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Evaluation of the Predictive Capabilities of a Phenomenological Combustion Model for Natural Gas SI Engine
Author(s) -
Rastislav Toman,
Jan Macek
Publication year - 2017
Publication title -
mecca journal of middle european construction and design of cars
Language(s) - English
Resource type - Journals
eISSN - 1804-9338
pISSN - 1214-0821
DOI - 10.1515/mecdc-2017-0007
Subject(s) - turbulence , mechanics , phenomenological model , turbulence kinetic energy , computational fluid dynamics , combustion , laminar flow , sensitivity (control systems) , cylinder , simulation , automotive engineering , physics , computer science , engineering , mechanical engineering , chemistry , organic chemistry , quantum mechanics , electronic engineering
The current study evaluates the predictive capabilities of a new phenomenological combustion model, available as a part of the GT-Suite software package. It is comprised of two main sub-models: 0D model of in-cylinder flow and turbulence, and turbulent SI combustion model. The 0D in-cylinder flow model (EngCylFlow) uses a combined K-k-ε kinetic energy cascade approach to predict the evolution of the in-cylinder charge motion and turbulence, where K and k are the mean and turbulent kinetic energies, and ε is the turbulent dissipation rate. The subsequent turbulent combustion model (EngCylCombSITurb) gives the in-cylinder burn rate; based on the calculation of flame speeds and flame kernel development. This phenomenological approach reduces significantly the overall computational effort compared to the 3D-CFD, thus allowing the computation of full engine operating map and the vehicle driving cycles. Model was calibrated using a full map measurement from a turbocharged natural gas SI engine, with swirl intake ports. Sensitivity studies on different calibration methods, and laminar flame speed sub-models were conducted. Validation process for both the calibration and sensitivity studies was concerning the in-cylinder pressure traces and burn rates for several engine operation points achieving good overall results.

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