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Machine learning models were shown to provide faster results but with similar accuracy to multidimensional computational fluid dynamics or in-depth experiments. This study used a support-vector machine (SVM), a set of related supervised learning methods, to predict the dynamic performance (i.e., engine power and torque) of a heavy-duty natural gas spark ignition engine. The single-cylinder four-stroke test engine was fueled with methane. The engine was operated at different spark timings, mixture equivalence ratios, and engine speeds to provide the data for training and testing the proposed SVM. The results indicated that the performance and accuracy of the built regression model were satisfactory, with correlation coefficient quantities all larger than 0.95 and root-mean-square errors close to zero for both training and validation datasets.

Emission legislation for passenger cars is requiring a drastic reduction of exhaust pollutants from internal combustion engines (ICE). In this framework, achieving a quick heating-up of the catalyst is of paramount importance to cut down the cold start emissions and meet future regulation requirements. This paper describes the development and the basic characteristics of a novel burner for gasoline engines exhaust systems designed for being activated immediately at engine cold start. The burner is comprised of a fuel injector, an air system, and an ignition device. The design of the combustion chamber is first presented, with a description of the air-fuel interactions and mixture formation processes. Swirl is used along with a flame-holder concept to anchor the flame at the mixer exit. Spray-swirl and spray-walls interaction are also discussed. Computational Fluid Dynamics (CFD) analyses have been used to investigate these aspects.

Internal combustion diesel engines with optical access (a.k.a. optical engines) increase the fundamental understanding of combustion phenomena. However, optical access requirements result in most optical engines having a different in-cylinder geometry compared with the conventional diesel engine, such as a flat bowl-in-piston combustion chamber. This study investigated the effect of the bowl geometry on the flow motion and emissions inside a conventional heavy-duty direct-injection diesel engine that can operate in both metal and optical-access configurations. This engine was converted to natural-gas spark-ignition operation by replacing the fuel injector with a spark plug and adding a low-pressure gas injector in the intake manifold for fuel delivery, then operated at steady-state lean-burn conditions. A 3D CFD model based on the experimental data predicted that the different bowl geometry did not significantly affect in-cylinder emissions distribution.

The combustion process in spark-ignition engines can vary considerably cycle by cycle, which may result in unstable engine operation. The phenomena amplify in natural gas (NG) spark-ignition (SI) engines due to the lower NG laminar flame speed compared to gasoline, and more so under lean burn conditions. The main goal of this study was to investigate the main sources and the characteristics of the cycle-by-cycle variation in heavy-duty compression ignition (CI) engines converted to NG SI operation. The experiments were conducted in a single-cylinder optically-accessible CI engine with a flat bowl-in piston that was converted to NG SI. The engine was operated at medium load under lean operating conditions, using pure methane as a natural gas surrogate. The CI to SI conversion was made through the addition of a low-pressure NG injector in the intake manifold and of a NG spark plug in place of the diesel injector.

3D CFD spark-ignition IC engine simulations are extremely complex for the regular user. Truly-predictive CFD simulations for the turbulent flame combustion that solve fully coupled transport/chemistry equations may require large computational capabilities unavailable to regular CFD users. A solution is to use a simpler phenomenological model such as the G-equation that decouples transport/chemistry result. Such simulation can still provide acceptable and faster results at the expense of predictive capabilities. While the G-equation is well understood within the experienced modeling community, the goal of this paper is to document some of them for a novice or less experienced CFD user who may not be aware that phenomenological models of turbulent flame combustion usually require heavy tuning and calibration from the user to mimic experimental observations.

A two-step simulation methodology was applied for the computation of the injector nozzle internal flow and the spray evolution in diesel engine-like conditions. In the first step, the multiphase cavitating flow inside injector nozzle is calculated by means of unsteady CFD simulation on moving grids from needle opening to closure. A non-homogeneous Eulerian multi-fluid approach - with three phases i.e. liquid, vapor and air - has been applied. Afterward, in the second step, transient data of spatial distributions of velocity, turbulent kinetic energy, dissipation rate, void fraction and many other relevant properties at the nozzle exit were extracted and used for the subsequent Lagrangian spray calculation. A primary break-up model, which makes use of the transferred data, is used to initialize droplet properties within the hole area.

Conventional spark-ignition engines are currently incapable of meeting rising customer performance demands while complying with even stringent pollutant-emissions regulations. As a result, innovative ignition systems are being developed to accomplish these targets. Radio-Frequency corona igniters stand out for their ability to accelerate early flame growth speed by exploiting the combined action of kinetic, thermal and transport effects. Furthermore, a volumetric discharge enables the promotion of combustion over a wide area, as opposed to the local ignition of traditional spark. The present work wants to evaluate the advantages of a Streamer-type Radio Frequency corona discharge at about 100 kHz with respect to those of traditional spark igniter.

In the present paper, a detailed numerical and experimental analysis of a spray momentum flux measurement device capability is presented. Particular attention is devoted to transient, engine-like injection events in terms of spray momentum flux measurement. The measurement of spray momentum flux in steady flow conditions, coupled with knowledge of the injection rate, is steadily used to estimate the flow mean velocity at the nozzle exit and the extent of flow cavitation inside the nozzle in terms of a velocity reduction coefficient and a flow section reduction coefficient. In the present study, the problem of analyzing spray evolution in short injection events by means of jet momentum flux measurement was approached. The present research was based on CFD-3D analysis of the spray-target interaction in a momentum measurement device.

Recent development in hydraulic fracking made natural gas (NG) to be a promising alternative gaseous fuel for heavy-duty diesel engines. The existing compression ignition (CI) engine can be retrofitted to NG spark ignition (SI) operation by replacing the diesel injector with a spark plug and fumigating NG into the intake manifold. However, the original diesel piston geometry (flat head and bowl-in-piston chamber) was usually retained to reduce modification cost. The goal of this study was to increase the understanding of the NG lean-burn characteristics in a diesel-like, fast-burn SI combustion chamber. The experimental platform can operate in conventional (i.e., all engine parts are metal) or in optical configuration (i.e., the stock piston and cylinder block are replaced with a see-through piston and an extended cylinder block). The optical data indicated a fast-propagated flame inside the piston bowl.

On- and off-road heavy-duty diesel engines modified to spark-ignition natural gas operation can reduce U.S. dependence on imported oil and enhance national energy security. Engine conversion can be achieved through the addition of a gas injector in the intake manifold and of a spark plug in place of the diesel injector. This paper investigated combustion characteristics and engine performance at several lean-burn operating conditions that changed spark timing, mixture equivalence ratio, and engine speed, using methane as NG surrogate.

The paper describes an experimental research which addressed the study of a 4-cylinder, spark-ignited, port-fuel-injected, production engine modified for hydrogen-methane blend fueling. The original engine was a 2.8-liter, naturally aspirated, methane-fuelled engine. The engine modifications included two fuel injectors per port and ECU replacement for controlling lean burn combustion and enabling real-time variation of the fuel blend, based on an alpha-N mapping approach. Since hydrogen infrastructures are an issue and its production costs are still today very high, pure hydrogen usage is not a viable solution for near future vehicles. In view of this, in the present paper, the maximum volumetric concentration of hydrogen in methane has been set to 35% (which on a mass basis corresponds to 6.3%). The variability of the fuel mixture has been achieved by installing two separate fuel lines connected to two fuel rails: a total of 8 injectors are installed.

In the present work, an experimental and numerical analysis of high pressure Diesel spray evolution is carried out in terms of spray momentum flux time history and instantaneous injection rate. The final goal of spray momentum and of injection rate analyses is the evaluation of the nozzle outlet flow characteristics and of the nozzle internal geometry possible influences on cavitation phenomena, which are of primary importance for the spray evolution. Further, the evaluation of the flow characteristics at the nozzle exit is fundamental in order to obtain reliable boundary conditions for injection process 3D simulation. In this paper, spray momentum data obtained in ambient temperature, high counter-pressure conditions at the Perugia University Spray Laboratory are presented and compared with the results of 3D simulations of the momentum rig itself.

Nowadays internal combustion engines can operate under lean combustion conditions to maximize efficiency, as long as combustion stability is guaranteed. The robustness of combustion initiation is one of the main issues of actual spark-ignition engines, especially at high level of excess-air or dilution. The enhancement of the in-cylinder global motion and local turbulence is an effective way to increase the flame velocity. During the ignition process, the excessive charge motion can hinder the spark discharge and eventually cause a misfire. In this perspective, the interaction between the igniter and the flow field is a fundamental aspect which still needs to be explored in more detail to understand how the combustion originates and develops. In this work, a combined experimental and numerical study is carried out to investigate the flow field around the spark gap, and its effect on the spark discharge evolution.

Natural gas is a promising alternative gaseous fuel due to its availability, economic, and environmental benefits. A solution to increase its use in the heavy-duty transportation sector is to convert existing heavy-duty compression ignition engines to spark-ignition operation by replacing the fuel injector with a spark plug and injecting the natural gas inside the intake manifold. The use of numerical simulations to design and optimize the natural gas combustion in such retrofitted engines can benefit both engine efficiency and emission. However, experimental data of natural gas combustion inside a bowl-in-piston chamber is limited. Consequently, the goal of this study was to provide high-quality experimental data from such a converted engine fueled with methane and operated at steady-state conditions, exploring variations in spark timing, engine speed and equivalence ratio.

Machine learning algorithms are effective tools to reduce the number of engine dynamometer tests during internal combustion engine development and/or optimization. This paper provides a case study of using such a statistical algorithm to characterize the heat transfer from the combustion chamber to the environment during combustion and during the entire engine cycle. The data for building the machine learning model came from a single cylinder compression ignition engine (13.3 compression ratio) that was converted to natural-gas port fuel injection spark-ignition operation. Engine dynamometer tests investigated several spark timings, equivalence ratios, and engine speeds, which were also used as model inputs. While building the model it was found that adding the intake pressure as another model input improved model efficiency.

Engine research community is developing innovative strategies capable of reducing fuel consumption and pollutant emissions while ensuring, at the same time, satisfactory performances. Spark ignition engines operation with highly diluted or lean mixture is demonstrated to be beneficial for engine efficiency and emissions while arduous for combustion initiation and stability. Traditional igniters are unsuitable for such working conditions, therefore, advanced ignition systems have been developed to improve combustion robustness. To overcome the inherent efficiency limit of combustion engines, the usage of renewable fuels is largely studied and employed to offer a carbon neutral transition to a cleaner future. For such a reason, both innovative ignition systems and bio or E-fuels are currently being investigated as alternatives to the previous approaches. Within this context, the present work proposes a synergetic approach which combines the benefits of a biofuel blend, i.e.

The conversion of existing diesel engines to natural-gas operation can reduce the dependence on petroleum imports and curtail engine-out emissions. A convenient way to perform such conversion is by adding a gas injector in the intake manifold and replacing the diesel fuel injector with a spark plug to initiate and control the combustion process. However, challenges may appear with respect to engine’s efficiency and emissions as natural-gas spark-ignition combustion inside a diesel combustion chamber is different to that in conventional spark ignition engines. For example, major difference is the phasing and duration of the fast burn, defined as the period in which the rate of heat release increases linearly with crank angle. This study presents a methodology to investigate the fast burn inside a diesel geometry using heat release data.

This work involves modeling internal and near-nozzle flows of a gasoline direct injection (GDI) nozzle. The Engine Combustion Network (ECN) Spray G condition has been considered for these simulations using the nominal geometry of the Spray G injector. First, best practices for numerical simulation of the two-phase flow evolution inside and the near-nozzle regions of the Spray G injector are presented for the peak needle lift. The mass flow rate prediction for peak needle lift was in reasonable agreement with experimental data available in the ECN database. Liquid plume targeting angle and liquid penetration estimates showed promising agreement with experimental observations. The capability to assess the influence of different thermodynamic conditions on the two-phase flow nature was established by predicting non-flashing and flashing phenomena.

The new real driving emission cycles and the growing adoption of turbocharged GDI engines are directing the automotive technology towards the use of innovative solutions aimed at reducing environmental impact and increasing engine efficiency. Water injection is a solution that has received particular attention in recent years, because it allows to achieve fuel savings while meeting the most stringent emissions regulations. Water is able to reduce the temperature of the gases inside the cylinder, coupled with the beneficial effect of preventing knock occurrences. Moreover, water dilutes combustion, and varies the specific heat ratio of the working fluid; this allows the use of higher compression ratios, with more advanced and optimal spark timing, as well as eliminating the need of fuel enrichment at high load. Computational fluid dynamics simulations are a powerful tool to provide more in-depth details on the thermo-fluid dynamics involved in engine operations with water injection.

Currently, conventional spark-ignition engines are unfit to satisfy the growing customer requirements on efficiency while complying with the legislations on pollutant emissions. New ignition systems are being developed to extend the engine stable operating range towards increasing lean conditions. Among these, the Radio-Frequency corona igniters represent an interesting solution for the capability to promote the combustion in a much wider region than the one involved by the traditional spark channel. Moreover, the flame kernel development is enhanced by means of the production of non-thermal plasma, where low-temperature active radicals are ignition promoters. However, at low pressure and at high voltage the low temperature plasma benefits can be lost due to occurrences of spark-like events. Recently, RF barrier discharge igniters (BDI) have been investigated for the ability to prevent the arc formation thanks to a strong-breakdown resistance.