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The European Union has defined legally binding CO2-fleet targets for new cars until 2030. Therefore, improvement of fuel economy and carbon dioxide emission reduction is becoming one of the most important issues for the car manufacturers. Today’s conventional car powertrain systems are reaching their technical limits and will not be able to meet future CO2 targets without further improvement in combustion efficiency, using low carbon fuels (LCF), and at least mild electrification. This paper demonstrates a highly efficient and performant combustion engine concept with a passive pre-chamber spark plug, operating at stoichiometric conditions and powered with liquefied petroleum gas (LPG). Even from fossil origin, LPG features many advantages such as low carbon/hydrogen ratio, low price and broad availability. In future, it can be produced from renewables and it is in liquid state under relatively low pressures, allowing the use of conventional injection and fuel supply components.

Methane abatement in the exhaust gas of natural gas engines is much more challenging in respect to the oxidation of other higher order hydrocarbons. Under steady state λ sweep, the methane conversion efficiency is high at exact stoichiometric, and decreases steeply under both slightly rich and slightly lean conditions. Transient lean to rich transitions can improve methane conversion at the rich side. Previous experimental work has attributed the enhanced methane conversion to activation of methane steam reforming. The steam reforming rate, however, attenuates over time and the methane conversion rate gradually converges to the low steady state values. In this work, a reactor model is established to predict steady state and transient transition characteristics of a three-way catalyst (TWC) mounted in the exhaust of a natural gas heavy-duty engine.

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).

Further improvements of internal combustion engines to reduce fuel consumption and to face future legislation constraints are strictly related to the study of mixture formation. The reason for that is the desire to supply the engine with homogeneous charge, towards the direction of a global stoichiometric blend in the combustion chamber. Fuel evaporation and thus mixture quality mostly depend on injector atomization features and charge motion within the cylinder. 3D-CFD simulations offer great potential to study not only injector atomization quality but also the evaporation behavior. Nevertheless coupling optical measurements and simulations for injector analysis is an open discussion because of the large number of influencing parameters and interactions affecting the fuel injection’s reproducibility. For this purpose, detailed numerical investigations are used to describe the injection phenomena.

Intensified emission regulations as well as consumption demands lead to an increasing significance of unburned hydrocarbon (UHC) emissions for diesel engines. On the one hand, the quantity of hydrocarbon (HC) raw emissions is important for emission predictions as well as for the exhaust after treatment. On the other hand, HC emissions are also important for predicting combustion efficiency and thus fuel consumption, since a part of unreleased chemical energy of the fuel is still bound in the HC molecules. Due to these reasons, a simulation model for predicting HC raw emissions was developed for diesel engines based on a phenomenological two-zone model. The HC model takes three main sources of HC emissions of diesel engines into account: Firstly, it contains a sub-model that describes the fuel dribble out of the injector after the end of injection. Secondly, HC emissions from cold peripheral zones near cylinder walls are determined in another sub-model.

In recent years, the increase of gasoline fuel injection pressure is a way to improve thermal efficiency and lower engine-out emissions in GDI homogenous combustion concept. The challenge of controlling particulate formation as well in mass and number concentrations imposed by emissions regulations can be pursued improving the mixture preparation process and avoiding mixture inhomogeneity with ultra-high injection pressure values up to 100 MPa. The increase of the fuel injection pressure in GDI homogeneous systems meets the demand for increased injector static flow, while simultaneously improves the spray atomization and mixing characteristics with consequent better combustion performance. Few studies quantify the effects of high injection pressure on transient gasoline spray evolution. The aim of this work was to simulate with OpenFOAM the spray morphology of a commercial gasoline injected in a constant volume vessel by a prototypal GDI injector.

The modeling of fuel sprays under well-characterized conditions relevant for heavy-duty Diesel engine applications, allows for detailed analyses of individual phenomena aimed at improving emission formation and fuel consumption. However, the complexity of a reacting fuel spray under heavy-duty conditions currently prohibits direct simulation. Using a systematic approach, we extrapolate available spray models to the desired conditions without inclusion of chemical reactions. For validation, experimental techniques are utilized to characterize inert sprays of n-dodecane in a high-pressure, high-temperature (900 K) constant volume vessel with full optical access. The liquid fuel spray is studied using high-speed diffused back-illumination for conditions with different densities (22.8 and 40 kg/m3) and injection pressures (150, 80 and 160 MPa), using a 0.205-mm orifice diameter nozzle.

The most significant operation limit prohibiting the further reduction of the CO2 emissions of gasoline engines is the occurrence of knock. Thus, being able to predict the incidence of this phenomenon is of vital importance for the engine process simulation - a tool widely used in the engine development. Common knock models in the 0D/1D simulation are based on the calculation of a pre-reaction state of the unburnt mixture (also called knock integral), which is a simplified approach for modeling the progress of the chemical reactions in the end gas where knock occurs. Simulations of thousands of knocking single working cycles with a model representing the Entrainment model’s unburnt zone were performed using a detailed chemical reaction mechanism. The investigations showed that, at specific boundary conditions, the auto-ignition of the unburnt mixture resulting in knock happens in two stages.

The interaction of turbulent premixed methane combustion with the surrounding flow field can be studied using optically accessible test rigs such as a rapid compression expansion machine (RCEM). The high flexibility offered by such a test rig allows its operation at various thermochemical conditions at ignition. However, limitations inherent to such test rigs due to the absence of an intake stroke do not allow turbulence production as found in IC-engines. Hence, means to introduce turbulence need to be implemented and the relevant turbulence quantities have to be identified in order to enable comparability with engine relevant conditions. A dedicated high-pressure direct injection of air at the beginning of the compression phase is considered as a measure to generate adjustable turbulence intensities at spark timing and during the early flame propagation.

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.

For long haul transport, diesel engine due to its low fuel consumption and low operating costs will remain dominant over a long term. In order to achieve CO2 neutrality, the use of electricity-based, synthetic fuels (e-fuels) provides a solution. Especially the group of oxymethylene ethers (OME) is given much attention because of its soot-free combustion. However, the new fuel properties and the changed combustion characteristics place new demands on engine design. Meanwhile, the use of new fuels also creates new degrees of freedom to operate diesel engines. In this work, the application of dimethoxymethane (OME1) is investigated by means of 1D simulation at three operating points in a truck diesel engine. The subsystems of fuel injection, air path and exhaust gas are sequentially adjusted for the purpose of low emissions, especially for low nitrogen oxides (NOx).

As a result of the R&D focus being shifted from internal combustion engines to electrified powertrains, resources for the development of internal combustion engines are restricted more and more. With that, the importance of highly efficient engine development tools is increased. In this context, 0D/1D engine simulation offers the advantage of low computational effort and fast engine model set-up. To ensure a high predictive ability of the engine simulation, a reliable burn rate model is needed. Considering the increasing interest in alternative fuels, the aspect of predicting the fuel influence on combustion is of special importance. To reach these targets, the change of engine combustion characteristics with changing fuels and changing air-fuel-ratios were investigated systematically in a first step. For this purpose, engine test bed data were compared with expected fuel-dependent flame wrinkling trends based on Markstein/Lewis number theory.

As a consequence of reduced fuel consumption, direct injection gasoline engines have already prevailed against port fuel injection. However, in-cylinder fuel homogenization strongly depends on charge motion and injection strategies and can be challenging due to the reduced available time for mixture formation. An insufficient homogenization has generally a negative impact on the combustion and therefore also on efficiency and emissions. In order to reach the targets of the intensified CO2 emission reduction, further increase in efficiency of SI engines is essential. In this connection, 0D/1D simulation is a fundamental tool due to its application area in an early stage of development and its relatively low computational costs. Certainly, inhomogeneities are still not considered in quasi dimensional combustion models because the prediction of mixture formation is not included in the state of the art 0D/1D simulation.

Today, Direct-Injection systems are widely used on Spark-Ignition engines in combination with turbo-charging to reduce the fuel-consumption and the knock risks. In particular, the spread of Gasoline Direct Injection (GDI) systems is mainly related to the use of new generations of multi-hole, high-pressure injectors whose characteristics are quite different with respect to the hollow-cone, low-pressure injectors adopted in the last decade. This paper presents the results of an experimental campaign conducted on the spray produced by a GDI six-holes injector into a constant volume vessel with optical access. The vessel was filled with air at atmospheric pressure. Different operating conditions were considered for an injection pressure ranging from 3 to 20 MPa. For each operating condition, spray images were acquired by a CCD camera and then post processed to evaluate the spray penetration and cone angles.

Many studies have been carried out to optimize the aerodynamic performances of a single car or a single vehicle. In present days the traffic increases and sophisticated technologies are developing to guarantee the drivers safety, to minimize the fuel consumption and be more environmentally friendly. Within this research area a new technique that is being studied is Platooning: this means that different vehicles travel in a configuration that minimizes the aerodynamic drag and therefore the fuel consumption and the longitudinal space. In the present study platoons with different vehicles and configurations are taken into account, to analyze the influence of car shape and relative distance between the vehicles. The research has been carried out using CFD techniques to investigate the different flow fields around different platoons, while wind tunnel tests have been used to validate the results of the CFD simulations.

The Pennsylvania State University is one of 16 North American universities that participated in the EcoCAR advanced vehicle technology competition (http://www.ecocarchallenge.org/). A series-hybrid-electric vehicle based on a General Motors crossover SUV platform has been designed, built and tested for this purpose. The powertrain features a 1.3 L turbodiesel engine running on a B20 fuel system, a 75kW generator directly coupled to the engine and advanced lithium-ion batteries. In this paper, the vehicle architecture and control strategy are detailed and performance predictions (e.g., acceleration, fuel consumption and emissions) are presented. This includes discussion of the development process that led to the selected designs. The predicted performance is compared with data obtained on a chassis dynamometer and during on-road measurements over specified drive cycles.

For a reliable and accurate simulation of SI engines reproduction of their operation limits (misfiring and knock limit) and in this context the knowledge of cyclic combustion variations and their influence on knock simulation are mandatory. For this purpose in this paper a real working-process simulation approach for the ability to predict cycle-to-cycle variations (ccv) of gasoline engines is proposed. An extensive measurement data base of four different test engines applying various operation strategies was provided in order to gain a better understanding of the physical background of the cyclic variations. So the ccv initiated by dilution strategies (internal EGR, lean operation), the ccv at full load and at the knock limit could be investigated in detail. Finally, the model was validated on the basis of three further engines which were not part of the actual development process.

This paper presents a cohesive set of engine-in-the-loop (EIL) studies examining the use of hierarchical model-predictive control for fuel consumption minimization in a class-8 heavy-duty truck intended to be equipped with Level-1 connectivity/automation. This work is motivated by the potential of connected/automated vehicle technologies to reduce fuel consumption in both urban/suburban and highway scenarios. The authors begin by presenting a hierarchical model-predictive control scheme that optimizes multiple chassis and powertrain functionalities for fuel consumption. These functionalities include: vehicle routing, arrival/departure at signalized intersections, speed trajectory optimization, platooning, predictive optimal gear shifting, and engine demand torque shaping. The primary optimization goal is to minimize fuel consumption, but the hierarchical controller explicitly accounts for other key objectives/constraints, including operator comfort and safe inter-vehicle spacing.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

Since 0D/1D-simulations of natural gas spark ignition engines use model theories similar to gasoline engines, the impact of changing fuel characteristics needs to be taken into consideration in order to obtain results of higher quality. For this goal, this paper proposes some approaches that consider the influence of binary fuel mixtures such as methane with up to 40 mol-% of ethane, propane, n-butane or hydrogen on laminar flame speed and knock behavior. To quantify these influences, reaction kinetics calculations are carried out in a wide range of the engine operation conditions. Obtained results are used to update and extend existing sub-models. The model quality is validated by comparing measured burn rates with simulation results. The benefit of the new sub-models are utilized by predicting the influence the fuel takes on engine operating limits in terms of knocking and lean misfire limits, the latter being determined by using a cycle-to-cycle variation model.