Neural Networks Techniques for Monitoring and Control of Internal Combustion Engines

Engine manufacturers are constantly striving to find new and improved techniques for the monitoring and control of motor-vehicle engines. The aim is to achieve reduced exhaust emissions and superior fuel economy. Intelligent-systems techniques, such as neural networks and fuzzy methods, are attractive for application in this area because of their capabilities in pattern-recognition, modelling and control. For this reason, the use of neural networks in the monitoring and control of motorvehicle engines is becoming an area of research which is receiving increasing attention from both the academic and commercial research communities. This paper reviews the way in which neural networks can be applied to gasoline or spark-ignition motor vehicle engines for combustion monitoring, on-board diagnostics and enhanced control strategies. It also describes research in these areas being carried out at the Transfrontier Centre for Automotive Research at the University of Brighton.

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