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An elite approach to re-design Aquila optimizer for efficient AFR system control

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  • Davut Izci
  • Serdar Ekinci
  • Abdelazim G Hussien

Abstract

Controlling the air-fuel ratio system (AFR) in lean combustion spark-ignition engines is crucial for mitigating emissions and addressing climate change. In this regard, this study proposes an enhanced version of the Aquila optimizer (ImpAO) with a modified elite opposition-based learning technique to optimize the feedforward (FF) mechanism and proportional-integral (PI) controller parameters for AFR control. Simulation results demonstrate ImpAO’s outstanding performance compared to state-of-the-art algorithms. It achieves a minimum cost function value of 0.6759, exhibiting robustness and stability with an average ± standard deviation range of 0.6823±0.0047. The Wilcoxon signed-rank test confirms highly significant differences (p

Suggested Citation

  • Davut Izci & Serdar Ekinci & Abdelazim G Hussien, 2023. "An elite approach to re-design Aquila optimizer for efficient AFR system control," PLOS ONE, Public Library of Science, vol. 18(9), pages 1-22, September.
    • Handle: RePEc:plo:pone00:0291788
    DOI: 10.1371/journal.pone.0291788
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    References listed on IDEAS

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    1. Lei Meng & Xiaofeng Wang & Chunnian Zeng & Jie Luo, 2019. "Adaptive Air-Fuel Ratio Regulation for Port-Injected Spark-Ignited Engines Based on a Generalized Predictive Control Method," Energies, MDPI, vol. 12(1), pages 1-19, January.
    2. Jo, Seongin & Cha, Junepyo & Park, Suhan, 2022. "Exhaust emission characteristics of stoichiometric combustion applying to diesel particulate filter(DPF) and three-way catalytic converter(TWC)," Energy, Elsevier, vol. 254(PB).
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