Cetane Number Prediction of Biodiesel from the Composition of the Fatty Acid Methyl Esters

Abstract

AbstractIn the present work, the measured cetane numbers (CN) of pure fatty acid methyl esters (FAME), as well as the FAME compositions and the reported CN of 59 kinds of biodiesels collected from literature were used to develop a simple model involving as more FAME component as possible for predicting CN of biodiesel from its FAME composition. Two different regression equations correlating the CN of pure FAME with the carbon number of fatty acid chain were obtained by regression analysis, which shows that the dependence of the CN on the carbon number varies with the unsaturated degree of fatty acid chain. The 59 biodiesels were divided into two categories and used, respectively to develop and test a multiple linear regression model (MLRM) correlating the CN of biodiesel with its FAME composition. A simple and convenient regression equation with a high accuracy and a good reproducibility (average absolute error of 0.49 CN for testing set and 1.52 CN for all data) were developed, showing excellent correlation (R2: 0.9904 for testing set). The model developed in the present work can be used conveniently to give a satisfactory predicted CN of biodiesel from the FAME composition.