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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 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.

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.

New internal combustion engines (ICE) are characterized by increasing maximum efficiency, thanks to the adoption of strategies like Atkinson cycle, downsizing, cylinder deactivation, waste heat recovery and so on. However, the best performance is confined to a limited portion of the engine map. Moreover, electric driving in urban areas is an increasingly pressing request, but battery electric vehicles use cannot be easily spread, due to limited vehicle autonomy and recharging issues. Therefore, hybrid propulsion systems are under development, in order to reduce vehicle fuel consumption, by decoupling the ICE running from road load, as well as to permit energy recovery and electric driving. This paper analyses a new-patented solution for power split hybrid propulsion system with gearbox. The system comprises an auxiliary power unit, adapted to store and/or release energy, and a planetary gear set, which is interposed between the ICE and the gearbox.

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.

Alternative combustion control in the form of lean operation offers significant advantages such as high efficiency and “clean” fuel oxidation. Maximum dilution rates are limited by increasing instability that can ultimately lead to partial burning or even misfires. A compromise needs to be reached between high tumble-turbulence levels that “speed-up” combustion and the inherent stochastic nature of this fluid motion. The present study is focused on gaining improved insight into combustion characteristics through thermodynamic analysis and flame imaging, in a wall-guided direct injection spark ignition engine with optical accessibility. Engine speed values were investigated in the range of 1000 to 2000 rpm, with commercial gasoline fueling, in wide open throttle conditions; mixture strength ranged from stoichiometric, down to the equivalence ratios that allowed acceptable cycle-by-cycle variations; and all cases featured spark timing close to the point of maximum brake torque.

An experimental campaign was carried out to evaluate the influence of CNG and gasoline on the exhaust emissions and fuel consumption of a bi-fuel passenger car over on-road tests performed in the city of Naples. The chosen route is very traffic congested during the daytime of experimental measurements. An on-board analyzer was used to measure CO, CO2, NOx tailpipe concentrations and the exhaust flow rate. Throughout a carbon balance on the exhaust pollutants, the fuel consumption was estimated. The exact spatial position was acquired by a GPS which allowed to calculate vehicle speed and the traffic condition was monitored by a video camera. Whole trip realized by the vehicle was subdivided in succession of kinematic sequences and the vehicle emissions and fuel consumption were analyzed and presented as value on each kinematic sequence. Moreover, throughout a multivariate statistical analysis of sequences, the driving cycles characterizing the use of vehicle were identified.

Automotive exhaust systems give a major contribution to the sound quality of a vehicle and must be properly designed in order to produce acceptable acoustic performances. Obviously, noise attenuation is strictly related to the used materials and to its internal geometry. This last influences the wave propagation and the gas-dynamic field. The purpose of this paper is to describe advantages and disadvantages of different numerical approaches in evaluating the acoustic performance in terms of attenuation versus frequency (Transmission Loss) of a commercial two perforated tube muffler under different conditions. At first, a one-dimensional analysis is performed through the 1D GTPower® code, solving the nonlinear flow equations which characterize the wave propagation phenomena. The muffler is characterized as a network of properly connected pipes and volumes starting from 3D CAD information. Then, two different 3D analyses are performed within the commercial STS VNOISE® code.

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 characteristics of the intake system affect both engine power output and gas-dynamic noise emissions. The latter is particularly true in downsized VVA engines, where a less effective attenuation of the pressure waves is realized, due to the intake line de-throttling at part-load. For this engine architecture, a refined air-box design is hence requested. In this work, the Transmission Loss (TL) of the intake air-box of a commercial VVA engine is numerically computed through a 3D FEM approach. Results are compared with experimental data, showing a very good correlation. The validated model is then coupled to an external optimizer (ModeFRONTIERTM) to increase the TL parameter in a prefixed frequency range. The improvement of the acoustic attenuation is attained through a shape deformation of the inner structure of the base device, taking into account constraints related to the device installation inside the engine bay.

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 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.

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 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.

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.

This is the second part of a study on using port water injection to quantifiably enhance the knock performance of fuels. In the United States, the metric used to quantify the anti-knock performance of fuels is Anti Knock Index (AKI), which is the average of Research Octane Number (RON) and Motor Octane Number (MON). Fuels with higher AKI are expected to have better knock mitigating properties, enabling the engine to run closer to Maximum Brake Torque (MBT) spark timing in the knock limited region. The work done in part I of the study related increased knock tolerance due to water injection to increased fuel AKI, thus establishing an ‘effective AKI’ due to water injection. This paper builds upon the work done in part I of the study by repeating a part of the test matrix with Primary Reference Fuels (PRFs), with iso-octane (PRF100) as the reference fuel and lower PRFs used to match its performance with the help of port water injection.

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 liquid fuels 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.

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.