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Cycle-To-Cycle Variability (CCV) must be properly considered when modeling the ignition process in SI engines operating with ultra-lean mixtures. In this work, a strategy to model the impact of the ignition type on the CCV was developed using the RANS approach for turbulence modelling, performing multi-cycle simulations for the power-cycle only. The spark-discharge was modelled through a set of Lagrangian particles, introduced along the sparkgap and interacting with the surrounding Eulerian gas flow. Then, at each discharge event, the velocity of each particle was modified with a zero-divergence perturbation of the velocity field with respect to average conditions. Finally, the particles velocity was evolved according to the Simplified Langevin Model (SLM), which keeps memory of the initial perturbation and applies a Wiener process to simulate the stochastic interaction of each channel particle with the surrounding gas flow.

Objective of this work is the incorporation of the flame stretch effects in an Eulerian-Lagrangian model for premixed SI combustion in order to describe ignition and flame propagation under highly inhomogeneous flow conditions. To this end, effects of energy transfer from electrical circuit and turbulent flame propagation were fully decoupled. The first ones are taken into account by Lagrangian particles whose main purpose is to generate an initial burned field in the computational domain. Turbulent flame development is instead considered only in the Eulerian gas phase for a better description of the local flow effects. To improve the model predictive capabilities, flame stretch effects were introduced in the turbulent combustion model by using formulations coming from the asymptotic theory and recently verified by means of DNS studies. Experiments carried out at Michigan Tech University in a pressurized, constant-volume vessel were used to validate the proposed approach.

The continuous pursuit of higher combustion efficiencies, as well as the possible usage of synthetic fuels with different properties than fossil-ones, require reliable and low-cost numerical approaches to support and speed-up engines industrial design. In this context, SI engines operated with homogeneous ultra-lean mixtures both characterized by a classical ignition configuration or equipped with an active prechamber represent the most promising solutions. In this work, for the classical ignition arrangement, a 3DCFD strategy to model the impact of the ignition system type on the CCV is developed using the RANS approach for turbulence modelling. The spark-discharge is modelled through a set of Lagrangian particles, whose velocity is modified with a zero-divergence perturbation at each discharge event, then evolved according to the Simplified Langevin Model (SLM) to simulate stochastic interactions with the surrounding gas flow.

In the recent years, the interest in heavy-duty engines fueled with Compressed Natural Gas (CNG) is increasing due to the necessity to comply with the stringent CO2 limitation imposed by national and international regulations. Indeed, the reduced number of carbon atoms of the NG molecule allows to reduce the CO2 emissions compared to a conventional fuel. The possibility to produce synthetic methane from renewable energy sources, or bio-methane from agricultural biomass and/or animal waste, contributes to support the switch from conventional liquid fuels to CNG. To drive the engine development and reduce the time-to-market, the employment of numerical analysis is mandatory. This requires a continuous improvement of the simulation models toward real predictive analyses able to reduce the experimental R&D efforts. In this framework, 1D numerical codes are fundamental tools for system design, energy management optimization, and so on.

Gasoline, direct injection engines represent one of the most widely adopted powertrain for passenger cars. However, further development efforts are necessary to meet the future fuel consumption and emission standards imposing an efficiency increase and a reduction of particulate matter emissions. Within this context, computational fluid dynamics is nowadays a consolidated tool to support engine design; this work is focused on the development of a set of CFD models for the prediction of combustion in modern GDI engines. The one-equation Weller model coupled with a zero-dimensional approach to handle initial flame kernel growth was applied to predict flame propagation. To account for mixture fraction fluctuations which might lead to the presence of soot precursor species, burned gas chemical composition is computed using tabulated kinetics with a presumed probability density function.