Development of a simplified n-heptane/methane model for high-pressure direct-injection natural gas marine engines

Abstract

High-pressure direct-injection (HPDI) of natu- ral gas is one of the most promising solutions for future ship engines, in which the combustion process is mainly controlled by the chemical kinetics. However, the employment of detailed chemical models for the multi-dimensional combustion simulation is significantly expensive due to the large scale of the marine engine. In the present paper, a reduced n-heptane/methane model consisting of 35-step reactions was constructed using multiple reduction approaches. Then this model was further reduced to include only 27 reactions by utilizing the HyChem (Hybrid Chemistry) method. An overall good agreement with the experimentally measured ignition delay data of both n-heptane and methane for these two reduced models was achieved and reasonable predictions for the measured laminar flame speeds were obtained for the 35-step model. But the 27-step model cannot predict the laminar flame speed very well. In addition, these two reduced models were both able to reproduce the experimentally measured in-cylinder pressure and heat release rate profiles for a HPDI natural gas marine engine, the highest error of predicted combustion phase being 6.5%. However, the engine-out CO emission was over-predicted and the highest error of predicted NO_x emission was less than 12.9%. The predicted distributions of temperature and equivalence ratio by the 35-step and 27-step models are similar to those of the 334-step model. However, the predicted distributions of OH and CH₂O are significantly different from those of the 334-step model. In short, the reduced chemical kinetic models developed provide a high-efficient and dependable method to simulate the characteristics of combustion and emissions in HPDI natural gas marine engines.

Graphical abstract

Keywords

high-pressure direct-injection / natural gas / chemical kinetics / combustion modelling / marine engine

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Acknowledgment

This work was supported by the National Natural Science Foundation of China (Grant Nos. 91941102 and 51922076).

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