Numerical Investigation of Syngas Fueled HCCI Engine Using Stochastic Reactor Model with Detailed Kinetic Mechanism 2018-01-1661
Research in the utilization of hydrogen and syngas has significantly increased due to their clean-burning properties and the prospect of production from several renewable resources. Homogeneous charge compression ignition (HCCI) engine is low-temperature combustion (LTC) concept which combines the best features of conventional spark-ignition (SI) and compression-ignition (CI) engines. HCCI combustion engine has shown the potential for higher efficiency and ultralow NOx and soot emissions. In this study, syngas fueled HCCI combustion is simulated using stochastic reactor model (SRM) with a detailed chemical kinetic mechanism (32 species and 173 reactions). Detailed syngas oxidation mechanism included NOx reactions also. In SRM models physical parameters are described by a probability density function (PDF). These parameters does not vary within the combustion chamber, and thus the spatial distribution (due to local inhomogeneity’s) of the charge is represented in terms of a PDF. The SRM based approach simplifies many aspects of CFD processes while retaining the predictive capability similar to 3-D CFD codes. Simulations are conducted for different engine operating conditions by varying intake temperature, engine load, and speed at compression ratio 19:1 for an engine of 0.435 L swept volume. The simulation shows good conformity with experimental engine data. Start of combustion and cylinder pressures are predicted with sufficient accuracy. Sensitivity analysis is conducted to determine the influential reactions in syngas oxidation. Combustion characteristics and efficiency of an engine operating on varying blends of synthesis gas in HCCI mode are also investigated.
Citation: Maurya, R., Saxena, M., Yadav, R., and Rathore, A., "Numerical Investigation of Syngas Fueled HCCI Engine Using Stochastic Reactor Model with Detailed Kinetic Mechanism," SAE Technical Paper 2018-01-1661, 2018, https://doi.org/10.4271/2018-01-1661. Download Citation