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The accurate prediction of engine performance maps can guide data-driven optimization of engine technologies to control fuel use and associated emissions. However, engine operational maps are scarcely reported in literature and often have missing data. Assessment of missing-data resilient algorithms in the context of engine data prediction could enable better processing of real-world driving cycles, where missing data is a more pervasive phenomenon. The goal of this study is, therefore, to determine the most effective technique to deal with missing data and employ it in prediction of engine performance characteristics. We assess the performance of two machine learning approaches, namely Artificial Neural Networks (ANNs) and the extreme tree boosting algorithm (XGBoost), in handling missing data.

The transportation industry has been scrutinized for its contribution towards the global greenhouse gas emissions over the years. While the automotive sector has been regulated by strict emission legislation globally, the emissions from marine transportation have been largely neglected. However, during the past decade, the international maritime organization focused on ways to lower the emission intensity of the marine sector by introducing several legislations. This sets limits on the emissions of different oxides of carbon, nitrogen and sulphur, which are emitted in large amounts from heavy fuel oil (HFO) combustion (the primary fuel for the marine sector). A 40% and 70% reduction per transport work compared to the levels of 2008 is set as target for CO2 emission for 2030 and 2050, respectively. To meet these targets, commonly, methanol, as a low-carbon fuel, and ammonia, as a zero-carbon fuel, are considered.

Investigating combustion characteristics of oxygenated gasoline and gasoline blended ethanol is a subject of recent interest. The non-linearity in the interaction of fuel components in the oxygenated gasoline can be studied by developing chemical kinetics of relevant surrogate of fewer components. This work proposes a new reduced four-component (isooctane, heptane, toluene, and ethanol) oxygenated gasoline surrogate mechanism consisting of 67 species and 325 reactions, applicable for dynamic CFD applications in engine combustion and sprays. The model introduces the addition of eight C1-C3 species into the previous model (Li et al; 2019) followed by extensive tuning of reaction rate constants of C7 - C8 chemistry. The current mechanism delivers excellent prediction capabilities in comprehensive combustion applications with an improved performance in lean conditions.

Strict regulations on air pollution motivates clean combustion research for fossil fuels. To numerically mimic real gasoline fuel reactivity, surrogates are proposed to facilitate advanced engine design and predict emissions by chemical kinetic modelling. However, chemical kinetic models could not accurately predict non-regular emissions, e.g. aldehydes, ketones and unsaturated hydrocarbons, which are important air pollutants. In this work, we propose to use machine-learning algorithms to achieve better predictions. Combustion chemistry of fuels constituting of 10 neat fuels, 6 primary reference fuels (PRF) and 6 FGX surrogates were tested in a jet stirred reactor. Experimental data were collected in the same setup to maintain data uniformity and consistency under following conditions: residence time at 1.0 second, fuel concentration at 0.25%, equivalence ratio at 1.0, and temperature range from 750 to 1100K.

The development of highly boosted and high compression spark-ignition engines with enhanced thermal efficiencies is primarily limited by knock and super-knock. Super-knock is an excessively high intensity knock which has been related to a developing detonation process. This study investigates the knocking tendency of different gasoline surrogate fuels with varying research octane numbers (RON), octane sensitivity (S) and composition. The ξ/ɛ diagram with an enclosed detonation peninsula is used to assess the knocking tendency of different fuels. The diagram plots ξ, the ratio of acoustic to auto-ignitive velocity, against ɛ, the ratio of the transit time of an acoustic wave through a hot spot, to the heat release time (τe). Constant volume simulations of auto-ignition delay times (τi) and excitation times (τe) obtained from chemical kinetic calculations, enable calculations of ξ and ɛ.

Pre-ignition remains a significant bottleneck to further downsizing and downspeeding technologies employed for reducing CO2 emissions in modern turbocharged spark-ignited engines. Pre-ignition, which occurs rarely, may lead to high peak pressures that auto-ignite the entire charge before TDC. The resulting high-pressure oscillations are known as super-knock, leading to sudden and permanent hardware damage to the engine. Over the years, numerous researchers have investigated the stochastic phenomenon’s source and concluded that there is a role of lubricant additives, deposits, gasoline properties, and hot surfaces in triggering pre-ignition. No single source has been identified; the research continues. Here, we take a different approach; rather than continue the search for the source(s) of super-knock, we explore mitigating super-knock by detecting pre-ignition early enough to take immediate evasive action.

The improvement of the indicated thermal efficiency of an argon power cycle (replacing nitrogen with argon in the combustion reaction) is investigated in a CFR engine at high compression ratios in homogeneous charge compression ignition (HCCI) mode. The study combines the two effects that can increase the thermodynamic efficiency as predicted by the ideal Otto cycle: high specific heat ratio (provided by argon), and high compression ratios. However, since argon has relatively low heat capacity (at constant volume), it results in high in-cylinder temperatures, which in turn, leads to the occurrence of knock. Knock limits the feasible range of compression ratios and further increasing the compression ratio can cause serious damage to the engine due to the high pressure rise rate caused by advancing the combustion phasing.

Octane-on-Demand (OoD) is a promising technology for reducing greenhouse emissions from automobiles. The concept utilizes a low-octane fuel for low and mid load operating conditions, and a high-octane additive is added at high load operating conditions. Researchers have focused on the minimum ethanol content required for operating at high load conditions when the low-octane fuel becomes knock limited. However, it is also widely known that ethanol has a high tendency to pre-ignite, which has been linked with its high laminar flame speed and surface ignition tendency. Moreover, ethanol has a lower stoichiometric air-fuel ratio, requiring a larger injected fuel mass per cycle. A larger fuel mass increases the potential for oil dilution by the liquid fuel, creating precursors for pre-ignition. Hence, the limits on ethanol addition owing to pre-ignition also need consideration before the technology can be implemented.

Pre-ignition is an abnormal engine combustion phenomenon where the inducted fuel-air charge ignites before the spark ignition. This premature combustion phenomenon often leads to heavy knocking events. The mixture preparation plays a critical role in pre-ignition tendency for a given load. Literature shows efforts made towards improving pre-ignition-limited-IMEP by splitting the injection pulse into multiple pulses. In this study, two direct injectors are used in a single cylinder research engine. A centrally mounted direct injector was used to inject Coryton Gasoline (RON 95) fuel early in the intake stroke. A second fluid was injected late in the compression stroke to suppress pre-ignition. The fluids used in the second direct injector was varied to see the effects of the molecule and its physical and chemical property on pre-ignition suppression tendency. Methanol, ethanol, water, and gasoline were tested as second fluid.

Pre-ignition in modern engines is largely attributed to oil-fuel mixture droplets igniting before the spark timing. Researchers have also found pre-ignition events to be triggered by high hydrocarbon emissions from the previous cycle as well as late spark timing in the previous cycle. Additionally, an ideally scavenged engine was not found to be limited by pre-ignition. These observations point to a significant role of residuals in triggering pre-ignition events. Current work studies pre-ignition in a probabilistic approach. The effect of residuals and in-cylinder thermodynamic state is studied by varying the exhaust back pressure and intake air temperature respectively. Experiments were performed with a fixed mass flow rate of air + fuel and intake air temperature while the exhaust back pressure was varied. Intake air pressure varied in response to fixed intake temperature. Pre-ignition and super-knock count increased with increasing exhaust back pressure.

Knock, and more recently, super-knock, have been limiting factors on improving engine efficiency. As a result, engines often operate rich at high loads to avoid damage resulting from knock and protect the after-treatment system from excessive thermal stress. In this work, port-fuel injection and direct injection of excess fuel is explored as a mechanism to suppress knock and super-knock. Under naturally aspirated conditions, increasing the fuel enrichment initially increases knock intensity. However, further increasing fuel enrichment subsequently decreases knock intensity. The competing mechanism from calorific value and latent heat of vaporization can be used to explain the phenomenon. However, when directly injecting the excess fuel after the spark plug has been fired, knock intensity monotonically decreases with increasing fuel quantity. This decrease is shown to be due to fuel quenching the flame that is propagating from spark location.

Stochastic pre-ignition remains one of the major barriers limiting further engine downsizing and down-speeding; two widely used strategies for improving the efficiency of spark-ignited engines. One of the most cited mechanisms thought to be responsible for pre-ignition is the ignition of a rogue droplet composed of lubricant oil and fuel. This originates during mixture formation from interactions between the fuel spray and oil on the cylinder liner. In the present study, this hypothesis is further examined using a single cylinder supercharged engine which employs a range of air-fuel mixture formation strategies. These strategies include port-fuel injection (PFI) along with side and central direct injection (DI) of an E5 gasoline (RON 97.5) using single and multiple injection events. Computational fluid dynamic (CFD) calculations are then used to explain the observed trends.

Toluene primary reference fuel (TPRF) (mixture of toluene, iso-octane and heptane) is a suitable surrogate to represent a wide spectrum of real fuels with varying octane sensitivity. Investigating different surrogates in engine simulations is a prerequisite to identify the best matching mixture. However, running 3D engine simulations using detailed models is currently impossible and reduction of detailed models is essential. This work presents an AramcoMech reduced kinetic model developed at King Abdullah University of Science and Technology (KAUST) for simulating complex TPRF surrogate blends. A semi-decoupling approach was used together with species and reaction lumping to obtain a reduced kinetic model. The model was widely validated against experimental data including shock tube ignition delay times and premixed laminar flame speeds. Finally, the model was utilized to simulate the combustion of a low reactivity gasoline fuel under partially premixed combustion conditions.

Gasoline compression ignition (GCI) engines are becoming more popular alternative for conventional spark engines to harvest the advantage of high volatility. Recent experimental study demonstrated that high reactivity gasoline fuel can be operated in a conventional mixing controlled combustion mode producing lower soot emissions than that of diesel fuel under similar efficiency and NOx level [1]. Therefore, there is much interest in using gasoline-like fuels in compression ignition engines. In order to improve the fidelity of simulation-based GCI combustion system development, it is mandatory to enhance the prediction of spray combustion of gasoline-like fuels. The purpose of this study is to model the spray characteristics of high reactivity gasoline fuels and validate the models with experimental results obtained through an optically accessible constant volume vessel under vaporizing [2] and reactive conditions [3].

Future internal combustion engines demand higher efficiency but progression towards this is limited by the phenomenon called knock. A possible solution for reaching high efficiency is Octane-on-Demand (OoD), which allows to customize the antiknock quality of a fuel through blending of high-octane fuel with a low octane fuel. Previous studies on Octane-on-Demand highlighted efficiency benefits depending on the combination of low octane fuel with high octane booster. The author recently published works with ethanol and methanol as high-octane fuels. The results of this work showed that the composition and octane number of the low octane fuel is significant for the blending octane number of both ethanol and methanol. This work focuses on toluene as the high octane fuel (RON 120). Aromatics offers anti-knock quality and with high octane number than alcohols, this work will address if toluene can provide higher octane enhancement.

The blending of ethanol with PRF (Primary reference fuel) 84 was investigated and compared with FACE (Fuels for Advanced Combustion Engines) A gasoline surrogate which has a RON of 83.9. Previously, experiments were performed at four HCCI conditions but the chemical effect responsible for the non-linear blending behavior of ethanol with PRF 84 and FACE A was not understood. Hence, in this study the experimental measurements were simulated using zero-dimensional HCCI engine model with detailed chemistry in CHEMKIN PRO. Ethanol was used as an octane booster for the above two base fuels in volume concentration of 0%, 2%, 5% and 10%. The geometrical data and the intake valve closure conditions were used to match the simulated combustion phasing with the experiments. Low temperature heat release (LTHR) was detected by performing heat release analysis.

Low-temperature gasoline combustion (LTGC) has the potential to provide gasoline-fueled engines with efficiencies at or above those of diesel engines and extremely low NOx and particulate emissions. Three key performance goals for LTGC are to obtain high loads, reduce the boost levels required for these loads, and achieve high thermal efficiencies (TEs). This paper reports the results of an experimental investigation into the use of partial fuel stratification, produced using early direct fuel injection (Early-DI PFS), and an increased compression ratio (CR) to achieve significant improvements in these performance characteristics. The experiments were conducted in a 0.98-liter single-cylinder research engine. Increasing the CR from 14:1 to 16:1 produced a nominal increase in the TE of about one TE percentage unit for both premixed and Early-DI PFS operation.

Increasing the anti-knock quality of gasoline fuels can enable higher efficiency in spark ignition engines. In this study, the blending anti-knock quality of dicyclopentadiene (DCPD), a by-product of ethylene production from naphtha cracking, with various gasoline fuels is explored. The blends were tested in an ignition quality tester (IQT) and a modified cooperative fuel research (CFR) engine operating under homogenous charge compression ignition (HCCI) and knock limited spark advance (KLSA) conditions. Due to current fuel regulations, ethanol is widely used as a gasoline blending component in many markets. In addition, ethanol is widely used as a fuel and literature verifying its performance. Moreover, because ethanol exhibits synergistic effects, the test results of DCPD-gasoline blends were compared to those of ethanol-gasoline blends. The experiments conducted in this work enabled the screening of DCPD auto-ignition characteristics across a range of combustion modes.

The blending of ethanol with primary reference fuel (PRF) mixtures comprising n-heptane and iso-octane is known to exhibit a non-linear octane response; however, the underlying chemistry and intermolecular interactions are poorly understood. Well-designed experiments and numerical simulations are required to understand these blending effects and the chemical kinetic phenomenon responsible for them. To this end, HCCI engine experiments were previously performed at four different conditions of intake temperature and engine speed for various PRF/ethanol mixtures. Transfer functions were developed in the HCCI engine to relate PRF mixture composition to autoignition tendency at various compression ratios. The HCCI blending octane number (BON) was determined for mixtures of 2-20 vol % ethanol with PRF70. In the present work, the experimental conditions were considered to perform zero-dimensional HCCI engine simulations with detailed chemical kinetics for ethanol/PRF blends.

Gasoline-ethanol-methanol (GEM) blends, with constant stoichiometric air-to-fuel ratio (iso-stoichiometric blending rule) and equivalent to binary gasoline-ethanol blends (E2, E5, E10 and E15 in % vol.), were defined to investigate the effect of methanol and combined mixtures of ethanol and methanol when blended with three FACE (Fuels for Advanced Combustion Engines) Gasolines, I, J and A corresponding to RON 70.2, 73.8 and 83.9, respectively, and their corresponding Primary Reference Fuels (PRFs). A Cooperative Fuel Research (CFR) engine was used under Spark Ignition and Homogeneous Charge Compression Ignited modes. An ignition quality tester was utilized in the Compression Ignition mode. One of the promising properties of GEM blends, which are derived using the iso-stoichiometric blending rule, is that they maintain a constant octane number, which has led to the introduction of methanol as a drop-in fuel to supplement bio-derived ethanol.