A Group Contribution Method for Predicting the Alkyl Ester and Biodiesel Densities at Various Temperatures

Abstract

Biofuels are an attractive alternative from polluting activities to low carbon ones. In this understanding, biodiesel has the potential to replace fossil diesel. Density is a relevant parameter of biodiesel to work out its quality. Density models lead to reducing the costly and time-consuming experimental measurements. We compiled two databases to prove a group contribution approach. For this purpose, the first database contained 1231 densities of 58 alkyl esters, while the second covered 696 densities of 16 pure biodiesel samples and 8 biodiesel blends. The group contribution method based on the molar volume was used to estimate the alkyl ester densities, while the mixing rule proposed by Kay was used to predict the biodiesel densities. The method developed here is easy to apply and provides excellent results, because an average absolute deviation of 0.29% was reached on the biodiesel density prediction.