Project 1
Q.Project 1 deals with the development of a forward energy-based fuel consumption model of a conventional vehicle.
Answer-
Title:-
Deals with the development of a forward energy-based fuel consumption model of a conventional vehicle.
Aim:-
1] Build a Simulink model using blocks and complete the vehicle model.
2] Writing scripts in MATLAB to load all the variables required for running the Simulink model.
3] Tabulate the fuel economy numbers (kmpl) for UDDS and HWFET cycles.
4] Plot the time trace for the engine, transmission input, transmission output, and wheel speed on one plot.
5] Plot engine torque, engine power, fuel rate, and fuel consumption using subplots.
6] Plot accelerator and brake pedal, gear command, vehicle desired and actual speed, and vehicle distance using subplots.
7] Plot the engine operating points on the engine fuel map.
8] Generate the plots for both drive cycles.
9] Study of Conventional vehicle Simulink model and creates graphs.
Conventional Vehicle:-
Conventional vehicles use an internal combustion engine fueled by gasoline or diesel to power the wheels. In this, the heat engine uses the principle of heat release through the combustion of a fuel with an oxidizer in a combustion chamber to create expanding gases that push against a piston creating force and torque output.
In this vehicle, the engine converts chemical energy stored in the fuel into heat which is used to produce useful work. Typically use fossil fuels like petroleum (petrol and diesel).
The most popular type of engine used in this system is 4 strokes reciprocating engine. The engine in the cylinder process can be represented by ideal thermodynamic cycles such as the Otto cycle, Diesel cycle. The Otto cycle is an ideal cycle that describes the cycle process for spark ignited SI engine. and the Diesel cycle is the ideal cycle that describes the cycle process for a compression-ignited CI engine.
Energy and performance of vehicle:-
In this system, the power demand on the wheel needs to be instantly supplied by the powertrain. In other words, the power coming from the powertrain dictates the power demand on the wheels (as per performance viz, acceleration, speed, etc determined by it.
In this vehicle, the powertrain consists of an engine connected to the wheels through a transmission therefore the power comes from the engine through the transmission.
Conventional powertrain efficiency:-
The engine generates power by converting chemical energy stored into mechanical energy through the process of combustion. This process of energy conversion also has efficiency and the energy input is in the form of fuel consumption.
- Instantaneous fuel consumption is given as
mf=Pe/ηe*ηt*QLHV
Where,
mf = mass flow rate in [kg]
pe = Power of engine
pt = power of transmission
nt = efficiency of transmission
ne = efficiency of the engine
QLHV = it is th calorific value/ lower heating value of the fuel.
In this system of IC engines if the power at the wheels is zero the engine is idling and still consumes some fuel to overcome the engine drag loss and keep it spinning this is the idling fuel consumption and is known as the idling process. The above-mentioned formula is applicable only when the wheel power is strictly powered. When the wheel power is negative either the engine is disengaged and idling or the engine is engaged and provides some engine braking due to the engine drag losses.
The engine is consuming fuel when it is idling but even for engine braking, the engine might be consuming some fuel.
The fuel consumption not only depends on the power requirement at the wheels but also is required to generate power to run the various engine and vehicle accessory loads.
System Dynamics:-
It deals with the modeling of multi-domain systems through the use of a unified approach based on an ordinary differential and algebraic equation describing the static and dynamic effects.
Each system has are two generalized variables-
1] Efforts:- It is a generalized force variable. ex-torque, force, voltage, and heating value.
2] Flow:- It is the generalized flow/velocity variable. ex:- velocity, current, mass flow rate.
3] Power:- It is the product of the effort and flow variable. It is interchangeable between energy domains.
Energy-based models- Element models
To model the internal physical properties of the element and the losses there are basically two kinds of approaches.
1] Map-based models:- Elements are modeled using maps that characterized the relationship between the input and output, output and losses, etc.
2] Analytical models:- Elements are modeled using physical equations that represent the internal dynamics. These are the two extremes most models are a combination of the two with some dynamics models analytically and some using maps.
In this model, We use Forward Model:-
It is also known as dynamic simulation. Dynamic models are used for detailed simulations. In this model force/torque/power is the input and the vehicle state variable velocity and acceleration are the outputs. The models and simulation are more realistic due to physical casualty and hence appropriate for control development. There is a feedback loop to meet the desired vehicle state. It is mainly used to simulate a vehicle on a driving cycle to analyze the dynamic behavior of the system helps significantly in control development.
MATLAB scripts:-
Used to load all the variables required 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.
%% 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 the 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);Now,
Let's see the Simulink model of a conventional vehicle,
In this project, a typical midsize car with a 1.9L engine and a 4-speed automatic transmission is considered. Data is taken from the ADVISOR database developed by NREL, USA. The transmission shift map and controller are taken from Matlab/Simulink example database.
The model developed has the capability to simulate the vehicle on different drive cycles like UDDS, HWFET, FTP, NEDC, etc.
“Project1_InitFile.m” is a Matlab script used to load all the variables required 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.
1)Driver Model:-
It is 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. In this we use drive cycles and based on these results of fuel consumption and emissions the vehicle gets certified and it also forms a basis for uniform assessment. It is based on time, and velocity then it all integrates and creates the output acceleration pedal and a brake pedal.
Scope Plot-
2)Control Model:-
The ‘Controller’ block is the brains of the vehicle, representing the electronic control units. It is 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.
i] Engine Control Unit:-
In this control model, We use an engine control unit that gives input Engine speed by creating a look-up table. in that table, we give input Maximum torque and map speed then also create 2nd lookup table in that gives input ct torque and map speed then it substracts and multiplied. the engine speed also gives to ideal control speed to integrate from this we meet the output of the engine required torque.
Scope Plot-
ii] Transmission Control Unit:-
In this unit, we create a steady flow variable state for controlling of gears of the vehicle in ascending and descending order with respect to time, speed, and distance. and give input to this steady state is vehicle speed in m/s to mph.
iii] Brake Control Unit:-
In this unit, we can calculate brake torque, and then all three control signals output is given to the powertrain.
3)PowerTrain:-
The powertrain encompasses every component that converts the engine's power into movement. This includes the engine, transmission, driveshaft, differentials, axles; basically anything from the engine through to the rotating wheels.
i] Engine:-
In this model, we used a map-based model to model the fuel consumption of the engine. It is based on maximum Torque and minimum torque from the controller. and then it saturated torque and gives output then saturated torque and speed map give fuel consumption takes the speed and torque then the output goes into saturated than its integrated.
Scope Plot-
ii] Transmission:-
In these models, we take engine torque, and gear selector from the controller for transmission of gear ratio. The ratio is multiplied by the transmission input torque and then the transmission efficiency positive torque and negative torque give the transmission input speed. In this case, the torque converter connects the engine to the transmission it is part of a transmission. In it basically, engine dynamics are decoupled.
Scope Plot-
iii] Differential:-
In this taking input is the transmission output then it's going to the differential ratio multiplied by the output and input torque then meets axle torque. The axle torque is lower than the transmission torque and differential ratio.
iv] Wheels:-
In this model, we take the axle torque from the differential and the brake torque from the controller. it is substracted and multiplied by the rolling radius and velocity then we meet the tractive force from the axle and brake torque. and the wheel speed is met using velocity.
v] Vehicle Dynamics:-
This model takes tractive force and road load. It detects vehicle speed based on tractive force and road load.
Scope Plot-
Now For creating Plots we use MATLAB coding-
%% 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]
%% 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(2)
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]');
figure(3)
hold on
grid on
plot(Eng_Fuel_Consump);
a). Tabulate the fuel economy numbers (kmpl) for UDDS and HWFET cycles. This forms the baseline numbers for comparison with the future hybrid version.
i)For UDDS Cycle-
i)For HWFET Cycle-
In comparing both cycles we used the UDDS drive cycle. It's best for asses of fuel consumption and Pollutant emissions of vehicles in a normalized way.
b. Plot the time trace for the engine, transmission input, transmission output, and wheel speed on one plot.And Plot accelerator and brake pedal, gear command, vehicle desired and actual speed, vehicle distance using subplots.
In this graph, we see the transmission input and transmission output will fluctuate up and down as increasing speed and time. And for comparing brake of vehicle the accelaration of vehicle is more so the brake torque is min required. and the gear shifting is also required wrt time.
C. Plot engine torque, engine power, fuel rate and fuel consumption using subplots.
In this engine torque, Engine power, engine fuel rate and engine fuel consumption is increase increasing wrt time.
e. Plot the engine operating points on the engine fuel map.
In this plot we can see the as decrease torque speed is increase.