Challenge

WOT Condition Part-2

MMuthavarapu Chaitanya Krishna5 Apr 2021

AIM: To Study WOT condition for HEV and EV reference applications of Powertrain Blocksets.

OBJECTIVES:

What is the difference between mapped and dynamic model of engine, motor and generator? How can you change model type?
How does the model calculate miles per gallon? Which factors are considered to model fuel flow?
Run the HEV Reference Application with WOT drive cycle. Change the grade and wind velocity in the environment block. Comment on the results.
Keeping all other parameters same, compare the simulated results of hybrid and pure electric powertrains.

INTRODUCTION:

Powertrain Blocksets: To Model and Simulate Automotive Powertrain Systems.

Powertrain Blockset provides fully assembled reference application models of automotive powertrains, including gasoline, diesel, hybrid and electric systems. It includes a component library for simulating engine subsystems, transmission assemblies, traction motors, battery packs, and controller models. Powertrain Blockset also includes a dynamometer model for virtual testing.

This can be referred as the Library of Automotive Components used to construct a Vehicle Model ranging of all types and applications and later used for Simulation.

Powertrain Blockset provides a standard model architecture that can be reused throughout the development process. You can use it for design trade-off analysis and component sizing, control parameter optimization and hardware-in-the loop testing. You can customize models by parameterizing components in a reference application with your own data or by replacing a subsystem with your own model.

Key Features:

Fully assembled models for gasoline, diesel, hybrid and electric powertrains.
Libraries of engine, transmission, traction motor, and battery components.
Basic controllers for powertrain subsystems.
Standard drive cycle data, including FTP75, NEDC and WOT.
Engine dynamometer model for virtual calibration and testing.
MDF file support for calibration data import.

Powertrain Blockset provides a library of automotive components as well as pre-assembled engine dynamometer and complete vehicle models for fast desktop simulation and real-time HIL testing (Hardware in Loop).

The Powertrain library includes the components essential for modelling automotive systems. You can assemble these library blocks to create a complete engine subsystem. You can then connect this engine with other components to create a complete vehicle model that you can simulate under a variety of test conditions.

Power Train Blocksets uses MATLAB & Simulink for the Simulation.

OBJECTIVE 1: What is the difference between mapped and dynamic model of engine, motor and generator? How can you change model type?

Powertrain Blockset provides two types of combustion engine models:

Mapped
Dynamic

Mapped Model:

The mapped model refers to the block where the inputs & outputs of the block are given in steady-state lookup tables. For example, in the case of a SI engine block, the inputs of the engine like fuel intake quantity, air intake, etc. and outputs of the engine such as torque output, power output, etc. are given in the form of lookup tables. Mapped model simulation is to be done when we have engine data. This type of simulation model is used for quasi steady-state simulations.

The mapped model is used for simulation to study the effect of a factor on the simulation in the system level. For example, we can use the mapped engine model to study the effect of valve timing, quantity of fuel injected/sprayed, etc. on the engine output parameters.

This is similar for the motor and generator models.

Figure 1.1, Mapped Motor Subsystem

Dynamic Model:

Dynamic model refers to one which breaks down a system or sub-system into its components. The output of these components combined is taken as the output of the system. This type of model can be used when we need a more detailed model. To use this type of model, we need to have the component level data as we will need to give input to each of the components and take their output. This type of model is used to analyse the impact of individual components on the overall performance.

This is similar for the motor and generator models.

Figure 1.2, Dynamic Motor Subsystem

Changing the Model Type:

Open the Power Train Blockset Module for the desired type of Vehicle Model.
Click on the Vehicle Block.
Then Select the Electric Plant or Engine
Click on EV Motor/Generator/Engine based on the Vehicle Model selected.
Right Click on the Default Block available and then select Variant Manager.
Now click on Override Variant and select the Model desired.

Figure 2.1, Changing Model Type

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OBJECTIVE 2: How does the model calculate miles per gallon? Which factors are considered to model fuel flow?

Miles per Gallon Gasoline Equivalent:

Miles per gallon gasoline equivalent is a way of measuring the energy needed equivalent to a gallon of gasoline to travel a distance in miles.

Because electric vehicles do not consume gasoline, the EPA set an equivalent amount of energy in kilowatt-hours that is equal to one gallon of gasoline. According to the EPA, one gallon of gasoline is equal to 33.705 kilowatt-hours.

The mile per gallon gasoline equivalent is a US customary unit of electric car efficiency. Miles per gallon gasoline equivalent can be abbreviated as MPGe; for example, 1 mile per gallon gasoline equivalent can be written as 1 MPGe.

The Powertrain Blockset have built in model for this.

Figure 2.2, Performance Calculations Block

Figure 2.3, Performance Calculations Subsystem

Factors considered to Model Fuel Flow:

According to the Model, following 3 factors are involved in calculating the Fuel Economy rating

Vehicle Speed
Fuel Flow
Battery Power

Vehicle Speed is a critical criterion in evaluating the Fuel consumption/Fuel flow. It is integrated with respect to time to obtain Distance Travelled later which is converted to Km Units. Saturation Block is used to bound Upper & Lower limits to the obtained value

Total Battery Power required to Propel the vehicle is simulated along way, Battery Power is converted to “Kw” and Battery Rating is obtained in terms of “Kwh”. Several Gains Blocks with some constant Values are used to get the Mass flow rate of the fuel in (Kg/m^3).

The above value is fed back as input in the Fuel flow block, using these values along with the Gain Blocks Fuel Consumption in “Litres” is Calculated

By the Results obtained from Vehicle speed & Fuel Flow, the total amount of fuel to run Vehicle for 100 Km is obtained (L/100Km).

OBJECTIVE 3: Run the HEV Reference Application with WOT drive cycle. Change the grade and wind velocity in the environment block. Comment on the results

HEV Reference Application:

The HEV Reference Application is extracted from MathWorks Documentation.

Figure 3.1, HEV Reference Application Model

Drive Cycle Source block: Generates a standard or user-specified drive cycle velocity versus time profile. In this Simulation we are evaluating for WOT.

Environment subsystem: Creates environment variables, including road grade, wind velocity, and atmospheric temperature and pressure.

Longitudinal Driver subsystem: Uses the Longitudinal Driver or Open Loop variant to generate normalized acceleration and braking commands.

Longitudinal Driver variant implements a driver model that uses vehicle target and reference velocities.

Open Loop variant allows you to configure the acceleration, deceleration, gear, and clutch commands with constant or signal-based inputs.

Controllers subsystem: Implements a powertrain control module (PCM) containing an input power-split hybrid control module (HCM) and an engine control module (ECM).

Passenger Car subsystem: Implements a hybrid passenger car that contains drivetrain, electric plant, and engine subsystems.

Visualization subsystem: Displays vehicle-level performance, battery state of charge (SOC), fuel economy, and emission results that are useful for powertrain matching and component selection analysis.

Simulation for WOT_1:

Figure 3.2, Drive Cycle for WOT

Grade Angle = 0 Degrees

Wind Velocity = 0 m/s

Total Simulation Time =100s

Nominal Speed = 40m/s (WOT Max Speed=144Kmph=90Mph)

Time @ Deceleration = 40s

Figure 3.3, HEV Output for WOT without changes in environmental conditions

Trace Velocity: A Shift/Delta exists between Actual & Target WOT condition. This is due to the Limitation on the Maximum Power availability from Energy Sources @ that instant.

Max Velocity is attained at t=21.6s
Deceleration Time to 0Mph = 4.96s

Speed (RPM): Displays the Speed of the Engine, Motor & Generator throughout the Simulation. This can be used to determine the Peak Speed and to corelate between the Engine and Generator RPM.

Torque (Nm): A useful Torque Characteristics Curve. To achieve the Top Speed (WOT),

Max Engine Torque = 173Nm
Peak Motor Torque = 307Nm (Instantaneous during Start)

Battery Current (A):

Max Current Drawn from Battery to achieve WOT = 514A
Current Drawn after attaining Max Speed = 154A
Current during Deceleration = -246A (Indicates Charging)

Battery SOC (%):

The SOC of Battery Decreased from initial 80% to 68.3% Rapidly in Linear Fashion until Vehicle reaches Max Speed.

The rate of SOC reduction reduced once the Vehicle attained the constant speed and SOC depleted slowly.

During Deceleration, Battery SOC has increased to 70% which constitutes Regenerative Braking.

US Fuel Economy (MPG): Indicated Maximum Distance (Miles), Vehicle can run per Gallon of Fuel @ that Speed.

@ 90MPH = 11.38MPG

Simulation for WOT_2:

Grade Angle = 10 Degrees

Wind Velocity = 10 m/s

Total Simulation Time =100s

Nominal Speed = 40m/s (WOT Max Speed=144Kmph=90Mph)

Time @ Deceleration = 40s

Figure 3.4, Environment Subsystem with changes in Wind Velocity and Grade.

Figure 3.5, HEV output for WOT after Environmental changes.

Comparing the results:

	Simulation_1	Simulation_2
Grade (Deg)	0	10
Wind Velocity (m/s)	0	10
Maximum Speed (Mph)	90	60.2
Deceleration Time (s)	4.96	2.94
Max Engine Torque (Nm)	173	173
Peak Motor Torque (Nm)	307	307
Max Battery Current Drawn (A)	514	525
Battery SOC	80% to 70%	80% to 64.6%
Fuel Economy (MPG)	11.38	4.82

Conclusion:

There exists a difference between actual Velocity Curve and the Input Curve due to the limitation on maximum power available from Propulsion/Energy sources.
Limiting factors involves Current or the Battery Module.
The Maximum Speed achieved in Simulation_2 is lesser compared to that of Simulation_1 because of the presence of Grade Angle and Opposing Wind Force.
It can be observed from the Plots that with the increase in Grade Angle,
- WOT response Time increase
- Velocity Decreases.
The Battery SOC also decreases considerably with the increase in the Traction Forces.
Fuel Economy falls to greater extent with the increase in the Demanding Traction Power.

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OBJECTIVE 4: Keeping all other parameters same, compare the simulated results of hybrid and pure electric powertrains.

HEV

Figure 4.1, HEV powertrain configuration

Figure 4.1, EV powertrain configuration

Simulation for WOT_3:

Grade Angle = 10 Degrees

Wind Velocity = 10 m/s

Total Simulation Time =100s

Nominal Speed = 40m/s (WOT Max Speed=144Kmph=90Mph)

Time @ Deceleration = 40s

Result Comparison

	HEV	EV
Grade (Deg)	10	10
Wind Velocity (m/s)	10	10
Maximum Speed (Mph)	60.2	50.96
Deceleration Time (s)	2.94	4.134
Max Engine Torque (Nm)	173	---
Peak Motor Torque (Nm)	307	280
Max Battery Current Drawn (A)	525	226.6
Battery SOC	80% to 64.6%	80% to 76.56%
Fuel Economy (MPG)	4.82	15.75

Conclusion:

The Pure EV drive achieves less Top Speed Compared with HEV.
Motor used in EV must be of more Capacity than the one used in HEV.
EV derives all power from its Motor alone and hence Torque developed by EV Motor is greater. Whereas, in HEV, Combined Torque from Motor and Engine propels the system.
The conventional HEV uses Lead Acid Battery whereas, EV uses Lithium-Ion Battery which is more Potential.
Instantaneous Torque at the start is more in EV compared with HEV or conventional vehicles.
Under similar environmental conditions, maximum battery current draw by EV is lower compared to that of HEV. Thus, Fuel economy is efficient in EV than HEV.

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REFERENCES:

WOT Condition Part-2

Ship work like this
in your own course.

Talk to a career counsellor

Ship work like thisin your own course.

Talk to a career counsellor

Ship work like this
in your own course.