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This paper is focused on the development and application of a CFD methodology that can be applied to predict the fuel-air mixing process in stratified charge, sparkignition engines. The Eulerian-Lagrangian approach was used to model the spray evolution together with a liquid film model that properly takes into account its effects on the fuel-air mixing process into account. However, numerical simulation of stratified combustion in SI engines is a very challenging task for CFD modeling, due to the complex interaction of different physical phenomena involving turbulent, reacting and multiphase flows evolving inside a moving geometry. Hence, for a proper assessment of the different sub-models involved a detailed set of experimental optical data is required. To this end, a large experimental database was built by the authors.

The paper describes the development and validation of a quasi-dimensional multi-zone combustion model for Gasoline Direct Injection engines. The model has been embedded in the 1D thermo-fluid-dynamic code for the simulation of the whole engine system named GASDYN and developed by the authors [1, 2 and 3]. The GDI engine combustion model solves mass, energy and species equations using a 4th order Runge-Kutta integration method; the fuel spray is initially divided into a number of zones fixed regardless of the injected amount and the time step, considering the following break-up, droplet evaporation and air entrainment in each single zone. Experimental correlations have been used for the spray penetration and spatial information. Once the ignition begins it is assumed that the flame propagates spherically, evaluating its velocity by means of a fractal combustion approach and considering the local air-fuel ratio, which is the result of the spray evolution within the combustion chamber.

In this work an integration between a 1D code (Gasdyn) with a CFD code (OpenFOAM®) has been applied to improve the performance of a Moto3 engine. The four-stroke, single cylinder S.I. engine was modeled, in order to predict the wave motion in the intake and exhaust systems and to study how it affects the cylinder gas exchange process. The engine considered was characterized by having an air induction system with integrated filter cartridge, air-box and intake runner, including two fuel injectors, resulting in a complex air-path from the intake mouth to the intake valves, which presents critical aspects when a 1D modeling is addressed. The exhaust and intake systems have been optimized form the point of view of the wave action. However, due to the high revolution speed reached by this type of engine, the interaction between the gas stream and the fuel spray becomes a key aspect to be addressed in order to achieve the best performance at the desired operating condition.

A detailed understanding of Gasoline Direct Injection (GDI) techniques applied to spark-ignition (SI) engines is necessary as they allow for many technical advantages such as increased power output, higher fuel efficiency and better cold start performances. Within this context, the extensive validation of multi-dimensional models against experimental data is a fundamental task in order to achieve an accurate reproduction of the physical phenomena characterizing the injected fuel spray. In this work, simulations of different Engine Combustion Network (ECN) Spray G conditions were performed with the Lib-ICE code, which is based on the open source OpenFOAM technology, by using a RANS Eulerian-Lagrangian approach to model the ambient gas-fuel spray interaction.

Direct-injection represents a consolidated technology to increase performance and efficiency in spark-ignition engines. It reduces the knock tendency and makes engine downsizing possible through the use of turbocharging. Better control of CO and HC emissions at cold-start is also ensured since there is no wall-impingement in the intake port. However, to take advantages of all the theoretical benefits derived from GDI technology, detailed investigations of both fuel-air mixing and combustion processes are necessary to extend the stratified charge operations in the engine map and to reduce soot emissions, that are now severely regulated by emission standards. In this work, the authors developed a CFD methodology to investigate and optimize the fuel-air mixing process in direct-injection, spark-ignition engines. The Eulerian-Lagrangian approach is used to model the evolution of the fuel spray emerging from a multi-hole injector.

The paper illustrates and validates a novel predictive combustion model for the estimation of performances and pollutant production in CI engines. The numerical methodology was developed by the authors for near real-time applications, while aiming at an accurate description of the air mixing process by means of a multi-zone approach of the air-fuel mass. Charge stratification is estimated via a 2D representation of the fuel spray distribution that is numerically derived by an axial one-dimensional control-volume description of the direct injection. The radial coordinate of each control volume is reconstructed a posteriori by means of a local distribution function. Fuel mass clustered in each zone is further split in ‘liquid’, ‘unburnt’ and ‘burnt’ sub-zones, given the local properties of the fuel spray control volumes with respect to space-time location of modelled ignition delay, liquid length, and flame lift-off.

The employment of hydrogen as energy carrier for transportation sector represents a significant challenge for powertrains. Spark-ignition (SI) engines are feasible and low-cost devices to convert the hydrogen chemical energy into mechanical work. However, significant efforts are needed to successfully retrofit the available configurations. The computational fluid dynamics (CFD) modelling represents a useful tool to support experiments, clarifying the impact of the engine characteristics on both the mixture preparation and the combustion development. In this work, a CFD investigation is carried out on typical light-duty SI engine configurations, exploring the two main strategies of hydrogen addition: port fuel injection (PFI) and direct injection (DI). The purpose is to assess the behaviour of widely-used numerical models and methodologies when hydrogen is employed instead of traditional carbon-based fuels.