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Journal articles on the topic 'Gasoline Surrogate'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Piehl, J. A., A. Zyada, L. Bravo, and O. Samimi-Abianeh. "Review of Oxidation of Gasoline Surrogates and Its Components." Journal of Combustion 2018 (December 6, 2018): 1–27. http://dx.doi.org/10.1155/2018/8406754.

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There has been considerable progress in the area of fuel surrogate development to emulate gasoline fuels’ oxidation properties. The current paper aims to review the relevant hydrocarbon group components used for the formulation of gasoline surrogates, review specific gasoline surrogates reported in the literature, outlining their utility and deficiencies, and identify the future research needs in the area of gasoline surrogates and kinetics model.

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2

Khan, Ahmed Faraz, Philip John Roberts, and Alexey A. Burluka. "Modelling of Self-Ignition in Spark-Ignition Engine Using Reduced Chemical Kinetics for Gasoline Surrogates." Fluids 4, no. 3 (August 17, 2019): 157. http://dx.doi.org/10.3390/fluids4030157.

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A numerical and experimental investigation in to the role of gasoline surrogates and their reduced chemical kinetic mechanisms in spark ignition (SI) engine knocking has been carried out. In order to predict autoignition of gasoline in a spark ignition engine three reduced chemical kinetic mechanisms have been coupled with quasi-dimensional thermodynamic modelling approach. The modelling was supported by measurements of the knocking tendencies of three fuels of very different compositions yet an equivalent Research Octane Number (RON) of 90 (ULG90, PRF90 and 71.5% by volume toluene blended with n-heptane) as well as iso-octane. The experimental knock onsets provided a benchmark for the chemical kinetic predictions of autoignition and also highlighted the limitations of characterisation of the knock resistance of a gasoline in terms of the Research and Motoring octane numbers and the role of these parameters in surrogate formulation. Two approaches used to optimise the surrogate composition have been discussed and possible surrogates for ULG90 have been formulated and numerically studied. A discussion has also been made on the various surrogates from the literature which have been tested in shock tube and rapid compression machines for their autoignition times and are a source of chemical kinetic mechanism validation. The differences in the knock onsets of the tested fuels have been explained by modelling their reactivity using semi-detailed chemical kinetics. Through this work, the weaknesses and challenges of autoignition modelling in SI engines through gasoline surrogate chemical kinetics have been highlighted. Adequacy of a surrogate in simulating the autoignition behaviour of gasoline has also been investigated as it is more important for the surrogate to have the same reactivity as the gasoline at all engine relevant p − T conditions than having the same RON and Motored Octane Number (MON).

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3

Juárez-Facio, Ana Teresa, Tiphaine Rogez-Florent, Clémence Méausoone, Clément Castilla, Mélanie Mignot, Christine Devouge-Boyer, Hélène Lavanant, et al. "Ultrafine Particles Issued from Gasoline-Fuels and Biofuel Surrogates Combustion: A Comparative Study of the Physicochemical and In Vitro Toxicological Effects." Toxics 11, no. 1 (December 26, 2022): 21. http://dx.doi.org/10.3390/toxics11010021.

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Gasoline emissions contain high levels of pollutants, including particulate matter (PM), which are associated with several health outcomes. Moreover, due to the depletion of fossil fuels, biofuels represent an attractive alternative, particularly second-generation biofuels (B2G) derived from lignocellulosic biomass. Unfortunately, compared to the abundant literature on diesel and gasoline emissions, relatively few studies are devoted to alternative fuels and their health effects. This study aimed to compare the adverse effects of gasoline and B2G emissions on human bronchial epithelial cells. We characterized the emissions generated by propane combustion (CAST1), gasoline Surrogate, and B2G consisting of Surrogate blended with anisole (10%) (S+10A) or ethanol (10%) (S+10E). To study the cellular effects, BEAS-2B cells were cultured at air-liquid interface for seven days and exposed to different emissions. Cell viability, oxidative stress, inflammation, and xenobiotic metabolism were measured. mRNA expression analysis was significantly modified by the Surrogate S+10A and S+10E emissions, especially CYP1A1 and CYP1B1. Inflammation markers, IL-6 and IL-8, were mainly downregulated doubtless due to the PAHs content on PM. Overall, these results demonstrated that ultrafine particles generated from biofuels Surrogates had a toxic effect at least similar to that observed with a gasoline substitute (Surrogate), involving probably different toxicity pathways.

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4

Machado, Guilherme Bastos, Tadeu C. Cordeiro de Melo, and Arthur C. de Albuquerque Fonseca Candido. "Flex-fuel engine: Influence of ethanol content on power and efficiencies." International Journal of Engine Research 22, no. 1 (March 12, 2019): 273–83. http://dx.doi.org/10.1177/1468087419833257.

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Gasoline is a complex mixture of different hydrocarbons, with a wide spectrum of constituents. Surrogate fuels have a reduced number of chemical components and therefore are used to model commercial fuels and enhance the understanding of fuel behavior in internal combustion engines. Surrogates also allow better fuel property control. In previous work, a surrogate fuel blend of iso-octane, n-heptane, toluene and ethanol was found to be suitable for commercial, high-octane, oxygenated Brazilian gasoline. This article investigates the influence on a Flex-fuel engine power and efficiencies of different ethanol levels in this surrogate fuel blend. The study found some different trends when comparing to other works in the literature. This article intends to make contributions presenting more detailed analyses of how fuel properties can influence several Flex-fuel engine performance parameters.

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5

Sarathy, S. Mani, Aamir Farooq, and Gautam T. Kalghatgi. "Recent progress in gasoline surrogate fuels." Progress in Energy and Combustion Science 65 (March 2018): 67–108. http://dx.doi.org/10.1016/j.pecs.2017.09.004.

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6

Mariani, Valerio, Leonardo Pulga, Gian Marco Bianchi, Stefania Falfari, and Claudio Forte. "Machine Learning-Based Identification Strategy of Fuel Surrogates for the CFD Simulation of Stratified Operations in Low Temperature Combustion Modes." Energies 14, no. 15 (July 30, 2021): 4623. http://dx.doi.org/10.3390/en14154623.

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Many researchers in industry and academia are showing an increasing interest in the definition of fuel surrogates for Computational Fluid Dynamics simulation applications. This need is mainly driven by the necessity of the engine research community to anticipate the effects of new gasoline formulations and combustion modes (e.g., Homogeneous Charge Compression Ignition, Spark Assisted Compression Ignition) to meet future emission regulations. Since those solutions strongly rely on the tailored mixture distribution, the simulation and accurate prediction of the mixture formation will be mandatory. Focusing purely on the definition of surrogates to emulate liquid phase and liquid-vapor equilibrium of gasolines, the following target properties are considered in this work: density, Reid vapor pressure, chemical macro-composition and volatility. A set of robust algorithms has been developed for the prediction of volatility and Reid vapor pressure. A Bayesian optimization algorithm based on a customized merit function has been developed to allow for the efficient definition of surrogate formulations from a palette of 15 pure compounds. The developed methodology has been applied on different real gasolines from literature in order to identify their optima surrogates. Furthermore, the ‘unicity’ of the surrogate composition is discussed by comparing the optimum solution with the most different one available in the pool of equivalent-valuable solutions. The proposed methodology has proven the potential to formulate surrogates characterized by an overall good agreement with the target properties of the experimental gasolines (max relative error below 10%, average relative error around 3%). In particular, the shape and the end-tails of the distillation curve are well captured. Furthermore, an accurate prediction of key chemical macro-components such as ethanol and aromatics and their influence on evaporative behavior is achieved. The study of the ‘unicity’ of the surrogate composition has revealed that (i) the unicity is strongly correlated with the accuracy and that (ii) both ‘unicity’ and accuracy of the prediction are very sensitive to the high presence of aromatics.

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7

Yin, Peng, Wenfu Liu, Yong Yang, Haining Gao, and Chunhua Zhang. "An Experimental and Modeling Study on the Combustion of Gasoline-Ethanol Surrogates for HCCI Engines." Security and Communication Networks 2022 (February 21, 2022): 1–10. http://dx.doi.org/10.1155/2022/5362928.

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As an effective clean fuel, ethanol has the characteristics of improving antiknock quality and reducing emissions. It is an ideal antiknock additive for Homogeneous Charge Compression Ignition (HCCI) engines. The oxidation of gasoline-ethanol surrogates in HCCI engines is a very complex process which is dominated by the reaction kinetics. This oxidation process directly determines the performance and emissions of HCCI engines. Coupling the computational fluid dynamic (CFD) model with the gasoline-ethanol surrogate mechanism can be used for fuel design, so the construction of a reduced mechanism with high accuracy is necessary. A mechanism (278 species, 1439 reactions) at medium and low temperatures and experiments in a HCCI engine for the oxidation of gasoline-ethanol surrogates were presented in this paper. Directed relation graph with error propagation (DRGEP) method and quasi-steady-state assumption (QSSA) method were used in order to get a reduced model. Then, the kinetics of the vital reactions related to the formation and consumption of H and OH were adjusted. To validate the model, the HCCI experiments for the oxidation of gasoline-ethanol surrogates were conducted under different operating conditions. The verification result indicated that the present model can predict the oxidation process of gasoline-ethanol effectively.

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8

Yang, Chao, and Zhaolei Zheng. "Construction of a Chemical Kinetic Model of Five-Component Gasoline Surrogates under Lean Conditions." Molecules 27, no. 3 (February 6, 2022): 1080. http://dx.doi.org/10.3390/molecules27031080.

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The requirements for improving the efficiency of internal combustion engines and reducing emissions have promoted the development of new combustion technologies under extreme operating conditions (e.g., lean combustion), and the ignition and combustion characteristics of fuels are increasingly becoming important. A chemical kinetic reduced mechanism consisting of 115 species and 414 elementary reactions is developed for the prediction of ignition and combustion behaviors of gasoline surrogate fuels composed of five components, namely, isooctane, n-heptane, toluene, diisobutylene, and cyclohexane (CHX). The CHX sub-mechanism is obtained by simplifying the JetSurF2.0 mechanism using direct relationship graph error propagating, rate of production analysis, and temperature sensitivity analysis and CHX is mainly consumed through ring-opening reactions, continuous dehydrogenation, and oxygenation reactions. In addition, kinetic parameter corrections were made for key reactions R14 and R391 based on the accuracy of the ignition delay time and laminar flame velocity predictions. Under a wide range of conditions, the mechanism’s ignition delay time, laminar flame speed, and the experimental and calculated results of multi-component gasoline surrogate fuel and real gasoline are compared. The proposed mechanism can accurately reproduce the combustion and oxidation of each component of the gasoline-surrogate fuel mixture and real gasoline.

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9

Cicci, Francesco, and Giuseppe Cantore. "Preliminary study on the influence of Octane Sensitivity on knock statistics in a GDI engine." E3S Web of Conferences 312 (2021): 07020. http://dx.doi.org/10.1051/e3sconf/202131207020.

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In the 3D-CFD practice, actual gasoline fuels are usually replaced by surrogate blends composed of Iso-Octane, n-Heptane and Toluene (Toluene Reference Fuels, TRFs). In this work, the impact of surrogate formulation on the probability of end-gas auto-ignition is investigated in a single cylinder engine. CFD simulations are run on equal charge stratification to discern the effect of fuel reactivity from that of evaporation and mixing. Blends are formulated using an internal methodology, coupled with a proprietary method to predict knock statistical occurrence within a RANS framework. Chemical kinetics calculations of Ignition delay times are performed in a 0D constant pressure reactor using a mechanism for gasoline surrogates, proposed by the Clean Combustion Research Center of King Abdullah University of Science and Technology (KAUST), consisting of 2406 species and 9633 reactions. Surrogates mimic a commercial European gasoline (ULG95). Five different formulations are presented. Three are characterised by equal RON (95) with progressively decreasing Octane Sensitivity S. The fourth and the fifth have a sensitivity of 10 but with lower RON (92.5 and 90). The combinations allow the reader to separate the effects of octane sensitivity from those of RON quality of the tested fuels. Applying the different surrogates, changes in each of autoignition phasing, magnitude and statistical probability are investigated. Results confirm the dependency of knock occurrence on the Octane Sensitivity, as well as the need to include engine-specific and operation-specific characteristics in the analysis of knock. The Octane Index (OI) formulation developed by Kalghatgi is discussed.

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10

Kong, Jun, Yanxin Qin, and Zhaolei Zheng. "Method for determining gasoline surrogate component proportions and development of reduced chemical kinetics model of the determined surrogate fuel." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233, no. 14 (February 18, 2019): 3658–70. http://dx.doi.org/10.1177/0954407019828852.

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Response surface method is used to build models for predicting an octane number and determining the component proportions of a gasoline surrogate fuel. The fuel is synthesized using toluene, iso-octane, and n-heptane and is referred to as toluene reference fuel. The built models include second-order model and third-order model. Both models can excellently predict the octane number of the toluene reference fuel with known component proportions. Moreover, the third-order model is more accurate than second-order model in determining the component proportions of the toluene reference fuel, and the relative error is less than 8%. Therefore, the third-order model can accurately predict the octane number and determine the component proportions of the toluene reference fuel. Moreover, a new reduced mechanism of the toluene reference fuel is proposed and validated by using shock tube ignition delay and in-cylinder pressure in a homogeneous charge compression ignition engine. The toluene reference fuel mechanism coupled with third-order model is used to simulate the ignition delay of American gasoline (RD387) and the homogeneous charge compression ignition combustion behaviors of European gasoline (ULG95). Both cases are simulated thoroughly.

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11

Morgan, Neal, Andrew Smallbone, Amit Bhave, Markus Kraft, Roger Cracknell, and Gautam Kalghatgi. "Mapping surrogate gasoline compositions into RON/MON space." Combustion and Flame 157, no. 6 (June 2010): 1122–31. http://dx.doi.org/10.1016/j.combustflame.2010.02.003.

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12

Yang, Chao, and Zhaolei Zheng. "Chemical Kinetic Model of Multicomponent Gasoline Surrogate Fuel with Nitric Oxide in HCCI Combustion." Molecules 25, no. 10 (May 12, 2020): 2273. http://dx.doi.org/10.3390/molecules25102273.

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This study presents a simplified mechanism of a five-component gasoline surrogate fuel (TDRF–NO) that includes n-heptane, isooctane, toluene, diisobutylene (DIB) and nitric oxide (NO). The mechanism consists of 119 species and 266 reactions and involves TDRF and NO submechanisms. Satisfactory results were obtained in simulating HCCI combustion in engines. The TDRF submechanism is based on the simplified mechanism of toluene reference fuel (TRF) and adds DIB to form quaternary surrogate fuel for gasoline. A simplified NO submechanism containing 33 reactions was added to the simplified mechanism of TDRF, considering the effect of active molecular NO on the combustion of gasoline fuel. The ignition delay data of the shock tube under different pressure and temperature conditions verified the validity of the model. Model verification results showed that the ignition delay time predicted by the simplified mechanism and its submechanics were consistent with the experimental data. The addition of NO caused the ignition delay time of the mechanism simulation to advance with increasing concentration of NO added. The established simplified mechanism effectively predicted the actual combustion and ignition of gasoline.

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13

Kim, Joohan, and Kyoungdoug Min. "Modeling laminar burning velocity of gasoline using an energy fraction-based mixing rule approach." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233, no. 5 (May 4, 2018): 1245–58. http://dx.doi.org/10.1177/0954407018768396.

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To determine an optimum combustion chamber design and engine operating strategies, computational fluid dynamics simulations of direct-injection spark-ignition engines have become an indispensable step in the powertrain development process. The laminar burning velocity of gasoline is known as an essential input parameter for combustion simulations. In this study, a new methodology for modeling the laminar burning velocity of gasoline for direct-injection spark-ignition engine simulations is proposed. Considering the gasoline as a complex mixture of hydrocarbon fuel, three hydrocarbons, iso-octane, n-heptane, and toluene were incorporated as surrogate fuel components to represent gasoline with distinct aromatic laminar flame characteristics compared to alkane. A mixing rule, based on energy fractions, was adopted to consider the compositional variation of gasoline. The laminar burning velocities of iso-octane, n-heptane, and toluene were calculated under wide thermo-chemical conditions in conjunction with detailed chemical reaction kinetics in the premixed flame simulation. Finally, a set of laminar burning velocity model equations was derived by curve-fitting the flame simulation results of each hydrocarbon component in consideration of the effect of temperature, pressure, and diluent. The laminar burning velocity model was validated against the measurement data of gasoline’s laminar burning velocity found in the literature, and was applied to the computational fluid dynamics simulation of a direct-injection spark-ignition engine under the various operating conditions to explore the prediction capability.

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14

Kobayashi, Yoshihiro, and Masataka Arai. "Characteristics of PM Exhausted from Pool Diffusion Flame with Gasoline and Surrogate Gasoline Fuels." SAE International Journal of Engines 9, no. 1 (September 1, 2015): 315–21. http://dx.doi.org/10.4271/2015-01-2024.

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15

Kim, Doohyun, Jeongwoo Song, Hwasup Song, Yunsung Lim, Sanguk Lee, and Han Ho Song. "Assessment of hydrocarbons for gasoline surrogate: An optimization study." Fuel 328 (November 2022): 125286. http://dx.doi.org/10.1016/j.fuel.2022.125286.

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16

Cai, Liming, and Heinz Pitsch. "Optimized chemical mechanism for combustion of gasoline surrogate fuels." Combustion and Flame 162, no. 5 (May 2015): 1623–37. http://dx.doi.org/10.1016/j.combustflame.2014.11.018.

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17

Lee, Kyeonghyeon, Yongrae Kim, and Kyoungdoug Min. "Development of a reduced chemical kinetic mechanism for a gasoline surrogate for gasoline HCCI combustion." Combustion Theory and Modelling 15, no. 1 (December 14, 2010): 107–24. http://dx.doi.org/10.1080/13647830.2010.528037.

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18

Knop, Vincent, Cécile Pera, and Florence Duffour. "Validation of a ternary gasoline surrogate in a CAI engine." Combustion and Flame 160, no. 10 (October 2013): 2067–82. http://dx.doi.org/10.1016/j.combustflame.2013.04.029.

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19

Selim, Hatem, Samah Y. Mohamed, Nils Hansen, and S. Mani Sarathy. "Premixed flame chemistry of a gasoline primary reference fuel surrogate." Combustion and Flame 179 (May 2017): 300–311. http://dx.doi.org/10.1016/j.combustflame.2017.02.008.

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20

Andrae, J. C. G. "Development of a detailed kinetic model for gasoline surrogate fuels." Fuel 87, no. 10-11 (August 2008): 2013–22. http://dx.doi.org/10.1016/j.fuel.2007.09.010.

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21

Yuan, Hao, Zhongyuan Chen, Zhenbiao Zhou, Yi Yang, Michael J. Brear, and James E. Anderson. "Formulating gasoline surrogate for emulating octane blending properties with ethanol." Fuel 261 (February 2020): 116243. http://dx.doi.org/10.1016/j.fuel.2019.116243.

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22

Liu, Lei, and Liang Hong. "Nickel phosphide catalyst for autothermal reforming of surrogate gasoline fuel." AIChE Journal 57, no. 11 (February 8, 2011): 3143–52. http://dx.doi.org/10.1002/aic.12505.

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23

Wang, Libing, Zengyang Wu, Ahfaz Ahmed, Jihad A. Badra, S. Mani Sarathy, William L. Roberts, and Tiegang Fang. "Auto-ignition of direct injection spray of light naphtha, primary reference fuels, gasoline and gasoline surrogate." Energy 170 (March 2019): 375–90. http://dx.doi.org/10.1016/j.energy.2018.12.144.

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24

Lemaire, R., E. Therssen, and P. Desgroux. "Effect of ethanol addition in gasoline and gasoline–surrogate on soot formation in turbulent spray flames." Fuel 89, no. 12 (December 2010): 3952–59. http://dx.doi.org/10.1016/j.fuel.2010.06.031.

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25

Sileghem, L., V. A. Alekseev, J. Vancoillie, K. M. Van Geem, E. J. K. Nilsson, S. Verhelst, and A. A. Konnov. "Laminar burning velocity of gasoline and the gasoline surrogate components iso-octane, n-heptane and toluene." Fuel 112 (October 2013): 355–65. http://dx.doi.org/10.1016/j.fuel.2013.05.049.

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26

Zhang, Ling Zhe, Ya Kun Sun, Su Li, and Qing Ping Zheng. "Simulation of HCCI Combustion Characteristics for Low RON Gasoline Surrogate Fuels." Applied Mechanics and Materials 694 (November 2014): 54–58. http://dx.doi.org/10.4028/www.scientific.net/amm.694.54.

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A reduced chemical kinetic model (103species and 468 reactions) for new low-RON(research octane number) gasoline surrogate fuels has been proposed. Simulations explored for ignition delay time have been compared with experimental data in shock tubes at pressure of 10atm-55 atm and temperatue of 600-1400 K (fuel/air equivalence ratio=0.5,1.0,2.0 and EGR rate=0, 20%). The simulation data presented 15% enlargement compared with experiments showed applicability of the new kinetic mode in this work. A combustion simulation model has been build for HCCI(homogeneous charge compression ignition) engine with Chemkin-pro. The effects of different air inlet temperature, inlet pressure, engine speed and the fuel air equivalence ratio on the combustion characteristics of the fuel were researched. The results indicated the combustion in an HCCI engine worked sufficiently with lean mixtures and low speed. Meanwhile the material strength could be influenced when the inlet conditions changed. This helps to promote the low-RON gasoline surrogate fuel application in the HCCI engine.

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27

Yan-Rong, LI, PEI Yi-Qiang, QIN Jing, and ZHANG Miao. "A Reaction Mechanismof Polycyclic Aromatic Hydrocarbons for Gasoline Surrogate Fuels TRF." Acta Physico-Chimica Sinica 30, no. 6 (2014): 1017–26. http://dx.doi.org/10.3866/pku.whxb201401251.

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28

Mehl, Marco, William J. Pitz, Charles K. Westbrook, and Henry J. Curran. "Kinetic modeling of gasoline surrogate components and mixtures under engine conditions." Proceedings of the Combustion Institute 33, no. 1 (2011): 193–200. http://dx.doi.org/10.1016/j.proci.2010.05.027.

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29

Choi, B. C., S. K. Choi, and S. H. Chung. "Soot formation characteristics of gasoline surrogate fuels in counterflow diffusion flames." Proceedings of the Combustion Institute 33, no. 1 (2011): 609–16. http://dx.doi.org/10.1016/j.proci.2010.06.067.

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30

Sarathy, S. Mani, Goutham Kukkadapu, Marco Mehl, Weijing Wang, Tamour Javed, Sungwoo Park, Matthew A. Oehlschlaeger, Aamir Farooq, William J. Pitz, and Chih-Jen Sung. "Ignition of alkane-rich FACE gasoline fuels and their surrogate mixtures." Proceedings of the Combustion Institute 35, no. 1 (2015): 249–57. http://dx.doi.org/10.1016/j.proci.2014.05.122.

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31

Niemeyer, Kyle E., and Chih-Jen Sung. "Reduced Chemistry for a Gasoline Surrogate Valid at Engine-Relevant Conditions." Energy & Fuels 29, no. 2 (January 26, 2015): 1172–85. http://dx.doi.org/10.1021/ef5022126.

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32

Li, Bo, and Yankun Jiang. "Chemical Kinetic Model of a Multicomponent Gasoline Surrogate with Cross Reactions." Energy & Fuels 32, no. 9 (August 20, 2018): 9859–71. http://dx.doi.org/10.1021/acs.energyfuels.8b01330.

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33

Kobashi, Yoshimitsu, Yoshio Zama, and Tatsuya Kuboyama. "Modeling wall film formation and vaporization of a gasoline surrogate fuel." International Journal of Heat and Mass Transfer 147 (February 2020): 119035. http://dx.doi.org/10.1016/j.ijheatmasstransfer.2019.119035.

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34

Frassoldati, A., A. Cuoci, T. Faravelli, and E. Ranzi. "Kinetic Modeling of the Oxidation of Ethanol and Gasoline Surrogate Mixtures." Combustion Science and Technology 182, no. 4-6 (June 10, 2010): 653–67. http://dx.doi.org/10.1080/00102200903466368.

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35

Zhen, Xudong, Yang Wang, and Daming Liu. "An overview of the chemical reaction mechanisms for gasoline surrogate fuels." Applied Thermal Engineering 124 (September 2017): 1257–68. http://dx.doi.org/10.1016/j.applthermaleng.2017.06.101.

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36

Pessina, Valentina, and Massimo Borghi. "Effect of Lagrangian-phase Modelling on Charge Stratification and Spatial Distribution of Threshold Soot Index for Toluene Reference Fuel Surrogates." E3S Web of Conferences 312 (2021): 07007. http://dx.doi.org/10.1051/e3sconf/202131207007.

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Nowadays, soot emissions are one of the major concerns in Direct Injection Spark Ignition engines. Soot prediction models can be computationally expensive, especially when particle mass, number, and size distribution are to be forecast. While soot formation heavily depends on the chemical and physical characteristics of the fuel, the simulation of the exact composition of a real gasoline is computationally unfeasible. Thus, it is essential to find simplified yet representative pathways to reduce the computational cost of the simulations. On the one hand, the a-priori investigation of the factors influencing particulate onset can be a simplified approach to compare different solutions and strategies with much cheaper costs than the modelling of soot formation and oxidation mechanisms. On the other hand, the use of surrogate fuels is a practical approach to cope with the fuel chemical nature. Although they poorly mimic the evaporation properties of a real gasoline, Toluene Reference Fuels are broadly adopted to match combustion relevant properties of the real fuels. In this study, the spatial distribution of the Threshold Soot Index in the fluid domain is investigated for three surrogates characterized by an increasing content of toluene (0 mol%, 30 mol%, 60 mol%). The correlation between the sooting tendency and the fuel distribution in the combustion chamber before spark ignition time can provide useful preliminary indications, without spending the computational effort of the whole soot model multicycle resolution. In particular, two approaches for the lagrangian description of the injected fuel are investigated: a multicomponent approach and a single component one, this last driven by a high-fidelity lumped modelling of the surrogate properties for both liquid and vapor phase.

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37

Tang, Meng, Jiongxun Zhang, Xiucheng Zhu, Kyle Yeakle, Henry Schmidt, Seong-Young Lee, Jeffrey Naber, and Cody Squibb. "Comparison of Direct-Injection Spray Development of E10 Gasoline to a Single and Multi-Component E10 Gasoline Surrogate." SAE International Journal of Fuels and Lubricants 10, no. 2 (March 28, 2017): 352–68. http://dx.doi.org/10.4271/2017-01-0833.

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38

Mehl, M., J. Y. Chen, W. J. Pitz, S. M. Sarathy, and C. K. Westbrook. "An Approach for Formulating Surrogates for Gasoline with Application toward a Reduced Surrogate Mechanism for CFD Engine Modeling." Energy & Fuels 25, no. 11 (November 17, 2011): 5215–23. http://dx.doi.org/10.1021/ef201099y.

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39

Zhao-Lei, ZHENG, and LIANG Zhen-Long. "Reduced Chemical Kinetic Model of a Gasoline Surrogate Fuel for HCCI Combustion." Acta Physico-Chimica Sinica 31, no. 7 (2015): 1265–74. http://dx.doi.org/10.3866/pku.whxb201505131.

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40

Kumar, Rohit, Upasana Priyadarshani Padhi, and Sudarshan Kumar. "Formulating a quaternary gasoline surrogate (MTRF-87) using laminar burning velocity measurements." Fuel 329 (December 2022): 125459. http://dx.doi.org/10.1016/j.fuel.2022.125459.

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41

Lan, Tian, Yiran Wang, Raza Ali, Hui Liu, Xiangyang Liu, and Maogang He. "Prediction and measurement of critical properties of gasoline surrogate fuels and biofuels." Fuel Processing Technology 228 (April 2022): 107156. http://dx.doi.org/10.1016/j.fuproc.2021.107156.

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42

KIUCHI, Shota, Tomoya FUNABASHI, Satoshi SAKAIDA, Kotaro TANAKA, and Mituru KONNO. "Experimental study on ignition characteristics of gasoline surrogate and 2-methylfuran mixture." Proceedings of Mechanical Engineering Congress, Japan 2019 (2019): J07107P. http://dx.doi.org/10.1299/jsmemecj.2019.j07107p.

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43

An, Yan-zhao, Yi-qiang Pei, Jing Qin, Hua Zhao, and Xiang Li. "Kinetic modeling of polycyclic aromatic hydrocarbons formation process for gasoline surrogate fuels." Energy Conversion and Management 100 (August 2015): 249–61. http://dx.doi.org/10.1016/j.enconman.2015.05.013.

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44

Kuwahara, Kazunari, Yoshihiro Ueda, Yasuyuki Sakai, Tsukasa Hori, Tomoyuki Mukayama, Eriko Matsumura, and Jiro Senda. "Empirical Approach to Small-Scale Reaction Mechanism for Regular Gasoline Surrogate Fuel." Proceedings of the International symposium on diagnostics and modeling of combustion in internal combustion engines 2017.9 (2017): A305. http://dx.doi.org/10.1299/jmsesdm.2017.9.a305.

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45

UESAKA, Hirokazu, Ryosuke MATSUI, Satoshi SHIBATA, Hidefumi KATAOKA, and Daisuke SEGAWA. "P035 Study on Laminar burning characteristics of Gasoline surrogate fuel/air mixture." Proceedings of Conference of Kansai Branch 2016.91 (2016): 409. http://dx.doi.org/10.1299/jsmekansai.2016.91.409.

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46

Lenhert, David B., David L. Miller, Nicholas P. Cernansky, and Kevin G. Owens. "The oxidation of a gasoline surrogate in the negative temperature coefficient region." Combustion and Flame 156, no. 3 (March 2009): 549–64. http://dx.doi.org/10.1016/j.combustflame.2008.11.022.

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47

Raj, Abhijeet, Iran David Charry Prada, Amer Ahmad Amer, and Suk Ho Chung. "A reaction mechanism for gasoline surrogate fuels for large polycyclic aromatic hydrocarbons." Combustion and Flame 159, no. 2 (February 2012): 500–515. http://dx.doi.org/10.1016/j.combustflame.2011.08.011.

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48

Fan, Yunchu, Yaozong Duan, Wang Liu, and Dong Han. "Effects of butanol blending on spray auto-ignition of gasoline surrogate fuels." Fuel 260 (January 2020): 116368. http://dx.doi.org/10.1016/j.fuel.2019.116368.

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49

Suzuki, Shunsuke, and William J. Pitz. "Fuel-rich oxidation of gasoline surrogate components in an atmospheric flow reactor." Combustion and Flame 249 (March 2023): 112623. http://dx.doi.org/10.1016/j.combustflame.2023.112623.

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50

Fan, Yunchu, Yaozong Duan, Dong Han, Xinqi Qiao, and Zhen Huang. "Influences of isomeric butanol addition on anti-knock tendency of primary reference fuel and toluene primary reference fuel gasoline surrogates." International Journal of Engine Research 22, no. 1 (May 29, 2019): 39–49. http://dx.doi.org/10.1177/1468087419850704.

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Abstract:

The anti-knock tendency of blends of butanol isomers and two gasoline surrogates (primary reference fuels and toluene primary reference fuels) was studied on a single-cylinder cooperative fuel research engine. The effects of butanol molecular structure (n-butanol, i-butanol, s-butanol and t-butanol) and butanol addition percentage on fuel research octane numbers were investigated. The experimental results revealed that butanol addition to either PRF80 or TPRF80 increased research octane numbers, and the research octane numbers of fuel blends showed higher linearity with the molar percentage than with the volumetric percentage of butanol addition. Furthermore, the research octane number boosting effects of butanol isomers were observed to change with the fuel compositions, that is, i-butanol >s-butanol >n-butanol >t-butanol for primary reference fuels and i-butanol >s-butanol >t-butanol >n-butanol for toluene primary reference fuels. In addition, butanol/primary reference fuel blends exhibited higher research octane numbers than butanol/toluene primary reference fuel blends. We thereafter tried to elucidate the underlying fuel combustion kinetics for the observed anti-knock quality of different butanol/gasoline surrogate blends. It was found that the measured research octane numbers of fuel blends showed the best correlation with the calculated ignition delay times at the thermodynamic condition of 770 K and 2 MPa, and the reaction sensitivity analysis in auto-ignition at this condition revealed that the H-abstraction reactions of butanol isomers by OH radical suppressed fuel reactivity, thus elevating the fuel research octane numbers when butanol was added to the gasoline surrogates. Compared with the butanol/primary reference fuel blends, the positive sensitive reactions related to n-heptane were of higher importance, while the inhibitive effects of sensitive reactions related to butanol and iso-octane decreased for the toluene primary reference fuel/butanol blends, thus leading to lower research octane numbers of the toluene primary reference fuel/butanol blends than those of the butanol/primary reference fuel blends.

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