LAPSE:2019.0789
Published Article
LAPSE:2019.0789
A Soft Sensor-Based Fault-Tolerant Control on the Air Fuel Ratio of Spark-Ignition Engines
July 26, 2019
The air/fuel ratio (AFR) regulation for spark-ignition (SI) engines has been an essential and challenging control problem for engineers in the automotive industry. The feed-forward and feedback scheme has been investigated in both academic research and industrial application. The aging effect can often cause an AFR sensor fault in the feedback loop, and the AFR control performance will degrade consequently. In this research, a new control scheme on AFR with fault-tolerance is proposed by using an artificial neural network model based on fault detection and compensation, which can provide the satisfactory AFR regulation performance at the stoichiometric value for the combustion process, given a certain level of misreading of the AFR sensor.
Record ID
Keywords
air/fuel ratio (AFR), artificial neural networks, fault-tolerant control, nonlinear dynamics, spark-ignition (SI) engines
Subject
Suggested Citation
Zhai YJ, Yu DL, Qian KJ, Lee S, Theera-Umpon N. A Soft Sensor-Based Fault-Tolerant Control on the Air Fuel Ratio of Spark-Ignition Engines. (2019). LAPSE:2019.0789
Author Affiliations
Zhai YJ: Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, 111, Ren’ai Road Duzhu Lake Higher Education Town SIP, Suzhou 215123, China
Yu DL: Control Research Group, Liverpool John Moores University, Liverpool L3 5UA, UK
Qian KJ: Suzhou Power Supply Company, Suzhou 215000, China
Lee S: Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, 111, Ren’ai Road Duzhu Lake Higher Education Town SIP, Suzhou 215123, China; Centre for Smart Grid and Information Convergence, Xi’an Jiaotong-Liverpool Univer
Theera-Umpon N: Biomedical Engineering Centre, Chiang Mai University, Chiang Mai 50200, Thailand; Electrical Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand [ORCID]
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Yu DL: Control Research Group, Liverpool John Moores University, Liverpool L3 5UA, UK
Qian KJ: Suzhou Power Supply Company, Suzhou 215000, China
Lee S: Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, 111, Ren’ai Road Duzhu Lake Higher Education Town SIP, Suzhou 215123, China; Centre for Smart Grid and Information Convergence, Xi’an Jiaotong-Liverpool Univer
Theera-Umpon N: Biomedical Engineering Centre, Chiang Mai University, Chiang Mai 50200, Thailand; Electrical Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand [ORCID]
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Journal Name
Energies
Volume
10
Issue
1
Article Number
E131
Year
2017
Publication Date
2017-01-20
Published Version
ISSN
1996-1073
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Original Submission
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PII: en10010131, Publication Type: Journal Article
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Published Article
LAPSE:2019.0789
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doi:10.3390/en10010131
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Version History
[v1] (Original Submission)
Jul 26, 2019
Verified by curator on
Jul 26, 2019
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v1
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https://psecommunity.org/LAPSE:2019.0789
Original Submitter
Calvin Tsay
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