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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.

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.

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.

Diesel combustion process was studied and characterized by digital imaging and ultraviolet-visible flame emission, extinction and scattering spectroscopy. Optical measurements were applied to a transparent diesel engine, realized by modifying a single cylinder, air-cooled, 4-stroke diesel engine by means of an external combustion chamber on the top of the engine, connected to the main chamber by a tangential passage. Diesel engine was equipped with a fully flexible electronic controlled ‘Common Rail’ injection system. Measurements were performed at 1000 rpm engine speed for two typical injection strategies. The first one consisted of a main injection in order to compare the results with those ones obtained by conventional injection system operating at low pressure. The other one was based on a pilot and main injection that is typical of current direct injection diesel engines.

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.

This study was conducted to determine the effects of the fouling process on the piezoelectric injectors in a transparent common-rail diesel engine. Piezoelectric injectors are characterized by a ceramic actuator that can dilate or retract when it receives a pulse of current. The piezo element controls a valve, which creates an imbalance in the pressure that is exerted at each end of the needle, causing the needle rising or closing. Two same model injectors were tested; one was new and the other one was fouled on a vehicle. The aim of the experimental investigation was to evaluate the performance of a new and a fouled piezoelectric injector in terms of injection and flame evolution. It was evaluated how the nozzle carbon deposits affect the injection quantity and combustion. The experimental apparatus was a single-cylinder research engine equipped with a Euro 5 multi-cylinder head. A second-generation common rail injection system and 6-hole piezoelectric injectors were used too.

In order to reduce fuel consumption and polluting emissions from engines, alternative fuels such as hydrogen could play an important role towards carbon neutrality. Moreover, dual-fuel (DF) technology has the potential to offer significant improvements in carbon dioxide emissions for transportation and energy sectors. The dual fuel concept (natural gas/diesel or hydrogen/diesel) represents a possible solution to reduce emissions from diesel engines by using low-carbon or carbon-free gaseous fuels as an alternative fuel. Moreover, DF combustion is a possible retrofit solution to current diesel engines by installing a PFI injector in the intake manifold while diesel is injected directly into the cylinder to ignite the premixed mixture. In the present study, dual fuel operation has been investigated in a single cylinder research engine.

Growing concerns about the emissions of internal combustion engines have forced the adoption of aftertreatment devices to reduce the adverse impact of diesel engines on health and environment. Diesel particulate filters are considered as an effective means to reduce the particle emissions and comply with the regulations. Research activity in this field focuses on filter configuration, materials and aging, on understanding the variation of soot layer properties during time, on defining of the optimal strategy of DPF management for on-board control applications. A model was implemented in order to simulate the filtration and regeneration processes of a wall-flow particulate filter, taking into account the emission characteristic of the engine, whose architecture and operating conditions deeply affect the size distribution of soot particles.

Many aspects of battery electric vehicles are very challenging from the engineering point of view in terms of safety, weight, range, and drivability. Commercial vehicle engines are often subjected to high loads even at low speeds and this can lead to an intense increment of the battery pack temperature and stress of the cooling system. For these reasons the optimal design of the battery pack and the relative cooling system is essential. The present study deals with the challenge of designing a battery pack that satisfies both the conditions of lowest weight and efficient temperature control. The trade-off between the battery pack size and the electrical stress on the cells is considered. The electric system has the aim to substitute a 3.0 liters compression ignition engine mainly for commercial vehicles.

Blends of propane-diesel fuel can be used in direct injection diesel engines to improve the air-fuel mixing and the premixed combustion phase, and to reduce pollutant emissions. The potential benefits of usinf propane in diesel engines are both environmental and economic; furthermore, its use does not require changes to the compression ratio of conventional diesel engines. The present paper describes an experimental investigation of the injection process for different liquid preformed blends of propane-diesel fuel in an optically accessible Common Rail diesel engine. Slight modifications of the injection system were required in order to operate with a blend of propane-diesel fuel. Pure diesel fuel and two propane-diesel mixtures at different mass ratios were tested (20% and 40% in mass of propane named P20 and P40). First, injection in air at ambient temperature and atmospheric pressure were performed to verify the functionality of the modified Common Rail injection system.

The present paper describes an experimental investigation over the impact of diesel injector nozzle flow number on spray formation and combustion evolution for a modern EURO5 light-duty diesel engine. The analysis has been carried out by coupling the investigations in non evaporative spray bomb to tests in optical single cylinder engine in firing conditions. The research activity, which is the result of a collaborative project between Istituto Motori Napoli - CNR and GM Powertrain Europe, is devoted to understanding the basic operating behaviour of low flow number nozzles which are showing promising improvements in diesel engine behaviour at partial load. In fact, because of the compelling need to push further emission, efficiency, combustion noise and power density capabilities of the last-generation diesel engines, the combination of high injection pressure fuel pumps and low flow number nozzles is general trend among major OEMs.