Simultaneous Estimation of the SOC and Parameters of Batteries for HEV/EV

Atsushi Baba, Kinnosuke Itabashi, Nozomu Teranishi, Yoshihiro Edamoto, Kensuke Osamura, Ichiro Maruta, Shuichi Adachi

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

1 Citation (Scopus)

Abstract

This paper proposes a battery state estimation on a battery management system (BMS) for hybrid electric vehicles (HEVs) and electric vehicles (EVs). It is important to estimate a state of charge (SOC) and parameters of the battery such as a state of health (SOH), internal resistances and dynamics of electrochemical reactions. The BMS can provide information on the driving range of the EVs to the drivers by accurately estimating SOC and SOH. It can also calculate a state of power (SOP) to use the battery safely by accurately estimated SOC, internal resistances and others. For that purpose, this paper proposes the BMS adopted a simultaneous state of charge (SOC) and parameter estimation method using log-normalized unscented Kalman filter (LnUKF). The key idea is a lognormalization of the parameters to improve numerical stability and robustness of the algorithm. The proposed system is verified by a series of simulations using experimental data with EVs. One of the SOC and parameter estimation results is for low temperature data on the chassis dynamometer. The proposed system can accurately estimate SOC and parameters of the battery without relying on the experimentally obtained data even if it is under the harsh conditions such as low temperature environment. As a result, it can accurately estimate SOH and SOP of the battery since they are estimated by using estimates of SOC and parameters of the battery.

Original languageEnglish
Title of host publicationSAE 2016 World Congress and Exhibition
PublisherSAE International
Volume2016-April
EditionApril
DOIs
Publication statusPublished - 2016 Apr 5
EventSAE 2016 World Congress and Exhibition - Detroit, United States
Duration: 2016 Apr 122016 Apr 14

Other

OtherSAE 2016 World Congress and Exhibition
CountryUnited States
CityDetroit
Period16/4/1216/4/14

Fingerprint

Hybrid vehicles
Electric vehicles
Health
Parameter estimation
Dynamometers
Chassis
Convergence of numerical methods
State estimation
Kalman filters
Temperature
Battery management systems

ASJC Scopus subject areas

  • Automotive Engineering
  • Safety, Risk, Reliability and Quality
  • Pollution
  • Industrial and Manufacturing Engineering

Cite this

Baba, A., Itabashi, K., Teranishi, N., Edamoto, Y., Osamura, K., Maruta, I., & Adachi, S. (2016). Simultaneous Estimation of the SOC and Parameters of Batteries for HEV/EV. In SAE 2016 World Congress and Exhibition (April ed., Vol. 2016-April). SAE International. https://doi.org/10.4271/2016-01-1195

Simultaneous Estimation of the SOC and Parameters of Batteries for HEV/EV. / Baba, Atsushi; Itabashi, Kinnosuke; Teranishi, Nozomu; Edamoto, Yoshihiro; Osamura, Kensuke; Maruta, Ichiro; Adachi, Shuichi.

SAE 2016 World Congress and Exhibition. Vol. 2016-April April. ed. SAE International, 2016.

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

Baba, A, Itabashi, K, Teranishi, N, Edamoto, Y, Osamura, K, Maruta, I & Adachi, S 2016, Simultaneous Estimation of the SOC and Parameters of Batteries for HEV/EV. in SAE 2016 World Congress and Exhibition. April edn, vol. 2016-April, SAE International, SAE 2016 World Congress and Exhibition, Detroit, United States, 16/4/12. https://doi.org/10.4271/2016-01-1195
Baba A, Itabashi K, Teranishi N, Edamoto Y, Osamura K, Maruta I et al. Simultaneous Estimation of the SOC and Parameters of Batteries for HEV/EV. In SAE 2016 World Congress and Exhibition. April ed. Vol. 2016-April. SAE International. 2016 https://doi.org/10.4271/2016-01-1195
Baba, Atsushi ; Itabashi, Kinnosuke ; Teranishi, Nozomu ; Edamoto, Yoshihiro ; Osamura, Kensuke ; Maruta, Ichiro ; Adachi, Shuichi. / Simultaneous Estimation of the SOC and Parameters of Batteries for HEV/EV. SAE 2016 World Congress and Exhibition. Vol. 2016-April April. ed. SAE International, 2016.
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