Artikel
Modeling charge polarization voltage for large lithium-ion batteries in electric vehicles
Purpose: Polarization voltage of the lithium-ion battery is an important parameter that has direct influence on battery performance. The paper aims to analyze the impedance characteristics of the lithium-ion battery based on EIS data. Design/methodology/approach: The effects of currents, initial SOC of the battery on charge polarization voltage are investigated, which is approximately linear function of charge current. The change of charge polarization voltage is also analyzed with the gradient analytical method in the SOC domain. The charge polarization model with two RC networks is presented, and parts of model parameters like Ohmic resistance and charge transfer impedance are estimated by both EIS method and battery constant current testing method. Findings: This paper reveals that the Ohmic resistance accounts for much contribution to battery total polarization compared to charge transfer impedance. Practical implications: Experimental results demonstrate the efficacy of the model with the proposed identification method, which provides the foundation for battery charging optimization. Originality/value: The paper analyzed the impedance characteristics of the lithium-ion battery based on EIS data, presented a charge polarization model with two RC networks, and estimated parameters like Ohmic resistance and charge transfer impedance.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Journal of Industrial Engineering and Management (JIEM) ; ISSN: 2013-0953 ; Volume: 6 ; Year: 2013 ; Issue: 2 ; Pages: 686-697 ; Barcelona: OmniaScience
- Klassifikation
-
Management
- Thema
-
charge polarization voltage
modeling
lithium-ion batteries
electric vehicles
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Jiang, Yan
Zhang, Caiping
Zhang, Weige
Shi, Wei
Liu, Qiujiang
- Ereignis
-
Veröffentlichung
- (wer)
-
OmniaScience
- (wo)
-
Barcelona
- (wann)
-
2013
- DOI
-
doi:10.3926/jiem.895
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Jiang, Yan
- Zhang, Caiping
- Zhang, Weige
- Shi, Wei
- Liu, Qiujiang
- OmniaScience
Entstanden
- 2013
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