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In this work an integration between a 1D code (Gasdyn) with a CFD code (OpenFOAM®) has been applied to improve the performance of a Moto3 engine. The four-stroke, single cylinder S.I. engine was modeled, in order to predict the wave motion in the intake and exhaust systems and to study how it affects the cylinder gas exchange process. The engine considered was characterized by having an air induction system with integrated filter cartridge, air-box and intake runner, including two fuel injectors, resulting in a complex air-path from the intake mouth to the intake valves, which presents critical aspects when a 1D modeling is addressed. The exhaust and intake systems have been optimized form the point of view of the wave action. However, due to the high revolution speed reached by this type of engine, the interaction between the gas stream and the fuel spray becomes a key aspect to be addressed in order to achieve the best performance at the desired operating condition.

The demand of game-changing technologies to improve efficiency and abate emissions of heavy-duty trucks and off-road vehicles promoted the development of novel engine concepts. The Recuperated Split-Cycle (R-SC) engine allows to recover the exhaust gases energy into the air intake by separating the compression and combustion stages into two different but connected cylinders: the compressor and expander, respectively. The result is a potential increase of the engine thermal efficiency. Accordingly, the 3D-computational fluid dynamics (CFD) modelling of the gas exchange process and the combustion evolution inside the expander becomes essential to control and optimize the R-SC engine concept. This work aims to address the most challenging numerical aspects encountered in a 3D numerical simulation of an R-SC engine.

Nowadays quasi-3D approaches are included in many commercial and research 1D numerical codes, in order to increase their simulation accuracy in presence of complex shape 3D volumes, e.g. plenums and silencers. In particular, these are regarded as valuable approaches for application during the design phase of an engine, for their capability of predicting non-planar waves motion and, on the other hand, for their low requirements in terms of computational runtime. However, the generation of a high-quality quasi-3D computational grid is not always straightforward, especially in case of complex elements, and can be a time-consuming operation, making the quasi-3D tool a less attractive option. In this work, a quasi-3D module has been implemented on the basis of the open-source CFD code OpenFOAM and coupled with the 1D code GASDYN.

Active prechamber combustion systems for SI engines represent a feasible and effective solution in reducing fuel consumption and pollutant emissions for both marine and ground heavy-duty engines. However, reliable and low-cost numerical approaches need to be developed to support and speed-up their industrial design considering their geometry complexity and the involved multiple flow length scales. This work presents a CFD methodology based on the RANS approach for the simulation of active prechamber spark-ignition engines. To reduce the computational time, the gas exchange process is computed only in the prechamber region to correctly describe the flow and mixture distributions, while the whole cylinder geometry is considered only for the power-cycle (compression, combustion and expansion). Outside the prechamber the in-cylinder flow field at IVC is estimated from the measured swirl ratio.

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.

This work presents a comprehensive numerical model for ice accretion and Ice Protection System (IPS) simulation over a 2D component, such as an airfoil. The model is based on the Myers model for ice accretion and extended to include the possibility of a heated substratum. Six different icing conditions that can occur during in-flight ice accretion with an Electro-Thermal Ice Protection System (ETIPS) activated are identified. Each condition presents one or more layers with a different water phase. Depending on the heat fluxes, there could be only liquid water, ice, or a combination of both on the substratum. The possible layers are the ice layer on the substratum, the running liquid film over ice or substratum, and the static liquid film between ice and substratum caused by ice melting. The last layer, which is always present, is the substratum. The physical model that describes the evolution of these layers is based on the Stefan problem. For each layer, one heat equation is solved.

The paper illustrates and validates a novel predictive combustion model for the estimation of performances and pollutant production in CI engines. The numerical methodology was developed by the authors for near real-time applications, while aiming at an accurate description of the air mixing process by means of a multi-zone approach of the air-fuel mass. Charge stratification is estimated via a 2D representation of the fuel spray distribution that is numerically derived by an axial one-dimensional control-volume description of the direct injection. The radial coordinate of each control volume is reconstructed a posteriori by means of a local distribution function. Fuel mass clustered in each zone is further split in ‘liquid’, ‘unburnt’ and ‘burnt’ sub-zones, given the local properties of the fuel spray control volumes with respect to space-time location of modelled ignition delay, liquid length, and flame lift-off.

SI engines fueled with hydrogen represent a promising powertrain solution to meet the ambitious target of carbon-free emissions at the tailpipe. Therefore, fast and reliable numerical tools can significantly support the automotive industry in the optimization of such technology. In this work, a 1D-3D methodology is presented to simulate in detail the combustion process with minimal computational effort. First, a 1D analysis of the complete engine cycle is carried out on the user-defined powertrain configuration. The purpose is to achieve reliable boundary conditions for the combustion chamber, based on realistic engine parameters. Then, a 3D simulation of the power-cycle is performed to mimic the combustion process. The flow velocity and turbulence distributions are initialized without the need of simulating the gas exchange process, according to a validated technique.

The dynamics and evolution of turbulent structures inside an engine-like geometry are investigated by means of Large Eddy Simulation. A simplified configuration consisting of a flat-top cylinder head with a fixed, axis-centered valve and low-speed piston has been simulated by the finite volume CFD code OpenFOAM®; the standard version of the software has been extended to include the compressible WALE subgrid-scale model, models for the generation of synthetic turbulence, some improvements to the mesh motion strategy and algorithms for LES data post-processing. In order to study both the initial transient and the quasi- steady operating conditions, ten complete engine cycles have been simulated. Phase and spatial averages have been performed over cycles three to ten in order to extract first and second moment of velocity; these quantities have then been used to validate the numerical procedure by comparison against experimental data.

A new electric powertrain and axle for light/medium trucks is presented. The indoor testing and the simulation of the dynamic behavior are performed. The powertrain and axle has been produced by Streparava and tested at the Laboratory for the Safety of Transport of the Politecnico di Milano. The tests were aimed at defining the multi-physics perfomance of the powertrain and axle (efficiency, acceleration and braking, temperature and NVH). The whole system for indoor tests was composed by the powertrain and axle (electric motor, driveline, suspensions, wheels) and by the test rig (drums, driveline and electric motor). The (driving) axle was positioned on a couple of drums, and the drums provided the proper torques to the wheels to reproduce acceleration and braking. Additionally a cleat fixed on one drum excited the vibration of the suspensions and allowed assessing NVH performance. The simulations were based on a special co-simulation between 1D-AMESIM and VIRTUAL.LAB.

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

This paper provides a review on state-of-art modern cooling systems employed for thermal cooling of electric motors for vehicle applications. In recent years, the pursue of a more sustainable and ecofriendly mobility has pushed the research towards the development of electric vehicle powertrain systems. Besides the evident advantages of the adoption of electric traction systems in terms of pollution and efficiency, the need of an effective cooling system for the electric machine components gained more and more importance in order to maintain high efficiency and ensure high durability. In fact, it is known that high temperatures can be harmful for the electric motor: besides the evident damages for mechanical parts, the influence on the permanent magnet properties is not negligible [1] [2]. In this fast-evolving environment, different solutions for the thermal problem have been researched and adopted, each one with its own pros and cons.

The paper focuses on the development of a mesh moving method based on non-conformal topologically changing grids applied to the simulation of IC engines, where the prescribed motion of piston and valves is accomplished by rigidly translating the sub-domain representing the moving component. With respect to authors previous work, a more robust and efficient algorithm to handle the connectivity of non-conformal interfaces and a mesh-motion solver supporting multiple layer addition/removal of cells, to decouple the time-step constraints of the mesh motion and of the fluid dynamics, has been implemented as a C++ library to extend the already existing classes for dynamic mesh handling of the finite-volume, open-source CFD code OpenFOAM®. Other new features include automatic decomposition of large multiple region domains to preserve processors load balance with topological changes for parallel computations and additional tools for automatic preprocessing and case setup.

Modeling the combustion process of a diesel-biodiesel fuel spray in a 3-dimensional (3D) computational fluid dynamics (CFD) domain remains challenging and time-consuming despite the recent advancement in computing technologies. Accurate representation of the in-cylinder processes is essential for CFD studies to provide invaluable insights into these events, which are typically limited when using conventional experimental measurement techniques. This is especially true for emerging new fuels such as biodiesels since fundamental understanding of these fuels under combusting environment is still largely unknown. The reported work here is dedicated to evaluating the Adaptive Local Mesh Refinement (ALMR) approach in OpenFOAM® for improved simulation of reacting biodiesel fuel spray. An in-house model for thermo-physical and transport properties is integrated to the code, along with a chemical mechanism comprising 113 species and 399 reactions.

The definition of a robust methodology to perform a full-cycle CFD simulation of IC engines requires as first step the availability of a reliable grid generation tool, which does not only have to guarantee a high quality mesh but also has to prove to be efficient in terms of required time. In this work the authors discuss a novel approach entirely based on the OpenFOAM technology, in which the available 3D grid generator was employed to automatically create meshes containing hexahedra and split-hexahedra from triangulated surface geometries in Stereolithography (STL) format. The possibility to introduce local refinements and boundary layers makes this tool suitable for IC engine simulations. Grids are sequentially generated at target crank angles which are automatically determined depending on user specified settings such as maximum mesh validity interval and quality parameters like non-orthogonality, skewness and aspect ratio.

Prediction of in-cylinder flows and fuel-air mixing are two fundamental pre-requisites for a successful simulation of direct-injection engines. Over the years, many efforts were carried out in order to improve available turbulence and spray models. However, enhancements in physical modeling can be drastically affected by how the mesh is structured. Grid quality can negatively influence the prediction of organized charge motion structures, turbulence generation and interaction between in-cylinder flows and injected sprays. This is even more relevant for modern direct injection engines, where multiple injections and control of charge motions are employed in a large portion of the operating map. Currently, two different approaches for mesh generation exist: manual and automatic. The first makes generally possible to generate high-quality meshes but, at the same time, it is very time consuming and not completely free from user errors.

The increasing diffusion of gasoline direct injection (GDI) engines requires a more detailed and reliable description of the phenomena occurring during the fuel injection process. As well known the thermal and fluid-dynamic conditions present in the combustion chamber greatly influence the air-fuel mixture process deriving from GDI injectors. GDI fuel sprays typically evolve in wide range of ambient pressure and temperatures depending on the engine load. In some particular injection conditions, when in-cylinder pressure is relatively low, flash evaporation might occur significantly affecting the fuel-air mixing process. In some other particular injection conditions spray impingement on the piston wall might occur, causing high unburned hydrocarbons and soot emissions, so currently representing one of the main drawbacks of GDI engines.

The thorough understanding of the effects due to the fuel direct injection process in modern gasoline direct injection engines has become a mandatory task to meet the most demanding regulations in terms of pollutant emissions. Within this context, computational fluid dynamics proves to be a powerful tool to investigate how the in-cylinder spray evolution influences the mixture distribution, the soot formation and the wall impingement. In this work, the authors proposed a comprehensive methodology to simulate the air-fuel mixture formation into a gasoline direct injection engine under multiple operating conditions. At first, a suitable set of spray sub-models, implemented into an open-source code, was tested on the Engine Combustion Network Spray G injector operating into a static vessel chamber. Such configuration was chosen as it represents a typical gasoline multi-hole injector, extensively used in modern gasoline direct injection engines.

Predictive combustion models are useful tools towards the development of clean and efficient engines operating with alternative fuels. This work intends to validate two different combustion models on compression-ignition engines fueled with Dimethyl Ether. Both approaches give a detailed characterization of the combustion kinetics, but they substantially differ in how the interaction between fluid-dynamics and chemistry is treated. The first one is single-flamelet Representative Interactive Flamelet, which considers turbulence-kinetic interaction but cannot correctly describe the stabilization of the flame. The second, named Tabulated Well Mixed, correctly accounts for local flow and mixture conditions but does not consider interaction between turbulence and chemistry. An experimental campaign was carried out on a heavy-duty truck engine running on DME at a constant load considering trade-off of EGR and SOI.

The employment of hydrogen as energy carrier for transportation sector represents a significant challenge for powertrains. Spark-ignition (SI) engines are feasible and low-cost devices to convert the hydrogen chemical energy into mechanical work. However, significant efforts are needed to successfully retrofit the available configurations. The computational fluid dynamics (CFD) modelling represents a useful tool to support experiments, clarifying the impact of the engine characteristics on both the mixture preparation and the combustion development. In this work, a CFD investigation is carried out on typical light-duty SI engine configurations, exploring the two main strategies of hydrogen addition: port fuel injection (PFI) and direct injection (DI). The purpose is to assess the behaviour of widely-used numerical models and methodologies when hydrogen is employed instead of traditional carbon-based fuels.