Online parameter estimation/tracking for Lithium-ion battery RC model

Zhaohui Cen, Pierre Kubiak, Ilias Belharouak

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

1 Citation (Scopus)

Abstract

as a basis for Battery SOC estimation and grid integration numerical analysis, Equivalent Circuit Model (ECM) based on RC circuit topology is one of the most widely-used battery models. In the ECM model, model parameters such as internal resistance, RC circuit capacitance, and resistance are physically time-variant and depend on the battery SOC and temperature. However, as a trade-off on the gap between model complexities computation simplification, the ECM model parameters are usually considered as constant or be piece-wisely constant. In this paper, we proposed an Adaptive Thau Observer(ATO) based online parameter estimation/tracking method, which can estimate the time-variant ECM model parameter such as RC circuit capacitance in real-time. The metrics of this method only depends on measurements of battery voltage and current, which is more feasible for real-world battery SOC/SOH estimation applications comparing with existing offline battery parameter identification methods. Finally, simulation results demonstrate the effectiveness of the proposed method.

Original languageEnglish
Title of host publicationProceedings of 2016 International Renewable and Sustainable Energy Conference, IRSEC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages936-940
Number of pages5
ISBN (Electronic)9781509057139
DOIs
Publication statusPublished - 18 Jul 2017
Event2016 International Renewable and Sustainable Energy Conference, IRSEC 2016 - Marrakech, Morocco
Duration: 14 Nov 201617 Nov 2016

Other

Other2016 International Renewable and Sustainable Energy Conference, IRSEC 2016
CountryMorocco
CityMarrakech
Period14/11/1617/11/16

Fingerprint

Parameter estimation
Equivalent circuits
Capacitance
Lithium-ion batteries
Electric network topology
Networks (circuits)
Numerical analysis
Identification (control systems)
Electric potential

Keywords

  • Adaptive Thau Observer
  • Battery RC Model
  • OCV Estimation
  • Online Parameter Estimation

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment

Cite this

Cen, Z., Kubiak, P., & Belharouak, I. (2017). Online parameter estimation/tracking for Lithium-ion battery RC model. In Proceedings of 2016 International Renewable and Sustainable Energy Conference, IRSEC 2016 (pp. 936-940). [7983979] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IRSEC.2016.7983979

Online parameter estimation/tracking for Lithium-ion battery RC model. / Cen, Zhaohui; Kubiak, Pierre; Belharouak, Ilias.

Proceedings of 2016 International Renewable and Sustainable Energy Conference, IRSEC 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 936-940 7983979.

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

Cen, Z, Kubiak, P & Belharouak, I 2017, Online parameter estimation/tracking for Lithium-ion battery RC model. in Proceedings of 2016 International Renewable and Sustainable Energy Conference, IRSEC 2016., 7983979, Institute of Electrical and Electronics Engineers Inc., pp. 936-940, 2016 International Renewable and Sustainable Energy Conference, IRSEC 2016, Marrakech, Morocco, 14/11/16. https://doi.org/10.1109/IRSEC.2016.7983979
Cen Z, Kubiak P, Belharouak I. Online parameter estimation/tracking for Lithium-ion battery RC model. In Proceedings of 2016 International Renewable and Sustainable Energy Conference, IRSEC 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 936-940. 7983979 https://doi.org/10.1109/IRSEC.2016.7983979
Cen, Zhaohui ; Kubiak, Pierre ; Belharouak, Ilias. / Online parameter estimation/tracking for Lithium-ion battery RC model. Proceedings of 2016 International Renewable and Sustainable Energy Conference, IRSEC 2016. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 936-940
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