DocumentCode :
666794
Title :
Parameter identification of a Double-Layer-Capacitor 2-branch model by a least-squares method
Author :
Pucci, M. ; Vitale, G. ; Cirrincione, Giansalvo ; Cirrincione, M.
Author_Institution :
ISSIA, Palermo, Italy
fYear :
2013
fDate :
10-13 Nov. 2013
Firstpage :
6770
Lastpage :
6776
Abstract :
A parameter estimation method has been developed by manipulation of the dynamical equations describing the equivalent circuit of a 2-branch Double-Layer-Capacitor (DLC) supercapacitor model. This results in an over-determined matrix equation which can be solved by a least-squares method, in particular the (Total Least Squares) TLS EXIN neuron, making it exploitable also for on-line applications. Three parameters of the circuit can be computed in this way. The remaining parameters can be easily computed by two discharge tests, respectively one at constant current and the other at constant current load This method is quick, it needs only one set of measurement data and is robust to noise and stochastic measurement errors. Both simulation and experimental tests have been made to assess the methodology.
Keywords :
equivalent circuits; estimation theory; least squares approximations; matrix algebra; measurement errors; neural nets; parameter estimation; stochastic processes; supercapacitors; 2-branch double-layer-capacitor supercapacitor model; DLC; TLS EXIN neuron; constant current load; discharge testing; dynamical equation manipulation; equivalent circuit; over-determined matrix equation; parameter estimation method; parameter identification; stochastic measurement error; total least square method; orthogonal regression; parameter estimation; supercapacitor; system identification; total least squares;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE
Conference_Location :
Vienna
ISSN :
1553-572X
Type :
conf
DOI :
10.1109/IECON.2013.6700253
Filename :
6700253
Link To Document :
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