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Simultaneous reduction of engine pollutants (e.g., CO, THC, NOx, and soot) is one of the main challenges in the development of new combustion systems. Low-temperature combustion (LTC) concepts in compression ignition (CI) engines like premixed charged compression ignition (PCCI) make use of pre-injections to create a partly homogenous mixture. In the PCCI combustion regime, a direct correlation between injection and pollutant formation is no longer present because of long ignition delay times. In LTC combustion systems, the in-cylinder pressure sensor is normally used to help the combustion control. However, to allow the control of PCCI engines, new sensor concepts are investigated to obtain additional information about the PCCI combustion for advanced controller structures. In LTC combustion systems like gasoline-controlled autoignition (GCAI) concepts, the application of ion current sensors enables additional monitoring of the combustion process with real-time capability.

The transition towards sustainable mobility encourages research into biofuels for use in internal combustion engines. For these alternative energy carriers, high-fidelity experimental data of flame speeds influenced by pressure, temperature, and air-fuel equivalence ratio under engine-relevant conditions are required to support the development of robust combustion models for spark-ignition engines. E.g., physicochemical-based approximation formulas adjusted to the fuel provide similar accuracy as high fidelity chemical kinetic model calculations at a fraction of the computational cost and can be easily adopted in engine simulation codes. In the present study, a workflow to enable predictive combustion engine modeling is applied first for a gasoline reference fuel and two biofuel blends recently proposed by Dahmen and Marquardt [Energy Fuels, 2017].

The European Commission has released strict emission regulations for passenger cars in the past decade in order to improve air quality in cities and limit harmful emission exposure to humans. In the near future, even stricter regulations containing more realistic/demanding driving scenarios and covering more exhaust gas components are expected to be released. Passenger cars fueled with gasoline are one contributor to unhealthy air conditions, due to the fact that gasoline engines emit harmful air pollutants. One option to minimize harmful emissions would be to utilize specifically tailored, low emission synthetic fuels or fuel blends in internal combustion engines. Methyl formate and dimethyl carbonate are two promising candidates to replace or substitute gasoline, which in previous studies have proven to significantly decrease harmful pollutants.

Modeling combustion of transportation fuels remains a difficult task due to the extremely large number of species constituting commercial gasoline and diesel. However, for this purpose, multi-component surrogate fuel models with a reduced number of key species and dedicated reaction subsets can be used to reproduce the physical and chemical traits of diesel and gasoline, also allowing to perform CFD calculations. Recently, a detailed surrogate fuel kinetic model, named C3 mechanism, was developed by merging high-fidelity sub-mechanisms from different research groups, i.e. C0-C4 chemistry (NUI Galway), linear C6-C7 and iso-octane chemistry (Lawrence Livermore National Laboratory), and monocyclic aromatic hydrocarbons (MAHs) and polycyclic aromatic hydrocarbons (PAHs) (ITV-RWTH Aachen and CRECK modelling Lab-Politecnico di Milano).

The increasingly stringent limits on pollutant emissions from internal combustion engine-powered vehicles require the optimization of advanced combustion systems by means of virtual development and simulation tools. Among the gaseous emissions from spark-ignition engines, the unburned hydrocarbon (HC) emissions are the most challenging species to simulate because of the complexity of the multiple physical and chemical mechanisms that contribute to their emission. These mechanisms are mainly three-dimensional (3D) resulting from multi-phase physics - e.g., fuel injection, oil-film layer, etc. - and are difficult to predict even in complex 3D computational fluid-dynamic (CFD) simulations. Phenomenological models describing the relationships between the physical-chemical phenomena are of great interest for the modeling and simplification of such complex mechanisms.

On the way to emission-free mobility, future fuels must be CO2 neutral. To achieve this, synthetic fuels are being developed. In order to better assess the effects of the new fuels on the engine process, simulation models are being developed that reproduce the chemical and physical properties of these fuels. In this paper, the fuel DMC+ is examined. DMC+ (a mixture of dimethyl carbonate (DMC) and methyl formate (MeFo) mainly, characterized by the lack of C-C Bonds and high oxygen content) offers advantages with regard to evaporation heat, demand of oxygen and knock resistance. Furthermore, its combustion is almost particle free. With the aid of modern 0D/1D simulation methods, an assessment of the potential of DMC+ can be made. It is shown that the simulative conversion of a state-of-the-art gasoline engine to DMC+ fuel offers advantages in terms of efficiency in many operating points even if the engine design is not altered.

The reduction of cycle-to-cycle variations (CCV) is a prerequisite for the development and control of spark-ignition engines with increased efficiency and reduced engine-out emissions. To this end, Large-Eddy Simulations (LES) can improve the understanding of stochastic in-cylinder phenomena during the engine design process, if the employed modeling approach is sufficiently accurate. In this work, an inhouse code has been used to investigate CCV in a direct-injected spark ignition (DISI) engine under fuel-lean conditions with respect to a stoichiometric baseline operating point. It is shown that the crank angle when a characteristic fuel mass fraction is burned, e.g. MFB50, correlates with the equivalence ratio computed as a local average in the vicinity of the spark plug. The lean operating point exhibits significant CCV, which are shown to be correlated also with the in-cylinder subfilter-scale (SFS) kinetic energy.

Premixed charged compression ignition (PCCI) is an advanced combustion strategy, which has the potential to achieve ultra-low nitrogen oxide and soot emissions at high thermal efficiencies. PCCI combustion is characterized by a complex nonlinear chemical-physical process, which indicates that a physical description involves significant development times and also high computation cost. This paper presents a method to use cylinder pressure data and engine operations parameters for prediction of PCCI engine emissions by unsupervised learning and nonlinear identification techniques. The proposed method first uses principal component analysis (PCA) to reduce the dimension of the cylinder-pressure data. Based on the PCA analysis, a multi-input multi-out model was developed for nitrogen oxide and soot emission prediction by multi-layer perceptron (MLP) neural network.

In the foreseeable future, the transportation sector will continue to rely on internal combustion engines. Therefore, reduction of engine-out emissions and increase in engine efficiency are important goals to meet future legislative regulations and restricted fuel resources. One viable option, which provides lower peak temperatures and increased mixture homogeneity and thus simultaneously reduces nitric oxide as well as soot, is a low-temperature combustion (LTC) concept. However, this might result in an increase of unburnt hydrocarbon, carbon monoxide, and combustion noise due to early combustion phasing and lower engine efficiency. Various studies show that these drawbacks can be compensated by advanced injection strategies, e.g. by employing multiple injections. The aim of this work is to identify the optimum injection strategy, which enables a wide range of engine operating points in LTC mode with reduced engine-out emissions.

The Computational Chemistry Consortium (C3) is dedicated to leading the advancement of combustion and emissions modeling. The C3 cluster combines the expertise of different groups involved in combustion research aiming to refine existing chemistry models and to develop more efficient tools for the generation of surrogate and multi-fuel mechanisms, and suitable mechanisms for CFD applications. In addition to the development of more accurate kinetic models for different components of interest in real fuel surrogates and for pollutants formation (NOx, PAH, soot), the core activity of C3 is to develop a tool capable of merging high-fidelity kinetics from different partners, resulting in a high-fidelity model for a specific application. A core mechanism forms the basis of a gasoline surrogate model containing larger components including n-heptane, iso-octane, n-dodecane, toluene and other larger hydrocarbons.

Direct injection (DI) compressed natural gas (CNG) engines are emerging as a promising technology for highly efficient and low-emission engines. However, the design of DI systems for compressible gas is challenging due to supersonic flows and the occurrence of shocks. An outwardly opening poppet-type valve design is widely used for DI-CNG. The formation of a hollow cone gas jet resulting from this configuration, its subsequent collapse, and mixing is challenging to characterize using experimental methods. Therefore, numerical simulations can be helpful to understand the process and later to develop models for engine simulations. In this article, the results of high-fidelity large-eddy simulation (LES) of a stand-alone injector are discussed to understand the evolution of the hollow cone gas jet better.

Especially for internal combustion engine simulations, various combustion models rely on the laminar burning velocity. With respect to computational time needed for CFD, the calculation of laminar burning velocities using a detailed chemical mechanism can be replaced by incorporation of approximation formulas, based on rate-ratio asymptotics. This study revisits an existing analytical approximation formula [1]. It investigates applicable temperature, pressure, and equivalence ratio ranges with special focus on engine combustion conditions. The fuel chosen here is methane and mixtures are composed of methane and air. The model performance to calculate the laminar burning velocity are compared with calculated laminar burning velocities using existing state of the art detailed chemical mechanisms, the GRI Mech 3.0 [2], the ITV RWTH [3], and the Aramco mechanism [4].

The performance of Gasoline Direct Injection (GDI) engines is governed by multiple physical processes such as the internal nozzle flow and the mixing of the liquid stream with the gaseous ambient environment. A detailed knowledge of these processes even for complex injectors is very important for improving the design and performance of combustion engines all the way to pollutant formation and emissions. However, many processes are still not completely understood, which is partly caused by their restricted experimental accessibility. Thus, high-fidelity simulations can be helpful to obtain further understanding of GDI injectors. In this work, advanced simulation and experimental methods are combined in order to study the spray characteristics of two different 3-hole GDI injectors.

The performance of modern boosted gasoline engines is limited at high loads by knock, stochastic Low Speed Pre-Ignition as well as megaknock. The main objective of the present work is to develop a predictive combustion model to investigate auto-ignition and megaknock events at high load conditions in gasoline engines. A quasi one-dimensional combustion simulation tool has been developed to model abnormal combustion events in gasoline engines using detailed chemical kinetics and a multi zone wall heat transfer model. The model features six boundary layers representing specific geometrical features such as liner and piston with individual wall temperatures and chemistry to accurately track the individual zone’s thermodynamic properties. The accuracy of the utilized auto-ignition and one-dimensional spark ignition combustion models was demonstrated by validating against experimental data.

For compliance with legislative regulations as well as restricted resources of fossil fuel, it is essential to further reduce engine-out emissions and increase engine efficiency. As a result of lower peak temperatures and increased homogeneity, premixed Low-Temperature Combustion (LTC) has the potential to simultaneously reduce nitrogen oxides (BSNOx) and soot. However, LTC can lead to higher emissions of unburnt total hydrocarbons (BSTHC) and carbon monoxide (BSCO). Furthermore, losses in efficiency are often observed, due to early combustion phasing (CA50) before top dead center (bTDC). Various studies have shown possibilities to counteract these drawbacks, such as split-injection strategies or different nozzle geometries. In this work, the combination of both is investigated. Three different nozzle geometries with included spray angles of 100°, 120°, and 148° and four injection strategies are applied to investigate the engine performance.

Compared to conventional injection techniques, Gasoline Direct Injection (GDI) has a lot of advantages such as increased fuel efficiency, high power output and low emission levels, which can be more accurately controlled. Therefore, this technique is an important topic of today's injection system research. Although the operating conditions of GDI injectors are simpler from a numerical point of view because of smaller Reynolds and Weber numbers compared to Diesel injection systems, accurate simulations of the breakup in the vicinity of the nozzle are very challenging. Combined with the complications of experimental techniques that could be applied inside the nozzle and at the nozzle exit, this is the reason for the lack of understanding the primary breakup behavior of current GDI injectors.

The use of exhaust gas recirculation (EGR) in internal combustion engines has significant impacts on combustion and emissions. EGR can be used to reduce in-cylinder NOx production, reduce emitted particulate matter, and enable advanced forms of combustion. To maximize the benefits of EGR, the exhaust gases are often cooled with on-engine liquid to gas heat exchangers. A common problem with this approach is the build-up of a fouling layer inside the heat exchanger due to thermophoresis and condensation, reducing the effectiveness of the heat exchanger in lowering gas temperatures. Literature has shown the effectiveness to initially drop rapidly and then approach steady state after a variable amount of time. The asymptotic behavior of the effectiveness has not been well explained. A range of theories have been proposed including fouling layer removal, changing fouling layer properties, and cessation of thermophoresis.

Exhaust gas recirculation (EGR) coolers are commonly used in diesel engines to reduce the temperature of recirculated exhaust gases in order to reduce NOx emissions. The presence of a cool surface in the hot exhaust causes particulate soot deposition as well as hydrocarbon and water condensation. Fouling experienced through deposition of particulate matter and hydrocarbons results in degraded cooler effectiveness and increased pressure drop. In this study, a visualization test setup is designed and constructed so that the effect of water condensation on the deposit formation and growth at various coolant temperatures can be studied. A water-cooled surrogate rectangular channel is employed to represent the EGR cooler. One side of the channel is made of glass for visualization purposes. A medium duty diesel engine is used to generate the exhaust stream.

Premixed charge compression ignition (PCCI) is an interesting alternative to conventional diesel combustion, as it allows very low emission levels for part load operation. The difficult control of the onset of combustion is an obstacle to the implementation of PCCI. In a recent study, different mixtures of gasoline and diesel fuel have been used in a modified diesel engine to delay the ignition and thus to allow for a substantial premixing time. For these cases, very low levels of particulate emissions have been reported. However, the emissions of CO and NOx were considerably high. In this study, combustion and pollutant formation in the above-mentioned modified diesel engine are simulated using the representative interactive flamelet (RIF) approach. A detailed chemical reaction mechanism for a mixture of n-heptane, iso-octane, toluene, and ethanol, serving as surrogate fuel for the diesel-gasoline blend, is used for the simulations.

Premixed low temperature combustion (LTC) in diesel engines simultaneously reduces soot and NOx at the expense of increased hydrocarbon (HC) and CO emissions. The use of biodiesel in the LTC regime has been shown to produce lower HC emissions than petroleum diesel; however, unburned methyl esters from biodiesel are more susceptible to particulate matter (PM) formation following atmospheric dilution due to their low volatility. In this study, the efficacy of a production-type diesel oxidation catalyst (DOC) for the conversion of light hydrocarbons species and heavier, semi-volatile species like those in unburned fuel is examined. Experimental data were taken from a high speed direct-injection diesel engine operating in a mid-load, late injection partially premixed LTC mode on ultra-low sulfur diesel (ULSD) and neat soy-based biodiesel (B100). Gaseous emissions were recorded using a conventional suite of analyzers and individual light HCs were measured using an FT-IR analyzer.