Search Results

The analysis of a spray behavior is confined to study the fluid dynamic parameters such as axial and radial velocity of the droplets, size distribution of the droplets, and geometrical aspect as the penetration length. In this paper, the spray is considered like a dynamic system and consequently it can be described by a number of parameters that characterize its dynamic behavior. The parameter chosen to describe the dynamic behavior is the external cone angle. This parameter has been detected by using an experimental injection chamber, a multi-hole (8 holes) injector for GDI applications and recorded by a high-speed C-Mos camera. The images have been elaborated by a fuzzy logic and neural network algorithm and are processed by using a chaos deterministic theory. This procedure carries out a map distribution of the working point of the spray and determines the stable (signature of the spray) and instable behavior.

In the present paper, two different methodologies are adopted and critically integrated to analyze the knock behavior of a last generation small size spark ignition (SI) turbocharged VVA engine. Particularly, two full load operating points are selected, exhibiting relevant differences in terms of knock proximity. On one side, a knock investigation is carried out by means of an Auto-Regressive technique (AR model) to process experimental in-cylinder pressure signals. This mathematical procedure is used to estimate the statistical distribution of knocking cycles and provide a validation of the following 1D-3D knock investigations. On the other side, an integrated numerical approach is set up, based on the synergic use of 1D and 3D simulation tools. The 1D engine model is developed within the commercial software GT-Power™. It is used to provide time-varying boundary conditions (BCs) for the 3D code, Star-CD™.

The increasing diffusion of gasoline direct injection (GDI) engines requires a more detailed and reliable description of the phenomena occurring during the fuel injection process. As well known the thermal and fluid-dynamic conditions present in the combustion chamber greatly influence the air-fuel mixture process deriving from GDI injectors. GDI fuel sprays typically evolve in wide range of ambient pressure and temperatures depending on the engine load. In some particular injection conditions, when in-cylinder pressure is relatively low, flash evaporation might occur significantly affecting the fuel-air mixing process. In some other particular injection conditions spray impingement on the piston wall might occur, causing high unburned hydrocarbons and soot emissions, so currently representing one of the main drawbacks of GDI engines.

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.

The Real Driving Emission (RDE) procedure will measure the pollutants, such as NOx, emitted by cars while driven on the road. RDE will not replace laboratory tests, such as the current WLTP but it will be added to them. RDE is complementary to the laboratory-based procedure to check the pollutant emissions level of a light-duty vehicle in real driving conditions. This means that the car will be driven on a real road according to random acceleration and deceleration patterns conditioned by traffic flow. So, the procedure will ensure that cars deliver real emissions over on-road and so the currently observed differences between emissions measured in the laboratory and those measured on road under real-world conditions, will be reduced. However, the identification of a path on the road to check the test conditions of RDE is not easy and hardly repeatable.

Today, Direct-Injection systems are widely used on Spark-Ignition engines in combination with turbo-charging to reduce the fuel-consumption and the knock risks. In particular, the spread of Gasoline Direct Injection (GDI) systems is mainly related to the use of new generations of multi-hole, high-pressure injectors whose characteristics are quite different with respect to the hollow-cone, low-pressure injectors adopted in the last decade. This paper presents the results of an experimental campaign conducted on the spray produced by a GDI six-holes injector into a constant volume vessel with optical access. The vessel was filled with air at atmospheric pressure. Different operating conditions were considered for an injection pressure ranging from 3 to 20 MPa. For each operating condition, spray images were acquired by a CCD camera and then post processed to evaluate the spray penetration and cone angles.

In this paper, first results regarding measurements of fuel consumption and emissions, relative to different traffic conditions and a specific urban area, are presented. The experimental approach used for the evaluation of emissions consists in: a) recording on-road car and engine operating conditions during designed trips performed in the center of Naples (Italy) by an instrumented car, b) determining by multivariate statistical analysis driving cycles characterizing typical traffic conditions, c) measuring emissions and fuel consumption in laboratory using defined driving cycles. Fuel flow rate measurements are performed at each second, while emissions are detected along a cycle and an average value per kilometer is obtained. Operating conditions of engine during laboratory testing are related to on-road operating conditions by comparing fuel consumption and exhaust gases temperatures measurements performed on-road and in laboratory by the same device.

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.

A numerical methodology to simulate the high pressure spray evolution and the fuel-air mixing in diesel engines is presented. Attention is focused on the employed atomization model, a modified version of the Huh and Gosman, on the definition of a turbulence length scale limiter and of an adaptive local mesh refinement technique to minimize the result grid dependency. All the discussed models were implemented into Lib-ICE, which is a set of libraries and solvers, specifically tailored for engine simulations, which runs under the open-source CFD technology OpenFOAM®. To provide a comprehensive assessment of the proposed methodology, the validation procedure consisted into simulating, with a unique and coherent setup of all models, two different sets of experiments: a non-evaporating diesel fuel spray in a constant-volume vessel with optical access and an evaporating non-reacting diesel fuel spray in an optical engine.

This paper presents the experimental results obtained on Fuel Cell System designed and realized in Istituto Motori and based on 16 kW PEM (Proton Exchange Membrane) stack. This activity is part of the HBUS Project, whose goal is the realization of a midi-bus for public transportation in urban areas based on fuel cell technology. This Project involves several private and public partners, comprising Istituto Motori as research institution, I2T3 (Industrial Innovation Through Technological Transfer) agency for technological innovation and project management, together with public transportation companies and vehicle component makers.

Advanced numerical techniques, such as fuzzy logic and neural networks have been applied in this work to digital images acquired on a mono-component fuel spray (iso-octane), in order to define, in a stochastic way, the gas-liquid interface evolution. The image is a numerical matrix and so it is possible to characterize geometrical parameters and the time evolution of the jet by using deterministic, statistical stochastic and other several kinds of approach. The algorithm used works with the fuzzy logic concept to binarize the shades gray of the pixel, depending them, by using the schlieren technique, on the gas density. Starting from a primary fixed threshold, the applied technique, can select the ‘gas’ pixel from the ‘liquid’ pixel and so it is possible define the first most probably boundary lines of the spray.

The work analyses, from both an experimental and a numerical point of view, the impingement of a spray generated from a GDI injector on a hot solid wall. The temperature of the surface is identified as an important parameter affecting the outcome after impact. A gasoline spray issuing from a customized single-hole injector is characterized in a quiescent optically-accessible vessel as it impacts on an aluminum plate placed at 22.5 mm from the injector tip. Optical investigations are carried out at atmospheric back-pressure by a direct schlieren optical set-up using a LED as light source. A synchronized C-Mos high-speed camera captures cycle-resolved images of the evolving impact. The spatial and temporal evolution of the liquid and vapor phases are derived. They serve to define a data base to be used for the validation of a properly formulated 3D CFD model suitable to describe the impact of the fuel on the piston head in a real engine.

This work presents the results of an experimental investigation on a GDI injector, in order to analyze fuel injection process and atomization phenomenon, correlating imaging and vibro-acoustic diagnostic techniques. A single-hole, axially-disposed, 0.200 mm diameter GDI injector was used to spray commercial gasoline in a test chamber at room temperature and atmospheric backpressure. The explored injection pressures were ranged from 5.0 to 20.0 MPa. Cycle-resolved acquisitions of the spray evolution were acquired by a high-speed camera. Simultaneously, the vibro-acoustic response of the injector was evaluated. More in detail, noise data acquired by a microphone sensor were analyzed for characterizing the acoustic emission of the injection, while a spherical loudspeaker was used to excite the spray injection at a proper distance detecting possible fuel spray resonance phenomena.

In-cylinder optical diagnostic was applied to study butanol-gasoline blend combustion in a SI engine. Spark timing and fuel injection mode were changed to work in normal and knocking conditions. The experiments were realized in a single-cylinder ported fuel injection SI engine with an external boosting device. The engine worked like-stoichiometric mixture at 2000 rpm, medium boosting and wide open throttle. UV-visible natural emission spectroscopy allowed to follow the formation and the evolution of the main compounds and radical species that characterize the combustion process from the spark ignition until the exhaust. Particular interest was devoted to OH and CO₂* evolution, and to the spectral evidence of soot precursors due to fuel deposits burning. OH resulted the best marker for combustion both in normal and abnormal conditions.

A reason of the lack of agreement between measured pollutants concentration in the air of urban areas and vehicle pollutant emissions evaluated by available emission models is the fact that catalyst performance variability is not considered. In this paper, an experimental study on the effect of performance variability of catalyst on emissions is presented. Average emissions have been measured using driving cycles representative of different levels of urban traffic, determined by statistical methods on the basis of data detected on-road by an instrumented car. For each driving cycle, representative of a certain traffic level, different thermal starting conditions of catalyst have been tested. These conditions have been determined by the characterization of catalyst performance at steady state and are representative of real catalyst conditions experienced on the road.

The easiest way to identify knock conditions during the operation of a SI engine is represented by the knowledge of the in-cylinder pressure. Traditional techniques like MAPO (Maximum Amplitude Pressure Oscillation) based method rely on the frequency domain processing of the pressure data. This technique may present uncertainties due to the correct specification of some model parameters, like the band-pass frequency range and the crank angle window of interest. In this paper two innovative techniques for knock detection, which make use of the in-cylinder pressure, are explained in detail, and the results are compared with those coming from the MAPO method. The first procedure is based on the use of statistical analysis by applying an Auto Regressive (AR) technique, while the second technique makes use of the Discrete Wavelet Transform (DWT). The data useful for the analysis have been acquired on a high compression ratio four cylinder, spark ignition engine.

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.

In this paper, a high performance V12 spark-ignition engine is experimentally investigated at test-bench in order to fully characterize its behavior in terms of both average parameters, cycle-by-cycle variations and knock tendency, for different operating conditions. In particular, for each considered operating point, a spark advance sweep is actuated, starting from a knock-free calibration, up to intense knock operation. Sequences of 300 consecutive pressure cycles are measured for each cylinder, together with the main overall engine performance, including fuel flow, torque, and fuel consumption. Acquired data are statistically analyzed to derive the distributions of main indicated parameters, in order to find proper correlations with ensemble-averaged quantities. In particular, the Coefficient of Variation (CoV) of IMEP and of the in-cylinder peak pressure (pmax) are correlated to the average combustion phasing and duration (MFB50 and Δθb), with a good coefficient of determination.

In recent years, the increase of gasoline fuel injection pressure is a way to improve thermal efficiency and lower engine-out emissions in GDI homogenous combustion concept. The challenge of controlling particulate formation as well in mass and number concentrations imposed by emissions regulations can be pursued improving the mixture preparation process and avoiding mixture inhomogeneity with ultra-high injection pressure values up to 100 MPa. The increase of the fuel injection pressure in GDI homogeneous systems meets the demand for increased injector static flow, while simultaneously improves the spray atomization and mixing characteristics with consequent better combustion performance. Few studies quantify the effects of high injection pressure on transient gasoline spray evolution. The aim of this work was to simulate with OpenFOAM the spray morphology of a commercial gasoline injected in a constant volume vessel by a prototypal GDI injector.

Multi-wavelength ultraviolet-visible extinction spectroscopy was applied to follow the evolution of fuel vapor injected by post-injection along the exhaust line of a common-rail turbocharged direct-injection diesel engine at moderate speed and load. The exhaust line was specifically designed and customized to allow the insertion of the optical access upstream of the Diesel Oxidation Catalyst. During the experimental campaign, the engine was fuelled with commercial B5 fuel and a B30 v/v blend of RME and ultra low sulfur diesel, monitoring emissions upstream of the catalyst and exhaust gas temperature across the catalyst. Tests were performed at different engine operating conditions with particular attention to moderate speed and load.