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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.

Unregulated emissions of polycyclic aromatic hydrocarbons (PAHs), carbonylic compounds, benzene and particulate matter (PM) were quantified in exhausts of a vehicle fleet representative of in use gasoline cars. Emission factors were obtained during both cold and hot start driving cycles (from urban to motorway driving conditions). Carbonylic compounds were sampled by DNPH cartridges and analyzed by HPLC. Benzene and other light hydrocarbons were collected in bags and then analyzed by GC-FID. PAHs were trapped in XAD-2 cartridges and then analyzed by GC-MS. PM was sampled by using the gravimetric procedure required for diesel cars. The effect of technology is significant with respect to regulated and unregulated emissions but different emissive behavior was found by varying the driving cycles. Cold start has a major influence on hydrocarbon emissions (included unregulated ones). This experimental work was carried out within the framework of the EU Artemis project.

In the last years, increasing concerns about environmental pollution and fossil sources depletion led transport sectors research and development towards the study of new technologies capable to reduce vehicles emissions and fuel consumption. Direct-injection systems (DI) for internal combustion engines propose as an effective way to achieve these goals. This technology has already been adopted in Gasoline Direct Injection (GDI) engines and, lately, a great interest is growing for its use in natural gas fueling, so increasing efficiency with respect to port-fuel injection ones. Alone or in combination with other fuels, compressed natural gas (CNG) represents an attractive way to reduce exhaust emission (high H/C ratio), can be produced in renewable ways, and is more widespread and cheaper than gasoline or diesel fuels. Gas direct-injection process involves the occurrence of under-expanded jets in the combustion chamber.

Spectral flame emissivity and absorption measurements with high temporal and spatial resolution were performed in an optically accessible high-swirl divided-chamber Diesel system. Simultaneous determination of soot temperature, soot volume fraction and the OH radical concentration were made from the start to the end of the combustion in 153 locations equally distributed in the chamber. The engine was run at 2000 rpm and at fixed air-fuel ratio realizing 200 consecutive combustion cycles. To visualize the spatial and temporal spray and flame evolution, direct high-speed photographic sequences were taken at 8000 frames/s. The photographic sequences showed that the spray is strongly distorted and mixed by very high swirl resulting in a well premixed region where the combustion starts. The OH radicals were detected in the fuel reaction zone. Moreover OH concentration and soot volume fraction are well correlated with soot temperature.

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.

In this paper the investigation with X-ray Tomography on the structure of a gasoline spray from a GDI injector for automotive applications based on polycapillary optics is reported. Table-top experiment using a microfocus Cu Kα X-ray source for radiography and tomography has been used in combination with a polycapillary halflens and a CCD detector. The GDI injector is inserted in a high-pressure rotating device actuated with angular steps Δθ = 1° at the injection pressure of 8.0 MPa. The sinogram reconstruction of the jets by slices permits a 360° spray access to the fuel downstream the nozzle tip. A spatial distribution of the fuel is reported along the direction of six jets giving a measure of the droplet concentration in a circle of 16 mm2 below the nozzle tip at atmospheric backpressure and ambient temperature.

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.

The effect of different fuel parameters on emissions is difficult to understand, the response depending upon different engine technologies. In addition the isolation of some of the fuel variables is often very hard. The present paper discusses the main results obtained testing a matrix of 14 fuels designed for obtain large variations of cetane number, sulphur and aromatic contents of Diesel oil. The aromatic structure of fuels and its effect on particulate emissions was also investigated. A linear regression analysis was performed in order to isolate the main controlling factors on particulate emissions. Finally the influence of aromatic contents of fuel on unregulated emissions was also assessed.

With the advent of the KIVA-4 code which employs an unstructured mesh to represent the engine geometry, the gap in flexibility between commercial and research modeling software becomes more narrow. In this study, we tried to perform a full cycle simulation of a 4-stroke HD diesel engine represented by a highly boosted research IF (Isotta Fraschini) engine using the KIVA-4 code. The engine mesh including the combustion chamber, intake and exhaust valves and helical manifolds was constructed using optional O-Grids catching a complex geometry of the engine parts with the help of the ANSYS ICEM CFD software. The KIVA-4 mesh input was obtained by a homemade mesh converter which can read STAR-CD and CFX outputs. The simulations were performed on a full 360 deg mesh consisting of 300,000 unstructured hexahedral cells at BDC. The physical properties of the liquid fuel were taken corresponding to those of real diesel #2 oil.

The evaluation of vehicles real emissions circulating in urban areas is a basic activity for planning and management of implemented traffic measures aiming at emission control and air quality improvement. National, region, and city emission inventories require overall average emission estimation based on modeling technique with a few input parameters such as fleet composition and mission profile, represented by average speed. But in the field of emission modeling an important open issue is the very expensive costs of experimental campaigns needed to obtain driving cycle statistically representative of driving behavior, also if only in a specific link of a network. A possible approach to deal with this problem is represented by the use of traffic microscopic simulation models which are capable to simulate individual car motion on the basis of traffic conditions, road characteristics and management rules.

Nowadays, the regulation regards only the particles larger than 23 nm. The attention is shifting towards the sub-23 nm particles because of their large presence at the exhaust of the modern engines and their negative impact on human health. The main challenge of the regulation of these particles is the definition of a proper procedure for their measure. The nature of the sub-23 nm particles is not well understood, and their measure is strongly affected by the sampling conditions leading to not reliable measure. The aim of this paper is to provide information on the emissions of sub-23 nm particles from GDI vehicles/engines. At the same time, the presence of volatiles, which mainly contribute to the formation of sub-23 nm particles, was evaluated and the effect of sampling conditions was investigated. The analysis was performed on a 1.8L GDI powered vehicle, widely used both in North America and Europe, and a 4-cylinder GDI engine, whose features are similar to those of the vehicle.

In the global scenario of encouraging the use of renewable sources, the bioethanol as fuel supply in the automotive sector is receiving increasing interest. In the present paper the results of a research activity aimed to study the impact of a bioethanol/biodiesel/mineral diesel blend on performance and emissions of an automotive diesel engine are reassumed. An experimental campaign has been devoted to characterize the engine fuelled by the ethanol based blend highlighting the advantages and issues related to the bioethanol use. Moreover, the effects of the most important injection settings on the engine performance have been detailed, applying a Design of Experiment (DoE) method, to identify the potentiality offered by a proper engine calibration to optimize the ethanol blend use.

In this paper some results relative to tests performed on road with a Fiat Panda Bipower, (CNG and gasoline powered), and a New Panda Twin Air with auto Start & Stop system, are presented. Gaseous emissions are measured with Portable Emission Measurement Systems (PEMS) on two different urban routes, in terms of traffic and slope characteristics during in use experiments. PEMS testing offers an easy and efficient way to evaluate the vehicle emissions over a huge variety of conditions and provides us a direct way to study the in-use emissions of combustion engines, when you want to verify the effect of the traffic and of a particular device on fuel economy and emissions reduction. Moreover now PEMS performances are very comparable to those obtained by standard laboratory instrumentation systems.

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).

Three dimensional computations of Diesel combustion were performed using a modified version of Kiva II code. The autoignition and combustion model were tuned on a set of experimental conditions, changing the engine design, the operating conditions and the fuel characteristics. The sensitivity of the model to the different test cases is acceptable and the experimental trends are well reproduced. In addition the peak of pressure and temperature computed by the code are quite close to the experimental values, as well as the pressure derivatives. Once tuned the combustion model constants, different but simple formulations for the soot formation and oxidation processes were implemented in the code and compared with the experimental measurements obtained both with fast sampling technique and two colors method. These formulations were found unable to give good prediction in a large range of engine operating conditions, even if the model tuning may be very good for each test point.

The problem of emission evaluation control and modelling is nowadays an open question. In the framework of a Decision Support System (DSS), a new approach was developed for modeling and evaluating automotive pollutant emissions. An interesting point of this proposal was the integration of the micro simulated model to obtain driving cycle. In fact an important open issue is the very expensive costs of experimental campaigns needed to obtain driving cycle statistically representative of driving behaviour. So to overcome these high costs and to extend the real vehicle operating conditions framework, a possible solution is to integrate a microsimulation model in the general context of emission modeling. But the reliability of driving cycles coming from simulation models must be evaluated with respect to the possible influence on test bench measured emissions. In this paper, we would try to present some results related to two aspects of the problem.