DocumentCode
3071423
Title
The Estimation of the Capacity of Lead-Acid Storage Battery Using Artificial Neural Networks
Author
Chen, Chao-Rong ; Huang, Kuo Hhua ; Teng, Hsiang Chung
Author_Institution
Nat. Taipei Univ. of Technol., Taipei
Volume
2
fYear
2006
fDate
8-11 Oct. 2006
Firstpage
1575
Lastpage
1579
Abstract
The capacity of lead-acid storage battery for communication system has been long estimated by constant current discharge method in the past. It spends a lot of time and labor and wastes more energy. This paper proposes a new method combining the measured data of battery discharge and the back-propagation neural network. After they are trained and learned, the back-propagation neural network can estimate the capacity of lead-acid storage battery after half hour discharge test. Therefore, the advantages of this paper are less discharge time of storage battery, less working hour and saving energy. The practical results show that the method has good performances.
Keywords
backpropagation; lead acid batteries; neural nets; power engineering computing; artificial neural networks; back-propagation neural network; constant current discharge method; lead-acid storage battery capacity; Artificial neural networks; Batteries; Cybernetics; Dielectrics and electrical insulation; Electrodes; Gravity; Lead compounds; Neural networks; Power supplies; Voltage; Back-propagation Artificial neural network (BP ANN); Battery Capacity; Lead-Acid Storage Battery;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man and Cybernetics, 2006. SMC '06. IEEE International Conference on
Conference_Location
Taipei
Print_ISBN
1-4244-0099-6
Electronic_ISBN
1-4244-0100-3
Type
conf
DOI
10.1109/ICSMC.2006.384942
Filename
4274076
Link To Document