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Challenge

Project 1

DDevesh Kashyap16 Aug 2022
MATLAB

AIM:- To compute the fuel economy numbers for the given vehicle (kmpl) on the urban cycle (UDDS) and highway cycle (HWFET). and analyze the vehicle operating condition.

OBJECTIVE : -

  • Tabulate the fuel economy numbers (kmpl) for UDDS and HWFET cycle.
  • 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.
  • 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.
  • Generate the plots for both drive cycles.

THEORY:-

Conventional vehicles use an internal combustion engine fuelled by gasoline or diesel to power the wheels. Electricity is used for some accessories, but is not used to move the vehicle. engine converts chemical energy stored in the fuel into heat which is used to produce useful work.

Architecture of the forward (conventional vehicle) Model

  • In this model includes a driver model that provides input commands acceleration and brake torque depending on the drive cycle and the actual speed of the vehicle.
  • A control model that controls the engine torque to the desired range and changes the gear command and control brake torque according to the driver input.
  • The transmission model that gives the actual speed of the vehicle as feedback to the driver model. The model includes the engine, transmission, differential, wheel and vehicle dynamics models separately.

Forward-Modelling - This approach is based on vehicle dynamics and the behaviour of each powertrain components and their dynamic interaction. 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. 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.

Vehicle Energy Consumption Estimation Models

classified in three main categories:

1.) Statistical models - Statistical models are built based on real world driving data analysis to derive empirical relationships between the different factors affecting Vehicles energy consumption.

2.) Analytical models - Analytical models are representative of the Vehicle behaviour and can be developed in MATLAB/Simulink by creating a vehicle model. They are based on fundamental theoretical equations. A model of the vehicle dynamics is built based on vehicle dynamics theory to calculate the power required at the wheels to overcome the resistances forces opposed to the vehicle motion: Aerodynamic Drag, Rolling, Inertia, Gradient and Transmission resistances. The power required derives from the tractive force expressed as the sum of the resistances forces above

3.) Computational models - There are mainly two kinds of computational models for energy consumption estimation

  1. Artificial Neural Networks (ANN) based model.
  2. Clustering based models.

VEHICLE MODEL

Pre-Processing script Before running the Simulink vehicle model, the script is initialized MATLAB to load all the vehicle parameter in to the workspace.

%% Skill-Lync -> Hybrid Drives Development
% Project 1 - Conventional Vehicle Model
% By - DEVESH KASHYAP 

% 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);

We can select the Drive Cycle 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 MODEL

  • The Simulink model for the convection vehicle model is created by using three main subblocks (Driver model, Control model and Powertrain model) blocks.
  • 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 gear shifting, engine torque, and brake torque to the Powertrain model.

Driver Model

Driver Model generates accelerator and brake pedal outputs to match the desired and actual vehicle speeds.The error between the required drive cycle and actual vehicle speed by providing acceleration and brake pedal output to the controller.

Controller Model

It mainly 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 three subsystem blocks an engine control unit, a transmission control unit and a brake control unit block.

  • Engine control unit

Engine Control Unit Compare engine speed with the maximum torque and minimum torque curves of the lookup table and give the required torque command to the engine block.

Idle Speed Controller:

Here The throttle input is combined with the idle speed throttle and gains with the 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.

Transmission control unit

Here gear command is passed to the Transmission block to select the desired gear ratio.

above study flow Variable chart represents gear shifting control logic.

Brake control unit

It Produce required amount of brake torque according to the brake pedal input and passes the brake torque to the wheel block in the transmission model.

Powertrain Model Block

It has all the components that convert the power of the engine into vehicle motion.including Engine, Transmission, Differential, Wheels and the vehicle body dynamics subsystems.

Engine Model:

Based on the Engine speed and The required torque from the controller block 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 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 fuel flow rate and Fuel consumption are scoped.

Transmission Model:

Here engine block is connected to the automatic transmission via a torque converter. The output of the transmission is connected to the differential.one subsystem block is also there which is Torque_converter.

Torque converter:

Gear selection from the transmission control unit block is multiplied by the engine torque. in this block, the efficiency and the engine dynamics of torque converter are applied.

Differential Model :

Transmission output torque is multiplied by the differential gear ratio and differential efficiency. In this block the torque is transmitted to the wheel (axle) torque.

Wheel Model:

Here we calculate Wheel speed with respect to vehicle velocity and saved in the workspace. brake torque from the control model is subtracted from the Axle torque and divides from the rolling radius to determine the Tractive force.

Vehicle Dynamics :

longitudinal dynamics of the vehicle along with the road load is represented in the ‘Vehicle Dynamics’ block

Here we use Tractive Force and Road loads for velocity calculation.

Acceleration, Velocity and Distance travelled are Calculated and stored into the workspace.

SIMULATION RESULTS (SCOPE):

UDDS Drive Cycle

  • Drive Cycle Vs Velocity

  • Engine Torque, Transmission Gear and Brake torque

  • Engine Torque

  • Engine Fuel Rate and Fuel Consumption

  • Gear Ratio, Transmission Output Speed and Transmission Input speed

  • Road Load:

  • Tractive Force, Road Load and Acceleration

HWFET Drive Cycle

  • Drive Cycle Vs Velocity

  • Engine Torque, Transmission Gear and Brake torque

  • Engine Torque

  • Engine Fuel Rate and Fuel Consumption

  • Gear Ratio, Transmission Output Speed and Transmission Input speed

  • Road Load:

  • Tractive Force, Road Load and Acceleration

MATLAB Post-Processing script

This script is used to analyse the data and generate plots. Here we rename the variables loaded from the model, do some basic post-process calculations and generate results and plots.

%% 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.Engine_fuel_rate   ;
Veh_Dist = out.Veh_Dist/1000;   % Distance traveled by vehicle [km]
Veh_Spd = out.Veh_Spd*18/5;     % Vehicle 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]

%% Average speed, Maximum speed and Fuel economy
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 vehicle characteristics time trace
figure(1)
subplot(3,1,1)
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(3,1,2)
hold on
grid on
plot(Time, Trans_In_Spd, 'linewidth', 1, 'Color', 'black');
plot(Time, Trans_Out_Spd, 'linewidth', 1, 'Color', 'red');
ylabel('Speed [rpm]')
xlim([0, Time(end)]);
ylim([0, 6000]);
legend('Trans Input','Trans Output');
subplot(3,1,3)
hold on
grid on
plot(Time, Gear_Cmd, 'linewidth', 1, 'Color', 'black');
xlim([0, Time(end)]);
xlabel('Time [s]');
ylabel('Gear');

%% 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('Engineeeee Speed [rpm]');
ylabel('Engine Torque [Nm]');
title('Engine Fuel Consumption Map [g/s]');

%% Engine power,Engine Torque,Engine fuel rate and Engine fuel consumption
figure(2)
subplot(4,1,1)
hold on
grid on
plot(Time, Eng_Trq, 'linewidth', 1, 'Color', 'B');
ylabel('Torque [Nm]')
xlim([0, Time(end)]);
xlabel('Time [s]');
subplot(4,1,2)
hold on
grid on
plot(Time, Eng_Pwr, 'linewidth', 1, 'Color', 'G');
ylabel('Power [KW]')
xlim([0, Time(end)]);
xlabel('Time [s]');
subplot(4,1,3)
hold on
grid on
plot(Time, Eng_Fuel_rate, 'linewidth', 1, 'Color', 'R');
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('Fuel Consumption [gram]');

RESULTS:-

for UDDS Drive cycle

  • Drive cycles

  • Fuel economy numbers (kmpl)

  • Engine torque, engine power, fuel rate and fuel consumption

  • Accelerator pedal, brake pedal, gear command, Transmission input and output speed

  • Engine operating points on the engine fuel map data

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

HWFET Drive cycle

  • Drive cycles

  • Fuel economy numbers (kmpl)

  • Engine torque, engine power, fuel rate and fuel consumption

  • Accelerator pedal, brake pedal, gear command, Transmission input and output speed

  • Engine operating points on the engine fuel map data

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

CONCLUSION: -

  • Here we Analyses and understands vehicle operating points based on engine speed, torque, transmission speed, pedal positions, gear, and distance travelled.
  • We successfully simulate forward energy-based fuel consumption model by the help of MATLAB and Simulink
  • Post process calculations were performed and the required graphs were successfully plotted.
  • We also Successfully calculated vehicle fuel efficiency numbers (kmpl) for the given city cycle (UDDS) and highway cycle (HWFET).

**************************************************************************************************************************************************************************************************************************************************************************************************************END

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