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Title: Combustion modeling in RCCI engines with a hybrid characteristic time combustion and closed reactor model
Authors: Zhou, Dezhi
Yang, Wenming
Li, Jing
Tay, Kun Lin
Kraft, Markus
Keywords: Engineering::Chemical engineering::Chemistry of fire
Issue Date: 2017
Source: Zhou, D., Yang, W., Li, J., Tay, K. L., & Kraft, M. (2017). Combustion modeling in RCCI engines with a hybrid characteristic time combustion and closed reactor model. Applied Energy, 227, 665-671. doi:10.1016/j.apenergy.2017.08.137
Journal: Applied Energy 
Abstract: This study proposed a hybrid model consisting of a characteristic time combustion (CTC) model and a closed reactor model for the combustion modelling with detailed chemistry in RCCI engines. In the light of the basic idea of the CTC model of achieving chemical equilibrium in high temperature, this hybrid model uses the CTC model to solve the species conversion and heat release in the diffusion flame. Except for the diffusion flame, the auto-ignition in RCCI combustion is computed by a closed reactor model with the CHEMKIN library by assuming that the computational cells are closed reactors. The border of the transition between the CTC model and closed reactor model is determined by two criteria, a critical temperature and a critical Damköhler number. On the formulation of this hybrid model, emphasis is placed on coupling detailed chemistry into this hybrid model. A CEQ solver for species equilibrium calculations at certain temperature, pressure was embedded with CTC for detailed chemistry calculation. Then this combustion model was integrated with the CFD framework KIVA4 and the chemical library CHEMKIN-II and validated in a RCCI engine. The predicted in-cylinder pressure and heat release rate (HRR) show a good consistency with the data from the experiment and better accuracy than that computed from the sole closed reactor model. More importantly, it is observed that this model could save computational time compared with closed reactor model due to less stiff ordinary differential equations (ODEs) computation. A sensitivity analysis of the critical temperature and critical Damköhler number was conducted to demonstrate the effect of these two parameters in the current model.
ISSN: 0306-2619
DOI: 10.1016/j.apenergy.2017.08.137
Schools: School of Chemical and Biomedical Engineering 
Rights: © 2017 Elsevier Ltd. All rights reserved. This paper was published in Applied Energy and is made available with permission of Elsevier Ltd.
Fulltext Permission: open
Fulltext Availability: With Fulltext
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