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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.

The challenge of industrial carbon footprint reduction is led by the engine manufacturers that are developing new technologies and fuels to lower CO2 emissions. Although the deployment of relevant investments for the development of battery electric vehicles, diesel, and gasoline cars are still widely used, especially for their longer operating range, faster refueling, and lower cost. For this reason, more efficient traditional internal combustion engines can guide the transition towards new propulsion systems. In this document, the innovative piston damage and exhaust gas temperature models previously developed by the authors are reversed and coupled to manage the combustion process, increasing the overall energy conversion efficiency. The instantaneous piston erosion and the exhaust gas temperature at the turbine inlet are evaluated according to the models’ estimation which manages both the spark advance, and the target lambda.

Nowadays, in the perspective of a full electric automotive scenario, internal combustion engines can still play a central role in the fulfilment of different needs if the efficiency will be improved, and the tailpipe emission will be further limited. Gasoline Compression Ignition engines can offer a favourable balance between NOx, particulate, operating range. Stable operations are ensured by ultra-high gasoline injection pressure and tailored injection patterns in order to design the most proper local fuel distribution. In this context, engine simulations by means of CFD codes can provide insights on the design of the injection parameters, and emphasis must be placed on the capture of spray-wall impingement behaviour under those non-conventional conditions. This paper aims to analyse the spray-wall impingement behaviour of ultra-high gasoline spray using a combined experimental-CFD approach.

The need to reduce carbon dioxide emissions from motor vehicles pushes the European Union towards drastic choices on future mobility. Despite this, the engines of the “future” have not yet been defined: the choice of engine type will undoubtedly depend on the type of application (journey length, availability of recharging/refueling facilities), practical availability of alternative fuels, and electricity to recharge the batteries. The electrification of vehicles (passenger and transportation cars) may be unsuitable for several aspects: the gravimetric energy density could be too low if the vehicle has to be lightweight, must achieve a high degree of autonomy, or needs a very short refueling time.

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 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 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.

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.

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.

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.

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 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.

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 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.

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.

In modern turbocharged downsized GDI engines the achievement of maximum thermal efficiency is precluded by the occurrence of knock. In-cylinder pressure sensors give the best performance in terms of abnormal combustion detection, but they are affected by long term reliability issues and still constitute a considerable part of the entire engine management system cost. To overcome these problems, knock control strategies based on engine block vibrations or ionization current signals have been developed and are widely used in production control units. Furthermore, previous works have shown that engine sound emissions can be real-time processed to provide the engine management system with control-related information such as turbocharger rotational speed and knock intensity, demonstrating the possibility of using a multi-function device to replace several sensors.

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.