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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.

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.

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.

This paper describes how a fully three-dimensional CFD model was used to investigate the turbulence generation mechanisms of an unthrottled 4 valve SI engine operating with different intake valve lift strategies (symmetric and asymmetric). In the context of Early Intake Valve Closure (EIVC) strategies, the aim of the work is to highlight the potentialities to increase turbulence levels also at light load using asynchronous intake valve lift, thus promoting both tumble and swirl motions. Six simulations are presented, four at low engine speed (2500 rpm) and two at high speed (6000 rpm, that serve as reference), concerning an SI engine at full and light load, with symmetric and asymmetric intake lifts. One of these simulations was executed in standard throttling conditions. The CFD transient simulations involved three strokes of the engine: exhaust, intake and compression up to combustion TDC. 1D data are used for boundary and initial conditions.

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.

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.

In the last decades, worldwide automotive regulations induced the industry to dramatically increase the application of electronics in the control of the engine and of the pollutant emissions reduction systems. Besides the need of engine control, suitable fault diagnosis tools had also to be developed, in order to fulfil OBD-II and E-OBD requirements. At present, one of the problems in the development of Diesel engines is represented by the achievement of an ever more sharp control on the systems used for the pollutant emission reduction. In particular, as far as NOx gas is concerned, EGR systems are mature and widely used, but an ever higher efficiency in terms of emissions abatement, requires to determine as better as possible the actual oxygen content in the charge at the engine intake manifold, also in dynamic conditions, i.e. in transient engine operation.

The present work concerns the analysis of a concept for a new variable valve actuation system for internal combustion engines, denoted HVC (Hydraulic Valve Control system). The system is an electro-hydraulic device which aims at minimizing the power consumption required for the valve actuation. Unlike lost motion devices, where the excess pumped oil is wasted in order to control the lift profile, the HVC system uses a reduced quantity of energy to ensure the actual lift profile. For that reason interesting potentialities to increase the global fuel conversion efficiency of the engine are expected, in addition to the benefits deriving from the control flexibility. The HVC system has been modeled by means of an hydraulic simulation tool, useful for the dynamic analysis of mechanical and hydraulic systems. In this work the main elements of the device will be described and their relevant modeling parameters will be discussed.

Lean operation of spark ignition engines is a promising strategy for increasing thermal efficiency and minimize emissions. Variability on the other hand is one of the main shortcomings in these conditions. In this context, the present study looks at the interaction between the spark produced by a J-type plug and the surrounding fluid flow. A combined experimental and numerical approach was implemented so as to provide insight into the phenomena related to the ignition process. A sweep of cross-flow velocity of air was performed on a dedicated test rig that allowed accurate control of the volumetric flow and pressure. This last parameter was varied from ambient to 10 bar, so as to investigate conditions closer to real-world engine applications. Optical diagnostics were applied for better characterization of the arc in different operating conditions. The spatial and temporal evolution of the arc was visualized with high-speed camera to estimate the length, width and stretching.

It has been proved that Radio Frequency Corona, among other innovative ignition systems, is able to stabilize combustion and to extend the engine operating range in lean conditions, with respect to conventional spark igniters. This paper reports on a sensitivity analysis on the combustion behavior for different values of Corona electric control parameters (supply voltage and discharge duration). Combustion analysis has been carried out on a single cylinder PFI gasoline-fueled optical engine, by means of both indicating measurements and imaging. A high-speed camera has been used to record the natural luminosity of premixed flames and the obtained images have been synchronized with corresponding indicating acquisition data. Imaging tools allowed to observe and measure the early flame development, providing information which are not obtainable by a pressure-based indicating system.

The new real driving emission cycles and the growing adoption of turbocharged GDI engines are directing the automotive technology towards the use of innovative solutions aimed at reducing environmental impact and increasing engine efficiency. Water injection is a solution that has received particular attention in recent years, because it allows to achieve fuel savings while meeting the most stringent emissions regulations. Water is able to reduce the temperature of the gases inside the cylinder, coupled with the beneficial effect of preventing knock occurrences. Moreover, water dilutes combustion, and varies the specific heat ratio of the working fluid; this allows the use of higher compression ratios, with more advanced and optimal spark timing, as well as eliminating the need of fuel enrichment at high load. Computational fluid dynamics simulations are a powerful tool to provide more in-depth details on the thermo-fluid dynamics involved in engine operations with water injection.

Large-Eddy simulations (LES) are becoming an engineering tool for studying internal combustion engines (ICE) thanks to their ability to capture cycle-to-cycle variability (CCV) resolving most of the turbulent flow structures. ICEs can operate under lean combustion conditions to maximize efficiency. However, instabilities associated with lean combustion may cause problems, such as excessive levels of CCV or even misfires. In this context, the energy released by the spark during the ignition and its interaction with the flow field are fundamental parameters that affect ignition stability and how combustion takes place and develops. The aim of this paper is the characterization of the combustion stability in a SI optical access engine, by means of multicycle LES simulations, using CONVERGE software. Sub-grid-scale turbulence is modeled with a viscous one-equation model.

In this paper the evaluation of the suitability of the Artificial Neural Networks for setting up simulation modules for “analytical redundancy” was further carried out. The performance of the ANN modules was enhanced, by taking into account the engine dynamics for the simulation of fast engine transients and obtaining satisfactory results. Working toward actual on board application in Fault Diagnosis systems, some ANN modules were implemented in an on-line system which acquires signals from an engine mounted on a test bench and compares in real time the experimental values with the estimated ones. In this way, it was possible to perform long duration tests of ANN's behaviour, substantially confirming the results of the conventional off-line analysis.