Application of micro-genetic algorithm for calibration of kinetic parameters in HCCI engine combustion model

Abstract

The micro-genetic algorithm (?GA) as a highly effective optimization method, is applied to calibrate to a newly developed reduced chemical kinetic model (40 species and 62 reactions) for the homogeneous charge compression ignition (HCCI) combustion of n-heptane to improve its autoignition predictions for different engine operating conditions. The seven kinetic parameters of the calibrated model are determined using a combination of the Micro-Genetic Algorithm and the SENKIN program of CHEMKIN chemical kinetics software package. Simulation results show that the autoignition predictions of the calibrated model agree better with those of the detailed chemical kinetic model (544 species and 2 446 reactions) than the original model over the range of equivalence ratios from 0.1–1.3 and temperature from 300–3 000 K. The results of this study have demonstrated that the mGA is an effective tool to facilitate the calibration of a large number of kinetic parameters in a reduced kinetic model.

Keywords

HCCI engine, n-heptane reduced kinetic model, kinetic parameter, optimization, micro-genetic algorithm