{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/120205"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/120205","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Modeling and control of thermal management systems on electric vehicles","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms","abstract_has_math":false,"creators":["Russell, Kayla Michelle"],"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":2023,"date_issued":"2023-05","date_published":"2023-05","updated_at":"2026-07-22T22:24:57Z","subjects":["Dynamic Modeling","Thermal Management","Model Predictive Control","Physics-based Modeling"],"languages":["en","eng"],"rights":["Copyright 2023 Kayla Russell"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/120205","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":["Russell, Kayla Michelle"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2023-05","2023-02-28"]},{"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":["Dynamic Modeling","Thermal Management","Model Predictive Control","Physics-based Modeling"]}]},{"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 2023 Kayla Russell"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/120205"]}]},{"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 2023-09-01 without embargo terms","The student, Kayla Russell, accepted the attached license on 2023-02-23 at 12:31.","The student, Kayla Russell, submitted this Thesis for approval on 2023-02-23 at 12:45.","This Thesis was approved for publication on 2023-02-28 at 09:45.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18855 on 2023-09-01 at 17:07:24","A growing emphasis on electrifying the transportation industry has led to an increase in the development and implementation of electric vehicles. The thermal management system on electric vehicles is one of the most critical subsystems that ensures safe and comfortable operation of these vehicles. Vapor compression systems are one of the most commonly used cooling methods in thermal management systems for electric vehicles. This thesis develops a vapor compression system model using graph-based modeling techniques. The graph-based modeling framework is extended in this work to capture coupled multi-timescale dynamics that exist in dynamic systems, such as the vapor compression system, while preserving the computational efficiency and modularity of the existing graph-modeling framework. This extended graph-based modeling framework is shown to accurately capture system dynamics within 1% of the current state of the art modeling approaches. Then the graph-based vapor compression system model is connected to a thermal cabin model to cool the interior cabin of an electric vehicle. This work also develops a model predictive control and a baseline control to manage the use of the vapor compression system to cool the cabin. The model predictive control and baseline control performed similarly in meeting the system constraints and objectives."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Modeling and control of thermal management systems on electric vehicles"]}]}],"canonical_facts":{"dc:contributor":["Alleyne, Andrew G"],"dc:creator":["Russell, Kayla Michelle"],"dc:date":["2023-05","2023-02-28"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms","The student, Kayla Russell, accepted the attached license on 2023-02-23 at 12:31.","The student, Kayla Russell, submitted this Thesis for approval on 2023-02-23 at 12:45.","This Thesis was approved for publication on 2023-02-28 at 09:45.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18855 on 2023-09-01 at 17:07:24","A growing emphasis on electrifying the transportation industry has led to an increase in the development and implementation of electric vehicles. The thermal management system on electric vehicles is one of the most critical subsystems that ensures safe and comfortable operation of these vehicles. Vapor compression systems are one of the most commonly used cooling methods in thermal management systems for electric vehicles. This thesis develops a vapor compression system model using graph-based modeling techniques. The graph-based modeling framework is extended in this work to capture coupled multi-timescale dynamics that exist in dynamic systems, such as the vapor compression system, while preserving the computational efficiency and modularity of the existing graph-modeling framework. This extended graph-based modeling framework is shown to accurately capture system dynamics within 1% of the current state of the art modeling approaches. Then the graph-based vapor compression system model is connected to a thermal cabin model to cool the interior cabin of an electric vehicle. This work also develops a model predictive control and a baseline control to manage the use of the vapor compression system to cool the cabin. The model predictive control and baseline control performed similarly in meeting the system constraints and objectives."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/120205"],"dc:language":["en","eng"],"dc:rights":["Copyright 2023 Kayla Russell"],"dc:subject":["Dynamic Modeling","Thermal Management","Model Predictive Control","Physics-based Modeling"],"dc:title":["Modeling and control of thermal management systems on electric vehicles"],"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":"2026-07-22T22:24:57Z"}