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http://dx.doi.org/10.6109/jkiice.2017.21.2.395

The injection petrol control system about CMAC neural networks  

Han, Ya-Jun (Department of Electronic Engineering, Gyeongnam National University of Science and Technology)
Tack, Han-Ho (Department of Electronic Engineering, Gyeongnam National University of Science and Technology)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.21, no.2, 2017 , pp. 395-400 More about this Journal
Abstract
The paper discussed the air-to-fuel ratio control of automotive fuel-injection systems using the cerebellar model articulation controller(CMAC) neural network. Because of the internal combustion engines and fuel-injection's dynamics is extremely nonlinear, it leads to the discontinuous of the fuel-injection and the traditional method of control based on table look up has the question of control accuracy low. The advantages about CMAC neural network are distributed storage information, parallel processing information, self-organizing and self-educated function. The unique structure of CMAC neural network and the processing method lets it have extensive application. In addition, by analyzing the output characteristics of oxygen sensor, calculating the rate of fuel-injection to maintain the air-to-fuel ratio. The CMAC may easily compensate for time delay. Experimental results proved that the way is more good than traditional for petrol control and the CMAC fuel-injection controller can keep ideal mixing ratio (A/F) for engine at any working conditions. The performance of power and economy is evidently improved.
Keywords
CMAC neural network; automobile engine; injection petrol control; ideal mixing ratio;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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