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

María Isabel Lamas Galdo, Javier Telmo Miranda, José Manuel Rebollido Lorenzo and Claudio Giovanni Caccia
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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

IJERPH, 2021, vol. 18, issue 23, 1-11

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.

Keywords: engine; emissions; consumption; artificial neural network; multi-criteria decision-making; computational fluid dynamics (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
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