Parameter Identification of Lithium-ion Battery Equivalent Circuit Model Based on Limited Memory Recursive Least Squares Algorithm with Variable Forgetting Factor

Equivalent circuit method is the most widely used methodology in dynamic modeling of lithium-ion battery. An equivalent circuit with second-order RC network is used to model lithium-ion battery, and a limited memory recursive least square with variable forgetting factor (VFF-LMRLS) is proposed to id...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of physics. Conference series Jg. 2246; H. 1; S. 12090 - 12099
Hauptverfasser: Peng, Xianghua, Yin, Jingyuan, Sun, Longfei, Ye, Zeyu, Wei, Tongzhen
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Bristol IOP Publishing 01.04.2022
Schlagworte:
ISSN:1742-6588, 1742-6596
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Equivalent circuit method is the most widely used methodology in dynamic modeling of lithium-ion battery. An equivalent circuit with second-order RC network is used to model lithium-ion battery, and a limited memory recursive least square with variable forgetting factor (VFF-LMRLS) is proposed to identify the model parameters in this paper. Firstly, based on the current and voltage data measured from the battery cyclic discharging experiment, the VFF-LMRLS algorithm is used to identify the time-varying parameters of equivalent circuit model. Then, the model verification system is constructed by taking the average value of the identification results in the stable stage as the component parameter value of the equivalent circuit. Finally, through the comparative experiment and analysis with the variable forgetting factor RLS (VFFRLS), it is verified that the terminal voltage error of the proposed method is smaller, indicating that the identified model parameters are closer to the actual parameters.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2246/1/012090