Pollutant Emission Reduction and Increased
Efficiency for Compression Ignition Engines
Utilizing Biodiesel through Optimization of
the Fuel Injection Process
Ehsan Tootoonchi and Gerald Micklow
Florida Institute of Technology
Outline
•
Background
– Pros and cons
– Soybean Methyl Ester (SME)
•
Accurate spray model
– Theory
– VW engine plots
•
Combustion model
– Theory
•
Fuel properties
– Theory
– Sandia study
•
•
•
Engine parameters and analysis methods
Results
Conclusion
Background
•
•
•
U.S. production of biodiesel was 991 million gallons in 2012 (3.8 percent of its
capacity in 2012, total of 26.3 billion gallons)
In the first 7 month of 2014 it raised to 4.8 percent of U.S. estimated capacity [1]
36.3 billion gallons of diesel consumed in U.S. in year 2012
•
Emission advantages
–
–
–
–
•
B20 produces 12 percent less Particulate Mater (PM) than petroleum diesel fuel and it is 47 percent
for neat biodiesel
Biodiesel can provide a closed loop CO2 cycle and limit CO2 accumulation in atmosphere
Zero sulfur content
Excellent lubricity characteristics
1-2 percent blends can improve poor lubricity diesel
fuels significantly
Notable problems
–
–
Poorer cold flow performance
Lower heating value
Soybean Methyl Ester (SME)
•
Soybean is the largest biodiesel feedstock in U.S.
– Soybean oil was almost 50% of the total biodiesel feedstock in July 2014 [1]
other sorces
Soybean Oil
•
Amongst other biodiesel sources Soybean based biodiesel reported to produce higher levels
of NOx emission
Computer Program
• Modified version of KIVA3V was used
• KIVA3V is a three-dimensional, transient code
• KIVA3V is a computer program for numerical calculation of chemically
reactive fluid flows with sprays
Spray Modeling
The following modifications were made to KIVA3V for the current application:
• Automatic SMR update
– A correlation was defined for Sauter Mean Radius (SMR) using the
experimental data available and is used for calculating and automatically
updating SMR for each iteration.
• Nozzle discharge coefficient
– A nozzle discharge coefficient was introduced into the KIVA3V code to
account for viscous effects in the fuel injection process.
• Fuel injection velocity
– Expressions for the varying fuel injection velocity as a function of injection
pressure and in-cylinder pressure which is updated at each iteration.
• Drag coefficient
– The model was further improved with an improved expression for the drop
drag coefficient which varies depending on in-cylinder conditions
Spray Model Verification
•
The model was verified in quartz 1.9 L Turbocharged Direct Injection (TDI) Volkswagen
engine.
March in time from left to right. The blue lines show the experimental results.
Engine parameters
Combustion Modeling
•
The overall reaction representing the oxidation of a typical hydrocarbon fuel in one-step
scheme was used:
•
With single rate expression of the form:
•
The above equation is based on chemical reaction rate, which may work well for premixed
combustion, and to consider the non-premixed combustion case the Magnussen and
Hjertager [2] method was used with the following formulation:
When excess oxidizer is present,
And when the fuel is in excess,
time-mean concentration
ε is the rate of dissipation of turbulent kinetic energy
k is the turbulent kinetic energy
Combustion Modeling
•
Numerous schemes can be generated in an attempt to model the physical phenomena. The
more applicable scheme for both the ignition delay and mixing controlled combustion stages
was used as follows:
Engine parameters
•
Bore (cm)
13.76
Stroke (cm)
16.51
RPM
1600
Compression Ratio
15.1
Inlet Pressure (KPa)
184
Injection pressure (MPa)
90
Number of nozzles
6
Comparisons of measured and computed cylinder pressure with above discussed model on a
Cat 3406 engine
Thermal NO Modeling
•
The Extended Zeldovich mechanism was used to account for Nitric Oxide generation
Thermophysical Properties of Biodiesel
•
•
Soybean Methyl Ester (SME) biodiesel (B100) was used
SME is a mixture of 5 methyl esters
•
Required data for modeling the new fuel are:
– Heat of Formation, and Enthalpy
– Liquid Latent Heats of Vaporization
– Vapor Pressure
– Liquid Viscosity
– Surface Tension
– Thermal Conductivity
Thermophysical Properties of Biodiesel
•
•
•
•
•
•
Heat of Formation, Enthalpy
– Heat of formation of each constituent was determined from NIST Material Measurement
Laboratory and the method of Osmont et al [3] was used to calculate Cp values for the
desired temperature range
Liquid Latent Heats of Vaporization (LHV)
– The Lee-Kesler [4] equation was used to calculate the critical mixture properties and the
method described in Yuan et al [4] was used to calculate the LHV
Vapor Pressure
– Pitzer [5] method was used to calculate vapor pressure of the mixture, and the acentric
factor of the mixture was calculated using Lee-Kessler equation
Liquid Viscosity
– Orrick and Erbar [6] method was used for viscosity calculation
Surface Tension
– The method described in Allen et al [7] was used for surface tension calculation
Thermal Conductivity
– Power law model for the mixture described in Latini et al [8] was used for thermal
conductivity calculations
Verification
•
•
Described models for fuel spray and combustion model were separately verified as discussed
before, fuel properties calculations was verified using a SCORE engine experimental data
from Cheng et al [9]
Results show a relative good agreement between calculated and measured values, although
the Start of Combustion (SOC) is a little bit off for calculated values
SME Biodiesel
Crank shaft angle [degrees]
Engine Parameters
•
•
•
To compare petrodiesel fuel (DF2) with biodiesel
fuel (BD) on emissions and power production a
Caterpillar 3406 compression ignition engine 360
degree mesh with the KIVA3V code with
following operating condition was used.
The effect of injection timing was studied.
After a grid independence study the following
grid with 179,255 cells was chosen for the study.
Methods
•
Considering the lower heating value for BD two methods was used:
1. Same mass (
) approach
In this method the mass of the fuel to be injected for the DF2 and the BD was the
same
2. Same (
) approach
In the second approach the mass of the BD injected was increased to have the
same heat release as the DF2 i.e., the mass injected times heating value was the
same. Since the heating value of BD is lower, the mass of injected fuel was
increased by increasing injection duration.
Percent reduction in power compared to DF2
case
BD-10.5
BD-8.5
BD-6.5
BD-5.5
BD-4.5
0
-5
-10
Percent
-15
-20
-25
-30
same mf
same
mf.QHV
-35
-40
-45
• -8.5 degrees was the manufacturer recommended injection timing for DF2
• Change in generated power with BD compared to the base case DF2
• There is a significant drop in power for all cases
• The same trend is visible for both methods
• SOI (Start of Injection) effectiveness on power increase is dependent on other factors (mass of fuel,
injection duration, etc)
• The power reduction is partly due to the lower heating value of BD, and partly due to
the poor atomization/evaporation of BD in compare to DF2
Percent reduction in thermal efficiency
compared to DF2 case
BD-10.5
BD-8.5
BD-6.5
BD-5.5
BD-4.5
0
-5
Percent
-10
same mf
-15
same mf.QHV
-20
-25
-30
This reduction in power is due to
Lower heating value of BD
• Change in thermal efficiency with BD compared to the base case DF2
• The same trend is visible for both methods
NO emission
Engine exit conditions
DF2 vs BD different injection timing
4.00E-03
3.50E-03
NO( gram)
3.00E-03
2.50E-03
2.00E-03
1.50E-03
same mf
1.00E-03
same mf.QHV
5.00E-04
0.00E+00
DF2-8.5 BD-10.5 BD-8.5 BD-6.5 BD-5.5 BD-4.5
• NO amounts decreases for all cases
• The main reason is the difference atomization/evaporation characteristics of BD
which reduces the high temperature volume responsible for NO generation
• The NO2 mechanism should be added for more accurate results
CO emission
DF2 vs BD different injection timing
1.40E-02
1.20E-02
CO (gram)
1.00E-02
8.00E-03
same mf
6.00E-03
same mf.QHV
4.00E-03
2.00E-03
0.00E+00
DF2-8.5
BD-10.5
BD-8.5
BD-6.5
BD-5.5
BD-4.5
• Significant reduction in CO emissions, this is due to the fact that a more complete
CO/CO2 conversion occurs for BD as a result of higher oxygen content
CO2 emission
DF2 vs BD different injection timing
0.50
0.45
0.40
CO2 (grams)
0.35
0.30
0.25
same mf
0.20
same mf.QHV
0.15
0.10
0.05
0.00
DF2-8.5
BD-10.5
BD-8.5
BD-6.5
BD-5.5
BD-4.5
• This figure is in agreement with CO mass which shows a better
CO/CO2 conversion for BD as a result of higher oxygen content
• Higher carbon content in BD accounts for higher CO2 production
Vaporous Fuel Concentration
Vaporous fuel concentration for DF2 base case at 5 Vaporous fuel concentration for BD base case at 5
degrees ATDC
degrees ATDC
• Poor atomization and evaporation results in lower vaporous fuel in BD cases
ATDC: After Top Dead Center
Temperature Distribution
Poor atomization and vaporization is visible. Biodiesel case is at a different stage of
Combustion although the same SOI was used.
Temperature distribution for DF2 base case at 5
degrees ATDC
Temperature distribution for BD base case at 5
degrees ATDC
NO Mass Comparison
NO mass at BDC for DF2 base case at 5 degrees ATDC
NO mass at BDC for BD base case at 5 degrees ATDC
•Bigger volume of high temperature regions lead to higher NO production for DF2
case
Conclusion
•
Results showed that the thermophysical differences in fuel properties have significant effect on
overall engine performance
•
The 6.5 BTDC injection timing results in optimum power/efficiency.
•
SOI effectiveness on power increase is dependent on other factors (mass of fuel,
injection duration, etc)
•
The power reduction is partly due to the lower heating value of BD, and partly due to
the poor atomization/evaporation of BD in compare to DF2
•
Results are in agreement with more complete CO/CO2 conversion for BD as a result of higher
oxygen content
•
The lower values for power generated in BD cases in compare to DF2 case showed that only
injection timing variation is not sufficient to achieve comparable engine performance
– Varying other parameters like injector geometry, fuel temperature, injection pressure, initial
cylinder temperature and pressure, etc should be considered to get closer performance
results
References
1- U.S. Energy Information Administration | Monthly Biodiesel Production Report
2- B.F. Magnussen, B.H. Hjertager, “On Mathematical Modeling of Turbulent Combustion with Special
Emphasis on Soot Formation and Combustion”, 16th Symposium on Combustion, Combustion
Institute, Pittsburgh, PA, 1976, pp. 719-729.
3- Osmont, A., Catoire, L., Gökalp, I., 2007. Thermochemistry of Methyl and Ethyl Esters from Vegetable
Oils. Int. J. Chem. Kinet., 39, 481–491.
4- Lee, B. I., and M. G. Kesler: AIChE J., 21: 510 (1975).
5- Pitzer, K. S., and R. F. Curl: The Thermodynamic Properties of Fluids, Inst. Mech. Eng., London, 1957b.
6- Orrick, C., and J. H. Erbar: Estiation of Pure Component Properties, December 1974.
7- Allen, C. W., K. C. Watts, and R. G. Ackman. 1999. Predicting the surface tension of biodiesel fuels
from their fatty acid composition. J. American Oil Chem. Soc. 76(3): 317-323.
8- Baroncini, C., P. Di Filippo, G. Latini, and M. Pacetti: Intern. J. Thermophys., 2(1): 21 (1981).
9- A. S. Cheng, A. Upatnieks and C. J. Mueller, "Investigation of the impact of biodiesel fuelling on NOx
emissions using an optical direct injection diesel engine," International Journal of Engine Research,
vol. 7, pp. 297-318, 2006.
Thank you for your attention!
Temperature Distribution for DF2 base case at
15 degrees ATDC
Temperature Distribution for BD base case at
15 degrees ATDC