Search Results

The global need for de-carbonization and stringent emission regulations are pushing the current engine research toward alternative fuels. Previous studies have shown that the uHC, CO, and CO2 emissions are greatly reduced and brake thermal efficiency increases with an increase in hydrogen concentration in methane-hydrogen blends for the richer mixture compositions. However, the combustion suffers from high NOx emissions. While these trends are well established, there is limited information on a detailed optical study on the effect of air-excess ratio for different methane-hydrogen mixtures. In the present study, experimental investigations of different methane-hydrogen blends between 0 and 100% hydrogen concentration by volume for the air-excess ratio of 1, 1.4, 1.8, and 2.2 were conducted in a heavy-duty optical diesel engine converted to spark-ignition operation. The engine was equipped with a flat-shaped optical piston to allow bottom-view imaging of the combustion chamber.

In modern compression ignition engines, the dense liquid fuel is directly injected into high pressure and temperature atmosphere, so the spray transitions from subcritical to supercritical conditions. To gain better control of the spray-combustion heat release process, it is important to have a physically accurate description of the spray development process. This work explored the effect of real-fluid thermodynamics in the computational prediction of multiphase flow for two non-ideal situations: the cryogenic nitrogen and non-cryogenic n-dodecane and ammonia sprays. Three real-fluid equations of state (EoS) such as the Soave-Redlich-Kwong (SRK), Peng-Robinson (PR), and Redlich-Kwong-Peng-Robinson (RKPR) coupled with the real-fluid Chung transport model were implemented in OpenFoam to predict the real-fluid thermodynamic properties. Validations against the CoolProp database were conducted.

Compared to conventional diesel combustion (CDC), isobaric combustion can achieve higher thermal efficiency while lowering heat transfer losses and nitrogen oxides (NOx). However, isobaric combustion suffers from higher soot emissions. While the aforementioned trends are well established, there is limited literature about the high-temperature reaction zones, the liquid-phase penetration distance, and the flame tip propagation velocity of isobaric combustion. In the present study, the line-of-sight integrated imaging of Mie-scattering, combustion luminosity, and CH* chemiluminescence were conducted in an optically accessible single-cylinder heavy-duty diesel engine. The engine was equipped with a flat-bowl-shaped optical piston to allow bottom-view imaging of the combustion chamber. The experiments were conducted using n-heptane fuel for CDC and isobaric combustion modes.

The study showcases the strength of machine learning (ML) models in imitating the operation of an advanced engine concept - the gasoline compression ignition (GCI) - at low loads. The GCI engine is prone to exceeding the limits of criteria emissions at such loads, especially at the cold start when the catalyst is not activated. One proposition to accelerate catalyst light-off is using spark-ignition. This, however, adds an extra level of complexity in identifying an optimum operation point. The ML models can be a useful tool in guiding the engine calibration process. In this study, the ML models are trained on GCI engine experiments, covering different intake conditions, injection strategies, and spark settings. The models can predict seven engine performance parameters: fuel consumption, four engine-out emissions, exhaust temperature, and coefficient of variation (COV) in indicated mean effective pressure (IMEP).

Compared to conventional diesel combustion (CDC), isobaric combustion can achieve a similar or higher indicated efficiency, lower heat transfer losses, reduced nitrogen oxides (NOx) emissions; however, with a penalty of soot emissions. While the engine performance and exhaust emissions of isobaric combustion are well known, the overall flame development, in particular, the flow-field details within the flames are unclear. In this study, the performance analysis of CDC and two isobaric combustion cases was conducted, followed by high-speed imaging of Mie-scattering and soot luminosity in an optically accessible, single-cylinder heavy-duty diesel engine. From the soot luminosity imaging, qualitative flow-fields were obtained using flame image velocimetry (FIV). The peak motoring pressure (PMP) and peak cylinder pressure (PCP) of CDC are kept fixed at 50 and 70 bar, respectively.

Isobaric combustion has shown the potential of improving engine efficiency by lowering the heat transfer losses. Previous studies have achieved isobaric combustion through multiple injections from a single central injector, controlling injection timing and duration of the injection. In this study, we employed three injectors, i.e. one centrally mounted (C) on the cylinder head and two side-injectors (S), slant-mounted on cylinder head protruding their nozzle tip near piston-bowl to achieve the isobaric combustion. This study visualized the flame development of isobaric combustion, linking flow-field details to the observed trends in engine efficiency and soot emissions. The experiments were conducted in an optically accessible single-cylinder heavy-duty diesel engine using n-heptane as fuel. Isobaric combustion, with a 50 bar peak pressure, was achieved with three different injection strategies, i.e. (C+S), (S+C), and (S+S).

The high-pressure isobaric combustion has been proposed as the most suitable combustion mode for the double compre4ssion expansion engine (DCEE) concept. Previous experimental and simulation studies have demonstrated an improved efficiency compared to the conventional diesel combustion (CDC) engine. In the current study, isobaric combustion was achieved using a single injector with multiple injections. Since this concept involves complex phenomena such as spray to spray interactions, the computational models were extensively validated against the optical engine experiment data, to ensure high-fidelity simulations. The considered optical diagnostic techniques are Mie-scattering, fuel tracer planar laser-induced fluorescence (PLIF), and natural flame luminosity imaging. Overall, a good agreement between the numerical and experimental results was obtained.

The effects of intake pressure (Pin), start of injection (SOI), injection pressure (Pinj), injection split ratio (Qsplit), internal and external exhaust gas recirculation rates were varied to optimize several key parameters at a partially pre-mixed combustion low load/low speed condition using CFD. These include indicated specific fuel consumption (ISFC), combustion phasing (CA50), maximum rate of pressure rise (MRPR), maximum cylinder pressure (Pmax), indicated specific NOx (sNOx), indicated specific hydrocarbons (sHC) and Filter Smoke Number (FSN) emissions. Low-load point (6 bar indicated mean effective pressure (IMEP), 1500 revolutions per minute (RPM)) was selected where Pin varied between 1.25 and 1.5 bar, SOI between -100 and -10 crank angle degree (CAD) after top dead center (aTDC), Pinj between 100 and 200 bar, split ratio between 0 and 0.5, EGR between 0 and 45% and internal EGR measured by rebreathing valve height was varied between 0 and 4.5 mm.

The combustion system of a heavy-duty diesel engine operated in a gasoline compression ignition mode was optimized using a CFD-based response surface methodology and a machine learning genetic algorithm. One common dataset obtained from a CFD design of experiment campaign was used to construct response surfaces and train machine learning models. 128 designs were included in the campaign and were evaluated across three engine load conditions using the CONVERGE CFD solver. The design variables included piston bowl geometry, injector specifications, and swirl ratio, and the objective variables were fuel consumption, criteria emissions, and mechanical design constraints. In this study, the two approaches were extensively investigated and applied to a common dataset. The response surface-based approach utilized a combination of three modeling techniques to construct response surfaces to enhance the performance of predictions.

The regulatory requirements to reduce both greenhouse gases and exhaust gas pollutants from heavy duty engines are driving new perspectives on the interaction between fuels and engines. Fuels that reliefs the burden on engine manufacturers to reach these goals are of particular interest. A low carbon fuel with a higher volatility and heating value than diesel is one such fuel that reduces engine-out emissions and carbon footprint from the entire hydrocarbon lifecycle (well-to-wheel) and improves fuel efficiency, which is a main enabler for gasoline compression ignition (GCI) technology. The present study investigated the potential of GCI technology by evaluating the performance of a low carbon high efficiency, high reactivity gasoline fuel in Doosan’s 6L medium duty diesel engine.

In this study, the combustion system of a light-duty compression ignition engine running on a market gasoline fuel with Research Octane Number (RON) of 91 was optimized using computational fluid dynamics (CFD) and Machine Learning (ML). This work was focused on optimizing the piston bowl geometry at two compression ratios (CR) (17 and 18:1) and this exercise was carried out at full-load conditions (20 bar indicated mean effective pressure, IMEP). First, a limited manual piston design optimization was performed for CR 17:1, where a couple of pistons were designed and tested. Thereafter, a CFD design of experiments (DoE) optimization was performed where CAESES, a commercial software tool, was used to automatically perturb key bowl design parameters and CONVERGE software was utilized to perform the CFD simulations. At each compression ratio, 128 piston bowl designs were evaluated.

The present investigation expands on our previous work on development of fast idle catalyst light-off strategy for a light duty gasoline compression ignition (GCI) engine. In part 1, the steady state experimental investigation in a single cylinder GCI engine indicate an optimum strategy for effective catalyst light off during cold start fast idle operation. According to this strategy, the strategy includes (1) dispersing a first fuel injection during the intake stroke, (2) dispersing a second fuel injection during the expansion stroke, and (3) igniting a spark during the expansion stroke. This strategy increases the exhaust temperature during cold starts thereby assisting in lighting the oxidation catalyst, and reduce emissions and provide greater combustion stability as compared to other injection and spark strategies.

Isobaric combustion has been proven a promising strategy for high efficiency as well as low nitrogen oxides emissions, particularly in heavy-duty Diesel engines. Previous single-cylinder research engine experiments have, however, shown high soot levels when operating isobaric combustion. The combustion itself and the emissions formation with this combustion mode are not well understood due to the complexity of multiple injections strategy. Therefore, experiments with an equivalent heavy-duty Diesel optical engine were performed in this study. Three different cases were compared, an isochoric heat release case and two isobaric heat release cases. One of the isobaric cases was boosted to reach the maximum in-cylinder pressure of the isochoric one. The second isobaric case kept the same boost levels as the isochoric case. Results showed that in the isobaric cases, liquid fuel was injected into burning gases. This resulted in shorter ignition delays and thus a poor mixing level.

The present investigation pertains to the development of fast idle catalyst light-off strategy for a light duty gasoline compression ignition (GCI) engine. The engine cold start fast idle operation poses a problem of increased criteria emissions if the catalyst is not activated during the warm up period. Therefore, a control strategy is proposed here to minimize the criteria pollutants during the fast idle phase via enabling fast catalyst light off in a GCI engine and relying on the spark ignition of a globally stoichiometric fuel air mixture. The engine has unique design features such as certain geometry configuration between spark plug and fuel injector arrangement, and the location of spark plug in a high compression ratio (CR) diesel-like combustion chamber. The experiments were performed in a single cylinder GCI engine at cold start fast idle conditions using certification gasoline fuel (RON 91).

Gasoline compression ignition (GCI) technology shows the potential to obtain high thermal efficiencies while maintaining low soot and NOx emissions in light-duty engine applications. Recent experimental studies and numerical simulations have indicated that high reactivity gasoline-like fuels can further enable the benefits of GCI combustion. However, there is limited empirical data in the literature studying the gasoline compression ignition process at relevant in-cylinder conditions, which are required for further optimizing combustion system designs. This study investigates the temporal and spatial evolution of the compression ignition process of various high reactivity gasoline fuels with research octane numbers (RON) of 71, 74 and 82, as well as a conventional RON 97 E10 gasoline fuel. A ten-hole prototype gasoline injector specifically designed for GCI applications capable of injection pressures up to 450 bar was used.

High-pressure isobaric combustion used in the double compression expansion engine (DCEE) concept was proposed to obtain higher engine brake thermal efficiency than the conventional diesel engine. Experiments on the metal engines showed that four consecutive injections delivered by a single injector can achieve isobaric combustion. Improved understanding of the detailed fuel-air mixing with multiple consecutive injections is needed to optimize the isobaric combustion and reduce engine emissions. In this study, we explored the fuel spray characteristics of the four-consecutive-injections strategy using high-speed imaging with background illumination and fuel-tracer planar laser-induced fluorescence (PLIF) imaging in a heavy-duty optical engine under non-reactive conditions. Toluene of 2% by volume was added to the n-heptane and served as the tracer. The fourth harmonic of a 10 Hz Nd:YAG laser was applied for the excitation of toluene.

Partially premixed combustion (PPC) is a low-temperature combustion concept, which is between conventional diesel compression ignition (CI) and homogeneous charge compression ignition (HCCI). In PPC mode, the start of injection timing (SOI) is earlier than that of CI and later than that of HCCI and stratified in-cylinder fuel/air mixture can be formed to control the auto-ignition by the fuel injection timing. Gasoline fuel is beneficial for PPC mode because of its superior resistance to auto-ignition, which can enhance fuel-air charge mixing process with longer ignition delay time. The scope of this study is to investigate in-cylinder auto-ignition, combustion evolution, combustion stratification, and engine-out emissions at PPC operating mode under lean and low load engine conditions with different injection timings. Primary reference fuel PRF77, was selected as the low-octane test fuel.

Direct injection compression ignition engines running on gasoline-like fuels have been considered an attractive alternative to traditional spark ignition and diesel engines. The compression and lean combustion mode eliminates throttle losses yielding higher thermodynamic efficiencies and the better mixing of fuel/air due to the longer ignition delay times of the gasoline-like fuels allows better emission performance such as nitric oxides (NOx) and particulate matter (PM). These gasoline-like fuels which usually have lower octane compared to market gasoline have been identified as a viable option for the gasoline compression ignition (GCI) engine applications due to its lower reactivity and lighter evaporation compared to diesel. The properties, specifications and sources of these GCI fuels are not fully understood yet because this technology is relatively new.

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].