Neuro fuzzy estimation of the most influential parameters for Kusum biodiesel performance. (15th August 2021)

• Record Type: Journal Article
• Authors: Petković, Dalibor; Barjaktarovic, Miljana; Milošević, Slaviša; Denić, Nebojša; Spasić, Boban; Stojanović, Jelena; Milovancevic, Milos
• Is Part Of: Energy. Volume 229(2021)
• Publication Date: 2021-08-15
• Subjects: Biodiesel -- Kusum oil -- Transesterification -- ANFIS; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2021.120621
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: In order to reduce cost of biodiesel production there is need to use non-edible oil. Kusum feed oil is non-edible oil, low cost and substantial available for biodiesel production. To improve Kusum biodiesel performance and emission parameters there is need to analyze input variables in more comprehensive way. It is suitable to establish computational models to obtain optimal parameters. The main goal of the paper was to establish and adaptive neuro fuzzy inference system (ANFIS) to determine the impact of blending, fuel injection timing, fuel injection pressure and engine load on brake thermal efficiency, unburnt hydrocarbons and oxides of nitrogen. It was found that the fuel injection pressure and engine load is the most influential factors on the brake thermal efficiency, unburnt hydrocarbons and oxides of nitrogen. The results could be useful for optimization of the Kusum biodiesel performance and emission parameters. Highlights: To reduce cost of biodiesel production there is need to use non-edible oil. Kusum feed oil is non-edible oil, low cost. To obtain optimal parameters. Fuel injection pressure and engine load is the most influential factors.