Predictive skeletal kinetic model of biodiesel autoxidation

Gradual depletion of fossil fuels, growing environmental concerns, and global warming have shifted the focus to renewable liquid fuels, such as biodiesel. Biodiesel is reported to cause less emission and can be used in engines without much modification. Even though biodiesel fuels have promising combustion and emission characteristics for use in engines, their poor oxidation stability due to aging is an inhibiting factor for wider usage. In this paper, an autoxidation model for biodiesel fuels is proposed, considering their major fatty acid constituents. The proposed kinetic parameters are optimized using a genetic algorithm with the help of experimental data available in the literature. Temperature and fuel effects on the optimized rate parameters are studied. The proposed kinetics scheme is useful to predict the oxidation of fuel constituents with a fair degree of accuracy. The model also enables prediction of a useful engineering quantity, viz., induction period, to facilitate a priori evaluation of autoxidation characteristics of biodiesel fuel.