A neural network air-fuel ratio estimator

The paper suggests that a cheap, reliable method of measuring or estimating engine Air-Fuel Ratio (AFR) is needed for effective control. The behaviour of the intake manifold, which is the main cause of the control problem, is discussed, and the use of neural networks for estimating AFR is suggested. The main features of such networks in system modelling are given and the training of two different networks using a simulator is described. The results of tests carried out on the trained networks are given and discussed, and it is concluded that such work deserves further research.