Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/565932
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dc.coverage.spatialOptimal battery management system for electric vehicle
dc.date.accessioned2024-05-22T06:01:00Z-
dc.date.available2024-05-22T06:01:00Z-
dc.identifier.urihttp://hdl.handle.net/10603/565932-
dc.description.abstractThe Battery Management System (BMS) is an electronic controller newlinethat monitors, controls, protects and balances the battery pack parameters like newlinecell voltage/current and temperature. The battery pack using Lithium-ion cells newlinecomes at a higher cost and needs protection circuits to ensure safe operation. newlineDue to environmental variations and manufacturing processes, problems like newlinecharge/discharge imbalance, variation in thermal conditions and internal newlineimpedances, self-cell charge rate and unequal charge storage in the cells newlineoccur. The mismatch reduces the cell life time and increases the chance of newlinedamage, fire or even explosion. Therefore, the primary research problem newlineidentified is the frequent overcharging/discharging conditions which newlinedeteriorates the battery life and worsen the performance of Li-ion battery newlinepack. newlineIn this case, it is necessary to have an advanced BMS controller to newlinemonitor cell parameters for achieving safer operation of the battery pack in newlineElectric Vehicles (EV), Hybrid Electric Vehicles (HEV), Renewable Energy newlineSystems (RES) and automobile industries. More equalization techniques have newlinebeen elaborated based on the connection type of the equalizers like series, newlineparallel, series/parallel structures. Some existing techniques like Proportional newlineIntegral (PI) control, Proportional Integral Derivative (PID) control and Fuzzy newlinelogic control (FLC) methods carried out by different researchers for battery newlinemodeling and BMS algorithm for battery pack have been presented. The newlineperformance characteristics like State of Charge (SOC), Battery Energy newlineStorage System (BESS) life, error rate and charging efficiency for those newlinemethods have been discussed to portray its characteristics and complexity. newline newline
dc.format.extentxvi,113p.
dc.languageEnglish
dc.relationp.102-112
dc.rightsuniversity
dc.titleOptimal battery management system for electric vehicle
dc.title.alternative
dc.creator.researcherJustin Raj P
dc.subject.keywordArtificial Ecosystem Optimization
dc.subject.keywordBattery Management System
dc.subject.keywordElectric Vehicle
dc.description.note
dc.contributor.guideVasan Prabhu V
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Electrical and Electronics Engineering
dc.date.registered
dc.date.completed2024
dc.date.awarded2024
dc.format.dimensions21cm.
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Electrical and Electronics Engineering

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01_title.pdfAttached File27.85 kBAdobe PDFView/Open
02_prelimpage.pdf725.99 kBAdobe PDFView/Open
03_contents.pdf19.77 kBAdobe PDFView/Open
04_abstracts.pdf16.88 kBAdobe PDFView/Open
05_chapter1.pdf57.71 kBAdobe PDFView/Open
06_chapter2.pdf204.57 kBAdobe PDFView/Open
07_chapter3.pdf1.56 MBAdobe PDFView/Open
08_chapter4.pdf1.01 MBAdobe PDFView/Open
09_chapter5.pdf542.71 kBAdobe PDFView/Open
10_chapter6.pdf19.18 kBAdobe PDFView/Open
11_annexures.pdf127.68 kBAdobe PDFView/Open
80_recommendation.pdf117.37 kBAdobe PDFView/Open


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