Charge Scheduling of Plug-in Hybrid Electric Vehicles (PHEVs) for Minimized Li-ion Battery Degradation

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.

Name thesis:degree_name

Master of Science in Electrical Engineering

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

College of Engineering

Grantor dc:publisher

University of Toledo

Year dc:date

2012

Author dc:creator

• Bandyopadhyay, Anik

Contributors dc:contributor

• Wang, Dr. Lingfeng

• Electrical Engineering

Statement 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.

Language dc:language

English

Repository record dc:identifier

http://rave.ohiolink.edu/etdc/view?acc_num=toledo1353015235

OAI identifier oai:identifier

oai:etd.ohiolink.edu:toledo1353015235