Project 2
ANSWER:
Forward Model Approach:
- the forward modeling approach is also called a cause-effect, engine-to-wheel method.
- the direction of calculation is the same as the direction of positive power flow from the engine to the wheel.
- this approach is based on the vehicle dynamics equation and the behavior of each powertrain component and their dynamics interaction.
- in this we start with 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.
- The ‘Controller’ block is the brains of the vehicle, representing the electronic control units. Based on the driver inputs, it generates desired engine torque, desired transmission gear, and desired brake torque.
- These inputs are fed to the ‘Powertrain’ block which represents the drivetrain of the vehicle. It consists of an ‘Engine’ and 'Electric Motor through a battery' connected to the ‘Automatic Transmission’ through a ‘Torque Converter’. The output of the transmission is connected to the ’Differential’, which powers the ‘Wheels’, which provides the tractive force for vehicle acceleration. The longitudinal dynamics of the vehicle along with the road load are represented in the ‘Vehicle Dynamics’ block.
P1 Hybrid Vehicle Model:
Honda Insight motor and battery are considered for this project. Data is taken from the ADVISOR database developed by NREL, USA. Data is provided in the project files.
Vehicle Model:
Pre-Processing:
A MATLAB script has been created to load all the variables needed for running the Simulink model and for post-processing. The drive cycle selection is also done here. Before running the Simulink vehicle model, run this initialization script.
%% Skill-Lync -> Hybrid Drives Development
% Project 1 - Conventional Vehicle Model
% By - IBRAHIM BARAWALE
% 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 = 2; % 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);
drive cycle can be selected from this MATLAB script by changing the variable Drive_cycle select to,
1
UDDS
2
HWFET
3
FTP
4
US06
5
NEDC
6
WLTP
SIMULINK MODELLING:
- Here we start with modeled using a ‘Driver model' block, which is a basic PI controller that generates accelerator and brake pedal outputs to match the desired and actual vehicle speeds.
- The ‘Controller model’ block is the brains of the vehicle, representing the electronic control units. Based on the driver inputs, it generates desired engine torque, desired transmission gear, and desired brake torque.
- These inputs are fed to the ‘Powertrain model’ block which represents the drivetrain of the vehicle. It consists of an ‘Engine model with Electric Motor’ connected to the ‘Automatic Transmission model’ through a ‘Torque Converter’. The output of the transmission is connected to the ’Differential’, which powers the ‘Wheels’, which provides the tractive force for vehicle acceleration. The longitudinal dynamics of the vehicle along with the road load are represented in the ‘Vehicle Dynamics model’ block.
Driver Model:
- ‘Driver model' block, which is a basic PI controller that generates accelerator and brake pedal outputs to match the desired and actual vehicle speeds.
- 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 Model:
- The ‘Controller’ block is the brains of the vehicle, representing the electronic control units. Based on the driver inputs, it generates desired engine torque, desired transmission gear, and desired brake torque. These inputs are fed to the ‘Powertrain’ block which represents the drivetrain of the vehicle.
- a state flow machine is used to represent the supervisory control unit which decided the operating mode whether it is the start /stop mode or cruising mode or regen braking mode for each mode the engine drive and the motor drive are controlled.
FLOWCHART:
- the input to the state flow charts is accel. and brake pedal input from the driver unit engine actual speed actual vehicle speed soc status and the clutch lockup state and the output to the controller is the mode engine on /off request engine input throttle and electric motor input throttle.
- all control signals passed to the transmission model which represents the drive train.
Engine control unit:
- engine control unit compares engine speed with the maximum torque and minimum torque curve of the lookup table and gives the required torque command to the engine block. the throttle input is combined with the idle speed throttle and gains with torque output from the lookup table to estimate the torque input required for the engine.
- throttle input idle throttle and their sum can be scoped from this block.
Idle speed controller:
Transmission control block:
- the transmission control block controls the gear shifting using the study flow variable chart.
- the gear shifting is controlled according to the vehicle speed and throttle input.
SHIFT LOGIC:
Electric motor control unit:
- motor control unit compares EM speed with the max torque curve and max torque generation curve of the lookup table and gives the required torque command to the electric motor the EM throttle input is used to compare the lookup table and to estimate the torque input required for the e-motor.
Brake control unit:
- brake control unit produces the required brake torque according to the brake pedal input and passes the brake torque into the wheel block in the transmission model.
Powertrain model:
- the power train model includes all the components that convert the power of the engine into the vehicle motion.
- this includes the engine,e-motor, battery pack, transmission, differential, wheels, and vehicle body dynamics subsystem.
Battery model:
- a battery pack subsystem is created with electric power input and battery soc as output
- 2 diffs. subblock has been created to determine the soc and terminal voltage separately soc is used to determine the terminal voltage.
SOC Estimation model:
- pack current in ampere is converted to amphr 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.
Terminal voltage model:
- ideal voltage and internal resistance are determined by a 1D lookup table and battery voltage is determined using the model.
- the specified values are sent back to the workspace using the to-workspace block and can be used for post-processing.
Engine model:
- based on the engine speed the required torque from the controller is saturated between the max torque curve and min torque curve and passes the engine torque to the transmission block
- the 2D lookup table is used to calculate the fuel flow rate based on engine speed and engine torque.
- the new engine also has an on/off feature to eliminate the fuel flow rate when the engine is off also the engine torque cannot be negative torque as min. torque curve mode saturated.
- the fuel 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 fuel flow rate and fuel consumption are scoped.
Electric motor model:
- based on the engine speed the required EM torque from the controller is saturated between the 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 based on the EM speed and EM torque.
crank hub:
- crank hub adds up the EM torque and the engine torque and passes it to the transmission block as the crank torque.
Transmission model:
- the engine block is connected to the automatic transmission via a torque converter the output of the transmission is connected to the differential.
Torque converter:
- the gear selection from the transmission control unit is multiplied by the engine torque in this block and the efficiency and engine dynamics of the torque converter are applied in this model.
Differential Model:
- the transmission output torque is multiplied by the differential ratio and differential efficiency in this block and the torque is transmitted to the wheel as the axle torque.
Wheel Model:
- the brake torque from the control model is subtracted from the axle torque and divided from the rolling radius to determine the tractive force
- the wheel speed is calculated from the vehicle velocity and saved in the workspace.
Vehicle dynamics:
- the longitudinal dynamics of the vehicle along with the road load is represented in the vehicle dynamics block
- tractive force and road loads are used to calculate the vehicle velocity.
1] tractive force = ηt*λt*Te/Rw = M*(dVveh/dt) + 0.5 *ρa *Af*Cd*(Vveh+Vwd)^2 + Cr*M*g*cosθ +M*g*sinθ
2] road load = 0.5 *ρa *Af*Cd*(Vveh+Vwd)^2 + Cr*M*g*cosθ +M*g*sinθ
where,
ρa = air density
Af = frontal area
Cd = drag coefficients
Cr = rolling coefficients
M = vehicle mass
g = acceleration due to gravity
θ = slope
- the variable is loaded on the workspace using MATLAB scripts.
- the acceleration velocity and distance traveled are calculated and stored in the workspace.
Simulation Result:
1] UDDS Drive Cycle:
a] Drive Cycle and Actual Velocity:
Engine Fuel Rate and Fuel Consumption:
VELOCITY, ROAD LOAD, ACCELERATION:
DIFFERENT ROAD LOADS:
SOC battery:
electric motor torque require and motor speed:
engine torque requires and gear cmd:
Post-processing:
Matlab script was used to analyze this data and to generate plots. This script needs to be executed after the Simulink model data has been loaded into the workspace. the variables loaded from the model (if desired), do some basic post-process calculations, and generate results and plots.
%% Hybrid Drives Development
% Project 2 - P1 Hybrid Vehicle Model
% By - IBRAHIM BARAWALE
%% 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]
Eng_Fuel_Rate = out.Eng_Fuel_Rate; %engine fuel rate
Veh_Dist = out.Veh_Dist/1000; % Distance traveled by vehicle [km]
Veh_Spd = out.Veh_Spd*18/5; % Vehicle speed [kmph]
Whl_Spd = out.Whl_Spd*30/pi; % wheel speed[RPM]
Desired_spd = out.Desired_Velo*18/5 ; %desired speed [KMPH]
EM_Spd = out.EM_Spd*30/pi; % E motor speed[rpm]
EM_Trq = out.EM_Trq; % E motor torque[Nm]
EM_Pwr = out.EM_Pwr; % E motor input power[W]
V_batt = out.V_battery; % battery pack voltage [V]
I_batt = out.I_battery; % battery pack current [I]
SOC = out.SOC; % STATE OF CHARGE [%]
RS = out.RS; % internal resistance
VOC = out.VOC; % open circuit voltage
%% 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];
% display fuel Economy of the cycle
formatspec = 'fuel economy is %2.2f kmpl';
fprintf(formatspec,kmpl);
%% Plotting vehicle characteristics time trace
% ploting transmission input,transmission output 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,Whl_Spd,'LineWidth',1,'Color','blue');
xlabel('Time[s]')
ylabel('speed[rpm]')
xlim([0,Time(end)]);
legend('trans input','trans Output','wheel speed');
title('transmission input transmission output and wheel speed')
% plotting engine torque,engine power,fuel rate ,fuel consumption
figure(2)
subplot(4,1,1)
hold on
grid on
plot(Time,Eng_Trq,'LineWidth',1,'Color','black');
ylabel('torque[NM]')
xlim([0,Time(end)]);
title('Engine Torque')
subplot(4,1,2)
hold on
grid on
plot(Time,Eng_Pwr,'LineWidth',1,'Color','black');
ylabel('power[KW]')
xlim([0,Time(end)]);
title('Engine Power')
subplot(4,1,3)
hold on
grid on
plot(Time,Eng_Fuel_Rate,'LineWidth',1,'Color','black');
xlim([0,Time(end)]);
xlabel('Time[s]');
ylabel('Engine fuel rate');
title('Engine fuel rate')
subplot(4,1,4)
hold on
grid on
plot(Time,Eng_Fuel_Consump,'LineWidth',1,'Color','black');
xlim([0,Time(end)]);
xlabel('Time[s]');
ylabel('Engine fuel consumption[g]');
title('Engine Fuel Consumption')
% plotting accelerator and brake pedal gear command vehicle desired and actual speed ,vehicle distance
figure(3)
subplot(4,1,1)
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');
title('Acceleration and brake pedal inputs')
subplot(4,1,2)
hold on
grid on
plot(Time, Gear_Cmd, 'linewidth', 1, 'Color', 'black');
xlim([0, Time(end)]);
xlabel('Time [s]');
ylabel('Gear');
title('gear command')
subplot(4,1,3)
hold on
grid on
plot(Time, Veh_Spd, 'linewidth', 1, 'Color', 'black');
plot(Time, Desired_spd, 'linewidth', 1, 'Color', 'red');
ylabel('Speed [kmph]')
xlim([0, Time(end)]);
legend('actual speed','desired speed');
title('vehicle actual and desired speed')
subplot(4,1,4)
hold on
grid on
plot(Time, Veh_Dist, 'linewidth', 1, 'Color', 'black');
xlim([0, Time(end)]);
xlabel('Time [s]');
ylabel('distance[km]');
title('vehicle distance')
% plotting drive cycle
figure(4)
hold on
grid on
plot(cyc_time,cyc_vel,'LineWidth',1,'Color','black')
xlabel('time[s]')
ylabel('velocity[mph]')
title('drive cycle')
% test result
Avg_speed = sum(Veh_Spd)/length(Veh_Spd);
Max_speed = maxk(Veh_Spd,1);
table (Avg_speed,Max_speed,kmpl,'variablenames',{'average speed[kmph]','maximum speed[kmph]','fuel economy[kmpl]'})
%% Plotting engine operating points on engine fuel map
figure('Name','Engine Operating Points');
hold on
grid on
title('Engine Operating Points','fontsize',12);
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({'Max Curve','Operating Points'});
axis([Eng_map_spd(1)*30/pi Eng_map_spd(end)*30/pi 0 Eng_map_trq(end)]);
%% Electric Motor
% plotting motor speed ,motor torque,motor input power
figure(6)
subplot(3,1,1)
hold on
grid on
plot(Time,EM_Spd,'LineWidth',1,'Color','b');
ylabel('Speed[rpm]')
xlim([0,Time(end)]);
title('motor speed')
subplot(3,1,2)
hold on
grid on
plot(Time,EM_Trq,'LineWidth',1,'Color','r');
ylabel('torque[Nm]')
xlim([0,Time(end)]);
title('motor torque')
subplot(3,1,3)
hold on
grid on
plot(Time,EM_Pwr,'LineWidth',1,'Color','g');
ylabel('power[W]')
xlim([0,Time(end)]);
title('motor input power')
%% BATTERY
% plotting pack current,voltage,soc,internal resistance,open circuit
% voltage
figure(7)
subplot(5,1,1)
plot(Time,V_batt,'LineWidth',1,'Color','r');
xlabel('Time[sec]');
ylabel('voltage[v]');
title('pack voltage')
xlim([0,Time(end)]);
grid on
subplot(5,1,2)
plot(Time,I_batt,'LineWidth',1,'Color','b');
xlabel('Time[sec]');
ylabel('current[I]');
title('battery current')
xlim([0,Time(end)]);
grid on
subplot(5,1,3)
plot(Time,SOC,'LineWidth',1,'Color','g');
xlabel('Time[sec]');
ylabel('SOC[%]');
title('STATE OF CHARGE')
xlim([0,Time(end)]);
grid on
subplot(5,1,4)
plot(Time,RS,'LineWidth',1,'Color','r');
xlabel('Time[sec]');
ylabel('Internal resistance[ohm]');
title('Internal resistance')
xlim([0,Time(end)]);
grid on
subplot(5,1,5)
plot(Time,VOC,'LineWidth',1,'Color','b');
xlabel('Time[sec]');
ylabel('Open circuit voltage[v]');
title('Open circuit voltage')
xlim([0,Time(end)]);
grid on
%% Plotting engine operating points on engine fuel 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');
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_gen_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 in power map [W]');
legend([p1 p4 p3],{'Max Curve','regen curve','Operating Points'});
xlim([EM_map_spd(1)*30/pi EM_map_spd(end)*30/pi]);
ylim([EM_max_gen_trq(1) EM_max_trq(1)]);
Post-Processing Results:
1] drive cycle:
a] UDDS:
HWFET:
2] fuel economy numbers(KMPL):
a] UDDS:
average speed[kmph] maximum speed[kmph] fuel economy[kmpl]
___________________ ___________________ __________________
31.528 91.742 28.979
HWFET:
average speed[kmph] maximum speed[kmph] fuel economy[kmpl]
___________________ ___________________ __________________
77.679 96.451 37.059
3] the time trace for engine, transmission input, transmission output, and wheel speed:
a] UDDS:
HWFET:
- much of the fluctuating input speed is facilitated 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 gear and differential ratio.
4] engine torque, engine power, fuel rate, fuel consumption:
a] UDDS:
HWFET:
5] accelerator and brake pedal, gear command, vehicle desired and actual speed, vehicle distance:
a] UDDS:
HWFET:
- acceleration and brake pedals are used more bcoz the drive cycle is not very smooth and the gear has to be shifted frequently.
- brake requirements are lower more accelerator pedals are applied on the highway drive cycle and gear shift often occurs bcoz the drive cycle is smoother.
- acceleration and brake pedal the gear command of the transmission control unit the required speed of the vehicle the actual speed and the actual vehicle distance are plotted.
6] the engine operating points on the engine fuel map:
a] UDDS:
HWFET:
- the engine operating points are plotted on the fuel map and the operating points are under the maximum torque curve.
7] the motor speed, motor torque, and motor input power:
a] UDDS:
HWFET:
8] the pack voltage, current, SOC, VOC, and internal resistance:
a] UDDS:
HWFET:
9] The motor operating points on the motor inputs power map, with the motor max motoring and generating torque curves:
UDDS:
HWFET:
CONCLUSION :
- therefore the forward energy-based fuel consumption model of a P1 Hybrid vehicle has been successfully simulated using MATLAB and SIMULINK.
- Analysis and understanding of vehicle operating points based on engine speed, torque, transmission speed, pedal position, gear, distance, velocity, acceleration, battery, voltage, current, SOC, and pedal position.
- Post-process calculations were performed and the required graphs were successfully plotted.
- Successfully calculated vehicle fuel efficiency number[kmpl] for the given city cycle [UDDS] and highway cycle[HWFET].and also compared to the conventional vehicle.