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Pre-chamber combustion (PCC) has re-emerged in recent last years as a potential solution to help to decarbonize the transport sector with its improved engine efficiency as well as providing lower emissions. Research into the combustion process inside the pre-chamber is still a challenge due to the high pressure and temperatures, the geometrical restrictions, and the short combustion durations. Some fundamental studies in constant volume combustion chambers (CVCC) at low and medium working pressures have shown the complexity of the process and the influence of high pressures on the turbulence levels. In this study, the pre-chamber combustion process was investigated by combustion visualization in an optically-accessible pre-chamber under engine relevant conditions and linked with the jet emergence inside the main chamber. The pre-chamber geometry has a narrow-throat. The total nozzle area is distributed in two six-hole rows of nozzle holes.

Research on alternative fuels has made significant progress as demands for cleaner and more efficient engine operation intensifies. Liquefied petroleum gas (LPG) can offer a potential alternative fuel route in the Diesel fuel dominated heavy-duty transportation sector due to its low cost, high anti-knock limit relative to gasoline, and reduced emission levels. In this work, experimental investigations are performed to study the effects of LPG compositions on performance, emissions, and combustion behavior of a spark-ignited (SI) cooperative fuel research (CFR) engine under stoichiometric conditions. Four LPG blends (chemically pure propane, a representative US blend, HD-5, and a representative European blend) representing the present LPG market are chosen. The impact of fuel composition is studied under different compression ratios (CR), ranging from 7:1 to 10:1 with one-unit increments, and at constant engine speed, intake manifold air pressure (IMAP) and 50% burn crank angle (CA50).

Hydrogen engines offer the possibility of a carbon neutral transportation - a focal point of current propulsion development activities especially for EU and US future concepts. From today's point of view, hydrogen can play an important role in this regard as it is a carbon-free fuel, no CO2 emissions are produced during its combustion process. Besides, it can be well used for lean burn combustion leading to very low NOx emissions, a key benefit in combination with an optimized after-treatment system for future ultra-low NOx legislations of heavy-duty (HD) engines. Comprehensive investigations using experimental tests and model-based development approach are performed using a six cylinder HD hydrogen engine featuring PFI (port fuel injection) aiming the definition of a high efficiency hydrogen engine concept.

Downsized turbocharged engines have been increasingly popular in modern light-duty vehicles due to their fuel efficiency benefits. However, high power density in such engines is achieved thanks to high in-cylinder pressure and temperature conditions that increase knock propensity. Next-cycle control has been studied as a method to reduce the damaging effects of knock by operating the engine in a low knock probability condition. This exploratory study looks at the feasibility of in-cycle knock prediction as a tool for advanced knock control algorithms. A methodology is proposed to 1) choose in-cycle features of the pressure trace that highly correlate with knock events and 2) train artificial neural networks to predict in-cycle knock events before knock onset. The methodology was validated at different operating conditions and different levels of generalization. Precision and recall were used as metrics to evaluate the binary classifier.

Ducted Fuel Injection (DFI) is a new technology recently developed with the aim of reducing soot emission formation in diesel compression ignition engines. DFI concept consists of the injection of fuel spray through a small duct located downstream of the injector nozzle leaving a certain gap, the so-called Stand-off distance. Currently, CFD modelers have investigated its performance using classical spray modeling techniques such as the Discrete Drops Method (DDM). However, as discussed in the literature, this type of technique is inappropriate when applied to dense jets as those occurring in diesel sprays, especially in the near-nozzle region (where the duct is placed). Therefore, considering a more appropriate modeling technique for such a problem is mandatory. In this research work, an Eulerian single-fluid diffuse-interface model called Σ-Y and implemented in the OpenFOAM framework is utilized for the simulation of non-reacting conditions.

To improve the combustion and emission characteristics of the large-bore marine engines, the spray is usually designed as an inter-spray impingement to promote the fuel-air mixing process, which implies frequent droplet collisions. Properly describing the collision dynamics of liquid droplets has been of interest in the field of spray modeling for marine engine applications. In this context, this work attempts to develop an accurate and efficient methodology for modeling impinging sprays under engine-like conditions. Experimental validations in terms of spray penetration and morphology are initially carried out at different operating conditions considering the parametric variations of ambient temperature and pressure, where the measurements are performed on a large-scale constant volume chamber with two symmetrical injectors.

In this study the volume and hardness were measured for thermoplastics and thermosetting resins with diesel containing up to 30% of the following blend stocks: biodiesel, renewable diesel, n-undecane, dibutoxymethane, 1-octanol, hexyl hexanoate, and 2-nonanone. Thermoplastics included polyphenylene sulfide (PPS), polyethylene terephthalate (PET), polytetrafluoroethylene (PTFE), polyvinylidene fluoride (PVDF), polyoxymethylene (POM), polybutylene terephthalate (PBT), polypropylene (PP), high density polyethylene (HDPE), nylons, acetals, polyetherimide (PEI), polyetheretherketone (PEEK), a PET co-polymer, polyphthalamides (PPAs), polyarylamide (PARA) and ethylene tetrafluoroethylene (ETFE). Three thermosetting resins were also evaluated. The material specimens were exposed to the test fuels under ambient conditions for 16 weeks.

Fuel chemistry plays a crucial role in the continued reduction of particulate emissions (PE) and cleaner air quality from vehicles and equipment powered by internal combustion engines (ICE). Over the past ten years, there have been great improvements in predictive particulate emissions indices (correlative mathematical models) based on the fuel’s composition. Examples of these particulate indices (PI) are the Honda Particulate Matter Index (PMI) and the General Motors Particulate Evaluation Index (PEI). However, the analytical chemistry lab methods used to generate data for these two PI indices are very time-consuming. Because gasoline can be mixtures of hundreds of hydrocarbon compounds, these lab methods typically include the use of the high resolution chromatographic separation techniques such as detailed hydrocarbon analysis (DHA), with 100m chromatography columns and long (3 - 4 hours) analysis times per sample.

Fuel spray interactions with piston surfaces and cylinder walls in internal combustion engines have been extensively studied in the past decades. However, there still exists an imperative knowledge gap on the fundamental understanding of dynamic droplet-wall interactions. Particularly, the impinging angle of droplet has been barely investigated as it renders asymmetrical droplet behaviors. This paper aims to provide detailed data of droplet-inclined surface impingement physics which could further support spray-wall model development. The experimental work of single diesel droplet impinging on an inclined dry surface was conducted under isothermal (25°C) conditions. Various droplet impact angle (φ) was achieved by adjusting surface tilting angle which was set from 0° to 45° in current study. A single diesel droplet impinged onto the inclined surface with different Weber number (around 20 ~ 800).

Fuel film deposited on fuel injector tips used in gasoline direct injection engines, otherwise known as nozzle tip wetting, has been identified as an essential source of particle emissions. Attempts have been made to reduce nozzle tip wetting by the optimization design of nozzle geometry parameters. However, relevant investigations are still limited to emission measurements and corresponding indirect analysis. Due to the lack of related visualization research, the mechanism of nozzle tip wetting formation and its link with nozzle internal flow are still unclear. To clarify the influence of spray hole length on nozzle tip wetting and the underlying mechanisms, the dynamic formation process and the fuel film area evolution of nozzle tip wetting were visualized directly using laser-induced fluorescence technique and photomicrography technique.

The injection strategy as well as the overall efficiency of the diesel engine are tightly related to the performance of the high-pressure injection pump. The paper deals with the modeling of a latest generation Common Rail injection pump, aiming at the characterization of its performance in terms of volumetric- and torque-efficiency. A lumped parameter approach is adopted; with reference to a commercial pump widely used in the field of light diesel engines, a dynamic model of the piston-cylinder pair is built, taking its mechanical drive, the hydraulic supply and delivery systems into account. Based on in-depth experimental activities that provide the performance diagrams of pump, the lumped-parameter model is built and assessed. Given the current strong interest in the use of alternative fuels that limit CO2 emissions, the pump model has been implemented to simulate, beside the standard diesel, the use of biofuel.

Hydrous ethanol not only has the advantages of high-octane number and valuable oxygen content, but also reduce the energy consumption in the production process. However, little literature investigated the internal flow and cavitation of hydrous ethanol-gasoline fuels in the multi-hole direct injector. In this simulation, a two-phase fuel flow model in injector is established based on the multi-fluid model of Euler-Euler method, and the accuracy of model is verified. On the basis of this model, the flow of different hydrous ethanol-gasoline blends is calculated under different injection conditions, and the cavitation, flow rate, and velocity at the outlet of the nozzle are predicted. Meanwhile, the influence of temperature and back pressure on the flow is also analyzed. The results show that the use of hydrous ethanol reduces the flow rate, compared with the velocity of E0, that of E10w, E20w, E50w, E85w, and E100w decreases by 10%, 12.9%, 17.6%, 20%, and 23.5%, respectively.

The temperature of fuel injectors can affect the flow inside nozzles and the subsequent spray and liquid films on the injector tips. These processes are known to impact fuel mixing, combustion and the formation of deposits that can cause engines to go off calibration. However, there is a lack of experimental data for the transient evolution of nozzle temperature throughout engine cycles and the effect of operating conditions on injector tip temperature. Although some measurements of engine surface temperature exist, they have relatively low temporal resolutions and cannot be applied to production injectors due to the requirement for a specialist coating which can interfere with the orifice geometry. To address this knowledge gap, we have developed a high-speed infrared imaging approach to measure the temperature of the nozzle surface inside an optical diesel engine.

Flame lift-off length (FLOL), ignition delay time (IDT), liquid length (LL), and Soot are essential parameters defining spray combustion characteristics. They help understand the combustion dynamics and validate the spray and combustion models for numerical simulations. However, obtaining extensive data from experiments is costlier and time-consuming. Machine learning (ML) models have advanced to the point where they could create efficient models that could be used as surrogates for experiments. In this study, five different ML algorithms have been trained using the experimental dataset available through the engine combustion network (ECN) community. A novel genetic algorithm-based hyperparameter optimization code has been used to optimize the models to improve prediction accuracy. The model performances were compared, and the better model was chosen as an experimental surrogate to predict FLOL, IDT, LL, and Soot.

This study presents experimental and numerical examination of directly injected (DI) propane and iso-octane, surrogates for liquified petroleum gas (LPG) and gasoline, respectively, at various engine like conditions with the overall objective to establish the baseline with regards to fuel delivery required for future high efficiency DI-LPG fueled heavy-duty engines. Sprays for both iso-octane and propane were characterized and the results from the optical diagnostic techniques including high-speed Schlieren and planar Mie scattering imaging were applied to differentiate the liquid-phase regions and the bulk spray phenomenon from single plume behaviors. The experimental results, coupled with high-fidelity internal nozzle-flow simulations were then used to define best practices in CFD Lagrangian spray models.

This paper investigated the spray characteristics of methanol under the flash and non-flash boiling conditions defined by the Engine Combustion Network (ECN) Spray G. As a counterpart, the spray features of iso-octane were also simulated and compared to methanol. The Volume of Fluid (VOF) approach under the Eulerian scheme was employed to model the internal nozzle flow details, which information was used to initialize the spray parcels and taken as input for the Lagrangian simulations, namely, the one-way coupling method. Since the Eulerian high-fidelity simulations allow capturing the effects of the flow inside the non-symmetrical injector, the rate of injection (ROI) profile, discharge coefficient, and plume angle et al. are not required for the Lagrangian simulations. The simulation results show that the flash boiling led to longer penetrations and higher evaporation compared to the non-flash boiling condition for both fuels.

This work presents a numerical study of the Spray A (n-dodecane) characteristics using Eulerian and Lagrangian models in a finite-volume framework. The standard k-ε turbulence model was applied for the spray simulations. For Eulerian simulations, the X-ray measured injector geometries from the Engine Combustion Network (ECN) were employed. The High-Resolution Interface Capturing (HRIC) scheme coupled with a cavitation model was utilized to track the fluid-gas interface. Simulations under both the cool and hot ambient conditions were performed. The effects of various grid sizes, turbulence constants, nozzle geometries, and initial gas volume within the injector sac on the modeling results were evaluated. As indicated by the Eulerian simulation results, no cavitation was observed for the Spray A injector; a minimum mesh size of 15.6 μm could achieve a reasonably convergent criterion; the nominal nozzle geometry predicted similar results to the X-ray measured nozzle geometry.

An experimental study on the laminar flame speeds (LFS) of premixed propane/dimethyl-ether (DME)/air flames was conducted inside a constant-volume chamber at UCF. Mixtures of propane and DME were selected for this study as they show promise as a fuel source that can be utilized in the automotive diesel industry as a low emission alternative fuel. The LFS of a fuel mixture is a crucial characteristic of combustion for its application in the design process of engines, as it can be used as a metric for fuel performance. Further underscoring the importance of gathering LFS data for these mixtures is its use in validating chemical kinetic mechanisms that can be utilized for further research in the field. LFS is dependent on fuel/oxidant mixture temperature, pressure, and equivalence ratio. While some studies exist examining other characteristics of combustion regarding propane/DME fuel mixtures, there is minimal information on the laminar flame speed of the mixtures.

Computational models widely employed for predicting the dispersion of fuel sprays in combustion engines suffer from well-known drawbacks associated with the utilization of case-dependent empirical phase-change models, describing the conversion of liquid into vapour during fuel injection. The present work couples the compressible Navier-Stokes and energy conservation equations with a thermodynamic closure approximation covering pressures from 25 to 2000bar and temperatures that expand from compressed liquid, vapor-liquid equilibrium to trans/supercritical mixing, and thus, cover the whole range of P-T values that diesel fuel undergoes during its injection into combustion engines. The model assumes mechanical and thermal equilibrium between the liquid, vapour and surrounding air phases and thus, it avoids utilization of case-dependent empirical phase-change models for predicting in-nozzle cavitation and vaporization of fuels.

The reduction of harmful emissions is a key challenge in fighting climate change and global warming. Besides battery electric vehicles (BEVs), improved engine efficiency and alternate fuels, such as e-fuels or biofuels, can improve the emission budget of the transportation sector. Pred ictive simulations can be utilized as these avoid relying on slow manufacturing processes and expensive experiments. As the properties of alternative fuels can change drastically compared to classical fuels, even engine parameters, such as the mass flow rate, need to be reevaluated and optimized. However, simulation frameworks often rely on mass flow rates as input quantity, and hence, a prediction is impossible. This paper gives accurate pressure-based boundary conditions for multiphase systems and focuses on equations of state (EOS) employed in homogeneous equilibrium models (HEMs). Additionally, a dual-density approach is introduced to correct modeling errors that are intrinsic to a particular EOS.