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Fault diagnosis algorithm based on switching function for boost converters

Title
Fault diagnosis algorithm based on switching function for boost converters
Authors
Cho, H.-K.[Cho, Hyun Ki]Kwak, S.-S.[Kwak, Sang Shin]Lee, S.-H.[Lee, Seong Hun]
DGIST Authors
Lee, S.-H.[Lee, Seong Hun]
Issue Date
2015
Citation
International Journal of Electronics, 102(7), 1229-1243
Type
Article
Article Type
Article
Keywords
BOOST ConverterCircuit ConfigurationsDC-DC Boost ConverterDC-DC ConvertersDiagnosis AlgorithmsDiscontinuous CurrentFault DetectionFault Diagnosis AlgorithmInductor CurrentsLearning AlgorithmsOpen- and Short-Circuit FaultsOpen-Circuit FaultPower Conversion SystemsReliabilityShort-Circuit FaultSwitching Functions
ISSN
0020-7217
Abstract
A fault diagnosis algorithm, which is necessary for constructing a reliable power conversion system, should detect fault occurrences as soon as possible to protect the entire system from fatal damages resulting from system malfunction. In this paper, a fault diagnosis algorithm is proposed to detect open- and short-circuit faults that occur in a boost converter switch. The inductor voltage is abnormally kept at a positive DC value during a short-circuit fault in the switch or at a negative DC value during an open-circuit fault condition until the inductor current becomes zero. By employing these abnormal properties during faulty conditions, the inductor voltage is compared with the switching function to detect each fault type by generating fault alarms when a fault occurs. As a result, from the fault alarm, a decision is made in response to the fault occurrence and the fault type in less than two switching time periods using the proposed algorithm constructed in analogue circuits. In addition, the proposed algorithm has good resistivity to discontinuous current-mode operation. As a result, this algorithm features the advantages of low cost and simplicity because of its simple analogue circuit configuration. © 2014 © 2014 Taylor & Francis.
URI
http://hdl.handle.net/20.500.11750/1580
DOI
10.1080/00207217.2014.966780
Publisher
Taylor and Francis Ltd.
Related Researcher
Files:
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Collection:
ETCETC
Convergence Research Center for Future Automotive Technology1. Journal Articles


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