Application of adaptive neuro-fuzzy inference system and response surface methodology in biodiesel synthesis from jatropha–algae oil and its performance and emission analysis on diesel engine coupled with generator

Sunil Kumar, Siddharth Jain and Harmesh Kumar

Energy, 2021, vol. 226, issue C

Abstract: Present study presents the results of methyl esters preparation from Jatropha-Algae oil using transesterification process. In this study, an adaptive neuro-fuzzy inference system (ANFIS) and the response surface methodology (RSM) based Box–Behnken techniques were used for modelling and analysis of different parameters viz molar ratio, temperature, reaction time, and catalyst concentration in biodiesel production process. Significant regression model with R2value of 0.9867 was obtained under a molar ratio of 6–12, KOH of 0–2% w/w, time of 60–180 min and temperature of 35–55 °C using RSM. The ANFIS model was used to individually correlate the output variable (biodiesel yield) with four input variables with R2 value of 0.9998. Finally, a study investigating the performance and emissions of a diesel engine fuelled with biodiesel blends (B0, B5, B10 and B20 vol%) has been performed concluding significant reduction of emission.

Keywords: Jatropha-algae oil; RSM,ANFIS; Engine performance; Exhaust emissions (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:226:y:2021:i:c:s0360544221006770

DOI: 10.1016/j.energy.2021.120428

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