An Information Analysis Based Online Parameter Identification Method for Lithium-ion Batteries in Electric Vehicles

This article proposes an information analysis-based multiple adaptive forgetting factors (FFs) recursive least squares (IA-MAFF-RLS) method to identify model parameters of lithium-ion batteries in electric vehicles. First, a Cramer-Rao lower bound (CRLB) based information analysis is implemented for...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on industrial electronics (1982) 2024-07, Vol.71 (7), p.1-11
Hauptverfasser:	Guo, Ruohan, Shen, Weixiang
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation models Batteries Data analysis Data models Electric vehicles Equivalent-circuit model Estimation error Extended Kalman filter Identification methods information analysis Information management Information theory Integrated circuit modeling Lithium-ion batteries lithium-ion battery (LIB) Lower bounds Noise levels Parameter identification Rechargeable batteries recursive least squares Regression models State of charge Voltage measurement
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!