Abstract
(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.