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The transport of goods and people by sea, today, must meet the need to reduce the consumption of fuel oil. In addition, it has to ensure operational reliability and vessel availability, to reduce maintenance costs and comply with emission legislation. To this end, it is necessary to apply a marine engine combustion control system already widely used in engines for land transport. This will allow the ship's engines to operate reliably and in compliance with the best performance for which it was designed. The combustion control could also ensure a more balanced operation of the cylinders and reduce the torsional vibrations of the entire engine, as well as the management of the engine according to the adopted fuel: diesel, dual fuel, methanol, ammonia. Generally, the control of combustion in engines is carried out through the use of pressure sensors that face directly into the combustion chamber.

Nowadays, the stricter regulations in terms of emissions have limited the use of diesel engines on urban roads. On the contrary, for marine and off-road applications the diesel engine still represents the most feasible solution for work production. In the last decades, dual fuel operation with methane supply has been widely investigated. Starting from previous studies on a research engine, where diesel-methane dual fuel combustion has been deepened both experimentally and numerically with the aid of a CFD code, the authors implemented and tested a kinetic mechanism. It is obtained from the combination of the well-established GRIMECH 3.0 and a detailed scheme for a diesel surrogate oxidation. Moreover, the Autoignition-Induced Flame Propagation model, included in the ANSYS Forte® software, is applied because it can be considered the most appropriate model to describe dual fuel combustion.

The permanent aim of the automotive industry is the further improvement of the engine efficiency and the simultaneous pollutant emissions reduction. The aim of the study was the optimization of the gasoline combustion by means of a passive prechamber. This analysis allowed the improvement of the engine efficiency in lean-burn operation condition too. The investigation was carried out in a commercial small Spark Ignition (SI) engine fueled with gasoline and equipped with a proper designed passive prechamber. It was analyzed the effects of the prechamber on engine performance, Indicated Mean Effective Pressure, Heat Release Rate and Fuel Consumption were used. Gaseous emissions were measured as well. Particulate Mass, Number and Size Distributions were analyzed. Emissions samples were taken from the exhaust flow, just downstream of the valves. Four different engine speeds were investigated, namely 2000, 3000, 4000 and 5000 rpm.

The current legislation does not take into account the limitation of sub 23 nm particles from engine. Nevertheless, the Common Rail Diesel engine emits a large number of nanoparticle, solid and volatiles, that are very dangerous for human health. In this contest, the challenge of the “dieper EU project” is to apply advanced technologies for exhaust after-treatment to existing diesel engines and to optimize the characteristics of a new generation of engines with regards to emissions, fuel consumption and drivability. Aim of the present paper is to provide useful information for the development of the after-treatment system that will have to fulfill Euro6 further steps. In order to characterize the chemical and physical nature of Particulate Matter emitted from Euro 6b Medium Duty diesel engine, the pollutants were collected and analyzed: from engine-out, downstream of the particulate filter (DPF), and at the exit of a selective catalytic reactor (SCR).

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 the results of an experimental activity performed on a small diesel engine for quadricycles, a category of vehicles that is spreading in Europe and is recently spreading over Indian countries. The engine is a prototype three-cylinder with 1000 cc of displacement and it is equipped with a direct common-rail injection system that reaches a maximum pressure of 1400 bar. The engine was designed to comply with Euro 4 emission standard that is a future regulation for quadricycles. It is worth underlining that the engine can meet emission limits just with EGR system and a DOC, without DPF. Various diesel/RME blends were tested; pure diesel and biodiesel fuels were also used. The investigation was carried out at the engine speeds of 1400, 2000 and 3400 rpm and full load. Combustion characteristics of both blended and pure RME were analyzed by means of in-cylinder pressure and heat released histories.

This paper deals with the combustion characteristics and exhaust emissions of a diesel engine fuelled with conventional diesel fuel and a biodiesel blend, in particular a 20% v/v concentration of rapeseed methyl ester (RME) mixed with diesel fuel. The investigation was carried out on a prototype three-cylinder engine with 1000 cc of displacement for quadricycle applications. The engine is equipped with a direct common-rail injection system that reaches a maximum pressure of 1400 bar. The engine was designed to comply with Euro 4 and BS IV exhaust emission regulations without a diesel particulate filter. Both in-cylinder pressure and rate of heat release traces were analyzed at different engine speeds and loads. Gaseous emissions were measured at the exhaust. A smoke meter was used to measure the particulate matter concentration. The sizing and the counting of the particles were performed by means of an engine exhaust particle sizer spectrometer.

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.

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.

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.

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.