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Project 1

AAkash Patil15 Mar 2023
HTMLMATLAB

Project 1

Ans:

  • Thesis:

    Forward-Modelling of Vehicle Approach:

    • This kind of approach is known as the cause-effect, engine-to-wheel or rear-to-front method, the direction of calculation is the same as the direct positive power flow method: power flow is from the engine to the wheel.
    • This approach is based on the vehicle dynamics equation and the behavior of single powertrain components and their dynamic interaction between the wheels.
    • A Driver Controller is required to control the vehicle to follow desired speed and to calculate.
    • The Controller is implemented to model that the driver will either push the accelerator or the brake pedal to match the desired speed which enables to study the braking of the vehicle
    • It also acts as a feedback loop for the vehicle which was used to determine the energy requirements to drive the vehicle.

Convectional Vehicle Modelling:

Basic architecture model of forwarding Vehicle Modeling:

  • The Simulation Process is been processed in 3 different stages:

    • Pre-processing
    • Simulation
    • Post-processing

    Stage 1:

    Pre-Processing

    In this Stage data which load as a program, it will take as an input program of the vehicles which is used for Post-processing of the Simulation by using the Simulink Model which is already built

    Drive Cycle selection is also done from here by choosing the variable in it eg:1 is for UDDS, 2 is for HWFET, and 3 is for FTP.

    Before running the Simulink model we have to induce inputs variables to the workspace to use by the Simulink model.

    Inputs such as:

    Mass of the vehicle (M) in kg

    Coefficient of Rolling resistance (Cr)

    Rolling Radius (Rw) in m

    Drag Coefficient (Cd)

    Frontal Area (Af) in m^2

    Air density (rhoa) in kg/m^3

    Wind Velocity (Vwind) in kmph

    Gravitational Force (g) in m/s^2

    Slope (theta) in deg

    Here the Input Data of the Vehicle Dynamics is Consists of a typical 4-gear vehicle

    Below I have attached the input program for the simulation:

  • %% 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 which was used in this program is US-based Vehicles Dynamics

    By the Changing the variable input for selecting different Drive_cycle

    1 UDDS

    2 HWFET

    3 FTP

    4 US06

    5 NEDC

    6 WLTP

  • Simulink Modeling:

    The Model of Simulink is for the convection model of the vehicle in which it has been divided into 3 main sub-blocks are:

    • Driver
    • Controller
    • Powertrain

    The Actual Vehicle speed is given as feedback to the driver block, and the driver block gives into the controller block in which the acceleration or brake output is connected.

    While the controller provides a control signal for engine torque, gear shifting, and brake torque to the powertrain block.

  • Driver:

    In this Driver Block, it is a basic PI controller model that is used to generate accelerator and brake pedal Outputs that are used to match the desired and actual vehicle speeds.

    The PI controller controls the error between the required drive cycle and the actual vehicle speed is been provided by the acceleration and brake pedal output of the controller unit.

  • Controller Unit:

    The brain of the vehicle unit is the 'Controller' block, which represents the ECU, Transmission Unit, and Basic Control Unit

    Based on the Driver Inputs, it generates desired engine Torque, desired transmission gear, and desired brake torque. These will be sent as feedback to the powertrain blocks as input which is represented the drivetrain of the vehicle.

  • Powertrain:

    To move up the vehicle we need a Body structure that is used to move the vehicle in forward and reverse directions as required.

    It consists of all components that will convert the Fuel power of the engine for the motion to move the vehicle.

    It consists of an Engine, Transmission, Wheels, Differential, Vehicle Dynamics

  • Engine

    Based on the Engine Speed, the required torque from the controller is between Max torque and Min Torque curve and it will transfer the Engine Torque to the Transmission Block.

    The 2D lookup table is used to calculate the fuel rate and is then integrated to find the fuel consumption rate of the engine, by using the engine speed and engine torque.

    By using the 'To Workspace' block command the estimated fuel flow rate, fuel consumption, engine torque, and engine speed is been passed to the workspace of MATLAB.

    To see the output of Engine Flow rate and Fuel Consumption is been scoped.

Transmission Model :

  • The input of the block is coming from the Engine model named 'Engtrq'.

    This input is connected to Torque Converter and this output is connected to a differential which is named 'TransOutTrq'.

Torque Converter:

Differential:
  • The Transmission output torque is multiplied by the differential ratio and differential eff in these blocks and the torque is transmitted to the wheel as the axle torque.

Wheel Model:

  • This takes input from brake torque in the control model is been 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 into the workspace.
  • Vehicle Dynamics:

    This block consists of the longitudinal dynamics of the vehicle which consists of Aerodynamics force, Rolling Resistance Force, Grade Force etc..,

    Formulas used:

    where

    ρa - Air Density

    Af - Frontal Area

    Cd-Drag Coefficient

    M - mass of a vehicle

    g - Acceleration due to gravitational force

    θ - Slope angle

    These variables have already been preloaded to the workspace using a MATLAB script

  • The output of UDDS and HWFET cycles:
  • UDDS cycles:
  • UDDS stands for Urban Dynamometer Driving Schedule and refers to a United States Environmental Protection Agency-mandated dynamometer test on fuel economy that represents city driving conditions and is used for light-duty vehicle testing.
  • Though it was originally created as a reference point for fossil-fueled vehicles, it is also used to give estimates on how many miles an electric vehicle will travel on a single charge
  • Drive cycles and Actual velocity:
Engine Torque, Brake Torque, Gear Command:
Engine Fuel Consumption, Engine Fuel Rate:
Actual Engine Torque:
Gear Ratio, Transmission Input, Transmission Output
AeroDynamics, Grade Force, Rolling Resistance force:

Road Load, Tractive Force, Acceleration:

For HWFET Cycles:

The Highway Fuel Economy Test (HWFET or HFET) cycle is a chassis dynamometer driving schedule developed by the US EPA for the determination of fuel economy of light-duty vehicles [40 CFR 600, subpart B]. The HWFET is used to determine the highway fuel economy rating, while the city rating is based on the FTP-75 test.

Drive cycles and Actual velocity:

Engine Torque, Brake Torque, Gear Command:

Engine Fuel Consumption, Engine Fuel Rate:

Actual Engine Torque:

Gear Ratio, Transmission Input, Transmission Output:
AeroDynamics, Grade Force, Rolling Resistance force
Road Load, Tractive Force, Acceleration:

Stage 3:

POST-PROCESSING:

In this Post-processing, a MATLAB script is created to analyze data and generate plots and for some variables, I have renamed for loaded model and then plotted the results.

%% 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]
%% 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
figure()
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('Engine Speed [rpm]');
ylabel('Engine Torque [Nm]');
title('Engine Fuel Consumption Map [g/s]');
p4 = plot(out.Eng_Spd,out.Eng_Trq,'.','color','k');
legend([p1 p4],{'Max Curve','Operating Points'});
axis([Eng_map_spd(1)*30/pi Eng_map_spd(end)*30/pi 0 Eng_map_trq(end)]);
Note : Plots are takking from Simulink model,

Conclusion:

Hence the forward energy-based fuel consumption model of a conventional vehicle has been successfully simulated using MATLAB and Simulink.

Analyses and understands vehicles operating points based on engine speed,Torque,Transmission inputs & output speed, Pedal Positions, gear, and Distance travelled by the vehicle.

Post-Porcessing is most efficiently used to calculate the performance and require graph and it is been successfully plotted above.

Successfully Calculated vehicle fuel efficiency numbers (kmpl) for the given cycles such as UDDS and HWFET.

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