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. (1st July 2021)

• Record Type: Journal Article
• Authors: Kumar, Sunil; Jain, Siddharth; Kumar, Harmesh
• Is Part Of: Energy. Volume 226(2021)
• Publication Date: 2021-07-01
• Subjects: Jatropha-algae oil -- RSM, ANFIS -- Engine performance -- Exhaust emissions; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2021.120428
• Languages: English
• ISSNs: 0360-5442

Abstract

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 R 2 value 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 R 2 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. Graphical abstract: Image 1 Highlights: Biodiesel produced from Jatropha–Algae oil. RSM used for design of experiment. ANFIS technique used for prediction. Performance and Emission analysis done on diesel coupled with electric generator.