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Predictive air-ratio controller for automotive engines based on online neural network: Design and experimental evaluation
Wong, Pak Kin; Wong H.C.; Vong C.M.; Ip W.F.
2010-11-29
Conference Name2010 IEEE/ACIS 9th International Conference on Computer and Information Science
Source PublicationProceedings - 9th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2010
Pages275-279
Conference Date18-20 Aug. 2010
Conference PlaceYamagata, Japan
Abstract

Air-ratio relates closely to pollution reduction, fuel efficiency and driveability among all of the engine control variables. Maintaining the air-ratio to be the stoichiometric value can obtain the best balance between power output and fuel consumption. The paper presents a nonlinear model predictive control algorithm for air-ratio regulation based on online neural network. The control algorithm has been implemented on a real car to test. The actual test results in experiments show that the proposed control algorithm can regulate the engine air-ratio to the stoichiometric value (1.0) under external disturbance with less than 5% tolerance. © 2010 IEEE.

KeywordAir-ratio Automotive Engine Intelligent Control System Neural Network
DOI10.1109/ICIS.2010.157
URLView the original
Indexed ByEI
Language英語English
Scopus ID2-s2.0-78649244448
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Citation statistics
Document TypeConference paper
CollectionDEPARTMENT OF ELECTROMECHANICAL ENGINEERING
Corresponding AuthorWong, Pak Kin
AffiliationUniversity of Macau
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Wong, Pak Kin,Wong H.C.,Vong C.M.,et al. Predictive air-ratio controller for automotive engines based on online neural network: Design and experimental evaluation[C], 2010, 275-279.
APA Wong, Pak Kin., Wong H.C.., Vong C.M.., & Ip W.F. (2010). Predictive air-ratio controller for automotive engines based on online neural network: Design and experimental evaluation. Proceedings - 9th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2010, 275-279.
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