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MODEL & ESTIMATION OF SOC/SOH EMISSION OF LI BATTERIES: Enhancing Battery Performance Through Battery Models
Halmstad University.
Halmstad University.
2024 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis [Artistic work]
Abstract [en]

SOC estimation is crucial for the efficient management of lithium-ion batteries, ensuring bothsafety and optimal performance in applications such as electric vehicles and energy storagesystems. This project focuses on developing and comparing SOC estimation techniques using theOpen Circuit Voltage and Extended Kalman Filter methods. The OCV method relies on therelationship between the terminal voltage of the battery and its SOC when the battery is in a relaxedstate. Although simple and effective for offline estimations, the OCV method is limited by itsreliance on long rest periods, making it less suitable for real-time applications. 

Place, publisher, year, edition, pages
2024. , p. 38
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:hh:diva-54729OAI: oai:DiVA.org:hh-54729DiVA, id: diva2:1903949
Subject / course
Mechanical Engineering
Educational program
Master's Programme in Mechanical Engineering, 60 credits
Presentation
2024-05-16, Halmstad University, Halmstad, 21:49 (English)
Supervisors
Examiners
Available from: 2024-10-08 Created: 2024-10-07 Last updated: 2025-10-01Bibliographically approved

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Rajan, JestinPrakash, Arjun
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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf