Adaptive, multi-parameter battery state estimator with optimized time-weighting factors

We derive and implement a battery control algorithm that can accommodate an arbitrary number of model parameters, with each model parameter having its own time-weighting factor, and we propose a method to determine optimal values for the time-weighting factors. Time-weighting factors are employed to...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Journal of applied electrochemistry Ročník 37; číslo 5; s. 605 - 616
Hlavný autor: Verbrugge, Mark
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Dordrecht Springer Nature B.V 01.05.2007
Predmet:
Adaptive algorithms
Control algorithms
Control theory
Lithium
Lithium-ion batteries
Mathematical models
Parameters
Rechargeable batteries
State estimation
Weighting
ISSN:0021-891X, 1572-8838
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:We derive and implement a battery control algorithm that can accommodate an arbitrary number of model parameters, with each model parameter having its own time-weighting factor, and we propose a method to determine optimal values for the time-weighting factors. Time-weighting factors are employed to give greater impact to recent data for the determination of a system’s state. We employ the (controls) methodology of weighted recursive least squares, and the time weighting corresponds to the exponential-forgetting formalism. The output from the adaptive algorithm is the battery state of charge (remaining energy), state of health (relative to the battery’s nominal performance), and predicted power capability. Results are presented for a high-power lithium ion battery.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ObjectType-Article-2
ObjectType-Feature-1
content type line 23
ISSN:0021-891X
1572-8838
DOI:10.1007/s10800-007-9291-7