Probabilistic Approach to Predict Abnormal Combustion in Spark Ignition Engines

2018-01-1722

09/10/2018

Features
Event
International Powertrains, Fuels & Lubricants Meeting
Authors Abstract
Content
This study presents a computational framework to predict the outcome of combustion process based on a given RANS initial condition by performing statistical analysis of Sankaran number, Sa, and ignition regime theory proposed by Im et al. [1]. A criterion to predict strong auto-ignition/detonation a priori is used in this study, which is based on Sankaran-Zeldovich criterion. In the context of detonation, Sa is normalized by a sound speed, and is spatially calculated for the bulk mixture with temperature and equivalence ratio stratifications. The initial conditions from previous pre-ignition simulations were used to compute the spatial Sa distribution followed by the statistics of Sa including the mean Sa, the probability density function (PDF) of Sa, and the detonation probability, PD. Sa is found to be decreased and detonation probability increased significantly with increase of temperature. The statistic mean Sa calculated for the entire computational domain and the predicted Sa from the theory were found to be nearly identical. The predictions based on the adapted Sankaran-Zel’dovich criterion and detonation probability agree well with the results of the previous high fidelity pre-ignition simulations.
Meta TagsDetails
DOI
https://doi.org/10.4271/2018-01-1722
Pages
7
Citation
Mubarak Ali, M., Luong, M., Sow, A., Hernandez Perez, F. et al., "Probabilistic Approach to Predict Abnormal Combustion in Spark Ignition Engines," SAE Technical Paper 2018-01-1722, 2018, https://doi.org/10.4271/2018-01-1722.
Additional Details
Publisher
Published
Sep 10, 2018
Product Code
2018-01-1722
Content Type
Technical Paper
Language
English