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In the present work, an experimental and numerical analysis of high pressure Diesel spray evolution is carried out in terms of spray momentum flux time history and instantaneous injection rate. The final goal of spray momentum and of injection rate analyses is the evaluation of the nozzle outlet flow characteristics and of the nozzle internal geometry possible influences on cavitation phenomena, which are of primary importance for the spray evolution. Further, the evaluation of the flow characteristics at the nozzle exit is fundamental in order to obtain reliable boundary conditions for injection process 3D simulation. In this paper, spray momentum data obtained in ambient temperature, high counter-pressure conditions at the Perugia University Spray Laboratory are presented and compared with the results of 3D simulations of the momentum rig itself.

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 study, experiments were carried out in an optical single-cylinder Direct Injection Spark Ignition engine fuelled with n-butanol and gasoline, alternatively. The engine is equipped with the head of a commercial turbocharged engine with similar geometrical specifications (bore, stroke, compression ratio). The head has four valves and a centrally located spark device with surface charge ignition. A conventional elongated hollow Bowditch piston is used and an optical crown, accommodating fused-silica window, is screwed onto it. The injector is side mounted and features 6 holes oriented to guide the jets towards the piston crown. During the experimental activity, the injection pressure was maintained at 100 bar for all conditions; the injection timing and the number of injections were adjusted to investigate their influence on combustion and emissions.

Nowadays internal combustion engines can operate under lean combustion conditions to maximize efficiency, as long as combustion stability is guaranteed. The robustness of combustion initiation is one of the main issues of actual spark-ignition engines, especially at high level of excess-air or dilution. The enhancement of the in-cylinder global motion and local turbulence is an effective way to increase the flame velocity. During the ignition process, the excessive charge motion can hinder the spark discharge and eventually cause a misfire. In this perspective, the interaction between the igniter and the flow field is a fundamental aspect which still needs to be explored in more detail to understand how the combustion originates and develops. In this work, a combined experimental and numerical study is carried out to investigate the flow field around the spark gap, and its effect on the spark discharge evolution.

A plasma ignition system was tested in a GDI engine with the target of combustion efficiency improvement without modifying engine configuration. The plasma was generated by spark discharge and successively sustained to enhance its duration up to 4 ms. The innovative ignition system was tested in an optically accessible single-cylinder DISI engine to investigate the effects of plasma on kernel stability and flame front propagation under low loads and lean mixture (λ≅1.3). The engine was equipped with the head of a commercial turbocharged engine with similar geometrical specifications (bore, stroke, compression ratio). All experiments were performed at 2000 rpm and 100 bar injection pressure. UV-visible 2D chemiluminescence was applied in order to study the flame front inception and propagation with particular interest in the early combustion stages. A bandpass filter allowed selecting luminous signal due to OH radicals.

The increasing limitations in engine emissions and fuel consumption have led researchers to the need to accurately predict combustion and related events in gasoline engines. In particular, knock is one of the most limiting factors for modern SI units, severely hindering thermal efficiency improvements. Modern CFD simulations are becoming an affordable instrument to support experimental practice from the early design to the detailed calibration stage. To this aim, combustion and knock models in RANS formalism provide good time-to-solution trade-off allowing to simulate mean flame front propagation and flame brush geometry, as well as “ensemble average” knock tendency in end-gases. Still, the level of confidence in the use of CFD tools strongly relies on the possibility to validate models and methodologies against experimental measurements.

Engine knock is one of the most limiting factors for modern Spark-Ignition (SI) engines to achieve high efficiency targets. The stochastic nature of knock in SI units hinders the predictive capability of RANS knock models, which are based on ensemble averaged quantities. To this aim, a knock model grounded in statistics was recently developed in the RANS formalism. The model is able to infer a presumed log-normal distribution of knocking cycles from a single RANS simulation by means of transport equations for variances and turbulence-derived probability density functions (PDFs) for physical quantities. As a main advantage, the model is able to estimate the earliest knock severity experienced when moving the operating condition into the knocking regime.

The occurrence of knock is the most limiting hindrance for modern Spark-Ignition (SI) engines. In order to understand its origin and move the operating condition as close as possible to onset of this potentially harmful phenomenon, a joint experimental and numerical investigation is the most recommended approach. A preliminary experimental activity was carried out at IM-CNR on a 0.4 liter GDI unit, equipped with a flat transparent piston. The analysis of flame front morphology allowed to correlate high levels of flame front wrinkling and negative curvature to knock prone operating conditions, such as increased spark timings or high levels of exhaust back-pressure. In this study a detailed CFD analysis is carried out for the same engine and operating point as the experiments. The aim of this activity is to deeper investigate the reasons behind the main outcomes of the experimental campaign.

Artificial Intelligence is becoming very important and useful in several scientific fields. Machine learning methods, such as neural networks and decision trees, are often proposed in applications for internal combustion engines as virtual sensors, faults diagnosis systems and engine performance optimization. The high pressure of the intake air coupled with the demand of lean conditions, in order to reduce emissions, have often close relationship with the knock events. Fuels autoignition characteristics and flame front speed have a significant impact on knock phenomenon, producing high internal cylinder pressures and engine faults. The limitations in using pressure sensors in the racing field and the challenge to reduce the costs of commercial cars, push the replacement of a hardware redundancy with a software redundancy.

The detailed study of part-load conditions is essential to characterize engine-out emissions in key operating conditions. The relevance of part-load operations is further emphasized by the recent regulations such as the new WLTP standard. Combustion development at part-load operations depends on a complex interplay between moderate turbulence levels (low engine speed and tumble ratio), low in-cylinder pressure and temperature, and stoichiometric-to-lean mixture quality (to maximize fuel efficiency). From a modelling standpoint, the reduced turbulence intensity compared to full-load operations complicates the interaction between different sub-models (e.g., reconsideration of the flamelet hypothesis adopted by common combustion models). In this article, the authors focus on chemistry-based simulations for laminar flame speed of gasoline surrogates at conditions typical of part-load operations. The analysis is an extension of a previous study focused on full-load operations.

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.

Conventional fossil fuels are more and more regulated in terms of both engine-out emissions and fuel consumption. Moreover, oil price and political instabilities in oil-producer countries are pushing towards the use of alternative fuels compatible with the existing units. N-Butanol is an attractive candidate as conventional gasoline replacement, given its ease of production from bio-mass and key physico-chemical properties similar to their gasoline counterpart. A comparison in terms of combustion behavior of gasoline and n-Butanol is here presented by means of experiments and 3D-CFD simulations. The fuels are tested on a single-cylinder direct-injection spark-ignition (DISI) unit with an optically accessible flat piston. The analysis is carried out at stoichiometric undiluted condition and lean-diluted mixture for both pure fuels.

Within the context of environmental impact reduction for small size spark ignition (SI) engines, especially green-house gas emissions, this study looked at laminar flame speed as an optimization parameter for hydrogen-methane fueled micro-generators. To this aim, SI engine operation was modeled in a 0D/1D simulation framework, so as to identify the best choice of methane-hydrogen ratios in different conditions. Starting from experimental data recorded on a small size engine, an optimization method was implemented for achieving the proposed goal. One of the main conclusions is that high concentrations of hydrogen and resulting fast burn rates are beneficial at high engine speed settings, while the opposite is true at low engine speed. Hydrogen addition was also considered as an additional control margin during lean operation, given that stable combustion can be achieved even with very low equivalence ratios.

This work aims at analyzing the fluid dynamic characteristics of a Ducati 4 valves SI engine, for racing motorcycle, during the intake and compression strokes, focusing on the correlation between steady state flow test data (experiments and simulations) and transient CFD simulation results, including the effect of variable valve actuation strategies with independent intake valve actuation. Several steady state flow test data were available in terms of maps of the discharge, tumble and swirl coefficients, at any combination of asymmetric lifts of the two intake valves. From these steady state data it can be argued that asymmetric strategies could enhance engine full load and part load operation characteristics, by exploiting favourable trade off occurring between the opposing needs for high mass flow rate and high charge motion intensity.

The present work is the continuation of the research activity developed by the same authors in last years about the use of recent technologies (Artificial Neural Networks) for the set up of “software redundancy” modules to be implemented On Board for the use in Diagnostic Systems. In the present work, a system based on Artificial Neural Networks models for automotive engines Fault Diagnosis and Isolation purposes is set-up and analysed. Four sensors/actuators (throttle valve, rotational speed, torque and intake manifold pressure) are considered, and the respective acquired data are used to train and test four ANN modules correlating the different quantities. An FDI scheme is presented which generates fault codes sequences by suitably treating the primary residuals, obtained by comparing experimental data with the calculated ones by the ANN modules. The robust fault isolation capabilities of the proposed FDI system are presented and discussed.

The recent introduction of electronic controlled, high pressure injection systems has deeply changed the scenario for light duty, automotive diesel engines. This change is mainly due to the enhanced flexibility in obtaining the desired injection law (time history and injected fuel quantity), while high injection pressures also favour a suitable mixture formation. This results in higher engine performance (efficiency and power) and in better pollutant emissions control. At the same time, in order to reduce the greenhouse gases net production, research is analyzing alternative resources, such as bio-derived fuels. In particular, methyl esters derived by different vegetable oils are characterized by high cetane numbers and very small sulfur content. The present work reports the results of a comparative analysis performed on a modern DI, common-rail, turbocharged engine by using three different bio-derived fuels (rape seed, soybean, waste cooked oil) and conventional fossil diesel fuel.

The design of new geometries of combustion chambers together with the design of improved intake systems are some of the most important applied research activities that attempt to improve the complex processes underlying combustion. The design and the analysis of new optimized geometries which use numerical simulations, based on a commercial CFD code utilization, seems to be a very interesting way to reduce the industrial costs in the engines developing activity. In the present work, steady state simulations of an intake system of a race engine head of Ducati Corse , using a commercial 3D-CFD code, are carried out to tune the parameters of the used models and to analyze different configurations. The models validation is based on the experimental results obtained from a parallel paper concerning the Tumble Coefficient (Nt) and the Discharge Coefficient (Cd) obtained using two configurations: with an L-shaped tumble adaptor and a standard one.

Multi-fuel operation is one of the main topics of investigative research in the field of internal combustion engines. Spark ignition (SI) power units are relatively easily adaptable to alternative liquid-as well as gaseous-fuels, with mixture preparation being the main modification required. Numerical simulations are used on an ever wider scale in engine research in order to reduce costs associated with experimental investigations. In this sense, quasi-dimensional models provide acceptable accuracy with reduced computational efforts. Within this context, the present study puts under scrutiny the assumption of spherical flame propagation and how calibration of a two-zone combustion simulation is affected when changing fuel type. A quasi-dimensional model was calibrated based on measured in-cylinder pressure, and numerical results related to the two-zone volumes were compared to recorded flame imaging.

Radio Frequency Corona ignition systems represent an interesting solution among innovative ignition strategies for their ability to stabilize the combustion and to extend the engine operating range. The corona discharge, generated by a strong electric field at a frequency of about 1 MHz, produces the ignition of the air-fuel mixture in multiple spots, characterized by a large volume when compared to a conventional spark, increasing the early flame growth speed. The transient plasma generated by the discharge, by means of thermal, kinetic and transport effects, allows a robust initialization of the combustion even in critical conditions, such as using diluted or lean mixtures. In this work the effects of Corona ignition have been analyzed on a single cylinder optical engine fueled with gasoline, comparing the results with those of a traditional single spark ignition.

Quasi-dimensional modeling is used on a wide scale in engine development, given its potential for saving time and resources compared to experimental investigations. Often it is preferred to more complex CFD codes that are much more computationally intensive. Accuracy is one major issue of quasi-dimensional simulations and for this reason sub-models are continuously developed for improving predictive capabilities. This study considers the use of equivalent fluid velocity and characteristic length scales for simulating the processes of fresh charge entrainment and oxidation behind the flame front. Rather than dividing combustion into three different phases (i.e. laminar kernel, turbulent flame propagation and oxidation near the walls), the concept of turbulent heat and mass transfer is imposed throughout the entire process.