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dc.contributor.authorPoloei, Fereshtehen
dc.date.accessioned2016-11-29T23:13:26Z
dc.date.available2016-11-29T23:13:26Z
dc.identifier.urihttp://hdl.handle.net/1974/15255
dc.description.abstractLithium Ion (Li-Ion) batteries have got attention in recent decades because of their undisputable advantages over other types of batteries. They are used in so many our devices which we need in our daily life such as cell phones, lap top computers, cameras, and so many electronic devices. They also are being used in smart grids technology, stand-alone wind and solar systems, Hybrid Electric Vehicles (HEV), and Plug in Hybrid Electric Vehicles (PHEV). Despite the rapid increase in the use of Lit-ion batteries, the existence of limited battery models also inadequate and very complex models developed by chemists is the lack of useful models a significant matter. A battery management system (BMS) aims to optimize the use of the battery, making the whole system more reliable, durable and cost effective. Perhaps the most important function of the BMS is to provide an estimate of the State of Charge (SOC). SOC is the ratio of available ampere-hour (Ah) in the battery to the total Ah of a fully charged battery. The Open Circuit Voltage (OCV) of a fully relaxed battery has an approximate one-to-one relationship with the SOC. Therefore, if this voltage is known, the SOC can be found. However, the relaxed OCV can only be measured when the battery is relaxed and the internal battery chemistry has reached equilibrium. This thesis focuses on Li-ion battery cell modelling and SOC estimation. In particular, the thesis, introduces a simple but comprehensive model for the battery and a novel on-line, accurate and fast SOC estimation algorithm for the primary purpose of use in electric and hybrid-electric vehicles, and microgrid systems. The thesis aims to (i) form a baseline characterization for dynamic modeling; (ii) provide a tool for use in state-of-charge estimation. The proposed modelling and SOC estimation schemes are validated through comprehensive simulation and experimental results.en
dc.language.isoengen
dc.relation.ispartofseriesCanadian thesesen
dc.rightsQueen's University's Thesis/Dissertation Non-Exclusive License for Deposit to QSpace and Library and Archives Canadaen
dc.rightsProQuest PhD and Master's Theses International Dissemination Agreementen
dc.rightsIntellectual Property Guidelines at Queen's Universityen
dc.rightsCopying and Preserving Your Thesisen
dc.rightsThis publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.en
dc.subjectModelling and Estimationen
dc.subjectBatteriesen
dc.subjectState of Chargeen
dc.subjectLi-Ion Batteryen
dc.titleA Novel Modeling and State of Charge Estimation Scheme for Lithium-Ion Batteriesen
dc.typethesisen
dc.description.degreeM.A.Sc.en
dc.contributor.supervisorBakhshai, Alirezaen
dc.contributor.departmentElectrical and Computer Engineeringen
dc.embargo.termsDue to some personal issues I have downgraded from a PhD program to a master's program. My supervisor believes that the research I have done so far is patentable and will later be continued by another student or by myself. For this reason I an requesting a restrict submission.en
dc.embargo.liftdate2021-11-25T21:31:22Z
dc.degree.grantorQueen's University at Kingstonen


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