final thesis - chalamy.tripod.comchalamy.tripod.com/finalthesis.pdf · Title: final thesis Author: sab2980 Created Date: 2/9/2001 6:29:00 PM

SIMULATION OF A SERIES POWER TRAIN

IN THE DEVELOPMENT OF A HYBRID ELECTRIC VEHICLE

(FOR INDIAN ROAD CONDITIONS)

A project report submitted to the

FACULTY OF ENGINEERING

in partial fulfillment of the requirements for the award of the Degree of

BACHELOR OF ENGINEERING

in MECHANICAL ENGINEERING

By

ARUN KUMAR C ARUN R

ARUNACHALAM N

Guided by Mrs. LATHA NAGENDRAN

Lecturer Department of Mechanical Engineering

DEPARTMENT OF MECHANICAL ENGINEERING

COLLEGE OF ENGINEERING, GUINDY

ANNA UNIVERSITY

MADRAS – 600 025.

MAY 2000

Simulation of a Series HEV - Arun Kumar C., Arun R., Arunachalam N.

Page 2 of 93

Bonafide Certificate

Certified that this project titled " SIMULATION OF A SERIES POWER

TRAIN IN THE DEVELOPMENT OF A HYBRID ELECTRIC VEHICLE

(FOR INDIAN ROAD CONDITIONS) " is a bonafide work of

ARUN KUMAR C., ARUN R. & ARUNACHALAM N., students of the eighth

semester, full time BACHELORS OF MECHANICAL ENGINEERING, AT COLLEGE OF

ENGINEERING, GUINDY, ANNA UNIVERSITY, MADRAS. This project work was

carried out in the academic year 1999-2000 under my supervision. Certified

further, that to the best of my knowledge, the work reported herein, does not form

part of any other thesis or dissertation on the basis of which a degree or award was

conferred on an earlier occasion on this or any other candidate.

DR. J. JEYACHANDRAN MRS. LATHA NAGENDRAN

Head of Department Lecturer Mechanical Engineering Mechanical Engineering College of Engineering, Guindy, College of Engineering, Guindy, Anna University Anna University Chennai - 600025. Chennai - 600025.


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Preface

We acknowledge the engineering excellence imparted to us through the entire

course of our BACHELOR OF ENGINEERING BY COLLEGE OF ENGINEERING, GUINDY,

ANNA UNIVERSITY, CHENNAI, which has undoubtedly made this project realistic in

its conceptualization and design.

We have great pleasure in expressing our gratitude to our guide, MRS. LATHA

NAGENDRAN, LECTURER IN THE DESIGN DIVISION, for guiding us and encouraging

us throughout the project work.

We thank the HEAD OF THE DEPARTMENT OF MECHANICAL ENGINEERING ,

for providing us the opportunity to do this project.

We are thankful to DR. TR JAGADEESAN, FORMER CHAIR PROFESSOR, who

started us on this wonderful project, and giving us all the support material. We

thank the SAE for supporting us with material, to increase our confide nce in our

designs.

We are also grateful to all the STAFF MEMBERS, especially MR.

NAGARAJAN, for their invaluable encouragement, help and suggestions, in making

this project successful.


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CONTENTS

BONAFIDE CERTIFICATE..............................................................................................................................2

PREFACE.................................................................................................................................................................3

CONTENTS .............................................................................................................................................................4

SUMMARY ..............................................................................................................................................................7

ABSTRACT .............................................................................................................................................................8

FREQUENTLY ASKED QUESTIONS ......................................................................................................... 10

INTRODUCTION................................................................................................................................................ 13

POLLUTION OF CONVENTIONAL VEHICLES..................................................................................................... 14 FULLY ELECTRIC VEHICLE – IS IT A DEFINITE SOL UTION IN THE NEAR FUTURE?..................................... 16 WHY HYBRID? ................................................................................................................................................... 17

TYPES OF DRIVETRAINS .............................................................................................................................. 22

SERIES DRIVETRAIN.......................................................................................................................................... 22 PARALLEL DRIVETRAIN.................................................................................................................................... 23

JUSTIFICATION FOR A SERIES HYBRID CONFIGURATION ...................................................... 24

SERIES CONCEPT: ............................................................................................................................................... 24 ADVANTAGES OF A SERIES CONFIGURATION:................................................................................................ 24 DRAWBACKS OF A SERIES CONFIGURATION: ................................................................................................ 25

TOOLS USED ....................................................................................................................................................... 26

MATLAB........................................................................................................................................................... 27 SIMULINK ........................................................................................................................................................ 27

AIM AND SCOPE OF THIS PROJECT ....................................................................................................... 28

FUTURE PARAMETRIC ANALYSIS ..................................................................................................................... 29

DATA FLOW IN BLOCK D IAGRAMS ....................................................................................................... 30

DATA COLLECTION ........................................................................................................................................ 31

DRIVING CYCLE................................................................................................................................................. 31 MARUTI ZEN PARAMETERS ............................................................................................................................ 32 MOTOR PARAMETERS ....................................................................................................................................... 32 FUEL CONVERTER (INTERNAL COMBUSTION ENGINE)................................................................................ 33 BATTERY DATA ................................................................................................................................................. 34

COMPONENTS IN MATLAB / SIMULINK............................................................................................... 35

STEPS INVOLVED IN BUILDING SIMULINK BLOCK DIAGRAMS ............................................ 36

TOP LEVEL BLOCK DIAGRAM OF THE SIMULATION SYSTEM ....................................................................... 37


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VEHICLE CONTROL BLOCK DIAGR AM ........................................................................................................... 38 DATA OUTPUT BLOCK D IAGRAM.................................................................................................................... 39

DRIVE CYCLE..................................................................................................................................................... 40

BLOCK D IAGRAM OF THE DRIVING CYCLE .................................................................................................... 40

VEHICLE............................................................................................................................................................... 41

BLOCK D IAGRAM OF THE VEHICLE M ODULE................................................................................................ 44

WHEEL AND AXLE........................................................................................................................................... 45

BLOCK D IAGRAM OF THE WHEEL AND AXLE ............................................................................................... 48

FINAL DRIVE ...................................................................................................................................................... 49

BLOCK D IAGRAM OF THE F INAL DRIVE ......................................................................................................... 52

MOTOR CONTROLLER ..................................................................................................................................53

BLOCK D IAGRAM OF THE M OTOR CONTROLLER.......................................................................................... 58

POWER BUS ......................................................................................................................................................... 59

BLOCK D IAGRAM OF THE POWER BUS ........................................................................................................... 62

GENERATOR CONTROLLER ...................................................................................................................... 63

BLOCK D IAGRAM OF THE GENERATOR C ONTROLLER ................................................................................. 63

ENERGY STORAGE SYSTEM (BATTERIES)......................................................................................... 64

BLOCK D IAGRAM OF THE ENERGY STORAGE SYSTEM ................................................................................ 69

SERIES HYBRID THERMO STAT CONTROL STRATEG Y............................................................... 70

BLOCK D IAGRAM OF THE SERIES HYBRID T HERMOSTAT CONTROL STRATEGY ..................................... 72

FUEL CONVERTER .......................................................................................................................................... 73

BLOCK D IAGRAM OF THE FUEL CONVERTER (IC ENGINE) ......................................................................... 79

RESULTS ............................................................................................................................................................... 80

SENSITIVITY ANALYSIS ............................................................................................................................... 83

DEFAULT VALUES OF OUTPUT VARIABLES ...................................................................................................84 NUMBER OF BATTERIES .................................................................................................................................... 85 MOTOR POWER .................................................................................................................................................. 86 IC ENGINE POWER ............................................................................................................................................ 86 UPPER AND LOWER SOC LIMITS (STRATEGY) .............................................................................................. 87 VEHICLE MASS .................................................................................................................................................. 89 DRIVING CYCLE................................................................................................................................................. 89 INF ERENCE.......................................................................................................................................................... 90

HOW TO RUN THE SIMULATION ............................................................................................................. 91

REFERENCES ...................................................................................................................................................... 93

JOURNAL ARTICLES........................................................................................................................................... 93 SIMULINK COMPONENT MODULES ............................................................................................................. 93 WEB-SITES ......................................................................................................................................................... 93


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SIMULATION OF A SERIES POWER TRAIN

IN THE DEVELOPMENT OF A

HYBRID ELECTRICAL VEHICLE

(FOR INDIAN ROAD CONDITIONS)


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Summary

Name of the Students : Arun Kumar C. (960095) Arun R. (960096) Arunachalam N. (960097) Degree : Bachelor of Engineering Branch : Mechanical Engineering Date of Submission : May 2000 Title of Project Work : SIMULATION OF A SERIES POWER

TRAIN IN THE DEVELOPMENT OF A HYBRID ELECTRIC VEHICLE (FOR INDIAN ROAD CONDITIONS)

Name and designation of

Supervisor : Mrs. Latha Nagendran Lecturer Dept. of Mechanical Engineering College of Engineering, Guindy, Anna University, Chennai-600025.

Date : 22nd May, 2000. Signatures : Arun Kumar C. Arun R. Arunachalam N.


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Abstract

As we step into the third millennium, we see tremendous advancement in the

field of Automotive Engineering . The world economy runs on the Transport

sector. At the same time, this very boon has turned into a bane, as a major cause of

pollution, global warming & depleting fossil fuels. As Mechanical engineers, it is

our duty to develop new technology for the efficient use of renewable and non-

renewable energy sources for Automobiles. A Hybrid Electric Vehicle is one such

technology.

A simulation is the first step in the evaluation of a system design. In our

project, we evaluate the performance of a Series Hybrid Electric Vehicle on a

computer, optimized for Indian Road conditions, using a standard small car, such

as the Maruti ZEN. The road conditions, vehicle parameters and performance

limits are enforced, to determine the efficacy of the system. The modeling of the

vehicle is done using MATLAB / SIMULINK, which is a vital tool for all

engineering simulations.

The energy used, and the performance characteristics of the various

components are obtained. A sensitivity analysis is carried out for a few vital

components. Our juniors would be using the simulation results to fabricate a

prototype. This project has been envisaged as a possible solution to India's

problems arising due to pollution and dwindling fossil fuels.


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Abstract In Tamil


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FREQUENTLY ASKED QUESTIONS


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Frequently Asked Questions

1. What is a Hybrid Electric Vehicle?

A Hybrid Electric Vehicle is one that uses 2 forms of energy (say Fossil fuel &

electric energy) to propel the vehicle. An Internal Combustion Engine uses

Gasoline & converts it into electrical energy. A Battery supplies electrical energy

to the Electrical Prime Mover.

2. What is the Series Hybrid Configuration?

In a Series Hybrid, the Wheels are driven only by the Electric Motor, whereas the

IC Engine runs a generator which charges the battery. There is physical link

between the ICE and wheels. This is useful for low power applications.

3. Why Hybrid Electric Vehicles (HEV)?

The future demands pollution-free transportation systems, such as Pure Electric-

Vehicles (EV). But due to the lack of advanced storage batteries, the best

intermediate alternative in the development of a Pure EV is the Hybrid Electric

Vehicle (HEV).

4. What is the Purpose of this Simulation / Aim of the project?

The Aim of the Project is to demonstrate the effectiveness of a Series Hybrid

Electric Vehicle (HEV)- City car - in Indian Road conditions, by displaying a

decrease in fuel consumption, reducing pollution simultaneously. The simulation

is done by Mathematically modeling a dynamic system representative of a series

HEV.

5. What is the necessity for the Indian Driving Cycle?

The Prime mover rotational characteristics heavily depend on the road-conditions.

The amount of energy used depends on how much / how fast the prime mover is

to rotate. The Indian - Road Urban driving cycle typically represents a low-speed,

low-power, short range cycle, for which the Series HEV is best suited.


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6. What is MATLAB / SIMULINK?

MATLAB is the world's most widely used Engineering software, which is used to

perform mathematical calculations with ease. Every logical system in the world

can be mathematically modeled and SIMULINK is the Modeling software

associated with MATLAB. SIMULINK is extensively used by Computer,

Electrical & Mech Engineering students to simulate Dynamic Systems.

7. Are the components used in the vehicle readily available?

The various components to be used in the HEV are taken from commercially

available products. Some components used are the chassis of the Maruti ZEN, IC

Engine from the Maruti 800, Electric Motors from Crompton Greaves etc.

8. What are the results of this Project? What have we proved?

We have mainly proved by mathematical modeling that a decrease in fuel

consumption is achieved when using a Series HEV design for Indian Road

conditions, compared to existing cars plying on Indian roads. It also brings along

with it, a decrease in pollution levels.

9. What can be done using the Project Simulation Results?

The results of this Project can be used in the development of a Series HEV:

ü Design and selection of components / sizes

ü Further fine tuning of selected components / sensitivity ana lysis

ü Estimation of fuel consumption based on newer designs.


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INTRODUCTION


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INTRODUCTION

At the turn of new millennium, we are facing major problems in the field of

Automotive Industry. They are the,

Ø Depletion of fossil fuels – we have consumed the fuels formed in million years

in just a century.

Ø Pollution of conventional vehicles.

Ø Global warming and other effects.

The alternate options for this industry ranges from fully electric vehicle to hybrid

ones. Definitely the future vehicle is Fully Electric vehicle but there are inherent

problems with it. In this intermediate state the best possible transitional solution is

the hybrid vehicle.

Pollution of conventional vehicles

Burning 1 gallon of gasoline yields 22 lbs. of carbon dioxide , the major

greenhouse gas. Air pollution has been named the #1 health threat to the lungs. A

study comparing the rates of economic growth and the rates of growth of

vehicular pollution and industrial pollution shows that during 1975–1995, the

Indian economy grew by 2.5 times, but the industrial pollution load grew by 3.47

times and the vehicle pollution load by 7.5 times. Indeed, Indian cities are being

exposed to high levels of air pollution and people living in these cities are paying

a price for the deterioration in air quality. The World Bank has estimated that

Indians are spending Rs 4550 crores every year on treatment of diseases caused by

ambient air pollution.

Perfect" Combustion:

FUEL (hydrocarbons) + AIR (oxygen and nitrogen) ==>> CARBON DIOXIDE + water + unaffected nitrogen

Typical Engine Combustion:

FUEL + AIR ==>> UNBURNED HYDROCARBONS + NITROGEN OXIDES +

CARBON MONOXIDE + CARBON DIOXIDE + water


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Thus we see the various pollutants from the conventional vehicle are

Hydrocarbons , Nitrogen oxides (NOx) , Carbon Monoxide , Carbon dioxide,

Evaporative Emissions and Sulphur oxides (Sox).

The Government of India has been seeking to reduce gaseous emissions from

automobiles by prescribing limits and progressively making them stringent. For

instance, the limit of carbon monoxide emissions in two-wheelers is down by

78%, compared to the 1992 level, with another 33% reduction planned by the year

2000. In diesel vehicles the reduction is 20% with another 59% reduction planned

by the year 2000. Whether this is possible by conventional methods and

technology is a million-dollar question.

Moreover this incomplete combustion leads to wastage of fuel. We are all aware

of the rapid increase in Oil Import bill, which is the major reason for the trade

deficit in India. By saving fuel, India can save several thousand crores in Oil

Import every fiscal year. It is even predicted that the fossil reserves will hold only

for another half a century at most. It is appalling to say,

“Fossil reserves which took millions of years to form has been consumed in just a

century by humans.”

It is high time people think of an alternate technology to support their growing

needs.

Emissions of PM (Particulate Matter) by source in Delhi, 1994 (tonnes/year)

Vehicles 9800

Buses 4800

Trucks 900

Diesel cars 600

Industry 3500 to 10200

Domestic 1300

Dung-cake 700

Kerosene 200

Fuelwood 300


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This pollution is the major cause for various respiratory health effects, like,

Pre-mature deaths, Asthma attacks , Respiratory symptoms and Chronic-

bronchitis.

Fully Electric vehicle – is it a definite solution in the near future?

There is no question about the fact that “fully electric vehicle” is the

VEHICLE OF THE FUTURE. But the technology to bring about this vehicle in

action is still in its developing stage, even there are few thousands plying on the

city roads. We are in a transitional phase and hybrid vehicle is a feasible solution

in this phase. Unlike an EV, an HEV utilizes the intermittent operation of a small

engine to assist a typically battery-powered electric propulsion system.

An Electric Vehicle (EV) drive train includes components (as shown in the figure)

like batteries and a motor. It uses only electric motive power, and it can use the

motor as a generator for capturing braking energy to be stored in the battery. The

batteries begin at full charge.


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The advantages of fully electric vehicle are numerous, but the significant one is

that it does not utilize fossil fuels and hence no emissions leading to a greener

world.

Given the technology we posses, there are problems with electric vehicle. They

are,

q Low range (Driving distance has to be short).

q Low power to weight ratio.

q Frequent recharging necessary.

q Expensive components such as high capacity battery for which battery technology

is just gearing up.

q EVs are still relatively expensive.

q When completely drained of power, the average EV takes six hours to fully

recharge using a 220-volt source.

q They say, when EVs in the United States exceed 1 million, new electric power

plants may be needed

q Driving distance, acceleration, and recharging times are all key to increased

acceptance of EVs.

q Infrastructure limitations (e.g., lack of public charging stations, repair/replacement

facilities, battery-recycling centers).

q As EVs become popular and common, their sale may negatively affect the

traditional automotive industry.

Hence it is clear from the above facts that “fully electric vehicle” is no immediate

solution to our growing transportation problem. There are even other solutions

like solar vehicle, CNG etc. but they are not immediate and long-term solution.

Hence there is a need for another immediate solution… which is the Hybrid

electric vehicle.

Why Hybrid?

It uses both an Internal Combustion Engine and an Electric motor to propel the

vehicle in a synergetic effect. The engine and the motor are small in size, and thus

consume less energy. The IC Engine is run only at the optimum efficiency range.


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The electric motor is used during city driving and slow traffic. The IC Engine is

used to recharge the batteries during the actual running. Regenerative braking is

possible, to recover valuable energy.

Main sub-systems of a Hybrid power Train:

q A small size IC Engine

q An electric prime mover (DC Series motor / AC Induction Motor)

q A transmission system to the wheels

q A device for coupling the IC Engine and motor.

q A control system for the hybrid configuration (The electronic hardware)

q A set of high-capacity batteries

Use of IC engine in Hybrid electric Vehicle:

q The IC Engine is used only in its peak efficiency range.

q The IC Engine is used only when the torque requirements exceed the electric

motor’s capacity (such as overtaking / gradients).

q The IC Engine is used to recharge the batteries by a separate generator.

q The IC Engine is shut off when driving in “Electric-only” mode, such as in low

speeds inside the city.

HEVs have several advantages over traditional internal combustion engine (ICE)

vehicles. Some of these follow:

ü The vehicle uses up half the amount of fuel, due to its small size.

ü The emission levels are reduced by half, due to small engine sizes, and peak-

efficiency usage.

ü Smaller batteries can be used, due to recharging facilities.

ü Performance can equal a normal car, due to the synergetic effect of the 2 prime

movers: the IC Engine and the electric motor.


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Some design and operation options appear to be possible with the HEVs now

being developed

ü Regenerative braking capability, which helps minimize the energy lost when

driving.

ü Engine is sized to average load, not peak load, which reduces the weight of the

engine.

ü Fuel efficiency is greatly increased, while emissions are greatly decreased.

ü HEVs can be operated using alternative fuels, therefore they need not be

dependent on fossil fuels.

The auto manufacturers' goal is to achieve these benefits with no appreciable loss

in vehicle performance, range, and safety. With two drive trains (ICE running on

gasoline or alternative fuels and a battery-driven electric drive train) the HEV is

able to operate approximately two times more efficiently than traditional ICE

vehicles.

Initially, HEVs are not expected to compete directly with standard vehicles on

performance alone (e.g., acceleration and range), but they are expected to offer

benefits that a standard vehicle does not offer.

ü reduce local/regional pollution by increased vehicle mileage and reducing

emissions by running the engine at its peak efficiency


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ü The HEV has another major advantage: even with high market penetration of

HEVs, few or no infrastructure changes will be required. In addition, consumers

may be more likely to accept future HEVs since their operational differences are

more likely to be "transparent" to the vehicle operator than those of an EV.

Hybrid Electric Vehicles (HEVs) are almost as clean as EVs and have vehicle

performance comparable to that of today's standard internal combustion engine

vehicles. More important, such performance appears to be available in the mid -

term future (e.g., 2001), and therefore represents a practical, technically -

achievable alternative approach. Prudence suggests we develop both EVs and

HEVs in parallel, because many of the technical advancements can be shared and

because either or both will be needed to achieve efficiency and cle an air goals.

A practical example of an available HEV Prius is one HEV which is available in the market. The Prius drivetrain is a

model of the Toyota Hybrid System. It contains a power split device also called a

continuously variable transmission (CVT) which consists of a planetary gear

system. The generator is connected to the sun gear, the motor is connected to the

ring gear and the engine is connected to the planet carrier. The motor and

generator provide or take power from the power-split device depending on their

mode of operation. There is no gear shifting in the Prius. Reverse is a motor only

mode and the generator is used in motor mode to crank the engine. The torque on

the generator controls its speed and the speed of the engine. Note there is no

clutch. The mileage of this HEV is 66 miles per gallon (28 km per liter)


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Another HEV in the market is Honda Insight, which has a mileage of 80miles

per gallon (34 km per liter). The Insight always uses the gas engine as its primary

power source. Insight’s electric motor is instead used to boost the engine’s power

during hard acceleration. Insight’s battery is just half the size of the Prius battery.


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Types of Drivetrains

There are two types of drivetrains depending on the position of individual

components. They are

1. Series Drivetrain

2. Parallel Drivetrain

Series Drivetrain

The series vehicle components include a fuel converter, a generator, batteries, and

a motor. The fuel converter does not drive the vehicle shaft directly. Instead, it

converts mechanical energy directly into electrical energy via the generator. All

torque used to move the vehicle comes from the motor. The default gearbox is a

one speed. The hybrid accessories are a constant electrical power load.


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Parallel Drivetrain

The parallel vehicle components include an engine, batteries, and a motor. It is

named parallel because both the motor and the engine can apply torque to move

the vehicle. The motor can act in reverse as a generator for braking and to charge

the batteries. The default gearbox is a 5 speed. The hybrid accessories are a

constant electrical power load.


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Justification for a Series Hybrid Configuration

In the evaluation of a suitable hybrid configuration, the target usage is

considered. For city driving in Indian Road conditions, with accommodation for

Highway driving, the Series Hybrid Configuration proves more fruitful and

efficacious.

Series concept:

A series hybrid configuration is shown in figure. As explained before, only the

Electric motor drives the wheels mechanically, while the IC Engine is used to

produce electricity through an alternator. Engine operation begins when the

battery pack is sufficiently depleted and ceases when a predetermined battery

State of Charge is attained. Typically, the engine is run at Constant Speed &

near Constant Load so that the engine can be tuned for maximum efficiency &

low emission levels. The battery pack therefore acts as a buffer between the

alternator and motor, supplying electricity on demand and storing exc ess energy

when not needed.

Advantages of a series configuration:

Requirement of Indian Urban Driving

Problem with Conventional Car

Advantage with a Series

Frequent Start - stops Engine Idling - inefficient

operation

Engine runs only at peak

efficiency irrespective of

vehicle speed.

Quick acceleration /

deceleration

Engine is most inefficient

during acceleration

No engine acceleration

Short trips Engine runs all the time Short trips can be handled

by the battery alone,

without the engine being

started.


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The arguments against a Parallel Configuration are as follows:

Parameter in Consideration

Parallel Configuration Series Configuration

Power delivered at the

wheels

More in case of parallel High power is required

only when accelerating on

highways. This can be

supported by a medium

power motor, without IC

Engine assist.

Pollution Engine accelerates and

decelerates based on

vehicle speed

Engine runs at constant

speed, giving better

efficiency.

Coupling Expensive coupling is

necessary between the

ICE and the motor - adds

to the weight and cost.

No expensive coupling is

necessary.

Control System A complicated control

system is necessary,

which increases cost.

A very simple thermostat

control system is used.

Cost Cost is more due to

coupling + control system

Cost is less

Drawbacks of a Series Configuration:

The series configuration does have some drawbacks, which can be neglected if the

system is designed properly.

1. The efficiency of each component is very important. The overall efficiency of the

entire system = ICE eff * Gen eff * Battery eff * Motor eff * transmission eff.

Thus, individual component efficiencies easily affect the overall efficiency.

2. Any individual component failure will lead to overall vehicle failure, as they are

connected in series. (In a parallel configuration, the ICE / motor can run even if

the other is down.)

These drawbacks are easily covered by efficient & careful design and

implementation.


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TOOLS USED

(MATLAB & SIMULINK)


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Tools Used

MATLAB

The name MATLAB stands for matrix laboratory. It is a high-performance

language for technical computing. It integrates computation, visualization, and

programming in an easy-to-use environment where problems and solutions are

expressed in familiar mathematical notation. Typical uses include:

• Math and computation

• Algorithm development

• Modeling, simulation, and prototyping

• Data analysis, exploration, and visualization

• Scientific and engineering graphics

• Application development, including Graphical User Interface building

MATLAB features a family of application-specific solutions called toolboxes.

Toolboxes are comprehensive collections of MATLAB functions (M-files) that

extend the MATLAB environment to solve particular classes of problems. Areas

in which toolboxes are ava ilable include signal processing, control systems, neural

networks, fuzzy logic, wavelets, simulation, and many others.

SIMULINK

SIMULINK, a companion program to MATLAB, is an interactive system for

simulating nonlinear dynamic systems. It is a graphical mouse-driven program

that allows one to model a system by drawing a block diagram on the screen and

manipulating it dynamically. It can work with linear, nonlinear, continuous -time,

discrete-time, multivariable, and multirate systems. Blocksets are add-ins to

SIMULINK that provide additional libraries of blocks for specialized applications

like communications, signal processing, and power systems. Real-time Workshop

is a program that generate C code from block diagrams and to run it on a variety

of real-time systems.


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Aim and Scope of this Project


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Aim and Scope of this Project

This project is envisaged to provide an estimate of the efficacy of a series

hybrid configuration in a Maruti ZEN. The main aim of the simulation is to show

an improvement in the mileage (decrease in the fuel consumption) of the system,

for the same driving schedules.

The scope of the project is enlisted in the few points below:

• An estimate of fuel economy & relative improvement

• An estimate on the no. of batteries required.

• The rating of the Auxilary Power Unit (IC Engine + Generator)

• An estimate of the rating of the Traction motor

NOTE: Exhaust calculations can be carried out easily, if the exhaust emissions

map of the IC Engine and the Catalytic Converter data are available, but due to the

difficulty in obtaining those values, the scope is limited to fuel economy.

Future parametric analysis

The simulation blocks can be used to test for various modules of batteries,

other motor configurations and varying APU output. The same driving cycle could

be used to test the efficiency of the system.


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Data Flow in Block Diagrams

The SIMULINK block diagram used is hybrid of a backward-facing

vehicle simulation and a forward-facing simulation.

Backward-facing vehicle simulations answer the question “Assuming the

vehicle meets the required trace, how must each component perform?” Simulation

programs of this type generally do not include a model of (human) driver

behavior, and can predict maximum effort performance only through iteration.

Forward -facing vehicle simulations include a driver model that seeks to

modulate throttle and brake commands to follow the trace. The throttle signal is

converted into a torque, which is passed down the driveline and ultimately

converted to a force, which is divided by mass and integrated to compute speed.

Simulation programs of this type excel at maximum effort performance

calculations, but are often very slow in computing vehicle behavior over a 10+

minute -long trace.

The block diagram uses a hybrid backward/forward approach that is closely

related to the customary strictly backward-facing approach, where each

component provides as much torque (or force) as is required by the immediately

"downstream" component (i.e. closer to the wheels) to meet the specified trace. Its

approach is unique in the way it handles the component performance limits in its

backward-facing stream of calculations and in the addition of a simple forward-

facing stream of calculations. The two overriding assumptions that describe its

combination of the backward-facing and forward-facing approaches are:

Ø No drivetrain component will require more torque or power from its upstream

neighbor than it can use.

Ø A component is as efficient in the forward-facing calculations as it was computed

to be in the backward-facing calculations.


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Data Collection

To properly run the simulation, the correct data for the components used must

be mentioned. For the components used:

• some standard values were used

• specific values were used for some components

• Approximations taken are indicated where necessary.

Driving Cycle

An Indian Driving cycle is necessary for the simulation path to be followed,

and is the most VITAL data for the simulation. The Driving cycle is taken on 2

separate runs - one for CITY/URBAN driving, and the other for HIGHWAY

driving.

Typical Madras Driving cycle - 6262 seconds, covering a distance of 57 kms in

and around Madras City.

INDIAN DRIVING C YCLE - T IME (SEC) VS SPEED (MPH)

The values were taken at 5-sec intervals, and were smoothened by the MATLAB

spline function (which interpolates taking a cubic eqn).

0 1000 2000 3000 4000 5000 60000

5

10

15

20

25

30

35

40

45

50

Time in seconds

Speed (mph)


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% MATLAB code to smoothen the driving cycle

% ceg_cyc_mph : the input matrix

% cyc_mph : the output matrix

for i=0 : (ceg_cyc_mph(size(ceg_cyc_mph,1))),

cyc_mph(i+1,1)=i;

cyc_mph(i+1,2)=spline(ceg_cyc_mph(:,1), ceg_cyc_mph(:,2), i);

end

Maruti ZEN Parameters

Certain Maruti ZEN parameters such as wheelbase, white-body mass, center

of gravity, coefficient of drag, frontal area etc.. are required for the calculation of

the force needed to propel the vehicle according to the driving cycle. These

parameters were obtained by:

è Direct measurement

è from MARUTI ZEN technical specifications, provided by the manufacturer.

Motor Parameters

A traction motor is modeled and the lookup table is created for the simulation.

This is a 3-phase induction motor, which has the greatest efficiency for motors.

The standard 3-D efficiency map for a 3-phase induction motor (obtained from

NREL USA) is scaled down to the available motor capacity from Crompton

Greaves. This scaling down gives us the lookup table for the motor efficiency

map. SPEED - T ORQUE CHARACTERISTICS OF 3-PHASE INDUCTION M OTOR

0 100 200 300 400 500 600 700 800 9000

20

40

60

80

100

120

140

160

180

200

Speed (rad/s)

Torque (Nm)


Page 33 of 93

EFFICIENCY MAP OF THE 3-PHASE INDUCTION MOTOR

Fuel Converter (Internal Combustion Engine)

The Fuel Converter used is the 3-cylinder Maruti 800 Multi-Point Fuel

Injected Engine. Its capacity is 800 cc, producing 34.316 KW of power at 6000

rpm.

IC ENGINE SPEED -TORQUE CHARACTERISTICS

-200-100

0100

200

0

500

10000.2

0.4

0.6

0.8

1

Torque (Nm)Speed (rad/s)

Efficiency

100 200 300 400 500 600 70052

54

56

58

60

62

64

Engine Speed (rad/s)

Torque (Nm)


Page 34 of 93

IC ENGINE (MARUTI 800 MPFI) FUEL USAGE MAP

Battery Data

The battery used in our design is from Standard Furukawa (Exide Company).

They are sealed Lead Acid batteries, which are used in present day Maruti ZEN

cars. The data is modeled form Standard Furukawa Data, given to us.

LEAD ACID BATTERY OPEN CIRCUIT VOLTAGE CHARACTERISTICS

0

20

40

60

80 0

200

400

600

800

100

200

300

400

500

600

700

Engine Speed (rpm)Engine Torque (Nm)

Fuel Used (gram per KWh)

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 111.5

12

12.5

13

State of Charge (SoC)

Open Circuit Voltage (v)


Page 35 of 93

COMPONENTS IN MATLAB / SIMULINK


Page 36 of 93

Steps involved in building SIMULINK Block diagrams

In building the required block diagrams for the simulation, the model parameters

and data flow logic are kept in mind. The following procedure is followed while

building the simulation blocks.

1. The component variables are noted and the logic for the component design is

planned.

2. The required basic building blocks are taken from the SIMULINK 3 Model

Library.

3. The Model is created using sub-systems for each component and the details

for each component is placed in the hierarchy inside their respective sub-

systems.

4. The variables to and from the workspace are specified, so as to be accessible

from the MATLAB command windows later.

The following block diagrams are shown in the subsequent pages:

1. The top-layer of the Simulation System

2. The Vehicle Control Block

3. The Data Output Block


Page 37 of 93

Top level block diagram of the Simulation system


Page 38 of 93

Vehicle Control Block Diagram


Page 39 of 93

Data Output Block Diagram


Page 40 of 93

Drive Cycle

The driving cycle is used to input the speed-time graph into the simulation

block diagrams. The driving cycle used is the Indian Driving Cycle, a combination

of Urban & Highway schedules taken in Madras.

Block Diagram of the Driving Cycle

The initial conditions, which are initiated before the simulation, are given

in the m file INIT.CONDS.m.

The importanat parameters given are:

• Density of Ambient Air = 1.2 g / m3

• Ambient Temperature = 30 ' C

• Average Specific H eat Capacity Cp of Air = 1009 J/kg/K

1

req'd vehiclespeed (m/s)repeated cycle

speed vs. time

0.447

mph-->m/s

distancetravelled (m)

cyc_mph_r Goto <sdo><vc>

distance

Goto <sdo>1


Page 41 of 93

Vehicle

This block determines the tractive force required at the tire/road interface

using the required vehicle speed at the end of time step.

The inputs for this block is given the file : VEH_ZEN_CEG.m. The input

parameters are

1. Vehicle mass w/o propulsion system (fuel converter, drive train, motor, ESS,

generator)

2. Coefficient of aerodynamic drag

3. Frontal area

4. Vehicle’s first Rolling Resistance Coefficient

5. Fraction of vehicle weight on front axle when standing still

6. Height of vehicle center -of-gravity above the road

7. Wheel base

8. Cargo Mass

The output of this block is the tractive force and speed required of tire and

wheel. It is given to wheel and axle block.

The sum of the following forces is calculated and given to the Wheel and Axle

block.

1. force required to overcome rolling resistance

= mass x accl. due to gravity x vehicle’s first RRC

2. force required to ascend (neglected in our case)

= mass x accl. due to gravity x sin θ

3. force required to overcome aerodynamic drag

= air density x Co-eff. of drag x frontal area x V2 / 2

4. force required to accelerate

= mass x (current speed – prev speed) / dt


Page 42 of 93

T RACTIVE FORCE REQUIRED OF TIRE AND WHEEL

SPEED REQUIRED OF T IRE AND WHEEL

0 1000 2000 3000 4000 5000 6000 7000-4000

-3000

-2000

-1000

0

1000

2000

3000

4000

5000

6000

Time (seconds)

Force (N)

0 1000 2000 3000 4000 5000 60000

5

10

15

20

25

Time in secs

Speed in meters per sec


Page 43 of 93

The input parameters file (VEH_ZEN_CEG.m) is given below

% Data file: VEH_ZEN_CEG.m % Defines road load parameters for a Maruti ZEN car. % Created on: 23-April-2000 By Arun Kumar, Arun Rajagopalan, Arunachalam, CEG, Madras. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % FILE ID INFO %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% veh_description='Maruti ZEN small car'; disp(['Data loaded: VEH_ZEN_CEG - ',veh_description]) %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % PHYSICAL CONSTANTS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% veh_gravity=9.81; % m/s^2 veh_air_density=1.2; % kg/m^3 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % VEHICLE PARAMETERS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% veh_glider_mass=500; % (kg), vehicle mass w/o propulsion

system (fuel converter, drivetrain, motor, ESS, generator)

veh_CD=0.3; % (--), coefficient of aerodynamic drag veh_FA=1.5795; % (m^2), frontal area veh_1st_rrc=0.009; % for the eqn: rolling_drag=mass*gravity*(veh_1st_rrc) veh_front_wt_frac=0.6; % fraction of vehicle weight on front

axle when standing still veh_cg_height=0.5; % height of vehicle center-of-gravity

above the road veh_wheelbase=2.335; veh_cargo_mass=300;


Page 44 of 93

Block Diagram of the Vehicle Module


Page 45 of 93

Wheel and Axle

This block determines the required axle torque and speed given the tractive

force and speed required to meet the trace in the top blocks, and determines the

available tractive force and possible vehicle speed given the drive train-input

torque and rotational speed in the bottom blocks.

The inputs for this block is given the file : WH_ZEN_CEG.m. The input

parameters are

1. Force and Mass ranges over which data is defined

2. Loss parameters

3. Rolling radius

4. Rotational inertia of all wheels, tires, and axles

5. Fraction of braking done by driveline

6. Fraction of braking done by front friction brakes,

7. Wheel mass

The output of this block is torque and speed required from drive train into

axle. It is given to final drive.

The "wheel control" blocks apply the braking strategy and ensure that

accelerations beyond the capability of the tires are not requested. The effects of

inertia and losses are taken in to account.

T ORQUE REQUIRED FROM DRIVETRAIN INTO AXLE

0 1000 2000 3000 4000 5000 6000-500

0

500

1000

1500

Time in seconds

Torque in N-m


Page 46 of 93

SPEED REQUIRED FROM DRIVETRAIN INTO AXLE

The input parameters file (WH_ZEN_CEG.m) is given below

% Data file: WH_ZEN_CEG.m % Notes: % Defines tire, wheel, and axle assembly parameters for for a Maruti ZEN small car % Created on: 23-April-2000 by Arun Kumar, Arun Rajagopalan, Arunachalam, CEG, Madras. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % FILE ID INFO %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% wh_description='Wheel/axle assembly for Maruti Zen small car'; disp(['Data loaded: WH_ZEN_CEG - ',wh_description]) %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % FORCE AND MASS RANGES over which data is defined %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % vehicle test mass vector used in tandem with "wh_axle_loss_trq" to estimate % wheel and axle bearing and brake drag wh_axle_loss_mass=[0 2000]; % (kg) % (tractive force on the front tires)/(weight on front axle), used in tandem % with "wh_slip" to estimate tire slip at any time wh_slip_force_coeff=[0 0.3913 0.6715 0.8540 0.9616 1.0212]; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % LOSS parameters %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

0 1000 2000 3000 4000 5000 60000

10

20

30

40

50

60

70

80

90

Time in seconds

Speed in radians per sec


Page 47 of 93

% drag torque applied at the front (drive) axle, used with "wh_axle_loss_mass" wh_axle_loss_trq=[4 24]*.4; % (Nm) % slip=(omega * r)/v -1; used with "wh_slip_force_coeff" wh_slip=[0.0 0.025 0.050 0.075 0.10 0.125]; % (--) %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % OTHER DATA %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% wh_radius=0.26; % (m), rolling radius of 145 / 70-R-13 % rotational inertia of all wheels, tires, and axles wh_inertia=181/2.205*wh_radius^2/2; % (kg*m^2) % fraction of braking done by driveline, indexed by wh_fa_dl_brake_mph wh_fa_dl_brake_frac=[0 0 0.5 0.8 0.8]; % (--) % (--), fraction of braking done by front friction brakes, % indexed by wh_fa_fric_brake_mph wh_fa_fric_brake_frac=[0.8 0.8 0.4 0.1 0.1]; % (--) wh_fa_dl_brake_mph=[-1 0 10 60 1000]; % (mph) wh_fa_fric_brake_mph=wh_fa_dl_brake_mph; % (mph) wh_mass=20;


Page 48 of 93

Block Diagram of the Wheel and Axle


Page 49 of 93

Final Drive

The final drive is the modeling of the entire transmission system, taking into

consideration the gear ratio and the overall efficiency.

The transmission system consists of:

1. A 1-spd gear reduction system

2. A differential

3. A final drive ratio (if 2-stage reduction is necessary)

This whole system can be considered as 1 model in SIMULINK with an

overall gear ratio and an overall efficiency for Mathematical simplicity. We

assume the overall transmission efficiency of a lubricated system to be ~ 95%.

Torque loss is assumed to be constant. The gear ratio reduces the speed input

and increases torque. Inertia is measured and losses are applied at the input side of

the gear reduction.

Calculation of the Ove rall ratio

For optimum acceleration and speed ranges, the overall ratio must be designed

according to the acceptable torque source of the Motor, the maximum attainable

motor rpm and the maximum desired road speed.

The overall ratio is dynamically calculated during simulation as

fd_ratio=maximum of (motor speed/(max. road speed *1.1 / wh_radius) )

where:

• 10% wheel slip is accommodated.

• The wheel radius of the Maruti ZEN is used.

Inputs

The inputs to the Final drive processing blocks are:

1. Torque & Speed requested by the Wheels

This defines the speed requested by the vehicle based o the force and road

speed required.


Page 50 of 93

2. Torque & Speed available from the Motor

This is based on what the motor can provide to the Transmission.

Outputs

The outputs available from the Block are:

1. Speed and torque requests to the Motor

This requests the motor to provide additional torque to overcome the losses in

the transmission.

2. Speed and torque actually available to the wheels

This is the output of the Block, which contains what actually comes out of the

Transmission system.

TORQUE ACHIEVED FROM THE TRANSMISSION SYSTEM

0 1000 2000 3000 4000 5000 6000-600

-400

-200

0

200

400

600

800

Time (s)

Torque (Nm)


Page 51 of 93

SPEED ACHIEVED FROM THE T RANSMISSION SYSTEM

The input parameters file (TX_1SPD_CEG.M) is given below ,

% Data file: TX_1SPD_CEG.m % This file defines a 1-speed gearbox by defining a gear ratio & mech & inertia losses. % Created on: 23-April-2000 By:Arun Kumar, Arun Rajagopalan, Arunachalam, CEG, Madras. disp(['Data loaded: TX_1SPD_CEG - a 1-speed Transmission system (Gear Box + Final Drive)']) % gear ratio to allow 87 (140 kmph) mph given the max. motor speed and 10% wheel slip fd_ratio=max(mc_map_spd*mc_spd_scale)/(87*0.447*1.1/wh_radius); fd_eff=0.95; % Overall Transmission Efficiency (Gearbox +

final drive) fd_loss=0; % (Nm), constant torque loss in final drive,

measured at input fd_inertia=0; % (kg*m^2), as yet unknown, rotational

inertia of final drive, measured at input fd_mass=100; % (kg), mass of the transmission

0 1000 2000 3000 4000 5000 60000

10

20

30

40

50

60

70

80

90

Time (s)

Speed (rad/s)


Page 52 of 93

Block Diagram of the Final Drive


Page 53 of 93

Motor Controller

This module takes the torque and speed required at the rotor end as the

input parameter and calculates the input power of the motor. This output is given

to the power bus module, which supplies the needed power from the energy

storage system. The rotor is directly coupled with the final drive. The torque and

speed available at the rotor is fed into the final drive module.

The input parameters for this module are entered in the file “MC_CEG.m”.

The various parameters required are,

§ Speed range of the motor (in radians/sec)

§ Torque range of the motor (in N-m)

§ Efficiency map of the motor

§ Limits such as maximum torque, Maximum Current and Minimum volts

§ Rotor's rotational inertia

§ Mass of the motor

We have collected details of 45-60KW rated motor deta ils of Kriloskar and

Cormpton Creaves. We have selected these 3-phase induction motors, as these are

best motors available in India. The top layer of motor controller module is shown

in the next page.

Process : The output torque at the rotor is calcula ted taking into the inertia effects of the

rotor and losses. The power required by the motor for this torque is obtained from

the index-map of the rotor, which is provided as input in the MC_CEG.m file.

As in previous modules, we utilize the benefit of both backward and

forward integration. In forward integration, the input power at the motor is taken

as the input parameter and the required torque and speed outputs are calculated.

The calculated torque is enforced within the limits of the motor.


Page 54 of 93

Outputs:

ROTOR SPEED ACHIEVED.

TORQUE AVAILABLE AT THE ROTOR

0 1000 2000 3000 4000 5000 60000

10

20

30

40

50

60

70

80Achieved Motor speed

Time in secs


0 1000 2000 3000 4000 5000 6000-600

-400

-200

0

200

400

600

800Torque achieved at the rotor end

Time in secs

Torque in N-m


Page 55 of 93

POWER AVAILABLE AT THE ROTOR

The input parameters file (Mc_ceg.m) is given below,

% 45 KW Crompton Greaves 4-pole 50 Hz 3-phase AC Induction Motor % Created on: 23-April-2000 By: Arun Kumar, Arun Rajagopalan, Arunachalam, CEG, Madras. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % FILE ID INFO %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% mc_description='45 KW Crompton Greaves 4-pole 50 Hz 3-phase AC Induction Motor/controller'; disp(['Data loaded: MC_CEG - ',mc_description]); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % SPEED & TORQUE RANGES over which data is defined %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % (rad/s), speed range of the motor mc_map_spd=[0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000 6500 7000 7500 8000]*(2*pi/60); % Conversion from RPM to rad/s % (N*m), torque range of the motor mc_map_trq=[0 25 50 75 100 125 150 175 200]; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % EFFICIENCY AND INPUT POWER MAPS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % (--), efficiency map indexed vertically by mc_map_spd and % horizontally by mc_map_trq

0 1000 2000 3000 4000 5000 6000-2

-1.5

-1

-0.5

0

0.5

1

1.5

2x 10

4 Power output achieved at the rotor end

Time in secs

Power in Watt


Page 56 of 93

mc_eff_map=[... 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.7 0.69 0.67 0.64 0.62 0.59 0.55 0.55 0.2 0.78 0.79 0.78 0.77 0.76 0.73 0.72 0.7 0.2 0.82 0.837 0.835 0.83 0.82 0.79 0.78 0.77 0.2 0.852 0.868 0.868 0.867 0.853 0.835 0.825 0.82 0.2 0.874 0.89 0.889 0.885 0.87 0.857 0.848 0.836 0.2 0.89 0.903 0.903 0.896 0.88 0.868 0.851 0.84 0.2 0.9 0.91 0.908 0.897 0.88 0.86 0.84 0.84 0.2 0.894 0.91 0.904 0.88 0.86 0.84 0.84 0.84 0.2 0.893 0.904 0.89 0.86 0.84 0.84 0.84 0.84 0.2 0.901 0.9 0.87 0.84 0.84 0.84 0.84 0.84 0.2 0.902 0.887 0.85 0.84 0.84 0.84 0.84 0.84 0.2 0.891 0.87 0.84 0.84 0.84 0.84 0.84 0.84 0.2 0.883 0.86 0.84 0.84 0.84 0.84 0.84 0.84 0.2 0.881 0.84 0.84 0.84 0.84 0.84 0.84 0.84 0.2 0.878 0.84 0.84 0.84 0.84 0.84 0.84 0.84 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2]; %if ~exist('mc_inpwr_map') % disp('Converting: MC_AC59 motor map efficiency data --> power loss data') %% find indices of well-defined efficiencies (where speed and torque > 0) pos_trqs=find(mc_map_trq>0); pos_spds=find(mc_map_spd>0); %% compute losses in well-defined efficiency area [T1,w1]=meshgrid(mc_map_trq(pos_trqs),mc_map_spd(pos_spds)); mc_outpwr1_map=T1.*w1; mc_losspwr_map=(1./mc_eff_map(pos_spds,pos_trqs)-1).*mc_outpwr1_map; % for torque and speed > 0 %% to compute losses in entire operating range %% ASSUME that losses are symmetric about zero-torque axis, and %% ASSUME that losses at zero torque are the same as those at the lowest %% positive torque, and %% ASSUME that losses at zero speed are the same as those at the lowest %% positive speed mc_losspwr_map=[fliplr(mc_losspwr_map) mc_losspwr_map(:,1) mc_losspwr_map]; mc_losspwr_map=[mc_losspwr_map(1,:);mc_losspwr_map]; %% compute input power (power req'd at electrical side of motor/inverter set) [T,w]=meshgrid(mc_map_trq,mc_map_spd); mc_outpwr_map=T.*w; % for torque and speed >=0 [T2,w2]=meshgrid(mc_map_trq(pos_trqs),mc_map_spd); temp=T2.*w2; % torque>0 and speed >=0 mc_outpwr_map=[-fliplr(temp) mc_outpwr_map]; mc_inpwr_map=mc_outpwr_map+mc_losspwr_map; % (W) mc_map_trq=[-fliplr(mc_map_trq(pos_trqs)) mc_map_trq]; % negative torques are represented too mc_eff_map=[fliplr(mc_eff_map(:,pos_trqs)) mc_eff_map]; % the new efficiency map % considers regenerative torques too %end


Page 57 of 93

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % LIMITS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % max torque curve of the motor indexed by mc_map_spd mc_max_trq=[190 190 190 190 190 190 180 160 128 118 99 80 70 60 50 42 0]; % (N*m) % maximum overtorque (beyond continuous, intermittent operation only) % below is quoted (peak intermittent stall)/(peak continuous stall) mc_overtrq_factor=1; % (--), estimated mc_max_crrnt=78; % (A), maximum current allowed by the controller and motor, estimated mc_min_volts=200; % (V), minimum voltage allowed by the controller and motor is 400V (the voltage avilable from ess is stepped up to this value (say a step up ratio of 2), estimated %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % DEFAULT SCALING %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % (--), used to scale mc_map_spd to simulate a faster or slower running motor mc_spd_scale=0.1875; % (--), used to scale mc_map_trq to simulate a higher or lower torque motor mc_trq_scale=4.1; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % OTHER DATA %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% mc_inertia=3.11; % (kg*m^2), rotor's rotational inertia mc_mass=150; % (kg), mass of motor and controller, estimated %the following variable is not used directly in modelling and should always be equal to one %it's used for initialization purposes mc_eff_scale=1; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % CLEAN UP %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% clear T w mc_outpwr1_map mc_losspwr_map T1 w1 pos_spds pos_trqs temp T2 w2


Page 58 of 93

Block Diagram of the Motor Controller


Page 59 of 93

Power Bus

This block determines whether the power required by the motor can be

supplied solely by the generator or the energy storage system should also be

brought in to action. The inputs of this module are the power required by the

motor and the power available from generator and energy storage system. The

output is given to the generator and the energy storage system modules.

The input parameters includes the accessory electrical load and efficiency

which are entered in ACC_ZEN_CEG.m

First, the required power from the motor controller module is added with

the accessory electrical load multiplied with the accessory electrical efficiency.

This represents the total power required from the power bus. This is then

subtracted from the power available from the generator. The balance is then

outputted as power required from the energy storage system provided it is on (i.e

if ess_on = 1). The power from the generator and the energy storage system is

subtracted from the accessory electrical load and given to motor controller as the

power available.

OUTPUT POWER FROM BUS

0 1000 2000 3000 4000 5000 6000-2

-1.5

-1

-0.5

0

0.5

1

1.5

2x 10

4

Time (seconds)

Power (W)


Page 60 of 93

POWER AVAILABLE FROM GENERATOR

POWER REQUIRED FROM ENERGY STORAGE SYSTEM

0 1000 2000 3000 4000 5000 6000 70000

5000

10000

15000

Time (seconds)

Power (W)

0 1000 2000 3000 4000 5000 6000-4

-3

-2

-1

0

1

2x 10

4

Time (seconds)

Power (W)


Page 61 of 93

The input parameters file (ACC_ZEN_CEG.m) is given below

% Data file: ACC_ZEN_CEG.m % Defines standard accessory load data for use with Maruti ZEN in ADVISOR. % Created on: 23-April-2000 By Arun Kumar, Arun Rajagopalan, Arunachalam, CEG, Madras. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % FILE ID INFO %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% acc_description='Accessory Loads on a Maruti ZEN'; disp(['Data loaded: ACC_ZEN_CEG - ',acc_description]) %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % LOSS parameters %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% acc_mech_pwr=500; % (W), mechanical accessory load, drawn from

the engine acc_elec_pwr=700; % (W), electrical acc. load, drawn from the

voltage/power bus acc_mech_eff=1; %efficiency of accessory acc_elec_eff=1; acc_mech_trq=0; % (Nm), constant accessory torque load on

engine


Page 62 of 93

Block Diagram of the Power Bus


Page 63 of 93

Generator Controller

This module gives the power output of the generator taking in the torque

and speed supplied to rotor. The fuel converter is mechanically linked to the

generator’s rotor.

The output of this block is the generator output power.

Torque and Speed from the fuel converter is taken and a simple formula

Power = Torque * Speed

is used to calculate the generator output power. Efficiency of the generator

(=90%) is imposed on the output.

Block Diagram of the Generator Controller

1

generatoroutput power (W)

gc_pwr_out_aTo Workspace9

gc_spd_in_a

To Workspace11

gc_trq_in_a

To Workspace10

Product

.9

Overall Generator efficiency

Demux

Demux

1

torque and speedsupplied to rotor

(Nm), (rad/s)


Page 64 of 93

Energy Storage System (Batteries)

The Batteries (Energy Storage System ESS) is a major component in an

Electric Vehicle / Series Hybrid. It is the primary power storage device for the

Electric Motor, and acts as a buffer between the generator and the electric motor.

The Battery provides electricity to the Power Bus to provide the Electric

motor. The batteries we are planning to use are the widely available lead-acid

batteries. The battery's state of charge (SoC) is constantly monitored using

available relations and formulae. A mathematical model using the relation

between the battery voltage and state of charge is used to calculate the power

available at different times.

Necessity

The Battery is a vital part of the hybrid-electric vehicle. The limits of State of

Charge (SoC upper & lower) are to be specified by the manufacturer. When the

battery is depleted, the IC Engine starts and the battery is charged. When the

battery has enough power, the ICE shuts down, thus saving fuel, and running the

vehicle in Zero Emission Vehicle (ZEV) mode. - This minimizes pollution and

maximizes fuel economy, for the same distance traveled.

Role of subsystem in vehicle

The Energy Storage System (ESS) block represents the battery pack that

stores energy on board the modeled vehicle. This block accepts a power request,

usually from the power bus, and returns available/actual power output from the

battery, the battery voltage and current, and the battery State of Charge (SOC). By

convention, positive power is discharge.

The modeling of the battery is de pendent on various factors, including voltage,

current, temperature etc.

The effect of temperature in out modeling is neglected because:

è Not much variation is obtained


Page 65 of 93

è Component thermal modeling is very difficult.

Although batteries seem to act like simple electrical energy storage devices,

when they deliver and accept energy, they actually undergo thermally -dependent

electrochemical processes that make them difficult to model. Thus, the electrical

behavior of a battery is a nonlinear function of a variety of constantly changing

parameters. A dynamic model of electrochemical battery behavior is a

compromise between trying to include all of the relevant effects and creating a

model that will actually work in a reasonable amount of time.

Input required:

The basic battery parameters required such as mass and dimensions are noted.

The following numerical data are given:

1. Initial State of Charge (SoC) ~ 0.0 to 1.0

2. Resistance to being charged (based on SoC)

3. Resistance to being discharged (based on SoC)

4. Open Circuit Voltage (based on SoC)

5. Maximum Ampere - hour capacity at the C/5 rating

6. No. of battery modules to be used. (based on the motor controller voltage

required)

OPEN CIRCUIT VOLTAGE CHARACTERISTICS (VS SOC)

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 111.5

12

12.5

13

Battery State of Charge (SoC)

Open Circuit Voltage of Lead Acid battery


Page 66 of 93

Processing :

The ESS block models the battery pack as a charge reservoir and an

equivalent circuit whose parameters are a function of the remaining charge in the

reservoir. The equivalent circuit accounts for the circuit parameters of the battery

pack as if it were a perfect open circuit voltage source in series with an internal

resistance. The amount of charge that the ESS can hold is taken as constant and

the battery is subject to a minimum voltage limit. The amount of charge that is

required to replenish the battery after discharge is affected by coulombic

efficiency. The charging of the battery is limited by a maximum battery voltage.

While the battery is treated as a perfect electrical voltage source with a known

resistance, the components to which the battery would be connected, such as a

motor or a generator, are treated as power sources or sinks. Power delivered by the

battery is limited to the maximum that the equivalent circuit can deliver or the

maximum that the motor controller can accept, given its minimum voltage

requirement.

The maximum power available from the battery is limited by three

parameters, all related to the available voltage. The operating voltage cannot drop

below either the motor's minimum voltage or the battery's minimum voltage. If

neither of these limits is exceeded, the maximum power available will be observed

when the voltage is equal to Voc/2.

SoC algorithm: The state of charge (SoC) algorithm is responsible for

determining the residual capacity, in units of Amp-hours (charge), that remains

available for discharge from the battery. It approximates this value in a series of

steps.

Outputs obtained

The Energy Storage System returns available/actual power output from the

battery, the battery voltage and current, and the battery State of Charge (SoC). By

convention, positive power is discharge, negative power is charge.


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• SoC History

The SoC logged over the trace is available, to determine the battery

performance.

• Battery Power Output available to the Power Bus

The request for power is processed and the output power is plotted.

SOC H ISTORY (BETWEEN LIMITS)

The input parameters file (ESS_PB_CEG.m) is given below, % Battery data file: ESS_PB_CEG.m % Notes: Exide Lead Acid Battery for Maruti ZEN % Created on: 23-April-2000 By Arun Kumar, Arun Rajagopalan, Arunachalam, CEG, Madras. ess_description='Ordinary Lead Acid Battery'; disp(['Data loaded: ESS_PB_CEG - ',ess_description]) ess_on=1; % Added by AR for the ess calculations to run % SOC RANGE over which data is defined ess_soc=[0:.1:1]; % SoC range split into 10 divisions % LOSS AND EFFICIENCY parameters ess_max_ah_cap=35; % (A*h), max. capacity at C/5 rate, ess_coulombic_eff=.9; % module's resistance to being discharged ess_r_dis=[40.7 37.0 33.8 26.9 19.3 15.1 13.1 12.3 11.7 11.8 12.2 ]/1000; % (ohm) % module's resistance to being charged, indexed by ess_soc

0 1000 2000 3000 4000 5000 6000 70000.35

0.4

0.45

0.5

0.55

0.6

0.65

0.7

0.75

Time (s)

State of Charge


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ess_r_chg=[31.6 29.8 29.5 28.7 28.0 26.9 23.1 25.0 26.1 28.8 47.2]/1000; % (ohm) % module's open-circuit (a.k.a. no-load) voltage, indexed by ess_soc ess_voc=[11.70 11.85 11.96 12.11 12.26 12.37 12.48 12.59 12.67 12.78 12.89]; % (V) % Open circuit Voltage based on SoC % LIMITS ess_min_volts=9.5; % Minimum operating voltage not to be exceeded during discharge ess_max_volts=16.5; % Maximum operating voltage not to be exceeded during charge % OTHER DATA ess_module_mass=12.5; % (kg), mass of a single ~12 V module ess_module_num=20; %a default value for number of modules


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Block Diagram of the Energy Storage System


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Series Hybrid Thermostat Control Strategy

The Series Hybrid Electric Vehicle Control is the most important aspect of

vehicle design. The optimum use of the energies available is the target. Thus, an

efficient yet simple strategy is evolved to control the energy used in propelling the

vehicle according to the conditions.

Role of subsystem in vehicle

The series thermostat control strategy uses the generator and fuel converter

to generate electrical energy for use by the vehicle.

Description of modeling approach

The series thermostat control strategy uses the fuel converter as follows:

1. To maintain charge in the battery, the fuel converter turns on when the SoC

reaches the low limit, cs_lo_soc.

2. The fuel converter turns off when the SoC reaches the high limit, cs_hi_soc.

3. The fuel converter operates at the most efficient speed and torque level.

Implementation

The implementation of the series thermostat control strategy is found in the

control strategy block diagram. The State Of Charge is input into the block, and

the required engine torque and speed are the outputs.

1. The fuel converter turns on if the SoC is below the low limit, cs_lo_soc.

2. The fuel converter remains on until the SoC reaches the high limit, cs_hi_soc,

if its previous state was on. After reaching the high limit, it turns off.

3. The fuel converter operates at the most efficient speed and torque level as

previously determined by the control file.


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The input parameter file (PTC_SER_CEG.m) is given below:

% Data file: PTC_SER_CEG.m % Notes: % Defines all powertrain control parameters for a series hybrid using a thermostat control strategy. % Created on: 23-April-2000 by Arun Kumar, Arun Rajagopalan, Arunachclam, CEG, Madras. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % FILE ID INFO %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% ptc_description='Powertrain control for Maruti ZEN series hybrid with pure THERMOSTAT Control Strategy, evolved by CEG Students (Arun Kumar, Arun Rajagopalan, Arunachclam)'; disp(['Data loaded: PTC_SER_CEG - ',ptc_description]) % HYBRID CONTROL STRATEGY ess_init_soc=0.7; % (--), initial battery SOC; now this is inputed from the simulation screen %%%%%%%%%NEW%%%%%%% Added by Arun Rajagopalan on 1st May 2000 %%%%%%%%%%%%%% cs_tstat_trq=41.804; % ICE Torque at which efficiency is maximum (from fc_map_trq & fc_eff_map) cs_tstat_spd=383.26; % ICE Speed at which efficiency is maximum (from fc_map_spd & fc_eff_map) cs_hi_soc=0.7; % (--), highest desired battery state of charge cs_lo_soc=0.4; % (--), lowest desired battery state of charge cs_fc_init_state=0; % (--), initial FC state; 1=> on, 0=> off vc_idle_spd=0; % The idling speed of the engine (set to 0 to indicate constant speed operation)


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Block Diagram of the Series Hybrid Thermostat Control Strategy


Page 73 of 93

Fuel Converter

This block models the internal combustion engine, and includes inertia

effects, performance limits, accessory loads. The other details like temperature

transient effects on fuel use, engine-out emissions, and catalyst efficiency are

temporarily being terminated for want of parameters.

The input parameters to this block are entered in the file

“FC_MARUTI800MPFI_CEG.m”. The parameters required are,

§ Fuel type ( which is gasoline/ petrol in this case)

§ Engine displacement

§ Speed range of the engine (in radians/ sec)

§ Torque range of the engine corresponding to the speed range (in Nm)

§ Fuel use map indexed vertically by speed and horizontally by torque

§ Engine mass

§ Fuel density and heating value of the fuel

§ Engine surface conductivity and emissivity

§ Engine surface area

We had requested for these parameters from Maruti through Dr. T.R.

Jagadeesan, who has contacted Maruti on this regard. We had chosen Maruti 800

MPFI for two reasons, namely, it is a small and compact engine and it is Euro II

compliant.

We have created the fuel converter model on this regard with reference to the

available one, the top layer of it is as shown in the figure in the next page.

Process

The torque and the speed required at the engine output shaft is given as input

to this module. The torque and the speed achieved is calculated taking into

considerations the effect of inertia and the accessory loads. The accessory’s

mechanical power output if any is also calculated. The other important input

parameter is the clutch state, which indicates whether the clutch is engaged with


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the drive train or not. Only when the engine is started (based on the requirements

of control strategy), the clutch is engaged, after which the necessary calculations

are carried out.

The other important process carried out in this module is the calculation of the

fuel (gasoline) consumed. It utilizes the engine parameters like heat value of the

engine material, thermal conductivity and emissivity and hood surface area.

The calculation of emissions given out by the engine is temporarily being

terminated for want of parameters. Moreover, it is not necessary since there is

little or no probability of incomplete combustion since the engine is only run at

the maximum efficiency state where there is almost complete combustion of the

fuel.

Output plots of this module:

FUEL CONSUMED (IN GALLONS )

[1 GALLON = 3.785412 LITERS]

0 1000 2000 3000 4000 5000 60000

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5Fuel Consumed

Time in secs

Fuel consumed in gallons


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ENGINE OUTPUT TORQUE CURVE (WHEN ON )

OUTPUT SPEED CURVE ( IN RAD/SEC WHEN ON)

0 1000 2000 3000 4000 5000 60000

5

10

15

20

25

30

35

40

45Torque output of the engine

Time in secs

Torque in N-m

0 1000 2000 3000 4000 5000 60000

50

100

150

200

250

300

350

400Engine output speed

Time in secs



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§ Other output parameters include exhaust gas characteristics, heat removed from

engine mass by radiator and engine temperature at every instant.

FC_MARUTI800MPFI_CEG.M % Maximum Power 34.316 kW @ 6000 rpm. % Peak Torque 62.784 Nm @ 3000 rpm. % Created on: 23rd April 2000 Arun Kumar, Arun Rajagopalan, Arunachalam, CEG, Madras fc_description='Maruti 800 MPFI 12-valve 3-cyl SI Engine (34.316 KW) - transient data'; fc_fuel_type='Gasoline'; fc_disp=0.796; % (L), engine displacement fc_emis=0; % boolean 0=no emis data; 1=emis data disp(['Data loaded: FC_MARUTI800MPFI_CEG.M - ',fc_description]); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % SPEED & TORQUE RANGES over which data is defined %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % (rad/s), speed range of the engine fc_map_spd =[109.99 157.05 232.52 314.15 383.26 458.62 534.1 581.25 628.31]; % (N*m), torque range of the engine fc_map_trq=[5.244 10.489 15.734 20.979 26.07 31.314 36.559 41.804 47.049 52.294 57.539 62.784]; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % FUEL USE AND EMISSIONS MAPS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % (g/kWh), fuel use map indexed vertically by fc_map_spd and % horizontally by fc_map_trq fc_fuel_map_gpkWh =[ 508.56 508.56 433.12 357.76 282.32 265.76 249.12 257.92 266.80 266.80 266.80 266.80 542.72 400.08 355.04 309.92 264.88 241.44 237.60 226.72 215.84 286.40 286.40 286.40 370.72 370.72 326.08 280.08 235.44 224.64 213.84 203.12 215.84 242.56 269.36 269.36 559.28 454.32 400.24 346.16 241.12 227.12 213.04 198.96 207.04 215.04 217.52 254.32 474.32 474.32 395.68 314.72 236.08 223.52 210.88 198.32 204.16 210.00 236.00 258.08 534.32 419.84 305.28 281.52 257.76 243.92 230.00 216.64 232.64 248.72 264.72 264.72 504.48 504.48 418.00 328.88 242.40 243.52 244.64 243.36 251.60 259.84 262.16 262.16 558.72 400.40 342.88 314.16 285.44 270.32 262.72 255.20 263.04 270.88 266.96 266.96 600.88 510.24 416.88 326.24 314.48 302.72 290.64 278.56 255.04 272.16 272.16 272.16]; % fuel map in g/kWh % convert g/kWh maps to g/s maps [T,w]=meshgrid(fc_map_trq, fc_map_spd); fc_map_kW=T.*w/1000; fc_fuel_map=fc_fuel_map_gpkWh.*fc_map_kW/3600;


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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % LIMITS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % (N*m), max torque curve of the engine indexed by fc_map_spd fc_max_trq=[52.46 57.19 60.92 62.784 59.99 59.13 56.88 53.31 52.46]; % (N*m), closed throttle torque of the engine (max torque that can be absorbed) % indexed by fc_map_spd -- correlation from JDMA fc_ct_trq=4.448/3.281*(-fc_disp)*61.02/24 * ... (9*(fc_map_spd/max(fc_map_spd)).^2 + 14 * (fc_map_spd/max(fc_map_spd))); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % DEFAULT SCALING %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % (--), used to scale fc_map_spd to simulate a faster or slower running engine fc_spd_scale=1.0; % (--), used to scale fc_map_trq to simulate a higher or lower torque engine fc_trq_scale=1.0; fc_pwr_scale=fc_spd_scale*fc_trq_scale; % -- scale fc power %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % STUFF THAT SCALES WITH TRQ & SPD SCALES (MASS AND INERTIA) %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% fc_inertia=0.1*fc_pwr_scale; % (kg*m^2), rotational inertia of the engine (unknown) fc_max_pwr=(max(fc_map_spd.*fc_max_trq)/1000)*fc_pwr_scale; % kW peak engine power fc_base_mass=1.8*fc_max_pwr; % (kg), mass of the engine block and head (base engine) % mass penalty of 1.8 kg/kW from 1994 OTA report, Table 3 fc_acc_mass=0.8*fc_max_pwr; % kg engine accy's, electrics, cntrl's - assumes mass penalty of 0.8 kg/kW (from OTA report) fc_fuel_mass=0.6*fc_max_pwr; % kg mass of fuel and fuel tank (from OTA report) fc_mass=fc_base_mass+fc_acc_mass+fc_fuel_mass; % kg total engine/fuel system mass fc_ext_sarea=0.3*(fc_max_pwr/100)^0.67; % m^2 exterior surface area of engine %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % OTHER DATA %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% fc_fuel_den=0.749*1000; % (g/l), density of the fuel fc_fuel_lhv=42.6*1000; % (J/g), lower heating value of the fuel %the following was added for the new thermal modeling of the engine 12/17/98 ss and sb fc_tstat=96; % C engine coolant thermostat set temperature (typically 95 +/- 5 C) fc_cp=500; % J/kgK ave cp of engine (iron=500, Al or Mg = 1000)


Page 78 of 93

fc_h_cp=500; % J/kgK ave cp of hood & engine compartment (iron=500, Al or Mg = 1000) fc_hood_sarea=1.5; % m^2 surface area of hood/eng compt. fc_emisv=0.8; % emissivity of engine ext surface/hood int surface fc_hood_emisv=0.9; % emissivity hood ext fc_h_air_flow=0.0; % kg/s heater air flow rate (140 cfm=0.07) fc_cl2h_eff=0.7; % -- ave cabin heater HX eff (based on air side) fc_c2i_th_cond=500; % W/K conductance btwn engine cyl & int fc_i2x_th_cond=500; % W/K conductance btwn engine int & ext fc_h2x_th_cond=10; % W/K conductance btwn engine & engine compartment % calc "predicted" exh gas flow rate and engine-out (EO) temp fc_ex_pwr_frac=[0.40 0.30]; % -- frac of waste heat that goes to exhaust as func of engine speed fc_exflow_map=fc_fuel_map*(1+14.5); % g/s ex gas flow map: for SI engines, exflow=(fuel use)*[1 + (stoic A/F ratio)] fc_waste_pwr_map=fc_fuel_map*fc_fuel_lhv - T.*w; % W tot FC waste heat = (fuel pwr) - (mech out pwr) spd=fc_map_spd; fc_ex_pwr_map=zeros(size(fc_waste_pwr_map)); % W initialize size of ex pwr map for i=1:length(spd) fc_ex_pwr_map(i,:)=fc_waste_pwr_map(i,:)*interp1([min(spd) max(spd)],fc_ex_pwr_frac,spd(i)); % W trq-spd map of waste heat to exh end fc_extmp_map=fc_ex_pwr_map./(fc_exflow_map*1089/1000) + 20; % W EO ex gas temp = Q/(MF*cp) + Tamb (assumes engine tested ~20 C) %the following variable is not used directly in modelling and should always be equal to one %it's used for initialization purposes fc_eff_scale=1; % clean up workspace clear T w fc_waste_pwr_map fc_ex_pwr_map spd fc_map_kW % Extras added on 3rd May 2000 ex_gas_cp=1089; % the Cp of Exhaust gas


Page 79 of 93

Block Diagram of the Fuel Converter (IC Engine)


Page 80 of 93

RESULTS


Page 81 of 93

Results

The simulation was carried out with the drive cycle stated earlier. It is an Indian

Urban driving cycle with a test distance of 46.5 km and a simulation time of 6261

seconds (approximately 1hr 45min). The whole simulation process was carried with

this drive cycle. The input parameter for this cycle is given in the file “cy_uh_ceg.m”.

The details of the components included in this simulation,

q Maruti 800 MPFI engine (34.31KW)

q 45 KW Crompton Greaves 4-pole 50 Hz 3-phase AC Induction Motor/controller

q Lead Acid Battery (20 nos.) with SOC limits set as 0.4(lower) and 0.7(upper).

q Maruti ZEN vehicle and wheel parameters

q A suitable generator capable of generating a maximum 30 KW.

The results obtained from this simulation are as follows,

q The mileage of the vehicle (using petrol (or) gasoline) is about 63.80 miles per

gallon ( approximately 27 kilometer per liter)

q There is a slight trace shortfall between the requested and achieved speed. This

shortfall is solely because of wheel slip, this can ascertained by plotting the

difference between the wheel torque requested and achieved. The trace shortfall in

this simulation is shown below,

0 1000 2000 3000 4000 5000 6000 7000-1

0

1

2

3

4

5

6

7

vehicle speed (mph)

time (s)

Difference between requested and achieved speeds


Page 82 of 93

q The average efficiency of various components run during this simulation are,

40.4447% : ENGINE average efficiency

79.3293% : MOTOR/INVERTER average motoring eff.

80.0997% : Average generating eff.

95.4082% : ESS average discharge eff.

81.3832% : ESS average recharge eff.

q Other important output data :

♦ Gallons of fuel consumed : 0.4530 (approximately 1.7 litres)

♦ At 2477 th second (at 15.5 km):

• State of charge of Ene rgy Storage system reaches 0.4

• Engine starts running thereby charging the battery

♦ At 3817 th second ( at 31.5 km):

• State of charge of Energy Storage system reaches 0.7

• Engine stops running at this stage.

♦ Maximum current discharged by the battery is 86.32 amps.

♦ Final drive ratio is 0.9547 .

♦ Vehicle mass is 1525 kg ( with 300kg cargo mass)

♦ Vehicle emissions were not considered, since the vehicle was run at its peak

efficiency and moreover the engine is an Euro II compliant one.


Page 83 of 93

SENSITIVITY ANALYSIS


Page 84 of 93

Sensitivity Analysis

Sensitivity Analysis is the study of variation of the output due to the variation

of some key inputs. It is like a trial-and-error method used to choose the perfect

input configuration i.e. the values of input variables at which output is nearest or

equal to the desired value.

In our simulation we identified the following as key inputs:

1) Number of Batteries

2) Motor Power

3) IC Engine Power

4) Upper and Lower SoC Limits (Strategy)

5) Vehicle Mass

6) Driving Cycle (Urban / Highway)

The output variables that are checked for evaluation are:

1) Mileage

2) Trace Lag

3) SoC History

Default Values of Output Variables

Mileage = 63.8 mpg

Maximum Trace Lag = 6 mph

SoC History

0 1000 2000 3000 4000 5000 6000 7000

0.35

0.4

0.45

0.5

0.55

0.6

0.65

0.7

0.75

Time (s)

SoC


Page 85 of 93

Number of Batteries

Variable : ess_module_num

Default value : 20

Values 20 (Default) 25 15

Mileage 63.8 mpg 58.3 mpg 51.6 mog

Maximum Trace Lag 6 mph 4.5 mph 10 mph

SoC History

Analysis

Ø When the number of batteries are increased SoC reaches its lower limit sometime

after and hence from the graph the final SoC is higher. Therefore the battery is

less utilized than the default case and the mileage decreases. Since there are more

number of batteries to power the motor the trace lag is less.

Ø When the number of batteries are decreased SoC reaches its lower limit sometime

before and hence from the graph the IC engine is run twice to meet the SoC limits.

Therefore the mileage decreases. Since there are only less number of batteries to

power the motor the trace lag is more.

0 1000 2000 3000 4000 5000 6000 70000.35

0.4

0.45

0.5

0.55

0.6

0.65

0.7

0.75

Time (s)

SoC

Default

Bat Num=25

Bat Num=15


Page 86 of 93

Motor Power

Default value : 45 kW

Values 45 kW 37 kW 55 kW

Mileage 63.8 mpg 64.0 mpg 63.3 mpg

Maximum Trace Lag 6 mph 8 mph 5 mph

SoC History

SoC remains same with change in Motor Power

Analysis

Ø The mileage almost remains same with change in motor power. The small

variation can be accounted to the change in weight of the vehicle.

Ø The Trace lag increases for small capacity motor showing that its power is not

enough to meet the required trace.

IC Engine Power

Default value : 33 kW

Values 33 kW 42 kW 25 kW



SoC History

0 1000 2000 3000 4000 5000 6000 70000.35

0.4

0.45

0.5

0.55

0.6

0.65

0.7

0.75

Time (s)

SoC

P = 42kW

P=33kW

P=25kW


Page 87 of 93

Analysis

Ø Using a low power IC Engine lowers the rate of charge of the battery. From the

graph it is seen that the battery charge is not fully utilized at the end of the cycle.

Hence the mileage reduces.

Ø Using a high power IC Engine increases the rate of charge of the battery. From the

graph it is seen that the battery is charging at the end of the cycle and hence its

charge is not fully utilized. Hence the mileage decreases.

Upper and Lower SoC Limits (Strategy)

Upper SoC Limit

Default value : 0.7

Values 0.7 0.8 0.6



SoC History

0 1000 2000 3000 4000 5000 6000 70000.35

0.4

0.45

0.5

0.55

0.6

0.65

0.7

0.75

0.8

0.85

Time (s)

SoC

SoC High=0.7

SoC High=0.8

SoC High=0.6


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Analysis

Ø If Upper Limit of SoC is increased the battery charges for more time and hence

the IC runs longer decreasing the mileage.

Ø If Upper Limit of SoC is decreased the battery charges and discharges frequently

and hence the IC runs longer decreasing the mileage

Lower SoC Limit

Default value : 0.4

Values 0.4 0.5 0.3



SoC History

Analysis

Ø When the Lower limit of SoC is increased the battery starts charging sometime

before and hence the IC engine runs longer decreasing the mileage.

Ø When the Lower limit of SoC is decreased the battery is not fully used at the end

of the cycle and hence the mileage decreases.

0 1000 2000 3000 4000 5000 6000 70000.25

0.3

0.35

0.4

0.45

0.5

0.55

0.6

0.65

0.7

0.75

Time (s)

SoC

SoC Low=0.5

SoC Low=0.4

SoC Low=0.3


Page 89 of 93

Vehicle Mass

Default value = 1500 kgs

Values 1500 kgs 1800 kgs 1200 kgs



SoC History

SoC remains same with change in Motor Power

Analysis

Ø An increase in the vehicle weight increases the force required to pull the vehicle

and hence increases the power required from the energy source. Hence the

mileage decreases.

Ø An increase in the vehicle weight decreases the force required to pull the vehicle

and hence decreases the power required from the energy source. Hence the

mileage increases.

Driving Cycle

Fully Urban Cycle (approximate ly 5400 secs)

0 1000 2000 3000 4000 5000 60000

5

10

15

20

25

30

35

40

Time (s)

Speed (miles/hr)


Page 90 of 93

The mileage for the above cycle during simulation is 58.2 mpg

Fully Highway Cycle

The engine didn’t run in this case. Thus we see for short trips the vehicle will run

only on battery (fully electric).

Inference

The results we have obtained show that the Series Hybrid Vehicle is a feasible

solution to the aforementioned problems. The Series Hybrid promises to be a

successful transportation technology in the near future, especially in India, as the

above simulation shows convincing results.

0 100 200 300 400 500 600 700 800 9000

5

10

15

20

25

30

35

40

45

50

Time (s)

Speed (miles/hr)


Page 91 of 93

HOW TO RUN THE SIMULATION


Page 92 of 93

HOW TO RUN THE SIMULATION

The basic requirement for running this simulation is MATLAB 5.3 and above

with Simulink

The sequence of steps involved in running the simulation is given below,

q Load the Complete vehicle file ( “cv_ser_ceg.m” ). This file automatically loads

the following m files

FC_MARUTI800MPFI_CEG.M - Maruti 800 MPFI 12-valve 3-cyl SI Engine

ACC_ZEN_CEG - Accessory Loads on a Maruti ZEN

ESS_PB_CEG - Ordinary Lead Acid Battery

MC_CEG - 45 KW Crompton Greaves 4-pole 50 Hz 3-phase AC Induction

Motor/controller

WH_ZEN_CEG - Wheel/axle assembly for Maruti Zen small car

TX_1SPD_CEG - a 1-speed Transmission system (Gear Box + Final Drive)

VEH_ZEN_CEG - Maruti ZEN small car

PTC_SER_CEG - Powertrain control for Maruti ZEN series hybrid with pure

THERMOSTAT Control Strategy

INIT_CONDS - Standard initial conditions

q Load the Indian drive cycle file “cyc_uh_ceg.m”

q Open the model “bd_ser_ceg.mdl” (Which is the series power train model

developed for this simulation). The model will be opened in a separate window.

q Run the simulation.

q View the results by plotting different variables or by just opening the

“outputs.m” file

NOTE: All the files listed can be loade d by just typing the file name at the command

prompt of MATLAB window, provided the path variable is correctly set.


Page 93 of 93

References

For the project, a number of journals have been referred to, as this is a

relatively new concept, and is available only in new SAE journals, we-sites etc.

Listed below, are some of the sources of information from which we have

obtained information on the project conceptualization.

Journal Articles

1. Design of the 1995 VT Hybrid Electric - William et al, SAE Technical Paper,

1995

2. The Univ. of Tulsa's HEV Prototype - Muhammad et al, SAE Technical Paper,

1995

3. Development of the Hybrid Battery ECU for the Toyota Hybrid System - Akira et

al, Technology for Electric & Hybrid vehicles SP -1331 SAE publications, 1998

4. Validation of Advisor as a simulation Tool for a Series Hybrid Electric Vehicle -

Randall et al, Technology for Electric & Hybrid vehicles SP-1331 SAE

publications, 1998

5. Hybrid Electric Vehicle Challenge - 1995, Technology for Electric &

Hybrid vehicles SP -1176, SAE publica tions, 1995

SIMULINK Component Modules

1. National Renewable Energy Laboratory (NREL - US) Advisor Software, which

contains default MATLAB/SIMULINK models for basic components such as IC

Engine, Battery, etc.

Web-Sites

1. http://www.nrel.gov - NREL Web site for component modules

2. http://www.ctts.nrel.gov - Advisor Help & reference journal

papers

3. http://www.sae.org - SAE Technical journals

Documents

final thesis - chalamy.tripod.comchalamy.tripod.com/finalthesis.pdf · Title: final thesis Author: sab2980 Created Date: 2/9/2001 6:29:00 PM