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The in-cylinder direct injection of fuels can be a further step towards cleaner and more efficient internal combustion engines. However, the injector design and its characterization, both experimental and from numerical simulation require accurate diagnostics and efficient models. This work aims to simulate the complex behavior of the gaseous and liquid jets through an outwardly opening injector characterized by optical diagnostics using a one-dimensional model without using three dimensional models. The behavior of the jet from an outwardly opening injector changes according to the type of fuel. In the case of the gas, the experimental investigations put in evidence three main jet regions: 1) near-field region where the jet shows a complex gas-dynamic structure; 2) transition region characterized by intense mixing; 3) far-field region characterized by a fully developed subsonic turbulent jet.

The urban mobility electrification has been proposed as the main solution to the vehicle emission issues in the next years. However, internal combustion engines have still great potential to decarbonize the transport sector through the use of low/zero-carbon fuels. Alcohols such us methanol, have long been considered attractive alternative fuels for spark ignition engines. They have properties similar to those of gasoline, are easy to transport and store. Recently, great attention has been devoted to gaseous fuels that can be used in existing engine after minor modification allowing to drastically reduce the pollutant emissions. In this regard, this study tries to provide an overview on the use of alternative fuels, both liquid and gaseous in spark ignition engines, highlighting the benefits as well as the criticalities. The investigation was carried out on a small displacement spark ignition engine capable to operate both in port fuel and direct injection mode.

In the global quest for preventing fossil fuel depletion and reducing air pollution, hybridization plays a fundamental role to achieve cleaner and more fuel-efficient automotive propulsion systems. While hybrid powertrains offer many opportunities, they also present new developmental challenges. Due to the many variants and possible architectures, development issues, such as the definition of powertrain concepts and the optimization of operating strategies, are becoming more and more important. The paper presents model-based fuel economy analyses of different hybrid vehicle configurations, depending on the position of the electric motor generator (EMG). The analyses are intended to support the design of powertrain architecture and the components sizing, depending on the driving scenario, with the aim of reducing fuel consumption and CO2 emissions.

In the last years the automotive industry has been involved in the development and implementation of CO2 reducing concepts such as the engines downsizing, stop/start systems as well as more costly full hybrid solutions and, more recently, waste heat recovery technologies. These latter include ThermoElectric Generator (TEG), Rankine cycle and Electric Turbo Compound (ETC) that have been practically implemented on few heavy-duty application but have not been proved yet as effective and affordable solutions for the automotive industry. The paper deals with the analysis of opportunities and challenges of the Electric Turbo Compound for automotive light-duty engines. In the ETC concept the turbine-compressor shaft is connected to an electric machine, which can work either as generator or motor. In the former case the power can satisfy the vehicle electrical demand to drive the auxiliaries or stored in the batteries.

A computer code oriented to S.I. engine control and powertrain simulation is presented. The model, developed in Matlab-Simulink® environment, predicts engine and driveline states, taking into account the dynamics of air and fuel flows into the intake manifold and the transient response of crankshaft, transmission gearing and vehicle. The model, derived from the code O.D.E.C.S. for the optimal design of engine control strategies now in use at Magneti Marelli, is suitable both for simulation analysis and to achieve optimal engine control strategies for minimum consumption with constraints on exhaust emissions and driveability via mathematical programming techniques. The model is structured as an object oriented modular framework and has been tested for simulating powertrain system and control performance with respect to any given transient and control strategy.

A computer code oriented to S.I. engine control and powertrain simulation is presented. The model predicts engine and driveline states, taking into account the dynamics of air and fuel flows into the intake manifold and the transient response of crankshaft, clutch, transmission gearing and vehicle. The whole model is integrated in the code O.D.E.C.S., now in use at Magneti Marelli, and is based on a hierarchical structure composed of different classes of models, ranging from black-box Neural Network to grey-box mean value models. By adopting the proposed approach, a satisfactory accuracy is achieved with limited computational demand, which makes the model suitable for the optimization of engine control strategies. Furthermore, in order to simulate the driver behavior during the assigned vehicle mission profile, two drive controllers have been implemented for throttle and brakes actuation, based on classical PID and fuzzy-logic theory.

Nowadays requirements towards a reduction in fuel consumption and pollutant emissions of Internal Combustion Engines (ICE) keep on pushing manufacturers to improve engines performance through the enhancement of existing subsystems (e.g.: electronic fuel injection, air systems) and the introduction of specific devices (e.g.: exhaust gas recirculation systems, SCR, …). Modern systems require a combined design and application of different after-treatment devices. Mathematical models are useful tools to investigate the complexity of different system layouts, to design and to validate (HIL/SIL testing) control strategies for the after-treatment management. This study presents a mean value model of an exhaust system with SCR; it has been coupled with a common rail diesel engine combustion black box model (Neural Network based). So, dedicated models for exhaust pipes, oxidation catalyst, diesel particulate filter and selective catalytic converter are developed.

Due to the greater need to reduce exhaust emissions of harmful gases (GHG, NOx, PM, etc.), to promote the decarbonisation process and to overcome the drawbacks of electric vehicles (low range, high cost, impact of electricity production on CO2 emissions…), the hybrid-electric vehicles are still considered as the more feasible path through sustainable mobility. However, one of the main tasks to be accomplished to get maximum benefit from hybrid-electric powertrain is the management of the energy flows between the different power sources, namely internal combustion engine, electric machine(s) and battery pack. In this paper a methodology for the experimental testing of HEVs energy management strategies at the engine test bed is presented. The experimental set-up consists in an eddy-current dyno and a light-duty common-rail Diesel engine.

The paper describes suited methodologies for developing Recurrent Neural Networks (RNN) aimed at estimating NOx emissions at the exhaust of automotive Diesel engines. The proposed methodologies particularly aim at meeting the conflicting needs of feasible on-board implementation of advanced virtual sensors, such as neural network, and satisfactory prediction accuracy. Suited identification procedures and experimental tests were developed to improve RNN precision and generalization in predicting engine NOx emissions during transient operation. NOx measurements were accomplished by a fast response analyzer on a production automotive Diesel engine at the test bench. Proper post-processing of available experiments was performed to provide the identification procedure with the most exhaustive information content. The comparison between experimental results and predicted NOx values on several engine transients, exhibits high level of accuracy.

Regarding automotive applications, Internal Combustion Engines (ICE) have become very complex plants to comply with present and future requirements in reduction of fuel consumption, pollutant emissions and performance improvement. As a consequence, the development of engine control and diagnostic system is a key aspect in the powertrain design. Mathematical models are useful tools in this direction, with applications that range from the definition of optimised management systems, to Hardware- and Software-in-the-Loop testing (HiL and SiL) and to modelbased control strategies. To this extent an original library has been developed by the authors for the simulation of last generation automotive engines. Library blocks were used to assembly a sub-model of the typical intake and exhaust system of a turbocharged engine (with VGT, intercooler, EGR circuit with cooler and throttle).

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.

Internal combustion engines performance greatly depends on the air-fuel mixture formation and combustion processes. In gasoline direct injection (GDI) engines, in particular, the impact of the liquid spray on the piston or cylinder walls is a key factor, especially if mixture formation occurs under the so-called wall-guided mode. Impact causes droplets rebound and/or deposition of a liquid film (wallfilm). After being rebounded, droplets undergo what is called secondary atomization. The wallfilm may remain of no negligible size, so that fuel vapor rich zones form around it leading to so-called pool-flames (flames placed in the piston pit), hence to unburned hydrocarbons (HC) and particulate matter (PM) formation. A basic study of the spray-wall interaction is here performed by directing a multi-hole GDI spray against a real shape engine piston, possibly heated, under standard air conditions.

The emissions limits of CO2 for vehicles are becoming more stringent with the aim of reducing greenhouse gas emissions and improve fuel economy. The New European Driving Cycle (NEDC) is adopted to measure emissions for all new internal combustion engines in the European Union, and it is performed on cold vehicle, starting at a temperature of 22°C ± 2°C. Consequently, the cold-start efficiency of internal combustion engine is becoming of predominant interest. Since at cold start the lubricant oil viscosity is higher than at the target operating temperature, the consequently higher energy losses due to increased frictions can substantially affect the emission cycle results in terms of fuel consumption and CO2 emissions. A suitable thermal management system, such as an exhaust-to-oil heat exchanger, could help to raise the oil temperature more quickly.

An integrated system of phenomenological models is applied in conjunction with identification techniques to simulate SI engine performance and emissions. In the framework of a hierarchical model architecture, the model structure provides the steady state engine data required for the design and validation of synthetic engine models. This approach allows limiting the recourse to the experimental data and speeds up the engine control strategies prototyping. The model structure is composed of a multi-zone thermodynamic engine model linked to a 1-D commercial fluid-dynamic model for intake and exhaust gas flow and to a physical model for NOx exhaust emissions. In order to improve model accuracy and generalization, an identification methodology is applied to estimate the optimal parameters for the turbulent combustion model. Due to the built-in physical content, the proposed methodology requires a relatively limited amount of experimental data for characterizing the under-study engine.

The use of methane as supplement to liquid fuel is one of the solution proposed for the reduction of the internal combustion engine pollutant emissions. Its intrinsic properties as the high knocking resistance and the low carbon content makes methane the most promising clean fuel. The dual fuel combustion mode allows improving the methane combustion acting mainly on the methane slow burning velocity and allowing lean burn combustion mode. An experimental investigation was carried out to study the methane-gasoline dual fuel combustion. Methane was injected in combustion chamber (DI fuel) while gasoline was injected in the intake manifold (PFI fuel). The measurements were carried out in an optically accessible small single-cylinder four-stroke engine. It was equipped with the cylinder head of a commercial 250 cc motorcycles engine representative of the most popular two-wheel vehicles in Europe.

This paper reports on the analysis of flame kinematics and cycle variation in port fuel injection (PFI) spark ignition (SI) engine. The engine was equipped with a four-valve head and with an external boost device. Different operating conditions were considered. Cycle-resolved digital imaging was used to investigate flame motion and the effects of an abnormal combustion due to the firing of fuel deposition near the intake valves and on the piston surface. Various algorithms are applied to the acquired images. Coefficients of Proper Orthogonal Decomposition (POD) were computed and used for a statistical analysis of cycle variability. The advantage is that the analysis can be run on a small number of scalar coefficients rather than on the full data set of pixel valued luminosity.

The use of lean or ultra-lean ratios is an efficient and proven strategy to reduce fuel consumption and pollutant emissions. However, the lower fuel concentration in the cylinder hinders the mixture ignition, requiring greater energy to start the combustion. The prechamber is an efficient method to provide high energy favoring the ignition process. It presents the potential to reduce the emission levels and the fuel consumption, operating with lean burn mixtures and expressive combustion stability. In this paper the analysis of the combustion process of SI engines equipped with an innovative architecture and operating in different injection modes was described. In particular, the effect of the prechamber ignition on the engine stability and the efficiency was investigated in stoichiometric and lean-burn operation conditions. The activity was carried out in two parts.

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.

Knock control systems based on engine block vibrations analysis are widely adopted in passenger car engines, but such approach shows its main limits at high engine speeds, since knock intensity measurement becomes less reliable due to the increased background mechanical noise. For small two wheelers engines, knock has not been historically considered a crucial issue, mainly due to small-sized combustion chambers and mixture enrichment. Due to more stringent emission regulations and in search of reduced CO2 emissions, an effective on-board knock controller acquires today greater importance also for motorcycle applications, since it could protect the engine when different fuel types are used, and it could significantly reduce fuel consumption (by avoiding lambda enrichment and/or allowing higher compression ratios to be adopted). These types of engines typically work at high rotational speeds and the reduced signal to noise ratio makes knock onset difficult to identify.

Main aim of this paper was to exploit the well-known Willans line method in a twofold manner: indeed, beyond the usual identification of Willans line parameters to enable internal combustion engine scaling, it is also proposed to infer further information from identified parameters and correlations, particularly aiming at characterizing mechanical and frictional losses of different engine technologies. The above objectives were pursued relying on extended experimental performance data, which were gathered on different engine families, including turbo-charged Diesel and naturally aspirated gasoline engines. The matching between Willans line scaled performance and experimental ones was extensively tested, thus allowing to reliably proceed to the subsequent objective of characterizing mechanical losses on the basis of identified Willans parameters.