FAULT ACCOMMODATION OF MASS AIR FLOW SENSORS IN DIESEL AUTOMOTIVE ENGINES

Giovanni Betta, Domenico Capriglione, Antonio Pietrosanto

Abstract

This paper deals with the design and the application of Artificial Neural Networks to the fault accommodation of the mass air flow meter in diesel engines. Several architectures are proposed and tested. In order to verify their real applicability to the automotive context, making use of suitable graphical tools and computational load indexes, their performance was compared in terms of accuracy and resource requirements.

Keywords

Instrument fault accommodation, Artificial Neural Networks (ANNs), Mass air flow meter

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PWC-2006-TC10-009u.pdf

DOI

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IMEKO TC

TC10 - Measurement for Diagnostics, Optimization and Control

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