Emberson, D., Lovas, T., Szczeciński, M., and Mazuro, P., "Stochastic Reactor Model Aiding Experimental HCCI Engine Operating on Surrogate Bio-Producer Gas," SAE Technical Paper 2016-01-2296, 2016, doi:10.4271/2016-01-2296.
A stochastic reactor model has been employed to aid the development of a new highly efficient and compact opposing piston, barrel engine. It is desirable to utilize the engine across a broad range of applications and the designers have identified the use of low calorific value fuels derived from low grade biomass gasification in HCCI mode as one possible end use. Biogas from solid fuel gasification can vary largely in composition of main components depending on feedstock and gasification method. Hence, in order to address the engines applicability to run on biogas in general terms, identifying a simple two-component surrogate fuel which can be varied under testing is of great importance. A stochastic reactor model in the form of a commercially available software, LOGEsoft, has been used to examine suitable surrogate gas mixtures which could be used to best simulate the biogas during initial engine testing and development. A sample biogas was simulated using the HCCI SRM module in the software using a chemical kinetic mechanism combining the GRI.mech 3.0 and Golovichev’s mechanisms. Surrogate gas mixtures comprising of propane, carbon dioxide and heptane (vapor) were then investigated numerically until a suitable composition was found which behaved similar to the biogas mixture in the HCCI simulation. Combustion pressure, heat release rate and OH mole fraction were used as the variables and properties to compare between the cases examined. The output of the SRM supplied the engine designers with a surrogate gas composition to experiment with that best matched the biogas mixture as well as some initial engine parameters such as compression ratio, initial gas temperature and pressure. Whilst not offering the insight into the complex flow fields that a full 3D model may provide, the SRM proved to be an ideal computational in-expensive tool to rapidly examine the impact of fueling on heat release and ignition in a HCCI engine while still accounting for important effects of mixing and inhomogeneities known to be crucial for HCCI combustion.