State of charge estimation of HEV/EV battery with series Kalman filter

Atsushi Baba, Shuichi Adachi

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

10 Citations (Scopus)

Abstract

This paper proposes a method of accurately estimating the state of charge (SOC) of lithium-ion rechargeable batteries in high fuel efficiency vehicles, such as hybrid electric vehicles (HEVs) and electric vehicles (EVs). Although it is important to accurately estimate SOC of the battery to maximize efficiency and safety, there exist many problems for conventional methods. To address this issue, a model-based approach using "Series Kalman Filters" is proposed and implemented in this paper. Its approach is verified with series of simulations under the basic HEV operating environment. A discussion on a limitation of the method is also included in this paper. The ultimate goal is to design a state estimator capable of providing accurate state estimation of batteries under any possible user conditions.

Original languageEnglish
Title of host publication2012 Proceedings of SICE Annual Conference, SICE 2012
PublisherSociety of Instrument and Control Engineers (SICE)
Pages845-850
Number of pages6
ISBN (Print)9781467322591
Publication statusPublished - 2012 Jan 1
Event2012 51st Annual Conference on of the Society of Instrument and Control Engineers of Japan, SICE 2012 - Akita, Japan
Duration: 2012 Aug 202012 Aug 23

Publication series

NameProceedings of the SICE Annual Conference

Other

Other2012 51st Annual Conference on of the Society of Instrument and Control Engineers of Japan, SICE 2012
CountryJapan
CityAkita
Period12/8/2012/8/23

Keywords

  • Electric vehicle (EV)
  • Hybrid electric vehicle (HEV)
  • Kalman filter
  • Parameter estimation
  • Rechargeable Battery
  • State of Charge (SOC)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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