DocumentCode
2380449
Title
The estimation of the state of charge for lithium-ion battery by fuzzy c-regression model (FCRM) clustering algorithm
Author
Kung, Chung-Chun ; Chang, Shuo-Chieh
Author_Institution
Dept. of Electr. Eng., Tatung Univ., Taipei, Taiwan
fYear
2011
fDate
9-12 Oct. 2011
Firstpage
1568
Lastpage
1573
Abstract
In this paper, the estimation of the state of charge (SOC) of lithium-ion battery by fuzzy c-regression model (FCRM) clustering algorithm is proposed. Based on these experiment data, we apply the FCRM clustering algorithm with affine linear functional cluster representatives to build the dynamic behavior of all parameters for the RC model. Finally, the simulation results demonstrate the effectiveness of the proposed approach.
Keywords
battery chargers; electric charge; fuzzy set theory; lithium; pattern clustering; regression analysis; secondary cells; FCRM clustering; RC model; affine linear functional cluster representatives; dynamic behavior; fuzzy c-regression model; lithium-ion battery; state of charge; Batteries; Clustering algorithms; Data models; Heuristic algorithms; Mathematical model; Resistors; System-on-a-chip; fuzzy c-regression model; lithium-ion battery; state of charge;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics (SMC), 2011 IEEE International Conference on
Conference_Location
Anchorage, AK
ISSN
1062-922X
Print_ISBN
978-1-4577-0652-3
Type
conf
DOI
10.1109/ICSMC.2011.6083894
Filename
6083894
Link To Document