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CNG engine air-fuel ratio control using fuzzy neural networks

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4 Author(s)
Zhang Weige ; Dept. of Electr. Eng., Northern Jiaotong Univ., Beijing, China ; Jiang Jiuchun ; Xia Yuan ; Zhou Xide

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.

Published in:

Autonomous Decentralized System, 2002. The 2nd International Workshop on

Date of Conference:

6-7 Nov. 2002