ANN-based Virtual Sensor for On-line Prediction of In-cylinder Pressure in a Diesel Engine

Abstract This study presents the process design and tune-up of robust artificial neural networks (ANN) to be used as virtual sensors for the diagnosis of a three-cylinder Diesel engine operating at various conditions. Particularly, a feed-forward neural network based on radial basis functions (RBF) is employed. The use of different radial basis functions, and their relevant parameters, is investigated in detail, with their effect on the network accuracy. The RBF network is validated using data not included in training, showing good correspondence between measured and reconstructed pressure signal. The accuracy of the predicted pressure signals is analyzed in terms of mean square error and in terms of a number of pressure-derived parameters. Results are promising in terms of performance and accuracy, both for the predicted pressure signals and for the pressure-derived engine parameters that can be used in a closed loop engine control system.

[1]  David S. Broomhead,et al.  Multivariable Functional Interpolation and Adaptive Networks , 1988, Complex Syst..

[2]  H.P.A. Calis,et al.  Optimum deNOx performance using inferential feedforward reductant flow control , 2000 .

[3]  F. Taglialatela,et al.  Determination of combustion parameters using engine crankshaft speed , 2013 .

[4]  Katarzyna Bizon,et al.  Reconstruction of In-Cylinder Pressure in a Diesel Engine from Vibration Signal Using a RBF Neural Network Model , 2011 .

[5]  Sébastien Candel,et al.  Combustion control and sensors: a review , 2002 .

[6]  Wai Kean Yap,et al.  Comparative analysis of artificial neural networks and dynamic models as virtual sensors , 2013, Appl. Soft Comput..

[7]  Katarzyna Bizon,et al.  Towards On-Line Prediction of the In-Cylinder Pressure in Diesel Engines from Engine Vibration Using Artificial Neural Networks , 2013 .

[8]  Giancarlo Chiatti,et al.  Combustion Characterization in Diesel Engine via Block Vibration Analysis , 2010 .

[9]  Mario Lavorgna,et al.  Use of Vibration Signal for Diagnosis and Control of a Four-Cylinder Diesel Engine , 2011 .

[10]  Satish Chand,et al.  Reconstruction of cylinder pressure for SI engine using recurrent neural network , 2010, Neural Computing and Applications.

[11]  Vasiliki Kazantzi,et al.  On the prediction of properties for diesel / biodiesel mixtures featuring new environmental considerations , 2010 .

[12]  Andrew Ball,et al.  A RBF neural network model for cylinder pressure reconstruction in internal combustion engines , 1996 .