Challenge

Project 2

AIM:

1) Load the Project2 folder as the Current Folder in Matlab.
2) Run the “Project2_InitFile.m” Matlab script.
3) Copy the Conventional vehicle Simulink model created for Project 1 in this folder. Figure 1: P1 Hybrid ArchitectureHybrid Drives Development
4) Modify this model into a hybrid vehicle model. The lecture presentations can be used as reference. Battery and Supervisory controller models developed in the assignments can be reused.
5) Add additional ‘To Workspace’ blocks for transferring the desired Simulink vehicle data into the Matlab workspace.
6) Simulate the hybrid model on the desired drive cycles.

ANSWER:

P1 Mild Hybrid Electric Vehicle:-

The P1 architecture, with the electric machine connected directly to the crankshaft, is the solution adopted by Honda on their first generation Integrated Motor Assist (IMA) technology. The electric motor functions as a generator, during vehicle deceleration, as an engine starter, and as a motor (to assist the engine) during vehicle accelerations. One of the biggest advantage of this solution is that the electric motor can provide higher torque than the BiSG, since there is no belt limitation (due to slip). However, since there is no speed / torque ratio between the electric machine and crankshaft, the torque requirements on the electric motor can be quite demanding.

SIMULINK MODELLING

  • The Simulink model for the convection model is created using 3 main sub-blocks for the driver model, control model and powertrain block.
  • 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 engine torque, gear shifting and brake torque to the Powertrain model.

Two examples of P1 MHEV architectures are:

  • Honda Insight Hybrid 2009 (with Integrated Motor Assist technology)
  • Mercedes Benz S400 Bluehybrid 2010

For example, the main characteristics of the P1 MHEV.

1] ELectric Machine Performance:-

Maximum torque up to 34 Nm.

Maximum power: 10KW

Efficiency: Up to 94 Percent

2] Hybrid Modes:-

Idle stop and stop

Moving stop and start

Engine load shift

Torque assist

Torque boost

Energy recuperation

Brake generation

3] Advantages:-

Higher efficiency

The 12V starter can be removed

4] Disadvantages:-

Output torque limited by thje size of the elctric machine

Energy recuperation affected by engine friction losses

High impact on existing vehicle architecture

Higher overall cost of the electrical components

Air cooling not possible for electric machine

5] Overall charcteristics:-

Toruqe Boosting capacity: High

Electrical energy recuperation: Medium

Driveability improvements: Medium

Electrical Creep/drive: Possible

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.

VEHICLE MODEL

Pre-Processing

  • A MATLAB script has been created to load all the variables needed to run and post-process the Simulink model.
    Drive cycle selection is also done from here. Before running the Simulink vehicle model, the script is initialized at MATLAB to load all the variables in the workspace.
%% 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
load Vehicle_Data/EM_Honda_Insight_10kW
load Vehicle_Data/ESS_NiMH6


ESS_init_soc = 0.8;
ESS_soc_max = 0.9;
ESS_soc_min = 0.6;


%% Driver Parameters
Kp = 10;                    % P gain for driver PI model
Ki = 1;                     % I gain for driver PI model
Drive_Cycle_Select = 2;     % 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);
  • he Drive Cycle can be selected from this MATLAB Script, By changing the variable Drive _Cycle _Select to,
    1. UDDS
    2. HWFET
    3. FTP
    4. USO6
    5. NEDC
    6. WLTP

Driver Model :

Driver Model is a basic PI controller that generates accelerator and brake pedal outputs to match the desired.

Controller Model :

    • The 'Controller block is the brains of the vehicle, representing the electronic controls units. Based on the driver
      inputs, it generates desired engine torque, desired motor torque, desired transmission gear and desired brake
      torque. These inputs are fed to the 'Powertrain' block which represents the drivetrain of the vehicle

  • The Input to the state flow charts is Acceleration and Brake pedal input from the driver unit, Engine actual
    speed, Actual vehicle speed, SOC status and the clutch lockup state. And the State flow Outputs to the
    individual controllers are the Mode, Engine On/ off request, Engine input throttle and Electric motor input Throttle
  • The controller consists of an engine control unit, a transmission control unit, Electric Motor control unit and a
    brake control unit.
  • All control signals re passed to transmission model which represents the drive train.

Engine Control Unit :

Idle Speed Controller :

  • 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. 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.

Electric Motor Control Unit:

  • Motor Control Unit Compare EM speed with the maximum torque curve and maximum torque generation
    curves of the lookup table and give the required torque command to the Electric Motor. The EM throttle input is
    used to compare the lookup tables and to estimate the torque input required for the E-Motor.

Transmission Control Block :


  • The transmission control block controls the gear shifting using the study flow Variable chart.


  • The Gear shifting is Controlled according to the vehicle speed and throttle input.
  • The gear command is passed to the Transmission block to select the desired gear ratio.

Brake Control Unit :

  • Brake Control unit Produce required brake torque according to the brake pedal input and passes the brake torque in to the wheel block in the transmission model.

Powertrain Model :

  • The powertrain model includes all the components that convert the power of the engine into vehicle motion.
  • This includes Engine, Battery Pack, Electric Motor, Crank Hub, Transmission, Differential, Wheels and the vehicle
    body dynamics subsystems.
  • The control signals from the control model are transmitted via a bus to the corresponding blocks in the
    powertrain model.

Battery Model:

  • A Battery pack Subsystem is created with Electric power input, and Battery SOC as output.
  • 2 different subblocks have been created to determine the SOC and terminal voltage separately, the SOC being
    used to calculate the terminal voltage.

SOC Estimation Model :

  • Pack current in Ampere is converted to AmpHour and divides with Max Capacity and adds with the Initial soc
    to determine the SOC of the battery at each instance, the SOC value is limited between 0 to 1.

Terminal Voltage Model :

  • Ideal voltage and internal resistance are determined by ID lookup tables, and battery voltage is determined
    using the model.
  • The specified values are sent back to workspace using the Two Workspace block and can used for post
    processing.

Engine Model :

  • Based on the Engine speed The required torque from the controller 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.

Electric Motor Model :

  • Based on the Engine speed The required EM torque from the controller is saturated between Max EM torque
    curve and max EM torque Generation curve and passes the EM torque to the Crank Hub.
  • The 2D lookup table is used to calculate the Input Electric Power to the Motor based on EM speed and EM torque.

Crank Hub :

  • Crank Hub adds up the EM torque and the Engine torque and pass it to the transmission block as the crank
    torque.

Transmission Model :

  • The Crank is connected to the automatic transmission via a torque converter. The output of the transmission is
    connected to the differential.
  • New Clutch LockUp feature is adding to this Hybrid version.

  • The gear selection from the transmission control unit is multiplied by the engine torque in this block, and the
    efficiencv and enaine dunamics of the torque converter are apolied in this model.

Torque Converter :

  • Torque converter defines the pumb and turbine torque by the clutch lock up status, and the combination gives
    us the desired transmission torque.

Differential Model :

  • The transmission output torque is multiplied by the differential ratio and differential efficiency in this block and the torque is transmitted to the wheel as the axle torque.

Wheel Model :

  • The brake torque from the control model is subtracted from the Axle torque and divides from the rolling radius to determine the Tractive force.
  • The Wheel speed is calculated from the vehicle velocity and saved in the workspace.

Vehicle Dynamics :

  • The longitudinal dynamics of the vehicle along with the road load is represented in the 'Vehicle Dynamics' block.
  • Tractive Force and Road loads are used to calculate the vehicle velocity,

`(etat* lambdat*Te)/(Romega) = M(dV_(veh))/dt + 1/2rhoaAfCd(V_(veh)+V_(omegad))^2+CrMgcostheta+Mgsintheta`

`(etat* lambdat*Te)/(Romega) =`Tractive force

`1/2rhoaAfCd(V_(veh)+V_(omegad))^2+CrMgcostheta+Mgsintheta =` Road Load

Where,

`rhoa =` Air Density

`Af =` Frontal Area

`Cd =` Drag Coefficient

`Cr =` Rolling Coefficient

`M =` Mass of Vehicle

`g =` Acceleration due to gravity

`theta =` Slope

  • The variables are loaded on the workspace using MATLAB script.
  • The Acceleration, Velocity and Distance travelled are Calculation and stored in the workspace.

SIMULATION RESULTS

  1. UDDS Drive Cycle :

Drive Cycle and Actual Velocity

Model

Post-Processing

  • A MATLAB script is Created to analyse data and to generate plots. Here we rename the variables loaded from the model, do some basic post-process calculations and generate results and plots.
%% 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()
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(Eng_Spd,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)]);

Result :

1. Drive Cycle

UDDS :

HWFET :

2. Fuel economy numbers (kmph) for UDDS and HWFET cycle.

UDDS :

For convectional Vehicle Model (Projet 1)

`("Average"" Speed" [kmph])/(31.35)`=`("Maximum""Speed"[kmph])/(91.99)`=`("Fuel Economy"[kmpl])/(16.89)`

For P1 Hybrid Vehicle Model

Fuel Economy = 18.07 Kmpl

`("Average"" Speed" [kmph])/(31.531)`=`("Maximum""Speed"[kmph])/(91.395)`=`("Fuel Economy"[kmpl])/(18.072)`

  • Fuel economy improves as engine eliminates negative torque and negative power. Negative Energy can be revived with regional breaking.

HWFET :

For convectional Vehicle Model (Projet 1)

`("Average"" Speed" [kmph])/(77.683)`=`("Maximum""Speed"[kmph])/(96.925)`=`("Fuel Economy"[kmpl])/(21.228)`

For P1 Hybrid Vehicle Model

Fuel Economy = 22.00 Kmpl

`("Average"" Speed" [kmph])/(77.682)`=`("Maximum""Speed"[kmph])/(96.401)`=`("Fuel Economy"[kmpl])/(21.997)`

  • Fuel efficiency is slightly improved as highway has less negative power when driving. But all negative power will be regenerated with regen braking and battery SOC will increase.
  • The City Fuel Economy is much lower than highway drive as the brake padel engagement and idle time on drive cycle is less.

3. The Time trace for engine, Transmission input,transmission output and wheel speed

UDDS :

HWFET :

  • Much of the fluctuating input speed is facilitated by the torque converter, and the transmission input speed fluctates according to the engine torque required to achieve the drive cycle.
  • Wheel speed and transmission output speed vary according to gear and differential ratio.

4. Engine troque, Engine power, fuel rate and fuel consumption

UDDS :

HWFET :

  • The torque requirements of the drive cycle are different, so the fuel flow rate varies and fuel consumption is calculated.
  • The HWFET drive cycle has higher power and torque requirements and less negative torque and power.

5. Accelerator and brake pedal, gear command, vehicle desired and actual speed, vehicle distance

UDDS:

  • Acceleration and brake pedals are used more because the drive cycle is not very smooth and the gear has to be shifted frequently.

HWFET:

  • Brake requirements are lower, more accelerator pedals are applied on the highway drive cycle, and gear shifts often occur because the drive cycle is smoother.
  • Acceleration and brake pedal, the gear command of the transmission control unit, the required speed of the vehicle, the actual vehicle speed and the actual vehicle distance are plotted.

6. The engine operating points on the engine fuel map

  • The engine operating point are plotted on the fuel map and the operating point is under the maximum torque curve.

7. The Motor speed, torque, motor input power.

UDDS:

  • Motor torque request is for engine start and region braking only. Electric input power is calculated by referring the motor speed according to the EM motor torque request.

HWFET:

  • EM motor torque demand is low as the vehicle moves at high speeds and less idle on highway drive

8. The Pack voltage, current and Soc

UDDS:

  • Battery SOC is responding according to the Motor torque request and the Regen braking.

HWFET:

  • Battery SO increases on highway drive cycles due to lower EMotor usage and region braking battery charging.

9. The motor operating points on the motor input power map, with the motor max motoring and generating
torque curves.

  • Electric motor can operates between max motoring torque curve and max generating torque curve.

Conclusion :

The Various performance of characteristics and operating point of UDDS drive cycle and HWFET drive cycle are analysed and graphs are plotted.

  • Time trace for engine, Transmission input, Transmission output and wheelspeed with respect to time.
  • Engine torque, Engine power, Fuel rate and Fuel consumption with respect to time.
  • Accelerator and brake pedal, gear command and vehicle desired, actual speed, vehicle distance with respect to time.
  • Engine operating points on the engine fuel map with respect to time
  • Motor speed, Torque, Motor input power with respect to time.
  • Pack voltage, Current and State of charging with respect to time.
  • The motor operating points on the motor input power map with respect to time.

Also it comparing with HWFET drive cycle and their numbers also compared.

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