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Revolutionizing green fuels through artificial intelligence-driven optimization: A life cycle assessment approach to minimize the environmental impacts of Baobab seeds in green diesel synthesis

Author

Listed:
  • Elendu, Collins Chimezie
  • Pei, Liang
  • Yang, Fan
  • Wufuer, Rehemanjiang
  • Duo, Jia
  • Duan, Pei-Gao

Abstract

This investigation aimed to assess the environmental consequences of using a blend of baobab seed oil green diesel (BSO-GD) (B20) and low-sulfur diesel (LSB0) in a 15-kW test bed under full-load conditions. The adaptive neuro-fuzzy inference system (ANFIS) approach was integrated to optimize the production parameters. The results revealed a 36.8 wt% BSO content, with an unsaturated fatty acid content of approximately 83.49 %. The ANFIS-AI model indicated that higher cetane numbers, purity, yield, and lower viscosity could be achieved at a methanol–oil ratio of 14:1–15:1, a reaction temperature of 60–62 °C, and a maximum catalyst dosage of 6 wt% during BSO-GD synthesis. BSO-GD (B20) demonstrated a 5.7 % improvement in fuel economy compared with LSB0, with an enhanced thermal efficiency of 39.1 % versus 35.9 % for LSB0. Emissions testing revealed a 59.2 % reduction in CO and a 28.5 % reduction in HC at engine speeds of 1400–1900 rpm. Life cycle assessment indicated that BSO-GD (B20) has fewer environmental impacts than LSB0 does, with effect drop values of 18.77 %, 29.1 %, 36.52 %, and 12 % for the ozone layer depletion potential, global warming potential, ecotoxicity potential, and eutrophication potential, respectively.

Suggested Citation

  • Elendu, Collins Chimezie & Pei, Liang & Yang, Fan & Wufuer, Rehemanjiang & Duo, Jia & Duan, Pei-Gao, 2025. "Revolutionizing green fuels through artificial intelligence-driven optimization: A life cycle assessment approach to minimize the environmental impacts of Baobab seeds in green diesel synthesis," Renewable Energy, Elsevier, vol. 248(C).
    • Handle: RePEc:eee:renene:v:248:y:2025:i:c:s0960148125006743
    DOI: 10.1016/j.renene.2025.123012
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