Project 2
AIM:
The main goal of this project is to understand the functionality of a P1 hybrid and be able to model it. To quantify the improvement in fuel economy numbers for the hybrid vehicle (kmpl), compared to the conventional vehicle, on the urban cycle (UDDS) and highway cycle (HWFET). Also, to analyze and understand the vehicle operating points in terms of engine and motor speed, torque, transmission speeds, pedal positions, gear, distance traveled, battery voltage, current, SoC etc. Modify Conventional vehicle Simulink model into a hybrid vehicle model. Write scripts in MATLAB to load all the variables needed to run the simulation model. Analyze data and create plots using MATLAB scripts.
OBJECTIVES:
a. 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.
b. Plot the time trace for engine, transmission input, transmission output and wheel speed on one plot.
c. Plot engine torque, engine power, fuel rate and fuel consumption using subplots.
d. Plot accelerator and brake pedal, gear command, vehicle desired and actual speed, vehicle distance using subplots.
e. Plot the engine operating points on the engine fuel map.
f. Plot motor speed, torque, motor input power using subplots.
g. Plot pack voltage, current and SoC using subplots.
h. Plot the motor operating points on the motor input power map, with the motor max motoring and generating torque curves.
i. Write down appropriate brief comments on each of these plots, describing the vehicle behavior throughout the drive cycle.
j. Generate the plots for both drive cycles
THEORY:
Crankshaft mounted electric machine (P1):
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.
Fig: MHEV P1 architecture – Integrated Starter Generator (ISG)
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.
Example of P1 MHEV architecture is:
Honda Insight Hybrid 2009 (with Integrated Motor Assist technology)
Fig: Integrated Motor Assist (IMA) for mild hybrid , Credit: Honda
The primary advantage of a P1 mild hybrid architecture, compared with P0, is the removal of the belt drive. This means that the efficiency increases a bit (no more belt losses) and the electric machine torque can be higher in terms of amplitude and response (no more belt slip).
The functions (modes) performed by this mild hybrid topology are similar with those of a BiSG (P0), but, overall, P1 configurations have two big disadvantages: higher cost and higher impact on the the existing vehicle architecture. Therefore, vehicle manufacturers and system suppliers are not investing in the further development of crankshaft-mounted integrated starter generator solution for MHEV applications.
VEHICLE MODEL: (PRE PROCESSING MATLAB FILE):
For this simulink model first need to load the all required variable using MATLAB initialization script which is given in the challange. So, first we load this file and run this data and then creating simulink model for this vehicle. Drive cycle selection is also done from here.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Skill-Lync -> Hybrid Drives Development
% Project 1 - Conventional Vehicle Model
% By - Ullekh Gambhira
% 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);There are different drive cycle which is selcted by entering the number of drive cycle in "Drive_Cycle_Select".
Here, The number is defined for diiferent drive cycle as per below details.
1 UDDS
2 HWFET
3 FTP
4 US06
5 NEDC
6 WLTP
Now, For this Vehicle the simulink model is created as per below.
SIMULINK MODEL:
The simulink model is same as project-1. here the model contains three major blocks.
These three Blocks are subsystem contains 1)Driver 2)Controller and 3)PowerTrain.
Here in the above model the driver block is give the input to controller as Acceleration and Brake, and then controller give the different control signals as a input to the powertrain subsystem. and in last the Driver subsystem get the feedback as a actual velocity from the powertrain block.
Driver Model:
The driver model generates the Output brakes and accelator using input as velocity. here for this use the drive cycle data in 1-D lookup table as an input.
The PI controller controls the error between the required drive cycle and actual vehicle speed by providing acceleration and
brake pedal output to the controller.
Controller:
In this subsystem the all control is doing here so this is the heart of the vehicle. There are 4 subsystem blocks added in controller model. and there are Engine control unit, Transmission control unit, EMotor control unit and brake control unit. Also the stateflow block is used which is for Mode selection.
The controller generates engine torque, motor torque, transmission gear and brake torque. These inputs are fed to the
'Powertrain' block using bus bar which represents the drivetrain of the vehicle.
In the mode selection blocks the Input and Output is define as below figure. The below image shows the model explorer for mode selection stateflow. Here three constant inputs are used SOC_min,SOC_max and Eng_idle_spd .
ModeSelection:
Stateflow block is used to represent the Mode selection unit, which decides the operating mode. While it is start/stop mode or drive mode or regen braking mode for each modes the engine drive and the e-motor drive are controlled.
The input to the stateflow chart is acceleration, brake, Engine speed, vehicle speed, SOC and the clutch lookup. The state flow output to the individual controllers are the Mode, Engine On/Off, Engine input throttle and Electric Motor input throttle.
In the Stateflow the condition are given as below and inputs are given as below image.
Engine Control Unit:
Engine control unit contains the blocks Lookup table and subsystem block and gain , sum, product and saturation blocks.
Engine control unit take input as a lookup table for the Maximum torque curve and minimum torque curve and using this it is product with the Throttal Idel which is output from the idel speed controller and then after using gain block the both are divided and given output as a Eangine required torque.
In the Idel speed controller subsystem using engine idel speed as input and engine actual speed it is calculated the idel throttal as output and this is used as a input in the engine control unit.
Transmission Control Block:
The transmission control block controls the gear shifting using the state flow variable chart.
In Transmission control unit the input is Throttle and Vehicle Speed in mph. and getting the output from the stateflow we gate the gear number.
The Gear Shift Logic is as per the below image:
Here, The gear shifting is controlled according to the vehicle speed and throttle input. It is determined whether the clutch is locked up or not, if the gear selection is greater than or equal to 3, the clutch will lock. And The gear command is passed to the transmission block to select the desired gear ratio.
The Simulink Function containing Thresold Calculation is given in the below image:
Electric Motor Control Unit (EM Control Unit):
The EM Control unit take Engine Speed as input and analys it and using this gives the output as EM torque required. here the use of lookup table which is contain Maximum torque curve for EM and Minimum torque curve for EM.
Brake Control Unit:
Brake control unit gives the brake torque as output using the calculating by input of brake value. the calculation eqation is given in the below image.
PowerTrain:
The powertrain subsystem includes all the components that convert the power of the engine into vehicle motion. This includes Engine, Battery Pack, Electric Motor, Crank Hub, Transmission, Differential, Wheels and the vehicle body dynamics subsystems.
The control signals from the control model are transmitted using a bus bar to the corresponding blocks in the powetrain model.
Battery:
A Battery pack subsystem Contains input as a Electric power, and output as a Battery SOC.
In the ESS Subsystem there are two different subblocks added to determine the SOC and terminal voltage seperately, the SOC being used to calculate the terminal voltage.
The Below Image is Terminal Voltage Subsystem given:
Ideal voltage and internal resistance are determined by 1D lookup tables, and battery voltage is determined using model. The specified values are sent back to workspace using the 'to workspace' block and can be used for post processing.
The Below Image is SOC Estimation Subsystem given:
In this model for calculating SOC here Pack current in Ampere is converted to AmpHour and divides with Max Capacity and adds with the initial SOC to determine the SOC of the battery at each instance, the SOC value is limited between 0 to 1 using Saturation block.
Engine:
Engine subsystem take input as a Engine speed and give the output as a engine torque. here in this subsystem lookup table is used which contains the value of maximum torque curve and minimum torque curve of the engine. also using the fuel consumption curve we can find the engine torque from required engine torque. Output is passes to the crankhub.
The 2D lookup table is used to calculate the fuel from rate based on engine speed and engine torque. The fuel flow rate is then integrated to find the fuel consumption.
Estimated fuel flow rate, fuel consumption, engine torque and engine speed are passed to the MATLAB workspace using the "to workspace" block. Engine fuelflow rate and Fuel consumption are scoped using scope block.
Electric Machine:
Using the engine speed the required EM torque from the controller is saturated between Max EM torque curve and Max EM
torque generation curve and passes the EM torque to the crank hub. The 2D lookup table is used to calculate the input electric power to the motor using EM speed and EM torque.
Crank Hub:
Crank Hub is the sum of the EM torque and the Engine torque and pass it to the transmission block input as the crank torque.
Transmission:
The crank hub is connected to transmission and transmission is connected to the differential block. here in the transmission block input is crank torque and the gear and cluch lockup and using this the output getting from this model is the transmission output torque.
here subsystem Torque converter is added which is convert the crank torque to the transmission torque using transmission speed and cluch lockup. also here use the lookup table for the transmission gear ratio curve.
The Torque Converter subsystem is shown in below image:
Torque converter defines the pump and turbine torque by the clutch lock up, and the combination gives us the desired transmission torque.
Differential:
The transmission output torque is multiplied by the differential ratio and differential efficiency using the positive torque and negative torque and the torque is given output as axle torque which is transmitted to wheel.
Wheel:
In this model input the brake torque from the control model is subtracted from the another input Axle torque and divides from the rolling radius to determine the tractive force as an output. also the wheel speed is calculated from the vehicle velocity and it is saved in the workspace.
Vehicle Dynamics:
The dynamics of the vehicle alog with the road load is represented in the 'Vehicle Dynamics' block also Tractive force and road loads are used to calculate the vehicle velocity. here, The variables are loaded on the workspace using MATLAB script. The acceleration, velocity and distance travelled are calculated and stored in the workspace.
MATLAB Scripts for PLOTS the data:
A MATLAB script is created to analyse data and to generate plots. Here we rename the variables loaded from the model and do some basic post-process calculations and generate results and plots.
%% Post processing file of P1 Hybrid Vehicle Model
%% By Rahul Sonagara
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_Spd = out.WheelSpeed*30/pi; % Wheel speed [rpm]
Desired_Spd = out.Desired_Velocity*18/5; % Desired Speed [kmph]
Eng_Fuel_Rate = out.Eng_Fuel_Rate; % Engine Fuel Rate [%]
EM_Speed = out.EMSpd*18/5; % Electric Motor Speed [rpm]
EM_Power = out.EMPwr; % Electric Motor Power
EM_Torque = out.EMTrq; % Electric Motot Torque [Nm]
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_consump = 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 bettery
%% Plot the time trace for engine, transmission input, transmission output and wheel speed on one plot.
figure (1)
hold on
grid on
plot (Trans_In_Spd,'lineWidth',2);
plot (Trans_Out_Spd,'lineWidth',2);
plot (Wheel_Spd,'lineWidth',2);
xlabel ('Time [s]');
ylabel ('Speed [rpm]');
legend ('Transmission Input','Transmission Output','Wheel Speed');
%% Plot engine torque, engine power, fuel rate and fuel consumption using subplots.
figure (2)
subplot (4,1,1)
plot (Time,Eng_trq,'lineWidth',2);
xlabel ('Time [s]');
ylabel ('Torque [Nm]');
legend ('Engine Torque');
grid on
subplot (4,1,2)
plot (Time,Eng_pwr,'lineWidth',2);
xlabel ('Time [s]');
ylabel ('Power [kW]');
legend ('Engine Power');
grid on
subplot (4,1,3)
plot (Time,Eng_fuel_rate,'lineWidth',2);
xlabel ('Time [s]');
ylabel ('Fuel Rate [%]');
legend ('Engine Fuel Rate');
grid on
subplot (4,1,4)
plot (Time,Eng_fuel_consump,'lineWidth',2);
xlabel ('Time [s]');
ylabel ('Fuel Consumption');
legend ('Engine Fuel Consumption');
grid on
%% Plot accelerator and brake pedal, gear command, vehicle desired and actual speed, vehicle distance using subplots.
figure (3)
subplot (5,1,1)
hold on
plot (Time,Acc_Pdl,'lineWidth',2);
plot (Time,Brk_Pdl,'linewidth',2);
xlabel ('Time [s]');
ylabel ('Pedal [%]');
legend ('Accel','Brake');
title ('Acceleration and Brake Pedal wrt Time');
grid on
subplot (5,1,2)
plot (Time,Gear_Cmd,'lineWidth',2);
xlabel ('Time [s]');
ylabel ('Gear');
legend ('Gear Change');
title ('Gear Command wrt Time');
grid on
subplot (5,1,3)
hold on
plot (Veh_Spd,'lineWidth',2);
xlabel ('Time [s]');
ylabel ('Speed [kmph]');
legend ('Actual Spd');
title ('Actual Speed of Vehicle');
grid on
subplot (5,1,4)
hold on
plot (Desired_Spd,'lineWidth',2);
xlabel ('Time [s]');
ylabel ('Speed [kmph]');
legend ('Desired Spd');
title ('Desired Speed of Vehicle');
grid on
subplot (5,1,5)
plot (Veh_Dist,'lineWidth',2);
xlabel ('Time [s]');
ylabel ('Distance [km]');
legend ('Distance');
title ('Vehicle Distance');
grid on
%% Plot the engine operating points on the 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)]);
%% Plot motor speed, torque, motor input power using subplots.
figure (5)
subplot (3,1,1)
plot (Time,EM_power,'lineWidth',2);
xlabel ('Time [s]');
ylabel ('Power [W]');
legend ('Electric Motor Power');
grid on
subplot (3,1,2)
plot (Time,EM_torque,'lineWidth',2);
xlabel ('Time [s]');
ylabel ('Torque [Nm]');
legend ('Electrical Motor Torque');
grid on
subplot (3,1,3)
plot (Time,EM_speed,'lineWidth',2);
xlabel ('Time [s]');
ylabel ('Speed [rpm]');
legend ('Electric Motor Speed');
grid on
%% Plot pack voltage, current and SoC using subplots.
figure (6)
subplot (3,1,1)
hold on
plot (Time,Pack_current,'lineWidth',2);
plot (Time,Brk_Pdl,'linewidth',2);
xlabel ('Time [s]');
ylabel ('Current [W]');
legend ('Pack Current');
grid on
subplot (3,1,2)
plot (Time,State_of_charge,'lineWidth',2);
xlabel ('Time [s]');
ylabel ('Charge [%]');
legend ('State of Charge');
grid on
subplot (3,1,3)
plot (Time,Term_Voltage,'lineWidth',2);
xlabel ('Time [s]');
ylabel ('Voltage [V]');
legend ('Terminal Voltage');
grid on
%% Plot the motor operating points on the motor input power map, with the motor max motoring and generating torque curves.
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');
p4=plot(EM_map_spd*30/pi,EM_max_gen_trq,'linewidth',2,'color','b');
p2=line([EM_map_spd(end)*30/pi EM_map_spd(end)*30/pi],[EM_max_gen_trq(end) 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],[EM_max_gen_trq(1) 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');
legend([p1 p4 p3],{'Max Curve','Regen Curve','Operating Points'});
axis([EM_map_spd(1)*30/pi EM_map_spd(end)*30/pi EM_max_gen_trq(1) EM_max_trq(1)]);Output Plots:
First I have run the MATLAB scripts for UDDS Drive cycle. and run the simulink model according to that cycle. The output Plots getting is as per the below images.
1)Drive Cycle:
2)Fuel Economy numbers (kmpl):
For P1 Hybrid vehicle model
Fuel economy - 18.072 [kmpl]
Fuel economy improvement is observed in P1 hybrid and it shows better economy than conventional vehicle model in UDDS cycle.
3)The Time trace for engine, transmission input, transmission output and wheel speed:
The Input speed is initiated by the torque converter, and the transmission input speed fluctuates according to the engine torque required to achieve the drive cycle. Wheel speed and transmission output speed vary according to the gear and differential ratio.
4)Engine torque, Engine power, Fuel rate and Fuel consumption using subplots:
5)Accelerator and brake pedal, Gear command, Vehicle desired and actual speed, Vehicle Distance:
Acceleration and brake pedals are used more because the drive cycle is not very smooth and the gear has to be shifted frequently.
6)The Engine Operating points on the engine fuel map:
7)The motor speed, torque and motor input power using subplots:
Motor torque request is for engine start and regen braking only. Electric input power is calculated by referring the motor speed according to the EM motor torque request.
8)Pack Voltage, current and SOC using subplots:
Battery SOC is responding according to the motor torque request and the regen braking.
9)The motor operating points on the motor input power map, with the motor max motoring and generating torque curves:
Second I have run the MATLAB scripts for HWFET Drive cycle. and run the simulink model according to that cycle. The output Plots getting is as per the below images.
1)Drive Cycle:
2)Fuel Economy numbers (kmpl):
For P1 Hybrid vehicle model
Fuel economy - 21.997 [kmpl]
Fuel efficiency is slightly improved as the highway has less negative power when driving. But all the negative power will be regenerated with regen braking and the battery SOC will increase.
3)The Time trace for engine, transmission input, transmission output and wheel speed:
The Input speed is initiated by the torque converter, and the transmission input speed fluctuates according to the engine torque required to achieve the drive cycle. Wheel speed and transmission output speed vary according to the gear and differential ratio.
4)Engine torque, Engine power, Fuel rate and Fuel consumption using subplots:
The HWFET drive cycle has higher power and torque requirements and less negative torque and power.
5)Accelerator and brake pedal, Gear command, Vehicle desired and actual speed, Vehicle Distance:
Brake requirements are lower, more accelerator pedals are applied on the highway drive cycle, and gear shifts often occur because the drive cycle is smoother.
6)The Engine Operating points on the engine fuel map:
The engine operating points are plotted on the fuel map and the operating point is under the maximum torque curve.
7)The motor speed, torque and motor input power using subplots:
EM motor torque demand is low as the vehicle moves at high speeds and less idle on highway drive.
8)Pack Voltage, current and SOC using subplots:
Battery SOC is increases on highway drive cycles due to lower EMotor usage and regen braking battery charging.
9)The motor operating points on the motor input power map, with the motor max motoring and generating torque curves:
Electric motor can operate between max motoring torque curve and max generating torque curve.
Conclusion:
Vehicle operating points based on engine and motor speed, torque, transmission speeds, pedal positions, gear, distance travelled, battery voltage, current, SOC etc have been analysed and understood using plots.
The improvement in the fuel efficiency numbers of the hybrid vehicle(kmpl) compared to the conventional vehicle was calculated on the Urban cycle (UDDS) and Highway cycle (HWFET).