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.

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

Pucci M;Vitale G;
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.
2013
Istituto di Studi sui Sistemi Intelligenti per l'Automazione - ISSIA - Sede Bari
supercapacitor
system identification
parameter estimation
orthogonal regression
total least squares
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/278787
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