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The electrochemical performance of a lithium-ion battery is strongly affected by the temperature. During charge and discharge cycles, batteries are subjected to an increment of temperature that can accelerate aging and loss of efficiency if critical values are reached. Knowing the thermal parameters that affect the heat exchange between the battery surface and the surrounding environment (air, cooling fins, plates, etc…) is fundamental to their thermal management. In this work, thermal imaging is applied to a laminated lithium-polymers battery as a non-invasive temperature-indication method. Measurements are taken during the discharge phase and the following cooling down until the battery reaches the ambient temperature. The 2d images are used to analyze the homogeneity of the temperature distribution on the battery surface. Then, experimental results are coupled with mathematical correlations.

The numerical reconstruction of the liquid jet generated by a multi-hole injector, operating in flash-boiling conditions, has been developed by means of a Eulerian- Lagrangian CFD code and validated thanks to experimental data collected with schlieren and Mie scattering imaging techniques. The model has been tested with different injection parameters in order to recreate various possible engine thermodynamic conditions. The work carried out is framed in the growing interest present around the gasoline direct-injection systems (GDI). Such technology has been recognized as an effective way to achieve better engine performance and reduced pollutant emissions. High-pressure injectors operating in flashing conditions are demonstrating many advantages in the applications for GDI engines providing a better fuel atomization, a better mixing with the air, a consequent more efficient combustion and, finally, reduced tailpipe emissions.

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.

Isooctane sprays from a multi-hole GDI injector were investigated in a constant volume chamber by means of high speed imaging techniques. The tests were performed under inert conditions (nitrogen), at temperatures and densities ranging between representative operating conditions of late injection, flash boiling and early injection in a GDI engine. The global parameters of the sprays were obtained by processing Schlieren, Shadowgraph, DBI and Mie-scattering images through an in-house image processing method. Thus, the boundaries of the spray vapor phase can be easily detected with great accuracy, regardless of whether Schlieren or the less sensitive shadowgraph imaging is used. Furthermore, the boundaries of the liquid phase were also obtained from shadowgraph images and compared with those obtained through DBI and scattering. The results show that the signature of the liquid phase in a shadowgraph image can be distinguished from that of the vaporized fuel.

The in-cylinder direct injection of natural gas can be a further step towards cleaner and more efficient internal combustion engines (ICE). However, the injector design and its characterization, both experimentally and by numerical simulation, is challenging because of the complex fluid dynamics related to gas compressibility and the small length scale. In this work, the under-expanded flow of methane from an outward-opening poppet-valve injector has been experimentally characterized by high-speed schlieren imaging. The investigation has been performed at ambient temperature and pressure and different nozzle pressure ratios (NPR) ranging from 10 to 18. The gaseous jet has been characterized in terms of its macroscale parameters. A scaling-law analysis of the results has been performed. The gas-dynamic structure at the nozzle exit has been also investigated.

This work presents the results of an experimental investigation on a GDI injector, in order to analyze fuel injection process and atomization phenomenon, correlating imaging and vibro-acoustic diagnostic techniques. A single-hole, axially-disposed, 0.200 mm diameter GDI injector was used to spray commercial gasoline in a test chamber at room temperature and atmospheric backpressure. The explored injection pressures were ranged from 5.0 to 20.0 MPa. Cycle-resolved acquisitions of the spray evolution were acquired by a high-speed camera. Simultaneously, the vibro-acoustic response of the injector was evaluated. More in detail, noise data acquired by a microphone sensor were analyzed for characterizing the acoustic emission of the injection, while a spherical loudspeaker was used to excite the spray injection at a proper distance detecting possible fuel spray resonance phenomena.

The application of more efficient compression ignition combustion concepts requires advancement in terms of fuel injection technologies. The injector nozzle is the most critical component of the whole injection system for its impact on the combustion process. It is characterized by the number of holes, diameter, internal shape, and opening angle. The reduction of the nozzle hole diameter seems the simplest way to promote the atomization process but the number of holes must be increased to keep constant the injected fuel mass. This logic has been applied to the development of a new generation of injectors. First, the tendency to increase the nozzle number and to reduce the diameter has led to the replacement of the nozzle with a circular plate. The vertical movement of the needle generates an annulus area for the fuel delivery on 360 degrees, so controlling the atomization as a function of the vertical plate position.

In order to meet the requirements in the stringent emission regulations, more and more research work has been focused on homogeneous charge compression ignition (HCCI) and partially premixed combustion (PPC) or partially premixed compression ignition (PCCI) as they have the potential to produce low NOx and soot emissions without adverse effects on engine efficiency. The mixture formation and charge stratification influence the combustion behavior and emissions for PPC/PCCI, significantly. An ultra-high speed burst-mode laser is used to capture the mixture formation process from the start of injection until several CADs after the start of combustion in a single cycle. To the authors’ best knowledge, this is the first time that such a high temporal resolution, i.e. 0.2 CAD, PLIF could be accomplished for imaging of the in-cylinder mixing process. The capability of resolving single cycles allows for the influence of cycle-to-cycle variations to be eliminated.

Gasoline Direct Injection (GDI) is a leading technology for Spark Ignition (SI) engines: control of the injection process is a key to design the engine properly. The aim of this paper is a numerical investigation of the gasoline injection and the resulting development of plumes from an 8-hole Spray G injector into a quiescent chamber. A LES approach has been used to represent with high accuracy the mixing process between the injected fuel and the surrounding mixture. A Lagrangian approach is employed to model the liquid spray. The fuel, considered as a surrogate of gasoline, is the iso-octane which is injected into the high-pressure vessel filled with nitrogen. The numerical results have been compared against experimental data realized in the optical chamber. To reveal the geometry of plumes two different imaging techniques have been used in a quasi-simultaneous mode: Mie-scattering for the liquid phase and schlieren for the gaseous one.

Metallic open-cell foams have proven to be valuable for many engineering applications. Their success is mainly related to mechanical strength, low density, high specific surface, good thermal exchange, low flow resistance and sound absorption properties. The present work aims to investigate three principal aspects of real foams: the geometrical characterization, the flow regime characterization, the effects of the pore size and the porosity on the pressure drop. The first aspect is very important, since the geometrical properties depend on other parameters, such as porosity, cell/pore size and specific surface. A statistical evaluation of the cell size of a foam sample is necessary to define both its geometrical characteristics and the flow pattern at a given input velocity. To this purpose, a procedure which statistically computes the number of cells and pores with a given size has been implemented in order to obtain the diameter distribution.

The management of multiple injections in compression ignition (CI) engines is one of the most common ways to increase engine performance by avoiding hardware modifications and after-treatment systems. Great attention is given to the profile of the injection rate since it controls the fuel delivery in the cylinder. The Injection Rate Shaping (IRS) is a technique that aims to manage the quantity of injected fuel during the injection process via a proper definition of the injection timing (injection duration and dwell time). In particular, it consists in closer and centered injection events and in a split main injection with a very small dwell time. From the experimental point of view, the performance of an IRS strategy has been studied in an optical CI engine. In particular, liquid and vapor phases of the injected fuel have been acquired via visible and infrared imaging, respectively. Injection parameters, like penetration and cone angle have been determined and analyzed.

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.

Multi-fuel operation is one of the main topics of investigative research in the field of internal combustion engines. Spark ignition (SI) power units are relatively easily adaptable to alternative liquid-as well as gaseous-fuels, with mixture preparation being the main modification required. Numerical simulations are used on an ever wider scale in engine research in order to reduce costs associated with experimental investigations. In this sense, quasi-dimensional models provide acceptable accuracy with reduced computational efforts. Within this context, the present study puts under scrutiny the assumption of spherical flame propagation and how calibration of a two-zone combustion simulation is affected when changing fuel type. A quasi-dimensional model was calibrated based on measured in-cylinder pressure, and numerical results related to the two-zone volumes were compared to recorded flame imaging.

The paper reports an innovative method of analysis based on an advanced statistical techniques applied to images captured by a high-speed camera that allows highlighting phenomena and anomalies hardly detectable by conventional optical diagnostic techniques. The images, previously elaborated by neural network tools in order for clearly identifying the contours, have been analyzed in their time evolution as pseudo-chaotic variables that may have internal periodic components. In addition to the Fourier analysis, tools as Lyapunov and Hurst exponents and average Kω permitted to detect the chaos level of the signals. The use of this technique has permitted to distinguish periodic oscillations from chaotic variations and to detect those parameters that actually determine the spray behavior.

In this paper, an improved analytical model accounting for thermal effects in the electromagnetic field solution as well as efficiency map calculation of an outer rotor surface permanent magnet (SPM) machine is described. The study refers in particular to an in-wheel motor designed for automotive electric powertrain. This high torque and low speed application pushes the electric machine close to its thermal boundary, which necessitates estimates of winding and magnet temperatures to update the winding resistance and magnet remanence in the efficiency calculation. An electromagnetic model based on conformal mapping is used to compute the field solution in the air gap. The slotted air-gap geometry is mapped to a simpler slotless shape, where the field solution can be obtained by solving Laplace's equation for scalar potential. The canonical slottless domain solution is mapped back to the original domain and verified with finite element model (FEM) results.

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.

Advanced numerical techniques, such as fuzzy logic and neural networks have been applied in this work to digital images acquired on a mono-component fuel spray (iso-octane), in order to define, in a stochastic way, the gas-liquid interface evolution. The image is a numerical matrix and so it is possible to characterize geometrical parameters and the time evolution of the jet by using deterministic, statistical stochastic and other several kinds of approach. The algorithm used works with the fuzzy logic concept to binarize the shades gray of the pixel, depending them, by using the schlieren technique, on the gas density. Starting from a primary fixed threshold, the applied technique, can select the ‘gas’ pixel from the ‘liquid’ pixel and so it is possible define the first most probably boundary lines of the spray.

The interest of the vehicle producers in fulfillment emission legislations without adopting after treatment systems is driving to the use of non-conventional energy sources for modern engines. A previous test campaign dealing with the use of blends of diesel and propane in a CI engine has pointed out the potential of this non-conventional fuel for diesel engines. The soft adaptation of the common rail injection system and the potential benefits, in terms of engine performances and pollutant emissions, encourage the use of propane-diesel blends if an optimization of the injection strategies is performed. In this work, the performances of a propane-diesel mixture in a research diesel engine have been investigated. The injection strategies of Euro 5 calibration have been used as reference for the development of optimized strategies. The aim of the optimization process was to ensure the same engine power output and reduce the pollutant emissions.

Data decomposition techniques have become a standard approach for the analysis of 2D imaging data originating from optically accessible internal combustion engines. In particular, the method of Proper Orthogonal Decomposition (POD) has proven to be a valuable tool for the evaluation of cycle-to-cycle variability based on luminous combustion imaging and particle image velocimetry (PIV) measurements. POD basically permits to characterize the dominant structures of the process under consideration. Recently, an alternative procedure based on Independent Component Analysis (ICA) has been introduced in the engine field. Unlike POD, the method of ICA identifies the patterns corresponding to physical processes that are statistically independent. In this work, a Group-ICA approach is applied to 2D cycle-resolved images of the luminosity emitted by the combustion process. The analysis is meant to characterize cyclic variability of a port fuel injection spark ignition (PFI SI) engine.

Present work investigates both experimentally and numerically the benefits deriving from the use of split injections in increasing the engine power output and reducing the tendency to knock of a gasoline direct injection (GDI) engine. The here considered system is characterized by an optical access to the combustion chamber. Imaging in the UV-visible range is carried out by means of a high spatial and temporal resolution camera through an endoscopic system and a transparent window placed in the piston head. This last is modified to allow the view of the whole combustion chamber almost until the cylinder walls, to include the so-called eng-gas zones of the mixture, where undesired self-ignition may occur under some circumstances. Optical data are correlated to in-cylinder pressure oscillations on a cycle resolved basis.