output accelration pedal and brake pedal.

Control Model:-

The ‘Controller’ block is the brains of the vehicle, representing the electronic controls units. It is 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.

1] Engine control Unit:-

In this control model We use engine control unit in that give input Engine speed through creating look up table. in that table we give input Maximum torque and map speed then also create 2nd look up trable in that give input ct torque and map speed then it substracts and multiplied. the engine speed also give to ideal contro speed to integrate from this we meet output of engine required torque.

Graph created from Scope in Driver Model:-

2] Transmission Control Unit:-

In this unit we create steadfy flow variable state for controlling of gears of vehicle as in ascending and descending order with respect to time, speed, distance. and give input to this steady state is vehicle speed in m/s to mph.

3] Brake Control Unit:-

In this calculate brake torque and then all three control signals output is give to powertrain.

3] PowerTrain:-

The powertrain encompasses every component that converts the engine's power into movement. This includes the engine, transmission, the driveshaft, differentials, axles; basically anything from the engine through to the rotating wheels.

1] Engine:-

In this model we used map based model to model the fuel consumption of engine. It is based on maximum Torque and minimum torque from the controller. and then it saturated torque and give output then saturated torque and speed map give fuel consumption takes the speed and torque then the output goes into saturated then its integrated.

Graph created from Scope in Driver Model:- Engine Torque

2] Transmission:-

In these model we take engine torque, gear selector from controllerb for transmission of gear ratio. The ratio is multiply by transmission input torque and then the transmission efficiency positive torque and negative torque gives transmission input speed. In this case torque converter connects the engine to transmission it is part of transmission. In it basically engine dynamics and that is decoupled.

Graph created from Scope in Driver Model:- 1] Transmission in speed 2] Gear ratio 3] Differential Ratio

3] Differential:-

In this taking input is the transmission output then its going to the differential ratio multiplied the output and input torque then meet axle torque. The axle torque is a lower than the transmission torque and differential ratio.

4] Wheels:-

In this model we take the axle torque from differentail and brake torque from controller. it is substracts and multiplied rolling radius and velocity then we meet the tractive force from axle and brake torque. and the wheelspeed is meet using velocity.

5] Vehicle Dynamics:-

In this takes tractive force and road load. It is dictates vehicle speed based on tractive force and road load.

the dynamic equation for calculating road load is

MeqdVvehdt=ηtλtotRwTm−(12p⋅A⋅Cd⋅(Vveh+Vw∈d)2+Cr⋅M⋅g⋅cos(θ)+M⋅g⋅sin(θ))

where,

p = air density [kg/m^3]

A = Frontal area [m^2]

Cd = drag Coefficiend

Vveh = velocity of vehicle [m/s^2]

Vwind = velocity of wind [m/s^2]

Cr = rolling resistance coefficient

M = mass in [Kg]

g = gravity.

Then we calculate and integrate then we meet acceleration of vehicle and velocity of vehicle it mean vehicle distance and vehicle speed.

Conclusion:-

Total Power is increase slowly as increasing aerodynamic drag and inertial resistance. but in this drive cycle bad impact occurs due to decreasing rolling resistance.

Result:-

As comparing both cycles we used to UDDS drive cycle. Its best for asses of fuel consumption and Pollutants emission of vehicle in a normalised way.

Now For creating Plots we use MATLAB coding So the coding will give down:-

Now For creating Plots we use MATLAB coding So the coding will give down:-

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Skill-Lync -> Hybrid Drives Development
% Project 1 - Conventional Vehicle Model
% By - Dazzle 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_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]
Wheel_Speed = out.wh_speed;     % Wheel speed [kmph]
Eng_Fuel_Rate = out.Eng_Fuel_Rate % Engine fuel rate [%]

%% 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 transmission IN/OUT and Wheel Speed
figure(1)
hold on
grid on
plot(Time, Trans_In_Spd, 'linewidth', 1, 'Color', 'black');
plot(Time, Trans_Out_Spd, 'linewidth', 1, 'Color', 'red');
plot(Time, Wheel_Speed, 'linewidth',1, 'color', 'blue')
ylabel('Speed [rpm]')
xlabel('Timem [s]')
xlim([0, Time(end)]);
ylim([0, 6000]);
legend('Trans Input','Trans Output','Wheel Speed');

%% Plotting vehicle characteristics time trace to Engine speed, Engine Torque, Engine Power, 
%  And Engine fuel rate, Engine fuel consumption
% Data conversion from Double Timeseries

Eng_spd = Eng_Spd.Data(:,1);   % engine speed
Eng_trq = Eng_Trq.Data(:,1);   % engine torque
Eng_pwr = Eng_Pwr.Data(:,1);   % engine power
Eng_fuel_rate = Eng_Fuel_Rate.Data(:,1);   % engine fuel rate
Eng_fuel_consumption = Eng_Fuel_Consump.Data(:,1);   % engine fuel consumption
Veh_dist = Veh_Dist.Data(:,1);   % vehicle distance
Veh_spd = Veh_Spd.Data(:,1);    % vehicle speed

% Plotting Engine speed, Engine Torque, Engine Power,Engine fuel rate,Engine fuel consumption wrt Time 
figure(2)
subplot(2,2,1)
plot(Time,Eng_trq,'linewidth',1,'color','black')
xlabel('Time [s]')
ylabel('Torque [Nm]')
legend('Engine Torque')
grid on
subplot(2,2,2)
plot(Time,Eng_pwr,'linewidth',1,'color','blue')
xlabel('Time [s]')
ylabel('Power [KW]')
legend('Engine Power')
grid on
subplot(2,2,3)
plot(Time,Eng_fuel_rate,'linewidth',1,'color','red')
xlabel('Time [s]')
ylabel('Fuel Rate [%]')
legend('Engine Fuel Rate')
grid on
subplot(2,2,4)
plot(Time,Eng_fuel_consumption,'linewidth',1,'color','green')
xlabel('Time [s]')
ylabel('Fuel Consumption')
legend('Engine Fuel Consumption')
grid on

% Plotting fuel economy Vs Engine Fuel consumption 
figure(3)
plot(Eng_fuel_consumption,Eng_fuel_rate,'color','r')
xlabel('Fuel consumption')
ylabel('Fuel Rate [%]')
title('Fuel economy Vs Fuel Consumption')
grid on

%% Potting Accelerator pedal, Brake pedal and gear command with respect to time
figure(4)
subplot(2,1,1)
hold on
plot(Time, Acc_Pdl, 'linewidth', 1, 'Color', 'black');
plot(Time, Brk_Pdl, 'linewidth', 1, 'Color', 'red');
ylabel('Pedal [%]')
xlabel('Time [s]');
xlim([0, Time(end)]);
grid on
legend('Accel','Brake');
title('Acceleration & Brake Pedal wrt Time')

subplot(2,1,2)
plot(Time, Gear_Cmd, 'linewidth', 1, 'Color', 'black');
xlim([0, Time(end)]);
xlabel('Time [s]');
ylabel('Gear');
grid on
title('Gear command wrt Time')

% Plotting gear command vehicle desired with actual speed
figure(5)
subplot(2,1,1)
plot(Veh_spd, Gear_Cmd, 'linewidth', 1, 'Color', 'black');
xlabel('Speed [rpm]');
ylabel('Gear');
grid on
title('Gear command wrt vehicle speed')

subplot(2,1,2)
plot(Veh_dist, Gear_Cmd, 'linewidth', 1, 'Color', 'red');
xlabel('Distance [kmpl]');
ylabel('Gear');
grid on
title('Gear command wrt Distance')

%% 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]');
legend([p1 p3],{'Max Curve','Operating Points'});
axis([Eng_map_spd(1)*30/pi Eng_map_spd(end)*30/pi 0 Eng_map_trq(end)]);