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A new method for State-Of-Charge determination for lithium-ion and lithium-ion-polymer rechargeable batteries

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Warianty tytułu
PL
Nowa metoda szacowania stanu naładowania baterii dla ogniw litowo--jonowych i litowo-polimerowych
Języki publikacji
EN
Abstrakty
EN
This paper presents a new method for State-Of-Charge and associated parameters estimation and calculation. The method introduces two separate calculation tracks: based on coulomb counting and electromotoric force of battery cell combined in Kalman filter. The method has been tested in laboratory conditions and then implemented in real microcontroller-based prototype of the system. The efficiency of method has been evaluated by series of tests held on a prototype.
PL
Artykuł prezentuje koncepcję metody obliczania parametrów State-Of-Charge I skojarzonych. Metoda składa się z dwóch oddzielnych torów obliczeniowych: prądowego bazującego na całkowaniu prądu, oraz napięciowego obliczającego siłę elektromotoryczną ogniwa baterii. Wyniki z tych dwóch torów są przetwarzane w filtrze Kalmana. Metoda została przetestowana w warunkach laboratoryjnych, a następnie zaimplementowana w prototypie rzeczywistego systemu wbudowanego. Wykonana została seria testów w celu zweryfikowania poprawności rozumowania autora.
Słowa kluczowe
Rocznik
Strony
264--269
Opis fizyczny
Bibliogr. 19 poz., rys.
Twórcy
autor
  • Industrial Research Institute for Automation and Measurements (PIAP), pbigaj@piap.pl
Bibliografia
  • [1] A. Vasebi, M. Partovibakhsh, and S. Taghi, A novel combined battery model for state of charge estimation in lead acid batteries based on extended Kalman filter for hybrid electric vehicle application, Journal of Power Sources, vol.74 (2007)
  • [2] Fei Zhang, Guangjun Liu, Lijin Fang, A Battery State of Charge Estimation Method with Extended Kalman Filter, IEEE/ASME International Conference on Advanced Intelligent Mechatronics (2008)
  • [3] L. Gao, S.A. Liu and R.A. Dougal, Dynamic Lithium-Ion Battery Model for System Simulation, IEEE Transactions on Components and Packaging Technologies, 25(3)(2002)
  • [4] B.S. Bhangu, P. Bentley, D.A. Stone, C.M. Bingham, Nonlinear Observers for Predicting State-of-Charge and Stateof-Health of Lead-Acid Batteries for Hybrid-Electric Vehicles, IEEE Transactions on Vehicular Technology, Vol 54(3)(2005)
  • [5] H. Blanke, 0. Bohlen, S. Buller, R.W. De Doncker, B. Fricke, A. Hammouche, D. Linzen, M. Thele, D.U. Sauer, Impedance Measurements on Lead-Acid Batteries for State-of-charge, State-of-health and Cranking Capability Prognosis in Electric and Hybrid Electric Vehicles, Journal of Power Sources Vol. 144, Issue 2, (2005)
  • [6] Tsutomu Y,Kazuaki S,and Ken-Ichiro M, Estimation of the Residual capacity of sealed lead-acid batteries by neural network, Telecommunications Energy Conference, INTELEC, 20th International (1998)
  • [7] J.H. Aylor, A. Thieme, B.W. Johnson, A battery state-of-charge indicator for electric wheelchairs, IEEE Transactions on Industrial Electronics, Vol.39 (1992)
  • [8] A.J. Salkind, C. Fennie, P. Singh, Determination of state-ofcharge and state-of-health of batteries by fuzzy logic methodology, Journal of Power Sources, Vol. 80 (1999)
  • [9] H.J. Bergveld, Feil Hand Van Beek JRGCM Method of predicting the state of charge as well as the use time left of a rechargeable battery, US Patent 6,515,453 (2000)
  • [10] S. Rodrigues, A.K. Munichandraiah Nand Shukla A review of state-of-charge indication of batteries by mean sofa. c.impedance measurements, Journal of Power Sources, Vol 87 (1999)
  • [11] B. Saha, K. Goebel, Uncertainty Management for Diagnostics and Prognostics of Batteries using Bayesian Techniques, IEEEAC paper #1361, (2007)
  • [12] Scho, W.S. Kruijt , Einerhand , S.A. Hanneman, H.J. Bergveld, Method and device for determining the charge condition of a battery, USPatent 6,420,851, (2000)
  • [13] Kong Soon Nga, Chin-Sien Mooa, Yi-Ping Chenb and Yao-Ching Hsiehc, Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries, Applied Energy, vol. 86, Issue 9, (2009)
  • [14] H.S. Ryua, H.J. Ahn, K.W. Kima, J.H. Ahna, K.K. Choa and T.H. Nama, Self-discharge characteristics of lithium/sulfur batteries using TEGDME liquid electrolyte, Electrochemica Acta, Vol. 52, Issue 4, (2006)
  • [15] Pier Paolo Prosini, Yongyao Xiaa, Takuya Fujiedaa, Raffaele Velloneb, Masahiro Shikanoa and Tetsuo Sakaia, Performance and capacity fade of V2O5–lithium polymer batteries at a moderate–low temperature, Electrochemica Acta, Vol. 46, Issue 17, (2001)
  • [16] H.J. Bergveld, W.S. Kruijt, P.H.L. Notten, Battery Management Systems – Design by Modeling vol.1, (2002]
  • [17] P. Bigaj, Inteligentny system monitorowania i estymacji ładunku SOC dla baterii litowo-jonowych i litowo-polimerowych, Konferencja Automation 2010.
  • [18] E. Meissner; G. Richter, Battery Monitoring and Electrical Energy Management - Precondition for future vehicle electric power systems, Journal of Power Sources, vol. 116, Issue 1,. 79-98(20), (2003)
  • [19] Shriram Santhanagopalana and Ralph E. White, Online estimation of the state of charge of a lithium ion cell, Journal of Power Sources , Vol. 161, Issue 2, (2006)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPOK-0031-0053
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