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Knocking combustions heavily limits the efficiency of Spark Ignition engines. The compression ratio is limited in the design stage of the engine development, letting to Spark Advance control the task of reducing the odds of abnormal combustions. A detailed analysis of knocking events can help improving engine performance and diagnosis strategies. An effective way is to use advanced 3D CFD (Computational Fluid Dynamics) simulation for the analysis and prediction of combustion performance. Standard 3D CFD approach is based on RANS (Reynolds Averaged Navier Stokes) equations and allows the analysis of the mean engine cycle. However knocking phenomenon is not deterministic and it is heavily affected by the cycle to cycle variation of engine combustions. A methodology for the evaluation of the effects of CCV (Cycle by Cycle Variability) on knocking combustions is here presented, based on both the use of Computation Fluid Dynamics (CFD) tools and experimental information.

Due to the recent anti-pollution policies, the performance increase in Spark Ignition (SI) engines is currently under the focus of automotive manufacturers. This trend drives control systems designers to investigate accurate solutions and build more sophisticated algorithms to increase the efficiency of this kind of engines. The development of a control strategy is composed of several phases and steps, and the first part of such process is typically spent in defining and investigating the logic of the strategy. During this phase it is often useful to have a light engine simulator, which allows to have robust synthetic combustion data with a low calibration and computational effort. In the first part of this paper, a description of the control-oriented ANalytical Engine SIMulator (ANESIM) is carried out.

Water Injection (WI) has become a key technology for increasing combustion efficiency in modern GDI turbocharged engines. In fact, the addition of water mitigates significantly the occurrence of knock, reduces exhaust gas temperatures, and opens the possibility to reach optimum heat release phasing even at high load. This work presents the latest development of a model-based WI controller, and its experimental validation on a GDI TC engine. The controller is based on a novel approach that involves an analytic combustion model to define the spark advance (SA) required to reach a combustion phase target, considering injected water mass effects. The calibration and experimental validation of the proposed controller is shown in detail in the paper.

This paper summarizes the main studies carried out by the authors for the development of indexes for remote combustion sensing applicable to different combustion types, i.e. conventional gasoline and diesel combustions, diesel PCCI and dual fuel gasoline-diesel RCCI. It is well-known that the continuous development of modern Internal Combustion Engine (ICE) management systems is mainly aimed at complying with upcoming increasingly stringent regulations throughout the world, both for pollutants and CO2 emissions. Performing an efficient combustion control is crucial for efficiency increase and pollutant emissions reduction. Over the past years, the authors of this paper have developed several techniques to estimate the most important combustion indexes for combustion control, without using additional cylinder pressure sensors but only using the engine speed sensor (always available on board) and accelerometers (usually available on-board for gasoline engines).

The vehicle WLTP and RDE homologation test cycles are pushing the engine technology toward the implementation of different solutions aimed to the exhaust gases emission reduction. The tightening of the policy on the Auxiliary Emission Strategy (A.E.S.), including those for the engine component protection, faces the Spark Ignited (S.I.) engines with the need to replace the fuel enrichment as a means to cool down both unburnt mixture and exhaust gases to accomplish with the inlet temperature turbine (TiT) limit. Among the whole technology solutions conceived to make SI engine operating at lambda 1.0 on the whole operation map, the water injection is one of the valuable candidates. Despite the fact that the water injection has been exploited in the past, the renewed interest in it requires a deep investigation in order to outcome its potential as well as its limits.

This paper presents an optimization algorithm, based on discrete dynamic programming, that aims to find the optimal control inputs both for energy and thermal management control strategies of a Plug-in Hybrid Electric Vehicle, in order to minimize the energy consumption over a given driving mission. The chosen vehicle has a complex P1-P4 architecture, with two electrical machines on the front axle and an additional one directly coupled with the engine, on the rear axle. In the first section, the algorithm structure is presented, including the cost-function definition, the disturbances, the state variables and the control variables chosen for the optimal control problem formulation. The second section reports the simplified quasi-static analytical model of the powertrain, which has been used for backward optimization. For this purpose, only the vehicle longitudinal dynamics have been considered.

Traditional User/Maintenance Manuals provide useful information when dealing with simple machines. However, when dealing with complex systems of systems and highly miniaturized technologies, like UAVs, or with machines with millions of parts, a commercial aircraft is a case in point, new technologies taking advantage of Augmented Reality can rapidly and effectively support the maintenance operations. This paper presents a User/Maintenance Manual based on Augmented Reality to help the operator in the detection of parts and in the sequence to be followed to assemble/disassemble systems and subsystems. The proposed system includes a handheld device and/or an head mounted display or special goggles, to be used by on-site operators, with software management providing data fusion and overlaying traditional 2D user/maintenance manual information with an augmented reality software and appropriate interface.

The maturity reached in the development of Unmanned Air Vehicles (UAVs) systems is making them more and more attractive for a vast number of civil missions. Clearly, the introduction of UAVs in the civil airspace requiring practical and effective regulation is one of the most critical issues being currently discussed. As several civil air authorities report in their regulations “Sense and Avoid” or “Detect and Avoid” capabilities are critical to the successful integration of UAV into the civil airspace. One possible approach to achieve this capability, specifically for operations beyond the Line-of-Sight, would be to equip air vehicles with a vision-based system using cameras to monitor the surrounding air space and to classify other air vehicles flying in close proximity. This paper presents an image-based application for the supervised classification of air vehicles.

The high number of hull losses is a main concern in the UAV field, mostly due to the high cost of on-board equipment. A crashworthiness design can be helpful to control the extent and position of crash impact damage, minimizing equipment losses. However, the wide use of composite materials has recently put the accent on the lack of data about the behavior of these structures under operative loads, such as the crash conditions. This paper presents the outcome of a set of tests carried out to achieve a controlled crush of UAV structures, and to maximize the Specific Energy Absorption. In this work, a small-scale experimental test able to characterize the energy absorption of a Carbon-fiber-reinforced polymer under compression was developed introducing self-supporting sinusoidal shape specimens, which avoid the need for complex anti-buckling devices.

Water injection is becoming a technology of increasing interest for SI engines development to comply with current and prospective regulations. To perform a rapid optimization of the main parameters involved by the water injection process, it is necessary to have reliable CFD methodologies capable of capturing the most important phenomena. In the present work, a methodology for the CFD simulation of combustion cycles of SI GDI turbocharged engines under water injection operation is proposed. The ECFM-3Z model adopted for combustion and knock simulations takes advantages by the adoption of correlations for the laminar flame speed, flame thickness and ignition delay times prediction obtained by a detailed chemistry calculation. The latter uses machine learning algorithms to reduce the time to generate the full database while still maintaining an even distribution along the variables of interest.

Metallic open-cell foams have proven to be valuable for many engineering applications. Their success is mainly related to mechanical strength, low density, high specific surface, good thermal exchange, low flow resistance and sound absorption properties. The present work aims to investigate three principal aspects of real foams: the geometrical characterization, the flow regime characterization, the effects of the pore size and the porosity on the pressure drop. The first aspect is very important, since the geometrical properties depend on other parameters, such as porosity, cell/pore size and specific surface. A statistical evaluation of the cell size of a foam sample is necessary to define both its geometrical characteristics and the flow pattern at a given input velocity. To this purpose, a procedure which statistically computes the number of cells and pores with a given size has been implemented in order to obtain the diameter distribution.

In PFI and GDI engines the tumble motion is the most important charge motion for enhancing the in-cylinder turbulence level at ignition time close to the spark plug position. In the open literature different studies were reported on the tumble motion, experimental and not. In the present paper the research activity on the tumble generation at partial load and very partial load conditions was presented. The added value of the analysis was the study of the effect of the throttle valve rotational direction on the tumble motion and the final level of turbulence at the ignition time close to the spark plug location. The focus was to determine if the throttle rotational direction was crucial for the tumble ratio and the turbulence level. The analyzed engine was a PFI 4-valves motorcycle engine. The engine geometry was formed by the intake duct and the cylinder. The CFD code was FIRE AVL code 2013.1.

During the development of an Internal Combustion Engine-based powertrain, traditional procedures for control strategies calibration and validation produce huge amount of data, that can be used to develop innovative data-driven applications, such as emission virtual sensing. One of the main criticalities is related to the data quality, that cannot be easily assessed for such a big amount of data. This work focuses on an emission modeling activity, using an enhanced Light Gradient Boosting Regressor and a dedicated data pre-processing pipeline to improve data quality. First thing, a software tool is developed to access a database containing data coming from emissions tests. The tool performs a data cleaning procedure to exclude corrupted data or invalid parts of the test. Moreover, it automatically tunes model hyperparameters, it chooses the best set of features, and it validates the procedure by comparing the estimation and the experimental measurement.