A comprehensive review of supercapacitor modelling and SOC, SOH, and RUL estimation techniques for energy management systems

Supercapacitors function as effective energy storage systems which provide high power output and fast charging and discharging and extended operational time. The precise measurement of state of charge and state of health and remaining useful life presents a major challenge that must be solved for successful energy management system implementation. This review offers an in-depth study which comprehensively examines all supercapacitor modelling methods and advanced estimation techniques that have been developed during recent years. The research assesses different modelling methods which include electrochemical models and equivalent circuit models and fractional-order models and data-driven models according to their accuracy and computational demands and their ability to function in real-world situations. The research investigates the various mechanisms which cause supercapacitors to fail and the aging patterns which result in performance loss. The article presents an extensive examination of techniques used for estimating state of charge and state of health and remaining useful life which includes model-based and data-driven and hybrid methods together with their benefits and drawbacks and their ability to function in real-time. The discussion addresses implementation factors which include sensing accuracy and computational constraints and environmental variability and system integration challenges. The research identifies existing limitations and research gaps and future development paths which will enable the creation of improved supercapacitor management systems that deliver better performance and greater reliability. This review provides essential research material which researchers and engineers can use to improve estimation accuracy and operational safety and lifecycle optimization of advanced supercapacitor energy storage systems.