Impact of fuel surrogate formulation on the prediction of knock statistics in a single cylinder GDI engine

Abstract

The statistical tendency of an optically accessible single-cylinder direct-injection spark-ignition engine to undergo borderline/medium knocking combustion is investigated using 3D-CFD. Focus is made on the role of fuel surrogate formulation for the characterization of anti-knock quality and flame speed of the actual fuel. An in-house methodology is used to design surrogates able to emulate laminar flame speed and autoignition delay times of the injected fuel. Two different surrogates, characterized by increasing level of complexity, are compared. The most complex one (six components) improves the representation of the real fuel, highlighting the crucial role of accurate fuel kinetics to predict flame propagation and unburnt mixture reactivity. A devoted chemical mechanism including the oxidation pathways for all the species in the surrogate is also purposely developed for the current analysis. Knock is investigated using a proprietary statistical knock model (GruMo-UNIMORE Statistical Knock Model, GK-PDF), which can infer the probability of knocking events within a RANS formalism. Predicted statistical distributions are compared to measured counterparts. The proposed numerical/experimental comparison demonstrates the possibility to efficiently integrate complex-chemistry driven information in 3D-CFD combustion simulations without online solving chemical reactions: a combination of laminar flame speed correlations, ignition delay look-up tables, and a statistics-based knock model is adopted to estimate the percentage of knocking cycles in a GDI engine while limiting the computational cost of the simulations.