Modelling Study of Cycle-To-Cycle Variations (CCV) in Spark Ignition (SI)-Controlled Auto-Ignition (CAI) Hybrid Combustion Engine by Using Reynolds-Averaged Navier–Stokes (RANS) and Large Eddy Simulation (LES)

Author:

Wang XinyanORCID,Zhao Hua

Abstract

The spark ignition (SI)-controlled auto-ignition (CAI) hybrid combustion is characterized by early flame propagation combustion and subsequent auto-ignition combustion. The application of combined SI–CAI hybrid combustion can be used to effectively extend the operating range of CAI combustion and achieve smooth transitions between SI and CAI combustion modes. However, SI–CAI hybrid combustion can produce significant cycle-to-cycle variations (CCV). In order to better understand the sources of CCV and minimize its occurrence, the large eddy simulation (LES) and Reynolds-averaged Navier–Stokes (RANS) approaches were employed in this study to model and understand the cyclic phenomenon of SI–CAI hybrid combustion. Both the multi-cycle LES and RANS simulations were analyzed against the experimental measurements in a single cylinder engine at 1500 rpm and a 5.43 bar average indicated the mean effective pressure (IMEP). The detailed analysis of the in-cylinder pressure traces, IMEP, in-cylinder peak pressure (PP), peak pressure rise rate (PPRR) and the crank angles with fuel mass burned fraction at 10%, 50%, 90% and mode transition was performed. The results indicate that overall, the adopted LES simulations could effectively predict the cyclic variations in the hybrid combustion observed in the experiments, while the RANS simulations failed to reproduce the cyclic characteristics at the chosen engine operating conditions. Based on the LES results, the correlation and visualization studies indicate that the cyclic variations in the local velocity around the spark plug lead to the variations in the early flame propagation, which in turn produce temperature fluctuations among the cycles and result in greater variations in the subsequent auto-ignition combustion events.

Funder

UK Research and Innovation

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction

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