{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/95407"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/95407","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Electromagnetic-thermal modeling for high-frequency air-core permanent magnet motor of aircraft application","abstract":"A 1 MW high-frequency air-core permanent-magnet (PM) motor, with power density over 13.8 kW/kg (8 hp/lb) and efficiency over 96\\%, is proposed for NASA hybrid-electric aircraft application. In order to maximize power density of the proposed motor topology, a large-scale multi-physics optimization is needed to obtain the best design candidates, which is not favorable for current electrical machine software. Therefore, developing electromagnetic (EM) and thermal analytical methods with computational efficiency and decent accuracy is a key enabling factor for future multi-physics optimization of motor power density. In this thesis, the detailed development process of electromagnetic analytical modeling for the proposed machine will be presented and verified with finite element analysis (FEA). Corresponding heat loads, including electrical and mechanical losses, will be quantified rigorously to assess efficiency and prepare for the following thermal analysis. Furthermore, accurate physical-thermal conductivities of different machine components are required to eliminate uncertainties in thermal performance prediction. One arising challenge is to quantify the equivalent thermal conductivity of a complicated composite component --- the winding --- which is also the most critical one regarding overheating risks. Detailed methods of quantifying winding equivalent thermal conductivity will be presented, discussed, and verified with a bench test. The last step in EM-thermal modeling is using a simplified thermal equivalent circuit to quickly detect hotspot temperature and therefore to eliminate infeasible machine designs efficiently. Similar to EM modeling, rigorous thermal analytical modeling will be presented and verified with FEA results.","abstract_html":"A 1 MW high-frequency air-core permanent-magnet (PM) motor, with power density over 13.8 kW/kg (8 hp/lb) and efficiency over 96\\%, is proposed for NASA hybrid-electric aircraft application. In order to maximize power density of the proposed motor topology, a large-scale multi-physics optimization is needed to obtain the best design candidates, which is not favorable for current electrical machine software. Therefore, developing electromagnetic (EM) and thermal analytical methods with computational efficiency and decent accuracy is a key enabling factor for future multi-physics optimization of motor power density. In this thesis, the detailed development process of electromagnetic analytical modeling for the proposed machine will be presented and verified with finite element analysis (FEA). Corresponding heat loads, including electrical and mechanical losses, will be quantified rigorously to assess efficiency and prepare for the following thermal analysis. Furthermore, accurate physical-thermal conductivities of different machine components are required to eliminate uncertainties in thermal performance prediction. One arising challenge is to quantify the equivalent thermal conductivity of a complicated composite component --- the winding --- which is also the most critical one regarding overheating risks. Detailed methods of quantifying winding equivalent thermal conductivity will be presented, discussed, and verified with a bench test. The last step in EM-thermal modeling is using a simplified thermal equivalent circuit to quickly detect hotspot temperature and therefore to eliminate infeasible machine designs efficiently. Similar to EM modeling, rigorous thermal analytical modeling will be presented and verified with FEA results.","abstract_has_math":false,"creators":["Yi, Xuan"],"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":["Haran, Kiruba"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-03-01T15:49:30Z","date_published":"2017-03-01T15:49:30Z","updated_at":"2026-07-22T22:26:37Z","subjects":["Electrical Machines","Multi-Physics Modeling"],"languages":["en"],"rights":["Copyright 2016 Xuan Yi"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/95407","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Haran, Kiruba"]},{"key":"dc:creator","label":"Author","values":["Yi, Xuan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2017-03-01T15:49:30Z","2016-12-09","2016-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"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":["Electrical Machines","Multi-Physics Modeling"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2016 Xuan Yi"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/95407"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["A 1 MW high-frequency air-core permanent-magnet (PM) motor, with power density over 13.8 kW/kg (8 hp/lb) and efficiency over 96\\%, is proposed for NASA hybrid-electric aircraft application. In order to maximize power density of the proposed motor topology, a large-scale multi-physics optimization is needed to obtain the best design candidates, which is not favorable for current electrical machine software. Therefore, developing electromagnetic (EM) and thermal analytical methods with computational efficiency and decent accuracy is a key enabling factor for future multi-physics optimization of motor power density. In this thesis, the detailed development process of electromagnetic analytical modeling for the proposed machine will be presented and verified with finite element analysis (FEA). Corresponding heat loads, including electrical and mechanical losses, will be quantified rigorously to assess efficiency and prepare for the following thermal analysis. Furthermore, accurate physical-thermal conductivities of different machine components are required to eliminate uncertainties in thermal performance prediction. One arising challenge is to quantify the equivalent thermal conductivity of a complicated composite component --- the winding --- which is also the most critical one regarding overheating risks. Detailed methods of quantifying winding equivalent thermal conductivity will be presented, discussed, and verified with a bench test. The last step in EM-thermal modeling is using a simplified thermal equivalent circuit to quickly detect hotspot temperature and therefore to eliminate infeasible machine designs efficiently. Similar to EM modeling, rigorous thermal analytical modeling will be presented and verified with FEA results.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2017-02-28 without embargo terms","The student, Xuan Yi, accepted the attached license on 2016-12-07 at 10:30.","The student, Xuan Yi, submitted this Thesis for approval on 2016-12-07 at 10:38.","This Thesis was approved for publication on 2016-12-09 at 09:40.","DSpace SAF Submission Ingestion Package generated from Vireo submission #10465 on 2017-02-28 at 15:03:36","Made available in DSpace on 2017-03-01T15:49:30Z (GMT). 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In order to maximize power density of the proposed motor topology, a large-scale multi-physics optimization is needed to obtain the best design candidates, which is not favorable for current electrical machine software. Therefore, developing electromagnetic (EM) and thermal analytical methods with computational efficiency and decent accuracy is a key enabling factor for future multi-physics optimization of motor power density. In this thesis, the detailed development process of electromagnetic analytical modeling for the proposed machine will be presented and verified with finite element analysis (FEA). Corresponding heat loads, including electrical and mechanical losses, will be quantified rigorously to assess efficiency and prepare for the following thermal analysis. Furthermore, accurate physical-thermal conductivities of different machine components are required to eliminate uncertainties in thermal performance prediction. One arising challenge is to quantify the equivalent thermal conductivity of a complicated composite component --- the winding --- which is also the most critical one regarding overheating risks. Detailed methods of quantifying winding equivalent thermal conductivity will be presented, discussed, and verified with a bench test. The last step in EM-thermal modeling is using a simplified thermal equivalent circuit to quickly detect hotspot temperature and therefore to eliminate infeasible machine designs efficiently. Similar to EM modeling, rigorous thermal analytical modeling will be presented and verified with FEA results.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2017-02-28 without embargo terms","The student, Xuan Yi, accepted the attached license on 2016-12-07 at 10:30.","The student, Xuan Yi, submitted this Thesis for approval on 2016-12-07 at 10:38.","This Thesis was approved for publication on 2016-12-09 at 09:40.","DSpace SAF Submission Ingestion Package generated from Vireo submission #10465 on 2017-02-28 at 15:03:36","Made available in DSpace on 2017-03-01T15:49:30Z (GMT). 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