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The European Commission is going to publish the new Euro7 standard shortly, with the target of reducing the impact on pollutant emissions due to transportation systems. Besides forcing internal combustion engines to operate cleaner in a wider range of operating conditions, the incoming regulation will point out the role of On-Board Monitoring (OBM) as a key enabler to ensure limited emissions over the whole vehicle lifetime, necessarily taking into account the natural aging of involved systems and possible electronic/mechanical faults and malfunctions. In this scenario, this work aims to study the potential of data-driven approaches in detecting emission-relevant engine faults, supporting standard On-Board Diagnostics (OBD) in pinpointing faulty components, which is part of the main challenges introduced by Euro7 OBM requirements.

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.

Measurement of particle number was introduced in the Euro 5/6 light duty vehicle emissions regulation. Due to the complex nature of combustion exhaust particles, and to transportation, transformation and deposition mechanisms, such type of measurement is particularly complex, and regression analysis is commonly used for the comparison of different measurement systems. This paper compares various commercial instruments, developing a correlation analysis focused on PN (Particle Number) measurement, and isolating the factors that mainly influence each measuring method. In particular, the experimental activity has been conducted to allow critical comparisons between measurement techniques that are imposed by current regulations and instruments that can be used also on the test cell. The paper presents the main results obtained by analyzing instruments based on different physical principles, and the effects of different sampling locations and different operating parameters.

Recent engine development has been mainly driven by increased specific volumetric power and especially by fuel consumption minimization. On the other hand the stringent emission limits require a very fast cold start that can be reached only using tailored catalyst heating strategy. This kind of thermal management is widely used by engine manufactures although it leads to increased fuel consumption. This fuel penalty is usually higher for high power output engines that have a very low load during emission certification cycle leading to very low exhaust gas temperature and, consequently, the need of additional energy to increase the exhaust gas temperature is high. An alternative way to reach a fast light off minimizing fuel consumption increase is the use of an Electrical Heated Catalyst (EHC) that uses mechanical energy from the engine to generate the electrical energy to heat up the catalyst.

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 paper deals with the reduction of pollutant emissions in urban areas by considering a Zero-Emission Zone (ZEZ) in which hybrid electric vehicles (HEVs) are allowed to be driven without using the internal combustion engine, as several cities have planned to realize in the next decades. Moreover, since vehicle connectivity has spread more and more in the last years, a vehicle-to-network (V2N) communication system has been taken into account to retrieve real-time navigation data from a map service provider and thus reconstructing the so-called electronic horizon, which is a reconstruction of the future conditions of the vehicle on the road ahead. The speed profile and the road slope are used as input for an on-board predictive control strategy of a plug-in HEV (PHEV). In particular, a dedicated algorithm predicts the amount of necessary energy to complete the city event in full-electric mode, giving a state of charge (SoC) target value.

The role of numerical simulations in the development of innovative and sustainable powertrains is constantly growing thanks to their capabilities to significantly reduce the calibration efforts and to point out potential synergies among different technologies. In such a framework, this paper describes the development of a fully physical 1D-CFD engine model to support the calibration of the highly efficient spark ignition engine of the PHOENICE (PHev towards zerO EmissioNs & ultimate ICE efficiency) EU H2020 project. The availability of a reliable simulation platform is essential to effectively exploit the combination of the several features introduced to achieve the project target of 47% peak gross indicated efficiency, such as SwumbleTM in-cylinder charge motion, Miller cycle combined with high Compression Ratio (CR), lean mixture exploiting cooled low pressure Exhaust Gas Recirculation (EGR) and electrified turbocharging.

The paper presents the development and real-time implementation of a combustion control system based on optimal management of multiple spark discharge events, in order to increase combustion stability, reduce pollutant emissions and fuel consumption, and avoid partial or missing combustion cycles. The proposed approach has been developed as a cost-effective solution to several combustion-related issues that affect Gasoline Direct Injection (GDI) engines during cold start and part load operation. The problem of optimizing combustion efficiency and improving its stability during such operating modes is even more critical for high performance engines, which are designed to maximize charge efficiency especially at medium-high engine speeds.

In this paper an integrated experimental and numerical approach is applied to optimize a new 2.5l, four valve, turbocharged DI Diesel engine, developed by VM Motori. The study is focused on the EGR system. For this engine, the traditional dynamometer bench tests provided 3-D maps for brake specific fuel consumption and emissions as a function of engine speed and brake mean effective pressure. Particularly, a set of operating conditions has been considered which, according to the present European legislation, are fundamental for emissions. For these conditions, the influence of the amount of EGR has been experimentally evaluated. A computational model for the engine cycle simulation at full load has been built by using the WAVE code. The model has been set up against experiments, since an excellent agreement has been reached for all the relevant thermo-fluid-dynamic parameters. The simulation model has been used to gain a better insight on the EGR system operations.

The recent search for extremely efficient spark-ignition engines has implied a great increase of in-cylinder pressure and temperature levels, and knocking combustion mode has become one of the most relevant limiting factors. This paper reports the main results of a specific project carried out as part of a wider research activity, aimed at modelling and real-time controlling knock-induced damage on aluminum forged pistons. The paper shows how the main damage mechanisms (erosion, plastic deformation, surface roughness, hardness reduction) have been identified and isolated, and how the corresponding symptoms may be measured and quantified. The second part of the work then concentrates on understanding how knocking combustion characteristics affect the level of induced damage, and which parameters are mainly responsible for piston failure.

Pre-ignition combustions are extremely harmful and undesired, but the recent search for extremely efficient spark-ignition engines has implied a great increase of the in-cylinder pressure and temperature levels, forcing engine operation to conditions that may trigger this type of anomalous combustion much more frequently. For this reason, an accurate on-board diagnosis system is required to adopt protective measures, preventing engine damage. Ion current signal provides relevant information about the combustion process, and it results in a good compromise between cost, durability and information quality (signal to noise ratio levels). The GDI turbocharged engine used for this study was equipped with a production ion current sensing system, while in-cylinder pressure sensors were installed for research purposes, to better understand the pre-ignition phenomenon characteristics, and to support the development of an on-board diagnostic system solely based on ion current measurements.

The paper presents the implementation of a combustion diagnosis system that integrates crankshaft speed oscillations analysis with ion current signal processing, for V8 and V12 high performance engines. Ion current sensing has been introduced in the last V8 and V12 Ferrari models in order to improve combustion control by implementing ion current based closed-loop spark-advance control systems, both under knocking and non-knocking conditions (respectively based on measured knocking level, and on ion current peak position control). Another area where ion current sensing can improve the engine controller performance is related to the ability of detecting and isolating missing and partial burn combustions.

Improved numerical methods and physical models have been applied to droplet collision modeling. Contrary to the common practice of using the fixed gas phase mesh to calculate droplet collision incidence, a new algorithm generates a collision mesh independent of the gas phase mesh at each time step. By partitioning collision cells according to the number density of parcels, the algorithm is capable of achieving higher spatial resolution than that of the gas phase mesh. At the same time this method maintains an adequate statistical sample of parcels in the collision cells to ensure statistically accurate results. The continual random rotation of the mesh ensures that parcels that are near each other will, on average, be in the same collision cell. This produces the physically reasonable result that parcels in close proximity should have the opportunity to collide. Another important advantage of the algorithm is that it can be applied to any orifice configuration.

The burden of creating meshes increases the cost of Computational Fluid Dynamics (CFD) and slows the rate at which new engine geometries can be investigated. Internal Combustion Engines (ICEs) with moving valves and piston present a special challenge, often requiring numerous different target meshes or case-specific codes for adapting the mesh. The goal of the present paper is to facilitate remeshing by calculating vertex motion, in parallel, for hybrid tetrahedral and hexahedral meshes. The calculated vertex motion is intended to maintain good mesh quality and reduce the need for interpolation to a new mesh. The demonstrated approach uses Laplacian-based smoothing for hexahedral cells and optimization-based smoothing for tetrahedral cells. Further, planar and cylindrical surfaces in the engine geometry are automatically recognized. As the engine volume changes shape, vertices may slide along the planar and cylindrical surfaces.

This paper shows the influence of different battery charge management strategies on the fuel economy of a hybrid parallel axle-split vehicle in a real driving scenario, for a vehicle control system that has the additional possibility to split the torque between front and rear axles. The first section regards the validation of a self-developed Model in the Loop (MiL) environment of a P1-P4 plug-in hybrid electric car, using experimental data of a New European Driving Cycle test. In its original version, which is implemented on-board the vehicle, the energy management supervisor implements a heuristic, or rule-based, Energy Management Strategy (EMS). During this project, a different EMS has been developed, consisting of a sub-optimal control scheme called Equivalent Consumption Minimization Strategy (ECMS), explained in detail in the second section.

Sac-type nozzles, which are often used in gasoline direct injection (DI), induce asymmetry to the spray. The drill angle, that is, the angle between the axis of the nozzle and the axis of the injector, is one of the key causes of the asymmetric flow. Despite its significance, the influence of the drill angle on spray is poorly understood. In the current work, a parametric study has been carried out using single-hole sac-type nozzles by varying the drill angle. The drill angle was varied from a value of 0° to 45° in steps of 15°. Apart from the geometric variation, the ambient pressure and the fuel temperature were varied to achieve flash-boiling and non-flash-boiling spray conditions. Simulations were carried out using an in-house computational fluid dynamics (CFD) solver that accounts for thermodynamic non-equilibrium coupled with a liquid-gas interface-area-density transport model to account for primary atomization of the fuel.

The paper presents possible solutions for developing fast and reliable turbocharger models, to be used mainly for control applications. This issue is of particular interest today for SI engines since, due to the search for consistent CO2 reduction, extreme downsizing concepts require highly boosted air charge solutions to compensate for power and torque de-rating. For engines presenting at least four in-line cylinders, twin-entry turbines offer the ability of maximizing the overall energy conversion efficiency, and therefore such solutions are actually widely adopted. This work presents a critical review of the most promising (and recent) modeling approaches for automotive turbochargers, highlighting the main open issues especially in the field of turbine models, and proposing possible improvements.