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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.

The use of oxygenated and renewable fuels is nowadays a widespread means to reduce regulated pollutant emissions produced by internal combustion engines, as well as to reduce the greenhouse impact of transportation. Besides PM, NOx and HC emissions, also the size distribution of particles emitted at the engine exhaust represent meaningful information, considering its adverse effects on the environment and human health. In this work, the results of a comprehensive investigation on the combustion characteristics and the exhaust emissions of a GDI high performance engine, fuelled with pure bio-ethanol and European gasoline, are shown. The engine is a 4-cylinder, 4-stroke, 1750 cm₃ displacement, and turbocharged. The engine was operated at different speed/load conditions and two fuel injection strategies were investigated: homogeneous charge mode and stratified charge mode.

Detailed experimental information on the early stages of spark ignition process represent a substantial part for guiding the development of engines with higher efficiencies and reduced pollutant emissions. Flame kernel formation influences strongly combustion development inside the cylinder, especially for a direct injection spark ignition engine. This study presents the analysis of the evolution of spark-ignited flame kernels with detailed view upon cycle-to-cycle variations. Experiments are performed in a SI optical engine equipped with the cylinder head and injection system of a commercial turbocharged engine. Blend of commercial gasoline and butanol (40% by volume) is tested at stoichiometric and lean mixture conditions. Experiments are carried out at 2000 rpm through conventional tests (based on in-cylinder pressure measurements and exhaust emission analysis) and through optical diagnostics. In particular, UV-visible digital imaging and natural emission spectroscopy are applied.

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.

Gasoline direct injection (GDI) engines are characterized by complex phenomena involving spray dynamics and possible spray-wall interaction. Control of mixture formation is indeed fundamental to achieve the desired equivalence ratio of the mixture, especially at the spark plug location at the time of ignition. Droplet impact on the piston or liner surfaces has also to be considered, as this may lead to gasoline accumulation in the liquid form as wallfilm. Wallfilms more slowly evaporate than free droplets, thus leading to local enrichment of the charge, hence to a route to diffusive flames, increased unburned hydrocarbons formation and particulate matter emissions at the exhaust. Local heat transfer at the wall obviously changes if a wallfilm is present, and the subtraction of the latent heat of vaporization necessary for secondary phase change is also an issue deserving a special attention.

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.

In the recent years, the interest in heavy-duty engines fueled with Compressed Natural Gas (CNG) is increasing due to the necessity to comply with the stringent CO2 limitation imposed by national and international regulations. Indeed, the reduced number of carbon atoms of the NG molecule allows to reduce the CO2 emissions compared to a conventional fuel. The possibility to produce synthetic methane from renewable energy sources, or bio-methane from agricultural biomass and/or animal waste, contributes to support the switch from conventional fuel to CNG. To drive the engine development and reduce the time-to-market, the employment of numerical analysis is mandatory. This requires a continuous improvement of the simulation models toward real predictive analyses able to reduce the experimental R&D efforts. In this framework, 1D numerical codes are fundamental tools for system design, energy management optimization, and so on.

A modified version of KIVA II code was used to perform three-dimensional calculations of combustion in a DI diesel engine. Both an ignition delay submodel and a different formulation of the fuel reaction rate were implemented and tested. The experiments were carried out on a single cylinder D.I. diesel of 0.75 I displacement equipped with sensors to detect injection characteristics and indicated pressure. A fast acting sampling valve was also installed in the combustion chamber to allow the measurement of main pollutants during the combustion cycle, by an ensemble average technique. Computational and experimental results are compared and the discrepancies are discussed. Today the demand for light duty engines that produce less emission and consume less fuel is increasing. Thus, if limits on CO2 emissions are established, the direct injection diesel engine for light duty applications will become an attractive option.

The electrochemical performance of a lithium-ion battery is strongly affected by the temperature. During charge and discharge cycles, batteries are subjected to an increment of temperature that can accelerate aging and loss of efficiency if critical values are reached. Knowing the thermal parameters that affect the heat exchange between the battery surface and the surrounding environment (air, cooling fins, plates, etc…) is fundamental to their thermal management. In this work, thermal imaging is applied to a laminated lithium-polymers battery as a non-invasive temperature-indication method. Measurements are taken during the discharge phase and the following cooling down until the battery reaches the ambient temperature. The 2d images are used to analyze the homogeneity of the temperature distribution on the battery surface. Then, experimental results are coupled with mathematical correlations.

In the present work, an Auto Regressive Moving Average (ARMA) model and a Discrete Wavelet Transform (DWT) are applied on vibrational signals, acquired by an accelerometer placed on the cylinder block of a Spark Ignition (SI) engine, for knock detection purposes. To the aim of tuning such procedures, the same analysis has been carried out by using the traditional MAPO (Maximum Amplitude of Pressure Oscillations) index and an Inverse Kinetic Model (IKM), both applied on the in-cylinder pressure signals. Vibrational and in-cylinder pressure signals have been collected on a four cylinder, four stroke engine, for different engine speeds, load conditions and spark advances. The results of the two vibrational based methods are compared and in depth discussed to the aim of highlighting the pros and cons of each methodology.

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 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.

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.

Present work investigates both experimentally and numerically the benefits deriving from the use of split injections in increasing the engine power output and reducing the tendency to knock of a gasoline direct injection (GDI) engine. The here considered system is characterized by an optical access to the combustion chamber. Imaging in the UV-visible range is carried out by means of a high spatial and temporal resolution camera through an endoscopic system and a transparent window placed in the piston head. This last is modified to allow the view of the whole combustion chamber almost until the cylinder walls, to include the so-called eng-gas zones of the mixture, where undesired self-ignition may occur under some circumstances. Optical data are correlated to in-cylinder pressure oscillations on a cycle resolved basis.

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).

Diesel sprays from an axially-disposed single-hole injector are studied under both non-vaporizing and vaporizing conditions in a constant-volume vessel. A hybrid shadowgraph/Mie-scattering imaging set-up is used to acquire the liquid and vapor phases of the fuel distribution in a near-simultaneous visualization mode by a high-speed camera (40,000 fps). A diesel injector with k0 factor is used, having the exit-hole diameter of 0.1 mm and the ratio L/d =10. The studies are performed at the injection pressures of 70, 120, and 180 MPa, 25.37 kg/m3 ambient gas density, at the environment temperature of 373, 453 and 900 K. The instantaneous tip penetration of the liquid and vapor phases is extracted from the collected images and processed by a properly assessed software, under the various operating conditions. The AVL FIRE™ code is also used to simulate the spray dynamics. The model is validated on the ground of the collected experimental data.

This paper reports an experimental and numerical investigation on the spatial and temporal liquid- and vapor-phase distributions of diesel fuel spray under engine-like conditions. The high pressure diesel spray was investigated in an optically-accessible constant volume combustion vessel for studying the influence of the k-factor (0 and 1.5) of a single-hole axial-disposed injector (0.100 mm diameter and 10 L/d ratio). Measurements were carried out by a high-speed imaging system capable of acquiring Mie-scattering and schlieren in a nearly simultaneous fashion mode using a high-speed camera and a pulsed-wave LED system. The time resolved pair of schlieren and Mie-scattering images identifies the instantaneous position of both the vapor and liquid phases of the fuel spray, respectively. The studies were performed at three injection pressures (70, 120, and 180 MPa), 23.9 kg/m3 ambient gas density, and 900 K gas temperature in the vessel.

The attention on emissions of two-wheelers has been poor in the past, but today in countries with a large two-wheeler population it gives a significant contribution to aggregate emissions. In this paper the results obtained on a fleet composed by 22 two-stroke motorcycles (including mopeds) are presented. Sixteen in-use mopeds and six 125 cm3 motorcycles have been tested over ECE 47 and ECE 40 driving cycles respectively. Regulated emissions (CO, HC, NOx), carbon dioxide, benzene and fuel consumption have been evaluated by fueling motorcycles with two different gasoline formulations. One gasoline was a commercial Italian leaded gasoline with 1% benzene content; the other was a lower benzene and aromatics content gasoline. Benzene emissions decreased according to benzene content of gasoline.