Online Supercapacitor Diagnosis for Electric Vehicle Applications

This paper presents an online diagnosis method for the supercapacitors' aging problem. State-of-health (SoH) estimation is an important feature since aging introduces degradation in the supercapacitors' performance, which might eventually lead to their failure. SoH is usually measured by electrochemical impedance spectroscopy. However, this has to be performed offline and requires interruption of the system's operation. Unlike this method, this paper presents an online diagnosis technique for supercapacitors using an extended Kalman observer as a well-known tool for its particularities and performances to study nonlinear parameter estimation. The main objective of this paper is the online SoH diagnosis based on the supercapacitors' aging indicator estimation. Moreover, the proposed online estimation strategy requires only voltage and current measurements, which reduces the number of sensors with respect to other methods. The effectiveness of the proposed online observer is shown through experimental results, and robustness to noise is also studied.