DocumentCode :
3445823
Title :
A new approach for Lead-Acid batteries modeling by local cosine
Author :
Capizzi, G. ; Bonanno, F. ; Napoli, C.
Author_Institution :
Dept. of Electr., Electron. & Syst. Eng., Univ. of Catania, Catania, Italy
fYear :
2010
fDate :
14-16 June 2010
Firstpage :
1074
Lastpage :
1079
Abstract :
In this paper a new approach based on the Local Cosine Bases is proposed in order to obtain an easy and improved Lead-Acid battery modeling so avoiding the training process of RNN and the need of big amount of relative data training sets. The wavelet packet analysis give us a tools to achieve major improvements on data discrimination and analysis. In particular the Local Cosine Bases transform allows us to sensitively reduce the number of significant coefficients, it is useful to synthesize a complex signal with an high degree of approximation of the original signal.
Keywords :
lead acid batteries; wavelet transforms; RNN; data discrimination; data training sets; lead-acid battery modeling; local cosine bases; recurrent neural networks; wavelet packet analysis; Batteries; Data analysis; Energy management; Hybrid electric vehicles; Mathematical model; Recurrent neural networks; Signal synthesis; Voltage; Wavelet analysis; Wavelet packets; Lead acid battery; Local cosine basis; Modeling and simulation; Wavelet packet;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Electronics Electrical Drives Automation and Motion (SPEEDAM), 2010 International Symposium on
Conference_Location :
Pisa
Print_ISBN :
978-1-4244-4986-6
Electronic_ISBN :
978-1-4244-7919-1
Type :
conf
DOI :
10.1109/SPEEDAM.2010.5542285
Filename :
5542285
Link To Document :
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