In this paper, a further step along a research line concerning the set up of a Fault Diagnosis system for OBD-II purpose is presented. The suitability of Artificial Neural Networks for the use as engine simulation modules in the framework of a software redundancy approach has been analyzed. Experimental tests were performed, by acquiring four main engine operational parameters. Using this knowledge base, the performance of a wide variety of different Net Types was analyzed and discussed. Peculiar aspects of the possible industrial applications of this methodology are also deeply examined.
Prediction of Engine Operational Parameters for On Board Diagnostics Using a Free Model Technology
GRIMALDI, Carlo Nazareno;MARIANI, Francesco
2000
Abstract
In this paper, a further step along a research line concerning the set up of a Fault Diagnosis system for OBD-II purpose is presented. The suitability of Artificial Neural Networks for the use as engine simulation modules in the framework of a software redundancy approach has been analyzed. Experimental tests were performed, by acquiring four main engine operational parameters. Using this knowledge base, the performance of a wide variety of different Net Types was analyzed and discussed. Peculiar aspects of the possible industrial applications of this methodology are also deeply examined.File in questo prodotto:
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