Implementation of an embedded neural network-based output-feedback controller for spark ignition engines
Implementation of an embedded neural network based output feedback controller for spark ignition engines
Keywords and Phrases
Exhaust gas recirculation
"A neural-network-based output-feedback controller is employed on a spark ignition engine to control fuel input during lean operation for fuel-air equivalence ratios less than 1.0 and in the presence of exhaust gas recirculation (EGR). At lean operating conditions, the engine exhibits significant cycle-to-cycle bifurcation of heat release - a characteristic of instability. The controller reduces the cyclic dispersion of heat release by minimizing the error between target heat release and measured engine heat release for every engine cycle in real time. Consequences of operating a spark-ignition engine under lean conditions are reduction of harmful NOx emissions and an improvement in fuel economy. When the controller is operating the engine, experimental results show that lean operation at decreased equivalence ratios returns similar results to lean engine operation from increased levels of EGR"--Abstract, leaf iii.
Electrical and Computer Engineering
M.S. in Computer Engineering
University of Missouri--Rolla
ix, 93 leaves
© 2005 Jonathan Blake Vance, All rights reserved.
Thesis - Citation
Library of Congress Subject Headings
Neural networks (Computer science)
Spark ignition engines -- Exhaust gas
Print OCLC #
Link to Catalog Record
Vance, Jonathan B., "Implementation of an embedded neural network-based output-feedback controller for spark ignition engines" (2005). Masters Theses. 5832.
This document is currently not available here.