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Article Dans Une Revue International Journal of Electrical Power & Energy Systems Année : 2013

Online Parameter Identification for Real-Time Supercapacitor Performance Estimation in Automotive Applications

Résumé

This paper focuses on synthesizing a real-time adaptive process for supercapacitor performance estimation using a dynamic model describing the SC behavior which can vary within each experiment. We develop a simple and linear-recursive model that proved its efficiency regarding the comparison between simulation results and real data from power cycling tests. Based on a recursive least squared algorithm with a time-variant forgetting factor, the on-line estimation of the dynamic supercapacitor-model parameters, mainly the internal resistance, served as a state of health indicator. Model shows very good performances since the maximum relative modeling error do not exceed 3%. Results from state of health indicator are compared to those issued from IEC standard and electrochemical impedance spectroscopy methods.

Domaines

Electronique

Dates et versions

hal-00807911 , version 1 (04-04-2013)

Identifiants

Citer

Akram Eddahech, Mohamed Ayadi, Olivier Briat, Jean-Michel Vinassa. Online Parameter Identification for Real-Time Supercapacitor Performance Estimation in Automotive Applications. International Journal of Electrical Power & Energy Systems, 2013, 51, pp.162-167. ⟨10.1016/j.ijepes.2013.03.001⟩. ⟨hal-00807911⟩
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