Evaluation of Predictive Models for the Viscosity of Biodiesel

Viscosity is an important biodiesel parameter, subject to specifications and with an impact on the fuel quality. A model that could predict the value of viscosity of a biodiesel based on the knowledge of its composition would be useful in the optimization of biodiesel production processes and the planning of blending of raw materials and refined products. This work aims at evaluating the predictive capability of several models previously proposed in the literature for the description of the viscosities of biodiesels and their blend with other fuels. The models evaluated here are Ceriani’s, Krisnangkura’s, and Yuan’s models, along with a revised version of Yuan’s model proposed here. The results for several biodiesel systems show that revised Yuan’s model proposed provides the best description of the experimental data with an average deviation of 4.65%, as compared to 5.34% for Yuan’s model, 8.07% for Ceriani’s model, and 7.25% for Krisnangkura’s model. The same conclusions were obtained when applying these models to predict the viscosity of blends of biodiesel with petrodiesel.