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Fault Monitoring of the Electric Machine in a Hybrid Vehicle
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-7349-1937
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
2013 (English)In: Proceedings of the 7th IFAC Symposium on Advances in Automotive Control, The International Federation of Automatic Control, Elsevier, 2013, Vol. 46, no 21, p. 548-553Conference paper, Published paper (Refereed)
Abstract [en]

A diagnosis system for the electric machine and the power electronics in a hybrid electric vehicle is designed, where the diagnosis system uses a map based model of the system to be monitored. Such a model gives an accurate description of the fault free system, and is therefore suited for fault detectability. However, one drawback using such a model for diagnosis is that fault isolation often requires that the model, in addition to the fault free case, also describes the faulty system, and thereby measurements of the faulty system are needed, which is costly. Another approach is to use a model including physical parameters of interest in the system to be monitored, to also describe the faults’ impact on the system. To achieve good diagnostic performance such a model needs to be accurate, which also is costly. Therefore, in the new approach taken here, two models for the system are used in combination to achieve good fault detectability and isolability; one is a map based model, and one is describing the faults of the system. It is shown that the approach works well and is a promising path to achieve both good fault detectability and isolability performance, without the need for neither measurements of a faulty system nor detailed physical modeling. In a simulation study evaluating the designed diagnosis system all faults are isolated and also accurately estimated.

Place, publisher, year, edition, pages
Elsevier, 2013. Vol. 46, no 21, p. 548-553
Series
IFAC Publications / IFAC Proceedings, ISSN 1474-6670 ; Vol. 46, Issue 21
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:liu:diva-137779DOI: 10.3182/20130904-4-JP-2042.00074OAI: oai:DiVA.org:liu-137779DiVA, id: diva2:1101979
Conference
7th IFAC Symposium on Advances in Automotive Control, The International Federation of Automatic Control, September 4-7, 2013. Tokyo, Japan
Available from: 2017-05-29 Created: 2017-05-29 Last updated: 2021-12-28Bibliographically approved

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Sundström, ChristoferFrisk, ErikNielsen, Lars

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CiteExportLink to record
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  • apa
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Output format
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