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The Direct Injection (DI) of gasoline in Spark Ignition (SI) engines is very attractive for fuel economy and performance improvements in spark ignition engines. Gasoline direct injection (GDI) offers the possibility of multi-mode operation, homogeneous and stratified charge, with benefits respect to conventional SI engines as higher compression ratio, zero pumping losses, control of the ignition process at very lean air-fuel mixture and good cold starting. The impingement of liquid fuel on the combustion chamber wall is generally one of the major drawbacks of GDI engines because its increasing of HC emissions and effects on the combustion process; in the wall guided engines an increasing attention is focusing on the fuel film deposits evolution and their role in the soot formation. Hence, the necessity of a detailed understanding of the spray-wall impingement process and its effects on the fuel distribution. The experimental results provide a fundamental data base for CFD predictions.

The common realization of the necessity to reduce the use of mineral sources is promoting the use of alternative fuels. Big efforts are being made to replace petroleum derivatives in the internal combustion engines (ICEs). For this purpose it is mandatory to evaluate the behavior of non-conventional fuels in the ICEs. The optical diagnostics have proven to be a powerful tool to analyze the processes that take place inside the engine. In particular, 2d imaging in the infrared range can reveal new details about the effect of the fuel properties since this technique is still not very common. In this work, a comparison between commercial diesel fuel and two non-conventional fuels has been made in an optically accessible diesel engine. The non-conventional fuels are: the first generation biofuel Rapeseed Methyl Ester (RME) and an experimental blend of diesel and a fuel with high glycerol content (HG).

In order to meet the stricter and stricter emission regulations, cleaner combustion concepts for Diesel engines are being progressively introduced. These new combustion approaches often requires closed loop control systems with real time information about combustion quality. The most important parameter for the evaluation of combustion quality in internal combustion engines is the in-cylinder pressure, but its direct measurement is very expensive and involves an intrusive approach to the cylinder. Previous researches demonstrated the direct relationship existing between in-cylinder pressure and engine block vibration signal and several authors tried to reconstruct the pressure cycle on the basis of information coming from accelerometers mounted on engine block. This paper proposes a method, based on the analysis of the engine vibration signal, for the diagnosis of combustion process in a Diesel engine.

In the last years, increasing concerns about environmental pollution and fossil sources depletion led transport sectors research and development towards the study of new technologies capable to reduce vehicles emissions and fuel consumption. Direct-injection systems (DI) for internal combustion engines propose as an effective way to achieve these goals. This technology has already been adopted in Gasoline Direct Injection (GDI) engines and, lately, a great interest is growing for its use in natural gas fueling, so increasing efficiency with respect to port-fuel injection ones. Alone or in combination with other fuels, compressed natural gas (CNG) represents an attractive way to reduce exhaust emission (high H/C ratio), can be produced in renewable ways, and is more widespread and cheaper than gasoline or diesel fuels. Gas direct-injection process involves the occurrence of under-expanded jets in the combustion chamber.

In this work, optical diagnostics were applied in a transparent DI diesel engine equipped with the head of Euro5 commercial engine and the last generation CR injection system. In order to realize the PCCI combustion the injection of neat bio-ethanol was performed in the intake manifold and European commercial diesel fuel was injected into the cylinder. Different amounts of bio-ethanol were injected in order to create PCCI combustion with high levels of pre-combustion mixing, and to ensure low equivalence ratio and low flame temperatures too. UV-Visible imaging and spectroscopic measurements were performed in the engine in order to investigate the autoignition of the charge and the combustion process, respectively. In particular, the detection of the species involved in the combustion, like OH, HCO, and CH, was performed. The relevance of the radicals and species on PCCI were evaluated and compared with the data from thermodynamic analysis.

Premixed charge compression ignition (PCCI) has been shown to be a promising strategy to simultaneously reduce emissions while realizing improved fuel economy. PCCI combustion uses high levels of pre-combustion mixing to lower both NOx and soot emissions by ensuring low equivalence ratio and low flame temperatures. The high level of pre-combustion mixing results in a primarily kinetics controlled combustion process. In this work, optical diagnostics have been applied in a transparent DI diesel engine equipped with the head of Euro5 commercial engine and the last generation CR injection system. In order to realize the PCCI combustion the injection of neat ethanol has been performed in the intake manifold. The engine run in continuous way at 1500 rpm engine speed and commercial diesel fuel has been injected into the cylinder. The PCCI combustion has been analyzed by means of UV- Visible digital imaging and the mixing process, the autoignition of the charge have been investigated.

This study aims at building efficient and robust artificial neural networks (ANN) able to reconstruct the in-cylinder pressure of Diesel engines and to identify engine conditions starting from the signal of a low-cost accelerometer placed on the engine block. The accelerometer is a perfect non-intrusive replacement for expensive probes and is prospectively suitable for production vehicles. In this view, the artificial neural network is meant to be efficient in terms of response time, i.e. fast enough for on-line use. In addition, robustness is sought in order to provide flexibility in terms of operation parameters. Here we consider a feed-forward neural network based on radial basis functions (RBF) for signal reconstruction, and a feed-forward multi-layer perceptron network with tan-sigmoid transfer function for signal classification. The networks are trained using measurements from a three-cylinder real engine for various operating conditions.

Internal combustion engines are characterized by high pressure and thermal loads on pistons and in cylinders. The heat generated by the combustion process is dissipated by means of water and oil cooling systems. For the best design and optimization of the engine components it is necessary to know the components temperature in order to estimate the thermal flows. The purpose of this work is to measure the piston sapphire window temperature in a research optically accessible engine by combining two different techniques: measurements with templugs and with thermography. The method is very simple and can provide a reliable value of temperature within a small interval. It fits well for applications inside the engine because of its low technical level requirements. It consists of application of temperature sensitive stickers on the target component that makes it a very robust method, not affected by piston movement.

The analysis of heat losses in internal combustion engines (ICEs) is fundamental to evaluate and to improve engine efficiency. Detailed and reliable heat transfer models are required for more complex 1d-3d combustion models. At the same time, the thermal status of engine components, like pistons, is needed for an efficient design. Measurements of piston temperature during ICEs operation represent an important and challenging result to get for the aforementioned purposes. In the present work, temperature measurements collected at different engine speeds and loads, both in motored and fired modes, have been performed and used to set-up a theoretical correlation and 1d model of heat transfer through the optical window of the piston. The in-cylinder gas and external ambient temperature, together with the thermodynamic and material properties are given. The model has been first calibrated in some selected operating conditions and then validated in the remaining.

The aim of this study is to investigate how the fouling that injectors undergo after several operating hours on a vehicle can affect the injection and combustion phases. The impact of the injector fouling on the pollutant formation has been also investigated. Moreover, the effects of the injector cleaning by deposits through the top quality diesel fuel commercialized by eni that is FAME free and contains multi performance additives have been investigated. The experimentation has been carried out on transparent compression ignition engine. It is a single cylinder equipped with a Euro 5 multi-cylinder head and a second-generation common rail injection system. Three indirect-acting piezoelectric injectors have been tested. The first one has been fouled with European commercial diesel fuel through the CEC DW10 injector-coking test. The second one has been fouled in the same way and, then, it has been cleaned with eni top quality diesel fuel. This fuel has fed the third injector too.

The aim of the present work is the study of the combustion process in Gasoline Direct Injection (GDI) engine fuelled with ethanol mixed with gasoline at percentages of 10 and 85. The characterization has been made in terms of performance and emission for different injection pressure conditions and the results correlated to the unperturbed non-evaporating evolution of the fuel injected in a pressurized quiescent vessel. Measurements were performed in the optically accessible combustion chamber made by modifying a real 4-stroke, 4-cylinder, high performance GDI engine. The cylinder head was instrumented by using an endoscopic system coupled to high spatial and temporal resolution camera in order to allow the visualization of the fuel injection and the combustion process. The engine is equipped with solenoid-actuated six-hole GDI injectors, 0.14 mm hole diameter, 9.0 g/s @ 10 MPa static flow.

An investigation has been carried out on the spray penetration and soot formation processes in a research diesel engine by means of a quasi-dimensional multizone combustion model. The model integrates a predictive non stationary 1D spray model developed by the Sandia National Laboratory, with a diagnostic multizone thermodynamic model, and is capable of predicting the spray formation, combustion and soot formation processes in the combustion chamber. The multizone model was used to analyze three operating conditions, i.e., a zero load point (BMEP = 0 bar at 1000 rpm), a medium load point (BMEP = 5 bar at 2000 rpm) and a medium-high load point (BMEP = 10 bar at 2000 rpm). These conditions were experimentally tested in an optical single cylinder engine with the combustion system configuration of a 2.0L Euro4 GM diesel engine for passenger car applications.

The present paper describes the results of a cooperative research project between GM Powertrain Europe and Istituto Motori - CNR aimed at studying the impact of both fresh and highly oxidized RME at two levels of blending on spray formation and combustion in modern automotive diesel engines. The tests were performed on an optical single-cylinder engine sharing combustion system configuration with the 2.0L Euro5 GM diesel engine for passenger car application. Two blends (B50 and B100) blending were tested for both fresh and aged RME and compared with commercial diesel fuel in two different operating points typical of NEDC (1500rpm/2bar BMEP and 2000rpm/5bar BMEP). The experimental activity was devoted to an in-depth investigation of the spray density, breakup and penetration, mixture formation, combustion and soot formation, by means of optical techniques.

In the next future, improvements of direct injection systems for spark-ignited engines are necessary for the potential reductions in fuel consumptions and exhaust emissions. The admission and spread of the fuel in the combustion chamber is strictly related to the injector design and performances, such as to the fuel and environmental pressure and temperature conditions. In this paper the spray characterization of a GDI injector under normal and flash-boiling injection conditions has been investigated. The paper is mainly focused both on the capability of the injection apparatus/temperatures controller system to realize flash-boiling conditions, and the diagnostic setup to catch the peculiarities of the spray behavior. The work aims reporting the spray characterization under normal and flash-boiling conditions.

Diesel sprays from an axially-disposed single-hole injector are studied under both non-vaporizing and vaporizing conditions in a constant-volume vessel. A hybrid shadowgraph/Mie-scattering imaging set-up is used to acquire the liquid and vapor phases of the fuel distribution in a near-simultaneous visualization mode by a high-speed camera (40,000 fps). A diesel injector with k0 factor is used, having the exit-hole diameter of 0.1 mm and the ratio L/d =10. The studies are performed at the injection pressures of 70, 120, and 180 MPa, 25.37 kg/m3 ambient gas density, at the environment temperature of 373, 453 and 900 K. The instantaneous tip penetration of the liquid and vapor phases is extracted from the collected images and processed by a properly assessed software, under the various operating conditions. The AVL FIRE™ code is also used to simulate the spray dynamics. The model is validated on the ground of the collected experimental data.

This paper reports an experimental and numerical investigation on the spatial and temporal liquid- and vapor-phase distributions of diesel fuel spray under engine-like conditions. The high pressure diesel spray was investigated in an optically-accessible constant volume combustion vessel for studying the influence of the k-factor (0 and 1.5) of a single-hole axial-disposed injector (0.100 mm diameter and 10 L/d ratio). Measurements were carried out by a high-speed imaging system capable of acquiring Mie-scattering and schlieren in a nearly simultaneous fashion mode using a high-speed camera and a pulsed-wave LED system. The time resolved pair of schlieren and Mie-scattering images identifies the instantaneous position of both the vapor and liquid phases of the fuel spray, respectively. The studies were performed at three injection pressures (70, 120, and 180 MPa), 23.9 kg/m3 ambient gas density, and 900 K gas temperature in the vessel.

In internal combustion engines, the direct injection at high pressures produces a strong impact of the fuel on the combustion chamber wall, especially in small-bore sizes used for passenger cars. This effect is relevant for the combustion process resulting in an increase of the pollutant emissions and in a reduction of the engine performances. This paper aims to report the effects of the injection pressure and wall temperature on the macroscopic behavior and atomization of the impinging sprays on the wall. The gasoline spray-wall interaction was characterized inside an optically accessible quiescent chamber using a novel make ready Z-shaped schlieren-Mie scattering set-up using a high-speed C-Mos camera as imaging system. The arrangement was capable to acquire alternatively the schlieren and Mie-scattering images in a quasi-simultaneous fashion using the same line-of-sight.

This study aims at building an efficient and robust radial basis function (RBF) artificial neural network (ANN), to reconstruct the in-cylinder pressure of a diesel engine starting from the signal of a low-cost accelerometer placed on the engine block. The accelerometer is a perfect non-intrusive replacement for expensive probes and is prospectively suitable for production vehicles. The RBF network is trained using measurements from different engine operating conditions. Training data are composed of time series from the accelerometer and corresponding measured in-cylinder pressure signals. The RBF network is then validated using data not included in training and the results show good correspondence between measured and reconstructed pressure signal. Various network parameters are used to optimize the network quality.

In order to meet the increasingly strict emission regulations, several solutions for NOx and PM emissions reduction have been studied. Exhaust gas recirculation (EGR) technology has become one of the more used methods to accomplish the NOx emissions reduction. However, actual control strategies do not consider, in the definition of optimal EGR, its effect on particle size and density. These latter have a great importance both for the optimal functioning of after-treatment systems, but also for the adverse effects that small particles have on human health. Epidemiological studies, in fact, highlighted that the toxicity of particulate particles increases as the particle size decreases. The aim of this paper is to present a Neural Network model able to provide real time information about the characteristics of exhaust particles emitted by a Diesel engine.

A set of additives was selected to improve the durability of the physical-chemical and biological characteristics of mineral diesel and its blend with biodiesel. Two biodiesels were used: soybean (SME) and rapeseed (RME). Both physical-chemical properties and fuel dispersion of fuel blends and their mixtures with additives were measured that could have effects on the combustion process in diesel engines. The dispersion of the fuel is affected by the injection nozzle integrity, influencing the capacity of the fuel to vaporize, while the modification of the fuel molecular structure can cause changes in combustion reaction. A 7 hole Common Rail (CR) 2nd generation injector, 136 μm in diameter, was used at 80 MPa and 1.0 ms injection pressure and duration, respectively. The injection rate was determined using the Bosch's Method, while the fuel dispersion was measured by analyzing the images of spray evolving in an optical accessible quiescent vessel.