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] 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: Comparisons of measured and computed cylinder pressure with above discussed model on a Cat 3406 engine Bore (cm)13.76 Stroke (cm)16.51 RPM1600 Compression Ratio15.1 Inlet Pressure (KPa)184 Injection pressure (MPa)90 Number of nozzles6 Engine parameters

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 conductivitycalculations

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 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 -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 Change in thermal efficiency with BD compared to the base case DF2 The same trend is visible for both methods This reduction in power is due to Lower heating value of BD

NO emission Engine exit conditions 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 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 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 for DF2 base case at 5 degrees ATDC Vaporous fuel concentration for BD base case at 5 degrees ATDC Poor atomization and evaporation results in lower vaporous fuel in BD cases Vaporous Fuel Concentration ATDC: After Top Dead Center

Temperature distribution for DF2 base case at 5 degrees ATDC Temperature distribution for BD base case at 5 degrees ATDC Poor atomization and vaporization is visible. Biodiesel case is at a different stage of Combustion although the same SOI was used. Temperature Distribution

NO mass at BDC for BD base case at 5 degrees ATDC NO mass at BDC for DF2 base case at 5 degrees ATDC Bigger volume of high temperature regions lead to higher NO production for DF2 case NO Mass Comparison

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 Osmont, A., Catoire, L., Gökalp, I., Thermochemistry of Methyl and Ethyl Esters from Vegetable Oils. Int. J. Chem. Kinet., 39, 481– 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 Allen, C. W., K. C. Watts, and R. G. Ackman Predicting the surface tension of biodiesel fuels from their fatty acid composition. J. American Oil Chem. Soc. 76(3): 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 , 2006.

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Temperature Distribution for DF2 base case at 15 degrees ATDC Temperature Distribution for BD base case at 15 degrees ATDC