State-of-charge estimation of rechargeable battery with hysteresis characteristics using robust gain-scheduled observer

Kenichi Hattaha, Masaki Inoue, Takahiro Kawaguchi, Kensuke Osamura, Shuichi Adachi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we consider model-based state-of-charge (SOC) estimation of a rechargeable battery with hysteresis characteristics. A standard approach is to describe the battery system as an approximated linear time-invariant model and to apply a linear estimator such as the robust observer or Kalman filter. However, this cannot achieve sufficient estimation accuracy due to the nonlinearity of the hysteresis characteristics. We propose to describe the battery system as a linear-parameter-varying (LPV) model, which does not require the approximation. Furthermore, parameter uncertainties are taken into account to derive robust gain-scheduled observer design. The effectiveness of the proposed method is illustrated through numerical experiments.

Original languageEnglish
Title of host publication1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages933-938
Number of pages6
Volume2017-January
ISBN (Electronic)9781509021826
DOIs
Publication statusPublished - 2017 Oct 6
Event1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017 - Kohala Coast, United States
Duration: 2017 Aug 272017 Aug 30

Other

Other1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017
CountryUnited States
CityKohala Coast
Period17/8/2717/8/30

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Hardware and Architecture
  • Software
  • Control and Systems Engineering

Fingerprint Dive into the research topics of 'State-of-charge estimation of rechargeable battery with hysteresis characteristics using robust gain-scheduled observer'. Together they form a unique fingerprint.

Cite this