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

Author

Gnanam, Gnanaprakash ; Habibi, Saeid R. ; Burton, Richard T. ; Sulatisky, Mike T.

Author_Institution

Dept. of Mech. Eng., Saskatchewan Univ., Saskatoon, Sask., Canada

fYear

2003

fDate

8-8 Oct. 2003

Firstpage

152

Lastpage

157

Abstract

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.

Keywords

fuel optimal control; intelligent control; internal combustion engines; neural nets; petroleum; CNG; Dodge four stroke bifuel engine; ECU; compressed natural gas; gasoline; intake air/fuel ratio control; intelligent control; neural control system; neural network control; vehicle manufacturers electronic control unit;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control. 2003 IEEE International Symposium on

Conference_Location

Houston, TX, USA

ISSN

2158-9860

Print_ISBN

0-7803-7891-1

Type

conf

DOI

10.1109/ISIC.2003.1253930

Filename

1253930