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 publicationProceedings of the SICE Annual Conference
Pages845-850
Number of pages6
Publication statusPublished - 2012
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

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

Fingerprint

Hybrid vehicles
Kalman filters
Secondary batteries
State estimation
Electric vehicles
Lithium
Ions
Battery electric vehicles

Keywords

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

ASJC Scopus subject areas

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

Cite this

Baba, A., & Adachi, S. (2012). State of charge estimation of HEV/EV battery with series Kalman filter. In Proceedings of the SICE Annual Conference (pp. 845-850). [6318559]

State of charge estimation of HEV/EV battery with series Kalman filter. / Baba, Atsushi; Adachi, Shuichi.

Proceedings of the SICE Annual Conference. 2012. p. 845-850 6318559.

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

Baba, A & Adachi, S 2012, State of charge estimation of HEV/EV battery with series Kalman filter. in Proceedings of the SICE Annual Conference., 6318559, pp. 845-850, 2012 51st Annual Conference on of the Society of Instrument and Control Engineers of Japan, SICE 2012, Akita, Japan, 12/8/20.
Baba A, Adachi S. State of charge estimation of HEV/EV battery with series Kalman filter. In Proceedings of the SICE Annual Conference. 2012. p. 845-850. 6318559
Baba, Atsushi ; Adachi, Shuichi. / State of charge estimation of HEV/EV battery with series Kalman filter. Proceedings of the SICE Annual Conference. 2012. pp. 845-850
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AB - 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.

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