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Authors
Affiliations
1 Mechanical Engineering, Sri Sai Ram Engineering College, Chennai-44, IN
2 M.N.R Engineering College, Hyderabad, IN
3 Mechanical Engineering, Udaya School of Engineering, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 4, No 11 (2012), Pagination: 612-617
Abstract
This paper presents the implementation of functional back propagation algorithm (FUBPA) for estimating the power, torque, specific fuel consumption and presence of carbon monoxide, hydrocarbons in the emission of a direct injection diesel engine. Experimental readings were obtained using the biodiesel prepared from the waste cooking oil collected from the canteen of Sri Sairam Engineering College, India. This waste cooking oil was due to the preparation of varieties of food (vegetables fried and non vegetarian). To obtain the biodiesel, transesterification was done in chemical lab for more than a week, and the biodiesel was obtained. The biodiesel was mixed in proportions of 10%, 20%, 30%, 40%, 50% with remaining combinations of the diesel supplied by the Indian government. Variable compression ratio (VCR) diesel engine with single cylinder, 4 stroke diesel type was used.
The outputs of the engine as power, torque and specific fuel consumption were obtained from the computational facility attached to the engine. The data collected for different input conditions of the engine was further used to train FUBPA.
The trained FUBPA network was further used to predict the power, torque and SFC for different speed, biodiesel and diesel combinations and full load conditions. The estimation performance of the FUBPA network is discussed.
Keywords
Functional Back Propagation Algorithm, Waste Cooking Oil, Biodiesel.
