Title :
Artificial intelligence reads battery state-of-health in three minutes
Author :
Buchmann, Isidor
Author_Institution :
Cadex Elextronics Inc., Richmond, BC, Canada
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;
Conference_Titel :
Applications and Advances, 2001. The Sixteenth Annual Battery Conference on
Conference_Location :
Long Beach, CA
Print_ISBN :
0-7803-6545-3
DOI :
10.1109/BCAA.2001.905135
