• CaF-144-634-637

Sources of CO emissions in an HCCI engine: A numerical analysis

Authors: Amit Bhave, Markus Kraft*, Luca Montorsi, and Fabian Mauss

Reference: Combustion and Flame 144, 634-637, (2006)


In this paper, we investigate the factors influencing a reliable prediction of CO emissions in a homogeneous charge compression ignition (HCCI) engine using an improved probability density function (PDF)-based engine cycle model. The PDF-based stochastic reactor model (SRM) as validated in our previous work is utilized to identify critical sources of CO emissions numerically. The full cycle model includes detailed chemical kinetics, accounts for the inhomogeneities in temperature and composition, and has been demonstrated to provide sufficiently reliable predictions of the combustion and engine parameters and emissions. The single-zone, multizone, and CFD-based engine cycle models have been widely used to gain insight into HCCI combustion; however, in general, the predictions of CO emissions have been poor. The underprediction of CO emissions using a single zone-based model results from its inability to account for the inhomogeneities. A closed volume, 10-zone model faced intrinsic difficulty in predicting the CO emissions, underpredicting the measurements by an order of magnitude. Studies involving a sequential multizone model and the segregated solver approaches also showed an error of around 70% in predicting the CO emissions. Such underprediction was attributed to the lack of mass and energy transfer between the zones while emphasizing the need for more detailed description of the in-cylinder temperature distribution. A 9-zone-based full cycle model with mass exchange between zones required modification of rate constants for the CO oxidation reaction to obtain a good agreement against measurements. A CFD-coupled cycle model located the cylinder liner wall as a major source of CO emissions, but the CO emissions were underpredicted by 80%. In another study, the segregated multizone-based model was improved by incorporating heat transfer and mixing during the post-main heat release part of the engine cycle and the CO emissions were predicted as 50% of the measurements for a specific operating point. It has been pointed out that implementing a certain inhomogeneity in the perfectly stirred individual zones of the multizone model could improve the prediction capability. In our previous works, the integrated SRM-based engine cycle model was demonstrated to predict CO emissions at 70-80% of the measurements. Here, we employ the model to investigate the factors responsible for the calculation of CO emissions in such a PDF-based modeling approach.

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*Corresponding author:
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Address: Department of Chemical Engineering and Biotechnology
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