By Topic

Battery state-of-charge estimation using polynomial enhanced prediction

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Unterrieder, C. ; Networked & Embedded Syst., Univ. of Klagenfurt, Klagenfurt, Austria ; Lunglmayr, M. ; Marsili, S. ; Huemer, M.

A novel polynomial-enhanced open-circuit voltage extrapolation method is presented. It is used to identify a battery's state-of-charge based on the estimation of the corresponding relaxation voltage. The proposed method represents the relaxation process via a polynomial enhanced voltage model, calculated by least squares estimation. Compared to state-of-the-art models, the proposed approach reduces the period of time needed until the state-of-charge can be accurately determined. For the particular cell under test, an open-circuit voltage accuracy of '1 can be reached within the first 11 minutes of the relaxation process. In addition, the reduced estimation time also leads to a lower power consumption of an integrated circuit-based battery identification solution.

Published in:

Electronics Letters  (Volume:48 ,  Issue: 21 )