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.
Evaluation of the Predictive Capabilities of a Phenomenological Combustion Model for Natural Gas SI Engine
2017
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
Phenomenological Combustion Model for a Quiescent Chamber Diesel Engine
SAE Technical Papers | 1981
|Phenomenological combustion model for a quiescent chamber Diesel engine
Automotive engineering | 1981
|A phenomenological combustion analysis of a dual-fuel natural-gas diesel engine
SAGE Publications | 2017
|Evaluation of a 0D Phenomenological SI Combustion Model
British Library Conference Proceedings | 2011
|A phenomenological combustion analysis of a dual-fuel natural-gas diesel engine
Online Contents | 2017
|