Application of Fuzzy-NSGA-II for achieving maximum biodiesel yield from waste cooking oil

Title

Application of Fuzzy-NSGA-II for achieving maximum biodiesel yield from waste cooking oil

Creator

Kavalli, Kiran; Hebbar, Gurumoorthy S.; Rout, Amruta

Description

The increasing demand for renewable energy and efficient waste management has highlighted the need for innovative biodiesel production techniques. This study optimises biodiesel production from waste cooking oil (WCO) using fuzzy modelling and non-dominated sorting genetic algorithm-II (NSGA-II). The optimisation process focuses on key input parameters: methanol quantity, reaction temperature, reaction time, and catalyst concentration, which were normalised and represented using linguistic variables. Fuzzy logic was employed to predict biodiesel yield, expressed in terms of linguistic variables, and defuzzified to yield crisp output values. The developed model achieved a high R2 value of 96.34%, demonstrating a strong correlation between input variables and biodiesel yield. The NSGA-II algorithm was utilised for multi-objective optimisation, determining the optimal conditions for biodiesel production: 150ml of methanol, a reaction temperature of 62C, a reaction time of 63min, and a catalyst concentration of 7.5g. These parameters resulted in a maximum biodiesel yield of 97.36%. The Box-Behnken experimental design validated the models efficiency, achieving a yield of 96.88%. This study emphasises the practical implications of optimised biodiesel production, such as reducing environmental pollution by recycling WCO and minimising reliance on fossil fuels. The optimised process meets ASTM standards and exhibits scalability potential for industrial-level production with minor modifications. The models robustness makes it suitable for integration into intelligent manufacturing systems, ensuring consistent biodiesel quality and yield through automated monitoring and control mechanisms. Despite its success, challenges such as feedstock variability and initial setup costs must be addressed. Future studies should focus on adaptive models and energy-efficient processing technologies to enhance scalability and sustainability. This research demonstrates a significant step towards sustainable biofuel production, combining waste management with renewable energy generation. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

Source

Environmental Science and Pollution Research;Volume;32;Issue;52;pp.29487-29501

Date

01-01-2025

Publisher

Springer

Subject

Biodiesel; Fuzzy; NSGA-II; Transesterification; Waste cooking Oil

Coverage

Kavalli K., Mechanical and Automobile Engineering Department, School of Engineering & Technology, CHRIST University, Karnataka, Bengaluru, 560029, India; Hebbar G.S., Mechanical and Automobile Engineering Department, School of Engineering & Technology, CHRIST University, Karnataka, Bengaluru, 560029, India; Rout A., Mechanical and Automobile Engineering Department, School of Engineering & Technology, CHRIST University, Karnataka, Bengaluru, 560029, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISSN: 9441344; CODEN: ESPLE

Format

online

Language

English

Type

Article

Identifier

https://doi.org/10.1007/s11356-025-36079-y

https://www.scopus.com/pages/publications/85219698070?origin=resultslist