Predicting cetane number in diesel fuels using FTIR spectroscopy and PLS regression

Cetane number (CN) is an important property which indicates the ignition quality of fuels and especially diesel oil. The usual method for CN determination is a most involving and risky task that requires specific devices. In this paper, Partial Least Square Regression (PLSR) was successfully used for the prediction of diesel cetane number based on Fourier Transform Infrared Spectroscopy (FTIR). The proposed model was characterized by a high correlation coefficient between real and predicted CN values (R2 = 0.99), with small prediction error values (RMSEC = 0.28 and RMSEP = 0.42) compared to previously published models developed using spectroscopic techniques, namely NIR and Raman spectroscopy Thus, the proposed approach that uses the FTIR spectroscopy for cetane number determination can be highly recommended as a clean, environment friendly, rapid and reliable solution for the prediction of this important quality parameter of diesel fuels.