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Internal Modifications to Optimize Pollution and Emissions of Internal Combustion Engines through Multiple-Criteria Decision-Making and Artificial Neural Networks

Author

Listed:
  • María Isabel Lamas Galdo

    (Escuela Politécnica de Ingeniería de Ferrol, Universidade da Coruña, 15403 Ferrol, Spain)

  • Javier Telmo Miranda

    (Escuela Técnica Superior de Ingenieros Industriales, UNED, 28040 Madrid, Spain)

  • José Manuel Rebollido Lorenzo

    (IES de Valga, 36645 Valga, Spain)

  • Claudio Giovanni Caccia

    (Department of Aerospace Engineering, Politecnico di Milano, 20156 Milan, Italy)

Abstract

The present work proposes several modifications to optimize both emissions and consumption in a commercial marine diesel engine. A numerical model was carried out to characterize the emissions and consumption of the engine under several performance parameters. Particularly, five internal modifications were analyzed: water addition; exhaust gas recirculation; and modification of the intake valve closing, overlap timing, and cooling water temperature. It was found that the result on the emissions and consumption presents conflicting criteria, and thus, a multiple-criteria decision-making model was carried out to characterize the most appropriate parameters. In order to analyze a high number of possibilities in a reasonable time, an artificial neural network was developed.

Suggested Citation

  • María Isabel Lamas Galdo & Javier Telmo Miranda & José Manuel Rebollido Lorenzo & Claudio Giovanni Caccia, 2021. "Internal Modifications to Optimize Pollution and Emissions of Internal Combustion Engines through Multiple-Criteria Decision-Making and Artificial Neural Networks," IJERPH, MDPI, vol. 18(23), pages 1-11, December.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:23:p:12823-:d:695595
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    References listed on IDEAS

    as
    1. M. I. Lamas & C. G. Rodriguez, 2019. "NOx Reduction in Diesel-Hydrogen Engines Using Different Strategies of Ammonia Injection," Energies, MDPI, vol. 12(7), pages 1-13, April.
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    3. Hua Tan, Kim & Peng Lim, Chee & Platts, Ken & Shen Koay, Hooi, 2006. "An intelligent decision support system for manufacturing technology investments," International Journal of Production Economics, Elsevier, vol. 104(1), pages 179-190, November.
    4. Golmohammadi, Davood, 2011. "Neural network application for fuzzy multi-criteria decision making problems," International Journal of Production Economics, Elsevier, vol. 131(2), pages 490-504, June.
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