Neural network control of air-to-fuel ratio in a bi-fuel engine

In this paper, a neural network based control system is proposed for fine control of intake air/fuel ratio in a bi-fuel engine. This control system is an add-on module for an existing vehicle manufacturer´s Electronic Control Unit (ECU). Typically the Electronic Control Unit (ECU) is calibrated for gasoline and provides a good control of intake air/fuel ratio with gasoline. The neural network based control system is developed to allow the conversion of a gasoline ECU to a bi-fuel form with Compressed Natural Gas (CNG) at minimal cost. The effectiveness of the neural control system is demonstrated by using a simulation of a Dodge four-stroke bi-fuel engine.