Challenge

Project 1

AAditya Shipte16 Mar 2022

MATLAB

Report

Aim:-

Development of a forward energy-based fuel consumption model of a conventional vehicle.
To compute the fuel economy numbers for the given vehicle (kmpl) on the urban cycle (UDDS) and highway cycle (HWFET).
To analyze and understand the vehicle operating points in terms of engine speed, torque, transmission speeds, pedal positions, gear, distance traveled.
Build simulink model using blocks and complete the vehicle model.
write scripts in MATLAB to load all the variable needed to run the simulink model.
analyze data and create plots using matlab scripts.

Objective:-

Tabulate the fuel economy numbers (kmpl) for UDDS and HWFET cycle. This forms the baseline numbers for comparing with the future hybrid version.
Plot the time trace for engine, transmission input, transmission output and wheel speed on one plot.
Plot engine torque, engine power, fuel rate and fuel consumption using subplots.
Plot accelerator and brake pedal, gear command, vehicle desired and actual speed, vehicle distance using subplots.
Plot the engine operating points on the engine fuel map.
Write down appropriate brief comments on each of these plots, describing the vehicle behavior throughout the drive cycle.
Generate the plots for both drive cycles

THEORY:

forward model approach:

the forward modelling approach is also called as cause-effect,engine to wheel 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 equation and the behaviour of each powertrain components 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 controls 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’ connected 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.

conventional vehicle modelling:

Architecture of the forward conventional vehicle model is presented in figure.

in this 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 controls 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’ connected to the ‘Automatic Transmission model’ 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 model’ block.

VEHICLE MODEL:

pre-processing:

A matleb scripts has been created to load all the variable 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 - Aditya Shipte 

% 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

%% 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);

drive cycle can be selected from this MATLAB scripts by changing the variable Drive_cycle select to,

UDDS

HWFET

FTP

US06

NEDC

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 controls 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’ connected to the ‘Automatic Transmission model’ 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 model’ block.

1] 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 control the error between the required drive cycle and actual vehicle speed by providing acceleration and brake pedal output to the controller.

2] Controller Model:

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. These inputs are fed to the ‘Powertrain’ block which represents the drivetrain of the vehicle.

The controller consists of an engine control unit,transmission control unit,brake control unit
and all signal can be scoped.

a] Engine control unit:

engine control unit compare engine speed with the maximum torque and minimum torque curve of the lookup table and give the required torque command to the engine block. the throttle input is combine 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:

b] Transmission control block:

the transmission control block control the gear shifting using the study flow variable chart.

the gear shifting is controlled according to the vehicle speed and throttle input.

the gear command is passed to the transmission block to select the desired gear ratio.

c] 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.

Powertrain Model:

the power train model include all the components that converts the power of the engine into the vehicle motion.

this includes the engine,transmission,diffential,wheels,and vehicle body dynamics subsystem.

1] Engine Model

based on the engine speed the required torque from the controller is saturated between 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 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.

2] 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.

a] 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.

3] Differential Model:

the transmission output torque is multiplied by the differential ratio and differential effieciency in this block and the torque is transmiteed to the wheel as the axle torque.

4] Wheel Model:

the brake torque from the control model is subtracted from the axle torque and divides from the rolling radius to determine the tractive force
the wheel speed is calculated from the vehicle velocity and saved in the workspace

5] 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 co-efficients

Cr = rolling co-efficients

M = vehicle mass

g = acceleration due to gravity

θ = slope

the variable are loaded on the workspace using MATLAB scripts.
the acceleration velocity and distance travelled are calculated and stored in the workspace.

Simulation Result:

1] UDDS Drive Cycle:

a] Drive Cycle and Actual Velocity:

b] Control Signal[Engine Torque,Transmission Gear,Brake Torque]:

c] Engine Fuel Rate and Fuel Consumption:

d] Engine Torque:

e] Gear Ratio,Transmission Input,Output Speed:

F] Torque Ratio and Pump Torque in Torque Converter:

g] Pump Speed and Turbine Speed in Torque Converter:

h] Different Road Loads[Rolling Resistance Load,Gradients Load,Aerodynamics Load]:

i] Tractive Force,Road Load,Acceleration:

2] HWFET Drive Cycle:

a] Drive Cycle and Actual Velocity:

b] Control Signal[Engine Torque,Transmission Gear,Brake Torque]:

c] Engine Fuel Rate and Fuel Consumption:

d] Engine Torque:

e] Gear Ratio,Transmission Input,Output Speed:

F] Torque Ratio and Pump Torque in Torque Converter:

g] Pump Speed and Turbine Speed in Torque Converter:

h] Different Road Loads[Rolling Resistance Load,Gradients Load,Aerodynamics Load]:

i] Tractive Force,Road Load,Acceleration:

Post processing:

Matlab script 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.

MATLAB CODE:

%% Hybrid Drives Development
% Project 1 - Conventional Vehicle Model
% By - Aditya Shipte 

% 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]
Whl_Spd = out.Whl_spd*30/pi;     % wheel speed[RPM]
Desired_spd = out.Desired_Velo*18/5 ;  %desired speed [KMPH]

%% 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
fprintf('nfuel Economy = %2.2fkmplnn',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');

% 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)]);

subplot(4,1,2)
hold on
grid on 
plot(Time,Eng_Pwr,'LineWidth',1,'Color','black');
ylabel('power[KW]')
xlim([0,Time(end)]);

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');

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]');

% 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');

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');

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');

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]');

% 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);
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)]);

Post Processing Results:

1] drive cycle:

a] UDDS:

b] HWFET:

2] fuel economy numbers(KMPL):

a] UDDS:

b] HWFET:

city[UDDS] fuel economy is much lower than the highway[HWFET] drive as the brake pedal engagement and idle time on the drive cycle is less.

3] the time trace for engine ,transmission input,transmission output,wheel speed:

a] UDDS:

b] HWFET:

much of the fluctuating input speed is facilitated by the torque convertor and the transmission input speed fluctuates according to the engine torque required to achive the drive cycle.
wheel speed and transmision output speed vary according to gear and differential ratio.

4] engine torque,engine power,fuel rate,fuel consumption:

a] UDDS:

b] HWFET:

the torque requirements of the drive cycle are different so the fuel flow rate varies and fuel consumption is calculated.
the HWFET drive cycle has higher power and torque requirement and less negative torque and power.

5] accelerator and brake pedal,gear command,vehicledesired and actual speed,vehicle distance:

a] UDDS:

acceleration and brake pedals are used more bcoz the drive cycle is not very smooth and the gear has to be shifted frequently.

b] HWFET:

brake requirement are lower more acceleretor pedal 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 engien fuel map:

a] UDDS:

b] HWFET:

the engine operating points are plotted on the fuel map and the operating points is under the maximum torque curve.

Conclusion:

so,the forward energy based fuel consumption model of a conventional vehicle has been succesfully simulated using MATLAB and simulink.
Analysis and understand vehicle operating points based on engine speed,torque,transmission speed,pedal position,gear,distance,velocity and acceleration.
Post process calculation were performed and the required graphs were successfully plotted.
Succesfully calculated vehicle fuel efficiency number[kmpl] for the given city cycle [UDDS] and highway cycle[HWFET].

Project 1

Ship work like this
in your own course.

Talk to a career counsellor

Ship work like thisin your own course.

Talk to a career counsellor

Ship work like this
in your own course.