Development of a RANS-Based Knock Model to Infer the Knock Probability in a Research Spark-Ignition Engine

Abstract

Engine knock is one of the most limiting factors for modern Spark-Ignition (SI) engines to achieve high efficiency targets. The stochastic nature of knock in SI units hinders the predictive capability of RANS knock models, which are based on ensemble averaged quantities. To this aim, a knock model grounded in statistics was recently developed in the RANS formalism. The model is able to infer a presumed log-normal distribution of knocking cycles from a single RANS simulation by means of transport equations for variances and turbulence-derived probability density functions (PDFs) for physical quantities. As a main advantage, the model is able to estimate the earliest knock severity experienced when moving the operating condition into the knocking regime. In this paper, improvements are introduced in the model, which is then applied to simulate the knock signature of a single-cylinder 400cm3 direct-injection SI unit with optical access; the engine is operated with two spark timings, under knock-safe and knocking conditions respectively. The statistical prediction of knock resulting from the presented knock model is compared to the experimental evidence for both investigated conditions. The agreement between the predicted and the measured knock distributions validates the proposed knock model. Finally, limitations and some unprecedented possibilities given by the model are critically discussed, with particular emphasis on the meaning of RANS knock prediction

CFD Analysis of Port Water Injection in a GDI Engine under Incipient Knock Conditions

“…Future work will be devoted to more extensive validation in multiple engine points, also considering different installation locations and injector designs, as well as different water-to-fuel ratios. From the modeling point of view, more accurate RANS models, like those proposed in [14,15], or LES models [12,26] with multiple combustion realizations can be considered for further assessment.…”

“…Tabulated kinetics for ignition (TKI) coupled with the extended coherent flamelet combustion model (ECFM) it is shown to provide high accuracy in predicting knock frequency and intensity. However, RANS is still the method of choice for large number of design space explorations [7,11,[13][14][15][16]. Some authors are proposing new advanced models with presumed probability distribution functions to include knock statistics upfront in RANS [14,15].…”

“…However, RANS is still the method of choice for large number of design space explorations [7,11,[13][14][15][16]. Some authors are proposing new advanced models with presumed probability distribution functions to include knock statistics upfront in RANS [14,15]. More simply, Berni et al [13] coupled a TKI model to the ECFM flame propagation model, to study water injection effects in a boosted V8 engine with satisfactory results.…”

The potential of statistical RANS to predict knock tendency: Comparison with LES and experiments on a spark-ignition engine

“…In RANS analyses a statistical version (RANS-PDF) of the knock model is used, which is developed to infer knock statistics from RANS equation and whose details can be found in [35][36][37]. The model details are briefly recalled here for the sake of completeness.…”

“…The approach is based on the RANS formalism for averaged quantities, combined with the use of transport equations for variances of physical conditions allowing to estimate a knock probability or a fraction of knocking cycles. Pursuing the same concept developed by Linse et al [46] and relying on transport equations for mixture fraction and enthalpy variances, a statistical RANS model described in [35][36][37] was proposed to infer not only the average KI but also the presumed distribution of knock intensity, and the model validation was carried out on both an optically accessible research engine as well as a production unit. Conversely from the use of a traditional RANS approach, the use of the developed statistics-based knock model gives a quantitative information regarding the presumed fraction of knocking cycles affecting the mean simulation for a given operating condition, thus enhancing the consistency of a RANS simulation of knock with a typical test-bench acquisition dataset.…”