Project 1

Title: Deals with developing a forward energy-based fuel consumption model for a conventional vehicle.

Aim:

1. Build the 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 (km) for UDDS and HWFET cycle.
4. Plot the time trace for engine, transmission input, transmission output, and wheel speed on one plot.
5. Plot engine torque, power, fuel rate, and consumption using subplots.
6. Plot accelerator and brake pedal, gear command. Vehicle desired and actual speed, 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 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 used to produce valuable work. Typically use fossil fuels like petroleum (petrol and diesel).

The most popular engine type used in this system is four strokes reciprocating engine Engine in the cylinder process can be represented by ideal thermodynamic cycles such as the Otto cycle Diesel cycle. The Otto cycle is a perfect cycle that describes the cycle process spark-ignitednited SI engine. The Diesel cycle is the ideal cycle describing the process for a compression ignited Cl engine.

Energy and performance of vehicle:

In this system, the power demand on the wheel must instantly be supplied by the powertrain. In other words, the power coming from the powertrain dictates the power demand on the reels (as per performance viz, acceleration, speed, etc. is 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 information.

Conventional powertrain efficiency:

The engine generates power by converting chemical energy stored into mechanical energy through combustion. This energy conversion process also has efficiency, and the energy input is in the form of fuel consumption.

Instantaneous fuel consumption is given as

`mf=(Pe)/(etae.etat.QLHV)`

Where,

MF = mass flow rate in (kg)

pe = Power of engine

pt = power of transmission

no = efficiency of transmission

no = efficiency of the engine

QLHV = it is thecalorific value/ lower heating value of 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 an idling process. The formula mentioned above applies only when the wheel power is strictly power. When the wheel power is negative, either the engine is disengaged and idling, or the engine is engaged and providing some engine braking due to the engine drag losses.

The engine consumes fuel when idling, but the machine might consume some power even for engine braking.

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 the algebraic equation describing the static and dynamic effects

Each method has two generalized variables:

1. Efforts are generalized force variables ex- torque, force voltage, and heating value.
2. Flow is the generalized flow/velocity variable ex velocity, current, and mass flow rate.
3. Power: It is the product of the effort and flow variably interchangeable between energy domains.

Energy-based models- Element models

To models the internal physical properties of the element and the losses, there are two kinds of approach,

• Map-based models:: Elements are modeled using maps that characterize the relationship between the input and output, output and losses, etc.
• Analytical models:- Elements are modeled using physical equations representing 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 outputs. The models and simulations 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 mainly simulates a vehicle on a driving cycle to analyze the system's dynamic behavior and significantly helps control development.

MATLAB scripts:

It loads all the variables required for running the Simulink model and post-processing. The drive cycle selection is also made here. Before running the Simulink vehicle model, run this initialization script.

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Skill-Lync -> Hybrid Drives Development
% Project 1 - Conventional Vehicle Model
% By - Ullekh Gambhira 

% 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);

Now,

let's see the Simulink model of a conventional vehicle,

This project considers a typical midsize car with a 1.9L engine and a 4-speed automatic transmission. 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 can simulate the vehicle on different drive cycles like UDDS, HWFET, FTP, NEDC, etc.

"Project! initial.m" is a Matlab script that loads all the variables required for running the Simulink model and post-processing. The drive cycle selection is also made here. Before running the Simulink vehicle model, run this initialization script.

DRIVER MODEL:

It is modeled using a 'Driver' block, a primary PI controller that generates accelerator and brake pedal outputs to match the desired and actual vehicle speeds. We use drive cycles based on fuel consumption and emissions results. The vehicle gets certified and forms a basis of uniform assessment. It is based on time, and velocity, then integrates and creates output acceacceleration brake pedals.

GRAPH CREATED FROM SCOPE IN DRIVER MODEL:

CONTROL MODEL:

The controller block represents the vehicle's brain, representing the electronic controls units. It is based on the driver Inputs; it generates desired engine torque, transmission gear, and brake torque. These inputs are fed to the Powertrain block, which represents the vehicle's drivetrain.

1) 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 offer input Maximum torque and map speed, then make 2nd lookup table in that give input ct torque and, map speed then subtracts and multiplies the engine speed and provide to superior control speed to integrate from this we meet the output of engine required torque.

GRAPH CREATED FROM SCOPE IN DRIVER MODEL- Engine control unit:

2) 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 concerning time, speed, and distance. And give input to this steady-state is vehicle speed in m/s to mph.

3) BRAKE CONTROL UNIT: Brake torque and all three control signals output are given to the powertrain in this calculation.

GRAPH CREATED FROM SCOPE IN DRIVER MODEL:

POWER TRAIN:

The powertrain encompasses every component that converts the engine's power into movement. This includes the engine, transmission, driveshaft, differentials, axles, and anything from the engine to the rotating wheels.

1) ENGINE: In this model, we used a map-based model to model the engine's fuel consumption. It is based on maximum Torque and minimum torque from the controller. Then it saturated torque and gives output, then flooded torque and speed map show fuel consumption takes the speed and torque then the work goes into saturated than integrated.

GRAPH CREATED FROM SCOPE IN DRIVE MODEL: ENGINE TORQUE

2) TRANSMISSION: We take the controller's engine torque and gear selector for gear ratio transmission in this model. The ratio is multiplied by transmission input torq, use, and thus the transmission efficiency positive and negative torque gives transmission input speed. In this case, the torque converter connects the engine to the transmission. It is part of the transmission. Its engine dynamics and that is decoupled.

GRAPH CREATED FROM SCOPE IN DRIVER MODEL: 1] Transmission in speed 2] Gear Ratio 3] Differential Ratio

3) DIFFERENTIAL: In this, input is the transmission output, then it goes to the differential ratio multiplied by the output and input torque, then meet axle torque. The axle torque is lower than the transmission torque and differential ratio.

4) WHEELS: In this model, we take the axle torque from the differential and brake torque from the controller; it is subtracted and multiplied by rolling radius and velocity, then we meet the tractive force from the axle and brake torque. And the wheel speed is met using momentum.

5) VEHICLE DYNAMICS:

This takes tractive force and road load. It dictates vehicle speech based on tractive force and road load

the dynamic equation for calculating road load is

`Meq(dVveh)/dt=(etatlambdatOt)/(Rw)Tm-(1/2p.A.Cd.(Vveh+Vw epsilond)^2+Cr.M.g.cos(theta)+M.g.sin(theta))`

where,

p = air density [kg/m^3]

A = Frontal area (m^2]

Cd = Drag Coefficient

Vveh = velocity of vehicle [m/s^2)

Vwind = velocity of wind [m/s^2]

Cr = rolling resistance coefficient

M = mass in [kg]

g = gravity.

Then we calculate and integrate the vehicle's acceleration and velocity, which means vehicle distance and speed.

GRAPH CREATED FROM SCOPE IN DRIVER MODEL: 1] Road Load 2] Acceleration 3] Tractive Force

Now,

We, Compute the Fuel economy numbers using UDDS and HWFET Cycle:

1) UDDS Drive Cycle

1] Time Vs. Speed: In this, the speed is increasing continuously.

2] Aerodynamic Drag: Drag increase when the power increase.

3] Rolling Resistance: It also increases when power is increased over time.

4] Total Power:

Conclusion: Total power increases slowly as rolling resistance, aerodynamic drag, and internal resistance increase.

2) HWFET Drive Cycle:

1] Time Vs. Speed: Speed continuously increases over time.

2] Aerodynamic Drag: Drag increases when the power is increased.

3] Rolling Resistance: Resistance decreases over time.

4] Total Power:

Conclusion:

Total Power increases slowly as increasing aerodynamic drag and inertial resistance. But in this drive cycle, destructive impact occurs due to decrease rolling resistance.

Result:

In comparing both cycles, we used to UDDS drive cycle. Its best to asses of fuel consumption and Pollutant emissions of the vehicle in a normalized way.

Now for creating plots, we use MATLAB Coding:

1) Plotting vehicle characteristics time trace transmission IN/OUT and Wheel Speed:

In this graph, we see the transmission input, and transmission input and transmission out will fluctuate up and down as increasing speed and time.

2) Plotting vehicle characteristics time trace to Engine Speed, Engine Torque, Engine Power, Engine Fuel Rate, Engine Fuel Consumption

In this engine, torque, engine power, engine fuel rate, and engine fuel consumption is increasing with respect to time.

3) Plotting fuel economy Vs. Engine Fuel consumption:

In this, the engine fuel consumption suddenly increases as the increasing fuel economy is constant, then the fuel consumption is also constant.

4) Potting Accelerator pedal, Brake pedal, and gear command with respect to time:

In this, as comparing brake of the vehicle, the acceleration of the vehicle is more so the brake torque is min required, and the gear shifting is also required wrt time.

5) Plotting gear command vehicle desired with actual speed:

In this, the gear shifting is required to increase vehicle speed as the shifting order is gear 1, then gear 2, then gear3, and then gear 4.

6) Plotting engine operating points on engine fuel map:

In this, the as decrease torque sped is increase.