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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 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.

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-cylinder ion sensing is a subject of interest due to its application in spark-ignited (SI) engines for feedback control and diagnostics including: combustion knock detection, rate and phasing of combustion, and mis-fire On Board Diagnostics (OBD). Further advancement and application is likely to continue as the result of the availability of ignition coils with integrated ion sensing circuitry making ion sensing more versatile and cost effective. In SI engines, combustion knock is controlled through closed loop feedback from sensor metrics to maintain knock near the borderline, below engine damage and NVH thresholds. Combustion knock is one of the critical applications for ion sensing in SI engines and improvement in knock detection offers the potential for increased thermal efficiency. This work analyzes and characterizes the ionization signal in reference to the cylinder pressure signal under knocking and non-knocking conditions.

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.

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.

Sensory jury testing was utilized to characterize vibration levels perceived by the operator, with respect to levels measured using instrumentation, in order to develop a tool for the evaluation of vibration at the operator interfaces. Details of the jury testing and jury data processing method are highlighted as well as the refinement of vibration characterization for a specific application. The vibration at user interface locations of both snowmobiles and ATVs was measured along with subjective feedback from a panel of jurists. Statistical analysis was performed on the jury data to provide both a qualitative and quantitative number to represent the opinion of the jury. Correlations were developed between the measured levels of vibration and the opinions of the jury. Finally, a set of correlation functions suitable for design predictions was developed.

This paper presents an innovative approach for quality engineering using the Eigenvector Dimension Reduction (EDR) Method. Currently industry relies heavily upon the use of the Taguchi method and Signal to Noise (S/N) ratios as quality indices. However, some disadvantages of the Taguchi method exist such as, its reliance upon samples occurring at specified levels, results to be valid at only the current design point, and its expensiveness to maintain a certain level of confidence. Recently, it has been shown that the EDR method can accurately provide an analysis of variance, similar to that of the Taguchi method, but is not hindered by the aforementioned drawbacks of the Taguchi method. This is evident because the EDR method is based upon fundamental statistics, where the statistical information for each design parameter is used to estimate the uncertainty propagation through engineering systems.

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 damping effectiveness of free-layer damping materials through standard Oberst bar testing, solid plate excitation (RTC3) testing, and prediction through numerical schemes. The main objective is to compare damping results from various industry test methods to performance in an automotive body structure. Existing literature on laboratory and vehicle testing of free-layer viscoelastic damping materials has received significant attention in recent history. This has created considerable confusion regarding the appropriateness of different test methods to measure material properties for damping materials/treatments used in vehicles. The ability to use the material properties calculated in these tests in vehicle CAE models has not been extensively examined. Existing literature regarding theory and testing for different industry standard damping measurement techniques is discussed.

The traditional method of dynamic characterization of elastomers used in industry has largely been based on sinusoidal input excitation. Discrete frequency sine wave signals at specified amplitudes are used to excite the elastomer in a step-sine sweep fashion. This paper will examine new methods of characterization using various broadband input excitations. These different inputs include continuous sine sweep (chirp), shaped random, and acquired road profile data. Use of these broadband data types is expected to provide a more accurate representation of conditions seen in the field, while helping to eliminate much of the interpolation that is inherent with the classic discrete step-sine technique. Results of the various input types are compared in this paper with those found using the classic discrete step-sine input.

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.

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.

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.

This paper aims to provide the experimental and numerical investigation of a single fuel droplet impingement on the different wall conditions to understand the detailed impinging dynamic process. The experimental work was carried out at the room temperature and pressure except for the variation of the impinged wall temperature. A high-speed camera was employed to capture the silhouette of the droplet impinging on wall process against a collimated light. Water, diesel, n-dodecane, and n-heptane were considered as four different droplets and injected from a precision syringe pump with the volume flow rate of 0.2 mL/min at various impact Weber numbers. The impingement outcomes after droplet impacting on the wall include stick, spread, rebound and splash, which depend on the controlling parameters of Weber number, Reynolds number, liquid and surface properties, etc.

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-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.