Title :
Neural network modelling of a new injection system for compressed natural gas engines
Author :
Binetti, Giulio ; Lino, Paolo ; Maione, Bruno
Author_Institution :
Dipt. di Elettrotec. ed Elettron., Politec. di Bari, Bari, Italy
Abstract :
The paper describes a neural network approach for modelling a CNG engine. A neural network model, whose structure is mainly based on general information about the system, is built for controlling the rail pressure. The structural identification and the parameter estimation from data gathered on a real engine are described. Simulations show the effectiveness of the proposed modelling.
Keywords :
engines; mechanical engineering computing; neural nets; parameter estimation; CNG engine; compressed natural gas engines; injection system; neural network modelling; parameter estimation; rail pressure; structural identification; Engines; Fuels; Integrated circuit modeling; Mathematical model; Rails; Solenoids; Valves;
Conference_Titel :
IECON 2011 - 37th Annual Conference on IEEE Industrial Electronics Society
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-61284-969-0
DOI :
10.1109/IECON.2011.6119383
