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The growing concern about Greenhouse Gas (GHG) emissions led institutions to further reduce the limits on vehicle-related CO2 emissions. Therefore, car manufacturers are developing vehicles with low environmental impact, like Hybrid-Electric Vehicles (HEVs), which in the series architecture employ an Internal Combustion Engine (ICE) coupled with an electric generator for battery recharging, thus extending the range of a Battery Electric Vehicle (BEV). For this kind of application, small four-stroke Spark Ignition (SI) engines are preferred, as they are a proven and reliable solution to increase the driving range with very low environmental impact. In series hybrid-electric powertrains, the ICE is decoupled from the drive wheels, then it can operate in a steady-state high-efficiency working point, regardless of the power required by the mission profile. The benefits of lean combustion can be exploited to increase efficiency and reduce CO2 and NOx emissions.

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.

Methane supply in diesel engines operating in dual fuel mode has demonstrated to be effective for the reduction of particulate matter and nitric oxides emissions from this type of engine. In particular, methane is injected into the intake manifold to form a premixed charge with air, while a reduced amount of diesel oil is still directly injected to ignite the mixture inside the cylinder. As a matter of fact, the liquid fuel burns following the usual diffusive combustion, so activating the gaseous fuel oxidation in a premixed flame. Clearly, the whole combustion process appears to be more complex to be described in a CFD simulation, mainly because it is not always possible to select in the 3-dimensional codes a different combustion model for each fuel and, also, because other issues arise from the interaction of the two fuels.

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.

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.

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.

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.

Gasoline direct injection (GDI) allows flexible operation of spark ignition engines for reduced fuel consumption and low pollutants emissions. The choice of the best combination of the different parameters that affect the energy conversion process and the environmental impact of a given engine may either resort to experimental characterizations or to computational fluid dynamics (CFD). Under this perspective, present work is aimed at discussing the assessment of a CFD-optimization (CFD-O) procedure for the highest performance of a GDI engine operated lean under both single and double injection strategies realized during compression. An experimental characterization of a 4-stroke 4-cylinder optically accessible engine, working stratified lean under single injection, is first carried out to collect a set of data necessary for the validation of a properly developed 3D engine model.

Ethanol is the most promising alternative fuel for spark ignition (SI) engines, that is blended with gasoline, typically. Moreover, in the last years great attention is paid to the dual fueling, ethanol and gasoline are injected simultaneously. This paper aims to analyze the better methods, blending or dual fueling in order to best exploit the potential of ethanol in improving engine performance and reducing pollutant emissions. The experimental activity was carried out in a small displacement single cylinder engine, representative of 2-3 wheel vehicle engines or of 3-4 cylinder small displacement automotive engines. It was equipped with a prototype gasoline direct injection (GDI) head. The tests were carried out at 3000, 4000, and 5000 rpm full load. The investigated engine operating conditions are representative of the European homologation urban driving cycle.

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 use of direct injection (DI) engines allows a more precise control of the air-fuel ratio, an improvement of fuel economy, and a reduction of exhaust emissions thanks to the ultra-lean combustion due to the charge stratification. These effects can be partially obtained also with an optimized Air Direct Injection that permits to increase the turbulence at low speed and load increasing the combustion stability especially in lean condition. In this paper, a gasoline PFI (named G-PFI), gasoline PFI-methane DI dual fuel (named G-MDF) lean combustion were analyzed. The G-MDF configuration was also compared with a gasoline PFI - air DI (named G-A) configuration in order to distinguish the chemical effect of methane from the direct injection physical effect. The tests were carried out in a small displacement PFI/DI SI engine. The experimental investigation was carried out in a transparent small single-cylinder, spark ignition four-stroke engine.

In the present activity, dual fuel operation was investigated in a single cylinder research engine. Methane was injected in the intake manifold while the diesel was delivered via the standard injector directly into the engine. The aim is to study the effect of increasing methane concentration at constant injected diesel amount on both pollutant emissions and combustion evolution in an optically accessible engine. Emissions are in line with those previously published by other authors, it is noted no PM and constant NOx emissions. Moreover, a decrease of the brake specific CO emissions and an increase of the brake specific THC for the operating condition with the highest premixed ratio was detected. THC was mainly constituted by methane unburned hydrocarbons. Combustion resulted more or less stable. Moreover, via both UV-VIS spectroscopy and digital imaging, the spatial distribution of several species involved in the combustion process was analyzed.

The aim of the paper is the comparison of the performance, gaseous and particle emissions from different injection configurations and fuels. The engine was operated in port fuel injection (PFI), direct injection (DI) and dual fuel (DF). For DF, ethanol DI-gasoline PFI and gasoline DI-gasoline PFI strategies were performed to discern the effect of injection strategy from the effect of the fuel. The experimental activity was carried out in a small displacement single cylinder engine, representative of 2-3 wheel vehicle engines or of 3-4 cylinder small displacement automotive engines. It was equipped with a prototype gasoline direct injection (GDI) head. The tests were carried out at 3000 rpm, 4000 rpm and 5000 rpm full load. The investigated engine operating conditions are representative of the homologation urban driving cycle. The gaseous and particle emissions were measured at the exhaust by means of a gas analyzer and a smoke meter.

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.