Abstract
This study optimised the production of biodiesel using response surface methodology (RSM), genetic algorithm (GA), and cuckoo search algorithm (CSA). Optimal conditions resulted in a microalgae methyl ester yield of 97.55%. The effects of a novel ternary blend of diethyl-ether and microalgae oil methyl ester with diesel on engine performance and emission characteristics were also investigated. Results showed that the ternary fuel blend (B20DEE10) improved engine performance and reduced emissions by 10%–30% compared to diesel. The study provides valuable insights into biodiesel production optimisation and the blending of novel ternary fuels for reducing environmental pollution and improving energy sustainability.
| Original language | English |
|---|---|
| Pages (from-to) | 294-313 |
| Number of pages | 20 |
| Journal | International Journal of Global Warming |
| Volume | 31 |
| Issue number | 3 |
| DOIs | |
| State | Published - 2023 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:Copyright © 2023 Inderscience Enterprises Ltd.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy
Keywords
- biodiesel production
- CSA
- cuckoo search algorithm
- emissions
- engine performance
- genetic algorithm
- response surface methodology
- RSM
ASJC Scopus subject areas
- Global and Planetary Change
- Atmospheric Science
- Management, Monitoring, Policy and Law
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