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Journal of Zhejiang University SCIENCE A
ISSN 1673-565X(Print), 1862-1775(Online), Monthly
2002 Vol.3 No.5 P.543-548
A method for predicting in-cylinder compound combustion emissions
Abstract: This paper presents a method using a large steady-state engine operation data matrix to provide necessary information for successfully training a predictive network, while at the same time eliminating errors produced by the dispersive effects of the emissions measurement system. The steady-state training conditions of compound fuel allow for the correlation of time-averaged in-cylinder combustion variables to the engine-out NOx and HC emissions. The error back-propagation neural network (EBP) is then capable of learning the relationships between these variables and the measured gaseous emissions, and then interpolating between steady-state points in the matrix. This method for NOx and HC has been proved highly successful.
Key words: Back-propagation neural network (EBP), Compound fuel, Emissions, Prediction
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Open peer comments: Debate/Discuss/Question/Opinion
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DOI:
10.1631/jzus.2002.0543
CLC number:
TK421+.5
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Received:
2001-10-08
Revision Accepted:
2002-01-20
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