Project 2
Aim:- Modeling of development of a forward energy-based fuel consumption model of a P1 hybrid vehicle.
Objectives:-
1] Tabulate the fuel economy numbers (kmpl) for UDDS and HWFET cycles. Compare these numbers with the baseline numbers for a 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, and vehicle distance using subplots.
5] Plot the engine operating points on the engine fuel map.
6] Plot motor speed, torque, and 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:-
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
For example, the main characteristics of the P1 MHEV.
1] ELectric Machine Performance:-
Maximum torque up to 34 Nm.
Maximum power: 10KW
Efficiency: Up to 94 Percent
2] Hybrid Modes:-
Idle stop and stop
Moving stop and start
Engine load shift
Torque assist
Torque boost
Energy recuperation
Brake generation
3] Advantages:-
Higher efficiency
The 12V starter can be removed
4] Disadvantages:-
Output torque is limited by the size of the electric machine
Energy recuperation affected by engine friction losses
High impact on existing vehicle architecture
The higher overall cost of the electrical components
Air cooling is not possible for electric machine
5] Overall characteristics:-
Torque Boosting capacity: High
Electrical energy recuperation: Medium
Driveability improvements: Medium
Electrical Creep/drive: Possible
In this model, We use Forward Model:-
It is also known as dynamic simulation. Dynamic models are used for detailed simulations. In this model force/torque/power is the input and the vehicle state variable velocity and acceleration are outputs. The models and simulations are more realistic due to physical casualty and hence appropriate for control development. There is a feedback loop to meet the desired vehicle state. It is mainly used to simulate a vehicle on a driving cycle to analyze the dynamic behavior of the system and helps significantly in control development.
Process:-
Load the Project2 folder as the Current Folder in Matlab.
Run the “Project2_InitFile.m” Matlab script.
The Drive cycle selection is done here.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Skill-Lync -> Hybrid Drives Development
% Project 2 - P1 Hybrid 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
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;
Eng_idle_spd = 600;
SOC_max = 0.9;
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);After running this coding file open the Simulink model.
Vehicle Model:-
1] Layout:-
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 for based on these results of fuel consumption and emissions the vehicle gets certified and it also forms a basis of uniform assessment. It is based on time, and velocity then it's all integrated and creates the output acceleration pedal and a 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.
Modification done in all Unit modeling. they showed in next figures.
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] Shiftlogic In this unit:-
8] Threshold Value in This controller:-
9] Electric Motor Control Unit:-
10] Brake Control Unit:-
In this calculate brake torque and then all three control signals output is give to powertrain.
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:-
13] Crankhub:-
14] 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.
15] Torque Converter:-
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 this takes tractive force and road load. It is dictates vehicle speed based on tractive force and road load.
Battery Modeling:-
19] Estimated storage system:-
In this we give input as power then it multiply and give to pack current. then from soc estimation meet output SOC its give to terminal voltage as input and then meet terminal voltage as output.
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] Pack Current:-
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.
%% 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.TransOutSpd*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.WheelSpeed; % Wheel speed [kmph]
Eng_Fuel_Rate = out.Eng_Fuel_Rate % Engine fuel rate [%]
EM_Speed = out.EMSpd*18/5; % Electric Motor Speed
EM_Power = out.EMPwr; % Electric Motor Power
EM_Torque = out.EMTrq; % Electric Motor Torque
Term_Volt = out.term_volt; % Terminal Voltage of battery
Soc = out.SOC; % State Of Charge
Pack_Current = out.Pack_Current; %Pack current of battery
%% 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 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
EM_speed = EM_Speed.Data(:,1); % motor speed
EM_power = EM_Power.Data(:,1); % Motor Power
EM_torque = EM_Torque.Data(:,1); % Motor Torque
Pack_current = Pack_Current.Data(:,1); %pack current of battery
State_of_charge = Soc.Data(:,1); %state of charge
Term_voltage = Term_Volt.Data(:,1); % terminal Voltage of battery
%% 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 Engine speed, Engine Torque, Engine Power,Engine fuel rate,Engine fuel consumption wrt Time
figure(2)
subplot(4,1,1)
plot(Time,Eng_trq,'linewidth',1,'color','black')
xlim([0, Time(end)]);
xlabel('Time [s]')
ylabel('Torque [Nm]')
legend('Engine Torque')
grid on
subplot(4,1,2)
plot(Time,Eng_pwr,'linewidth',1,'color','blue')
xlim([0, Time(end)]);
xlabel('Time [s]')
ylabel('Power [KW]')
legend('Engine Power')
grid on
subplot(4,1,3)
plot(Time,Eng_fuel_rate,'linewidth',1,'color','red')
xlim([0, Time(end)]);
xlabel('Time [s]')
ylabel('Fuel Rate [%]')
legend('Engine Fuel Rate')
grid on
subplot(4,1,4)
plot(Time,Eng_fuel_consumption,'linewidth',1,'color','green')
xlim([0, Time(end)]);
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)]);
%% State of Charge, Pack Current, And Terminal Voltage with respect to Time
figure(6)
subplot(3,1,1)
plot(Time,Pack_current,'linewidth',1,'color','black')
xlim([0, Time(end)]);
xlabel('Time [s]')
ylabel('Current [W]')
legend('Pack Current')
grid on
subplot(3,1,2)
plot(Time,State_of_charge,'linewidth',1,'color','blue')
xlim([0, Time(end)]);
xlabel('Time [s]')
ylabel('Charging [%]')
legend('State Of Charge')
grid on
subplot(3,1,3)
plot(Time,Term_voltage,'linewidth',1,'color','red')
xlim([0, Time(end)]);
xlabel('Time [s]')
ylabel('Voltage [V]')
legend('Terminal Voltage')
grid on
%% Motor Speed, Torque, Motor input power with respect to Time
figure(7)
subplot(3,1,1)
plot(Time,EM_power,'linewidth',1,'color','black')
xlim([0, Time(end)]);
xlabel('Time [s]')
ylabel('Power [W]')
legend('Electric Motor Power ')
grid on
subplot(3,1,2)
plot(Time,EM_torque,'linewidth',1,'color','blue')
xlim([0, Time(end)]);
xlabel('Time [s]')
ylabel(' Torque [Nm]')
legend('Electric Motor Torque')
grid on
subplot(3,1,3)
plot(Time,EM_speed,'linewidth',1,'color','red')
xlim([0, Time(end)]);
xlabel('Time [s]')
ylabel('Speed [Rpm]')
legend('Electrical Motor Speed')
grid on
%% Plotting EM Operating Points on motor input power Map
figure('Name','Electric Motor Operating Points');
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]');
legend([p1 p3],{'Max Curve','Operating Points'});
axis([EM_map_spd(1)*30/pi EM_map_spd(end)*30/pi 0 EM_map_trq(end)]);Que:- Tabulate the fuel economy numbers (kmpl) for UDDS and HWFET cycle. Compare these numbers with the baseline numbers for conventional vehicle model from Project 1.
Answer:-
Fuel Economy Numbers for project 2
| S.No | Drive cycle | Fuel Economy Number (KMpl) |
| 1 | UDDS | 15.0773 |
| 2 | HWFET | 17.1613 |
As we see the fuel economy is high in HWFET compared to UDDS. It is because in urban driving the vehicle encounters more traffic and it has to stop for fever distance and it consumes more fuel at the starting. In HWFET the vehicle encounters no traffic and it moves without use of too much braking so it will have more fuel economy number.
Comparing with fuel economy numbers for project 1
| S.No | Drive cycle | Fuel Economy Number (KMpl) |
| 1 | UDDS | 14.209 |
| 2 | HWFET | 16.503 |
As we see the fuel economy numbers for project 2 are bit higher when compared to project 1 because of implementing the electric motor as it is P1 hybrid it may not have much variation in the fuel economy but as we implement other architechture it will increase by huge amount.
