Title :
Estimation of Lithium Polymer cell characteristic parameters through genetic algorithms
Author :
Paschero, Maurizio ; Di Giacomo, Vito ; Del Vescovo, Guido ; Rizzi, Antonello ; Mascioli, Fabio Massimo Frattale
Author_Institution :
INFOCOM Dept., Univ. di Roma Sapienza, Rome, Italy
Abstract :
In this paper the possibility to characterize a Lithium Polymer (LiPo) cell, starting from a small amount of measurements only, is investigated. Experimental results achieved by a deep measurement campaign performed on one of the lithium batteries capable of the highest power on the market are partially reported and described. Part of these results together with an analytical model and a data driven procedure based on a genetic algorithm are used to deduce different quantities believed to be important for the description of the cell behavior. Finally, deduced quantities are compared with the equivalent measured ones in order to evaluate the correctness of the proposed approach.
Keywords :
genetic algorithms; lithium; parameter estimation; power markets; secondary cells; Li; genetic algorithms; lithium batteries; lithium polymer cell; parameter estimation; power market; Batteries; Current measurement; Discharges; Resistance; System-on-a-chip; Temperature measurement; Voltage measurement;
Conference_Titel :
Electrical Machines (ICEM), 2010 XIX International Conference on
Conference_Location :
Rome
Print_ISBN :
978-1-4244-4174-7
Electronic_ISBN :
978-1-4244-4175-4
DOI :
10.1109/ICELMACH.2010.5608060