Latest Developments in Gasoline Auto-Ignition Modelling Applied to an Optical CAI (Tm) Engine

Abstract

The accuracy of predictive engine modelling for Compression Ignition (CI) combustion modes is heavily depending on the quality of the description of the auto-ignition process. The Controlled Auto- Ignition (CAITM ) combustion process is a CI combustion mode using gasoline as fuel. Its modelling requires to account for the chemical characteristics of the fuel in low temperature, low equivalence ratio operating conditions. Existing models based on correlations do not allow to cover the whole range of thermodynamic conditions encountered in those engines and the effect of local inhomogeneities on the auto-ignition occurrence. A dedicated auto-ignition model derived from detailed chemical kinetics calculations for a wide range of burnt gas dilution ratios and octane numbers is presented in this paper. Depending on local thermodynamic conditions, 3D CFD auto-ignition parameters are interpolated in a database describing low temperature effects and progress variable reaction rates for Primary Reference Fuels (PRF). The model validation is performed by comparing 3D CFD calculations with detailed chemical kinetics results for homogeneous configurations and rapid compression machines. To highlight the basic thermal and chemical processes responsible for the occurrence of auto-ignition in a CAITM engine, a reference operating point for an optical diagnostic engine is simulated. The assessment of the quality of the model prediction relies not only on global data, such as mean in-cylinder pressure, but also on the comparison of local volumetric reaction rates with the direct visualisation of light emitted during engine operation.