Project 2

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

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.

Process:-

Load the Project2 folder as the Current Folder in Matlab.

Run the “Project2_InitFile.m” Matlab script.

The Drive cycle selection is done here

%% Skill-Lync -> Hybrid Drives Development
% Project 1 - Conventional Vehicle Model
% By - Sachin Kushare

% 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 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
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 = 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);

After running this coding file open the Simulink model.

Vehicle Model:-

SIMULINK MODELLING

1] Layout:-

2] Driver:-

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.

3] Controller:-

The Controller block is the brain of the vehicle, representing the electronic control units. It is based on the driver inputs, it generates desired engine torque, desired transmission gear desired motor torque, and desired brake torque. These inputs are fed to the ‘Powertrain’ block which represents the drivetrain of the vehicle. In this, we require to create a Stateflow block explain in the next figure.

4] Stateflow for Controller:-

In this, we created four conditions stop, start, drive, and regeneration braking. The initial block represents the stop condition. In which the engine is off. The engine and motor throttle conditions are zero. Then the second block represents the start condition. In mode 1 the electric motor throttle is only used to provide the required torque and power to the vehicle. the engine is off and engine throttle conditions are zero.

State 1 and state 2 are connected using the links i.e. it moves from state 1 to state 2 when acceleration is less than one or SOC is less than the minimum SOC.

State 3 Represents mode 2 ii. e. engine is on and the engine throttle is also having a positive value from the driver but the electric motor throttle is zero. It changes from state 2 to state 3 when the engine speed is greater than or equal to the engine idle speed.

state 4 represents regenerative braking which is model 3 In this state the engine is on but the engine throttle is having no input from the driver whereas the electric motor receives the negative power due to braking.

The inputs given to the chart are Acceleration, brake, engine speed, vehicle speed, SOC, and clutch lockup.

The output we get from the chart is the mode, engine condition, engine throttle condition, and electric motor throttle condition.

Modification is done in all Unit modeling. they showed in the next figures.

5] 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 multiplies. the engine speed also gives to ideal control speed to integrate from this we meet the output of the engine required torque.

6] 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.

7] Shiftlogic In this unit:-

8] Threshold Value in This controller:-

9] Electric Motor Control Unit:-

10] Brake Control Unit:-

In this calculation brake torque and then all three control signals output is given to the powertrain.

11] 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 then it is integrated.

12] Electric Motor:-

13] Crankhub:-

14] 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 that are decoupled.

15] Torque Converter:-

16] Differential:-

In this taking input is the transmission output than it's going 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.

17] Wheel:-

In this model, we take the axle torque from the differential and the brake torque from the controller. it is substracted 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 velocity.

18] Vehicle Dynamics:-

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

Battery Modeling:-

19] Estimated storage system:-

In this we give input as power then it multiplies and gives to pack current. then from soc estimation meets output SOC is given to terminal voltage as input and then meets terminal voltage as output.

20] Terminal Voltage:-

In this user input, SOC it is connected to 1d lookup table 1st table variable interpolated as a state of charge and open voltage circuit. In the 2nd table, variable is interpolated as resistance discharge and state of charge and in the 3rd table variable is interpolated as resistance charge and state of charge. Then it is passed to the switch block for controlling the threshold. then they give voltage limits as max volts and min volts. then meet terminal Voltage.

21] Pack Current:-

In this, we integrate pack current and convert it rad to the amp then saturate and meet SOC.

Then we create one coding file for creating plots and to meet all answers. that file is shown next.

SIMULATION RESULTS

1. UDDS Drive Cycle :

Drive Cycle and Actual Velocity

Model

Post-Processing

• A MATLAB script is Created to analyze data and 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.

Fuel Economy Numbers for project 2

Sr. No Drive Cycle Fuel Economy Number (KMpl)

1 UDDS 15.0773

2 HWFET 17.1613

As we see the fuel economy is high in HWFET compared to UDDS. It is because in urban driving the vehicle encounters more traffic and it has to stop for a fever distance and it consumes more fuel at the starting. In HWFET the vehicle encounters no traffic and it moves without the use of too much braking so it will have more fuel economy number.

Comparing with fuel economy numbers for project 1

Sr. No Drive Cycle Fuel Economy Number (KMpl)

1 UDDS 14.209

2 HWFET 16.503

As we see the fuel economy numbers for project 2 are a bit higher when compared to project 1 because implementing the electric motor as it is a P1 hybrid may not have many variations in the fuel economy but as we implement other architecture it will increase by a huge amount.

3. The Time trace for the 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 fluctuates according to the engine torque required to achieve the drive cycle.
• The wheel speed and transmission output speed vary according to gear and differential ratio.

4. Engine torque, 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 is plotted on the fuel map and the operating point is under the maximum torque curve.

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

UDDS:

• The motor torque request is for engine start and region braking only. Electric input power is calculated by referring to 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 motor 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.

• The electric motor can operate between the max motoring torque curve and the max generating torque curve.

Conclusion :

The Various performance of characteristics and operating points of the UDDS drive cycle and HWFET drive cycle are analyzed and graphs are plotted.

• Time trace for engine, Transmission input, Transmission output, and wheel speed 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, and 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.

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