Project 2

AIM:- Modeling of development of a forward energy-based fuel consumption model of a P1 hybrid vehicle.

OBJECTIVES:-

1. abulate the fuel economy numbers (kmpl) for UDDS and HWFET cycle. Compare these numbers with the baseline numbers for conventional vehicle.
2. Plot the time trace for engine, transmission input, transmission output and wheel speed on one plot.
3. Plot engine torque, engine power, fuel rate and fuel consumption using subplots.
4. Plot accelerator and brake pedal, gear command, vehicle desired and actual speed, vehicle distance using subplots.
5. Plot the engine operating points on the engine fuel map.
6. Plot motor speed, torque, motor input power using subplots.
7. Plot pack voltage, current and SoC using subplots.
8. Plot the motor operating points on the motor input power map, with the motor max motoring and generating torque curves.
9. Generate the plots for UDDS and HWGET drive cycles

THEORY:-

Introduction:-

• Hybrid electric vehicles are powered by an internal combustion engine and one or more electric motors, which uses energy stored in batteries. A hybrid electric vehicle cannot be plugged in to charge the battery. Instead, the battery is charged through regenerative braking and by the internal combustion engine. The extra power provided by the electric motor can potentially allow for a smaller engine. The battery can also power auxiliary loads and reduce engine idling when stopped. Together, these features result in better fuel economy without sacrificing performance.

P1 Mild Hybrid Electric Vehicle:-

• The P1 architecture, with the electric machine connected directly to the crankshaft, is the solution adopted by Honda on their first generation Integrated Motor Assist (IMA) technology. The electric motor functions as a generator, during vehicle deceleration, as an engine starter, and as a motor (to assist the engine) during vehicle accelerations. one of the biggest advantage of this solution is that the electric motor can provide higher torque than the BiSG, since there is no belt limitation (due to slip). However, since there is no speed / torque ratio between the electric machine and crankshaft, the torque requirements on the electric motor can be quite demanding.
• Two examples of P1 MHEV architectures are:

• Honda Insight Hybrid 2009 (with Integrated Motor Assist technology)
• Mercedes Benz S400 Bluehybrid 2010

Forward-Modelling Approach:-

• The forward modelling approach is also known as cause-effect, engine-to-wheel or rear-to-front method. The direction of calculation is the same as the direction of positive power flow, from engine-to-wheel.
• This approach is based on vehicle dynamics equations and the behaviour of each powertrain components and their dynamic interaction.
• Moreover, a driver controller is required to control the vehicle to follow a desired speed and set the start of the calculations. The controller is implemented to model the driver that will either push the accelerator or the brake pedal to match the desired speed which enables to study the driver behaviour. The controller is used as part of a feedback loop that will determine the energy required to drive the vehicle.

Project-Implementation In Matlab:-

• Load the Project2 folder as the Current Folder in Matlab.
• Run the “Project2_InitFile.m” Matlab script.
• The Drive cycle selection is done in Initfile.

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Skill-Lync -> Hybrid Drives Development
% Project 2 - Conventional Vehicle Model
% By - SHRIKANT GAIKWAD 

% 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);

1] Simulink P1 Hybrid Architecture or Vehicle Model:

• The Simulink model for the convection model is created using 3 main subblocks for the driver model, control model and powertrain block.
• The actual vehicle speed is given as feedback to the driver block, and the driver block gives the controller block the required acceleration or brake output, while the controller block provides control signals for engine torque, gear shifting and brake torque to the Powertrain model.

2] Driver:-

• 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.

3] Controller:-

• 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 desired motor torque and desired brake torque. These inputs are fed to the ‘Powertrain’ block which represents the drivetrain of the vehicle. In this we require to create stateflow block it explain in next figure

4] Stateflow for Controller:-

• In this we created four conditions as stop, start, drive and regenration braking. The initial block represent the stop condition. In which the engine is off. The engine and motor throttle conditions are zero. Then the second block represent start condition. In which the mode is 1 the electric motor throttle is only used to provide the required torque and power to the vehicle. the engine is off and engine throttle conditionis zero.
• The state 1 and state 2 are connected using the links i.e. it moves from state 1 to state 2 when acceleration is less than one or SOC is less then the minimum SOC.
• State 3 Represtents mode 2 ii.e. engine is on and the engine throttle is also having positive value from the driver but the electric motor throttle is zero. It changes form state 2 to state 3 when engine speed is graeter than or equal to engine idle speed.
• state 4 represents regenrative braking which is model 3 In this state the engine is on but the engine throttle is having no input from driver whereas the electric moto receives the negative power due to braking.
• The inputs are given to chart is Acceleration, barke, engine speed, vehicle speed, SOC, and clutch lockup.
• The output we get from the chart is mode, engine condition, engine throttle condition, and electric motor throttle condition.

5] 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.

6] 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.

7] In the Shiftlogic unit :-

• The transmission control block controls the gear shifting using the study flow Variable chart.

9] Electric Motor Control Unit:-

• Electric motor control unit control the motor parameters according to close loop feedbacck system signal.after comparing output signal then EM unit gives required input.

10] Brake Control Unit:-

• Brake Control unit Produce required brake torque according to the brake pedal input and passes the brake torque in to the wheel block in the transmission model.

P1 Hybrid Powertrain Model:-

• The powertrain model includes all the components that convert the power of the engine into vehicle motion.

• This includes Engine,Motor,Battery, Transmission, Differential, Wheels and the vehicle body dynamics subsystems.

11] 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.

12] Electric Motor:-

• In motor subsystem also, based on the the motor torque request from the controller and engine speed the torque and input power to the motor is calculated. The engine speed is considered because it is considered that engine and motor are running at the same speed in P1 hybrid Vehicle. Figure 13 shows the simulink block arrangement for the Motor subsystem.

13] Crank:-

• power of engine and electric motor given to the crank.this crank connected to the transmission system according to driver need power transmitted to the wheel.

14] Transmission:-

• In the transmission subsystem,based on the input crank torque and Transmission In speed,the torque from the torque converter is calculated. Basedon the gear command from the controller, gear ratio is selected by considering the gear and gear ratio data from the lookup table. product of gear ratio and torque from the torque converter gives us the total output torque from the transmission. Based on the nature of torque its efficiency is assigned and output torque is calculated. Figure 15 shows the block arrangement for the transmission subsystem.

15] Torque Converter:-

• A torque converter is a type of fluid coupling which is used to transfer rotating power from the engine of a vehicle to the transmission.

16] 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.

17] Wheel:-

• 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.

18] Vehicle Dynamics:-

• In vehicle body subsystem, all the resistive/ resistance force is calculated.The resistance force is subtracted from the total tractive force and result is divided by the mass of the vehicle to obtain the accleration of a vehicle. The integration of accleration is done to find out the velocity of the vehicle. This velocity is again reverted back to the driver block and based on which driver applies brake or accleration by comparing the velocity with the given drive cycle. Figure 16 shows the simulink block arrangement for the Vehicle body subsystem.Figure 17 shows the above mentioned subsystem arrangement for the powertrain block.

19] Battery System:-

• In battery subsystem,based on the input power demand from the motor, the current from the battery is considered. And based on the current drawn , SOC level of the battery is calculated by considered the technique called as columb counting. The Voltage of the battery being the function of the SOC level of the battery, so the open circuit voltage is calculated by SOC level of battery.Figure 14 shows the simulink block arrangement for the battery subsystem.

20] Terminal Voltage:-

• In this use input SOC it is connected to 1d lookup table 1st table variable interpolated as state of charge and open voltage circuit. In 2nd table variable interpolated as resistance discharge and state of charge and in 3rd table variable interpolated as resistance charge and state of charge. Then it is passed to switch block for controlling the threeshold. then they give voltage limits as max volts and min volts. then meet terminal Voltage.

21] Soc Estimation:-

• In this we integrate pack current and convert it rad to amp then saturated and meet SOC.
• Then we create one coding file for creating plots and to meet all answers. that file shown in next.

Project 2 Processing File:-

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Skill-Lync -> Hybrid Drives Development
% Project 1 - Conventional Vehicle Model
% By - shrikant gaikwad 

% 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 P1 HYBRID 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_Dst = out.veh_Dst/1000;   % Distance traveled by vehicle [km]
veh_Spd = out.veh_spd*18/5;     % Vehicle speed [kmph]
wheel_speed = out.wheel_speed;   % wheel speeed [Kmph} 
Eng_Fuel_rate = out.Eng_Fuel_Rate; % engine fuel rate [%}
M_speed = out.motorspeed*18/5;         % motor speed
M_power = out.MotorPower;       % motor power
M_torque = out.motorTorque;      % motor torque
M_voltage = out.Term_Volt;       % battery terminal voltage 
soc = out.SOC;                   % battery state of charge
current = out.current;           % battery current
Drive_Velocity = out.Velocity;  % Velocity of drive cycle 
%% 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_Dst(end)/(Eng_Fuel_Consump(end)/1000/rho_petrol);    % Fuel economy [kmpl] 
%% (b) Plotting vehicle characteristics time trace transmission IN/OUT 
figure(1);
subplot(311);
plot(Time, Trans_In_Spd, 'linewidth', 1, 'Color', 'black');grid;
subplot(312);
plot(Time, Trans_Out_Spd, 'linewidth', 1, 'Color', 'red');grid;
subplot(313);
plot(Time, wheel_speed, 'linewidth', 1, 'Color', 'blue');grid;
ylabel('Speed [rpm]');
xlim([0, Time(end)]);
ylim([0, 6000]);
%% (c) Plotting Engine speed, Engine Torque, Engine Power,Engine fuel rate,Engine fuel consumption wrt Time 
% figure(2);
% subplot(311);
% plot(Eng_Trq, 'linewidth',1, 'Color', 'black');grid;
% xlim([0, Time(end)]);
% title('Engine Torque [Nm]');
% legend('Engine Torque');
% subplot(312);
% plot(Eng_Pwr, 'linewidth',1, 'Color', 'red');grid;
% xlim([0, Time(end)]);
% title('Engine Power [KW]')
% legend('engine power');
% subplot(313);
% plot(Eng_Fuel_rate, 'linewidth',1,'color','red');grid;
% xlim([0, Time(end)]);
% xlabel('Time [s]');ylabel('Fuel Rate [%]');
% legend('Engine Fuel Rate')
% subplot(414);
% plot(Eng_Fuel_Consump, 'linewidth',1,'color','red');
% xlim([0, Time(end)]);
% xlabel('Time [s]');ylabel('Fuel consumption [%]');
% legend('Engine Fuel consumption');
%% (d)Potting Accelerator pedal, Brake pedal and gear command
figure(3);
subplot(411);
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');

% Plotting gear command vehicle desired with actual speed
subplot(413);
hold on
grid on
plot(veh_Spd, Gear_cmd, 'linewidth', 1, 'Color', 'black');
xlabel('Speed [rpm]');
ylabel('Gear');
title('Gear command wrt vehicle speed')
subplot(414);
hold on
grid on
plot(veh_Dst, Gear_cmd, 'linewidth', 1, 'Color', 'black');
xlabel('Speed [rpm]');
ylabel('Gear');
title('Gear command wrt vehicle distance')
%% (e) Plotting engine operating points on engine fuel map
figure(4);
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)]);

%% (f) Plotting Emotor characteristics time trace
figure(5);
subplot(311);
plot(Time, M_torque, 'linewidth', 1, 'Color', 'red');hold;grid;
title('time vs torque');xlabel('speed');ylabel('torque');

subplot(312);
plot(Time, M_power, 'linewidth', 1, 'Color', 'green');hold;grid;
title('TIME vs MOTOR POWER');xlabel('time');ylabel('motor power');

subplot(313);
plot(Time, M_speed, 'linewidth', 1, 'Color', 'black');hold;grid;
title('time vs speed');xlabel('speed');ylabel('torque');

%% (g) plotting voltage,current,soc(state of charge)
figure(6);
subplot(321);
plot(Time, soc, 'linewidth', 1, 'Color', 'black');hold;grid;
title('TIME vs SOC');xlabel('time');ylabel('SOC');

subplot(322);
plot(Time,current, 'linewidth', 1, 'Color', 'red');hold;grid;
title('TIME vs current');xlabel('time');ylabel('current');

subplot(323);
plot(Time, M_voltage, 'linewidth', 1, 'Color', 'red');hold;grid;
title('TIME vs voltage');xlabel('time');ylabel('voltage');

%% (h)  Plotting EM Operating Points on motor input power Map
figure(7);
hold on
grid on
title('Electric Motor Operating Points','fontsize',12);
p1=plot(EM_map_spd*30/pi,EM_max_trq,'linewidth',2,'color','r');
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('motor Speed [rpm]');
ylabel('motor Torque [Nm]');
title('motor input power map [g/s]');
p4 = plot(Eng_Spd,Eng_Trq,'.','color','k');
legend([p1 p4],{'Max Curve','Operating Points'});
axis([EM_map_spd(1)*30/pi EM_map_spd(end)*30/pi 0 EM_map_trq(end)]);
%% (j) Plot for HWFET cycles
% figure(8);
% plot(Time, Drive_Velocity, 'linewidth', 1, 'Color', 'red');hold;grid;
% title('DRIVE CYCLE HWFET ');xlabel('time');ylabel('Velocity');

 %% (j) Plot for UDDS cycles
figure(9);
plot(Time, Drive_Velocity, 'linewidth', 1, 'Color', 'black');hold;grid;
title('DRIVE CYCLE UDDS ');xlabel('time');ylabel('Velocity');
%% (c) Plotting Engine speed, Engine Torque, Engine Power,Engine fuel rate,Engine fuel consumption wrt 
figure(10);
subplot(311);
plot(Eng_Trq, 'linewidth',1, 'Color', 'black');grid;
xlim([0, Time(end)]);
title('Engine Torque [Nm]');
legend('Engine Torque');
subplot(312);
plot(Eng_Pwr, 'linewidth',1, 'Color', 'red');grid;
xlim([0, Time(end)]);
title('Engine Power [KW]')
legend('engine power');
subplot(313);
plot(Eng_Fuel_rate, 'linewidth',1,'color','red');grid;
xlim([0, Time(end)]);
xlabel('Time [s]');ylabel('Fuel Rate [%]');
legend('Engine Fuel Rate')

RESULTS:

UDDS:

(a) Fuel economy numbers (kmpl) for UDDS cycle

• from the below two result we have observed in improved fuel economy in hybrid vehicle model.
• improved fuel economy also observed in engine and motor fuel consumtion map

PROJECT 1 CONVENTIONAL VEHICLE MODEL:-

PROJECT 2 P1 HYBRID VEHICLE MODEL:-

• improved fuel economy due to hybridization

(b) Plotting vehicle characteristics time trace transmission IN/OUT

figure(1);