Condition Monitoring of Lithium Polymer Batteries Based on a Sigma-Point Kalman Filter

Title
Condition Monitoring of Lithium Polymer Batteries Based on a Sigma-Point Kalman Filter
Author(s)
이동춘서보환누옌탄하이이교범[이교범]김장목[김장목]
Keywords
STATE-OF-CHARGE; PARAMETER-ESTIMATION; MODEL; SYSTEM; HEALTH; OBSERVER
Issue Date
201209
Publisher
KOREAN INST POWER ELECTRONICS
Citation
JOURNAL OF POWER ELECTRONICS, v.12, no.5, pp.778 - 786
Abstract
In this paper, a novel scheme for the condition monitoring of lithium polymer batteries is proposed, based on the sigma-point Kalman filter (SPKF) theory. For this, a runtime-based battery model is derived, from which the state-of-charge (SOC) and the capacity of the battery are accurately predicted. By considering the variation of the serial ohmic resistance (R-o) in this model, the estimation performance is improved. Furthermore, with the SPKF, the effects of the sensing noise and disturbance can be compensated and the estimation error due to linearization of the nonlinear battery model is decreased. The effectiveness of the proposed method is verified by Matlab/Simulink simulation and experimental results. The results have shown that in the range of a SOC that is higher than 40%, the estimation error is about 1.2% in the simulation and 1.5% in the experiment. In addition, the convergence time in the SPKF algorithm can be as fast as 300 s.
URI
http://hdl.handle.net/YU.REPOSITORY/27371http://dx.doi.org/10.6113/JPE.2012.12.5.778
ISSN
1598-2092
Appears in Collections:
공과대학 > 전기공학과 > Articles
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE