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Predicting the Cetane Number of Biodiesel Fuels from Their Fatty Acid Methyl Ester Composition

Author:
Mishra, Shashank, Anand, K., Mehta, Pramod S.
Source:
Energy & Fuels 2016 v.30 no.12 pp. 10425-10434
ISSN:
1520-5029
Subject:
biodiesel, data collection, fatty acid methyl esters, models, prediction, regression analysis
Abstract:
One of the important properties of fuel related to compression ignition (CI) engine applications is the cetane number. The present work aims to develop a universal model to predict the cetane number of any candidate biodiesel fuel based on its fatty acid methyl ester composition using a multi-linear regression approach. The biodiesel composition effects on the cetane number are captured through two new parameters, viz., straight-chain saturated factor (SCSF) and modified degree of unsaturation (DUₘ), which can be estimated directly from the measured biodiesel composition data. The proposed composition-based approach for predicting the cetane number of biodiesel is not limited to a specific data set. The predictions from the proposed correlation are compared to the measured cetane number of nine different biodiesel fuels of varied compositions, having wide variations of the cetane number in the range of 49–62. The comparison is found to be quite satisfactory, with a regression coefficient of 0.95 and an average absolute deviation of 1.63%. Further, the predictions from the present model are found to be much better than the existing cetane number prediction models for biodiesel fuels.
Agid:
5594494