Fuels For Advanced Combustion Engines Research Articles

Effects of knock intensity measurement technique and fuel chemical composition on the research octane number (RON) of FACE gasolines: Part 2 – Effects of spark timing

The Research and Motor Octane Number (RON, MON) characterize a fuel’s knock resistance by rating the knock intensity of a sample fuel relative to that of Primary Reference Fuels (PRF) in a Cooperative Fuel Research (CFR) Engine. A fuel’s octane number is regulated to prevent damage from autoignition leading to knocking combustion in spark-ignition engines. The operational differences between the standard RON rating and modern engine operation are explored in a three-part publication series. The previous study focused on the effects of lambda and knock characterization. This second study primarily focuses on the effects of spark timing on RON determination. Following the findings from the first publication, the knock intensity was captured by the knockmeter and by the maximum amplitude of pressure oscillations (MAPO) at the lambda of peak knock intensity and stoichiometry. Knock-limited spark advance tests were conducted for a set of seven Fuels for Advanced Combustion Engines (FACE) from the Coordinating Research Council (CRC) with varying chemical composition, PRFs, and Toluene Standardization Fuels (TSFs). For retarded spark timings, pre-spark low-temperature heat release was found for low RON PRFs. Low RON PRFs also showed knocking characteristics before reaching the center of combustion suggesting that the use of knock-limited spark advance (KLSA) was preferred over the knock-limited combustion phasing. Primarily paraffinic fuels tended towards increased pressure oscillations while dominantly aromatic fuels experienced higher pressure rise rates. A MAPO-based KLSA correlated best to Octane Index at a negative K-factor suggesting beyond RON operation despite being at otherwise RON conditions. At stoichiometry, the MAPO-based KLSA did neither correlate to RON nor Octane Index. Good agreement was found between KLSA-based effective RON from this study to the MAPO-based effective RON from the first study.

Understanding of the octane response of gasoline/MTBE blends

Despite the wide utilization of MTBE as an octane booster for market gasoline fuels, the blending characteristics of methyl tert-butyl ether (MTBE) with gasoline fuels are not fully understood. This arises from the lack of octane number measurement of MTBE/gasoline blends, along with lack of detailed analyses of MTBE blending characteristics. In an attempt to address the knowledge gap in MTBE blending, this study provides new research octane number (RON) and motor octane number (MON) measurements of MTBE blended with various pure components and gasoline fuels. The first set of blends were binary mixtures of pure components blended with MTBE. The pure components we chosen to represent PIONA (paraffins, iso-paraffins, olefins, naphthenes and aromatics) molecular classes. The second set of blends were Fuels for Advanced Combustion Engines (FACE) and market gasoline fuels with MTBE. It was observed that the addition of MTBE to n-paraffins, iso-paraffins and olefins results in synergistic octane number effect while linear-by-volume and antagonistic blending was observed for MTBE blends with naphthenes and aromatics, respectively. The octane numbers and response of gasoline/MTBE blends are also dependent on the composition of the base gasoline fuel. These new measurements along with literature dataset were utilized to develop octane predictive models for MTBE blended with gasoline fuels. Various blending rules such as linear-by-volume (LBV), octane sensitivity (OS) and PIONA based models were developed in this work. The most accurate model was the linear-by-volume with the iso-paraffins and aromatics terms where more than 80% of the predictions are within the experimental reproducibility limits. The model can be used to predict and quantify the characteristics of octane boost caused by MTBE addition to gasoline fuels. It can also be used to optimize the octane boost due to the addition of MTBE by changing the composition of the base gasoline fuel.

Investigation on the ignition delay prediction model of multi-component surrogates based on back propagation (BP) neural network

The ignition delay prediction model of three-component surrogates was established based on the back propagation (BP) neural network. The ambient temperature, ambient pressure, molar fraction of n-heptane, iso-octane and toluene were utilized as the input parameters. The ignition delay was utilized as the output parameter. The training and validation set only contained the 0-D simulation ignition delay of single- and two-component surrogates. But the trained BP neural network also showed a strong predictive ability towards the ignition delay of three component toluene primary reference fuel (TPRF) surrogates. Results show that the BP neural network with two hidden layers performs better than that with single hidden layer. With the optimization of genetic algorithm (GA) and particle swarm optimization (PSO) algorithm, the correlation coefficient is higher than 0.9996. The mean relative error (MRE) and the mean square error (MSE) are also maintained at a low level. The computational costs of 0-D simulation and BP neural network methods are compared. In 0-D simulation, the computational time of one case is 28 s. When the BP neural network is utilized, the computational time of 176 cases is just 3.2 s, which shows a significant improvement in the computation time. Through the mean impact value (MIV) analysis, the significance of each input variable to the output results is investigated. The input parameters of ambient temperature and molar fraction of iso-octane obtain the highest and lowest absolute value of MIV, respectively, indicating the major and minor effects on the ignition delay. Based on the predicted ignition delay of three-component TPRF surrogates, the research octane number (RON) and motor octane number (MON) can also be accurately predicted with the maximum deviance no more than 3 units. For real fuels of fuels for advanced combustion engines (FACE) gasolines, such as FACE A and FACE C gasolines, the surrogate fuel which has the same ignition delay at the specific pressure and temperature can be determined through the construction of the ignition delay look-up table of TPRF surrogates by the BP neural network. Following this method, the ignition delay of the real fuels can be matched accurately and the molar fraction of each component of the corresponding TPRF surrogates can also be acquired.

Experimental and Kinetic Modeling Study of 3-Methyl-2-butenol (Prenol) Oxidation

Longer chain alcohols with 4–5 carbon atoms are attractive alternative fuels as they can be derived from biological sources and since their combustion leads to lower exhaust gas levels of NOx and soot compared to commercial fossil fuels. The auto-ignition behavior of fuels that contain both a hydroxyl group and a C═C double bond in their molecular structure is not well established in the literature. Understanding the influence of these functional groups on the ignition behavior of fuels is critical in the development of tailor-made fuels for advanced combustion engines. In this study, ignition delay times of an unsaturated alcohol, 3-methyl-2-butenol (prenol), are measured using a high-pressure shock tube and a rapid compression machine at pressures of 15 and 30 bar at equivalence ratios of 0.5, 1.0, and 2.0 in “air” in the temperature range 600–1400 K. A detailed kinetic model is developed and validated using the new experimental data in this study. In addition, speciation data in a jet-stirred reactor, ignition delay times, and laminar burning velocities available in the literature were also used to validate the new kinetic model. Fuel flux and sensitivity analyses are performed using this new model to determine the important fuel consumption pathways and critical reactions that affect the reactivity of prenol.

Unraveling the octane response of gasoline/ethanol blends: Paving the way to formulating gasoline surrogates

Ethanol is widely used as a gasoline octane booster, and yet, its blending response is not fully understood. Blending ethanol with gasoline most often leads to a synergistic effect (higher than expected relative to linear blending), but can also lead to a linear or antagonistic blending (lower than expected relative to linear blending). To address the knowledges gap in ethanol blending, this study provides new research octane number (RON) and motor octane number (MON) measurements of ethanol blended with various gasoline surrogates. The first set of blends are ternary mixtures, designed to study the interactions between primary reference fuels (PRFs) and certain gasoline components when blended with ethanol. These gasoline components are 1-hexene, 1,2,4-trimethylbenzene and cyclopentane, which, represents the olefin, aromatic and naphthenes classes in commercial gasoline fuels, respectively. The second set represents multicomponent surrogates for Fuels for Advanced Combustion Engines (FACE) gasolines, developed in our previous work (Badra et al., Applied Energy 2017 p. 778-793). This study developes an octane blending model of ethanol/gasoline surrogates that utilize the new measurements along with datasets available in literature. The model consists of the conventional linear by ethanol molar fraction correlation, with the addition of non-linearity terms that depend on base fuel properties, namely, the octane sensitivity and the mole fraction of gasoline components. The model can predict the octane numbers (RON and MON) of blends containing gasoline surrogates composed of n-heptane, n-pentane, iso-octane, iso-pentane, toluene, 124-trimethylbenzene, cyclopentane, cyclohexane (for RON only) and 1-hexene. To ensure the generality of the developed model and avoid over-fitting, the model is trained using 85% of the available dataset while the remaining measurements have been used to test the model. The proposed model outperforms many ethanol blending models available in literature with 87% of the RON and 83% of the MON measurements being within the reproducibility limits. This model can be integrated to the process of designing gasoline surrogates that contain ethanol.

Effects of knock intensity measurement technique and fuel chemical composition on the research octane number (RON) of FACE gasolines: Part 1 – Lambda and knock characterization

The Research and Motor Octane Number (RON and MON) rate the knock propensity of gasoline in the Cooperative Fuel Research (CFR) engine by comparing the knock intensity of sample fuels relative to that of primary reference fuels (PRF), a binary blend of iso-octane and n-heptane. Important differences exist between standard octane testing and automotive spark ignition (SI) engine knock testing including speed, load, air-to-fuel equivalence ratio (lambda), and knock characterization, which lead to a discrepancy between a fuel’s RON rating and its knock resistance characterized on an automotive SI engine based on knock-limited spark advance. This is the first of a set of three publications which modify operating parameters of the RON test method (ASTM D2699) to investigate the effects of these differences with automotive SI engine knock-limited spark advance testing. A fuel’s standard RON is evaluated at the lambda of the highest knock intensity, whereas automotive SI engines typically operate at stoichiometry. This study analyzes the effects of a stoichiometric RON rating methodology. Additionally, the knock intensity response from the standard CFR knockmeter system is compared to a cylinder pressure oscillation-based knock intensity at several lambda settings. All experiments were performed with a set of seven Coordinating Research Council (CRC) Fuels for Advanced Combustion Engines (FACE) gasolines with approximately 95 RON. The fuel chemical composition impacted the lambda of the highest knock intensity, which resulted in fuel-specific offsets between the standard and stoichiometric RON ratings. The knock system comparison showed significant offsets between cylinder pressure-based and knockmeter-based knock intensity levels.

Investigation on the influence of initial thermodynamic conditions and fuel compositions on gasoline octane number based on a data-driven approach

The objective of this work is to clarify the influence mechanism of initial thermodynamic conditions and fuel chemistry on gasoline’s octane numbers (ON), including research octane number (RON) and motor octane number (MON). Investigated fuels include three kinds of well-characterized gasoline, FACE (Fuels for Advanced Combustion Engines) A, C and J, which were simplified as toluene primary reference (TRF) mixtures in this work. The parameters of interest cover initial thermodynamic environment parameters and the ratios of each composition in gasoline. A hybrid analysis framework, combining the transient tracking method, data-driven modeling algorithm, global sensitivity and reaction analysis, was proposed to realize the fast forward prediction and analysis on fuel’s ONs. The effectiveness of this framework was verified by comparing with two empirical correlations. Different data-driven algorithms were fully compared to determine the optimal ON modeling scheme. The polynomial chaos expansion approach has proved to be the best modeling choice, which could substantially reduce computational costs by 2 orders of magnitude in comparison with the sampling-based method (SBM) for predicting ONs with a satisfactory accuracy (greater than 0.985). Global sensitivity analysis showed the initial thermodynamic parameters had more impact on fuel’s ONs than fuel compositions, while the chemical reasons provided by the reaction analysis. Furthermore, a slight change in fuel composition was found could result in a complex shift of reaction pathways of small-molecules under both RON/MON test standards. Therefore, it is suggested that a rigorous influence analysis should be conducted before new gasoline-like fuel is applied.

Counterflow ignition and extinction of FACE gasoline fuels

The demand for petroleum-derived gasoline in the transportation sector is on the rise. For better knowledge of gasoline combustion in practical combustion systems, this study presents experimental measurements and numerical prediction of autoignition temperatures and extinction limits of six FACE (fuels for advanced combustion engines) gasoline fuels in counterflow flames. Extinction limits were measured at atmospheric pressures while the experiments for autoignition temperatures were carried out at atmospheric and high pressures. For atmospheric pressure experiment, the fuel stream consists of the pre-vaporized fuel diluted with nitrogen, while a condensed fuel configuration is used for ignition experiment at higher chamber pressures. The oxidizer stream is pure air. Autoignition temperatures of the tested fuels are nearly the same at atmospheric pressure, while a huge difference is observed as the pressure is increased. Unlike the ignition temperatures at atmospheric pressures, minor difference exists in the extinction limits of the tested fuels. Simulations were carried out using a recently developed gasoline surrogate model. Both multi-component and n-heptane/isooctane mixtures were used as surrogates for the simulations. Overall, the n-heptane/isooctane surrogate mixtures are consistently more reactive as compared the multi-component surrogate mixtures. Transport weighted enthalpy and radical index analysis was used to explain the differences in extinction strain rates for the various fuels.

The influence of chemical composition on ignition delay times of gasoline fractions

Tailoring fuel properties to maximize the efficiency of internal combustion engines is a way towards achieving cleaner combustion systems. In this work, the ignition properties along with the chemical composition (expressed as functional groups) of various light distillate (e.g., gasoline) cuts were analyzed to better understand the properties of full boiling range fuels. Various distillation cuts were obtained with a spinning band distillation system, which were then tested in an ignition quality tester (IQT) to obtain their global chemical reactivity (i.e., ignition delay time (IDT)). The distillates were further analyzed with 1H nuclear magnetic resonance (NMR) spectroscopy to identify and quantify various functional groups present in them. Various gasolines of research grade with specific target properties set forth by the Coordinating Research Council (CRC) that are known as FACE (fuels for advanced combustion engines) gasolines were distilled. When fuels with low aromatic content were distilled, the higher boiling point (BP) range (i.e., higher molecular weight) fractions exhibited lower IDT. However, distilled fractions of fuels with high aromatic content showed an initial decrease in IDT with increasing BP, followed by drastic increase in IDT primarily due to increasing aromatic groups. This study provides an understanding of the contribution of various volatile fractions to the IDTs of a multicomponent fuel, which is of relevance to fuel stratification utilized in gasoline compression ignition (GCI) engines to tailor heat release rates.

Predicting fuel low-temperature combustion performance using Fourier-transform infrared absorption spectra of neat hydrocarbons

This work uses support vector machine regression to correlate infrared absorption spectra to a metric representing low temperature combustion engine (LTC) performance, the LTC index: a singular value encapsulating achievable engine loads, combustion phasing, and efficiency. 313 total fuels informed the model, including mixtures and surrogate gasoline fuels containing n-heptane, isooctane (i.e., 2,2,4-trimethylpentane), toluene, ethanol, methylcyclohexane, xylene(s), 2-methybutane, and 2-methylhexane. We predicted LTC indices of the FACE (Fuels for Advanced Combustion Engines) gasolines A–J within ±6.0 units. The proposed methodology can be used to both predict gasoline LTC performance and also identify important hydrocarbon components that most improve (or reduce) LTC engine performance.

Surrogate definition and homogeneous chemical kinetic model for two alkane-rich FACE gasoline fuels

A surrogate formulation methodology is proposed by directly using functional groups , , , and phenyl to build the surrogate models for the FACE (fuels for advanced combustion engines) A and C gasoline fuels. The surrogates were formulated with the mixture of n-butane/n-heptane/iso-octane/2,5-dimethylhexane for FACE A, and with the mixture of n-butane/n-heptane/iso-octane/2,5-dimethylhexane/toluene for FACE C gasoline fuel. Based on the kinetic mechanisms of the candidate components, the surrogate fuel models were assembled through a hierarchical construction way. In order to get a simpler surrogate model, the detailed mechanism of 2,5-dimethylhexane has been reduced by the path flux analysis (PFA) method and optimised by updating the reaction rate constants of selected reactions before the surrogated fuel model construction. Thereafter, the accuracy of the surrogate models was demonstrated by comparing the model predictions against ignition delay measurements for FACE A and C gasoline fuels in a wide range of conditions (10–40 bar; 0.5–1 equivalence ratios), and the results show that the presented surrogate fuel models can reproduce the ignition behaviours better especially in the low-temperature conditions. The surrogate chemical kinetic model construction method can be used in other fuels to get simpler and lower computational cost surrogate fuel models.

Auto-ignition study of FACE gasoline and its surrogates at advanced IC engine conditions

Robust surrogate formulation for gasoline fuels is challenging, especially in mimicking auto-ignition behavior observed under advanced combustion strategies including boosted spark-ignition and advanced compression ignition. This work experimentally quantifies the auto-ignition behavior of bi- and multi-component surrogates formulated to represent a mid-octane (Anti-Knock Index 91.5), full boiling-range, research grade gasoline (Fuels for Advanced Combustion Engines, FACE-F). A twin-piston rapid compression machine is used to achieve temperature and pressure conditions representative of in-cylinder engine operation. Changes in low- and intermediate-temperature behavior, including first-stage and main ignition times, are quantified for the surrogates and compared to the gasoline. This study identifies significant discrepancies in the first-stage ignition behavior, the influence of pressure for the bi- to ternary blends, and highlights that better agreement is achieved with multi-component surrogates, particularly at lower temperature regimes. A recently-updated detailed kinetic model for gasoline surrogates is also used to simulate the measurements. Sensitivity analysis is employed to interpret the kinetic pathways responsible for reactivity trends in each gasoline surrogate.

Predicting Octane Number Using Nuclear Magnetic Resonance Spectroscopy and Artificial Neural Networks

Machine learning algorithms are attracting significant interest for predicting complex chemical phenomenon. In this work, a model to predict research octane number (RON) and motor octane number (MON) of pure hydrocarbons, hydrocarbon-ethanol blends, and gasoline–ethanol blends has been developed using artificial neural networks (ANNs) and molecular parameters from 1H nuclear magnetic resonance (NMR) spectroscopy. RON and MON of 128 pure hydrocarbons, 123 hydrocarbon–ethanol blends of known composition, and 30 FACE (fuels for advanced combustion engines) gasoline–ethanol blends were utilized as a data set to develop the ANN model. The effect of weight percent of seven functional groups including paraffinic CH3 groups, paraffinic CH2 groups, paraffinic CH groups, olefinic −CH═CH2 groups, naphthenic CH–CH2 groups, aromatic C–CH groups, and ethanolic OH groups on RON and MON was studied. The effect of branching (i.e., methyl substitution), denoted by a parameter termed as branching index (BI), and molecular w...

A minimalist functional group (MFG) approach for surrogate fuel formulation

Surrogate fuel formulation has drawn significant interest due to its relevance towards understanding combustion properties of complex fuel mixtures. In this work, we present a novel approach for surrogate fuel formulation by matching target fuel functional groups, while minimizing the number of surrogate species. Five key functional groups; paraffinic CH3, paraffinic CH2, paraffinic CH, naphthenic CHCH2 and aromatic CCH groups in addition to structural information provided by the Branching Index (BI) were chosen as matching targets. Surrogates were developed for six FACE (Fuels for Advanced Combustion Engines) gasoline target fuels, namely FACE A, C, F, G, I and J. The five functional groups present in the fuels were qualitatively and quantitatively identified using high resolution 1H Nuclear Magnetic Resonance (NMR) spectroscopy. A further constraint was imposed in limiting the number of surrogate components to a maximum of two. This simplifies the process of surrogate formulation, facilitates surrogate testing, and significantly reduces the size and time involved in developing chemical kinetic models by reducing the number of thermochemical and kinetic parameters requiring estimation. Fewer species also reduces the computational expenses involved in simulating combustion in practical devices. The proposed surrogate formulation methodology is denoted as the Minimalist Functional Group (MFG) approach. The MFG surrogates were experimentally tested against their target fuels using Ignition Delay Times (IDT) measured in an Ignition Quality Tester (IQT), as specified by the standard ASTM D6890 methodology, and in a Rapid Compression Machine (RCM). Threshold Sooting Index (TSI) and Smoke Point (SP) measurements were also performed to determine the sooting propensities of the surrogates and target fuels. The results showed that MFG surrogates were able to reproduce the aforementioned combustion properties of the target FACE gasolines across a wide range of conditions. The present MFG approach supports existing literature demonstrating that key functional groups are responsible for the occurrence of complex combustion properties. The functional group approach offers a method of understanding the combustion properties of complex mixtures in a manner which is independent, yet complementary, to detailed chemical kinetic models. The MFG approach may be readily extended to formulate surrogates for other complex fuels.

Influence of Ethanol and Exhaust Gas Recirculation on Laminar Burning Behaviors of Fuels for Advanced Combustion Engines (FACE-C) Gasoline and Its Surrogate

Laminar burning velocities of fuels for advanced combustion engines (FACE-C) gasoline and a surrogate comprising toluene primary reference fuels (TPRFs) were investigated under the effects of exhaust gas recirculation (EGR) dilution and ethanol blending. Measurements were conducted in a spherical constant volume combustion chamber for a range of equivalence ratios from 0.8 to 1.6 at initial temperatures and pressures up to 383 K and 0.6 MPa, respectively. These measurements highlighted the effects of real combustion residuals (using combustion products directly) at mole fractions up to 0.3 and various volumetric percentages of ethanol blending. For both studied fuels, significant reductions in stretched and unstretched flame speeds were observed for mixtures laden with real combustion residuals. Blends with less than 50% ethanol showed barely a minimal enhancement in the flame speed. By combining both EGR and ethanol blending, the flame speed reduction by EGR can be compensated for with ethanol addition. ...

Ignition studies of two low-octane gasolines

Low-octane gasolines (RON ∼ 50–70 range) are prospective fuels for gasoline compression ignition (GCI) internal combustion engines. GCI technology utilizing low-octane fuels has the potential to significantly improve well-to-wheel efficiency and reduce the transportation sector's environmental footprint by offsetting diesel fuel usage in compression ignition engines. In this study, ignition delay times of two low-octane FACE (Fuels for Advanced Combustion Engines) gasolines, FACE I and FACE J, were measured in a shock tube and a rapid compression machine over a broad range of engine-relevant conditions (650–1200 K, 20 and 40 bar and ϕ = 0.5 and 1). The two gasolines are of similar octane ratings with anti-knock index, AKI = (RON + MON)/2, of ∼ 70 and sensitivity, S = RON–MON, of ∼ 3. However, the molecular compositions of the two gasolines are notably different. Experimental ignition delay time results showed that the two gasolines exhibited similar reactivity over a wide range of test conditions. Furthermore, ignition delay times of a primary reference fuel (PRF) surrogate (n-heptane/iso-octane blend), having the same AKI as the FACE gasolines, captured the ignition behavior of these gasolines with some minor discrepancies at low temperatures (T < 700 K). Multi-component surrogates, formulated by matching the octane ratings and compositions of the two gasolines, emulated the autoignition behavior of gasolines from high to low temperatures. Homogeneous charge compression ignition (HCCI) engine simulations were used to show that the PRF and multi-component surrogates exhibited similar combustion phasing over a wide range of engine operating conditions.

On the effects of fuel properties and injection timing in partially premixed compression ignition of low octane fuels

A better understanding on the effects of fuel properties and injection timing is required to improve the performance of advanced engines based on low temperature combustion concepts. In this work, an experimental and computational study was conducted to investigate the effects of physical and chemical kinetic properties of low octane fuels and their surrogates in partially premixed compression ignition (PPCI) engines. The main objective was to identify the relative importance of physical versus chemical kinetic properties in predicting practical fuel combustion behavior across a range of injection timings. Two fuel/surrogate pairs were chosen for comparison: light naphtha (LN) versus the primary reference fuel (PRF) with research octane number of 65 (PRF 65), and FACE (fuels for advanced combustion engines) I gasoline versus PRF 70. Two sets of parametric studies were conducted: the first varied the amount of injected fuel mass at different injection timings to match a fixed combustion phasing, and the second maintained the same injected fuel mass at each injection timing to assess resulting combustion phasing changes. Full-cycle computational fluid dynamic engine simulations were conducted by accounting for differences in the physical properties of the original and surrogate fuels, while employing identical chemical kinetics. The simulations were found to capture trends observed in the experiments, while providing details on spatial mixing and chemical reactivity for different fuels and injection timings. It was found that differences in physical properties become increasingly important as injection timing was progressively delayed from premixed conditions, and this was rationalized by analysis of mixture stratification patterns resulting from injection of fuels with different physical properties. The results suggest that accurate descriptions of both physical and chemical behavior of fuels are critical in predictive simulations of PPCI engines for a wide range of injection timings.

Relating the octane numbers of fuels to ignition delay times measured in an ignition quality tester (IQT)

A methodology for estimating the octane index (OI), the research octane number (RON) and the motor octane number (MON) using ignition delay times from a constant volume combustion chamber with liquid fuel injection is proposed by adopting an ignition quality tester. A baseline data of ignition delay times were determined using an ignition quality tester at a charge pressure of 21.3bar between 770 and 850K and an equivalence ratio of 0.7 for various primary reference fuels (PRFs, mixtures of iso-octane and n-heptane). Our methodology was developed using ignition delay times for toluene reference fuels (mixtures of toluene and n-heptane). A correlation between the OI and the ignition delay time at the initial charge temperature enabled the OI of non-PRFs to be predicted at specified temperatures. The methodology was validated using ignition delay times for toluene primary reference fuels (ternary mixtures of toluene, iso-octane, and n-heptane), fuels for advanced combustion engines (FACE) gasolines, and certification gasolines. Using this methodology, the RON, the MON, and the octane sensitivity were estimated in agreement with values obtained from standard test methods. A correlation between derived cetane number and RON is also provided.

Jet-stirred reactor oxidation of alkane-rich FACE gasoline fuels

Understanding species evolution upon gasoline fuel oxidation can aid in mitigating harmful emissions and improving combustion efficiency. Experimentally measured speciation profiles are also important targets for surrogate fuel kinetic models. This work presents the low- and high-temperature oxidation of two alkane-rich FACE gasolines (A and C, Fuels for Advanced Combustion Engines) in a jet-stirred reactor at 10bar and equivalence ratios from 0.5 to 2 by probe sampling combined with gas chromatography and Fourier Transformed Infrared Spectrometry analysis. Detailed speciation profiles as a function of temperature are presented and compared to understand the combustion chemistry of these two real fuels. Simulations were conducted using three surrogates (i.e., FGA2, FGC2, and FRF 84), which have similar physical and chemical properties as the two gasolines. The experimental results reveal that the reactivity and major product distributions of these two alkane-rich FACE fuels are very similar, indicating that they have similar global reactivity despite their different compositions. The simulation results using all the surrogates capture the two-stage oxidation behavior of the two FACE gasolines, but the extent of low temperature reactivity is over-predicted. The simulations were analyzed, with a focus on the n-heptane and n-butane sub-mechanisms, to help direct the future model development and surrogate fuel formulation strategies.

Compositional effects on the ignition of FACE gasolines

As regulatory measures for improved fuel economy and decreased emissions are pushing gasoline engine combustion technologies towards extreme conditions (i.e., boosted and intercooled intake with exhaust gas recirculation), fuel ignition characteristics become increasingly important for enabling stable operation. This study explores the effects of chemical composition on the fundamental ignition behavior of gasoline fuels. Two well-characterized, high-octane, non-oxygenated FACE (Fuels for Advanced Combustion Engines) gasolines, FACE F and FACE G, having similar antiknock indices but different octane sensitivities and chemical compositions are studied. Ignition experiments were conducted in shock tubes and a rapid compression machine (RCM) at nominal pressures of 20 and 40atm, equivalence ratios of 0.5 and 1.0, and temperatures ranging from 650 to 1270K. Results at temperatures above 900K indicate that ignition delay time is similar for these fuels. However, RCM measurements below 900K demonstrate a stronger negative temperature coefficient behavior for FACE F gasoline having lower octane sensitivity. In addition, RCM pressure profiles under two-stage ignition conditions illustrate that the magnitude of low-temperature heat release (LTHR) increases with decreasing fuel octane sensitivity. However, intermediate-temperature heat release is shown to increase as fuel octane sensitivity increases. Various surrogate fuel mixtures were formulated to conduct chemical kinetic modeling, and complex multicomponent surrogate mixtures were shown to reproduce experimentally observed trends better than simpler two- and three-component mixtures composed of n-heptane, iso-octane, and toluene. Measurements in a Cooperative Fuels Research (CFR) engine demonstrated that the multicomponent surrogates accurately captured the antiknock quality of the FACE gasolines. Simulations were performed using multicomponent surrogates for FACE F and G to reveal the underlying chemical kinetics linking fuel composition with ignition characteristics. A key discovery of this work is the kinetic coupling between aromatics and naphthenes, which affects the radical pool population and thereby controls ignition.