Hybrid Vehicle Using Matlab And Simulink To Analyze Data
OBJECTIVE:
To develop a forward energy-based fuel consumption model of a P1 hybrid vehicle using matlab and simulink to analyze data and generate plots.
THEORY:
A hybrid electric vehicle (HEV) is a type of hybrid vehicle that combines a conventional internal combustion engine (ICE) system with an electric propulsion system (hybrid vehicle drivetrain). The presence of the electric powertrain is intended to achieve either better fuel economy than a conventional vehicle or better performance. There is a variety of HEV types and the degree to which each function as an electric vehicle (EV) also varies. The most common form of HEV is the hybrid electric car, although hybrid electric trucks (pickups and tractors), buses, boats and aircraft also exist.
In this project, we will deal with the development of an hybrid vehicle with P1 architecture. In this type of architecture ,the electric machine is connected directly with the crankshaft of the internal combustion engine.
MODEL:
INITIAL MATLAB CODE:
- A matlab code “Project2_InitFile.m” was created to load the variable to the workspace. In this project,Honda Insight motor and battery are considered for integrating with a typical midsize car with a 1.9L engine and a 4-speed automatic transmission for the hybrid application. 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.
The CODE:
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Skill-Lync -> Hybrid Drives Development
% Project 2 - P1 Hybrid Electric Vehicle Model
% 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
load Vehicle_Data/EM_Honda_Insight_10kW
load Vehicle_Data/ESS_NiMH6
ESS_init_soc = 0.8;
ESS_soc_max = 0.9;
ESS_soc_min = 0.6;
%% 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 SIMULINK 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.
- This accelerator and brake pedaldata is generated using the drive cycle data in which is fed through look up table.
DRIVER BLOCK:
CONTROLLER BLOCK:
- 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 and EM torque and clutch lock by with the help of a supervisory controller .
POWERTRAIN:
- The data inputs are fed to the ‘Powertrain’ block which represents the drivetrain of the vehicle. It consists of an ‘Engine’ and 'Electric Motor' connected via crank hub and 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.
THE ENGINE BLOCK:
ELECTRIC MOTOR BLOCK:
THE TRANSMISSION BLOCK:
THE DIFFERENTIAL BLOCK:
THE WHEELS BLOCK:
THE VEHICLE DYNAMICS BLOCK:
- The equation used here is:
POST PROCESSING:
- The Data from the SIMULINK model was transferred to matlab workspace using 'To Workspace' block
- A post processing MATLAB code was used to generate the necessary plots.
THE CODE:
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Skill-Lync -> Hybrid Drives Development
% Project 2 - P1 Hybrid Electric Vehicle Model
% 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_speeed = out.Wheel_speed.Data; % Wheel speed [kmph]
Eng_Fuel_rate = out.Eng_Fuel_Rate; % Engine Fuel Rate [%]
Veh_Desired_Sped = out.Veh_desired_spd; % Desired Vehicle Speed [kmph]
EM_sped = out.EMspeed;
EM_torq = out.EMtorque;
EM_PWR = out.EMinpwr;
Pack_currnt = out.packCurnt;
Pack_Voltg = out.packVoltg;
S_OC = out.S_o_C;
%% 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_speeed,'LineWidth',1,'Color','blue');
xlabel('Time [s]')
ylabel('Speed [rpm]')
xlim([0, Time(end)]);
ylim([0, 6000]);
legend('Transmission Input','Transmission Output','Wheel Speed','Engine Speed');
%% 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('Engine 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');
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)]);
%% Plotting motor speed, torque, motor input power
figure(7)
subplot(2,2,1)
plot(Time,EM_torq.Data,'LineWidth',1,'Color','g')
xlabel('Time [s]')
ylabel('Torque [Nm]')
legend('Torque')
subplot(2,2,2)
plot(Time,EM_PWR.Data,'LineWidth',1,'Color','black')
xlabel('Time [s]')
ylabel('Power [kW]')
legend('Engine Power')
subplot(2,2,3)
plot(Time,EM_sped.Data,'LineWidth',1,'Color','red')
xlabel('Time [s]')
ylabel('EM speed')
legend('EM SPEED')
%% Plotting pack voltage, current and SoC
figure(8)
subplot(2,2,1)
plot(Time,Pack_currnt.Data,'LineWidth',1,'Color','g')
xlabel('Time [s]')
ylabel('CURRENT')
legend('current')
subplot(2,2,2)
plot(Time,Pack_Voltg.Data,'LineWidth',1,'Color','black')
xlabel('Time [s]')
ylabel('Voltage')
legend('Voltage')
subplot(2,2,3)
plot(Time,S_OC.Data,'LineWidth',1,'Color','red')
xlabel('Time [s]')
ylabel('SOC')
legend('SOC')
%% Plotting EM operating points on EM map
figure('Name','Motor Operating Points');
hold on
grid on
title('Engine Operating Points','fontsize',12);
p1=plot(EM_map_spd*30/pi,EM_max_trq,'linewidth',2,'color','r');
p4=plot(EM_map_spd*30/pi,EM_max_gen_trq,'linewidth',2,'color','black');
p2=line([EM_map_spd(end)*30/pi EM_map_spd(end)*30/pi],[0 EM_max_trq(end)]);
set(p2,'linewidth',1,'linestyle','--','color','k');
p3=line([EM_map_spd(1)*30/pi EM_map_spd(1)*30/pi],[0 EM_max_trq(1)]);
set(p3,'linewidth',1,'linestyle','--','color','k');
[c,h] = contour(EM_map_spd'*30/pi,EM_map_trq,EM_inpwr_map');
clabel(c,h);
xlabel('EM Speed [rpm]');
ylabel('EM Torque [Nm]');
title('EM Input Power');
legend([p1 p4 p3],{'Max Curve','Regen Curve','Operating Points'});
THE PLOTS:
UDDS CYCLE:
(1) Fuel Consumption vs Fuel Rate:
(2) Vehicle characteristics time trace Engine,Transmission Input, Transmission Output and Wheel Speed:
(3) Vehicle characteristics time trace engine torque, engine power, fuel rate and fuel consumption:
(4) Vehicle characteristics time trace accelerator and brake pedal, gear command, vehicle desired and actual speed:
(5) Engine operating points on engine fuel map:
(6)Motor speed, Torque, Motor input power Characteristics:
(7) Pack Voltage, Pack Current, SOC Characteristics:
(8) EM Operating Points:
(1) Fuel Consumption vs Fuel Rate:
(2) Vehicle characteristics time trace Engine,Transmission Input, Transmission Output and Wheel Speed:
(3) Vehicle characteristics time trace engine torque, engine power, fuel rate and fuel consumption:
(4) Vehicle characteristics time trace accelerator and brake pedal, gear command, vehicle desired and actual speed:
(5) Engine operating points on engine fuel map:
(6)Motor speed, Torque, Motor input power Characteristics:
(7) Pack Voltage, Pack Current, SOC Characteristics:
(8) EM Operating Points:
CONCLUSION:
The Forward energy-based fuel consumption model of a P1 Hybrid ELectric vehicle was developed using MATLAB and SIMULINK and the plots were obtained for UDDS and HWFET cycles.