Intelligent System Architecture for Virtual Sensing of Oxygen in Bi-Fuel Vehicles

The automotive industry is one of the most important sectors in Brazilian's economy and all over the world. In recent years, this industry has been forced to improve the performance of their 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 of bi-fuel vehicles, using multilayer Perceptron artificial neural networks. The implemented topologies reach satisfactory results, with mean relative errors less than 1% in thousands of topologies. It was also noted that the neural network trained with E20 and E100, using subsets of universal set, it is the most appropriate to have a virtual sensing of oxygen in bi-fuel vehicles.