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In this paper three-dimensional Large Eddy Simulations (i.e., LES) by using a PLIC-VOF method have been adopted to investigate the atomization process of round liquid jets issuing from automotive multi-hole injector-like nozzles. LES method is used to compute directly the effect of the large flow structure, being the smallest one modelled. A mesh having a cell size of 4 μm was used in order to derive a statistics of the detached liquid structures, i.e. droplets and ligaments. The latter have been identified by using an algorithm coded by authors. Cavitation modeling has not been included in the present computations. Two different mean injection nozzle flow velocities of 50 m/s and 270 m/s, corresponding to two mean nozzle flow Reynolds numbers of 1600 and 8700, respectively, have been considered in the calculations as representative of laminar and turbulent nozzle flow conditions.

Nowadays, an automotive DI Diesel engine is demanded to provide an adequate power output together with limit-complying NOx and soot emissions so that the development of a specific combustion concept is the result of a trade-off between conflicting objectives. In other words, the development of a low-emission DI diesel combustion concept could be mathematically represented as a multi-objective optimization problem. In recent years, genetic algorithm and CFD simulations were successfully applied to this kind of problem. However, combining GA optimization with actual CFD-3D combustion simulations can be too onerous since a large number of simulations is usually required, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes.

Nowadays numerical simulations play a major role in the development of future sustainable powertrain thanks to their capability of investigating a wide spectrum of innovative technologies with times and costs significantly lower than a campaign of experimental tests. In such a framework, this paper aims to assess the predictive capabilities of an 1D-CFD engine model developed to support the design and the calibration of the innovative highly efficient spark ignition engine of the PHOENICE (PHev towards zerO EmissioNs & ultimate ICE efficiency) EU H2020 project. As a matter of fact, the availability of a reliable simulation platform is crucial to achieve the project target of 47% peak indicating efficiency, by synergistically exploiting the combination of innovative in-cylinder charge motion, Miller cycle with high compression ratio, lean mixture with cooled Exhaust Gas Recirculation (EGR) and electrified turbocharger.

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.

In the field of passenger car engines, recent research advances have proven the effectiveness of downsized, turbocharged and direct injection concepts, applied to gasoline combustion systems, to reduce the overall fuel consumption while respecting particularly stringent exhaust emissions limits. Knock and turbocharger control are two of the most critical factors that influence the achievement of maximum efficiency and satisfactory drivability, for this new generation of engines. The sound emitted from an engine encloses many information related to its operating condition. In particular, the turbocharger whistle and the knock clink are unmistakable sounds. This paper presents the development of real-time control functions, based on direct measurement of the engine acoustic emission, captured by an innovative and low cost acoustic sensor, implemented on a platform suitable for on-board application.

The flight simulation of airships and hot air balloons usually considers the envelope geometry as a fixed shape, whose volume is eventually reduced by ballonets. However, the dynamic pressure or helium leaks in airships, and the release of air to allow descent in hot air balloons can significantly change the shape of the envelope leading to potential dangerous situations. In fact, in case of semi-rigid and non-rigid airships a reduction in envelope internal pressure can reduce the envelope bending stiffness leading to the loss of the typical axial-symmetric shape. For hot air balloons thing goes even worse since the lost of internal pressure can lead to the collapsing of the balloon shape to a sort of vertically stretched geometry (similar to a torch) which is not able to sustain the attached basket and its payload.

A detailed analysis of knocking events can help improving engine performance and diagnosis strategies. The paper aim is a better understanding of the phenomena involved in knocking combustions through the combination of CFD and signals analysis tools. CFD simulations have been used in order to reproduce knock effect on the in-cylinder pressure trace. In fact, the in-cylinder pressure signal holds information about waves propagation and heat losses: for the sake of the diagnosis it is important to relate knock severity to knock indexes values. For this purpose, a CFD model has been implemented, able to predict the combustion evolution with respect to Spark Advance, from non-knocking up to heavy knocking conditions. The CFD model validation phase is crucial for a correct representation of both regular and knocking combustions: the operation has been carried out by means of an accurate statistical analysis of experimental in-cylinder pressure data.

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.

The first part of the paper gives an overview of the results obtained with European GDI-powered vehicles launched on the market. Thereafter, a discussion of in-vehicle limitations due to the exhaust gas after-treatment system requirements is given. The paper continues with a description of the current development status of European lean stratified direct injection system layouts. A detailed presentation is made of the mixture preparation system key components, basic control algorithms and the necessary new high-level experimental and analytical development tools. Particularly the topic of the multi-purpose use of 3-D numerical simulation is addressed both in the development and the engine control strategy calibration phases. The development of a small 1.6 liter lean stratified engine project is taken as example to demonstrate the dual application capability of the 3D simulation tool.

Metallic foams or sponges are materials with a cell structure suitable for many industrial applications, such as reformers, heat catalytic converters, etc. The success of these materials is due to the combination of various characteristics such as mechanical strength, low density, high specific surface, good thermal exchange properties, low flow resistance and sound absorption. Different materials and manufacturing processes produce different type of structure and properties for various applications. In this work a genetic algorithm has been developed and applied to support the design of catalytic devices. In particular, two substrates were considered, namely the traditional honeycomb and an alternative open-cell foam type. CFD simulations of pressure losses and literature based correlations for the heat and mass transfer were used to support the genetic algorithm in finding the best compromise between flow resistance and pollutant abatement.

Unmanned Aerial Vehicles (UAVs) provide the ability to perform a variety of experimental tests of systems and unproven research technologies, including new autopilot systems and obstacle avoidance capabilities, without risking the lives of human pilots. This paper describes the activities of design, optimization, and flight operations of a UAV conceived at Clarkson University (USA) and equipped to perform wind speed measurements to support wind farmsite planning. The UAV design has been assisted and validated by the use of an automatic virtual environment for the assisted design of civil UAVs. This tool can be used as a “computing machine” for civil UAVs. The operator inputs the mission profile and other generic parameters and data about performance, aerodynamics, and weight breakdown are extracted. A mathematical model of the UAV for flight simulation and its dynamic computations, along with automatic drawing is also produced.

Modern turbo-charged downsized engines reach high values of specific power, causing a significant increase of the exhaust gas temperature. Such parameter plays a key role in the overall powertrain environmental impact because it strongly affects both the catalyst efficiency and the turbine durability. In fact, common techniques to properly manage the turbine inlet gas temperature are based on mixture enrichment, which causes both a steep increase in specific fuel consumption and a decrease of catalyst efficiency. At the test bench, exhaust gas temperature is typically measured using thermocouples that are not available for on-board application, and such information is processed to calibrate open-loop look-up-tables. A real-time, reliable, and accurate exhaust temperature model would then represent a strategic tool for improving the performance of the engine control system.

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.

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.

People make judgements of the sound produced by vehicles in a variety of situations and contexts. The most common type of assessment is an overall judgement of sound quality like pleasantness and sportiveness. From the car manufacturer''s point of view it is important to note that subjective judgements of sound influence the buyer''s opinion of the performance and value of the vehicle. Consequently, there is a need to quantify the subjective perception of the sound quality associated with a vehicle. This paper presents a study of the sound quality of vehicle exhaust noise based on the correlation between the subjective perception associated with this type of sound and measured psycho-acoustic parameters such as loudness, sharpness and roughness. The tailpipe noise of a selection of representative vehicles was recorded using an artificial head. A subjective evaluation of these sound recordings was made by a jury using standard relative techniques.

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.

Experimental measurements and numerical computations were made to characterize a spray generated by a high-pressure swirl injector. The Phase Doppler technique was applied to get information on droplet sizes (d10) and axial velocities at defined distances from the injector tip. Global spray visualization was also made. Computations were carried out using a modified version of KIVA 3V. In particular, the break-up length of the sheet and its dimension were computed from a semi-empirical correlation related to the wave instability theory suggested by Dombrowski, including the modifications introduced by Han and Reitz. Two different approaches were used to describe the initial spray conditions. According to the first, discrete particles with a characteristic size equal to the thickness of the sheet are injected. The second approach assumes, that the particles having a SMD computed by a semi-empirical correlation are injected according to a statistical distribution.

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.

The most recent European regulations for two- and three-wheelers (Euro 5) are imposing an enhanced combustion control in motorcycle engines to respect tighter emission limits, and Air-Fuel Ratio (AFR) closed-loop control has become a key function of the engine management system also for this type of applications. In a multi-cylinder engine, typically only one oxygen sensor is installed on each bank, so that the mean AFR of two or more cylinders rather than the single cylinder one is actually controlled. The installation of one sensor per cylinder is normally avoided due to cost, layout and reliability issues. In the last years, several studies were presented to demonstrate the feasibility of an individual AFR controller based on a single sensor. These solutions are based on the mathematical modelling of the engine air path dynamics, or on the frequency analysis of the lambda probe signal.

The water injection is one of the recognized technologies capable of helping the future engines to work at full load conditions with stoichiometric mixture. In the present work, a methodology for the CFD simulation of reacting flow conditions using AVL Fire code v. 2020 is applied for the assessment of the water injection effect on modern GDI engines. Both Port Water Injection and Direct Water Injection have been tested for the same baseline engine configuration under reacting flow conditions. The ECFM-3Z model adopted for combustion and knock simulations have been performed by adopting correlations for laminar flame speed, flame thickness and ignition delay times prediction, to consider the modified chemical behavior of the mixture due to the added water vapor.