{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/117713"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/117713","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Dynamic modeling and control of a hybrid electric quadrotor powertrain and thermal management system","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-04-12 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-04-12 without embargo terms","abstract_has_math":false,"creators":["Smith, Reid Dukes"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Mechanical Engineering","degree_department":null,"school":null,"contributors":["Alleyne, Andrew G"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-12","date_published":"2022-12","updated_at":"2026-07-22T22:24:56Z","subjects":["Modeling","Control","Dynamic","Powertrain","Thermal Management","Urban Air Mobility","Graph Model","Model Predictive Control"],"languages":["en","eng"],"rights":["Copyright 2022 Reid Dukes Smith"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/117713","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Alleyne, Andrew G"]},{"key":"dc:creator","label":"Author","values":["Smith, Reid Dukes"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2022-12","2022-09-08"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical Engineering"]},{"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":["Modeling","Control","Dynamic","Powertrain","Thermal Management","Urban Air Mobility","Graph Model","Model Predictive Control"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2022 Reid Dukes Smith"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/117713"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-04-12 without embargo terms","The student, Reid Smith, accepted the attached license on 2022-08-26 at 10:52.","The student, Reid Smith, submitted this Thesis for approval on 2022-08-26 at 11:08.","This Thesis was approved for publication on 2022-09-08 at 15:27.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18471 on 2023-04-12 at 07:23:11","Within the aviation industry, hybrid electric and fully electric aircraft are ushering in the next phase of electrification. These aircraft pose unique control challenges due to the interconnected mechanical, electrical, and thermal dynamics within the aircraft powertrain and cabin systems. As the behavior of each of these subsystems influences the others, a holistic modeling approach allows for understanding of the control and design impacts of these interactions. This thesis seeks to capture the multi-domain dynamics within hybrid electric aircraft by developing component and system models which can be represented in a unified modeling framework. Graph-based models are used to provide a computationally efficient and modular framework for the aircraft system. Novel thermodynamic cycle system, AC synchronous motor, cabin, and power electronics graph-based models are synthesized with existing graph-based models to build a system model which includes propulsion, power management, and thermal management systems. Details on the development of these models from data in the literature is presented to provide a methodology for model recreation. Although this system model captures dynamics throughout the powertrain with vastly different timescales, the computational efficiency of the model allows for its application into online control. Following the development of the system model, the performance of a centralized model predictive controller is compared to a baseline logic-based controller. As operating equipment outside of the designed performance region leads to degradation and system failure, the model predictive controller considers constraints on component operating regions in addition to fuel consumption and trajectory tracking. The model predictive controller demonstrates significant reductions in constraint violations and trajectory tracking error while providing slight reductions in fuel consumption. The results display the advantages of advanced control strategies within electrified systems and the necessity of capturing multi-domain power interconnections present within the next generation of aircraft."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Dynamic modeling and control of a hybrid electric quadrotor powertrain and thermal management system"]}]}],"canonical_facts":{"dc:contributor":["Alleyne, Andrew G"],"dc:creator":["Smith, Reid Dukes"],"dc:date":["2022-12","2022-09-08"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-04-12 without embargo terms","The student, Reid Smith, accepted the attached license on 2022-08-26 at 10:52.","The student, Reid Smith, submitted this Thesis for approval on 2022-08-26 at 11:08.","This Thesis was approved for publication on 2022-09-08 at 15:27.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18471 on 2023-04-12 at 07:23:11","Within the aviation industry, hybrid electric and fully electric aircraft are ushering in the next phase of electrification. These aircraft pose unique control challenges due to the interconnected mechanical, electrical, and thermal dynamics within the aircraft powertrain and cabin systems. As the behavior of each of these subsystems influences the others, a holistic modeling approach allows for understanding of the control and design impacts of these interactions. This thesis seeks to capture the multi-domain dynamics within hybrid electric aircraft by developing component and system models which can be represented in a unified modeling framework. Graph-based models are used to provide a computationally efficient and modular framework for the aircraft system. Novel thermodynamic cycle system, AC synchronous motor, cabin, and power electronics graph-based models are synthesized with existing graph-based models to build a system model which includes propulsion, power management, and thermal management systems. Details on the development of these models from data in the literature is presented to provide a methodology for model recreation. Although this system model captures dynamics throughout the powertrain with vastly different timescales, the computational efficiency of the model allows for its application into online control. Following the development of the system model, the performance of a centralized model predictive controller is compared to a baseline logic-based controller. As operating equipment outside of the designed performance region leads to degradation and system failure, the model predictive controller considers constraints on component operating regions in addition to fuel consumption and trajectory tracking. The model predictive controller demonstrates significant reductions in constraint violations and trajectory tracking error while providing slight reductions in fuel consumption. The results display the advantages of advanced control strategies within electrified systems and the necessity of capturing multi-domain power interconnections present within the next generation of aircraft."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/117713"],"dc:language":["en","eng"],"dc:rights":["Copyright 2022 Reid Dukes Smith"],"dc:subject":["Modeling","Control","Dynamic","Powertrain","Thermal Management","Urban Air Mobility","Graph Model","Model Predictive Control"],"dc:title":["Dynamic modeling and control of a hybrid electric quadrotor powertrain and thermal management system"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Mechanical Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:56Z"}