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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.

Internal combustion engines are the primary transportation mover for today society and they will likely continue to be for decades to come. Hybridization is the most common solution to reduce the petrol-fuels consumption and to respect the new raw emission limits. The gasoline engines designed for running together with an electric motor need to have a very high thermal efficiency because they must work at high loads, where engine thermal efficiency is close to the maximum one. Therefore, the technical solutions bringing to thermal efficiency enhancement were adopted on HVs (Hybrid Vehicles) prior to conventional vehicles. In these days, these solutions are going to be adopted on conventional vehicles too. The purpose of this work was to trace development guidelines useful for engine designers, based on the target power and focused on the maximization of the engine thermal efficiency, following the engine rightsizing concept.

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.

Compression-ignited engines are still considered the most efficient and reliable technology for automotive applications. However, current and future emission regulations, which severely limit the production of NOx, particulate matter and CO2, hinder the use of diesel-like fuels. As a matter of fact, the spontaneous ignition of directly-injected Diesel leads to a combustion process that is heterogeneous by nature, therefore characterized by the simultaneous production of particulate matter and NOx. In this scenario, several innovative combustion techniques have been investigated over the past years, the goal being to benefit from the high thermal efficiency of compression-ignited engines, which results primarily from high Compression Ratio and lean and unthrottled operation, while simultaneously mitigating the amount of pollutant emissions.

The implementation of increasingly stricter regulations on CO2 emissions by the European Community is pushing the automotive industry towards a radical change. In a rush to electrify their model ranges, global carmakers are investing heavily on developing new electrified powertrains. Within this context, this work focuses on the analysis of electric axles drives (eAxles) for a BEV (battery electric vehicle) sport car, with the aim to develop an analytical tool useful to perform predictive analysis in the concept design phase. Through a parametric definition of the procedure, the tool is able to “adapt” to any drivetrain layout analysed. The tool actually allows to enter more than 100 input values including lubrication conditions (oil viscosity and operating temperature), gears (number, macrogeometry, mesh), bearings (number, type, geometry, mounting layout, angle mesh), shafts, oil seals, external layout and external fluid conditions.

Today, the contribution of the transportation sector on greenhouse gases is evident. The fast consumption of fossil fuels and its impact on the environment have given a strong impetus to the development of vehicles with better fuel economy. Hybrid electric vehicles fit into this context with different targets, starting from the reduction of emissions and fuel consumption, but also for performance and comfort enhancement. Lamborghini has recently invested in the development of a hybrid super sport car, due to performance and comfort reasons. Aventador series gearbox is an Independent Shift Rod gearbox with a single clutch and during gear shifts, as all the single clutch gearbox do, it generates a torque gap. To avoid the additional weight of a Dual Clutch Transmission, a 48V Electric Motor has been connected to the wheels, in a P3 configuration, to fill the torque gap, and to habilitate regenerative braking and electric boost functions.

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 LES hybridization of standard two-equation turbulence closures is often achieved leaving formally unchanged the turbulent viscosity expression in the URANS and LES modes of operation. Although generally convenient in terms of ease of implementation, this choice leaves some theoretical consistency questions unanswered, the most obvious being the actual meaning of the two transported turbulent scalars and their exact role in the modeled viscosity build-up. A possible remedy to this is represented by the simultaneous modification of one or both the turbulent transport equations and of the turbulent viscosity formula, for which a standard LES behavior is enforced whenever needed. The present work compares a conventional DES-based hybrid model with a consistency-enforcing modified variant for turbulent fuel spray simulation. In our case, LES-mode consistency is accomplished by excluding the second turbulent scalar quantity from the viscosity calculation.

Hybrid URANS/LES turbulence modeling is rapidly emerging as a valuable complement to standard LES for full-engine multi-cycle simulation. Among the available approaches, zonal hybrids are potentially attractive due to the possibility of clearly identify URANS and LES zones, eventually introducing further zone types with dynamically switching behavior. The present work aims at evaluating the impact of different zonal configurations on the simulated flow statistics using the well-assessed TCC-III experimental engine setup. More specifically, different methods (URANS, LES or seamless DES) are applied inside the cylinder volume, as well as into the intake/exhaust ports and plenums. For each of the five tested configurations, in-cylinder flow features are compared against the reference TCC-III experimental measurements, in terms of velocity field statistics and quality indices.

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.

Turbulence modeling for fuel spray simulation plays a prominent role in the understanding of the flow behavior in Internal Combustion Engines (ICEs). Currently, a lot of research work is actively spent on Large Eddy Simulation (LES) turbulence modeling as a replacement option of standard Reynolds averaged approaches in the Eulerian-Lagrangian spray modeling framework, due to its capability to accurately describe flow-induced spray variability and to the lower dependence of the results on the specific turbulence model and/or modeling coefficients. The introduction of LES poses, however, additional questions related to the implementation/adaptation of spray-related turbulence sources and to the rise of conflicting numerics and grid requirements between the Lagrangian and Eulerian parts of the simulated flow.

To meet the requirements in relation to pollutants, CO2-emissions, performances, comfort and costs for 2025 timeframe, many technology options for the powertrain, that plays a key role in the vehicle, are possible. Beside the central aspect of reducing standard cycle consumption levels and emissions, consumer demands are also growing with respect to comfort and functionality. In addition, there is also the challenge of finding cost efficient ways of integrating technologies into a broad range of vehicles with different levels of hybridization. High degrees of electrification simultaneously provide opportunities to reduce the technology content of the internal combustion engines (ICE), resulting in a cost balancing compromise between combustion engine and hybrid technology. The design and optimization of powertrain topologies, functionalities, and components require a complex development process.

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.

The interest in Unsteady Reynolds-Averaged Navier-Stokes (URANS)/Large Eddy Simulation (LES) hybrids, for the simulation of turbulent flows in Internal Combustion Engines (ICE), is consistently growing. An increasing number of applications can be found in the specialized literature for the past few years, including both seamless and zonal hybrid formulations. Following this trend, we have already developed a Detached Eddy Simulation (DES)-based zonal modeling technique, which was found to have adequate scale-resolving capabilities in several engine-like reference tests. In the present article we further extend our study by evaluating the effects of the underlying turbulence model and of the grid quality/morphology on the scale-resolved part of the flow. For that purpose, we consider DES formulations based on an enhanced version of the k-g URANS model and on the URANS form of the popular RNG k-ε model.

Gasoline Direct Injection (GDI) is a leading technology for Spark Ignition (SI) engines: control of the injection process is a key to design the engine properly. The aim of this paper is a numerical investigation of the gasoline injection and the resulting development of plumes from an 8-hole Spray G injector into a quiescent chamber. A LES approach has been used to represent with high accuracy the mixing process between the injected fuel and the surrounding mixture. A Lagrangian approach is employed to model the liquid spray. The fuel, considered as a surrogate of gasoline, is the iso-octane which is injected into the high-pressure vessel filled with nitrogen. The numerical results have been compared against experimental data realized in the optical chamber. To reveal the geometry of plumes two different imaging techniques have been used in a quasi-simultaneous mode: Mie-scattering for the liquid phase and schlieren for the gaseous one.

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 continuous development of modern Internal Combustion Engine (ICE) management systems is mainly aimed at combustion control improvement. Nowadays, performing an efficient combustion control is crucial for drivability improvement, efficiency increase and pollutant emissions reduction. These aspects are even more crucial when innovative combustions (such as LTC or RCCI) are performed, due to the high instability and the high sensitivity with respect to the injection parameters that are associated to this kind of combustion. Aging of all the components involved in the mixture preparation and combustion processes is another aspect particularly challenging, since not all the calibrations developed in the setup phase of a combustion control system may still be valid during engine life.

The primary target of the internal combustion engines design is to lower the fuel consumption and to enhance the combustion process quality, in order to reduce the raw emission levels without performances penalty. In this scenario the direct injection system plays a key role for both diesel and gasoline engines. The spray dynamic behaviour is crucial in defining the global and the local air index of the mixture, which in turns affects the combustion process development. At the same time it is widely recognized that the spray formation is influenced by numerous parameters, among which also the cavitation process inside every single hole of the injector nozzle. The proper prediction of the cavitation development inside the injector nozzle holes is crucial in predicting the liquid jet emerging from them.