Advanced combustion modelling of high bmep engines under water injection conditions with chemical correlations generated with detailed kinetics and machine learning algorithms

Water injection is becoming a technology of increasing interest for SI engines development to comply with current and prospective regulations. To perform a rapid optimization of the main parameters involved by the water injection process, it is necessary to have reliable CFD methodologies capable of capturing the most important phenomena. In the present work, a methodology for the CFD simulation of combustion cycles of SI GDI turbocharged engines under water injection operation is proposed. The ECFM-3Z model adopted for combustion and knock simulations takes advantages by the adoption of correlations for the laminar flame speed, flame thickness and ignition delay times prediction obtained by a detailed chemistry calculation. The latter uses machine learning algorithms to reduce the time to generate the full database while still maintaining an even distribution along the variables of interest. The results demonstrate the applicability of the proposed methodology, capable of capturing not only the thermodynamic effects of water injection but also the chemical kinetics aspects related to the mixture water dilution whose prediction is mandatory for addressing the engine design according to different goals: complying with new emission directives and limits, turbine inlet temperature constraints, minimization of the BSFC and possibly engine power increase.