Chan, Kinyip, Ordys, Andrzej, Duran, Olga, Volkov, Konstantin and Deng, Jiamei (2014) Adaptive neuro-fuzzy method to estimate virtual SI engine fuel composition using residual gas parameters. In: 10th International Conference on Control (Control 2014); 9 - 11 Jul 2014, Loughborough.

Abstract

This paper addresses computer engine simulation with an adaptive neuro fuzzy method to estimate the fuel composition by using the residual gas information. The availability of fuel composition is divided into. The actual ready mixed composition provided from suppliers, named in gasoline, contains different name hydro-carbon atoms. The composition is unknown, but varies with standard based on engine combustion profile. This study researches the idea of further engine control on fuel composition to improve engine performance and reduce on emissions. Fuel composition can be estimated using combustion product after gas exchange. This study investigates a computer based engine model which uses Adaptive Neuro-Fuzzy Interface System (ANFIS) to identify the fuel composition. The residual composition contains the level of Carbon Dioxide (CO2), Oxygen (O), Carbon Monoxide (CO) and Nitric Oxide (NO) which developed the network to estimate the Hydrocarbon level of original fuel input. Results show that ANFIS control is reasonably distinguish three different fuel compositions in the tests.

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