Estimation of cetane numbers of biodiesel and diesel oils using regression and PSO-ANFIS models

Abolfazl Sajadi Noushabadi, Amir Dashti, Mojtaba Raji, Alireza Zarei and Amir H. Mohammadi

Renewable Energy, 2020, vol. 158, issue C, 465-473

Abstract: One of the essential characteristics of diesel oils is their cetane number (CN) which indicates the ignition delay of the fuel in the process. In this study, using PSO-ANFIS technique, CNs of biodiesel and conventional diesel (called petrodiesel) oils were modeled and estimated based on the fatty acid methyl ester compositions of biodiesel oils and carbon type structure of the diesel fuels. For the first time, novel correlations were developed for the estimation of CNs of biodiesel and conventional diesel oils. For the models development, as the raw data, 232 biodiesel and 134 conventional diesel oils samples were derived from the literature. Based on the obtained results, the coefficient determinations (R2) of 0.91 and 0.93 and %AARD of 6.4 and 9.6 were obtained by PSO-ANFIS and MNR models for the estimation of biodiesel oil CN, respectively. The R2 of 0.98 and 0.96 and %AARD of 2 and 2.9 were resulted using PSO-ANFIS and MNR models for the prognostication of diesel oil CN, respectively. Based on the gained results, PSO-ANFIS and MNR algorithms are capable of estimating the biodiesel and diesel oils CNs. The novelty of this study is the development of novel correlations and smart models with high accuracies.

Keywords: Biodiesel oil; Cetan number; Fatty acid methyl esters (FAMEs); Multivariate Nonlinear Regression (MNR); PSO-ANFIS; Diesel oil (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:158:y:2020:i:c:p:465-473

DOI: 10.1016/j.renene.2020.04.146

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