DocumentCode
469290
Title
Prediction of Engine Emissions through Fuzzy Logic Modeling
Author
Bose, N. ; Kumar, N. Senthil
Author_Institution
Mepco Schlenk Eng. Coll., Tamil Nadu
Volume
1
fYear
2007
fDate
13-15 Dec. 2007
Firstpage
420
Lastpage
428
Abstract
Pollution is a major problem for the present generation. The pollution from internal combustion engines contribute to nearly 30% of the total atmospheric pollution. Of the two engines namely petrol and diesel, the later contributes more smoke and Oxides of nitrogen (NOx) harmful to the health and environment. Prediction of these emissions would help in reducing them to a large extent. In this paper, the prediction of smoke and NOx using fuzzy logic has been attempted. Fuzzy logic is a multi-valued logic that allows intermediate values to be defined between conventional evaluations. The input parameters for prediction of emissions considered are Peak pressure, Load, Indicated mean effective pressure, Ignition delay and Combustion duration. Rules have been framed based on the engine system. The output parameters are pollutants NOx and smoke. The comparison between the actual experimental readings and the values through fuzzy logic shows that there is a good correlation. Once the fuzzy logic model has been validated, emissions can be predicted for any intermediate load conditions in the absence of the pollutant measurement devices, thus helping the manufacturers to meet the Euro norms for emission regulations.
Keywords
air pollution; fuzzy logic; internal combustion engines; atmospheric pollution; emission regulations; engine emission; fuzzy logic modeling; internal combustion engines; Air pollution; Atmospheric modeling; Diesel engines; Fuzzy logic; Ignition; Internal combustion engines; Multivalued logic; Nitrogen; Petroleum; Predictive models;
fLanguage
English
Publisher
ieee
Conference_Titel
Conference on Computational Intelligence and Multimedia Applications, 2007. International Conference on
Conference_Location
Sivakasi, Tamil Nadu
Print_ISBN
0-7695-3050-8
Type
conf
DOI
10.1109/ICCIMA.2007.214
Filename
4426616
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