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ENERGY EFFICIENT AND ENVIRONMENT FRIENDLY BIODIESEL FROM MANILKARA
ZAPOTA SEED OIL AS A SUSTAINABLE FUEL FOR DIESEL ENGINES
A THESIS
Submitted by
R. SATHISH KUMAR
Under the guidance of
Dr. K. SURESHKUMAR
in partial fulfillment for the award of the degree of
DOCTOR OF PHILOSOPHY
In
MECHANICAL ENGINEERING
B.S.ABDUR RAHMAN UNIVERSITY
(B.S. ABDUR RAHMAN INSTITUTE OF SCIENCE & TECHNOLOGY)
(Estd. u/s 3 of the UGC Act. 1956)
www.bsauniv.ac.in
JUNE 2015
iv
B.S.ABDUR RAHMAN UNIVERSITY
(B.S. ABDUR RAHMAN INSTITUTE OF SCIENCE & TECHNOLOGY)
(Estd. u/s 3 of the UGC Act. 1956)
www.bsauniv.ac.in
BONAFIDE CERTIFICATE
Certified that this thesis ENERGY EFFICIENT AND ENVIRONMENT
FRIENDLY BIODIESEL FROM MANILKARA ZAPOTA SEED OIL AS A
SUSTAINABLE FUEL FOR DIESEL ENGINES is the bonafide work of
R. SATHISH KUMAR (RRN: 0981201) who carried out the thesis work 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.
SIGNATURE
Dr. K. SURESHKUMAR RESEARCH SUPERVISOR Professor Department of Mechanical Engineering B.S. Abdur Rahman University Vandalur, Chennai – 600 048.
SIGNATURE
Dr. R. RAJARAMAN HEAD OF THE DEPARTMENT
Professor & Head Department of Mechanical Engineering
B.S. Abdur Rahman University Vandalur, Chennai – 600 048.
v
ACKNOWLEDGEMENT
I am greatly indebted to my supervisor Dr. K. Sureshkumar,
Professor, Department of Mechanical Engineering, B. S. Abdur Rahman
University, Chennai, for the invaluable guidance, suggestions and for the
constant encouragement and help rendered in overcoming the problems
encountered during the course of the investigation.
I am extremely grateful to Dr. M. Murugan, Professor and Dean,
School of Mechanical Sciences, and Dr. R. Rajaraman, Professor and Head,
Department of Mechanical Engineering, B. S. Abdur Rahman University,
Chennai, for sharing their valuable time and help rendered during the course
of the investigation.
I wish to express my sincere thanks to the Doctoral Committee
Members Dr. R. Velraj, Director, Institute for Energy Studies, Anna
University, Chennai and Dr. D. Eswaramoorthy, Professor, Department of
Chemistry, B. S. Abdur Rahman University, for their valuable suggestions
and guidance in each and every stage of my research work.
I wish to express my sincere thanks to the Management, Vice
Chancellor, Pro-Vice Chancellor, Registrar and Dean (AR) of B. S. Abdur
Rahman University, Chennai, for their support rendered.
I wish to express my sincere thanks to all the faculty members of
Mechanical Engineering Department, B. S. Abdur Rahman University, for
their support. My sincere thanks are also due to the supporting staff of our
University, especially Mr. R. Tamilselvan and Mr. S. N. Shajahan for their
support.
I would like to place on record my sincere gratitude to my father
Mr. K. Rajamanickam, mother Mrs. R. Umashankari and family members,
for their patience and countless support during the course of the study.
R. SATHISH KUMAR
vi
ABSTRACT
Alarming rate of depletion of fossil reserves and environmental
destruction due to excessive fossil fuel combustion have been perennial
global concerns over the decades. Transport vehicles greatly pollute the
environment through harmful emissions and their contribution towards
environmental destruction is very much significant. Scientists and
researchers across the globe carryout extensive research, to find suitable
renewable substitute to fossil diesel, in order to combat the ever increasing
fuel demand and destruction of environment.
Biodiesel is an important renewable substitute to diesel in diesel
engine applications. Biodiesel is produced from many resources such as raw
vegetable oil, animal fats, algae and waste fried oils, of which vegetable oils
are the major and vital resource for bulk production. Several research works
had been carried out to examine the performance and exhaust emissions of
unmodified diesel engines, fuelled with first and second generation biodiesels
derived from edible vegetable oils and non-edible vegetable oils respectively.
The current research focus is on identification and production of biodiesel
from non-edible and underutilized oil seeds of edible crops.
In this research work, a new vegetable based oil (Manilkara Zapota
seed Oil (MZO)) has been identified as third generation biodiesel resource. A
study on the suitability of MZO for biodiesel production, based on its fatty
acid composition and physicochemical properties has been carried out. The
vii
results strongly ascertained its suitability on account of the high proportion of
mono unsaturated fatty acid (64.15% oleate) and low saturated and poly
unsaturated fatty acids.
Based on the free fatty acid content of MZO, single step alkyl
catalyzed transesterification process was adopted for biodiesel production.
As MZO is a very new resource, optimizing the yield of biodiesel through
transesterification process has been carried out using Taguchi method.
Among the different parameters influencing the yield of biodiesel, only the
four most influencing parameters, methanol to oil molar ratio, catalyst
concentration, reaction temperature and reaction time were considered for
optimization. Methanol to oil molar ratio of 6:1, 1% (w/w) concentration of
catalyst, 90 minutes of reaction time and 50ºC temperature of reaction were
found to be the optimal parameter values for maximizing the yield of
Manilkara Zapota Methyl Ester (MZME) and the corresponding maximum
yield was 94.83%. The biodiesel produced with optimum values of
transesterification process parameters has been characterized and found to
meet the biodiesel requirements of EN 14214 standards.
Experimental investigation has been carried out in an unmodified,
single cylinder, water cooled, naturally aspirated diesel engine, fuelled with
MZME and its diesel blends, to analyse the combustion, performance and
exhaust emission characteristics. Combustion characteristics of engine
revealed that, the highest peak pressure is recorded for the blend B50
followed by B25 and diesel. The value of peak pressure for the blend B50 is
viii
59.97 bar at full load which is 1.64% more than that of diesel. Also B50
released 44.17 J/CA of net heat energy at full load, which is approximately
10% more than diesel.
Engine performance analysis revealed that test fuel B50 (50% MZME
and 50% diesel) produced 17% increase in brake thermal efficiency and
14.34% decrease in brake specific fuel consumption, with a reduction of
34.21% and 4.32% in CO and unburnt hydrocarbon emissions respectively
as compared to fossil diesel. Though an increase in CO2 emission of 38.91%
has been registered in comparison with pure diesel, all the CO2 emitted
through biodiesel combustion could be sequestered during the growth of the
plants and hence the effect on the environmental destruction is neutralised.
Hence it is concluded that, the oil extracted from underutilized
Manilkara zapota seeds can be a potential candidate for biodiesel production.
The biodiesel MZME produced from MZO, up to 50% (B50) could effectively
replace fossil diesel in unmodified diesel engine applications, with better
engine performance and exhaust emissions.
ix
TABLE OF CONTENTS
CHAPTER NO. TITLE PAGE NO.
ABSTRACT vi
LIST OF TABLES xiii
LIST OF FIGURES xiv
LIST OF SYMBOLS AND ABBREVIATIONS xvi
1 INTRODUCTION 1
1.1 GENERAL 1
1.2 ENERGY SCENARIO 2
1.2.1 Indian energy scenario 4
1.3 ALTERNATE SOURCE OF ENERGY 5
1.4 BIOFUELS 6
1.4.1 Advantages and limitations of biodiesel 7
1.4.2 Historical development of biodiesel 7
1.4.3 Feed stocks for biodiesel production 8
1.4.4 Manilkara zapota – A new resource for
biodiesel production 11
1.5 AN INTRODUCTION TO TAGUCHI METHOD 12
1.6 OBJECTIVES OF THE STUDY 18
1.7 OVERALL METHODOLOGY OF THE
RESEARCH WORK 18
1.8 ORGANIZATION OF THE THESIS 20
2 LITERATURE REVIEW 22
2.1 INTRODUCTION 22
2.2 VEGETABLE OIL AS FUEL 22
2.3 BIODIESEL PREPARATION METHODS 23
2.4 BIODIESEL PRODUCTION BY
TRANSESTERIFICATION PROCESS 26
2.5 OPTIMIZATION OF BIODIESEL PRODUCTION 30
x
CHAPTER NO. TITLE PAGE NO.
2.6 DIESEL ENGINE FUELLED WITH BIODIESEL
AND ITS DIESEL BLENDS 33
2.7 COMMENTS ON EARLIER WORKS 38
2.8 PRESENT WORK 38
3 OIL EXTRACTION AND CHARACTERIZATION 40
3.1 GENERAL 40
3.2 COLLECTION AND PREPARATION OF
MANILKARA ZAPOTA SEEDS 40
3.3 OIL EXTRACTION 41
3.4 MEASUREMENT PROCEDURE FOR
PHYSICOCHEMICAL PROPERTIES OF
MANILKARA ZAPOTA SEED OIL 43
3.5 GAS CHROMATOGRAPH SYSTEM 43
3.6 MEASUREMENT PROCEDURE FOR FATTY
ACID COMPOSITION OF MANILKARA
ZAPOTA SEED OIL 45
4 OPTIMIZATION OF BIODIESEL PRODUCTION AND
ITS CHARACTERIZATION 46
4.1 GENERAL 46
4.2 TRANSESTERIFICATION PROCEDURE 46
4.3 CHEMICALS AND EXPERIMENTAL SETUP 49
4.4 DESIGN OF EXPERIMENTS USING TAGUCHI
METHOD 51
4.4.1 Introduction to orthogonal array design 51
4.4.2 Properties of an orthogonal array 52
4.4.3 Selection of control parameters and
their levels 52
4.4.4 Selection of orthogonal array and
assignment of the variables 53
xi
CHAPTER NO. TITLE PAGE NO.
4.4.5 Signal to noise ratio (SNR) 53
4.4.6 Analysis of variance (ANOVA) 54
4.4.7 Prediction of maximum yield 55
5 ENGINE PERFORMANCE – AN EXPERIMENTAL
INVESTIGATION 56
5.1 GENERAL 56
5.2 EXPERIMENTAL SETUP 56
5.3 EXPERIMENTAL PROCEDURE 59
6 RESULTS AND DISCUSSION 60
6.1 RAW OIL CHARACTERIZATION 60
6.1.1 Fatty acid profile of Manilkara zapota
seed oil 60
6.1.2 Physicochemical properties of Manilkara
zapota seed oil 61
6.1.3 Suitability of Manilkara zapota seed oil for
biodiesel production based on its fatty
acid profile 63
6.2 OPTIMIZATION OF BIODIESEL PRODUCTION 65
6.2.1 Determination of optimal experimental
condition by Taguchi method 65
6.2.2 Identification of significant parameter and
% contribution of each parameter 67
6.2.3 Prediction of maximum yield and
Its validation 68
6.3 CHARACTERIZATION OF MANILKARA
ZAPOTA METHYL ESTER 69
6.3.1 Fatty acid profile of Manilkara zapota
methyl ester 69
6.3.2 Physicochemical properties of Manilkara
zapota methyl ester 69
xii
CHAPTER NO. TITLE PAGE NO.
6.4 ENGINE PERFORMACNE STUDY 73
6.4.1 Combustion characteristics 73
6.4.2 Performance analysis 85
6.4.3 Emission characteristics 88
7 CONCLUSION 92
7.1 SUMMARY 92
7.2 CONCLUSION 92
7.3 SCOPE FOR FUTURE WORK 94
REFERENCES 95
APPENDIX - 1 107
LIST OF PUBLICATIONS 110
TECHNICAL BIOGRAPHY 111
xiii
LIST OF TABLES
TABLE NO. TITLE PAGE NO.
1.1 Feed stocks of biodiesel production and their
physicochemical properties 9
1.2 Physicochemical properties and FAME yield of
biodiesel from different oil sources 10
1.3 L9 orthogonal array 15
4.1 Chosen parameters and their levels 52
4.2 L9 orthogonal array for four parameters at three levels 53
5.1 Test engine specification 58
5.2 Exhaust gas analyzer specifications 59
6.1 Composition of fatty acids of Manilkara zapota seed oil 61
6.2 Physicochemical properties of Manilkara zapota seed oil 62
6.3 Percentage of yield and SNR for the experiments 65
6.4 SNRL, ΔSNR and Rank values 66
6.5 Percentage contribution of process parameters 68
6.6 Composition of fatty acids of Manilkara zapota
methyl ester 70
6.7 Properties of Manilkara zapota methyl ester in
comparison with biodiesel standard and diesel 72
A.1.1 Summary of estimated uncertainties 109
xiv
LIST OF FIGURES
FIGURE NO TITLE PAGE NO.
1.1 Global energy consumption (1965 – 2012) 3
1.2 Total world energy consumption by source (2012) 3
1.3 World energy consumption by sector 2012 3
1.4 Total energy consumption in India (2012) 4
1.5 Photographic views of Manilkara zapota tree and fruit 11
1.6 Pictorial depiction of steps in Taguchi method 13
1.7 Orthogonal Array selector 15
1.8 Methodology flow chart for new biodiesel development 19
3.1 Photographic views of (a) Sample seeds
(b) Removed shells (c) Kernels 41
3.2 Schematic diagram of screw expeller 42
3.3 Photographic view of screw expeller 42
4.1 Transesterification reaction 47
4.2 Process flow chart of biodiesel production from
Manilkara zapota seed oil 48
4.3 Schematic diagram of the batch type
transesterification reactor 49
4.4 Photographic view of transesterification setup 50
4.5 Equilibrium distribution stereogram of L9 orthogonal
array design 51
5.1 Schematic representation of experimental setup 57
5.2 Photographic view of experimental setup 57
6.1 Chromatogram sample of Manilkara zapota seed oil 61
6.2 SNRL of each parameter at different levels 67
6.3 Chromatogram sample of Manilkara zapota methyl ester 70
6.4(a) Pressure versus Crank Angle for 0 % load 73
6.4(b) Pressure versus Crank Angle for 20 % load 74
xv
6.4(c) Pressure versus Crank Angle for 40 % load 74
6.4(d) Pressure versus Crank Angle for 60 % load 75
6.4(e) Pressure versus Crank Angle for 80 % load 75
6.4(f) Pressure versus Crank Angle for 100 % load 76
6.5 Cylinder peak pressure versus loads 76
6.6(a) Net Heat Release versus Crank Angle for 0 % load 78
6.6(b) Net Heat Release versus Crank Angle for 20 % load 78
6.6(c) Net Heat Release versus Crank Angle for 40 % load 79
6.6(d) Net Heat Release versus Crank Angle for 60 % load 79
6.6(e) Net Heat Release versus Crank Angle for 80 % load 80
6.6(f) Net Heat Release versus Crank Angle for 100 % load 80
6.7 Variation of Ignition Delay with percentage of load 81
6.8(a) Cumulative Heat Release Vs Crank Angle for 0 % load 82
6.8(b) Cumulative Heat Release Vs Crank Angle for 20 % load 82
6.8(c) Cumulative Heat Release Vs Crank Angle for 40 % load 83
6.8(d) Cumulative Heat Release Vs Crank Angle for 60 % load 83
6.8(e) Cumulative Heat Release Vs Crank Angle for 80 % load 84
6.8(f) Cumulative Heat Release Vs Crank Angle
for 100 % load 84
6.9 Variation of brake thermal efficiency with load 85
6.10 Variation of brake specific fuel consumption with load 86
6.11 Variation of exhaust gas temperature with load 87
6.12 Variation of CO emission with load 88
6.13 Variation of CO2 emission with load 89
6.14 Variation of NOx emission with load 90
6.15 Variation of unburnt hydrocarbon emission with load 91
xvi
LIST OF SYMBOLS AND ABBREVIATIONS
Symbols
p pressure (kPa)
T temperature (C)
t time (s)
Greek Symbols
density (kg/m3)
ϴ crank angle (°)
Abbreviations
AMW - Average Molecular Weight
ANOVA - Analysis of Variance
ASTM - American Society for Testing and Materials
ATDC - After Top Dead Centre
B100 - 100% biodiesel
B20 - Blend of diesel with 20% biodiesel
B25 - Blend of diesel with 25% biodiesel
B50 - Blend of diesel with 50% biodiesel
B75 - Blend of diesel with 75% biodiesel
BP - Brake Power
BSEC - Brake Specific Energy Consumption
BSFC - Brake Specific Fuel Consumption
BTDC - Before Top Dead Centre
BTE - Brake Thermal Efficiency
CHR - Cumulative Heat Release
CI - Compression Ignition
CO - Carbon Monoxide
CO2 - Carbon Dioxide
CPC - Column Planer Chromatography
xvii
CV - Calorific Value
D100 - 100% diesel
DCM - Double Metal Cyanide
EGT - Exhaust Gas Temperature
EIA - Energy Information Administration
EN - European Norms
ESG - Eruca Sativa Gars vegetable oil
FA - Fatty Acids
FAME - Fatty Acid Methyl Ester
FFA - Free Fatty Acid
FID - Flame-Ionization Detector
GC - Gas Chromatography
GC-MS - Gas Chromatography – Mass Spectrometric
GDP - Gross Domestic Product
GLC - Gas-Liquid Chromatography
H2SO4 - Sulfuric Acid
HC - Hydro Carbon
HP - Horse Power
HPLC - High Performance Liquid Chromatography
IEA - International Energy Agency
kg - kilo grams
kJ - kilo Joules
KOH - Potassium Hydroxide
kWh - kilo Watt hour
LHR - Low Heat Rejection
LTB - Larger the Better
mgl-1 - milligram per liter
MJ - Mega Joules
MMT - Million Metric Tones
MNRE - Ministry of New and Renewable Energy
MOME - Mahua Oil Methyl Ester
MSD - Mass Spectrometric Detector
MT - Metric Tone
MTs - Metric Tones
xviii
MW - Molecular Weight
MZME - Manilkara Zapota Methyl Ester
MZO - Manilkara Zapota Seed Oil
N2O - Nitrous Oxide
N2O2 - Dinitrogen Dioxide
N2O3 - Dinitrogen Trioxide
N2O4 - Dinitrogen Tetroxide
N2O5 - Dinitrogen Pentoxide
NaOH - Sodium Hydroxide
NDIR - Non Distractive Infra-Red
NIST - National Institute of Standards and Technology
NO - Nitric Oxide
NO2 - Nitrogen Dioxide
NOx - Nitrogen Oxides
NRSA - National Remote Sensing Agency
NTB - Nominal the Best
OA - Orthogonal Array
OAs - Orthogonal Arrays
PCRA - Petroleum Conservation Research Association
PFME - Poultry Fat Methyl Esters
PM - Particulate Matter
ppm - parts per million
PPME - Pongamia Pinnata Methyl Ester
RBO - Rice Bran Oil
ROHR - Rate of Heat Release
rpm - revolutions per minute
SEC - Size Exclusion Chromatography
SFC - Specific Fuel Consumption
SNR - Signal to Noise Ratio
SNRL - Level mean Signal to Noise Ratio
SNRT - Total mean Signal to Noise Ratio
SO2 - Sulphur Dioxide
SOx - Sulphur Oxides
STB - Smaller the Better
xix
TDC - Top Dead Centre
THC - Total Heat Content
UBHC - Un-Burnt Hydrocarbon
UN - United Nation
VCR - Variable Compression Ratio
VOME - Vegetable Oil Methyl Ester
WCO - Waste Cooking Oil
1
1. INTRODUCTION
1.1. GENERAL
Energy resources can be classified into three groups namely fossil,
renewable, and fissile or nuclear.
Fossil fuels were formed many years ago by the underground heat and
pressure and are not renewable. The fossil energy sources are
petroleum, coal, bitumens, natural gas, oil shales, and tar sands.
Renewable energy is the energy from a source that is not depleted
when used, such as wind, solar power etc..
Fissile or nuclear material is one that is capable of sustaining a chain
reaction of nuclear fission. The principal fissile materials are Uranium-
235, Plutonium-239, and Uranium-233.
From the mid and near tail of 19th century, energy crisis had been a
worldwide alarming concern. Exponentially increasing population, rapid
growth of industrialization and the global trend of urbanization have
drastically increased the demand for energy resources. The rapid depletion
of fossil fuel and environmental air pollution due to fossil fuel combustion are
the two major consequences of energy demand compensation. These two
consequences further affect the economy and development of any growing
country like India.
Energy is the primary requirement in various sectors like power,
transport, industrial, commercial and residential etc.. The development of any
country depends upon the availability of various natural resources, in
particular energy resources and their effective utilization. Energy
conservation and efficient use of energy are very essential to promote
development. The per capita energy consumption determines the status of a
country whether developed or underdeveloped. In the present day’s energy
and environment scenario, it is very much crucial for any country, to promote
the use of renewable energy sources for various applications.
2
Scientists and researchers are forced to concentrate attention on
finding new renewable, and environment friendly alternate sources of energy.
Vegetable oils have become more attractive recently because of their
environmental benefits and better exhaust emissions. They don’t contribute
any rise in the level of carbon dioxide in the atmosphere and most
importantly they are renewable. Development of more such vegetable based
biodiesel and their maximum utilization to meet the energy demand in various
sectors across the globe is very much crucial to combat the twin alarming
global concerns of “Global Warming” and “Environmental Degradation”.
1.2. ENERGY SCENARIO
Total world energy consumption in the year 2012 was grown by 1.8%.
In comparison with the consumption in the year 1965, approximately it has
tripled in the year 2012 as shown in Figure 1.1. Industrial growth, increasing
mobility, modern means of transport, changing lifestyle and mechanization of
labour are some considerable reasons for the increase in consumption at an
alarming rate. Oil fulfils around 34% of the total energy consumption followed
by coal with 30%, gaseous fuels contributing 22%, biomass with 8%, hydro
energy with 6% and at last nuclear materials share 4%.
Currently 78.2% of the global energy demand is met by fossil fuels
such as petrochemicals, natural gas and coal followed by renewable energy
sources 19% and 2.8% by nuclear sources. In renewable energy sources
biomass and hydro power and bio heat contribute major share as shown in
Figure 1.2. Since the demand and cost of petroleum based fuel are growing
rapidly, and if the present pattern of fossil consumption continues, these
resources will be depleted in few years.
In the present scenario, industrial sector consumes 51.7 % of the total
energy consumption. Next largest energy consumption sector is
transportation sector which consumes around 26.6 % followed by residential
and commercial sectors with 13.9 % and 7.8 % respectively. It is shown in
the Figure 1.3.
3
Figure 1.1: Global energy consumption (1965 – 2012)
(Source: BP Statistical Review of World Energy 2013)
Figure 1.2: Total world energy consumption by source (2012) (Source: BP Statistical Review of World Energy 2013)
Figure 1.3: World energy consumption by sector 2012 (EIA data)
4
1.2.1. Indian energy scenario
India has extraordinary economic growth over the last few decades.
Today, India is the tenth largest economy in the world (listed by UN) with
GDP of 1,875,213 million US dollars. The real GDP growth of Indian
economy in the last 5 years is 8.7% and in the last 10 years is 7.5%. This
high order of unrelenting economic growth is attracting more industries to
come to India and placing enormous demand on its energy resources. The
imbalance in demand and supply of energy resources is forcing the
Government of India to take serious efforts to augment energy supplies.
Even though global economy is slowing down, energy demand in India is
continued to rise rapidly. Indian Planning Commission report says that India’s
energy demand will grow by 41% by 2017 from the present.
India was the fourth largest consumer of crude oil and natural gas in
2011 – 12. Demand for petroleum products in the transport sector is growing
rapidly in the recent years. The crude oil consumption of India during
1970 – 71 was 18.38 MTs; the same was increased to 211.42 MTs during
2011 – 2012 with compound annual growth rate of 5.99%.
Figure 1.4: Total energy consumption in India (2012).
(Source: International Energy Agency, BP statistical review)
5
According to International Energy Agency, 44 % of Indian energy
consumption is relying on coal and 22 % on petroleum oils, another 22 % on
energy from biomass and waste. Hydroelectric energy is contributing 3%
followed by nuclear energy with 1% as shown in Figure 1.4.
Clean and renewable energy alternatives, capacity addition, energy
conservation, energy sector reforms and monitoring of energy exploitation
are very critical for energy security in India. Especially energy conservation
and effective utilization of energy resources play a crucial role in bridging the
gap between supply and demand of energy. The most desirable option for
short term bridging of the gap between supply and demand is improving
energy efficiency.
Indian economy and development suffer drastically due to the ever-
growing crude oil import and the severe global threat posed by increasing
fossil fuel combustion emissions. Hence scientists and researchers are
forced to concentrate on finding renewable and environment friendly
alternate source of energy.
1.3. ALTERNATE SOURCE OF ENERGY
The current rate of utilization of liquid fossil fuel and its derivatives
shows that they will not sustain for energy supply for longer period.
Particularly developing countries like India have seriously thought of
switching over to nuclear and renewable sources. Meeting the supply and
demand gap in energy is of fundamental importance to India’s imperatives of
economic growth. Developing resources for efficient and reliable energy
supply for long term perspective is crucial for economic growth of developing
countries. Unfortunately India has very limited availability of conventional
energy sources and are depleting in a faster rate.
In the year 2012 – 2013, 40 % of the energy demand was met by
crude oil import in India. Increase in fossil fuel utility correspondingly
increases the crude oil import, as India’s crude oil resource is very low. The
6
uncertainty in crude oil supply and frequent price hike give severe setback in
industrial and transport sectors. Hence, newer energy resource development
with least possible cost attains importance to conquer self-reliance in energy
and economic development.
Global warming, ozone depletion and acid precipitation are three
major environmental degradations due to fossil fuel combustion. Acidification
of lakes, streams and ground waters, damage to fish and aquatic life,
damage to forests and agricultural crops and deterioration of materials are
some more serious problems caused by harmful and toxic emissions from
fossil fuel combustion. Most of the global air pollution are caused by the use
of fossil fuels for transportation. Diesel engines are a major source of air
pollution. The exhaust gases from diesel engines contain oxides of nitrogen
(NOx), carbon monoxide (CO), carbon dioxide (CO2), unburnt or partially
burned hydrocarbons (HC), and particulate matter. Hence efforts are being
made to explore the alternative sources of energy.
The above discussed twin problems of fossil fuel depletion and the
environmental hazards emphasize the need for alternate renewable energy
sources to have sustainability of energy resources, better sociability and
better environmental conditions. Finding an eco-friendly and energy efficient
resource is the timely need of the world.
1.4. BIOFUELS
Biomass fuels are very attractive replacement for the fossil energies,
because they do not require primary energy raw material and thus cannot
give rise to any of the pollutants. Renewable biomass energies are closed
loop energy systems, without radioactivity and they do not supply additive
carbon or heat to the geo-sphere. In view of this, vegetable oil is a promising
alternative because it has several advantages; it is renewable, environ-
friendly and produced easily in rural areas, where there is an acute need for
modern forms of energy [1&2]. Biomass based fuels draw attention all over
the world because they are sustainable, improve the environmental quality
7
and provide new job opportunities in rural areas [3]. Several developed
countries have introduced policies encouraging the use of biofuels made
from grains, vegetable oil or biomass to replace part of their fossil fuel use in
transport.
1.4.1. Advantages and limitations of biodiesel
Biodiesel has gained greater attention because of the advantages
such as (i) being renewable and biodegradable (ii) higher cetane number (iii)
lower emission of carbon monoxide, particulate matters and unburnt
hydrocarbon and (iv) lower sulphur and aromatic content. However, still it is
not fully replacing fossil diesel, because of disadvantages such as higher
NOx emission, higher viscosity, lower oxidative and storage stability which
need to be addressed. Through persistent and intensive research, some of
the above problems have already been addressed. An antioxidant additive
can be used to increase the long term storage stability. Oxygenated,
antioxidant and cetane number improving additives can be used to reduce
the NOx emission.
1.4.2. Historical development of biodiesel
First usage of vegetable oil as substitute fuel for diesel engine had
been introduced by Rudolf Diesel in the year 1902. The concept of viscosity
reduced fatty acid methyl esters called biodiesel was introduced by
Chavanne in 1937. He had described the procedure of converting raw palm
oil into biodiesel through transesterification reaction. After that, Expedito
Parente in 1977 had applied the first patent of industrial process for biodiesel
fuel. It took one decade time to establish the first biodiesel pilot plant. The
first industrial-scale plant was installed in 1989 [4]. Even though, usage of
vegetable oil and its biodiesel as fuel to IC engines was identified in the
beginning of 20th century, extensive researches have been started in the tail
of 20th century, particularly 1990s, when the demand for fossil fuel increased.
Many governments, such as the United States, France and Italy, promoted
the usage of biodiesel as an alternative for diesel fuel. Countries like Brazil,
8
Canada, Germany, China and Japan had begun to invest and established
biodiesel plants.
International standards of biodiesel such as ASTM D6751 and EN
14214 have been introduced and used around the world for quality control of
biodiesel products and safe operation of biodiesel in unmodified diesel
engines. Biodiesel product must meet the requirements of these international
standards for use as commercial engine fuel. At present, biodiesel is blended
with commercial diesel in some proportion like B20 (20% biodiesel and 80%
diesel), B40 (40% biodiesel and 60% diesel) and used as fuel for diesel
engines in European countries and United States [4]. With improved and
optimized production process and sophisticated storage technologies,
biodiesel will gain significant attention in the years to come.
1.4.3. Feed stocks for biodiesel production
Biodiesel products are the mono-alkyl esters of fatty acids, mostly
derived from tree borne oils, vegetable based oils, fats of animal and waste
cooked oil. As most of the feed stocks used for biodiesel are edible and the
cost of raw material is very high to the tune of 60-80% of the total cost, it
becomes essential now a days to identify new and underutilized feedstock for
biodiesel production. To overcome the above problem, researchers have
turned focusing more attention on oils of non-edible nature like jatropha,
pongamia, neem, rubber, camelina and soap seed etc.. Table 1.1 shows
some of the feed stocks reported so far and their physicochemical properties.
High level of saturated fatty acids content in animal fat makes it to be
considered as another feedstock for biodiesel production even though it is
expensive as compared to vegetable oils. The problem in animal fats is that,
it becomes solid in room temperature which causes problems in biodiesel
production process [5].
9
Table 1.1: Feed stocks of biodiesel production and their physicochemical properties
(Source: Wu, Xuan, Ph.D. thesis, The University of Hong Kong, August, 2012)
Type Specifies Density (g/cm3)
Kinematic viscosity
(cst, 40 ºC)
Flash point (ºC)
Acid value (mg KOH/g)
Heating value
(MJ/ kg) Reference
Edible
Soybean 0.91 32.9 254 0.2 39.6 (Byun et al., 1995; Srivastava and Prasad, 2000)
Rapeseed 0.91 35.1 246 2.92 39.7 (Demirbas, 2003; Azcan and Danisman, 2008)
Sunflower 0.92 32.6 274 ---- 39.6 (San Jose Alonso et al., 2008)
Palm 0.92 39.6a 267 0.1 ---- (Singh and Singh, 2009)
Peanut 0.90 22.72 271 3 39.8 (Kaya et al., 2009; Rao et al., 2009)
Corn 0.91 34.9a 277 ---- 39.5 (Saraf and Thomas, 2007; Singh and Singh, 2009)
Camelina 0.91 ---- ---- 0.76 42.2 (Bernardo et al., 2003)
Canola ---- 38.2 ---- 0.4 ---- (Issariyakul et al., 2008)
Cotton 0.91 18.2 234 ---- 39.5 (Singh and Singh, 2009)
Pumpkin 0.92 35.6 >230 0.55 39 (Schinas et al., 2009)
Non-edible
Jatropha curcas 0.92 29.4 225 28 38.5 (Berchmans and Hirata, 2008)
Pongamia pinnata 0.91 27.8 205 5.06 34 (Sahoo and Das, 2009)
Sea mango 0.92 29.6 ---- 0.24 40.86 (Kansedo et al., 2009)
Palanga 0.90 72.0 221 44 39.25 (Meher et al., 2006)
Animal fats
Tallow 0.92 ---- ---- ---- 40.05 (Goodrum et al., 2003; Saraf and Thomas, 2007)
Nile tilapia 0.91 32.1b ---- 2.81 ---- (Santos, Malveira, et al., 2009)
Poultry 0.90 ---- ---- ---- 39.4 (Goodrum et al., 2003; Liu et al., 2004)
Used cooking oil 0.90 44.7 ---- 2.5 ---- (Issariyakul et al., 2008)
a Kinematic viscosity at 38 ºC, mm2/s; b Kinematic viscosity at 37 ºC, mm2/s;
9
10
Table 1.2: Physicochemical properties and FAME yield of biodiesel from different oil sources
(Source: Wu, Xuan, Ph.D. thesis, The University of Hong Kong, August, 2012)
Specifies Density (g/cm3)
Kinematic viscosity
(cst, 40 ºC)
Iodine value
Cetane number
Acid value (mg KOH/g)
Heating value
(MJ/ kg)
FAME yield (%)
Reference
Soybean 0.885 4.08 138.7 52 0.15 40 >95 (Liu et al., 2008; Winayanuwattikun et al., 2008)
Rapeseed 0.88 - 0.888 4.3 - 5.83 ---- 49 – 50 0.25 - 0.45 45 95 - 96 (Rashid and Anwar, 2008)
Sunflower 0.88 4.9 142.7 49 0.24 45.3 97.1 (Rashid et al., 2008; Winayanuwattikun et al., 2008)
Palm 0.86-0.9 4.42 60.07 62 0.08 34 89.23 (Winayanuwattikun et al., 2008; Hameed et al., 2009;
Singh and Singh, 2009)
Peanut 0.883 4.42 67.45 54 ---- 40.1 89 (Winayanuwattikun et al., 2008; Kaya et al., 2009;
Singh and Singh, 2009)
Corn 0.89 3.39 120.3 58 - 59 ---- 45 85 - 96 (Winayanuwattikun et al., 2008; Patil and Deng, 2009)
Camelina 0.882-0.888 6.12 – 7a 152-157 ---- 0.08 - 0.52 ---- 97.9 (Frohlich and Rice, 2005)
Canola 0.88-0.9 3.53 103.8 56 ---- 45 80 - 95 (Winayanuwattikun et al., 2008; Patil and Deng, 2009)
Cotton 0.875 4.07 104.7 54 0.16 45 96.9 (Rashid et al., 2009)
Pumpkin 0.8837 4.41 115 ---- 0.48 38 97.5 (Winayanuwattikun et al., 2008; Schinas et al., 2009)
Jatropha curcas 0.8636 4.78 108.4 61 - 63 0.496 40 - 42 98 (Chitra et al., 2005; Patil and Deng, 2009)
Pongamia pinnata 0.883 4.8 ---- 60 - 61 0.62 42 97 - 98 Meher et al., 2006; Patil and Deng, 2009; Sahoo and
Das, 2009)
Palanga 0.869 3.99 ---- ---- ---- 41 85 (Sahoo and Das, 2009)
Tallow 0.856 ---- 126 59 0.65 ---- 98.28 (Bhatti et al., 2008)
Nile tilapia ---- ----- 88.1 51 1.4 ---- 98.2 (Santos, Malverira, et al., 2009)
Poultry 0.867 ---- 130 61 0.25 ---- 99.72 (Bhatti et al., 2008)
Used cooking oil ---- 4 ---- ---- 0.15 ---- 94.6 (Leung and Gua, 2006)
a Kinematic viscosity at 20 ºC.
10
11
Waste cooking oil (WCO) is another suitable feedstock for biodiesel
production. The cost of WCO is comparatively lower than fresh vegetable oil,
which results in low production cost for biodiesel. The major problem with
WCO is its inferior quality. The physical and chemical properties of WCO
depend on its previous usage and the contents of fresh cooking oil. It may
contain lots of undesired impurities, such as water, free fatty acids and solid
cocking wastes [5-8]. Bad quality of waste cooking oil would affect the quality
of finished biodiesel product. Table 1.2 shows some of the physiochemical
properties and fatty acid methyl ester yield of final biodiesel produced from
different feed stocks
1.4.4 Manilkara zapota – A new resource for biodiesel production
Manilkara zapota, popularly known as sapodilla, a forest tree with long
life span is mostly found in southern Mexico, Caribbean and Central
America. It is also cultivated in larger scale in India, Thailand, Cambodia,
Malaysia, Indonesia, Bangladesh mainly for its fruit. It is known as chikoo
(chiku) in Northern India, and sapota in southern parts of India. It is an
evergreen tree growing in all tropical lands like wet tropics to dry cool
subtropical areas. Even though the tree flowers and fruits throughout the
year, maximum yield occurs only during the period of March to June.
Photographic views of Zapota tree and fruits are shown in Figure 1.5.
Figure 1.5: Photographic views of Manilkara zapota tree and fruit
12
The homogenous, deep red color valuable wood is majorly used for
heavy constructions, to make furniture and tool handles. The timber of
Manilkara zapota is having good qualities such as very strong, dense, tough,
hard, and durable. The milky latex tapped from the tree is used as principal
constituent of chewing gum before the invention of synthetics in America. In
the past years, the gum has also been used in transmission belts and dental
surgery before the invention of suitable plastics for these applications.
Decoction from the leaf is consumed as medicine for fever, haemorrhage,
wounds and ulcers.
Sapota is a fruit with sweet juicy flesh covered by a rough brownish
skin containing 1 – 12 seeds of brown or black colour. It is eaten raw or
made into jam and juice. The seeds are not utilized for any major purpose
except seedling. Manilkara zapota seeds have an oil content of 23 – 30 %
and hence this underutilized oil seeds can be considered for production of
biodiesel.
1.5. AN INTRODUCTION TO TAGUCHI METHOD
Dr.G.Taguchi developed a new method to examine the effect of
different parameters of a process on the mean and variance of performance
characteristic that determines the proper functioning of the process. This
method for design of experiments makes use of orthogonal arrays for the
optimization of different parameters influencing the process and the extent to
which they can be varied. The very specialty of this method is not to
investigate all the possible parameters combinations but only few pairs of
combinations.
This method paves way for collation of data for the determination of
factors which most influence the quality of product with minimal number of
experiments so as to reduce the precious time and resources. This method is
very effective with nominal number of parameters (3 to 50), few interactions
between them and a very few contributing significantly. The flow diagram
13
depicting the general steps involved in Taguchi method is given in
Figure 1.6. The general steps involved in Taguchi Method are given below.
Figure 1.6: Pictorial depiction of steps in Taguchi method
Validation Experiment
Individual factor
contribution
Relative factor
interaction
Determination of optimum
levels
ANOVA and SNR analysis
Performance under
optimum conditions
Determine the factors
Identify test conditions
Identify control and noise factors
Design the matrix experiments (OAs)
Define the data analysis procedure
Conduct designed experiments
Analyse the data
Predict the performance at these
14
Selection of the independent variables
Identification of the process parameters or independent variables
called factors which are influencing the outcome or response dependant
variable is primary and foremost important step in Taguchi method. Based on
the thorough knowledge on the problem, first all the independent variables
affecting the response variable are to be listed and then the required
variables are to be identified.
Deciding the number of levels
The next crucial step in Taguchi method is fixing the number of levels
for each selected independent variable. The number of levels is selected
based on the kind of relationship between each independent variable and
dependent variable. If the independent variable is having linear relationship
with dependent variable, then 2 shall be the ideal number of level. However,
if the relation between independent and dependent variable is quadratic,
cubic or higher order, then one could go for 3, 4 or higher levels respectively.
Selection of an orthogonal array
Before selecting the orthogonal array (OA), the least possible number
of experiments (N) to be conducted shall be fixed based on the number of
parameters and the variation levels of each parameter. The minimum
number of experiments N is decided based on the total degrees of freedom
available. It is calculated using the relation N = (L–1) P + 1. In the above
relation L is the number of levels and P is number of chosen independent
parameters. Once the minimum number of experiments is decided,
appropriate orthogonal array can be selected based on the number of
independent variables and levels for each independent variable using the OA
selector, shown in Figure 1.7. For example with four parameters and three
levels, a minimum of nine experiments are to be conducted. From the OA
selector, the best suitable orthogonal array is L9. Four parameters and their
15
levels for each experiment are assigned in the corresponding rows as shown
in Table 1.3.
Assigning the independent variables to columns
Once the appropriate OA is selected, the independent variables and
their level values should be assigned to the corresponding vertical columns.
The independent variables are to be assigned at right columns as specified
by the orthogonal array in case of mixed level variables and interaction
between variables.
Figure 1.7: Orthogonal Array selector
Table 1.3: L9 orthogonal array
Experiment no. Parameters and their levels
A B C D
1 1 1 1 1
2 1 2 2 2
3 1 3 3 3
4 2 1 2 3
5 2 2 3 1
6 2 3 1 2
7 3 1 3 2
8 3 2 1 3
9 3 3 2 1
16
Conducting the experiment
Once the selected orthogonal array is assigned with independent
variables and their level values, the experiments are conducted as per the
given combinations. It is necessary that all the experiments be conducted. If
any interaction column and dummy variable column are available in the OA,
then they shall not be considered for conducting the experiment. However
they are needed during the analysis of the data in order to understand the
interaction effect. Each experiment can be repeated any number of times
based on the quality requirement of the product yield. The measured
response parameter under the study is noted down for each experiment, for
further data analysis.
Analysis of the data
The effect of individual independent variable at a particular level on
dependent variable cannot be directly identified from a single experiment, as
each experiment is the combination of different factor levels. This could be
identified by calculating the arithmetic mean of the performance values for
the corresponding parameter at particular level settings. For example, in
order to calculate the effect of level 2 of the independent variable 1 as given
in Table 1.3, find the mean of the performance values of the experiments 4, 5
and 6. Similarly for level 2 of variable 3, calculate the mean of the
experimental results of 2, 4 and 9.
Once the mean value of each level of a particular independent
variable is calculated, the sum of square of deviation of each of the mean
value from the total mean value is calculated. This sum of square of
deviation of a particular variable is used to identify whether the change in
level settings of that variable is significant or not. If for a particular parameter,
the value of sum of square of deviation is large, then that particular
parameter is most significant and if its value is close to zero, then it is
insignificant. To identify which parameter influences more on the response
17
variable, sensitivity analysis should be conducted using signal to noise ratio.
The percentage contribution of a particular independent variable can be
identified by performing Analysis of Variance (ANOVA).
Inference
Once the statistical analysis discussed in the previous step is done
the following inferences may be made, an independent variable which
possesses higher SNR ratio will be the most influencing parameter as
compared to others. The ratio of individual sum of square of a particular
independent variable to the total sum of squares of all the variables is known
as percentage contribution of that particular variable. This ratio will help to
calculate the individual contribution level of each parameter. Along with the
above inferences, theoretical nearer optimum solution to the problem can
also be calculated. However this optimum solution is not a global optimum, it
could be used as an initial optimum solution.
Assumptions in Taguchi method
The additive assumption implies that the individual effects of the
independent variables on the performance parameter are separable. Under
this assumption, the effect of each factor can be linear, quadratic or of higher
order, but the model assumes that there exists no cross product effects
(interactions) among the individual factors. That means the effect of
independent variable 1 on the performance parameter does not depend on
the different level settings of any other independent variable and vice versa.
If at any time, this assumption is violated, then the additivity of the main
effects does not hold, and the variables interact.
18
1.6. OBJECTIVES OF THE STUDY
The present study aims to develop a new biodiesel from Manilkara
zapota seed oil.
As the Manilkara zapota seed oil is very new resource to attempt and
not yet reported earlier, it is important to optimize the process
parameters of transesterification process for maximum biodiesel
yield.
Hence this research work aims to optimize four most influencing
transesterification process parameters using Taguchi method of
design of experiments, and to produce the biodiesel using optimal
parameter values.
Another main objective of the research is to analyse the
performance, combustion and emission characteristics of an
unmodified diesel engine fuelled with 100% Manilkara zapota methyl
ester (MZME) (B100), blends of MZME with diesel in proportions of
25%, 50% and 75% under different loading conditions varying from 0
to 100% with 20% step increment.
1.7. OVERALL METHODOLOGY OF THE RESEARCH WORK
Methodology flow chart for the new biodiesel development from
Manilkara zapota seed oil is illustrated in Figure 1.8. It starts with the
collection of Manilkara zapota seeds and subsequent cleaning and drying
processes. Once the seeds are cleaned and dried, their shell is removed
manually. Next step is the extraction of oil from the kernels. Physicochemical
properties and fatty acid contents of the extracted vegetable oil are the two
important characteristics to identify the suitability of any vegetable oil to be
used as biodiesel resource. Hence physicochemical properties and fatty acid
contents of Manilkara zapota seed oil (MZO) are estimated and analysed.
19
Figure 1.8: Methodology flow chart for new biodiesel development
As MZO is a new biodiesel resource, the four most influencing
transesterification process parameters are optimized by using Taguchi
method. Physicochemical properties and fatty acid contents of the new
biodiesel MZME are measured and compared with fossil diesel and EN
14214 biodiesel standards. The last step in the process is experimental
Collection and preparation of Manilkara zapota (L) seeds
Extraction of oil using screw expeller
Optimisation of transesterification process parameters using Taguchi method
Characterization of Manilkara Zapota Seed Oil (MZO)
Characterization of Manilkara Zapota Methyl Ester (MZME)
Performance, combustion and exhaust emission characteristics of an unmodified CI engine fuelled
with MZME and its diesel blends
20
investigation of performance, combustion and emission characteristics of an
unmodified CI engine fuelled with MZME and its diesel blends.
1.8. ORGANIZATION OF THE THESIS
This introductory chapter is followed by six chapters.
Chapter 2 presents an extensive literature review related to this research
work. This chapter reveiws literatures in the areas of need and importance of
biodiesel, biodiesel production methods, biodiesel production through
transesterification process, optimization of tranesterification process
parametes, and performance and exhaust emission characteristics of
biodiesel fuelled diesel engine.
Chapter 3 describes about the collection and preparation of seeds, oil
extraction, characterisation of raw manilkara zapota seed oil (i.e estimation
of fatty acid composition and psysico-chemical properties) and theoritical
study on suitability of MZO for biodiesel production by correlating its fatty
acid profile with biodiesel characteistics.
Chapter 4 deals with optimisation of key parameters of transesterification
process using Taguchi method of experimental design. In this chapter the
method of identifying the optimum level of set of parameters, highly
influencing parameter and contribution of each parametrs for maximum yield
of biodiesel from Manilkara zapota seed oil are well described. It also
describes the charaterization of the produced biodiesel.
Chapter 5 describes about the detailed specification of experimental engine
setup and exhaust gas analyser. It also describes the experimental
procedure followed to measure the engine combustion, performance and
emission characteristics of an unmodified diesel engine fuelled with MZME
and its diesel blends.
21
Chapter 6 discusses with the results pertaining to raw oil characterisation,
optimisation of transesterification process parameters using Taguchi method
and the combustion, performance and emission characteristics of an
unmodified diesel engine fuelled with MZME and its diesel blends.
Chapter 7 summarizes the conclusions arrived from the optimization study,
fuel characterization and the experimental investigation of biodiesel usage in
diesel engine. It also describes the scope for future research in this area and
the possibility of extension of the work.
22
2. LITERATURE REVIEW
2.1. INTRODUCTION
In the recent years, biodiesel has gained increased attention among
scientists and researchers to use it as a substitute for fossil diesel in diesel
engine applications. To understand the current scenario about biodiesel utility
and its related issues, an extensive literature review has been carried out and
reported in this chapter. The present review highlights the various issues
related to biodiesel such as vegetable oil as fuel, biodiesel preparation
methods, biodiesel production by transesterification process, optimisation of
biodiesel production and use of biodiesel and its diesel blends as fuel in an
unmodified diesel engines.
2.2. VEGETABLE OIL AS FUEL
“The use of vegetable oils for engine fuels may seem insignificant
today, but such oils may in course of time be as important as petroleum and
the coal tar products of the present time” said by Rudolph Diesel around 100
years ago when he has tested peanut oil in his CI engine. Rudolph Diesel
made an attempt to use peanut oil directly as a fuel in diesel engine [9]. Being
renewable in nature, vegetable oils are assuring feed stocks for biodiesel
production.
There are many problems encountered during the direct usage of
vegetable oils in diesel engines such as improper fuel atomization due to
plugged orifices, gelling of lubrication oil, carbon deposits, and oil ring sticking
etc.. All the above stated problems are due to the high viscosity and low
volatilities of the vegetable oil and animal fats which cause improper
vaporization, incomplete combustion and deposits in engines [10].
Large triglyceride molecule and higher molecular mass are the reasons
for high viscosity of vegetable oils. An effective method of overcoming all the
problems of direct use of vegetable oils as fuel in diesel engine is to convert
23
the oil into less viscous mono alkyl esters called biodiesel [11]. Biodiesel has
higher cetane number than petroleum diesel, no aromatics, and contains 10-
11% oxygen by weight thus facilitating complete combustion. These
characteristics reduce the emissions of carbon monoxide (CO), hydrocarbons
(HC), and particulate matter (PM) in comparison with diesel [12].
Biodiesels possess attractive characteristics such as non-toxic,
biodegradability, less pollutant to water and soil and contains very small
amount of phosphorus and sulphur [13 & 14]. Monyem et al. (2001) pointed
out the biodiesel suffers from lower calorific value, lower power output and
increased NOx emission, despite having some advantages [15].
Sharma et al. (2008) recorded the latest aspects of development of
biodiesel. It was reported that the yield of biodiesel was affected by molar ratio,
moisture and water content, reaction temperature, stirring, specific gravity,
etc.. The authors have critically reviewed the biodegradability, kinetics
involved in the process of biodiesel production, and its stability. During the
review, emissions and performance of biodiesel have also been reported. The
authors felt that the edible oils are used extensively in developed nations such
as USA and European nations but developing nations are not self-sufficient in
the production of edible oils. It was concluded that the seeds of many plant
species remain unutilized for the production of biodiesel [16].
2.3. BIODIESEL PREPARATION METHODS
Past research works revealed that high viscosity, density, iodine value
and poor non volatility are the problems associated with the use of vegetable
oils in diesel engines leading to problems in pumping, atomization and
gumming, injector fouling, piston and ring sticking and contamination of
lubricating oils in the long run operations [17-19]. Hence it is essential to
reduce the viscosity of the vegetable oils by methods like preheating, thermal
cracking and transesterification. Peterson et al. (1983) reiterated that the two
major problems associated with the use of vegetable oils as fuels were oil
deterioration and incomplete combustion [20].
24
Bagby (1987) reiterated that the high viscosity of vegetable oils leads
to poor fuel atomization and inefficient mixing with air, which in turn contribute
to incomplete combustion [21]. Even though vegetable oils can be successfully
used in diesel engines, in long-term use, durability problems like nozzle
coking, carbon deposition in different parts of the engine and lubricating oil
dilution are encountered [22].
Considerable research has been carried out on vegetable oils as
substitute to diesel fuel, which includes rubber seed oil, cottonseed oil, palm
oil, soybean oil, sunflower oil, coconut oil, rapeseed oil, tung oil and others.
Many researchers investigated the different methods to overcome the
problems associated with the use of vegetable oils as diesel engine fuel i.e.
conversion in to biodiesel [23].
Dennis et al. (2010) reviewed the different approaches of reducing free
fatty acids in the raw oil and refinement of crude biodiesel that are adopted in
the industry. The authors described other new processes of biodiesel
production. It was concluded that with increasing concern over global warming,
it is foreseeable that biodiesel usage would continue to grow at a fast pace
which will trigger the development of more sophisticated methods of biodiesel
production to cope with the increasing market demand [24].
Gerpen (2005) has discussed the processing and production of
biodiesel. He observed that the reaction conditions involve a trade-off between
reaction time and temperature and most of the process complexity originates
from contaminants in the feedstock, such as water and free fatty acids, or
impurities in the final product, such as methanol, free glycerol, and soap. The
author has developed processes to produce biodiesel from high free fatty acid
feedstock, such as recycled restaurant grease, animal fats, and soap stock.
He has concluded that the biodiesel is an important new alternative
transportation fuel which can be produced from many vegetable oil or animal
fat feedstock [25].
25
(i) Micro emulsions
Pryde (1984) reported that micro emulsions could improve the spray
characteristics of the vegetable oils by explosive vaporization of the low boiling
constituents [26]. Ziejewski et al. (1984) prepared an emulsion of 53% (vol)
alkali-refined and winterized sunflower oil, 13.3% (vol) 190-proof ethanol and
33.4% (vol) 1-butanol. This nonionic emulsion had a viscosity of 6.31 cSt at
40°C, a cetane number of 25 and an ash content of less than 0.01%. Lower
viscosities, better spray patterns, no compromise in performance were
observed, but irregular injector needle sticking, heavy carbon deposits,
incomplete combustion and an increase of lubricating oil viscosity were also
resulted [27]. Lin and Wang (2004) studied the effects of combustion improver
on the engine performance and emission using three phase emulsions as fuel
[28]. Schwab et al. (1987) studied the effect of micro emulsions with solvents
such as methanol, ethanol and 1-butanol on the viscosity of vegetable oils for
use in engines [29].
(ii) Thermal cracking (pyrolysis)
Pyrolysis is the process of conversion of one substance into another by
means of heat or by heat with the aid of a catalyst. The pyrolyzed material can
be vegetable oils, animal fats, natural fatty acids and methyl esters of fatty
acids. The pyrolysis of fats has been investigated for more than 100 years,
especially in those areas of the world that lack deposits of petroleum [30].
Pyrolysis involves heating in the absence of air or oxygen and cleavage of
chemical bonds to yield small molecules [31].
Chang and Wan (1947) reported a large-scale thermal cracking of tung
oil calcium soaps. Tung oil was first saponified with lime and then thermally
cracked to yield a crude oil, which was refined to produce diesel fuel and small
amounts of gasoline and kerosene. 68 kg of the soap from the saponification
of tung oil produced 50 liters of crude oil [32]. Soybean oil was thermally
decomposed and distilled in air and nitrogen spared with a standard ASTM
distillation apparatus [33 & 34]. Billaud et al. (1995) pyrolyzed rapeseed oil to
26
produce a mixture of methyl esters in a tubular reactor between 500 °C and
850 °C [35].
(iii) Transesterification (Alcoholysis)
Transesterification is the process of converting a fat or vegetable oil
with an alcohol to form esters and glycerol. A catalyst is usually used to
improve the reaction rate and yield [36]. Methanol, ethanol, propanol, butanol
and amyl alcohol are some of the alcohols used in the transesterification
process. Methanol and ethanol are the most commonly used in this chemical
reaction. The reason is primarily due to its superior advantages of high
solubility in oil, fast reaction rate with triglycerides, good physical and chemical
properties, and low cost [37]. Zhang (1994) transesterified edible beef tallow
with a free fatty acid content of 0.27% [38]. Ma et al. (1998, 1999) have also
studied the transesterification process of beef tallow with methanol [39 & 40].
2.4. BIODIESEL PRODUCTION BY TRANSESTERIFICATION PROCESS
Demirbas (2003) carried out a detailed review on the production and
characterization of biodiesel and a review of various experimental works with
biodiesel. In this work, it was reported that the transesterification of
triglycerides by methanol, ethanol, propanol and butanol proved to be the most
promising process for converting the vegetable oils into biodiesels [41].
Ghadge and Raheman (2005) developed a technique to produce
biodiesel from mahua oil (Madhuca indica) with high free fatty acids (19%
FFA). The high FFA level of mahua oil was reduced to less than 1% by a two-
step pretreatment process. Each step was carried out with 0.30–0.35 v/v
methanol to oil ratio in the presence of 1% v/v H2SO4 as an acid catalyst in
1-hour reaction at 60°C. After the reaction, the mixture was allowed to settle
for an hour and methanol–water mixture that separated at the top was
removed. The second step product at the bottom was transesterified using
0.25-v/v methanol and 0.7% w/v KOH as alkaline catalyst to produce biodiesel.
27
The fuel properties of mahua biodiesel were comparable to those of diesel and
conforming to both the American and European standards [42].
Sanjib et al. (2005) prepared biodiesel from Pongamia Pinnata by
transesterification of the crude oil with methanol and KOH as the catalyst and
reported that properties such as viscosity, flash point compare well with
accepted biodiesel standards [43].
Burnwal and Sharma (2005) reported two different methods for
improvement in fuel properties (i) catalytic transesterification of triglycerides
with alcohols to form mono alkyl esters of long chain fatty acids (ii) the
supercritical method of producing biodiesel, which is quite similar to
hydrocarbon based diesel fuels [44].
Bala (2005) strongly insisted that although there are many ways and
procedure to convert vegetable oil into biodiesel, transesterification process
was found to be the most viable oil modification process [45].
Sreeprasath et al. (2006) applied Fe-Zn double metal cyanide (DMC)
complexes as solid acid catalysts in the preparation of fatty acid alkyl esters
(biodiesel / biolubricants) from vegetable oils. It is reported that unlike other
solid catalysts, the fe-zn DMC catalysts are highly active even for the
simultaneous transesterification of triglycerides and esterification of the free
fatty acids present in unrefined and waste cooking oils as well as non-edible
oils [46].
Sahoo et al. (2006) prepared biodiesel (Polanga oil methyl ester) from
polanga (calophyllum inophyllum) oil by triple stage transesterification process
[47]. Richard et al. (2006) prepared biodiesel through transesterification
process from beef tallow, a bi-product of meat production and processing
system and investigated the resource availability, energetic efficiency, and
economic feasibility of this biodiesel as a substitute to diesel [48].
28
He et al. (2007) prepared methyl esters (biodiesel) by the
transesterification of cottonseed oil with methanol in the presence of solid
acids as heterogeneous catalysts. The authors found that the methyl esters
yielded over 90% under the conditions of 230°C, reaction time of 8 h and
catalyst amount (catalyst/oil) of 2% (w) [49].
Demirbas (2008) conducted comparative studies on transesterification
methods. It was found that diesel is obtained from a chemical reaction called
transesterification (ester exchange) and the reaction converts esters from long
chain fatty acids into mono alkyl esters. The authors observed that the
vegetable oils can be transesterified by heating them with a large excess of
anhydrous methanol and an acidic or basic reagent as catalyst. They also
developed a non-catalytic biodiesel production route with supercritical
methanol which gives high yield due to the transesterification of triglycerides
and methyl esterification of fatty acids. The authors concluded that increasing
the reaction temperature to supercritical conditions had a favorable influence
on the yield of ester conversion [50].
Moser (2009) elaborated the process of biodiesel preparation, the types
of catalysts used in biodiesel production, the influence of free fatty acids on
biodiesel production and the use of different monohydric alcohols in the
preparation of biodiesel [51].
Lin et al. (2009) proposed fermentation, transesterification and
pyrolysis of biomass, industrial and domestic wastes as alternative solutions
for the increasing energy demand. The authors carried out the production of
biodiesel from RBO. Overall results from the study confirm that RBO may be
used as a resource to obtain biodiesel by a series of experiments. One of the
main conclusions derived from this study is that the high FFA level of crude
rice bran oil can be reduced to less than 0.5% in a two-step pretreatment
process of esterification using acid-catalyzed reaction with methanol [52].
Hanh (2009) studied the biodiesel production through
transesterification of triolein with various alcohols such as methanol, ethanol,
29
propanol, butanol, hexanol, octanol and decanol. It was recorded that the rate
of alkyl ester formation under the ultrasonic irradiation condition was higher
than that under the stirring condition. The authors confirmed that the rate
depended upon the kind of alcohols as the number of carbon in alcohol
increased, the rate of the ester formation tended to decrease [53].
Oliviera et al. (2010) investigated the production of biodiesel by
esterification with ethanol using waste oil generated in the refining of coconut
oil. During the study, methanol was also evaluated as an esterification agent
and conversions over 99 % mol were observed for both ethanol and methanol
[54].
Vieitez et al. (2010) investigated and compared the reaction
performance of soybean oil transesterification under supercritical methanol
and ethanol, in a continuous catalyst-free process, as a cleaner alternative to
conventional chemically catalyzed process. The authors performed reactions
in a tubular reactor, at 20 MPa, with oil to alcohol ratio of 1:40. The authors
concluded that both methanolysis and ethanolysis of refined soybean oil at
different temperatures can be conveniently performed in order to maximize the
alkyl ester content in the product and minimize the degradation of fatty acids
[55].
Mthiyazhagan and Ganapathy (2011) reviewed the factors involved in
transesterification reaction and recorded that biodiesel is a renewable
alternate fuel to diesel engines which can partially or fully replace or reduce
the use of petroleum diesel fuel and it can be produced from plant and animal
fats through transesterification reaction [56].
Chandra Deka (2012) synthesised biodiesel from Pithecellobium
monadelphum seed oil by transesterification with methanol and determined
the composition of the biodiesel by employing various instrumental
techniques. The chemical composition of biodiesel was determined by
GC-MS analysis [57].
30
2.5. OPTIMIZATION OF BIODIESEL PRODUCTION
The process of transforming sunflower oil into biodiesel through
transesterification process was optimized using Taguchi’s methodology. Three
times of stoichiometric quantity of methanol, 0.28% w/w of potassium
hydroxide, reaction temperature of 70 °C and two times washing process were
identified as the optimum set of parameters with maximum conversion rate
[58].
Prakash et al. (2006) optimized the transesterification parameters
reaction temperature, quantity of alcohol, amount of catalyst and reaction time
using Taguchi method. Methanol with KOH as base catalyst was used in the
experiments. 1.5 g of KOH, 45 ml of methanol, 80 °C of reaction temperature
and reaction time of 60 min were found to be the optimized data for 100 ml of
Pongamia Pinnata seed oil. The maximum contribution of 59.5% on the yield
was recorded for amount of methanol followed by the amount of catalyst with
32.66% [59].
Meher (2006), based on his investigation on optimization of alkali
catalyst methanolysis of Pongamia Pinnata oil, he has recorded 97 – 98% of
yield with 6:1 molar ratio of MeOH to oil, 65 °C temperature, and 360 rpm
stirring speed within two hours [60].
Alok Kumar Tiwari et al. (2007) could reduce the FFA level of raw
jatropha oil from 14% to less than 1% through pre-treatment with optimized
parameter values of methanol (0.28 v/v), H2SO4 as catalyst (1.43% v/v) in 88-
min reaction time at 60 °C temperature. In the second step transesterification,
optimized parameter values of methanol (0.16 v/v) and 24 min of reaction time
resulted in 99% yield [61].
Umer Rashid (2008) could achieve a biodiesel yield of 97.1% from
sunflower oil using alkali catalyzed methanolysis with the optimized parameter
values of 6:1 molar ratio of menthol to oil, reaction temperature of 60 °C and
31
1 wt % of catalyst amount. He has also concluded that among NaOH, KOH,
NaOCH3 and KOCH3, NaOH is the suitable catalyst [62].
Eevera et al. (2009) have done an extensive study on optimizing
process parameters such as amount of methanol, amount of sodium
hydroxide, reaction time and reaction temperature for both edible and non-
edible oils. Coconut oil, palm oil, groundnut oil, rice bran oil and gingelly oil are
edible in nature and Pongamia, cotton seed oil and neem oil are non-edible
oils considered for the study. Traditional optimization method was adapted in
this study. The optimal value of each parameter was obtained by considering
other parameters at constant level. After optimal value of each parameter was
attained, those parameters were used for other parameter optimization. Out of
five levels of each variables, 1.5 wt % of catalyst, 90 min of reaction time, 210
ml of alcohol and 50 °C of reaction temperature were obtained as the optimal
values for different oil types [63].
Kyong-Hwan Chung et al. (2009) recorded that the optimum parameter
values of KOH 0.5% wt, 6:1 molar ratio of methanol to duck tallow and 3 hours
of reaction time for the yield of 97% biodiesel from duck tallow, with no
significant influence from reaction temperature [64]. Prafulla and Shuguang
(2009) optimized the transesterification process parameters for some of the
edible and non-edible vegetable oils and reported a biodiesel yield of about
90–95% for Jatropha, 80–85% for Pongamia, 80–95% for canola, and 85–96%
for corn using potassium hydroxide (KOH) as catalyst [65].
Nakpong and Wootthikanokkhan (2010) used coconut oil with 12.8%
free fatty acid (FFA) as a feedstock to produce biodiesel by a two-step
process. The authors studied the effect of parameters related to these
processes and optimized the parameters of methanol-to-oil ratio, catalyst
concentration, reaction temperature, and reaction time. Methyl ester content
of the coconut biodiesel was determined by GC to be 98.4% under the
optimum condition. It was concluded that the viscosity of coconut biodiesel
product was very close to that of Thai petroleum diesel and other measured
properties met the Thai biodiesel (B100) specification [66].
32
The utility of non-edible moringa oleifera oil for biodiesel production was
studied by Kafuku and Mbarawa (2010). The single step transesterification
process using base catalyst was adopted for biodiesel production based on
the acid value of oil which was found to be 0.6% (<2.5%). Five most influencing
process parameters such as catalyst amount, methanol to oil ratio, reaction
time, reaction temperature and agitation speed were considered for
optimization process. Each parameter was varied with five levels. For
identifying the effect of one parameter on end effect, other parameters were
kept constant. At the end of the study, 1% (wt) of catalyst amount, methanol
quantity of 30% (wt), 60 °C reaction temperature, 60 min of reaction time and
400 rpm of agitation speed were identified as the optimum results with 82% of
conversion efficiency [67].
Sun Tae Kim et al. (2010) adopted Taguchi method for optimization of
process parameters for Rapeseed methyl ester production. It was reported
that, 96.7% yield of biodiesel was achieved using Potassium hydroxide as the
catalyst, 1.5 Wt% catalyst concentration and 60 °C of reaction temperature as
optimized parameters values [68].
Biodiesel production optimization from camelina seed oil using
orthogonal experimental design has been carried out by Xuan Wu (2011).
Methanol quantity, reaction time, reaction temperature and catalyst
concentration were the four major parameters considered for optimization
process. Catalyst concentration was identified as the most significant factor
affecting the biodiesel yield followed by reaction time, reaction temperature
and methanol to oil ratio. 95.8% of biodiesel yield was achieved under the
optimum conditions of 8:1 methanol to oil ratio, 70 min reaction time, 50 °C of
reaction temperature and 1% (wt) of catalyst [69].
Optimization of process parameters of two stage esterification process
using design of experiments for high fatty acid rubber seed oil has been
studied by Edwin Raj et al. (2011). The optimization problem was aimed at
reducing the acid value in the first stage esterification process and maximizing
the methyl ester yield in in second stage transesterification process. H2SO4
33
and NaOH were used as catalyst in first and second stage process
respectively. Multi variant approach called response surface design was used
in this study, as it took in to account of interaction effect between the variables.
The minimum acid value at the end of the first stage esterification optimization
was 3.8 mg KOH/g. Maximum methyl ester yield of 97.1% was attained with
the following optimum set of variables: 0.2% (v/v) methanol to oil ratio, 0.5%
(w/v) NaOH at 51.23 °C temperature and at 82.52 min time [70].
2.6. DIESEL ENGINE FUELLED WITH BIODIESEL AND ITS DIESEL
BLENDS
Dorado et al. (2003) analysed the exhaust emissions characteristics of
a direct injection diesel engine fuelled with methyl ester of waste olive oil. The
results revealed 58.9% reduction in CO emission, upto 8.6 % reduction in CO2
emission, upto 57.7% reduction in SOx with slight increase in brake specific
fuel consumption and NOx emission [71].
Ramadhas et al. (2005) derived biodiesel from high free fatty acid
Rubber seed oil, through two step transesterification and successfully used
Rubber seed oil methyl ester as fuel in diesel engine with a notable increase
in brake thermal efficiency and decrease in fuel consumption [72].
Sukumar Puhan et al. (2005) produced biodiesel from mahua oil by
transesterification using sulfuric acid (H2SO4) as catalyst and ethanol as
alcohol, conducted an experimental investigation on a 4-stroke direct injection
natural aspirated diesel engine at a rated speed of 1500 rpm with different
brake mean effective pressures and reported that Mahua oil ethyl ester
produced, brake thermal efficiency at par with diesel and improved emissions
in comparison with diesel [73].
Lin and Lin (2006) compared the performance, combustion and
emission characteristics of a diesel engine fuelled with biodiesel from soybean
oil, produced with and without peroxidation process. The results showed that
the fuel consumption rate, brake thermal efficiency, equivalence ratio and
34
exhaust gas temperature were higher while emissions of CO2, CO and NOx
were lower for fuel produced with peroxidation process [74].
Sahoo et al. (2007) prepared biodiesel from high free fatty acid (44 mg
KOH/gm) polanga oil through three stage transesterification process and
successfully tested an unmodified diesel engine fuelled with 100% polanga oil
methyl ester with 0.1% improved thermal efficiency, 3.5% reduction in smoke
emission and 4% reduction in NOx emission in comparison with diesel at full
load [75].
Canakci (2007) compared the combustion characteristics of soybean
biodiesel with two different petroleum diesels at steady state conditions in a
four cylinder turbocharged diesel engine at full load with a rated speed of 1400
rpm. It was reported that use of biodiesel resulted in 11.2% increase in NOx
with a significant reduction in PM, CO and UBHC emissions and with 11.8%
increase in bsfc in comparison with petroleum diesel [76].
Karthikeyan and Mahalakshmi (2007) investigated the feasibility of use
of a new bio-oil, turpentine derived from the resin of pine tree as a fuel in a
dual fuel engine. The study ascertained the possibility of 60–65% replacement
of diesel with turpentine within 75% load with better engine performance and
better emissions except CO and UBHC [77].
Ejas (2008) through an extensive literature review made a general
comment that 20% blending of biodiesel with diesel could be a better fuel for
long run diesel engine applications without any engine modifications [78].
Srivastava and Madhumita (2008) tested methyl esters of Karanja oil in
a direct injection diesel engine and recorded a small reduction in thermal
efficiency with the corresponding increase in brake specific fuel consumption
and increased emissions of CO, HC and NOx [79].
Sureshkumar et al. (2008) carried out an experimental investigation in
an unmodified diesel engine fuelled with Pongamia Pinnata methyl ester
35
(PPME) and ascertained that, the blends of PPME with diesel up to 40% by
volume (B40) provide better engine performance in terms of brake specific fuel
consumption (BSFC) and brake specific energy consumption (BSEC) and
improved emission characteristics [80].
Godiganur et al. (2009) carried out an experimental investigation on a
Cummins 158 HP rated power, turbocharged heavy duty diesel engine fuelled
with mahua oil methyl ester and its diesel blends and reported that 20%
blending of mahua oil methyl ester with diesel could be suitable alternative fuel
for heavy-duty engines with performance and emissions at par with diesel [81].
Baiju et al. (2009) produced methyl and ethyl esters from Pongamia
Pinnata oil and tested in a compression ignition engine with several diesel
blends. They had reported that methyl ester showed better performance and
emission characteristics than that of ethyl ester of Pongamia oil and 10 – 25%
increase in NOx emission was noted for both biodiesel in comparison with
diesel at part loads [82].
Devan and Mahalakshmi (2009) used blends of paradise oil methyl
ester and eucalyptus oil as a total replacement for diesel to run an unmodified
CI engine and successfully reported that 49% reduction in smoke, 34.5%
reduction in HC emission, 37% reduction in CO emission and 2.7% increase
in NOx emission with 2.4% increase in brake thermal efficiency for 50% (v/v)
blend of both oils at full load condition [83].
Nurun et al. (2009) used cotton seed oil methyl ester to run a CI engine
and reiterated that 10% addition of the biodiesel with diesel resulted in 24%
reduction in particulate matters and 14% reduction in smoke emissions as
compared to diesel. They also experienced that 30% addition of biodiesel
resulted in 24% reduction in CO emission and 10% increased NOx emission
[84].
Sahoo et al. (2009) produced methyl esters from three different non
edible oils namely Jatropha, Karanja and Polanga and tested them in a three
36
cylinder water cooled tractor engine. Nine different test fuels were produced
with 20%, 50% and 100% blends of each biodiesel with diesel and the results
were compared with diesel. It was reported that the maximum increase in
power was observed for 50% jatropha biodiesel and diesel blend at the rated
speed [85].
Purushothaman and Nagarajan (2009) examined the performance,
emission and combustion characteristics of a single cylinder, constant speed,
direct injection diesel engine fuelled with raw orange oil and compared the
results with standard diesel. It was concluded that use of orange oil resulted
in better performance and combustion characteristics with reduced CO and
HC emissions and increased NOx emission as compared to diesel [86].
Haldar et al. (2009) had produced alternative fuels form three different
non edible oils namely Putranjiva, Jatropha and Karanja through a new
chemical process called degumming and conducted an experimental
investigation on a diesel engine. The results confirmed the improved
performance and emission characteristics produced by Jatropha oil in
comparison with other fuels [87].
Aydin and Ilkilic (2010) studied the effect of ethanol as an additive to
biodiesel for unmodified diesel engines applications. The results confirmed
that 20% addition of ethanol with 80% biodiesel produced improved
performance with reduced emissions in comparison with biodiesel diesel blend
B20 [88].
Jindal et al. (2010) tested a diesel engine fuelled with 100% Jatropha
methyl ester and concluded that a compression ratio of 18 and injection
pressure of 250 bar were the optimum working conditions to run the engine
without any compromise on engine performance and emission characteristics
[89].
Panwar et al. (2010) confirmed the possibility of use of methyl esters of
caster seed oil (derived through transesterification using KOH as catalyst) as
37
fuel in a diesel engine. The experimental investigation revealed that test fuels
with lower biodiesel content produced improved brake thermal efficiency with
reduced fuel consumption [90].
Rao (2011) investigated the combustion and NOx emission
characteristics of Pongamia Pinnata methyl ester fuelled naturally aspirated,
single cylinder, four-stroke, stationary, water cooled, rated speed, direct
injection diesel engine and also studied the effect of preheating of the biodiesel
and compared the results with diesel. It was recorded that the peak pressure
and net heat release were slightly high for biodiesel against diesel and
preheated biodiesel. Decreased peak cylinder pressure for preheated methyl
ester was noted due to late injection and faster evaporation of the fuel. The
emission of NOx at full load for Pongamia Pinnata methyl ester was increased
by 6% and a significant reduction was noted for preheated biodiesel [91].
Jinlin Xue et al. (2011) concluded through the extensive literature
review that a slight power loss, increase in fuel consumption and increase in
NOx emission along with a significant reduction in PM, HC and CO emissions
were recorded for biodiesel and diesel blends in CI engine. It was ascertained
that use of biodiesel in an unmodified diesel engine applications favours
engine durability through reduced carbon deposits on key engine parts and
blending of biodiesel with diesel in smaller proportions could be a solution for
air pollution and diesel scarcity [92].
Breda (2011) through numerical and experimental investigations on a
Rape seed oil methyl ester fuelled diesel engine, reported an advancement in
injection timing and increase in injection pressure, due to high density, high
viscosity and high bulk modulus of the biodiesel. Also a slight increase in NOx
emission with substantial reduction in smoke and CO emission, due to higher
injection pressure and higher oxygen content were noted [93].
Muralidharan and Vasudevan (2009) investigated the effect of variation
of compression ratio on fuel consumption, combustion pressures and exhaust
gas emissions of an unmodified diesel engine fuelled with the methyl esters of
38
waste cooking oil and compared with diesel. The result revealed that, at high
compression ratio, the waste cooking oil methyl ester recorded the maximum
rate of pressure rise, longer ignition delay, higher mass fraction burnt and
lower heat release rate in comparison with diesel [94].
2.7. COMMENTS ON EARLIER WORKS
An exhaustive literature review has been carried out with the following
conclusions.
Biodiesel has been derived from many different vegetable oils and so
far no body across the world has tried to extract it from Manilkara zapota
seed oil. MZO based biodiesel research has not been reported in any
literature so far.
Transesterification is the most suitable process to convert the vegetable
oils in to biodiesel.
Taguchi method is the most widely used one for the optimization of
transesterification process parameters influencing the biodiesel yield.
Biodiesel derived from all vegetable oils and their blends with petro-
diesel could be successfully used as fuel to run CI engine without any
modification.
2.8. PRESENT WORK
The objective of the present work is to study the suitability of a new third
generation biodiesel resource Manilkara zapota seed oil, optimization of
biodiesel production from that resource and studies on its diesel engine
application. In order to accomplish the above objective, this investigation has
been divided into three major parts.
In the first part, the Manilkara zapota seed oil is completely characterized
and its suitability for biodiesel production based on its fatty acid profile
and physicochemical properties was studied.
39
In the second part, the optimization of key transesterification process
parameters for maximum biodiesel yield has been done using Taguchi
experimental design.
In the third part the combustion, performance and emission
characteristics of an unmodified diesel engine fuelled with new biodiesel
and its diesel blends have been studied.
40
3. OIL EXTRACTION AND CHARACTERIZATION
3.1. GENERAL
Raw oil characteristics of any biodiesel feed stock is very much
essential for selection of appropriate production process, process parameters
and other raw materials. More over suitability of raw oil, for a good quality
biodiesel production purely depends on its physiochemical properties and
fatty acid composition. Hence, an extensive study on the raw oil
characterization is one of the prime steps in any new biodiesel development.
This chapter describes about the collection and preparation of Manilkara
Zapota (L) seeds, extraction of oil, methods of determining physicochemical
properties and chromatogram analysis of raw oil.
3.2. COLLECTION AND PREPARATION OF MANILKARA ZAPOTA
SEEDS
Since it is a very new feed stock for biodiesel (not yet reported) and
Manilkara Zapota seeds are not used for any other major purpose other than
seedling, Manilkara Zapota seeds are not commercially available. The
required amount of seeds were collected from the local fruit market in
Chennai, India. Collected seeds were washed using clean water to remove
the sticky fruit pulps. After washing, seeds were dried in direct sunlight for
nearly 24 hours for the easy removal of the shells from the seeds. The black
or brown colour shells were removed manually from the dry seeds. Shells
may possess approximately 30 to 40 % weight of total seed weight. After
removal of shell, the fresh kernel or seeds were again dried in direct sunlight
for about 48 hours to remove the moisture content. Fresh Manilkara zapota
seeds may have 10 to 15 % moisture content in it. Figure 3.1 shows the
photographic views of Manilkara zapota seeds, removed shells and kernels.
41
(a) (b) (c)
Figure 3.1: Photographic view of (a) Sample seeds (b) Removed shells
(c) Kernels
3.3. OIL EXTRACTION
Oil can be extracted from the seeds in many ways like extraction using
mechanical presses, solvent extraction using chemicals and extraction using
screw expellers etc.. Out of these, extraction using screw expeller is very
economical and best suitable for batch type process. Heavy mechanical
presses are used for high capacity and continuous oil extraction. Solvent
extraction is suitable for laboratory scale production and is not economical. In
this research work, screw type mechanical expeller manufactured by
M/s. Rajkumar Agro Engineers private limited, Pune India was used to
extract the oil from seeds. Dry seeds were gradually fed in to the hopper to
reach the press. Seeds were squeezed inside the press by a pair of powerful
pressing screws operated by a motor and gear box. The screw is operated at
medium speed around 100 rpm for better performance. If the screws are
operated at high speed, seeds and oil cake will be heated up quickly and
jammed inside the expeller. Schematic diagram and photographic view of the
screw expeller used in this research are shown in Figures 3.2 and 3.3
respectively.
Extracted oil was filtered using a fine mesh filter to remove the solid
wastes and de-oiled cake from it. Then the oil was heated up to 60ºC for
42
about one hour to remove the moisture content. Moisture content in the raw
oil is detrimental for biodiesel yield through transesterification process.
Moisture content reacts with methanol and catalyst in the reaction and affects
the biodiesel yield. The oil is ready for biodiesel production with any further
pre-treatment.
Figure 3.2: Schematic diagram of screw expeller
Figure 3.3: Photographic view of screw expeller
43
3.4. MEASUREMENT PROCEDURE FOR PHYSICOCHEMICAL
PROPERTIES OF MANILKARA ZAPOTA SEED OIL
The various important properties of the raw oil were estimated and
tabulated. Kinematic viscosity was measured at 40°C using a Brookfield
DV-II Pro viscometer as per the procedure of ASTM D 445. The pour point
and the cloud point were simultaneously estimated in accordance with
standards ASTM D 5949 and ASTM D 5773 respectively. Flash point was
measured using Pensky Martene open cup apparatus. Heating value was
determined with the use of Parr – 6772 bomb calorimeter. Density at 15°C
was measured using a Rudolph DDM 2909 Automatic Density Meter. The
values of iodine number and cetane number were calculated as per the
standards of ASTM. The acid value was determined using a suitable titration
with standardized KOH solution with phenolphthalein as the indicator.
3.5. GAS CHROMATOGRAPH SYSTEM
Fatty acid compositions of MZO and MZME were measured using a
gas chromatograph instrument facilitated with mass spectrum. The study of
the separation of mixtures of any chemical or oil or fat is known as
chromatography which is often used to identify unknown components in a
mixture. In chromatography, the components in a mixture move along a
stationary phase. Each component in a mixture moves at a rate based on its
own characteristics and properties. Mixture to be separated is passed into
the mobile phase through the stationary phase to achieve separation of the
individual component in a mixture using the rate of migration. The mobile
phase flow rate (RF) across the separation medium is measured in ml/min or
μl/min.
The most commonly used chromatographic techniques are Gas
Chromatography (GC), Column Planer Chromatography (CPC), High
performance liquid chromatography (HPLC), Size exclusion chromatography
(SEC), Super critical fluid chromatography and Ion exchange
chromatography. There are other rarely used chromatographic methods for
44
very specific applications such as simulated moving bed chromatography,
Reverse phase column chromatography, Pyrolysis gas chromatography,
Two-dimensional chromatography, etc..
Gas-liquid chromatography (GLC) is a special chromatography
method used in biodiesel applications. In this method, a gaseous mobile
phase and an immobilized liquid phase on the surface of an inert solid are
used for the separation of mixtures. The action of continuously adding fresh
mobile phase through a column for washing anlytes is called elution which is
used for mixture separation. The compound in a mixture which has retained
strongly by the stationary phase will spend small fraction of time in the mobile
phase and further slowly moving with the mobile phase flow. This retention of
the component which has longer retention time will show the peak in
chromatogram. The interaction of component and stationary phase will
depend on the structure and boiling point of each compound. Hydrogen,
Helium, Argon, and Nitrogen are some of the inert gases used in gaseous
mobile phase.
Flame-ionization detector (FID) and mass spectrometric detector
(MSD) are the two popular and widely used detectors in gas
chromatography. The flame-ionization detector (FID) is most widely used for
quantification purposes. In this method the organic components are
pyrolyzed at the temperature produced by air-hydrogen flame to release ions
and electrons. An electrode located above the flame drives these ions and
electrons towards the detector. The variation in current caused by the
released ions and electrons is measured by a detector. The measured
current is directly proportional to the released number of ions and electrons
and mass of the compound in the mixture.
A mass spectrometric detector (MSD) attached gas chromatography is
known as GC-MS. It is a powerful tool to identify the components in a
mixture. In GC-MS, a compound in a mixture is first converted into ionic
fragments, and then the total number of ions are detected and plotted versus
45
time. A mass spectrum of selected ions obtained during a chromatographic
run is known as mass chromatogram.
3.6. MEASUREMENT PROCEDURE FOR FATTY ACID COMPOSITION
OF MANILKARA ZAPOTA SEED OIL
Fatty acid compositions were measured using Perkin-Elmer Clarus
500 Auto System XL Gas Chromatograph equipped with Elite series PE - 5
capillary column of dimension 30 m x 0.25 mm x 1 μm. The oven
temperature was initially held at 100°C for 10 min, increased to 200°C at the
rate of 10°C/min and then held for 10 min. The injector, source and the
transfer line temperatures were 220°C, 200°C and 200°C respectively. DB-1
(100% dimethylpolysiloxane) column with Helium as carrier gas at a flow rate
of 1 ml/min was used. The equipment is equipped with mass spectrometer of
Turbo EI Ionization source of 70 eV electron energy and ion energy of 1.5 V.
The samples were injected in split mode as 10:1. Mass spectral scan range
was set at 45-450 (m/z). FAME identification was carried out using NIST
Ver.2.1 MS data library.
46
4. OPTIMIZATION OF BIODIESEL PRODUCTION AND ITS
CHARACTERIZATION
4.1. GENERAL
There are several methods for biodiesel production; out of which
transesterification is a very simple and economical process for batch type
biodiesel production. During transesterification process the percentage yield
of biodiesel is affected by several parameters. Some of these parameters
strongly influence the biodiesel yield and others have little influence on yield.
Identification of the highly influencing parameter and how much it contributes
in the percentage yield of biodiesel is one of the important steps in new
biodiesel development. Experimental identification of the influencing
parameters and their contribution level is very difficult. Also conducting such
numerous number of experiments with some repetition for accuracy and
precision is highly time consuming and laborious. Hence in the present
research, it was proposed to adopt Taguchi’s experimental design for
conducting minimum number of experiments to optimize the
transesterification process parameters for maximum biodiesel yield. The
transesterification procedure, chemicals used, experimental setup used for
biodiesel production and procedure followed in Taguchi experimental design
and the related statistical analysis are discussed in detail in this chapter.
4.2. TRANSESTERIFICATION PROCEDURE
The type of transesterification process to convert a vegetable oil into
the corresponding biodiesel depends upon the free fatty acid (FFA) content
of the raw vegetable oil. If the FFA content of the oil is less than 2.5%, then
one step transesterification process with a base catalyst should be used and
if it exceeds 2.5%, two step transesterification process should be the choice.
In this study as the FFA content of MZO was 1.86%, single step base
catalyst transesterification method has been adopted.
47
100 g (± 0.1) of MZO was placed in a four-necked batch reactor and
heated to the required temperature. The stirrer speed was maintained at 500
rpm for constant mixing. The methoxide solution was prepared by dissolving
the exactly measured quantity of solid catalyst (KOH) in premeasured
quantity of methanol. Once the oil reached the required temperature, the
prepared methoxide was slowly poured in to the reactor. The completion of
pouring instant was taken as the start of reaction. The condenser was
installed on one of the four necks to capture and reuse any methanol vapour
formation. Figure 4.1 shows the chemical kinetics of transesterification
process. The four major influencing parameters considered for optimization
and testing in the transesterification process are molar ratio of methanol to
oil, time of reaction, temperature of reaction, and concentration of catalyst.
H2C
HC
O
O
H2CO
C
C
C
O
O
O
(CH2)n
(CH2)n
(CH2)n
CH3
CH3
CH3
+ 3 CH3OH
H2C
HC
OH
OH
H2COH
C
O
(CH2)n CH3H3CO+ 3
triglyceride in
vegetable oilmethanol glycerol methyl ester of fatty acid
"biodiesel"
Figure 4.1: Transesterification reaction
Upon reaching the predefined time of reaction, the reactor was taken
out of the heating mantle and the products of the reaction were shifted to a
500 ml separating conical funnel. After 24 hours of settling, the heavy
glycerol layer settled at the bottom of the funnel was removed through a
drainage valve. The remaining crude biodiesel produced from MZO was
gently washed with distilled water at 40°C in order to remove the unreacted
methanol, catalysts and impurities. The percentage yield of biodiesel has
been calculated using the formula given in equation 4.1.
𝑩 𝒚 % : 𝒀 = 𝒂 𝒚 𝒂 𝒂 × (4.1)
48
The step by step procedure followed in the production of biodiesel
from Manilkara zapota seed oil through transesterification process is shown
in Figure 4.2. The biodiesel produced under optimal condition was analyzed.
ASTM specifications were followed to determine the properties of MZME and
the estimated properties have been compared with EN14214 biodiesel
standards.
Figure 4.2: Process flow chart for biodiesel production from Manilkara
zapota seed oil
Transesterification using base catalyst
Phase separation
Crude biodiesel
Purification using distilled water
Pure biodiesel
Crude glycerol
Manilkara Zapota seed oil MZO
Pre-treatment
Titration
FFA ≤ 2.5% FFA > 2.5%
Esterification using acid catalyst
KOH
Methanol
Methoxide solution
49
4.3. CHEMICALS AND EXPERIMENTAL SETUP
Analytical grade methanol of 99.9 % purity and potassium hydroxide in
pellet form of purity above 85% were used for the production of biodiesel
through transesterification process. The experimental setup consists of a
half-litre four-necked batch type spherical glass reactor, with a water-cooled
condenser installed in one of the necks to capture and reuse any methanol
vapour formed. A speed controllable mechanical stirrer equipped with glass
rod and Teflon stirrer was used for precise control of stirring speed. A
temperature controllable heating mantle was used for heating the reactor. A
thermometer was installed in one of the necks to monitor the temperature
during the experiment. The schematic diagram and photographic views of the
batch type transesterification reactor used in the study are shown in
Figure 4.3 and Figure 4.4 respectively.
Figure 4.3: Schematic diagram of the batch type transesterification
reactor
50
(a) During Transesterification (b) During Settling
(c) After settling
Figure 4.4: Photographic views of transesterification setup
51
4.4. DESIGN OF EXPERIMENTS USING TAGUCHI METHOD
4.4.1. Introduction to Orthogonal Array design
In the orthogonal array design, understanding of two vital terms
namely factor and level is essential. Factor refers to the independent variable
which has effects on the dependent variable. Level refers to a variable
increment of the factor. Every factor is set up with different levels in the
orthogonal array design. It is like gridding in a net. Consider an example case
with three factors and three levels. It can be expressed as a cube with
gridding the total of 27 points as shown in Figure 4.5.
Full-scale test takes all the 27 points. If several levels and factors are
adopted, the full-scale test will be laborious and time-consuming. Therefore,
the orthogonal array design selects some representative points (the
combination of factors and levels) for the experiments. All the representative
combinations are distributed uniformly in the research area as shown as red
points in Figure 4.5 and can greatly reflect the situation of the whole selected
examined area. As mentioned earlier, the power of an orthogonal array is the
ability to evaluate several factors in a minimum number of tests. This method
is efficient, as much information can be obtained from a few trials.
Figure 4.5: Equilibrium distribution stereogram of L9 orthogonal array
design
52
4.4.2. Properties of an orthogonal array
The orthogonal array has the following special features that reduce the
number of experiments to be conducted.
First property is called balancing property. All level settings under
each independent variable appear equal number of times in a column.
All the level values of independent variables are used for conducting
the experiments.
The sequence of level values for conducting the experiments shall not
be changed. This means one cannot conduct experiment 1 with
variable 1 at level 2 and experiment 4 with variable 1 at level 1. The
reason for this is that the array of each factor column is mutually
orthogonal to any other column of level values. The inner product of
vectors corresponding to weights is zero.
4.4.3. Selection of control parameters and their levels
Among the different parameters influencing the production yield of
biodiesel such as reaction temperature, time for reaction, type of alcohol and
its quantity, type of catalyst and its concentration, agitation or stirring speed,
quality of the reactants and moisture content in the oil, only the four most
influencing parameters and three levels were considered in this study. Table
4.1 shows the chosen four most influencing parameters affecting the yield of
biodiesel in transesterification process and their levels.
Table 4.1: Chosen parameters and their levels
Parameters Levels
1 2 3
A Methanol to Oil (Molar ratio) 4:1 6:1 8:1
B Concentration of catalyst (Wt. %) 0.5 1 1.5
C Time of reaction (min) 60 90 120
D Temperature of Reaction (°C) 50 60 70
53
4.4.4. Selection of orthogonal array and assignment of the variables
As four parameters and three levels were considered for the
optimization of biodiesel production in this research work (L = 3, P = 4 as
shown in Table 4.1), the minimum number of experiments to be conducted
has been computed as 9. From the OA selector L9 orthogonal array has been
chosen as the best suitable OA and the four parameters and their levels for
each experiment were assigned in the corresponding rows as shown in
Table 4.2. Each experiment has been repeated thrice in order to minimize
errors.
Table 4.2: L9 orthogonal array for four parameters at three levels
Experiment no.
Parameters and their levels
Methanol / Oil (Molar ratio)
Concentration of catalyst
(Wt %)
Time for reaction
(min)
Reaction Temperature
(°C)
1 4:1 0.5 60 50
2 4:1 1.0 90 60
3 4:1 1.5 120 70
4 6:1 0.5 90 70
5 6:1 1.0 120 50
6 6:1 1.5 60 60
7 8:1 0.5 120 60
8 8:1 1.0 60 70
9 8:1 1.5 90 50
4.4.5. Signal to noise ratio (SNR)
In Taguchi method SNR is used to calculate the extent of deviation of
quality function from the expected value. There are three types of SNRs used
in Taguchi method depending upon the objective of the problem. They are
Larger-the-Better (LTB) for maximization problems, Smaller-the-Better (STB)
for minimization problem and Nominal-the-Best (NTB) for normalization
54
problems. The SNR (dB) for NTB, STB and LTB models can be calculated as
detailed below using equations 4.2 to 4.6.
𝑁 = (��2𝑠2 ) 𝑁 ℎ (4.2)
𝑁 = − (∑ 𝑦2𝑛𝑛= ) ℎ (4.3)
𝑁 = − 𝑛 (∑ 𝑦2𝑛= ) ℎ (4.4)
Where
= 𝑛 (∑ ,𝑛= ) (4.5)
= 𝑛− (∑ , − 𝑛= ) (4.6)
Where
− 𝐸 − − 𝑁
Accordingly the optimal level of control or design parameter will be the level
with the highest SNR.
4.4.6. Analysis of variance (ANOVA)
The optimal value of different factors can be easily determined by
SNR analysis. However, the SNR analysis cannot distinguish the reason why
the data of each factor level fluctuated differently. It might be caused by
experimental conditions or by experimental errors. Therefore, the
experimental error cannot be determined by SNR analysis. Moreover, SNR
55
cannot comprehensively evaluate the differences among the mean values
and indicate the magnitudes of the factor effects using the same standard.
Due to the limitations of SNR analysis, ANOVA analysis is necessary
for obtaining the magnitudes of the factor affecting the index. The statistically
significant process parameter was identified by conducting statistical analysis
of variance (ANOVA) of the response data and the optimum set of process
parameters was also identified. The most significant process parameter was
identified by calculating the percentage contribution of each parameter on the
biodiesel yield. The percentage of contribution was calculated by the
following equations 4.7 to 4.9.
% = 𝑇 × (4.7)
where SSi is the sum of the square for ith parameter and SST is the total sum
of the square of all parameters.
= ∑ [ 𝑁 𝐿 − 𝑁 ]= (4.8)
= ∑ = (4.9)
4.4.7. Prediction of maximum yield
The prediction of theoretical maximum yield of biodiesel (MZME)
under the optimum conditions can be calculated by using the equation 4.10.
𝐘𝐨 = 𝐍 𝐨𝟓 (4.10)
Where SNRo is the SN ratio under optimum conditions and Yo is the
theoretical optimum yield. In order to validate the percentage yield of MZME
correspond to optimal conditions predicted from this study, MZME was
prepared through transesterification process in three trials under the optimum
level of parameters.
56
5. ENGINE PERFORMANCE – AN EXPERIMENTAL INVESTIGATION
5.1. GENERAL
This chapter highlights the detailed description about the experimental
setup, experimental procedure and specifications of the various equipment
used in the experimental investigation to measure the various engine
performance characteristics such as brake thermal efficiency (BTE), brake
specific fuel consumption (BSFC), exhaust gas temperature (EGT),
combustion characteristics like pressure - crank angle (p-ϴ) diagram, rate of
heat release with crank angle and engine emission characteristics such as
CO, CO2, NOx and UBHC.
5.2. EXPERIMENTAL SETUP
The experimental setup of the present study includes a four stroke,
single cylinder, variable compression ratio (VCR) engine coupled with an
eddy current dynamometer. The instruments necessary to measure important
parameters such as airflow, crank angle, combustion pressure, fuel flow,
temperatures and load are also provided with the setup. The signal from the
various measuring instruments are directly interfaced to a computer through
a data acquisition system of high speed nature. In addition to the fuel tank, a
separate 5 litre capacity tank is attached to the engine for the bio-diesel and
its blends.
The flow of cooling water and calorimeter water can be easily
measured using the attached rotameters. This engine setup is capable of
enabling performance analysis of a VCR engine in terms of indicated power,
brake power, frictional power, indicated mean effective pressure, brake mean
effective pressure, specific fuel consumption, Air fuel ratio, volumetric
efficiency, mechanical efficiency, brake thermal efficiency, indicated thermal
efficiency, heat balance and combustion analysis. The engine performance
monitoring system can achieve most of its functions such as monitoring,
57
reporting, data entry and data logging through Lab view based state of the art
software.
Figure 5.1: Schematic representation of experimental setup
Figure 5.2: Photographic view of experimental setup
58
Schematic representation and photographic view of the experimental
engine setup are shown in Figure 5.1 and Figure 5.2 respectively. Table 5.1
provides the specifications of the test engine setup in detail. An analyzer of
exhaust gas, model AUTO 5-1 of make M/s Kane International Ltd., (UK) is
included in the experimental setup to measure the various emission
parameters. The detailed specifications of the analyzer used in this work are
given in Table 5.2.
Table 5.1: Test engine specification
Engine Single cylinder, 4 stroke, water cooled
Make Kirloskar
Stroke 110 mm
Bore 87.5 mm
Capacity 661 cc
Power 3.5 kW
Rated speed 1500 rpm
Compression Ratio range
12:1 to18:1
Injection variation 0- 25º BTDC
Dynamometer Eddy current, water cooled
Piezo sensor Combustion: Range 350Bar, Diesel line: Range 350 Bar,
Crank angle sensor Resolution 1 Deg, Speed 5500 RPM with TDC pulse.
Data acquisition device NI USB-6210, 16-bit, 250kS/s.
Temperature sensor Type K Thermocouple
Load sensor strain gauge type Load cell, range 0-50 Kg
59
Table 5.2: Exhaust Gas Analyzer Specifications
Parameter Range Principle of detection
Percentage uncertainty
CO 0–20% NDIR 0.2
UBHC 0–10,000ppm NDIR 0.2
NO 0–5000ppm Electro chemical 0.4
CO2 0–20% NDIR 0.2
NOx 0–5000ppm Electro chemical 0.4
5.3. EXPERIMENTAL PROCEDURE
A series of experimental trails were conducted with different test fuels,
under varying load conditions from no load to 100% rated full load, at the
rated constant speed of 1500 rpm. Even though the test engine is capable of
work in different compression ratios, 16:1 is the compression ratio used in
this experimental study with fuel injection at 23° before TDC. Each
experiment was conducted three times for better results. As there was slight
deviation among the values of different trials, the average value of the trials
has been taken into consideration. During every experimental trial, after
allowing the engine to attain the rated speed, key parameters pertaining to
engine performance such as time to consume 20 cm3 of fuel and the data
related to combustion analysis like pressure with crank angle were
automatically measured and stored in the computer using data acquisition
system. The parameter values pertaining to engine exhaust emission such as
CO, CO2, UBHC and NOx were also recorded from the online exhaust gas
analyzer.
60
6. RESULTS AND DISCUSSION
This chapter highlights the results of various investigations carried out
in respect of the new biodiesel resource MZO. The various results discussed
in this chapter are:
Characterisation of raw Manilkara zapota seed oil, describing the
physicochemical properties and fatty acid profile and percentage
content of fatty acids.
Optimization of transesterification process parameters using Taguchi
experimental design.
Characterisation (Fatty acid profile and physicochemical properties) of
biodiesel MZME produced with optimized set of transesterification
process parameters.
Combustion, performance and emission characteristics of a single
cylinder direct injection four stroke diesel engine fuelled with 100%
MZME and blends of MZME with diesel in varying proportions.
6.1. RAW OIL CHARACTERIZATION
6.1.1. Fatty acid profile of Manilkara zapota seed oil
The composition of fatty acid of MZO was determined by gas
chromatography analysis. The chromatogram of MZO sample is shown in
Figure 6.1. Crude MZO has been used for biodiesel production without any
refining process. Fatty acid composition of MZO has been studied to find its
suitability as feed stock for biodiesel production. Table 6.1 shows the
composition and the percentage weight content of different types of saturated
and unsaturated fatty acids of MZO. The highest content of unsaturated fatty
acid was found to be oleic acid (64.15%) followed by linoleic acid (17.92%).
Among saturated fatty acid content, palmitic acid tops the list with 13.27%
followed by stearic acid with 2.8%. The total unsaturated and saturated fatty
acid content of MZO were found to be 83.93% and 16.07% respectively.
61
Table 6.1: Composition of fatty acids of Manilkara zapota seed oil
Fatty acids Content (%) Molecular Weight
Saturated group
Palmitic acid (C16:0) 13.27 256.4
Stearic acid (C18:0) 2.80 284.5
Unsaturated group
Oleic acid (C18:1) 64.15 282.5
Linoleic acid (C18:2) 17.92 280.5
Linolenic acid (C18:3) 1.86 278.4
Figure 6.1: Chromatogram sample of Manilkara zapota seed oil
6.1.2. Physicochemical properties of Manilkara zapota seed oil
Major properties of MZO namely density, viscosity, acid value, peroxide
value, heating value, pour point, flash point, iodine value, pH, and cetane
number were estimated as per ASTM standards and reported in Table 6.2.
The molecular weight of MZO has been calculated as 873.95 g/mol. The
molecular weight of each fatty acid was first calculated by multiplying the
number of atoms and atomic weights of constituting atoms present in the
molecule. The average molecular weight of all constituent fatty acids (AMWFA)
62
was calculated by summing up the products of molecular weight of each fatty
acid and its constituent proportion in the total fatty acids content of the oil. As
the oil is a triglyceride containing three fatty acids and one glycerol, its
molecular weight is calculated using the relation
MW = 3*(AMWFA) + 38.049 (6.1)
where 38.049 is the weight of glycerol backbone.
Based on the FFA content of any raw oil, either one step
transesterification process or two step transesterification could be adopted. In
two step process, initially esterification can be done with methanol and
sulphuric acid to reduce the FFA content and then base catalyst
transesterification can be done. In this study, as the FFA content of the MZO
was found to be 1.86%, single step base catalyst transesterification method
has been adopted.
Table 6.2: Physicochemical properties of Manilkara zapota seed oil
Parameters Values
Density at 15°C (g/cm3) 0.887
Kinematic viscosity at 40°C (mm2/s) 34.75
Free fatty acid (% FFA as oleic acid) 1.89
Acid value (mg KOH/g) 3.79
Iodine value (g Iodine/100 g) 65.02
Peroxide value (g/kg O2) 269.54
Color Brownish yellow
Molecular weight (g/mol) 873.95
Percentage oil content in kernel (%) 23 – 30%
Physical state at room temperature Liquid
pH 3.5
Cloud point (°C) -1
Pour point (°C) -3
Flash point (°C) 243
Gross Heating value (MJ/kg) 35.9
63
6.1.3. Suitability of Manilkara zapota seed oil for biodiesel production
based on its fatty acid profile
Chain length, degree of unsaturation and branching of chain are the
three structural features that influence the physical properties of a fatty ester
molecule. Ignition quality, calorific value, cold flow property, oxidative stability,
viscosity, density, lubricity and exhaust emission are the various properties of
biodiesel influenced by fatty acid profile of the biodiesel. While selecting
vegetable oil for biodiesel production, it is very much essential to understand
the relationship between the fatty acid profile and physical properties, to get a
good quality biodiesel [95 & 96].
In order to improve the cold temperature flow characteristics of a
biodiesel, it is required to select a fuel with low saturated fatty acid level and at
the same time to reduce the NOx emission and to improve the oxidative
stability, an oil with low amount of mono unsaturated and poly unsaturated fatty
acids should be considered. In addition, the cetane number as a measure of
ignition quality is appreciably affected by increased unsaturation. As such no
specific fatty acid profile is available to satisfy the crucial biodiesel
requirements of flow characteristics at low temperature, oxidative stability,
cetane number, and NOx emission [95 & 96].
Viscosity, one of the major physical properties of the biodiesel increases
with increasing number of carbon atoms (chain length) in the chemical
structure. The degree of random intermolecular interactions increases with
increase in chain length. Viscosity increases with increasing degree of
saturation. Presence of one double bond in the chemical structure increases
the viscosity, whereas two or three double bond occurrence in structure
causes decrease in viscosity.
In addition to the above, viscosity is increased due to higher molecular
weight and presence of hydroxyl group in the molecule. It has been reported
that higher the saturation or longer the fatty acid chain, the more viscous is the
oil and faster in changing with temperature. The vegetable oils, owing to their
64
higher trans fatty acids (FAs) content and higher saturated FAs content have
high viscosity and oils with higher unsaturated FAs content possess lower
viscosity [95 – 98].
Density increases with decrease in chain length, increase in number of
double bonds and rich in unsaturated components. At the same time it
decreases with the presence of low density contaminants [99]. The lubricity of
the biodiesel fuel is better than that of petrodiesel fuel. Biodiesel with higher
unsaturated fatty acid content showed better lubricity than saturated species.
The cetane number (CN) is an elative measure of ignition delay of any fuel.
Higher the CN, the shorter the ignition delay and vice versa. Higher CN in turn
guarantee good cold start characteristics of biodiesel. For any bio based fuels,
CN reduces with decreasing chain length and increasing branching. At the
same time, it increases with presence of more saturated fatty acid components
such as palmitate and stearate and it is in medium range for the mono
unsaturated fatty acids [1, 100 – 101].
Heating value of the biodiesel is highly influenced by two factors, one is
energy content of the fatty acid methyl esters (FAMEs) and second is their
density. The unsaturated FAMEs have lower energy content; however their
density is high and hence they have more energy per unit volume [102].
From the above extensive discussion about the relationship between
fatty acid profile of the biodiesel and its physical properties, it is very clear that
a biodiesel with high mono unsaturated fatty acids such as oleate or
palmitoleate and low in both saturated and polyunsaturated fatty acids will be
the best fuel with all the required properties. Since transesterification process
will not alter the fatty acid composition of the feedstock, selection of feed stock
with the above conditions is very much essential. Manilkara zapota seed oil is
one such oil with high in mono unsaturated fatty acid (64.15% oleate) and low
in both saturated and poly unsaturated fatty acids, hence best suited for
biodiesel production.
65
6.2. OPTIMIZATION OF BIODIESEL PRODUCTION
6.2.1. Determination of optimal experimental condition by Taguchi
method
The percentage yield of methyl ester from raw MZO under the designed
nine set of experiments, their SNRs and overall mean SNR are tabulated in
Table 6.3. The results show that the experiment number 5 has the highest
mean yield of 93.6 % and experiment 7 has the lowest mean yield of 72.2 %.
Though the set of parameters correspond to experiment 5 has the highest
yield, this would not be the optimum set of parameters.
Table 6.3: Percentage of yield and SNR for the experiments
Experiment no.
A B C D
% of Yield Mean yield (%)
SNR Trail
1 Trail
2 Trail
3
1 4:1 0.5 60 50 70.8 78.4 77.6 75.6 37.57
2 4:1 1.0 90 60 83.5 87.8 85.6 85.6 38.65
3 4:1 1.5 120 70 83.3 77.8 79.5 80.2 38.08
4 6:1 0.5 90 70 82.4 81.8 75.2 79.8 38.04
5 6:1 1.0 120 50 94.4 91.8 94.6 93.6 39.43
6 6:1 1.5 60 60 84.5 93.4 87.0 88.3 38.92
7 8:1 0.5 120 60 70.1 74.4 72.2 72.2 37.17
8 8:1 1.0 60 70 81.4 84.3 85.3 83.7 38.45
9 8:1 1.5 90 50 87.2 82.8 85.6 85.2 38.61
Overall Mean SNRT 38.32
In Taguchi method SNR is used to calculate the extent of deviation of
quality function from the expected value. As the objective is to maximize the
percentage yield of MZME, LTB has been used to find the SNR (dB) as given
below.
66
𝑁 = − 𝑙 𝑔 𝑛 (∑ 𝑦2𝑛= ) (6.2)
In this relationship yi represents the yield of biodiesel and n is the number of
trials.
The level mean signal to noise ratio (SNRL), which is the algebraic mean
of all the SNRs of a particular control parameter at a specified level, has been
calculated and shown in table 6.4. In this experimental study, for parameter B
at level 1, SNRL has been found to be 37.59 using the values (37.57, 38.04
and 37.17) taken from experiment Nos. 1, 4 and 7 and at level 2, SNRL (38.84)
corresponding to the values (38.65, 39.43 and 38.45) taken from experiment
Nos. 2, 5 and 8 and so on. The SNRL, ΔSNR (difference in maximum SNRL to
minimum SNRL of particular parameter), and rank for all four parameters are
given in Table 6.4. The rank was given based on the value of ΔSNR. Higher
ΔSNR value was assigned rank 1. Based on the rank, the concentration of
catalyst has been identified as the most influencing parameter on the yield of
MZME. Molar ratio of methanol to oil and temperature of reaction are the
second and third influencing factors followed by time of reaction.
Table 6.4: SNRL, ΔSNR and Rank values
Levels
SNRL
Methanol / Oil (Molar ratio)
Concentration of catalyst
Time for reaction
Reaction Temperature
1 38.10 37.59 38.31 38.53
2 38.79 38.84 38.43 38.25
3 38.08 38.54 38.23 38.19
ΔSNR = (max-min)
0.72 1.25 0.21 0.34
Rank 2 1 4 3
The effects of each parameter at three different levels on MZME yield
in terms of SNRL are shown in Figure 6.2. A higher value of SNRL infers to a
greater influence of the particular parameter at that level. The maximum value
67
in each graph specifies the optimum level of that particular parameter on the
yield of MZME. Therefore, the optimum levels of each parameter for the
maximum yield of MZME were A (Molar ratio of methanol to oil) at level 2 (6:1),
B (concentration of catalyst) at level 2 (1%), C (time of reaction) at level 2 (90
min) and D (temperature of reaction) at level 1 (50ºC).
Figure 6.2: SNRL of each parameter at different levels
6.2.2. Identification of significant parameter and percentage of
contribution of each parameter
The most significant process parameter was identified by calculating the
percentage contribution of each parameter on the biodiesel yield. The
percentage of contribution was calculated by using the following equations.
% 𝑟𝑖 𝑖 = 𝑇 × (6.3)
321
39.0
38.5
38.0
37.5321
321
39.0
38.5
38.0
37.5
321
Methanol : oil molar ratio
Me
an
of S
N r
atio
s
Catalyst concentration
Reaction time Reaction Temperature
Signal-to-noise: Larger is better
68
where SSi is the sum of the square for ith parameter and SST is the total sum
of the square of all parameters.
= ∑ [ 𝑁 𝐿 − 𝑁 ]= (6.4)
= ∑ = (6.5)
The calculated SSi and % contribution are shown in Table 6.5. From the
contribution table it was observed that concentration of catalyst was the most
significant parameter followed by molar ratio of methanol to oil. The time of
reaction was the least influencing process parameter with 1.6 % contribution
followed by temperature of reaction.
Table 6.5: Percentage contribution of process parameters
Parameter SSi % contribution
Methanol / Oil (Molar ratio) 0.3269 25.85
Concentration of catalyst 0.8517 67.34
Time for reaction 0.0203 1.60
Reaction Temperature 0.0659 5.21
6.2.3. Prediction of maximum yield and its validation
The prediction of theoretical maximum yield of MZME under the
optimum conditions can be calculated by using the relation
Yo = N o5 (6.6)
where SNRo is the SN ratio under optimum conditions and Yo is the theoretical
optimum yield. SNRo is calculated using additive model as given below:
SNRo = SNRT + {(SNRLA2 – SNRT) + (SNRLB2 – SNRT) + (SNRLC2 – SNRT)
+ (SNRLD1 – SNRT)} (6.7)
69
where SNRLA2, SNRLB2, SNRLC2 and SNRLD1 are the level mean SNR at the
optimum level of each parameter.
The predicted theoretical yield of MZME under optimum conditions was
95.83%. In order to validate the percentage yield of MZME correspond to the
optimal conditions predicted from this study, biodiesel MZME was prepared
through transesterification process in three trials under the optimum level of
parameters. The results were 94.50%, 93.80% and 96.20% from trail 1, trail 2
and trail 3 respectively. The mean value of the three trails, 94.83% closely
matches with that of theoretical estimated value and the slight variation could
be due to the influence of extraneous variable.
6.3. CHARACTERIZATION OF MANILKARA ZAPOTA METHYL ESTER
6.3.1. Fatty acid profile of Manilkara zapota methyl ester
The weight percentage content of different fatty acid methyl esters of
MZME was determined from its chromatogram profile and the same has been
listed in Table 6.6. The molecular weight and chemical structure of each fatty
acid methyl ester are also given in Table 6.6. The major constituents of MZME
are methyl oleate, methyl linoleate and methyl palmitate with percentage
content of 62.9, 17.4, and 12.8 respectively. The chromatogram of MZME
sample is shown in Figure 6.3.
6.3.2. Physicochemical properties of Manilkara zapota methyl ester
Major properties of MZME namely density, viscosity, acid value,
peroxide value, heating value, pour point, flash point, iodine value, pH, and
cetane number were estimated using ASTM and EN standards and reported
in Table 6.7. All the above mentioned properties were compared with EN
14214 biodiesel standards. The results show that all the properties of MZME
are meeting the requirements of EN14214 biodiesel standards and hence
MZME could be a potential substitute to petrodiesel. The quality of atomization
of any liquid fuel in a pressurized fuel injection system is greatly influenced by
70
the fuel density. According to EN14214 standard, the value of biodiesel density
should be within the range of 0.86 to 0.9 g/cm3 for diesel engine applications.
It is found that the density of MZME is within the acceptable range.
Table 6.6: Composition of fatty acids of Manilkara zapota methyl ester
Methyl Ester Name Content (%) Molecular
Weight Chemical Formula
Methyl Laurate 0.5 214.3 C13H26O2
Methyl Myristate 1.3 242.4 C15H30O2
Methyl Palmitate 12.8 270.5 C17H34O2
Methyl Palmitoleate 0.3 268.4 C17H32O2
Methyl Stearate 2.4 298.5 C19H38O2
Methyl Oleate 62.9 296.5 C19H36O2
Methyl Linoleate 17.4 294.5 C19H34O2
Methyl Linolenate 1.2 292.5 C19H32O2
Methyl Nonadecanoate 0.6 312.5 C20H40O2
Methyl Arachidate 0.5 326.5 C21H42O2
Figure 6.3: Chromatogram sample of Manilkara zapota methyl ester
71
Viscosity of a liquid is the resistance offered against flow. Use of high
viscosity fuel results in low atomizing efficiency, low rate of fuel delivery,
leading to starting trouble and knocking in diesel engines. Low viscosity fuel
may not give the required lubrication to the injection system. The viscosity of
MZO was found to be 11.74 times that of diesel. After transesterification the
viscosity was greatly reduced to 1.57 times, which is well within the acceptable
range of biodiesel standards.
Iodine number of biodiesel is characterized by the number of double
bonds in it and is used to quantify the unsaturation level of biodiesel. It also
influences the stability of oxidation of biodiesel. The iodine number of MZME
is well below the specified limit. Acid value is the amount of base in terms of
mg of KOH essential to neutralize the acidic nature of any substance. It is the
quantitative measure of the carbolic acid group in a fatty acid or a mixture of
fatty acids. The acid value for MZO was 1.96. After transesterification the acid
value of MZME was reduced to 0.15 which is very much comparable to that of
diesel.
Peroxide value is the quantitative measure of oxidative rancidity of
unsaturated fats and oils. The double bonds present in fats and oils are
responsible for auto oxidation. Peroxides are the intermediates in oxidation
reaction. The amount of peroxide in an oil or fatty acid is the judging parameter
for the level of auto oxidation. This value for raw MZO was 269.54 and after
transesterification, it was reduced to 238.
When a vegetable oil or fuel is subjected to cooling, the temperature at
which bio wax in the oil forms a cloudy appearance is called cloud point and
with further cooling, the temperature at which the oil becomes semi solid state
and loses its flow characteristics is called pour point. These two are vital
parameters to measure the cold weather characteristics of any fuel. If the cloud
point and pour point are above 1ºC, they cause transportation problem as well
as fuel clog in the injection line and injectors. Both MZO and MZME satisfy the
above requirements.
72
Table 6.7: Properties of Manilkara zapota methyl ester in comparison
with biodiesel standard and diesel
Properties Units EN
14214 MZME Diesel Test method
Ester content % (m/m) Min 96.5 96.8 EN14103
Density at 15 °C g/cm3 0.86-0.90
0.875 0.861 ASTM D4052
Kinematic viscosity mm2/s 3.5 – 5 4.67 2.96 ASTM D445
Acid value mg KOH/g Max 0.50 0.15 0.18 ASTM D664
Iodine value g iodine/100 g Max 120 65.28 -- AOAC CD1-25
Pour point °C Max 0 - 6 -12 ASTM D97
Flash point °C Min 120 174 48 ASTM D93
Heating value MJ/kg Min 35 37.2 44.8 ASTM D240
Cetane number -- Min 51 52 51 ASTM D613
Sulphur content mg/kg Max 10 0 350 ASTM D5459
Monoglyceride content
%(m/m) Max 0.8 0.52 -- EN14105
Diglyceride content
%(m/m) Max 0.2 0.13 -- EN14105
Triglyceride content
%(m/m) Max 0.2 0.12 -- EN14105
Free glycerol content
%(m/m) Max 0.02 0.00 -- EN14105
Total glycerol %(m/m) Max 0.25 0.17 -- EN14105
Flash point is the minimum temperature at which a small flame passes
over the liquid surface causes a momentary flash due to the vapour ignition
caused by an external ignition source. It is used to measure the fire hazard
characteristics of liquid fuels. The flash point is actually different from
auto-ignition temperature and it does not have any relation to the performance
of engine. In the present study, the flash point of MZO was measured 1.4 times
greater than that of MZME and 5 times greater than that of commercial diesel.
It is evident from the comparison table that, all the properties of MZME are well
within the specified range of biodiesel standards.
73
6.4. ENGINE PERFORMANCE STUDY
6.4.1 Combustion characteristics
Variation of cylinder pressure with crank angle
The variation of cylinder pressure with crank angle for all the test fuels
at all load conditions is given in Figure 6.4 (a) to 6.4 (f). From the figures it is
clear that, all the test fuels follow the similar trend as that of diesel. The highest
peak pressure is recorded for the blend B50 followed by B25 and diesel. It is
clear from the graphs that the attainment of peak cylinder pressure is in the
range of 8° to 9° CA, ATDC for all the test fuels at all load conditions, which is
attributed to reduced knocking, and hence better engine durability in the long
run. The cylinder pressure histogram trend is almost same for the fuels B50,
B25 and diesel due to their similar combustion characteristics. When the
proportion of MZME in the blend goes beyond 50%, appreciable change in
cylinder pressure histogram is noted. This is due to the lower ignition delay
and hence reduced energy release in the premixed or rapid combustion stage
[75, 83, & 85].
Figure 6.4 (a): Pressure versus Crank Angle for 0 % load
0
10
20
30
40
50
60
300 320 340 360 380 400 420 440 460
Cylin
der
Pre
ssu
re (
ba
r)
Crank Angle (Degree)
0 % LOADD100
B25
B50
B75
B100
74
Figure 6.4 (b): Pressure versus Crank Angle for 20 % load
Figure 6.4 (c): Pressure versus Crank Angle for 40 % load
0
10
20
30
40
50
60
300 320 340 360 380 400 420 440 460
Cylin
der
Pre
ssu
re (
bar)
Crank Angle (Degree)
20 % LOADD100
B25
B50
B75
B100
0
10
20
30
40
50
60
300 320 340 360 380 400 420 440 460
Cylin
der
Pre
ssu
re (
bar)
Crank Angle (Degree)
40 % LOAD D100
B25
B50
B75
B100
75
Figure 6.4 (d): Pressure versus Crank Angle for 60 % load
Figure 6.4 (e): Pressure versus Crank Angle for 80 % load
0
10
20
30
40
50
60
300 320 340 360 380 400 420 440 460
Cylin
der
Pre
ssu
re (
bar)
Crank Angle (Degree)
60 % LOADD100
B25
B50
B75
B100
0
10
20
30
40
50
60
300 320 340 360 380 400 420 440 460
Cylin
der
Pre
ssu
re (
bar)
Crank Angle (Degree)
80 % LOAD
D100
B25
B50
B75
B100
76
Figure 6.4 (f): Pressure versus Crank Angle for 100 % load
Figure 6.5: Cylinder peak pressure versus loads
0
10
20
30
40
50
60
300 320 340 360 380 400 420 440 460
Cylin
der
Pre
ssu
re (
bar)
Crank Angle (Degree)
100 % LOADD100
B25
B50
B75
B100
51
52
53
54
55
56
57
58
59
60
61
0 20 40 60 80 100
Cylin
der
Peak P
ressu
re (
bar)
Load (%)
D100 B25 B50 B75 B100
77
Variation of cylinder peak pressure with load
The variation of cylinder peak pressure with load is shown in Figure 6.5.
From the figure it is clear that peak pressure is increasing with increase in load
for all the test fuels. This is due to the increase in the mass of fuel injected with
increase in load. The blend B50 showed better result in comparison with other
blends and diesel, due to the complete combustion and better atomization
efficiency. The blends B75 and B100 showed poor results because of the
negative effect of their high viscosity, poor atomization and spray
characteristics which in turn affect the combustion process [76, 105].
Variation of net heat release with crank angle
Figures 6.6 (a) to 6.6 (f) depict the change in net heat release rate of all
fuels with crank angle at all loads. Heat release pattern of a fuel is very much
significant to extract important information about combustion like ignition delay,
duration of combustion, heat release at different crank angles etc.. It is
significant to note that the ignition delay for biodiesel and its blends is less than
that of diesel. Blends B50 and B25 released more heat energy than diesel,
although they exhibited less ignition delay. This could be due to the presence
of excess oxygen in the blends and the absence of initiation of negative effect
of high viscosity, leading to rapid mixing of air and the blends and subsequent
release of high energy in the premixed combustion stage itself.
Very low ignition delay noted for B75 and B100, resulted in the
advancement of peak pressure occurrence, leading to knocking which affects
the engine durability [83, 85, 76, 105]. The second peak in the net heat release
histogram reveals the diffusion combustion phase of the different fuels tested.
It is evident from the graph that the heat released by diesel is more than that
of other fuels in the diffusion combustion phase and also the heat released by
the blends B50 and B25 is close to that of diesel. In case of fuels with higher
biodiesel content (B75 and B100), the negative effect of higher viscosity plays
a role to hinder the flame propagation, which leads to reduced heat release
[93]. The variation of ignition delay with load is shown in Figure 6.7.
78
Figure 6.6 (a): Net Heat Release versus Crank Angle for 0 % load
Figure 6.6 (b): Net Heat Release versus Crank Angle for 20 % load
-5
0
5
10
15
20
25
30
35
40
45
300 320 340 360 380 400 420 440 460
Net
Heat
Rele
ase (
J/C
A)
Crank Angle (Degree)
0 % LOADD100
B25
B50
B75
B100
-5
0
5
10
15
20
25
30
35
40
45
300 320 340 360 380 400 420 440 460
Net
Heat
Rele
ase (
J/C
A)
Crank Angle (Degree)
20 % LOADD100
B25
B50
B75
B100
79
Figure 6.6 (c): Net Heat Release versus Crank Angle for 40 % load
Figure 6.6 (d): Net Heat Release versus Crank Angle for 60 % load
-5
0
5
10
15
20
25
30
35
40
45
300 320 340 360 380 400 420 440 460
Net
Heat
Rele
ase (
J/C
A)
Crank Angle (Degree)
40 % LOAD D100
B25
B50
B75
B100
-5
0
5
10
15
20
25
30
35
40
45
300 320 340 360 380 400 420 440 460
Net
Heat
Rele
ase (
J/C
A)
Crank Angle (Degree)
60 % LOADD100
B25
B50
B75
B100
80
Figure 6.6 (e): Net Heat Release versus Crank Angle for 80 % load
Figure 6.6 (f): Net Heat Release versus Crank Angle for 100 % load
-5
0
5
10
15
20
25
30
35
40
45
300 320 340 360 380 400 420 440 460
Net
Heat
Rele
ase (
J/C
A)
Crank Angle (Degree)
80 % LOAD D100
B25
B50
B75
B100
-5
0
5
10
15
20
25
30
35
40
45
300 320 340 360 380 400 420 440 460
Net
Heat
Rele
ase (
J/C
A)
Crank Angle (Degree)
100 % LOADD100
B25
B50
B75
B100
81
Figure 6.7: Variation of Ignition Delay with percentage of load
Variation of cumulative heat release with crank angle
Figures 6.8(a) to 6.8(f) depict the variation of amount of cumulative heat
release of all test fuels with crank angle at all load conditions. The cumulative
heat release pattern of the engine is the combined effect of heat release in two
stage such as premixed and diffused combustion stages. Blend B50 recorded
maximum heat release pattern closely followed by B25 and Diesel at all loading
conditions. B50 resulted in higher cumulative heat release, as compared to the
diesel, by 4%, 2.5%, 3%, 4.5%, 3% and 3% for different load values of no load
to full condition with 20% increment in each loading. This is due to the high
cetane number and inherent excess oxygen present in the biodiesel. Upto 50%
blending, the negative effect of high viscosity in terms of slower evaporation is
compensated by higher cetane number by shortening the ignition delay
[106 & 107]. On further increasing the biodiesel percentage in the test fuel,
even though low ignition delay recorded, effect of higher viscosity on slower
evaporation dominates and resulted in incomplete combustion.
0
2
4
6
8
10
12
14
16
18
20
0 20 40 60 80 100
Ign
itio
n D
ela
y (
CA
)
Load (%)
D100 B25 B50 B75 B100
82
Figure 6.8 (a): Cumulative Heat Release Vs Crank Angle for 0 % load
Figure 6.8 (b): Cumulative Heat Release Vs Crank Angle for 20 % load
0
0.2
0.4
0.6
0.8
1
1.2
300 320 340 360 380 400 420
Cu
mu
lati
ve H
eat
Rele
ase (
kJ)
Crank Angle (Degree)
0 % LOAD
D100
B25
B50
B75
B100
0
0.2
0.4
0.6
0.8
1
1.2
300 320 340 360 380 400 420
Cu
mu
lati
ve H
eat
Rele
ase (
kJ)
Crank Angle (Degree)
20 % LOAD
D100
B25
B50
B75
B100
83
Figure 6.8 (c): Cumulative Heat Release Vs Crank Angle for 40 % load
Figure 6.8 (d): Cumulative Heat Release Vs Crank Angle for 60 % load
0
0.2
0.4
0.6
0.8
1
1.2
300 320 340 360 380 400 420
Cu
mu
lati
ve H
eat
Rele
ase (
kJ)
Crank Angle (Degree)
40 % LOAD
D100
B25
B50
B75
B100
0
0.2
0.4
0.6
0.8
1
1.2
300 320 340 360 380 400 420
Cu
mu
lati
ve H
eat
Rele
ase (
kJ)
Crank Angle (Degree)
60 % LOAD
D100
B25
B50
B75
B100
84
Figure 6.8 (e): Cumulative Heat Release Vs Crank Angle for 80 % load
Figure 6.8 (f): Cumulative Heat Release Vs Crank Angle for 100 % load
0
0.2
0.4
0.6
0.8
1
1.2
300 320 340 360 380 400 420
Cu
mu
lati
ve H
eat
Rele
ase (
kJ)
Crank Angle (Degree)
80 % LOAD
D100
B25
B50
B75
B100
0
0.2
0.4
0.6
0.8
1
1.2
300 320 340 360 380 400 420
Cu
mu
lati
ve H
eat
Rele
ase (
kJ)
Crank Angle (Degree)
100 % LOAD
D100
B25
B50
B75
B100
85
6.4.2. Performance analysis
Brake thermal efficiency
The variation of brake thermal efficiency (BTE) with load for diesel,
MZME and their blends is shown in Figure 6.9. It is evident from the graph that
the BTE for the blends B25 and B50 is more than that of diesel and this value
for B75 and B100 is less than that of diesel at all loads. It is significant to realize
that, addition of biodiesel to diesel upto 50% increased the value of BTE and
beyond which, further addition of biodiesel resulted in the corresponding
decrease in BTE. In case of fuels with biodiesel content upto 50%, even though
B25 and B50 have 4.2% and 8.5% lesser calorific value than diesel, the
inherent 11% dissolved oxygen helped to achieve better combustion and the
higher viscosity of the biodiesel content would have provided better lubricity.
Also the negative effect of higher viscosity of biodiesel in the blends would not
have been initiated [105 & 106]. However test fuels B75 and B100 recorded
significant reduction in BTE due to the lower heating value of the biodiesel.
Also the higher viscosity of the oil would have drastically affected the delay
period, flow characteristics and atomization of fuel, leading to reduced BTE.
Figure 6.9: Variation of brake thermal efficiency with load
15
17
19
21
23
25
27
29
31
33
0 20 40 60 80 100
Bra
ke T
herm
al E
ffic
ien
cy (
%)
Load (%)
D100
B25
B50
B75
B100
86
Brake specific fuel consumption
The amount of fuel consumed to produce one kilo Watt brake power for
one complete hour is known as brake specific fuel consumption (BSFC). The
variation of BSFC with load for all test fuels is depicted in Figure 6.10. The
BSFC for all test fuels decrease with increase in load. This phenomenon is due
to the higher percentage increase in brake power with load as compared to
increase in fuel consumption. It is interesting to note that, with increase in
proportion of biodiesel in the blends upto 50%, decrease in BSFC is noted and
beyond which BSFC increased in comparison with diesel. This could be due
to the inherent oxygen content of biodiesel in the blends, which would have
prompted the combustion process and the non-initiation of the ill effect of
higher viscosity of biodiesel [72, 73, & 80]. Also the lower heating value of the
blends is compensated by the higher density as compared to diesel. However
with biodiesel content in the blends exceeding 50%, higher kinematic viscosity
affects the flow and atomization of fuel, leading to incomplete combustion. To
meet the rated speed of the engine at a given load, additional fuel is consumed
resulting in increased BSFC.
Figure 6.10: Variation of brake specific fuel consumption with load
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0 20 40 60 80 100
Bra
ke S
pecif
ic F
uel
Co
nsu
mp
tio
n (
kg
/kW
hr)
Load (%)
D100
B25
B50
B75
B100
87
Exhaust Gas Temperature
Figure 6.11 depicts the variation of exhaust gas temperature (EGT) at
all loads for the different fuels tested. As evidenced from the graph, the EGT
of all fuels increased with increase in load. This is due to the increase in the
amount of fuel injected with increase in load in order to maintain the engine
power output. It is noted that at all loads, with increase in biodiesel content in
the fuel, corresponding increase in EGT is recorded in comparison with diesel.
This could be due to the enhanced combustion on account of excess oxygen
in biodiesel and subsequent release of more heat [80].
The EGT recorded for B25 and B50 are close to that of diesel. This is
due to the effective early stage combustion and heat release in the premixed
combustion stage. This fact is also evidenced in the graphs pertaining to
variation of net heat release, BTE and BSFC. Higher values are noted for B75
and B100. This is due to the shorter ignition delay, reduced premixed
combustion and subsequent longer after burning combustion, leading to
increased EGT. This fact is also reflected in net the heat release histogram.
Figure 6.11: Variation of exhaust gas temperature with load
100
150
200
250
300
350
400
450
500
0 20 40 60 80 100
Exh
au
st
Gas T
em
pera
ture
(ºC
)
Load (%)
D100
B25
B50
B75
B100
88
6.4.3. Emission characteristics
CO emission
The variation of CO emission for different fuels at different loads is
provided in Figure 6.12. As evidenced from the graph, biodiesel and its blends
produced less CO emission than diesel. As biodiesel contains dissolved
oxygen, most of the carbon molecules would have been converted in to CO2
rather than CO. It is significant to realize that CO is more vulnerable to human
health than CO2. The CO emission for all fuels is found to increase with
increase in load. At higher loads more fuel is inducted in to the cylinder, which
leads to reduced premixed combustion and resulted in incomplete combustion.
More emission is recorded for diesel. Also with increase in biodiesel content in
the fuel, corresponding decrease in emission is noted upto B50 and beyond
which corresponding increase in emission is recorded. The increase in
emission noted for the fuels beyond B50 is due to incomplete combustion on
account of negative effect of higher viscosity.
Figure 6.12: Variation of CO emission with load
0
0.02
0.04
0.06
0.08
0.1
0.12
0 20 40 60 80 100
CO
(%
-V
ol)
Load (%)
D100
B25
B50
B75
B100
89
CO2 emission
Figure 6.13 reveals the variation of CO2 emission with load for all the
fuels tested. Maximum emission at all loads is recorded for the blend B50,
which also produced the least CO emission. It is also noted that at higher
loads, B75 and B100 produced lower CO2 than other test fuels. This is due to
the incomplete combustion, explained in the earlier section. At low load
conditions, diesel is recorded with the least CO2 emission. Although CO2
emission from biodiesel blended fuels is more than that of diesel, biodiesel is
considered carbon neutral, as all the CO2 emitted during combustion would
have been sequestered during the growth of the plants and hence the
environmental CO2 balance is unaffected.
Figure 6.13: Variation of CO2 emission with load
NOx emission
NOx is a mixture of greenhouse gases, which consists of nitric oxide
(NO), dinitrogen dioxide (N2O2), nitrous oxide (N2O), dinitrogen trioxide (N2O3),
0
0.5
1
1.5
2
2.5
0 20 40 60 80 100
CO
2(%
-V
ol)
Load (%)
D100
B25
B50
B75
B100
90
nitrogen dioxide (NO2), dinitrogen tetroxide (N2O4) and dinitrogen pentoxide
(N2O5). They are produced from the reaction of nitrogen and oxygen gases in
the air during combustion, especially at elevated temperatures. Nitric oxide
(NO) and nitrogen dioxide (NO2) are the two most important nitrogen oxide air
pollutants. In most combustion processes, the majority of the NOx (95%)
produced is in the form of nitric oxide (NO).
Figure 6.14: Variation of NOx emission with load
Figure 6.14 reveals the variation of NOx emission with load for all test
fuels. An increasing trend for NOx emission with respect to load is recorded for
all the fuels. This is due to the higher cylinder temperature and exhaust gas
temperature at higher load conditions. It is evident from the plot that diesel
produced the least emission at all loads. This is due to the shorter ignition
delay and raising peak in-cylinder temperature noted for biodiesel, resulting in
the rapid formation of thermal NOx at elevated temperatures. Also prompt NOx
is produced due to the formation of free radicals in the hydrocarbon flame
fronts, at lower temperatures.
0
20
40
60
80
100
120
140
160
180
0 20 40 60 80 100
NO
X(p
pm
)
Load (%)
D100
B25
B50
B75
B100
91
Unburnt Hydrocarbon emission
Figure 6.15 presents the variation of unburnt hydro carbon (UBHC)
emissions with load. Obviously due to induction of more fuel to maintain the
engine speed, the emission for all fuels is found to increase with increase in
load. It is significant to register that, B25 and B50 produced less emission than
other fuels at lower and medium loads. This is due to the complete combustion
and better engine performance, resulting from the inherent excess oxygen
content in biodiesel. When the percentage of biodiesel in the fuel exceeds
50%, the emission is found to increase, due to limited heating value and
influence of higher viscosity on combustion and engine performance.
Figure 6.15: Variation of unburnt hydrocarbon emission with load
0
10
20
30
40
50
60
0 20 40 60 80 100
UB
HC
(p
pm
)
Load (%)
D100
B25
B50
B75
B100
92
7. CONCLUSION
7.1. SUMMARY
In the recent years, biodiesel has gained enormous attention among
scientists and researchers to use it as a substitute for fossil diesel in diesel
engine applications. To understand the current scenario about biodiesel
utility, its related issues, an extensive literature review related to biodiesel
production methods, optimization of biodiesel production and effect of
biodiesel and its blends on diesel engine performance and emission
characteristics had been carried out. In this research work, an attempt has
been made to come out with a new biodiesel derived from Manilkara Zapota
seed oil (MZO). Raw MZO was characterised and ensured its suitability for
biodiesel production and optimization of four key process parameters
influencing the transesterification of MZO was carried out using Taguchi
method. Manilkara zapota methyl ester was prepared using the optimized
parameter values and characterised. Experimental investigation was carried
out in an unmodified diesel engine fuelled with MZME and its diesel blends.
7.2. CONCLUSION
The following conclusions were arrived based on the outcome of the
research work.
Manilkara zapota seed oil is having higher mono unsaturated fatty
acid (64.15% oleate) and low in both saturated and poly
unsaturated fatty acids, hence best suitable for good quality
biodiesel production.
6:1 methanol to oil molar ratio, 1% (w/w) concentration of catalyst,
90 min time of reaction and 50ºC temperature of reaction are the
optimized parameter values for transesterification of MZO into
MZME, based on Taguchi method and the corresponding
maximum biodiesel yield was 94.83%.
The biodiesel has been characterized and found to meet the
requirements of biodiesel standard EN 14214.
93
Combustion characteristics of engine revealed that, the highest
peak pressure is recorded for the blend B50 followed by B25 and
diesel. The value of peak pressure for B50 blend is 59.97 bar at
full load which is 1.64 % higher than diesel.
Also B50 released 44.17 (J/CA) net heat energy at full load
condition which is approximately 10% higher than diesel.
Engine performance analysis revealed that blends B25 and B50
resulted in higher BTE than that of diesel. Maximum BTE was
recorded for B50 which is 17% higher than diesel.
Blends B25 and B50 recorded the reduced BSFC as compared to
pure diesel and for B50, it was found 14.5% lesser than that of
diesel.
Among the blends, B25 and B50 produced less CO emission at all
loads as compared to diesel and B50 recorded the maximum
reduction of 34.21% in comparison with diesel.
All the blends produced more CO2 emission than pure diesel at all
loads.
All the blends produced more NOX emission than pure diesel at all
loads.
Blends B25 and B50 produced lower UBHC at lower and medium
loads and at par with pure diesel at higher loads. The maximum
reduction was recorded as 4.32% for B50 in comparison with
diesel.
It is concluded that MZO is a potential candidate for biodiesel
production and the biodiesel MZME up to 50% (B50) could effectively replace
fossil diesel in unmodified diesel engine applications, with better engine
performance and reduced CO and UBHC emissions. However all the blends
produced more CO2 emission as compared to diesel, biodiesels are
considered carbon neutral, because all CO2 released during combustion had
been sequestered from the atmosphere for the growth of the plants.
94
7.3. SCOPE FOR FUTURE WORK
The present study could be extended with prime focus on the following
aspects:
Identification of suitable nano additive to reduce the emissions
of CO2 and NOx.
Experimental investigation for long run applications of the
engine.
Experimental investigation on optimizing the operating
conditions of the engine, such as CR, advancement of injection
timing, injection pressure for better performance with pure
biodiesel (B100).
Biogas generation from the de-oiled cake with special measure
to control the factors affecting the gas generation.
95
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APPENDIX
ERROR ANALYSIS
GENERAL FORMS
As mentioned in the chapter 3 and 4, the errors associated with various
measurements and the calculations of important parameters are computed in
this section. The maximum possible errors in various measured parameters
namely temperature, time, voltage and current are estimated from the
minimum values of output and accuracy of the instrument. The errors in the
estimated parameters such as fuel consumption, brake power, BSFC and
BSEC are calculated using the method proposed by Moffat (1985). This
method is based on careful specification of the uncertainties in the various
experimental measurements.
If an estimated quantity, S depends on independent variables like (x1,
x2, x3 …………xn) then the error in the value of “S” is given by
2
1
2
2
2
2
2
2
2
1
1.....
x
x
x
x
x
x
s
s (A1.1)
where, 1
1
x
x
, 2
2
x
x
etc… are the errors in the independent variables.
ERRORS IN MEASURED QUANTITIES
Temperature
Iron constantan thermocouple is used to measure the temperature of
the engine exhaust gas. The maximum possible error in the case of
temperature measurement is calculated from the minimum values noted and
108
the accuracy of the instrument. The errors in the temperature measurement
for the thermocouple are:
002833.0353
1
K
K
T
T
Exp
(A1.2)
00202839.0493
1
K
K
T
T
Exp
(A1.3)
Brake power
The brake power is given by
g
VIPB
1000. (A1.4)
The overall error in the estimation of brake power is given as
2
1
22
.
.
I
I
V
V
PB
PB 2
1
22
033.00166.0 (A1.5)
= 0.0169 or ± 1.69%
Fuel consumption
1000.
.3600..
t
xCF
(A1.6)
The overall error in the estimation of Specific fuel consumption is given as
2
1
22
.
.
t
t
x
x
CF
CF 2
1
22
016.0005.0 (A1.7)
= 0.0167 or ± 1.67%
BSFC
BSFC =
PB
SFC
. (A1.8)
The overall error in the estimation of BSFC is given as
109
2
1
22
0169.00167.0
BSFC
BSFC = 0.02375 or ± 2.375% (A1.9)
BSEC
BSEC = BSFC X C.V (A1.10)
The overall error in the estimation of BSFC is given as
2
1
22
002375.0
BSEC
BSEC = 0.02375 or ± 2.375% (A1.11)
Table A 1.1: Summary of estimated uncertainties
Parameters Uncertainty (%)
Temperature 0.283
Time 1.66
Current 3.3
Voltage 1.66
Burette reading 0.5
Gas collection reading 1.0
Brake power 1.69
Specific fuel consumption 1.67
BSFC 2.375
BSEC 2.375
110
LIST OF PUBLICATIONS
International Journals:
1. R. Sathish Kumar, K. Sureshkumar, R. Velraj “Optimization of biodiesel
production from Manilkara zapota (L.) seed oil using Taguchi method” Fuel
140 (2015) 90–96.
2. R. Sathish Kumar, K. Sureshkumar “Effect of methanol blending with
Pongamia pinnata biodiesel and diesel blends on engine performance and
exhaust emission characteristics of an unmodified Compression Ignition
engine” International Journal of Ambient Energy 36 (2) (2015) 70-75.
3. R. Sathish Kumar, K. Sureshkumar, R. Velraj “Manilkara Zapota (L.) Seed
Oil – A New Third Generation Biodiesel Resource” Energy Education
Science and Technology Part A: Energy Science and Research (Under
review)
4. R. Sathish Kumar, K. Sureshkumar, R. Velraj “Combustion, Performance
and emission characteristics of an unmodified diesel engine fuelled with
Manilkara Zapota Methyl Ester and its diesel blends” Applied Energy
(communicated)
International Conferences:
1. R.Sathish Kumar, K.Suresh Kumar, D.Narendran. “Performance and
Exhaust Emission Characteristics of C.I. Engine Fuelled with Blends of
Pongamia Pinnata Methyl Ester and Different Fuels” International
Conference on Engineering Materials and Processes (ICEMAP- 2013)-
May 23rd & 24th 2013.
2. R.Sathish Kumar, K.Suresh Kumar, R.Velraj. “Performance and Exhaust
Emission Characteristics of an Unmodified CI Engine Fuelled with
Biodiesel-Diesel-Methanol Blends” Annual International Conference on
Sustainable Energy and Environmental Sciences organized by Global
Science and Technology Forum during 13th and 14th of February 2012 in
Singapore.
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TECHNICAL BIOGRAPHY
Mr. Sathish Kumar R. (RRN: 0981201) is a citizen of India, born in
Chengalpattu, Kancheepuram District, Tamilnadu on 16.05.1981. He received
his Bachelor’s degree in Mechanical Engineering in the year 2003 from
University of Madras, Tamilnadu. He obtained his master’s degree in First
Class with distinction in the field of Computer Aided Design from A.C.College
of Engineering and Technology, Karaikudi, Anna University, Tamilnadu in the
year 2006.
He received many awards during schooling for academic achievements
and oratorical skills. He secured Anna University Fourth Rank and received
Gold Medal from A.C.College of Engineering and Technology in his Master’s
degree. He has 10 years of teaching experience at various levels and presently
working as Assistant Professor (Senior Grade) in the Department of
Mechanical Engineering, B.S. Abdur Rahman University, Vandalur, Chennai,
Tamilnadu, India.
He is a life member of Combustion Institute Indian Section (CIIS). He has
published/presented several papers in various national and international
journals / conferences.
