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Parameter Identification of a Double-Layer-Capacitor 2-Branch Model by a Least-Squares Method

Conference Paper
Publication Date:
2013
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.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
supercapacitor; system identification; parameter estimation; orthogonal regression; total least squares
List of contributors:
Vitale, Gianpaolo; Pucci, Marcello
Authors of the University:
PUCCI MARCELLO
VITALE GIANPAOLO
Handle:
https://iris.cnr.it/handle/20.500.14243/278787
Published in:
PROCEEDINGS OF THE ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY
Series
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