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Incremental modelling of automotive engine performance using LS-SVM
Vong C.M.; Wong P.K.; Zhang R.
2009-11-23
Conference NameIEEE International Conference on Information and Automation (ICIA 2009)
Source Publication2009 IEEE International Conference on Information and Automation, ICIA 2009
Pages1537-1540
Conference DateJUN 22-24, 2009
Conference PlaceZhuhai, PEOPLES R CHINA
Abstract

Modem automotive engines are controlled by the electronic control unit (ECU). The engine performance referred to as output torque is significantly affected by the setup of control parameters in the ECU. Traditional ECU tune-up is done by trial-and-error method through repeated dynamometer tests. LS-SVM (Least Squares Support Vector Machines) is a powerful machine learning technique which can handle complex and nonlinear function estimation problems. It was employed to estimate the above engine performance function. However, current LS-SVM is an offline algorithm, i.e., the estimated torque functions built from LS-SVM can not be updated with the subsequent expensive dynamometer tests for verification. In the paper, online LS-SVM is presented and used for estimating the engine torque functions for precision prediction so that the number of dynamometer tests can be significantly reduced. © 2009 IEEE.

DOI10.1109/ICINFA.2009.5205161
URLView the original
Indexed BySCI
Language英语
WOS Research AreaAutomation & Control Systems ; Computer Science ; Engineering
WOS SubjectAutomation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000277076800276
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Citation statistics
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
DEPARTMENT OF ELECTROMECHANICAL ENGINEERING
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Vong C.M.,Wong P.K.,Zhang R.. Incremental modelling of automotive engine performance using LS-SVM[C],2009:1537-1540.
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