Adaptive Energy Estimation for Supercapacitors Using Observer-Based Methods Under Scenario Variation

This paper presents an adaptive observer-based approach to estimate the state-of-energy (SoE) of supercapacitors (SCs) under varying load scenarios. We model the SC with a first-order resistance–capacitance (RC) equivalent circuit with time-varying parameters and design an adaptive observer to track the internal resistance and capacitance in real time. The SoE is then computed using the updated parameters. For validation, all experiments are conducted using manually generated simulation data of three deterministic load profiles to mimic realistic charge/discharge scenarios. We compare three estimation methods: the conventional fixed-capacitance method, an ideal reference (using true dynamic parameters), and our proposed adaptive estimator. Results show that the adaptive method converges the parameter estimates quickly and maintains an accurate SoE prediction across all scenarios. In contrast, the conventional estimator accumulates error when the operating conditions change. The adaptive approach yields significantly lower root-mean-square error (RMSE) in SoE (on the order of ۰.۵–۱%) compared to several percent error for the conventional method, demonstrating its robustness under scenario variation.

کلیدواژه ها:

Supercapacitor state-of-energy (SoE) estimation ، Adaptive observer ، Online parameter identification ، Equivalent circuit model (RC model) ، Scenario-based robustness analysis