DocumentCode :
592292
Title :
Adaptive detection of terminal voltage collapses for Li-ion batteries
Author :
Mukhopadhyay, Saibal ; Fumin Zhang
Author_Institution :
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
fYear :
2012
fDate :
10-13 Dec. 2012
Firstpage :
4799
Lastpage :
4804
Abstract :
We introduce a novel approach for detecting and predicting terminal voltage collapses in Li-ion batteries without having complete knowledge of a battery model. We present a simplified dynamic model for a Li-ion battery that is forced to track the output voltage curve of a physical Li-ion battery by using universal adaptive stabilization (UAS). We prove that when the physical Li-ion battery becomes unstable, then the simplified dynamic model becomes unstable. Our results do not require a sophisticated model for a battery that faithfully captures all dynamics. Using our results, we present an algorithm for detecting impending voltage collapses for Liion batteries.
Keywords :
lithium; secondary cells; Li; UAS; adaptive detection; battery model; lithium-ion batteries; simplified dynamic model; terminal voltage collapses prediction; universal adaptive stabilization; Adaptation models; Batteries; Current measurement; Discharges (electric); System-on-a-chip; Threshold voltage; Voltage measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
Conference_Location :
Maui, HI
ISSN :
0743-1546
Print_ISBN :
978-1-4673-2065-8
Electronic_ISBN :
0743-1546
Type :
conf
DOI :
10.1109/CDC.2012.6426223
Filename :
6426223
Link To Document :
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