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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.

Compared to fossil fuels, ammonia is an environmentally friendly, cost-effective, and readily available fuel that carries hydrogen. It is expected to play a crucial role in the development of carbon-neutral internal combustion engines for the next generation. However, a significant challenge arises due to the presence of nitrogen in both the fuel and air, leading to the complex generation of intertwined thermal and fuel-based nitrogen oxides (NOx) during ammonia combustion. To gain a deeper understanding of NOx emission characteristics and propose effective technologies for controlling NOx emissions from ammonia engines, it is essential to decouple the mechanisms responsible for thermal and fuel-based NOx and analyze the formation and evolution of both types separately. In this study, a novel approach employing argon circulation is applied to eliminate the thermal NOx formation mechanism.

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.

The conversion of compression ignition (CI) internal combustion engines to spark-ignition (SI) operation by adding a spark plug to ignite the mixture and fumigating the fuel inside the intake manifold can increase the use of alternative gaseous fuels (e.g., natural gas) in heavy-duty applications. This study proposed a novel, less-complex methodology based on the inflection points in the apparent rate of heat release (ROHR) that can identify and separate the fast-burning stage inside the piston bowl from the slower combustion stage inside the squish region (a characteristic of premixed combustion inside a diesel geometry). A single-cylinder 2L CI research engine converted to natural gas SI operation provided the experimental data needed to evaluate the methodology, at several spark timings, equivalence ratios, and engine speeds.

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.

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.

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.

The conversion of existing diesel engines to natural gas with the least amount of modifications can reduce the dependence on conventional oil and enhance national energy security. This study investigated such engine conversion using an experimental platform that consisted of a single-cylinder diesel engine modified for lean-burn natural-gas spark-ignition operation through the addition of a gas injector and a spark plug. Following steady-state experiments at several operating conditions that changed spark timing, mixture equivalence ratio, and engine speed, the experimental results suggested that the combustion phenomena in diesel engines retrofitted to lean-burn natural gas spark ignition presents significant differences compared to that in a conventional stoichiometric spark ignition engine.