El Mejdoubi, A. and Chaoui, H. and Gualous, H. and Oukaour, A. and Slamani, Y. and Sabor, J. (2016) Supercapacitors state-of-health diagnosis for electric vehicle applications. In: UNSPECIFIED.

Full text not available from this repository.
Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

This paper presents an online diagnosis method for supercapacitors' aging problem. State-of-Health (SoH) estimation is an important feature since aging introduces degradation in supercapacitors' performance, which might eventually lead to their failure. The diagnosis model is based on a sliding mode observer as a well-known technique for its high nonlinear parameters estimation performance. The main objective of this paper is the online State-of-Health diagnosis based on supercapacitors' aging indicators estimation. The effectiveness of the proposed online observer is shown through experimental results.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Uncontrolled Keywords: Diagnosis; Electric vehicles; Energy storage; Forecasting; Health; Vehicles, Aging indicators; EDLC (electric double layer capacitor or supercapacitor); Important features; Internal resistance; On-line diagnosis; Sliding mode observers; State of health; Vehicle applications, Supercapacitor
Subjects: Energy
Divisions: SCIENTIFIC PRODUCTION > Energy
Depositing User: Administrateur Eprints Administrateur Eprints
Last Modified: 31 Jan 2020 15:47
URI: http://eprints.umi.ac.ma/id/eprint/3071

Actions (login required)

View Item View Item