The present study proposes the use of a MLP neural network to model the relationship between the engine crankshaft speed and parameters derived from the incylinder pressure cycle. This allows to have an indirect measure of cylinder pressure permitting a real time evaluation of combustion quality. The structure of the model and the training procedure is outlined in the paper. The application of the model is demonstrated on a single-cylinder engine with data from a wide range of speed and load. Results confirm that a good estimation of combustion pressure parameters can be obtained by means of a suitable processing of crankshaft speed signal.
Use of engine crankshaft speed for determination of cylinder pressure parameters
Merola SS;Vaglieco BM
2009
Abstract
The present study proposes the use of a MLP neural network to model the relationship between the engine crankshaft speed and parameters derived from the incylinder pressure cycle. This allows to have an indirect measure of cylinder pressure permitting a real time evaluation of combustion quality. The structure of the model and the training procedure is outlined in the paper. The application of the model is demonstrated on a single-cylinder engine with data from a wide range of speed and load. Results confirm that a good estimation of combustion pressure parameters can be obtained by means of a suitable processing of crankshaft speed signal.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
