Masters Theses

Title

Implementation of an embedded neural network-based output-feedback controller for spark ignition engines

Alternative Title

Implementation of an embedded neural network based output feedback controller for spark ignition engines

Keywords and Phrases

Exhaust gas recirculation

Abstract

"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.

Department(s)

Electrical and Computer Engineering

Degree Name

M.S. in Computer Engineering

Publisher

University of Missouri--Rolla

Publication Date

Fall 2005

Pagination

ix, 93 leaves

Rights

© 2005 Jonathan Blake Vance, All rights reserved.

Document Type

Thesis - Citation

File Type

text

Language

English

Library of Congress Subject Headings

Neural networks (Computer science)
Spark ignition engines -- Exhaust gas
Nitrogen oxides

Thesis Number

T 8895

Print OCLC #

71003887

Link to Catalog Record

Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.

http://laurel.lso.missouri.edu/record=b5626580~S5

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