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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 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.

The present paper describes the results of a cooperative research project between GM Powertrain Europe and Istituto Motori - CNR aimed at studying the capability of GM Combustion Closed-Loop Control (CLCC) in enabling seamless operation with high biodiesel blending levels in a modern diesel engine for passenger car applications. As a matter of fact, fuelling modern electronically-controlled diesel engines with high blends of biodiesel leads to a performance reduction of about 12-15% at rated power and up to 30% in the low-end torque, while increasing significantly the engine-out NOx emissions. These effects are both due to the interaction of the biodiesel properties with the control logic of the electronic control unit, which is calibrated for diesel operation. However, as the authors previously demonstrated, if engine calibration is re-tuned for biodiesel fuelling, the above mentioned drawbacks can be compensated and the biodiesel environmental inner qualities can be fully deployed.

The paper describes the results achieved in developing a new diesel combustion system for passenger car application that, while capable of high power density, delivers excellent fuel economy through a combination of mechanical and thermodynamic efficiencies improvement. The project stemmed from the idea that, by leveraging the high fuel injection pressure of last generation common rail systems, it is possible to reduce the engine peak firing pressure (pfp) with great benefits on reciprocating and rotating components light-weighting and friction for high-speed light-duty engines, while keeping the power density at competitive levels. To this aim, an advanced injection system concept capable of injection pressure greater than 2500 bar was coupled to a prototype engine featuring newly developed combustion system. Then, the matching among these features have been thoroughly experimentally examined.

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.

In the global scenario of encouraging the use of renewable sources, the bioethanol as fuel supply in the automotive sector is receiving increasing interest. In the present paper the results of a research activity aimed to study the impact of a bioethanol/biodiesel/mineral diesel blend on performance and emissions of an automotive diesel engine are reassumed. An experimental campaign has been devoted to characterize the engine fuelled by the ethanol based blend highlighting the advantages and issues related to the bioethanol use. Moreover, the effects of the most important injection settings on the engine performance have been detailed, applying a Design of Experiment (DoE) method, to identify the potentiality offered by a proper engine calibration to optimize the ethanol blend use.

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.

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.

This paper deals with the combustion behavior and exhaust emissions of a small compression ignition engine modified to operate in diesel/methane dual fuel mode. The engine is a three-cylinder, 1028 cm3 of displacement, equipped with a common rail injection system. The engine is provided with the production diesel oxidation catalyst. Intake manifold was modified in order to set up a gas injector managed by an external control unit. Experiments were carried out at different engine speeds and loads. For each engine operating condition, the majority of the total load was supplied by methane while a small percentage of the load was realized using diesel fuel; the latter was necessary to ignite the premixed charge of gaseous fuel. Thermodynamical analysis of the combustion phase was performed by in-cylinder pressure signal. Gas emissions and particulate matter were measured at the exhaust by commercial instruments.

In this paper, a parametric analysis on the main engine calibration parameters applied on gasoline Partially Premixed Combustion (PPC) is performed. Theoretically, the PPC concept permits to improve both the engine efficiencies and the NOx-soot trade-off simultaneously compared to the conventional diesel combustion. This work is based on the design of experiments (DoE), statistical approach, and investigates on the engine calibration parameters that might affect the efficiencies and the emissions of a gasoline PPC. The full factorial DoE analysis based on three levels and three factors (33 factorial design) is performed at three engine operating conditions of the Worldwide harmonized Light vehicles Test Cycles (WLTC). The pilot quantity (Qpil), the crank angle position when 50% of the total heat is released (CA50), and the exhaust gas recirculation (EGR) factors are considered. The goal is to identify an engine calibration with high efficiency and low emissions.

The paper reports the results of an experimental campaign aimed to assess the impact of the compression ratio (CR) variation on the performance and pollutant emissions, including the particle size spectrum, of a single cylinder research engine (SCE), representatives of the engine architectures for automotive application, operated in dual-fuel methane-diesel mode. Three pistons with different bowl volumes corresponding to CR values of 16.5, 15.5 and 14.5 were adopted for the whole test campaign. The injection strategy was based on two injection pulses per cycle, as conventionally employed for diesel engines. The test methodology per each CR included the optimization of both 1st injection pulse quantity and intake air mass flow rate in order to lower as much as possible the unburned methane emissions (MHC).

The combustion quality in modern diesel engines depends strictly on the quality of the air-fuel mixing and, in turn, from the quality of spray atomization process. So air-fuel mixing is strongly influenced by the injection pressure, geometry of the nozzle duct and the hydraulic characteristics of the injector. In this context, spray concepts alternative to the conventional multi-hole nozzles could be considered as solutions to the extremely high injection pressure increase to assure a higher and faster fuel-air mixing in the piston bowl, with the final target of increasing the fuel efficiency and reducing the engine emissions. The study concerns an experimental depiction of a spray generated through a prototype high-pressure hollow-cone nozzle, under evaporative and non-evaporative conditions, injecting the fuel in a constant-volume combustion vessel controlled in pressure and temperature up to engine-like gas densities in order to measure the spatial and temporal fuel patterns.

In the present paper, a new concept of open nozzle spray was investigated as possible application for compression ignition engines. The study concerns an experimental and numerical characterization of a spray generated through a prototype high-pressure hollow-cone nozzle (HCN). The experimental description of the injection process was carried out under evaporative and non-evaporative conditions injecting the fuel in a constant-volume combustion vessel controlled in pressure and temperature in order to measure the spatial and temporal fuel pattern at engine-like gas densities. OpenFOAM libraries in the lib-ICE version of the numerical code were employed for simulating the spray dynamics after a first validation phase based on the experimental data. Results show a typical spray structure of the outward-opening nozzle with the overall fluid-dynamic arrangement having a good fuel distribution along the hollow-cone geometry but showing a reduced spatial penetration.