DocumentCode
2897233
Title
Artificial intelligence reads battery state-of-health in three minutes
Author
Buchmann, Isidor
Author_Institution
Cadex Elextronics Inc., Richmond, BC, Canada
fYear
2001
fDate
2001
Firstpage
263
Lastpage
265
Abstract
This work is a response to the growing need for quick testing battery reliability. Accurate quick battery testing is important as current chargers and analyzers do not provide an accurate state-of-health reading. This paper examines the development of firmware based on fuzzy logic which significantly affects the introduction of precise quick battery testing. The paper describes the Cadex 7200 battery analyser with QuickTest function
Keywords
artificial intelligence; battery testers; computerised instrumentation; firmware; fuzzy neural nets; secondary cells; Cadex 7200 battery analyser; QuickTest function; artificial intelligence; battery state-of-health; firmware; fuzzy logic; fuzzy neural network; quick testing battery reliability; Artificial intelligence; Batteries; Chemicals; Cobalt; Electronic equipment testing; Fuzzy logic; Impedance measurement; Manufacturing; Microprogramming; 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.2001.905135
Filename
905135
Link To Document