Performance prediction of supercapacitor energy storage system based on characteristic parameter identification

Supercapacitor energy storage system is commonly composed of a large number of cells in parallel and series, which will increase the system's complexity and decrease its reliability and safety. In order to make sure that the system is in good condition during working cycles, mastering each cell's current performance is a key point. The current performance of supercapacitor can be described by some characteristic parameters such as equivalent capacitance and resistence. In this paper, performance prediction of supercapacitor based on equivalent circuit model and parameter identification is presented and analysed in details. According to the identification results, we can acquire the whole system's performance state and realize condition-based maintenance, which will help to extend the energy storage system's lifetime and ensure its reliability and safety.