Parameter Identification of Lithium-ion Battery using Dragonfly Algorithm

Parameter identification is the basis for state estimation, energy equalization, and charging optimization in the battery management system. In this paper, the parameter identification scheme using Dragonfly Algorithm (DA) is developed for lithium-ion batteries. The system model is discretised for c...

Full description

Saved in:
Bibliographic Details
Published in2024 IEEE 25th China Conference on System Simulation Technology and its Application (CCSSTA) pp. 565 - 569
Main Authors Tian, Jiaqiang, Yin, Xinxiang, Pan, Tianhong, Zhang, Xu, Yang, Duo, Ni, Liping
Format Conference Proceeding
LanguageEnglish
Published IEEE 21.07.2024
Subjects
Accuracy
dragonfly algorithm
first-order RC model
Integrated circuit modeling
Lithium-ion batteries
Mathematical models
Parameter estimation
parameter identification
Particle swarm optimization
Root mean square
State estimation
Systems simulation
Voltage
Online AccessGet full text
DOI10.1109/CCSSTA62096.2024.10691832

Cover

Abstract Parameter identification is the basis for state estimation, energy equalization, and charging optimization in the battery management system. In this paper, the parameter identification scheme using Dragonfly Algorithm (DA) is developed for lithium-ion batteries. The system model is discretised for constructing the voltage error evaluation function according to the first-order RC model. The DA is used for model parameter identification. The estimation effects of Particle Swarm Optimization (PSO) and Ant Lion Optimizer (ALO) are compared. The experimental results show that the proposed DA parameter identification algorithm has higher estimation accuracy.
AbstractList Parameter identification is the basis for state estimation, energy equalization, and charging optimization in the battery management system. In this paper, the parameter identification scheme using Dragonfly Algorithm (DA) is developed for lithium-ion batteries. The system model is discretised for constructing the voltage error evaluation function according to the first-order RC model. The DA is used for model parameter identification. The estimation effects of Particle Swarm Optimization (PSO) and Ant Lion Optimizer (ALO) are compared. The experimental results show that the proposed DA parameter identification algorithm has higher estimation accuracy.
Author Yang, Duo
Pan, Tianhong
Tian, Jiaqiang
Yin, Xinxiang
Zhang, Xu
Ni, Liping
Author_xml – sequence: 1
  givenname: Jiaqiang
  surname: Tian
  fullname: Tian, Jiaqiang
  email: 23706@ahu.edu.cn
  organization: Anhui University,School of Eelectrical Engineering and Automation,Hefei,China
– sequence: 2
  givenname: Xinxiang
  surname: Yin
  fullname: Yin, Xinxiang
  email: z23301167@stu.ahu.edu.cn
  organization: Anhui University,School of Eelectrical Engineering and Automation,Hefei,China
– sequence: 3
  givenname: Tianhong
  surname: Pan
  fullname: Pan, Tianhong
  email: thpan@ahu.edu.cn
  organization: Anhui University,School of Eelectrical Engineering and Automation,Hefei,China
– sequence: 4
  givenname: Xu
  surname: Zhang
  fullname: Zhang, Xu
  email: 2022078@aust.edu.cn
  organization: Anhui University of Science and Technology,Institute for Advanced Research,Hefei,China
– sequence: 5
  givenname: Duo
  surname: Yang
  fullname: Yang, Duo
  email: yangduo@zzu.edu.cn
  organization: Zhengzhou University,School of Electrical Engineering,Henan,China
– sequence: 6
  givenname: Liping
  surname: Ni
  fullname: Ni, Liping
  email: lni@sinoev.com
  organization: Anhui JAC SinoEV Battery System Co., Ltd.,Hefei,China
BookMark eNo1j8tKxDAYRiPoQsd5AxfxAVrzJ2nSLGu9FQoK0_2Qpn9qoBfJZBbz9o6oq8MHhw_ODblc1gUJuQeWAzDzUNe7XVcpzozKOeMyB6YMlIJfkK3RphQFE0opxq5J82GjnTFhpM2ASwo-OJvCutDV0zakz3Ccs5_5aNNZOtHjISwjfYp2XBc_nWg1jWs8e_MtufJ2OuD2jxvSvTx39VvWvr82ddVmwUDKvJaDGbRDWYDnRWHc4PoSSygdaK2YYr3pe4fOC40owUqQqJWUnjvwaMWG3P3eBkTcf8Uw23ja_weKbzx8TNg
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/CCSSTA62096.2024.10691832
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume
IEEE Xplore All Conference Proceedings
IEEE/IET Electronic Library (IEL)
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
EISBN 9798350366600
EndPage 569
ExternalDocumentID 10691832
Genre orig-research
GrantInformation_xml – fundername: National Natural Science Foundation of China
  funderid: 10.13039/501100001809
– fundername: Research and Development
  funderid: 10.13039/100006190
GroupedDBID 6IE
6IL
CBEJK
RIE
RIL
ID FETCH-LOGICAL-i91t-f74d9d7ce451f2559cdcb8e818c1776060b9bbcecf37ee41a414e7644f2c1fea3
IEDL.DBID RIE
IngestDate Wed Oct 09 06:12:58 EDT 2024
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i91t-f74d9d7ce451f2559cdcb8e818c1776060b9bbcecf37ee41a414e7644f2c1fea3
PageCount 5
ParticipantIDs ieee_primary_10691832
PublicationCentury 2000
PublicationDate 2024-July-21
PublicationDateYYYYMMDD 2024-07-21
PublicationDate_xml – month: 07
  year: 2024
  text: 2024-July-21
  day: 21
PublicationDecade 2020
PublicationTitle 2024 IEEE 25th China Conference on System Simulation Technology and its Application (CCSSTA)
PublicationTitleAbbrev CCSSTA
PublicationYear 2024
Publisher IEEE
Publisher_xml – name: IEEE
Score 1.8796729
Snippet Parameter identification is the basis for state estimation, energy equalization, and charging optimization in the battery management system. In this paper, the...
SourceID ieee
SourceType Publisher
StartPage 565
SubjectTerms Accuracy
dragonfly algorithm
first-order RC model
Integrated circuit modeling
Lithium-ion batteries
Mathematical models
Parameter estimation
parameter identification
Particle swarm optimization
Root mean square
State estimation
Systems simulation
Voltage
Title Parameter Identification of Lithium-ion Battery using Dragonfly Algorithm
URI https://ieeexplore.ieee.org/document/10691832
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1NS8NAEB1sD-JJxYrfrOB1YzfZfB1LtVTRUmiF3kp2s1uLtiklOdRf70ySKgqCtyQMJMwmvHmTeW8BbsjkTlhy-Qx0wKX0Y65UGnAlfY1w15bWI3Hy8yDov8jHiT-pxeqlFsYYUw6fGYcOy3_5aaYLapXhFx7E9Ao2oIHMrRJr7cJ17Zt52-2ORuNO4GJVjsTPlc42_sfOKSVw9PZhsL1lNS_y5hS5cvTHLzfGfz_TAbS-NXps-IU-h7BjlkfwMExo2ApzxSoFrq1bciyz7Gmev86LBafTylZzw2jsfcbu1smM5CEb1nmfZWuMW7Rg3Lsfd_u83iyBz2ORcxvKNE5DbaQvLNEEnWoVGYRjLcIQWUpbxUppo60XGiNFIoU0IRZD1tXCmsQ7huYyW5oTYEpEFoOTtheTH5-rsCiTQmkkdkgHo-gUWpSG6aqyw5huM3D2x_Vz2KPVoIaoKy6gma8Lc4lInqurcgU_AbEAnxw
linkProvider IEEE
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1NS8NAEB20gnpSseK3K3hN7Sabr2OpSqttKTRCbyW72a1F20hJDvXXO5OkioLgLQkbEmYT3rzZeW8Bbsjkjhty-fSUZwnhhpaUiWdJ4SqEu6YwDomT-wOv8ywex-64EqsXWhitddF8pht0WKzlJ6nKqVSGf7gX0ie4CVsI_C4v5VrbcF05Z96226NR1PJszMuR-tmisb7jx94pBXQ87MFg_dCyY-S1kWeyoT5--TH--632of6t0mPDL_w5gA29OITuMKZ2K4wWKzW4pirKsdSw3ix7meVzi05LY80Vo8b3KbtbxlMSiKxY622aLnHcvA7Rw33U7ljVdgnWLOSZZXyRhImvtHC5IaKgEiUDjYCsuO8jT2nKUEqllXF8rQWPBRfax3TI2IobHTtHUFukC30MTPLA4OC46YTkyGdLTMsElwqpHRLCIDiBOoVh8l4aYkzWETj94_oV7HSifm_S6w6ezmCXZobKozY_h1q2zPUF4nomL4vZ_AQuQaJl
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2024+IEEE+25th+China+Conference+on+System+Simulation+Technology+and+its+Application+%28CCSSTA%29&rft.atitle=Parameter+Identification+of+Lithium-ion+Battery+using+Dragonfly+Algorithm&rft.au=Tian%2C+Jiaqiang&rft.au=Yin%2C+Xinxiang&rft.au=Pan%2C+Tianhong&rft.au=Zhang%2C+Xu&rft.date=2024-07-21&rft.pub=IEEE&rft.spage=565&rft.epage=569&rft_id=info:doi/10.1109%2FCCSSTA62096.2024.10691832&rft.externalDocID=10691832