Predicción de gases de escape en motores otto mediante la PME empleando RNA

Wilmer Contreras, Yasmany Aguilar, Pablo León, Daniel Piña

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

Resumen

This document deals with the prediction of exhaust gases from a provoked ignition engine (MEP), through its mean effective pressure (PME), through the use of artificial neural networks (ANN). The methodology applied consists of acquiring signals from the PME, load, revolutions per minute (rpm) and the manifold absolute pressure sensor (MAP) of the engine of the armfield dynamometric bench cm11, of which it obtains a database and that through statistical analysis it is determined that to predict polluting emissions it is necessary to apply cascade RNA, that is, first the engine load is predicted and therefore the exhaust gases, with which a rating error less than 10e-4. For the validation of this project an experimental analysis is carried out, which consists in acquiring new engine data to check the percentage of error between the values simulated by the RNAs and the actual values, where there is an error of less than 2% and 3% for the prediction of the load and the exhaust gases respectively.

Título traducido de la contribuciónExhaust gas prediction in otto engines using PME and RNA
Idioma originalEspañol
Páginas (desde-hasta)351-365
Número de páginas15
PublicaciónRISTI - Revista Iberica de Sistemas e Tecnologias de Informacao
Volumen2020
N.ºE30
EstadoPublicada - jun. 2020

Palabras clave

  • Dynamometer bench
  • Exhaust gases
  • Load percentage
  • PME
  • Prediction

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