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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.

As emission limits become increasingly stringent and the price of gaseous fuels decreases, more emphasis is being placed on promoting gas engines. In the field of large engines for power generation, dual fuel combustion concepts that run on diesel/natural gas are particularly attractive. Knock in diesel/natural gas dual fuel engines is a well known yet not fully understood complex phenomenon that requires consideration in any attempt to increase load and efficiency. Thus combustion concept development requires a reliable yet robust methodology for detecting knock in order to ensure knock-free engine operation. Operating parameters such as rail pressure, start of injection and amount of diesel injected are the factors that influence oscillations in the in-cylinder pressure trace after the start of combustion. Oscillations in the pre-mixed combustion phase, or ringing, are caused by the rapid conversion of large parts of the injected diesel.

Using natural gas as a fuel in internal combustion engines is a promising way to obtain efficient power generation with relatively low environmental impact. Dual fuel operation is especially interesting because it can combine the safety and reliability of the basic diesel concept with fuel flexibility. To deal with the greater number of degrees of freedom caused by the interaction of two fuels and combining different combustion regimes, it is imperative to use simulation methods in the development process to gain a better understanding of the combustion behavior. This paper presents current research into ignition and combustion of a premixed natural gas/air charge with a diesel pilot spray in a large bore diesel ignited gas engine with a focus on 3D-CFD simulation. Special attention was paid to injection and combustion. The highly transient behavior of the diesel injector especially at small injection quantities poses challenges to the numerical simulation of the spray.

It is critical for gas and dual fuel engines to have improved transient characteristics in order that they can successfully compete with diesel engines. Testing of transient behavior as well as of different control strategies for the multi-cylinder engine (MCE) should already be done on the single cylinder engine (SCE) test bed during the development process. This paper presents tools and algorithms that simulate transient MCE behavior on a SCE test bed. A methodology that includes both simulation and measurements is developed for a large two-stage turbocharged gas engine. Simple and fast models and algorithms are created that are able to provide the boundary conditions (e.g., boost pressure and exhaust back pressure) of a multi-cylinder engine in transient operation in real-time for use on the SCE test bed. The main models of the methodology are discussed in detail.

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.

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.

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.

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.