{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/110870"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/110870","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"In situ power-loss estimation of IGBT modules","abstract":"A fault detection and prediction method for insulated-gate bipolar transistors (IGBTs) has been improved over the past decades to reduce system downtime. In situ lifetime estimation of IGBT modules has been challenging due to a number of requirements: the necessity to operate at high voltage in the switching environment and the measurement precision of the gate-threshold voltage or collector-to-emitter voltage. This thesis presents a wear-fatigue estimation framework that consists of collector-to-emitter measurement, power loss calculation, and thermal lifetime prediction model. The measurement circuit enables the estimation of power loss across a variety of IGBT modules with minimum impact on system reliability.","abstract_html":"A fault detection and prediction method for insulated-gate bipolar transistors (IGBTs) has been improved over the past decades to reduce system downtime. In situ lifetime estimation of IGBT modules has been challenging due to a number of requirements: the necessity to operate at high voltage in the switching environment and the measurement precision of the gate-threshold voltage or collector-to-emitter voltage. This thesis presents a wear-fatigue estimation framework that consists of collector-to-emitter measurement, power loss calculation, and thermal lifetime prediction model. The measurement circuit enables the estimation of power loss across a variety of IGBT modules with minimum impact on system reliability.","abstract_has_math":false,"creators":["Jin, Qichen"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Banerjee, Arijit"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-09-17T04:06:56Z","date_published":"2021-09-17T04:06:56Z","updated_at":"2026-07-22T22:24:52Z","subjects":["IGBT","real-time monitoring","lifetime estimation"],"languages":["en"],"rights":["Copyright 2021 Qichen Jin"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/110870","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Banerjee, Arijit"]},{"key":"dc:creator","label":"Author","values":["Jin, Qichen"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2021-09-17T04:06:56Z","2023-09-17T04:07:01Z","2021-04-29","2021-05"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["IGBT","real-time monitoring","lifetime estimation"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2021 Qichen Jin"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/110870"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["A fault detection and prediction method for insulated-gate bipolar transistors (IGBTs) has been improved over the past decades to reduce system downtime. In situ lifetime estimation of IGBT modules has been challenging due to a number of requirements: the necessity to operate at high voltage in the switching environment and the measurement precision of the gate-threshold voltage or collector-to-emitter voltage. This thesis presents a wear-fatigue estimation framework that consists of collector-to-emitter measurement, power loss calculation, and thermal lifetime prediction model. The measurement circuit enables the estimation of power loss across a variety of IGBT modules with minimum impact on system reliability.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2023-05-01","The student, Qichen Jin, accepted the attached license on 2021-04-29 at 10:53.","The student, Qichen Jin, submitted this Thesis for approval on 2021-04-29 at 10:58.","This Thesis was approved for publication on 2021-04-29 at 15:19.","DSpace SAF Submission Ingestion Package generated from Vireo submission #16596 on 2021-09-16 at 20:14:39","Made available in DSpace on 2021-09-17T04:06:56Z (GMT). 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In situ lifetime estimation of IGBT modules has been challenging due to a number of requirements: the necessity to operate at high voltage in the switching environment and the measurement precision of the gate-threshold voltage or collector-to-emitter voltage. This thesis presents a wear-fatigue estimation framework that consists of collector-to-emitter measurement, power loss calculation, and thermal lifetime prediction model. The measurement circuit enables the estimation of power loss across a variety of IGBT modules with minimum impact on system reliability.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2023-05-01","The student, Qichen Jin, accepted the attached license on 2021-04-29 at 10:53.","The student, Qichen Jin, submitted this Thesis for approval on 2021-04-29 at 10:58.","This Thesis was approved for publication on 2021-04-29 at 15:19.","DSpace SAF Submission Ingestion Package generated from Vireo submission #16596 on 2021-09-16 at 20:14:39","Made available in DSpace on 2021-09-17T04:06:56Z (GMT). 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