Supercapacitors Online Parameters Estimation and State-of-Health Determination in Hybrid

Supercapacitors, also known as ultracapacitors, have received much attention from the transportation sector due to their attractive features, such as high power density, and long life-cycle, among others. Supercapacitors (SCs) can be used as an additional energy storage component in energy storage systems (ESS) in combination with lithium-ion batteries, to enhance the performance of electric vehicles (EVs) in dynamic states, including acceleration and regenerative braking modes of operation. Online accurate estimation of supercapacitors state-of-health (SoH) is essential for an efficient energy management and real-time condition monitoring. The main objective of this paper is the online State-of-Health (SoH) diagnosis based on the supercapacitors aging indicators estimation. The SoH is based on the estimation of the equivalent series resistance (ESR) and the capacitance (C), which ensures that model parameters can be defined in real-time to limit the effects of ageing. The Short-Time Fourier Transform (STFT) approach is designed to estimate the ESR and C parameters online, allowing a continuous evaluation of supercapacitors state condition. The effectiveness of the proposed method is verified by several simulation tests of a hybrid energy storage system (HESS).