Project 1
Objective: 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)Writing script in MATLAB to load all the variable 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 barke 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 create graphs.
Theory:
1) In a conventional vehicle the power is generated by an internal combustion engine that converts the chemical energy in the fuel to mechanical energy.
2) This energy reach the wheels through a drivetrain which contains the transmission, defferential components.
3) The efficiency of an IC engine is defined as the raio of workdone to the energy supplied to an engine. The different types of efficiencies are:
a. Mechanical efficiency
b. Indicated thermal efficiency
c. Brake thermal efficiency
d. Volumetric efficiency
e. overall efficiency
MATLAB scripts-
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 model run this initialization script.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Skill-Lync -> Hybrid Drives Development
% Project 1 - Conventional Vehicle Model
% By - Harsh Sahu
% 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);Simulink Model:
1)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.
2)the accelerator and brake pedal data is generated using the drive cycle data in which is fed through lookup table.
Driver block:
Contoller block:
1)The controller block is the brain of the, representing the electronic control units. Based on the driver inputs.
2) The data inputs are fed to the powertrain block which represents the drivetrain of the vehicle. It consists of an 'engine' connected to 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.
Powertrain block:
The engine block:
The transmission block:
The differential block:
The wheels block:
The vehicle dynamics block:
The equation used here is:
Post processing:
1)The data from the simulink model was transferred to MATLAB workspace using 'To workspace' block.
2)A post processing MATLAB code was used to generate the necessary plots.
The code:
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Skill-Lync -> Hybrid Drives Development
% Project 1 - Conventional Vehicle Model
% By - Harsh Sahu
% 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 = 2000;
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.Wheel_speed.Data; % Wheel speed [kmph]
Eng_Fuel_rate = out.Veh_desired_spd; % Desired Vehicle speed [kmph]
%% 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 consumption vs Fuel rate
figure(1)
hold on
grid on
plot(Time, Eng_Fuel_Consump.Data, 'linewidth', 1, 'Color', 'black');
plot(Time, Eng_Fuel_rate.Data, 'linewidth', 1, 'Color', 'red');
xlabel('Fuel Consumption')
ylabel('Fuel Rate')
xlim([0, Time(end)]);
legend('Fuel Consumption','Fuel Rate');
%% Plotting vehicle characteristics time trace Engine, Transmission Input, Transmission Output and Wheel speed
figure(2)
hold on
grid on
plot(Time,Eng_Spd.Data,'linewidth', 1, 'Color', 'g' );
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' )
xlabel('Time [s]')
ylabel('Speed [rpm]')
xlim([0, Time(end)]);
ylim([0, 6000]);
legend('Transmission Input','Transmission Output');
%% Plotting vehicle characteristics time trace engine torque, engine power, fuel rate and fuel consumption
figure(3)
subplot(2,2,1)
plot(Time, Eng_Trq.Data, 'linewidth', 1, 'Color', 'g');
xlabel('Time [s]');
ylabel('Torque [Nm]');
legend('Torque')
subplot(2,2,2)
plot(Time, Eng_Pwr.Data, 'linewidth', 1, 'Color', 'black');
xlabel('Time [s]');
ylabel('Power [kW]');
legend('Power')
subplot(2,2,3)
plot(Time, Eng_Fuel_rate.Data, 'linewidth', 1, 'Color', 'red');
xlabel('Time [s]');
ylabel('Fuel Rate [%]');
legend('Fuel Rate')
subplot(2,2,4)
plot(Time, Eng_Fuel_Consump.Data, 'linewidth', 1, 'Color', 'blue');
xlabel('Time [s]');
ylabel('Fuel Consumption [kmpl]');
legend('Fuel Consumption')
%% Plotting vehicle characteristics time trace accelerator and brake pedal, gear command, vehicle desired and actual speed.
figure(4)
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, Veh_Desired_Sped.Data, 'LineWidth',1,'Color','black');
plot(Time, Veh_Spd.Data, 'LineWidth',1,'Color','red');
ylabel('Speed [rpm]')
xlim([0, Time(end)]);
legend('Vehicle Desired Speed','Vehicle Actual Speed');
subplot(3,1,3)
hold on
grid on
plot(Time, Gear_Cmd, 'LineWidth',1,'Color','black');
plot(Time, Brk_Pdl, 'LineWidth',1,'Color','red');
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 p3],{'Max Curve','Operating Points'});
axis([Eng_map_spd(1)*30/pi Eng_map_spd(end)*30/pi 0 Eng_map_trq(end)]);
The plots:
UDDS cycle-
1) Fuel consumption vs Fuel rate
2)Vehicle characteristics time trace Engine, Transmission Input, Transmission Output and Wheel speed
3)Plotting vehicle characteristics time trace engine torque, engine power, fuel rate and fuel consumption
4)Plotting vehicle characteristics time trace accelerator and brake pedal, gear command, vehicle desired and actual speed
5)Plotting engine operating points on engine fuel map
HWFET cycle-
1) Fuel consumption vs Fuel rate
2)Vehicle characteristics time trace Engine, Transmission Input, Transmission Output and Wheel speed
3)Plotting vehicle characteristics time trace engine torque, engine power, fuel rate and fuel consumption
4)Plotting vehicle characteristics time trace accelerator and brake pedal, gear command, vehicle desired and actual speed
5)Plotting engine operating points on engine fuel map
Conclusion: The forward energy-based fuel consumption model of a conventional vehicle was developed using MATLAB and SIMULINK and plots were obtained for UDDS and HWFET cycle