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Detailed Composition-Based Model for Predicting the Cetane Number of Diesel Fuels

We have developed a simple composition-based model for predicting the cetane number of diesel fuels with general applicability to any diesel fuel regardless of the refining process it originates from. The cetane number is correlated to a total of 129 different hydrocarbon lumps determined by a combination of supercritical fluid chromatography, gas chromatography, and mass spectroscopic methods. A total of 203 diesel fuels are considered in this study derived from various diesel-range refinery process streams and their commercial blends. Across the multitude of such process streams and blends, the model predicts the cetane number with a standard error of 1.25 numbers, which is well within the experimental error of the measurement.