Predictability of Biodiesel Fuel Properties from the Fatty Acid Composition of the Feedstock Oils

Abstract

Among alternative transport fuels, biodiesel is an eco-friendly substitute for petrodiesel. The quality of biodiesel is dependent on the composition of feedstock oils used for its preparation. The mathematical/statistical tools are used to determine the biodiesel properties, and their outputs are further compared with experimental results for their consistency and reliability. To reduce the cost, efforts and resources, the current study aims to evaluate the predicting ability of the standalone software BiodieselAnalyzer. In the present study, properties of 45 biodiesels are predicted using BiodieselAnalyzer software and the obtained results are compared with earlier published literature. The % absolute relative deviation was found as 4.47% and 5.31% for density and higher heating value, respectively, but the highest deviation was found for kinematic viscosity (70.19%), oxidation stability (131.19%), cloud point (118.57%) and cold filter plugging point (234.17%). The results indicate that the software shows a good performance in predicting the density and higher heating value; however, the software shows poor reliability in predicting kinematic viscosity, oxidation stability, cloud point and cold filter plugging point. This inconsistency might be due to the non-inclusion of factors such as minor oil components, natural antioxidant in oil, oil extraction process, storage conditions of oil, impurities in oil, production processes, oil and biodiesel clean-up process. Based on this work, it is recommended to improve/develop the software in terms of accuracy and precision for predicting the biodiesel properties or adopt experimentation to determine biofuel properties.