Syngas produced from biomass gasification is being increasingly considered as a promising alternative to traditional fuels in Spark-Ignition (SI) Internal Combustion Engines (ICEs). Due to the low energy density and extreme variability in the composition of this gaseous fuel, numerical modeling can give an important contribution to assure stable engine performances.
The present work intends to give a contribution in this sense in this sense, by proposing a multi-level set of approaches, characterized by an increasing detail, as a tool aimed at the optimization of energy conversion of non-conventional fuels.
At first, a specific characterization of the dependency of the syngas laminar flame speed upon its composition is achieved through an iterative approach pursued in the ANSYS ChemkinTM environment, where validated correlations of the flame speed tuning parameters are obtained in a zero-dimensional framework.
Subsequently, the interaction between combustion kinetics and fluid dynamics is considered through the development of a mono-dimensional (1D) model of the whole engine system in the GT-Power environment. A predictive combustion model, tuned on the ground of the combustion parameters determined through the previous approach, is implemented to guarantee the correct prediction of the engine efficiencies as the primary energy related to the gaseous fuel composition varies.
At last, a 3D Computational Fluid Dynamics (CFD) model is developed within the AVL FIRETM software to reproduce the engine combustion cycle within a Reynolds Averaged Navier Stokes (RANS) schematization. The detailed chemical reaction mechanism GRI-Mech 3.0 is used to give details about the syngas oxidation chain. All the numerical results are validated with respect to literature data as regards the laminar flame speed prediction, and by using experimental measurements under real operation and syngas generation through biomass gasification, as concerns the engine performances. The proposed multi-level analysis is proposed as a robust procedure suitable of fully accounting of the overall variability that characterizes the gaseous fuel as the biomass composition and operative conditions are varied.