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Using Artificial Neural Networks for Virtual Sensing of Oxygen in a Vehicle Moved by Ethanol

The automotive industry is one of the most important sectors in Brazilian’s economy and all over the world. Recently, this industry has been forced to improve the performance of their produced vehicles and to reduce their costs. One of the landmarks of this transformation was the development of the oxygen sensor, which is one of the main elements of the engine management systems. This work proposes the use of intelligent systems architectures for virtual oxygen sensing in vehicles moved by alcohol. Using supervised artificial neural networks of type multilayer Perceptron, theirs topologies reaches satisfactory results in relation to those obtained by experimental tests.