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Lean combustion technologies show promise for improving engine efficiency and reducing emissions. Among these technologies, prechamber-assisted combustion (PCC) is established as a reliable option for achieving lean or ultra-lean combustion. In this study, the effect of engine speed on PCC was investigated in a naturally aspirated heavy-duty optical engine: a comparison has been made between analytical performances and optical flame behavior. Bottom view natural flame luminosity (NFL) imaging was used to observe the combustion process. The prechamber was fueled with methane, while the main chamber was fueled with methanol. The engine speed was varied at 1000, 1100, and 1200 revolutions per minute (rpm). The combustion in the prechamber is not affected by changes in engine speed. However, the heat release rate (HRR) in the main chamber changed from two distinct stages with a faster first stage to more gradual and merged stages as the engine speed increased.

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.

The current work utilizes computational fluid dynamics (CFD) simulations to assess the effects of different piston geometries in an active-type pre-chamber combustion engine fueled with methane. Previous works identified that the interaction of the jets with the main chamber flow and piston wall are key aspects for the local turbulent flame speed and overall burning duration. The combustion process is simulated with the G-equation model for flame propagation combined with the MZ-WSR model to determine the post-flame composition and to predict possible auto-ignition of the reactant mixture. Four setups were considered: two bowl-shaped and one flat piston, and one additional case of the flat piston with jets at wider jet angles to the cylinder axis. The results show that premature jet-wall interaction impacts the main chamber pressure build-up, turbulence, and burn rate.

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.

To elucidate the complex characteristics of pre-chamber combustion engines, the interaction of the hot gas jets initiated by an active narrow throated pre-chamber with lean premixed CH4/air in a heavy-duty engine was studied computationally. A twelve-hole KAUST proprietary pre-chamber geometry was investigated using CONVERGE software. The KAUST pre-chamber has an upper conical part with the spark plug, and fuel injector, followed by a straight narrow region called the throat and nozzles connecting the chambers. The simulations were run for an entire cycle, starting at the previous cycle's exhaust valve opening (EVO). The SAGE combustion model was used with the chemistry modeled using a reduced methane oxidation mechanism based on GRI Mech 3.0, which was validated against in-house OH chemiluminescence data from the optical engine experiments.

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.

Pre-chamber Combustion (PCC) extends the lean operation limit operation of spark ignition (SI) engines, thus it has been of interest for researchers as a pathway for increased efficiency and reduced emissions. Optical diagnostic techniques are essential to understand the combustion process, but the engine components such as the piston geometry, are often different from real engines to maximize the optical access. In this study, ignition and subsequent main chamber combustion are compared in an optically accessible PCC engine equipped with a “flat” and a real engine-like “bowl” piston geometry. An active fueled narrow throat pre-chamber was used as the ignition source of the charge in the main-chamber, and both chambers were fueled with methane. Three pre-chamber fuel effective mean pressure (FuelMEP) ratios (PCFR) namely 6%, 9% and 11% of the total amount of fuel were tested at two global excess air ratios (λ) at values of 1.8 and 2.0.

Pre-chamber combustion (PCC) enables leaner air-fuel ratio operation by improving its ignitability and extending flammability limit, and consequently, offers better thermal efficiency than conventional spark ignition operation. The geometry and fuel concentration of the pre-chamber (PC) is one of the major parameters that affect overall performance. To understand the dynamics of the PCC in practical engine conditions, this study focused on (i) correlation of the events in the main chamber (MC) with the measured in-cylinder pressure traces and, (ii) the effect of fuel concentration on the MC combustion characteristics using laser diagnostics. We performed simultaneous acetone planar laser-induced fluorescence (PLIF) from the side, and OH* chemiluminescence imaging from the bottom in a heavy-duty optical engine. Two different PC Fueling Ratios (PCFR, the ratio of PC fuel to the total fuel), 7%, and 13%, were investigated.

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.