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The advent of digitalization opens up new avenues for advances in large internal combustion engine technology. Key engine components are becoming "intelligent" through advanced instrumentation and data analytics. By generating value-added data, they provide deeper insight into processes related to the components. An intelligent common rail diesel fuel injection valve for large engine applications in combination with machine learning allows reliable prediction of key combustion parameters such as maximum cylinder pressure, combustion phasing and indicated mean effective pressure. However, fault-related changes to the injection valve also have to be considered. Based on experiments on a medium-speed four-stroke single-cylinder research engine with a displacement of approximately 15.7 liter, this study investigates the extent to which the intelligent injection valve can improve the reliability of combustion parameter predictions in the presence of injection valve faults.

To achieve global climate goals, greenhouse gas emissions must be drastically reduced. The energy and transportation sectors are responsible for about one third of the greenhouse gases emitted worldwide, and they often use internal combustion engines (ICE). One effective way to decarbonize ICEs may be to replace carbon-containing fossil fuels such as natural gas entirely, or at least partially, with hydrogen. Cost-effective development of sustainable combustion concepts for hydrogen and natural gas/hydrogen mixtures in ICEs requires the intensive use of fast and robust simulation tools for prediction. The key challenge is appropriate modeling of flame front propagation. This paper evaluates and applies different approaches to modeling laminar flame speeds from the literature. Both appropriate models and reaction kinetic calculations are considered.

Digital technologies are capable of making a significant contribution to improving large internal combustion engine technology. In particular, methods from the field of artificial intelligence are opening up new avenues. So-called “intelligent” engine components rely on advanced instrumentation and data analytics to create value-added data, which in turn can serve as the basis for applications such as condition monitoring, predictive maintenance and controls. For related components and systems, these data may also allow for novel condition monitoring approaches. This paper describes the use of value-added data from an intelligent diesel fuel injection valve that give detailed information about the injection process for real-time prediction of key combustion parameters such as indicated mean effective pressure, maximum cylinder pressure and combustion phasing.

Precise prediction of combustion parameters such as peak firing pressure (PFP) or crank angle of 50% burned mass fraction (MFB50) is essential for optimal engine control. These quantities are commonly determined from in-cylinder pressure sensor signals and are crucial to reach high efficiencies and low emissions. Highly accurate in-cylinder pressure sensors are only applied to test rig engines due to their high cost, limited durability and special installation conditions. Therefore, alternative approaches which employ virtual sensing based on signals from non-intrusive sensors retrieved from common knock sensors are of great interest. This paper presents a comprehensive comparison of selected approaches from literature, as well as adjusted or further developed methods to determine engine combustion parameters based on knock sensor signals. All methods are evaluated on three different engines and two different sensor positions.

Gasoline compression ignition using a single gasoline-type fuel has been shown as a method to achieve low-temperature combustion with low engine-out NOx and soot emissions and high indicated thermal efficiency. However, key technical barriers to achieving low temperature combustion on multi-cylinder engines include the air handling system (limited amount of exhaust gas recirculation) as well as mechanical engine limitations (e.g. peak pressure rise rate). In light of these limitations, high temperature combustion with reduced amounts of exhaust gas recirculation appears more practical. Furthermore, for high temperature Gasoline compression ignition, an effective aftertreatment system allows high thermal efficiency with low tailpipe-out emissions. In this work, experimental testing was conducted on a 12.4 L multi-cylinder heavy-duty diesel engine operating with high temperature gasoline compression ignition combustion using EEE gasoline.

To increase reliability and the maintenance interval of an internal combustion engine while operating it with the lowest possible emissions, spark plug wear must be reduced. In this context, information about the spark plug center and the ground electrode temperature is key. Several measurement devices have been developed that measure the temperature of spark plug electrodes. The great challenge is to measure the temperature of the center electrode; on the one hand, the measurement device must be insulated and capable of withstanding the high voltage of the ignition system, and on the other hand, the device should not influence the ignition system. All previously studied devices presented in this paper have in common that major reconstruction of the ignition system and/or spark plugs whose design is very different from the standard engine spark plug were necessary.

Virtual sensing refers to the processing of desired physical data based on measured values. Virtual sensors can be applied not only to obtain physical quantities which cannot be measured or can only be measured at an unreasonable expense but also to reduce the number of physical sensors and thus lower costs. In the field of spark ignited internal combustion engines, the virtual sensing approach may be used to predict the cylinder pressure signal (or characteristic pressure values) based on the acceleration signal of a knock sensor. This paper presents a method for obtaining the cylinder pressure signal in the high-pressure phase of an internal combustion engine based on the measured acceleration signal of a knock sensor. The approach employs a partial differential equation to represent the physical transfer function between the measured signal and the desired pressure. A procedure to fit the modeling constants is described using the example of a large gas engine.

Increasing demands regarding the efficiency and emissions of internal combustion engines will require higher peak firing pressures and increased indicated mean effective pressures in the future. Adaptation of these parameters will result in higher thermal and mechanical loads that act on core engine components. To meet the future requirements, it is essential to make changes to the design of the tribological system, which is composed of the piston, piston rings, liner and lube oil, while maintaining the robustness and reliability of the engine and its components. Modification of the tribological system requires in-depth knowledge of wear and friction. This paper presents the setup of a model of the tribological system (piston, piston rings, liner and lube oil) of a large gas engine in the commercial software AVL EXCITE™ Piston&Rings as well as its calibration and validation with data obtained from a test bed.

Gasoline compression ignition is a promising strategy to achieve high thermal efficiency and low emissions with limited modifications to the conventional diesel engine hardware. It is a partially premixed concept which derives its superiority from higher volatility and longer ignition delay of gasoline-like fuels combined with higher compression ratio typical of diesel engines. The present study investigates the combustion process in a gasoline compression ignition engine using computational fluid dynamics. Simulations are carried out on a single cylinder of a multi cylinder heavy-duty compression ignition engine which operates at a compression ratio of 17:1 and an engine speed of 1038 rev/min. In this study, a late fuel injection strategy is used because it is less sensitive to combustion kinetics compared to early injection strategies, which in turn is a better choice to assess the performance of the spray model.

In-cylinder flows in internal combustion engines are highly turbulent in nature. An important property of turbulence that plays a key role in mixture formation is anisotropy; it also influences ignition, combustion and emission formation. Thus, understanding the turbulence anisotropy of in-cylinder flows is critical. Since the most widely used two-equation Reynolds-averaged Navier-Stokes (RANS) turbulence models assume isotropic turbulence, they are not suitable for correctly capturing the anisotropic behavior of turbulence. However, large eddy simulation (LES) can account for the anisotropic behavior of turbulence. In this paper, the Reynolds stress tensor (RST) is analyzed to assess the predictive capability of RANS and LES with regard to turbulence anisotropy. The influence of mesh size on turbulence anisotropy is also looked into for multi-cycle LES.

The transient operation of gas engines is of paramount importance to sustainable power generation as it increases the share of renewable energy. Fast-reacting and highly flexible power plants are an integral component of scenarios for the smart power generation of the future. Modern gaseous fueled large bore engines already adapt to fluctuating load demands quickly and also provide high efficiency throughout all load conditions. However, future energy systems that integrate predominantly fluctuating renewables will require even further improved transient capabilities of these engines. The goal is to be competitive with diesel engines in applications with the highest transient requirements and to meet the high transient requirements while simultaneously generating significantly less emissions than other fossil generation facilities to support the future sustainable power supply.

This work focuses on reducing the computational effort of a 0-dimensional combustion model developed for compression ignition engines operating on gasoline-like fuels. As in-cylinder stratification significantly contributes to the ignition delay, which in turn substantially influences the entire gasoline compression ignition combustion process, previous modeling efforts relied on the results of a 1-dimensional spray model to estimate the in-cylinder fuel stratification. Insights obtained from the detailed spray model are leveraged within this approach and applied to a reduced order model describing the spray propagation. Using this computationally efficient combustion model showed a reduction in simulation time by three orders of magnitude for an entire engine cycle over the combustion model with the 1-dimensional spray model.

Turbulence anisotropy has a great influence on mixture formation and flame propagation in internal combustion engines. However, the visualization of turbulence in simulations is not straightforward; traditional methods lack the ability to display the anisotropic properties in the engine geometry. Instead, they use invariant maps, and important information about the locality of the turbulence anisotropy is lost. This paper overcomes this shortcoming by visualizing the anisotropy directly in the physical domain. Componentality contours are applied to directly visualize the anisotropic properties of turbulence in the three-dimensional engine geometry. Using an RGB (red, green, blue) color map, the three limiting states of turbulence (one-component, axisymmetric two-component and isotropic turbulence) are displayed in the three-dimensional physical domain.

Lean burn combustion concepts with high mean effective pressures are being pursued for large gas engines in order to meet future stringent emission limits while maintaining high engine efficiencies. Since severe boundary conditions for the ignition process are encountered with these combustion concepts, the processes of spark ignition and flame initiation are important topics of applied research, which aims to avoid misfiring and to keep cycle-to-cycle combustion variability within reasonable limits. This paper focuses on the fundamental investigation of early flame kernel development using different ignition system settings. The investigations are carried out on a rapid compression-expansion machine in which the spark ignition process can be observed under engine-like pressure and excess air ratio conditions while low flow velocities are maintained.

High-pressure direct injection (HPDI) of natural gas into the combustion chamber enables a non-premixed combustion regime known from diesel engines. Since knocking combustion cannot occur with this combustion process, an increase in the compression ratio and thus efficiency is possible. Due to the high injection pressures required, this concept is ideally suited to applications where liquefied natural gas (LNG) is available. In marine applications, the bunkering of and operation with LNG is state-of-the-art. Existing HPDI gas combustion concepts typically use a small amount of diesel fuel for ignition, which is injected late in the compression stroke. The diesel fuel ignites due to the high temperature of the cylinder charge. The subsequently injected gas ignites at the diesel flame. The HPDI gas combustion concept presented in this paper is of a monovalent type, meaning that no fuel other than natural gas is used.

A zero-dimensional heat release model was developed for compression ignition engines. This type of model can be utilized for parametric studies, off-line optimization to reduce experimental efforts as well as model-based control strategies. In this particular case, the combustion model, in a simpler form, will be used in future efforts to control the combustion in compression ignition engines operating on gasoline-like fuels. To allow for a realistic representation of the in-cylinder combustion process, a spray model has been employed to allow for the quantification of fuel distribution as well as turbulent kinetic energy within the injection spray. The combustion model framework is capable of reflecting premixed as well as mixing controlled combustion. Fuel is assigned to various combustion events based on the air-fuel mixture within the spray.

Using natural gas in large bore engines reduces carbon dioxide emissions by up to 25% at a lower fuel cost than diesel engines. In demanding applications with highly transient operating profiles, however, premix gas engines have disadvantages compared to diesel engines because of the potential for knocking and misfire to occur. Operating a gas engine using the diesel cycle requires high gas injection pressures. Furthermore, a source of ignition is needed due to the high autoignition temperature of methane. State-of-the-art solutions inject a small quantity of diesel fuel before introducing the natural gas. One monofuel alternative ignites the gas jets with flame torches that originate in a prechamber. This paper presents the simulation based development of a prechamber ignited high pressure direct injection (HPDI) gas combustion concept and subsequent experimental validation.

Gasoline compression ignition (GCI) using a single gasoline-type fuel for direct/port injection has been shown as a method to achieve low-temperature combustion with low engine-out NOx and soot emissions and high indicated thermal efficiency. However, key technical barriers to achieving low temperature combustion on multi-cylinder engines include the air handling system (limited amount of exhaust gas recirculation (EGR)) as well as mechanical engine limitations (e.g. peak pressure rise rate). In light of these limitations, high temperature combustion with reduced amounts of EGR appears more practical. Previous studies with 93 AKI gasoline demonstrated that the port and direct injection strategy exhibited the best performance, but the premature combustion event prevented further increase in the premixed gasoline fraction and efficiency.

In the research and development of internal combustion engines, there are several drivers for developing an accurate online lube oil consumption (LOC) measurement system. Lube oil consumption is considered to be a root cause of hydrocarbon and particle emissions and lubricating oil autoignition. It also negatively influences the life cycle cost for engine operators. Highly accurate measurement of lube oil consumption must be possible before it can be reduced - or rather optimized - to levels stakeholders will require in the future. State-of-the-art methods such as gravimetric and volumetric measurements are not fully satisfactory for several reasons. Generally, offline LOC measurement is no longer suitable for fast and accurate measuring cycles, oil condition monitoring and wear monitoring. At present, tracer methods are considered to be the most promising approach. However, current tracer methods have their downsides as well.

The CFR F1 engine is the standard testing apparatus used for rating the research octane number (RON) of gasoline fuels. Unlike the motor octane number (MON) method, where the intake port temperature after the carburetor is controlled by an electric heater, the mixture temperature can vary during the RON test due to the heat of vaporization (HoV) of the fuel. Ethanol is receiving increasing attention as a high octane and high HoV fuel component. This work presents an analysis of the combustion characteristics during the RON rating of ethanol fuel blends according to the standard ASTM D2699 method, highlighting the effects of ethanol concentration and base fuel composition. All fuels were blended to a constant RON of 98. Ethanol levels varied from 0 to 50 vol% and the base fuels were surrogate blends composed of primary reference fuels (PRF), toluene standardization fuels (TSF), and a four component gasoline surrogate.