A novel parameters identification method of Lithium-ion battery equivalent circuit model under dynamic stress test

Hung Yu Pai; Yi Hua Liu; Guan Jhu Chen; Desire Rasolomampionona; Elia Brescia; Enrico De Tuglie

doi:10.1109/EEEIC/ICPSEurope57605.2023.10194649

A novel parameters identification method of Lithium-ion battery equivalent circuit model under dynamic stress test

Hung Yu Pai
, Yi Hua Liu
, Guan Jhu Chen
, Desire Rasolomampionona
, Elia Brescia
, Enrico De Tuglie

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

Abstract

This paper selects the second-order equivalent circuit model (2nd ECM) as the battery model and proposes decoupled recursive least squares with adaptive moving window forgetting factor (AMWFF-DRLS), and the algorithm decouples different dynamic impedances in the 2nd ECM. The objective function solves the interference between each other and successfully combines the proposed AMWFF technology to make adaptive weight adjustments through historically predicted voltage response error data points, effectively reducing the amount of algorithm calculation and improving parameter identification accuracy. Finally, this paper establishes a mathematical model of Lithium-ion batteries on the MATLAB platform and selects a dynamic stress test (DST), to verify the model parameter estimation ability of the AMWFF-DRLS. The estimation performance is compared with traditional RLS methods. Under the DST working condition, the average absolute error (MAE) of AMWFF-DRLS is improved by 16.67 % compared to the traditional RLS, while the root mean square error (RMSE) is improved by 14.93 %.

Original language	English
Title of host publication	Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023
Editors	Zbigniew Leonowicz
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350347432
DOIs	https://doi.org/10.1109/EEEIC/ICPSEurope57605.2023.10194649
State	Published - 2023
Externally published	Yes
Event	2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023 - Madrid, Spain Duration: 06 06 2023 → 09 06 2023

Publication series

Name	Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023

Conference

Conference	2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023
Country/Territory	Spain
City	Madrid
Period	06/06/23 → 09/06/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

Adaptive forgetting factor
Battery management system
Equivalent circuit model
Recursive least square

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/EEEIC/ICPSEurope57605.2023.10194649

Cite this

Pai, H. Y., Liu, Y. H., Chen, G. J., Rasolomampionona, D., Brescia, E., & De Tuglie, E. (2023). A novel parameters identification method of Lithium-ion battery equivalent circuit model under dynamic stress test. In Z. Leonowicz (Ed.), Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023 (Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EEEIC/ICPSEurope57605.2023.10194649

Pai, Hung Yu ; Liu, Yi Hua ; Chen, Guan Jhu et al. / A novel parameters identification method of Lithium-ion battery equivalent circuit model under dynamic stress test. Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023. editor / Zbigniew Leonowicz. Institute of Electrical and Electronics Engineers Inc., 2023. (Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023).

@inproceedings{2f5ad75137664abe8217d77c657bfe3e,

title = "A novel parameters identification method of Lithium-ion battery equivalent circuit model under dynamic stress test",

abstract = "This paper selects the second-order equivalent circuit model (2nd ECM) as the battery model and proposes decoupled recursive least squares with adaptive moving window forgetting factor (AMWFF-DRLS), and the algorithm decouples different dynamic impedances in the 2nd ECM. The objective function solves the interference between each other and successfully combines the proposed AMWFF technology to make adaptive weight adjustments through historically predicted voltage response error data points, effectively reducing the amount of algorithm calculation and improving parameter identification accuracy. Finally, this paper establishes a mathematical model of Lithium-ion batteries on the MATLAB platform and selects a dynamic stress test (DST), to verify the model parameter estimation ability of the AMWFF-DRLS. The estimation performance is compared with traditional RLS methods. Under the DST working condition, the average absolute error (MAE) of AMWFF-DRLS is improved by 16.67 \% compared to the traditional RLS, while the root mean square error (RMSE) is improved by 14.93 \%.",

keywords = "Adaptive forgetting factor, Battery management system, Equivalent circuit model, Recursive least square",

author = "Pai, \{Hung Yu\} and Liu, \{Yi Hua\} and Chen, \{Guan Jhu\} and Desire Rasolomampionona and Elia Brescia and \{De Tuglie\}, Enrico",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023 ; Conference date: 06-06-2023 Through 09-06-2023",

year = "2023",

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series = "Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

editor = "Zbigniew Leonowicz",

booktitle = "Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023",

address = "美国",

}

Pai, HY, Liu, YH, Chen, GJ, Rasolomampionona, D, Brescia, E & De Tuglie, E 2023, A novel parameters identification method of Lithium-ion battery equivalent circuit model under dynamic stress test. in Z Leonowicz (ed.), Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023. Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023, Madrid, Spain, 06/06/23. https://doi.org/10.1109/EEEIC/ICPSEurope57605.2023.10194649

A novel parameters identification method of Lithium-ion battery equivalent circuit model under dynamic stress test. / Pai, Hung Yu; Liu, Yi Hua; Chen, Guan Jhu et al.
Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023. ed. / Zbigniew Leonowicz. Institute of Electrical and Electronics Engineers Inc., 2023. (Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A novel parameters identification method of Lithium-ion battery equivalent circuit model under dynamic stress test

AU - Pai, Hung Yu

AU - Liu, Yi Hua

AU - Chen, Guan Jhu

AU - Rasolomampionona, Desire

AU - Brescia, Elia

AU - De Tuglie, Enrico

PY - 2023

Y1 - 2023

N2 - This paper selects the second-order equivalent circuit model (2nd ECM) as the battery model and proposes decoupled recursive least squares with adaptive moving window forgetting factor (AMWFF-DRLS), and the algorithm decouples different dynamic impedances in the 2nd ECM. The objective function solves the interference between each other and successfully combines the proposed AMWFF technology to make adaptive weight adjustments through historically predicted voltage response error data points, effectively reducing the amount of algorithm calculation and improving parameter identification accuracy. Finally, this paper establishes a mathematical model of Lithium-ion batteries on the MATLAB platform and selects a dynamic stress test (DST), to verify the model parameter estimation ability of the AMWFF-DRLS. The estimation performance is compared with traditional RLS methods. Under the DST working condition, the average absolute error (MAE) of AMWFF-DRLS is improved by 16.67 % compared to the traditional RLS, while the root mean square error (RMSE) is improved by 14.93 %.

AB - This paper selects the second-order equivalent circuit model (2nd ECM) as the battery model and proposes decoupled recursive least squares with adaptive moving window forgetting factor (AMWFF-DRLS), and the algorithm decouples different dynamic impedances in the 2nd ECM. The objective function solves the interference between each other and successfully combines the proposed AMWFF technology to make adaptive weight adjustments through historically predicted voltage response error data points, effectively reducing the amount of algorithm calculation and improving parameter identification accuracy. Finally, this paper establishes a mathematical model of Lithium-ion batteries on the MATLAB platform and selects a dynamic stress test (DST), to verify the model parameter estimation ability of the AMWFF-DRLS. The estimation performance is compared with traditional RLS methods. Under the DST working condition, the average absolute error (MAE) of AMWFF-DRLS is improved by 16.67 % compared to the traditional RLS, while the root mean square error (RMSE) is improved by 14.93 %.

KW - Adaptive forgetting factor

KW - Battery management system

KW - Equivalent circuit model

KW - Recursive least square

UR - https://www.scopus.com/pages/publications/85168708056

U2 - 10.1109/EEEIC/ICPSEurope57605.2023.10194649

DO - 10.1109/EEEIC/ICPSEurope57605.2023.10194649

M3 - 会议稿件

AN - SCOPUS:85168708056

T3 - Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023

BT - Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023

A2 - Leonowicz, Zbigniew

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023

Y2 - 6 June 2023 through 9 June 2023

ER -

Pai HY, Liu YH, Chen GJ, Rasolomampionona D, Brescia E, De Tuglie E. A novel parameters identification method of Lithium-ion battery equivalent circuit model under dynamic stress test. In Leonowicz Z, editor, Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023). doi: 10.1109/EEEIC/ICPSEurope57605.2023.10194649

A novel parameters identification method of Lithium-ion battery equivalent circuit model under dynamic stress test

Abstract

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Bibliographical note

Keywords

UN SDGs

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