CNG engine air-fuel ratio control using fuzzy neural networks

Accurate control of the air fuel ratio in a spark-ignition engine is critical to satisfying future emissions regulators. The goal of this research is to explore the use of fuzzy neural networks as a means of precisely controlling the air fuel ratio of a lean-burn compressed natural gas (CNG) engine. A control, without based on engine model, has been utilized to construct a feedforward/feedback control scheme to regulate air fuel ratio. Using fuzzy neural networks, a fuzzy neural hybrid controller is obtained based on PI controller. The new controller, which can adjust self parameters online, has been tested in transient air fuel ratio control of engine.