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.
Neural network modelling of a new injection system for compressed natural gas engines / Binetti, G.; Lino, Paolo; Maione, B.. - STAMPA. - (2011), pp. 628-633. (Intervento presentato al convegno 37th Annual Conference of the IEEE Industrial Electronics Society, IECON 2011 tenutosi a Melbourne, Australia nel November 7-10, 2011) [10.1109/IECON.2011.6119383].
Neural network modelling of a new injection system for compressed natural gas engines
LINO, Paolo;
2011-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
