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A Time-Skew Resilient Online Condition Monitoring Technique for Power MOSFETs Based on ON-State Resistance Estimation
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.ORCID iD: 0000-0001-5919-2308
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.ORCID iD: 0000-0002-1136-581x
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.ORCID iD: 0000-0002-1755-1365
Linköping University, Linköping, Sweden.
2024 (English)In: Proceedings 9th IEEE Southern Power Electronics Conference, SPEC 2024, Institute of Electrical and Electronics Engineers (IEEE) , 2024Conference paper, Published paper (Refereed)
Abstract [en]

This article presents a unique method of extracting the ON-state resistance of metal-oxide-semiconductor field-effect transistors (MOSFETs) used in power electronic systems. The proposed method uses ON-state voltage measurements of the device-under-test as well as the load current. Contrary to prior-art solutions, the proposed method does not require estimating the device currents, but rather directly uses the load current measurements. This reduces the computational effort for estimation without reducing the estimation accuracy. Moreover, it is shown that unlike time-based estimation techniques such as the recursive least-squares estimation method, the proposed solution does not require ON-state voltage and current measurements to be accurately synchronized. The extracted ON-state resistance can be used for online condition monitoring of semiconductors, as well as for estimating the junction temperature. The efficacy of the proposed method is verified experimentally under constant and variable load conditions. Moreover, the extracted resistance values from the online setup are compared to offline measurements from an industrial curve tracer, where an overall estimation error of less than 1% is observed.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2024.
Keywords [en]
Condition monitoring, health monitoring, on-state resistance, online estimation, reliability, semiconductor devices, state of health
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-362226DOI: 10.1109/SPEC62217.2024.10893107ISI: 001445813800048Scopus ID: 2-s2.0-105001107560OAI: oai:DiVA.org:kth-362226DiVA, id: diva2:1951020
Conference
9th IEEE Southern Power Electronics Conference, SPEC 2024, Brisbane, Australia, Dec 2 2024 - Dec 5 2024
Note

QC 20250414

Available from: 2025-04-09 Created: 2025-04-09 Last updated: 2025-06-12Bibliographically approved

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Asoodar, MohsenNahalparvari, MehrdadNee, Hans-Peter

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