DocumentCode :
2897383
Title :
Smart battery adaptive algorithms-system gain calibration elimination by use of adaptive learn cycle in integrated VFC measurement circuit
Author :
Bonnett, W. Bruce
Author_Institution :
Adv. Analog Products, Texas Instrum. Inc., Dallas, TX, USA
fYear :
2001
fDate :
2001
Firstpage :
311
Lastpage :
316
Abstract :
Factory calibration is eliminated for system level voltage to charge conversion gain for available charge estimation systems used in rechargeable battery applications, by taking advantage of normalized capacity learning methods. These methods allow the use of state of charge modeling techniques to predict remaining time for portable electronics applications such as talk time on cellular phones or remaining use time on computers, and eliminates the need for absolute units such as amp-hours. One such algorithm is discussed showing how this calibration can be eliminated. Time-of-use estimates are compared and analyzed against laboratory data
Keywords :
battery testers; electric current measurement; secondary cells; voltage-frequency convertors; adaptive learn cycle; cellular phone talk time; charge estimation systems; computers; current measurement; gain calibration elimination; integrated VFC measurement circuit; normalized capacity learning methods; portable electronics; rechargeable battery; remaining use time; smart battery adaptive algorithms; time-of-use estimates; Application software; Batteries; Calibration; Cellular phones; Data analysis; Learning systems; Portable computers; Predictive models; Production facilities; Voltage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applications and Advances, 2001. The Sixteenth Annual Battery Conference on
Conference_Location :
Long Beach, CA
ISSN :
1089-8182
Print_ISBN :
0-7803-6545-3
Type :
conf
DOI :
10.1109/BCAA.2001.905145
Filename :
905145
Link To Document :
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