{"id":{"repo_id":"ohiolink","oai_identifier":"oai:etd.ohiolink.edu:toledo1353015235"},"canonical_url":"https://search.dev.ndltd.org/etd/ohiolink/oai:etd.ohiolink.edu:toledo1353015235","repository":{"repo_id":"ohiolink","name":"OhioLINK","base_url":"https://etd.ohiolink.edu/acprod/odb_etd/ws/oai/oai"},"display":{"title":"Charge Scheduling of Plug-in Hybrid Electric Vehicles (PHEVs) for Minimized Li-ion Battery Degradation","abstract":"Plug-in Hybrid Electric Vehicles (PHEVs) are being touted as one of the most important technological advancements that will help make the smart grid a reality. The Vehicle to Grid (V2G) feature of PHEVs has the potential to help both the PHEV user as well as the electric utilities. However, overuse of V2G for profit will result in the accelerated degradation of the Li-ion batteries of the PHEVs. Thus, it is necessary to have charging schedules that would meet the requirements of all parties. Swarm intelligence techniques are used in this thesis in order to devise strategies that would help in preventing the unnecessary degradation of Li-ion batteries. These optimization techniques are employed for specific scenarios for a future smart grid environment involving PHEVs. Various studies have been carried out to simulate the effect of aggregated PHEV loads. Simulations were also performed to simulate PHEVs in a fast charging scheme. All simulations have been performed with the aim to obtain a balance between profit margins and battery health degradation.","abstract_html":"Plug-in Hybrid Electric Vehicles (PHEVs) are being touted as one of the most important technological advancements that will help make the smart grid a reality. The Vehicle to Grid (V2G) feature of PHEVs has the potential to help both the PHEV user as well as the electric utilities. However, overuse of V2G for profit will result in the accelerated degradation of the Li-ion batteries of the PHEVs. Thus, it is necessary to have charging schedules that would meet the requirements of all parties. Swarm intelligence techniques are used in this thesis in order to devise strategies that would help in preventing the unnecessary degradation of Li-ion batteries. These optimization techniques are employed for specific scenarios for a future smart grid environment involving PHEVs. Various studies have been carried out to simulate the effect of aggregated PHEV loads. Simulations were also performed to simulate PHEVs in a fast charging scheme. All simulations have been performed with the aim to obtain a balance between profit margins and battery health degradation.","abstract_has_math":false,"creators":["Bandyopadhyay, Anik"],"institution":"University of Toledo","degree_name":"Master of Science in Electrical Engineering","degree_level":"masters","degree_discipline":"College of Engineering","degree_department":null,"school":null,"contributors":["Wang, Dr. Lingfeng"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012","date_published":"2012","updated_at":"2026-07-24T03:36:23Z","subjects":["Electrical Engineering"],"languages":["English"],"rights":["unrestricted","This thesis or dissertation is protected by copyright: some rights reserved. It is licensed for use under a Creative Commons license. 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It is licensed for use under a Creative Commons license. Specific terms and permissions are available from this document's record in the OhioLINK ETD Center."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://rave.ohiolink.edu/etdc/view?acc_num=toledo1353015235"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Plug-in Hybrid Electric Vehicles (PHEVs) are being touted as one of the most important technological advancements that will help make the smart grid a reality. The Vehicle to Grid (V2G) feature of PHEVs has the potential to help both the PHEV user as well as the electric utilities. However, overuse of V2G for profit will result in the accelerated degradation of the Li-ion batteries of the PHEVs. Thus, it is necessary to have charging schedules that would meet the requirements of all parties. Swarm intelligence techniques are used in this thesis in order to devise strategies that would help in preventing the unnecessary degradation of Li-ion batteries. These optimization techniques are employed for specific scenarios for a future smart grid environment involving PHEVs. Various studies have been carried out to simulate the effect of aggregated PHEV loads. Simulations were also performed to simulate PHEVs in a fast charging scheme. All simulations have been performed with the aim to obtain a balance between profit margins and battery health degradation."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf","914.4 KB"]},{"key":"dc:title","label":"Title","values":["Charge Scheduling of Plug-in Hybrid Electric Vehicles (PHEVs) for Minimized Li-ion Battery Degradation"]}]}],"canonical_facts":{"dc:contributor":["Wang, Dr. Lingfeng"],"dc:creator":["Bandyopadhyay, Anik"],"dc:date":["2012"],"dc:description":["Plug-in Hybrid Electric Vehicles (PHEVs) are being touted as one of the most important technological advancements that will help make the smart grid a reality. The Vehicle to Grid (V2G) feature of PHEVs has the potential to help both the PHEV user as well as the electric utilities. However, overuse of V2G for profit will result in the accelerated degradation of the Li-ion batteries of the PHEVs. Thus, it is necessary to have charging schedules that would meet the requirements of all parties. Swarm intelligence techniques are used in this thesis in order to devise strategies that would help in preventing the unnecessary degradation of Li-ion batteries. These optimization techniques are employed for specific scenarios for a future smart grid environment involving PHEVs. Various studies have been carried out to simulate the effect of aggregated PHEV loads. Simulations were also performed to simulate PHEVs in a fast charging scheme. All simulations have been performed with the aim to obtain a balance between profit margins and battery health degradation."],"dc:format":["application/pdf","914.4 KB"],"dc:identifier":["http://rave.ohiolink.edu/etdc/view?acc_num=toledo1353015235"],"dc:language":["English"],"dc:publisher":["University of Toledo / OhioLINK"],"dc:rights":["unrestricted","This thesis or dissertation is protected by copyright: some rights reserved. It is licensed for use under a Creative Commons license. Specific terms and permissions are available from this document's record in the OhioLINK ETD Center."],"dc:subject":["Electrical Engineering"],"dc:title":["Charge Scheduling of Plug-in Hybrid Electric Vehicles (PHEVs) for Minimized Li-ion Battery Degradation"],"dc:type":["Electronic Thesis or Dissertation"],"thesis:degree_discipline":["College of Engineering"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science in Electrical Engineering"],"thesis:institution_name":["University of Toledo"]},"updated_at":"2026-07-24T03:36:23Z"}