Battery open-circuit voltage estimation by a method of statistical analysis

Iryna Snihir, William Rey, Evgeny Verbitskiy, Afifa Belfadhel-Ayeb, Peter H.L. Notten

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Abstract

The basic task of a battery management system (BMS) is the optimal utilization of the stored energy and minimization of degradation effects. It is critical for a BMS that the state-of-charge (SoC) be accurately determined. Open-circuit voltage (OCV) is directly related to the state-of-charge of the battery, accurate estimation of the OCV leads to an accurate estimate of the SoC. In this paper we describe a statistical method to predict the open-circuit voltage on the basis of voltage curves obtained by charging batteries with different currents. We employ a dimension reduction method (Karhunen–Loeve expansion) and linear regression. Results of our modelling approach are independently validated in a specially designed experiment.
Original languageEnglish
Pages (from-to)1484-1487
Number of pages4
JournalJournal of Power Sources
Volume159
DOIs
Publication statusPublished - 2006
Externally publishedYes

Keywords

  • Regression
  • Karhunen–Loeve expansion
  • State-of-charge
  • Open-circuit voltage
  • Battery

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