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GDI injection systems have become dominant in passenger cars due to their flexibility in managing and advantages in the fuel economy. With the increasingly stringent emissions regulations and concurrent requirements for enhanced engine thermal efficiency, a comprehensive characterization of the fuel spray behavior has become essential. Different engine loads produce in a variety of fuel supplying conditions that affect the air/fuel mixture preparation and influence the efficiency and pollutant production. The flash boiling is a particular state that occurs for peculiar thermodynamic conditions of the engine. It could strongly influence the mixture in sub-atmospheric environments with detrimental effects on emissions. In order to obtain an in-depth understanding of the flash boiling phenomena, it is necessary to study the parameters influencing the mixture formation and their appearance in diverse engine conditions.

In the context of a transport sustainability, some solutions could be proposed from the integration of many disciplines, architects, environmentalists, policy makers, and consequently it may be addressed with different approaches. These solutions would be applied at different geographical levels, i.e. national, regional or urban scale. Moreover, the assessment of cars emissions in real use plays a fundamental role for their reductions. This is also the direction of the new harmonized test procedures (WLTP). Furthermore, it is fundamental to keep in mind that the new WLTC cycle will reproduce a situation closer to the reality comparing to the EUDC/NEDC driving cycle. In this paper, we will be focused on vehicle kinematic evaluation aimed at valuation of traffic situation and emissions.

The management of multiple injections in compression ignition (CI) engines is one of the most common ways to increase engine performance by avoiding hardware modifications and after-treatment systems. Great attention is given to the profile of the injection rate since it controls the fuel delivery in the cylinder. The Injection Rate Shaping (IRS) is a technique that aims to manage the quantity of injected fuel during the injection process via a proper definition of the injection timing (injection duration and dwell time). In particular, it consists in closer and centered injection events and in a split main injection with a very small dwell time. From the experimental point of view, the performance of an IRS strategy has been studied in an optical CI engine. In particular, liquid and vapor phases of the injected fuel have been acquired via visible and infrared imaging, respectively. Injection parameters, like penetration and cone angle have been determined and analyzed.

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.

The increased limitations to both NOx and soot emissions have pushed engine researchers to rediscover gasoline engines. Among the many technologies and strategies, gasoline direct injection plays a key-role for improving fuel economy and engine performance. The paper aims to investigate an extremely complex task such as the idle operating engine condition when the engine runs at very low engine speeds and low engine loads and during the warm-up. Due to the low injection pressure and to the null contribution of the turbocharger, the engine condition is far from the standard points of investigation. Taking into account the warm-up engine condition, the analyses are performed with a temperature of the coolant of 50°C. The paper reports part of a combined numerical and experimental synergic activity aiming at the understanding of the physics of spray/wall interaction within the combustion chamber and particular care is used for air/fuel mixing and the combustion process analyses.

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.

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.

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.

Hydrogen (H₂) added to natural gas (NG), improves the combustion process of the air-fuel mixture. This gives the potentiality to develop engines with better performance and lower environmental impact. In any case how hydrogen is produced represents a crucial aspect. In general, if H₂ is produced utilizing fossil fuels and not renewable or nuclear sources, the environmental benefit of CO₂ reduction could be reduced. In this paper two engines, a light-duty (LD) and a heavy-duty (HD), were tested in stoichiometric conditions. The engines were fuelled with NG and with two blends of NG with a 20% and a 40% by volume of H₂, respectively named NG/H₂ 20% and NG/H₂ 40%. The light-duty engine was tested at different loads and speeds, with spark advance set by the electronic control unit (ECU). The ECU actuated a retarded ignition, especially at low load. With the heavy-duty engine, the tests were carried out only at high load.

In the present paper, infrared (IR) measurements were performed in order to study the development of injection and combustion in a transparent Euro 5 diesel engine operating in premixed mode. An elongated single-cylinder engine equipped with the multi-cylinder head of commercial passenger car and with common rail (CR) injection system, respectively, was used. A sapphire window was set in the bottom of the combustion chamber, and a sapphire ring was placed between the head and the top of the cylinder line. Measurements were carried out through both accesses by a new high-speed infrared (IR) digital imaging system obtaining information that was difficult to achieve by the conventional UV-visible camera. IR camera was able to detect the emitted light in the wavelength range 1.5-5 μm that is relevant for the emission bands of CO₂ and H₂O. The evaporation phase of pre and main injection, and subsequent combustion evolution were analyzed.

In this paper, the modifications realized to make optically accessible a commercial high performance spark ignition and direct injection (DI) 4-cylinder engine are reported. The engine has been designed trying to keep as much as possible its thermo-fluid dynamic configuration in order to maintain its performance and emissions. Two optical accesses have been realized in order to interfere as little as possible with the combustion chamber geometry. A first optical access has been achieved in the piston head and a second by inserting an endoscopic fiber probe in the head. Preliminary results demonstrated that this optical assessment responds to the design targets and allowed a characterization of a commercial GDI engine working with homogeneous and stratified charge mode.

The addition of alcohol to conventional hydrocarbon fuels for a spark-ignition engine can increase the fuel octane rating and the power for a given engine displacement and compression ratio. In this work, the influence of butanol addition to gasoline was investigated. The experiments were performed in an optical ported fuel injection single-cylinder SI engine with an external boosting device. The engine was equipped with the head of a commercial SI turbocharged engine having the same geometrical specifications (bore, stroke and compression ratio). The effect of a blend of 20% of n-butanol and 80% of gasoline (BU20) on in-cylinder combustion process was investigated by cycle-resolved visualization. The engine worked at low speed, medium boosting and wide open throttle. Changes in spark timing and fuel injection phasing were considered. Comparisons between the flame luminosity and the combustion pressure data were performed.

The paper reports an innovative method of analysis based on an advanced statistical techniques applied to images captured by a high-speed camera that allows highlighting phenomena and anomalies hardly detectable by conventional optical diagnostic techniques. The images, previously elaborated by neural network tools in order for clearly identifying the contours, have been analyzed in their time evolution as pseudo-chaotic variables that may have internal periodic components. In addition to the Fourier analysis, tools as Lyapunov and Hurst exponents and average Kω permitted to detect the chaos level of the signals. The use of this technique has permitted to distinguish periodic oscillations from chaotic variations and to detect those parameters that actually determine the spray behavior.

During the last years, a number of techniques aimed at the experimental identification of the knocking onset in Spark-Ignition (SI) Internal Combustion Engines have been proposed. Besides the traditional procedures based on the processing of in-cylinder pressure data in the frequency domain, in the present paper two innovative methods are developed and compared. The first one is based on the use of statistical analysis by applying an Auto Regressive Moving Average (ARMA) technique, coupled to a prediction algorithm. It is shown that such parametric model, applied to the instantaneous in-cylinder pressure measurements, is highly sensitive to knock occurrence and is able to identify soft or heavy knock presence in different engine operating conditions. An alternative, more expensive procedure is developed and compared to the previous one.

The improvement in engines efficiency and reduction of emissions is the permanent aim of engine industry in order to meet European standards regulation. To optimize small internal combustion engines it is necessary to improve the basic knowledge of thermo-fluid dynamic phenomena occurring during the combustion. This paper describes the combustion process in an optically accessible two-stroke spark-ignition engine used in a commercial 43 cm3 chainsaw. Two different feeding systems were tested: standard and CWI one. The engine head was modified in order to allow the visualization of the combustion using endoscopic system coupled with a high spatial resolution ICCD camera. Flame front propagation was evaluated through an image processing procedure. The image visualization and chemiluminence allowed to follow the combustion process from the spark ignition to the exhaust phase at high engine speed. All the optical data were correlated with engine parameters and exhaust emissions.

In this paper the methane-gasoline dual fuel combustion was investigated. Gasoline was injected in the intake manifold (PFI fuel), while methane was injected in the combustion chamber (DI fuel), in order to reproduce a stratified combustion. The combustion process and the related engine performance and pollutant emissions were analyzed. The measurements were carried out in an optically accessible small single-cylinder four-stroke engine. It was equipped with the cylinder head of a commercial 250 cc engine representative of the most popular two-wheel vehicles in Europe. Optical measurements were performed to analyze the combustion process with high spatial and temporal resolution. In particular, optical techniques based on 2D-digital imaging were used to follow the flame front propagation and the soot and temperature concentration in the combustion chamber.

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.

In this paper, a high temporal resolution optical technique, based on the multi-wavelength UV-visible-near IR extinction spectroscopy, was applied at the exhaust of an automotive diesel engine to investigate the post-injection strategy impact on the fuel vapor. Experimental investigations were carried out using three fuels: commercial diesel (B5), a blend of 80% diesel with 20% by vol. of gasoline (G20) and a blend of 80% diesel with 20% by vol. of n-butanol (BU20). Experiments were performed at the engine speed of 2500rpm and 0.8MPa of brake mean effective pressure exploring two post-injection timings and two EGR rates. The optical diagnostic allowed evaluating, during the post-injection activation, the evolution of the fuel vapor in the engine exhaust line. The investigation was focused on the impact of post-injection strategy and fuel properties on the aptitude to produce hydrocarbon rich gaseous exhaust for the regeneration of diesel particulate trap (DPF).

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.

A wide investigation on powered two-wheelers (PTWs) is presented, aiming at the analysis of the influence of the driving characteristics on PTWs exhaust emissions and fuel consumption, a deeper comprehension of the engine and after-treatment system behavior within the cold start transient and the evaluation of cold start additional emissions for different two-wheelers classes. The study was developed with reference to an European context focusing on Euro 3 motorcycles and Euro 2 mopeds. An experimental investigation on instantaneous speed measurements was carried out with instrumented motorcycles, considering typical urban trips in the city of Genoa. A selection of speed profiles was then performed by processing experimental values.