Hydrogen is the energy vector that will lead us toward a more sustainable future. It could be the fuel of both fuel cells and internal combustion engines. Internal combustion engines are today the only motors characterized by high reliability, duration and specific power, and low cost per power unit. The most immediate solution for the near future could be the application of hydrogen as a fuel in modern internal combustion engines. This solution has advantages and disadvantages: specific physical, chemical and operational properties of hydrogen require attention. Hydrogen is the only fuel that could potentially produce no carbon, carbon monoxide and carbon dioxide emissions. It also allows high engine efficiency and low nitrogen oxide emissions. Hydrogen has wide flammability limits and a high flame propagation rate, which provide a stable combustion process for lean and very lean mixtures. Near the stoichiometric air–fuel ratio, hydrogen-fueled engines exhibit abnormal combustions (backfire, pre-ignition, detonation), the suppression of which has proven to be quite challenging. Pre-ignition due to hot spots in or around the spark plug can be avoided by adopting a cooled or unconventional ignition system (such as corona discharge): the latter also ensures the ignition of highly diluted hydrogen–air mixtures. It is worth noting that to correctly reproduce the hydrogen ignition and combustion processes in an ICE with the risks related to abnormal combustion, 3D CFD simulations can be of great help. It is necessary to model the injection process correctly, and then the formation of the mixture, and therefore, the combustion process. It is very complex to model hydrogen gas injection due to the high velocity of the gas in such jets. Experimental tests on hydrogen gas injection are many but never conclusive. It is necessary to have a deep knowledge of the gas injection phenomenon to correctly design the right injector for a specific engine. Furthermore, correlations are needed in the CFD code to predict the laminar flame velocity of hydrogen–air mixtures and the autoignition time. In the literature, experimental data are scarce on air–hydrogen mixtures, particularly for engine-type conditions, because they are complicated by flame instability at pressures similar to those of an engine. The flame velocity exhibits a non-monotonous behavior with respect to the equivalence ratio, increases with a higher unburnt gas temperature and decreases at high pressures. This makes it difficult to develop the correlation required for robust and predictive CFD models. In this work, the authors briefly describe the research path and the main challenges listed above.

DI Diesel engine are widely used both for industrial and automotive applications due to their durability and fuel economy. Nonethe- less, increasing environmental concerns force that type of engine to comply with increasingly demanding emission limits, so that, it has become mandatory to develop a robust design methodology of the DI Diesel combustion system focused on reduction of soot and NOx simultaneously while maintaining a reasonable fuel economy. In recent years, genetic algorithms and CFD three-dimensional combustion simulations have been successfully applied to that kind of problem. However, combining GAs op- timization with actual CFD three-dimensional combustion simulations can be too onerous since a large number of calculations is usually needed for the genetic algorithm to converge, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes. In order to make the optimization process less time-consuming, CFD simulations can be more conveniently used to generate a training set for the learning process of an artifical neural network which, once correctly trained, can be used to forecast the engine outputs as a function of the design parameters during a GA optimization performing a so-called virtual optimization.In the current paper, a numerical methodology for the multi-objective virtual optimization of the combustion of an automotive DI Diesel engine, which relies on artificial neural networks and genetic algorithms, was developed

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. Many experimental campaigns have been performed while only few researches have deeply investigated the effect of the water injection on the air-fuel mixture under engine operating conditions. Since the experiments perform like a black box and they might hide some important phenomena, CFD numerical investigation steps are mandatory in order to provide a wider and deeper overview on the thermo-fluid dynamics characteristics involved in engine operations with water injection. This paper aims to provide an insight into those processes by using a CFD numerical approach to investigate the effect of the water injection on a non-reacting air-fuel mixture. The investigation has been carried out with the aid of CFD simulations by using AVL FIRE v.2017 solver. The influence of the physical, chemical and in-cylinder thermodynamic conditions on the effectiveness of the water cooling effect of the mixture is discussed and the application of the water injection to a spark ignition engine case at full load and high BMEP is examined. Port Water Injection (PWI) and Direct Water Injection (DWI) solutions are compared showing the high potential involved in DWI.

Today, Direct-Injection systems are widely used on Spark-Ignition engines in combination with turbo-charging to reduce the fuel-consumption and the knock risks. In particular, the spread of Gasoline Direct Injection (GDI) systems is mainly related to the use of new generations of multi-hole, high-pressure injectors whose characteristics are quite different with respect to the hollow-cone, low-pressure injectors adopted in the last decade.This paper presents the results of an experimental campaign conducted on the spray produced by a GDI six-holes injector into a constant volume vessel with optical access. The vessel was filled with air at atmospheric pressure. Different operating conditions were considered for an injection pressure ranging from 3 to 20 MPa. For each operating condition, spray images were acquired by a CCD camera and then post processed to evaluate the spray penetration and cone angles. A flat plate was placed inside the vessel to investigate the spray-wall impingement and liquid-film evolution.The experimental database was used to obtain a CFD methodology defined to simulate the GDI spray behavior. This methodology was based on a classic Eulerian-Lagrangian approach and it was implemented into the Lib-ICE code, developed into the OpenFOAM platform. In particular, specific sub-models were implemented to correctly reproduce the fuel atomization and the droplet-wall interaction.