Project 1

Aim:- 

1] Build Simulink model using blocks and complete the vehicle model.

2] Writting 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 cycle. 

4] Plot the time trace for 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, 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 combustion of a fuel with an oxidizer in a combustion chamber to create expanding gases which pushes against a piston creating forcce and torque output.

In this vehicle 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 is used in this system is 4 stroke reciprocating engine. Engine in cyclinder process can be represented by ideal thermodynamic cycles such as Otto cycle, Diesel cycle. Otto cycle is a ideal cycle thet describes the cycle process for spark ignited SI engine. and the Diesel cycle is the ideal cycle thet describes the cycle process for a compression ignited CI engine.

Energy and performance of vehicle:-

In this system trge power demand on the wheel need to instant supplied by the powertrain. In otyher word the power coming from the powertrain dictates the power demand on the wheels (as per performance viz, acceleration, speed etc is determined by it.

In tis vehicle the powertrain is consists of an engine connected to the wheels through a transmission therefore the power comes from the engine through the transmission.

Conventional powwertrain efficiency:-

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

- Instantaneous fuel consumption is given as 

mf=Pe/ηe⋅nt⋅QLHV

Where,

mf = mass flow rate in [kg]

pe = Power of engine

pt = power of transmission

nt = efficiency of transmission

ne = efficiency of engine

QLHV = it is th ecalorific value/ lower heating value of fuel.

In this system of IC engine if tge 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 know as idling process. Above mentioned formula is applicable only when the wheel power is strictly power. When the wheel power is negative either th engine is disengaged and idling or the engiune is engaged and providing 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 depend on the power requirement at the wheels but also is required to generate power to run the various engine and vehicle accessory loads.

Energy based models- Element models

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

1] Map based models:- Elements are modeled using maps which characterized the relationship between the input and output , output and losses etc.

2] Analytical models:- Elements are modeled using physical equation that represent the internal dynamics. These are the two extremes most models are a combination of the two with some dynamics models analytically and for some using maps.

In this model We use Forward Model:-

It 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 simulatios are more realistic due to phhysical casualty hence appropriate for control development. There is feedback loop to meet the desired vehicle state. It is mainly used to simulate a vehicle on a driving cycle to analyse the dynamic behaviour 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.

%% Skill-Lync -> Hybrid Drives Development

% Project 1 - Conventional Vehicle Model

% By - Dharmesh Ravindra Bonde 

% 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 coefficientRw = 0.35;

% Rolling radius [m]Cd = 0.33;

% Drag coefficientAf = 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 RatioDiffEff = 0.99;

% Differential efficiency (assumed independent of operating conditions)NumGear = 4;

% Number of gears in transmissionTransGear = [1:NumGear];

% Transmission GearsTransRatio = [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/PumpTrqTC_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]

% 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);

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 fro the based on these results of fuel consumption and emissions the vehicle gets certified and it also forms a basis of uniform asessment. It is based on time, velocity then its all integrate and creates output accelration pedal and brake pedal.

Control Model:-

The ‘Controller’ block is the brains of the vehicle, representing the electronic controls 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.

1] Engine control Unit:

In this control model We use engine control unit in that give input Engine speed through creating look up table. in that table we give input Maximum torque and map speed then also create 2nd look up trable in that give input ct torque and map speed then it substracts and multiplied. the engine speed also give to ideal contro speed to integrate from this we meet output of engine required torque.

2] Transmission Control Unit:-

In this unit we create steadfy flow variable state for controlling of gears of vehicle as in ascending and descending order with respect to time, speed, distance. and give input to this steady state is vehicle speed in m/s to mph.

3] Brake Control Unit:-

In this calculate brake torque and then all three control signals output is give to powertrain.

3] PowerTrain:-

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

1] Engine:-

In this model we used map based model to model the fuel consumption of engine. It is based on maximum Torque and minimum torque from the controller. and then it saturated torque and give output then saturated torque and speed map give fuel consumption takes the speed and torque then the output goes into saturated then its integrated.

2] Transmission:-

In these model we take engine torque, gear selector from controllerb for transmission of gear ratio. The ratio is multiply by transmission input torque and then the transmission efficiency positive torque and negative torque gives transmission input speed. In this case torque converter connects the engine to transmission it is part of transmission. In it basically engine dynamics and that is decoupled.

3] Differential:-

   In this taking input is the transmission output then its going to the differential ratio multiplied the output and input torque then meet axle torque. The axle torque is a lower than the transmission torque and differential ratio.

 4] Wheels:-

 In this model we take the axle torque from differentail and brake torque from controller. it is substracts and multiplied rolling radius and velocity then we meet the tractive force from axle and brake torque. and the wheelspeed is meet using velocity.

 5] Vehicle Dynamics:-

   In this takes tractive force and road load. Itis dictates vehicle speed based on tractive force and road load. 

 the dynamic equation for calculating road load is 

 Meq dVveh|dt=ηtλtot|Rw Tm

−(1|2p⋅A⋅Cd⋅(Vveh+Vw∈d)2+Cr⋅M⋅g⋅cos(θ)+M⋅g⋅sin(θ))

where,

p = air density [kg/m^3]

A = Frontal area [m^2]

Cd = drag Coefficiend

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 then we meet acceleration of vehicle and velocity of vehicle it mean vehicle distance and vehicle speed.

%% Skill-Lync -> Hybrid Drives Development

% Project 1 - Conventional Vehicle Model

% By - Dharmesh Ravindra Bonde

% 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]

Wheel_Speed = out.wh_speed; % Wheel speed [kmph]

Eng_Fuel_Rate = out.Eng_Fuel_Rate % Engine fuel rate [%]

%% 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 transmission IN/OUT 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, Wheel_Speed, 'linewidth',1, 'color', 'blue')

ylabel('Speed [rpm]')

xlabel('Timem [s]')

xlim([0, Time(end)]);

ylim([0, 6000]);

legend('Trans Input','Trans Output','Wheel Speed');

 %% Plotting vehicle characteristics time trace to Engine speed, Engine Torque, Engine Power, 

% And Engine fuel rate, Engine fuel consumption

% Data conversion from Double Timeseries

Eng_spd = Eng_Spd.Data(:,1); % engine speed

Eng_trq = Eng_Trq.Data(:,1); % engine torque

Eng_pwr = Eng_Pwr.Data(:,1); % engine power

Eng_fuel_rate = Eng_Fuel_Rate.Data(:,1); % engine fuel rate

Eng_fuel_consumption = Eng_Fuel_Consump.Data(:,1); % engine fuel consumption

Veh_dist = Veh_Dist.Data(:,1); % vehicle distance

Veh_spd = Veh_Spd.Data(:,1); % vehicle speed

% Plotting Engine speed, Engine Torque, Engine Power,Engine fuel rate,Engine fuel consumption wrt Time 

figure(2)

subplot(2,2,1)

plot(Time,Eng_trq,'linewidth',1,'color','black')

xlabel('Time [s]')

ylabel('Torque [Nm]')

legend('Engine Torque')

grid on

subplot(2,2,2)

plot(Time,Eng_pwr,'linewidth',1,'color','blue')

xlabel('Time [s]')

ylabel('Power [KW]')

legend('Engine Power')

grid on

subplot(2,2,3)

plot(Time,Eng_fuel_rate,'linewidth',1,'color','red')

xlabel('Time [s]')

ylabel('Fuel Rate [%]')

legend('Engine Fuel Rate')

grid on

subplot(2,2,4)

plot(Time,Eng_fuel_consumption,'linewidth',1,'color','green')

xlabel('Time [s]')

ylabel('Fuel Consumption')

legend('Engine Fuel Consumption')

grid on

% Plotting fuel economy Vs Engine Fuel consumption 

figure(3)

plot(Eng_fuel_consumption,Eng_fuel_rate,'color','r')

xlabel('Fuel consumption')

ylabel('Fuel Rate [%]')

title('Fuel economy Vs Fuel Consumption')

grid on

%% Potting Accelerator pedal, Brake pedal and gear command with respect to time

figure(4)

subplot(2,1,1)

hold on

plot(Time, Acc_Pdl, 'linewidth', 1, 'Color', 'black');

plot(Time, Brk_Pdl, 'linewidth', 1, 'Color', 'red');

ylabel('Pedal [%]')

xlabel('Time [s]');

xlim([0, Time(end)]);

grid on

legend('Accel','Brake');

title('Acceleration & Brake Pedal wrt Time')

subplot(2,1,2)

plot(Time, Gear_Cmd, 'linewidth', 1, 'Color', 'black');

xlim([0, Time(end)]);

xlabel('Time [s]');

ylabel('Gear');

grid on

title('Gear command wrt Time')

% Plotting gear command vehicle desired with actual speed

figure(5)

subplot(2,1,1)

plot(Veh_spd, Gear_Cmd, 'linewidth', 1, 'Color', 'black');

xlabel('Speed [rpm]');

ylabel('Gear');

grid on

title('Gear command wrt vehicle speed')

subplot(2,1,2)

plot(Veh_dist, Gear_Cmd, 'linewidth', 1, 'Color', 'red');

xlabel('Distance [kmpl]');

ylabel('Gear');

grid on

title('Gear command wrt Distance')

%% 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/piEng_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