# A Switching Observer for State-of-Charge Estimation of Reconfigurable Supercapacitors
## 5 Conclusions  
This paper addressed the challenge of accurate State-of-Charge (SOC) estimation for supercapacitors in reconfigurable circuits, a critical aspect for ensuring reliable operation and efficient energy management in these systems. We began by establishing a comprehensive mathematical model encompassing the two distinct operating states of supercapacitors within reconfigurable circuits. This model was rigorously analyzed to demonstrate its continuity and observability properties, laying the foundation for observer design.  
Recognizing the limitations of traditional observers in handling the dynamic nature of reconfigurable circuits, we proposed a novel switching observer tailored to this specific application. To rigorously evaluate its performance, we conducted a series of experiments on a hardware platform, comparing its performance against both classical and open-loop observers. The experimental results unequivocally demonstrated the superiority of the proposed switching observer, showcasing its faster convergence speed, enhanced robustness to parameter variations, and accurate tracking capabilities even during dynamic charging and switching events.  
Future research directions include the following:  
(1) Combining the switching observer framework with more sophisticated estimation algorithms, such as switching Kalman Filtering or sliding-mode observers, could further enhance its convergence speed and disturbance rejection capabilities. This integration could lead to even more accurate and robust SOC estimation, particularly in noisy environments or under rapidly changing operating conditions.  
(2) The current supercapacitor model, while effective, could be further refined by incorporating temperature dependencies and variations in ESR. These factors can significantly influence supercapacitor behavior, and their inclusion in the model would enhance the observer's accuracy, particularly over a wider range of operating temperatures and during long-term operation. This could involve developing more sophisticated temperature and aging models for the supercapacitor parameters, potentially leveraging data-driven approaches for enhanced accuracy.  
**Author Contributions**: Methodology, H.L. and Z.Z.; data curation, Z.Z.; writing--original draft preparation, H.L. and Z.Z.; writing--review and editing, C.H. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was sponsored in part by the National Natural Science Foundation of China (No. 62177046 and 62477046), Hunan 14 th Five-Year Plan Educational Science Research Project(No. XJK23 AJD022 and XJK23 AJD021), Hunan Social Science Foundation (No. 22 YBA012), and High Performance Computing Center of Central South University.  
**Institutional Review Board Statement**: Not applicable.  
**Informed Consent Statement**: Not applicable.  
**Data Availability Statement**: The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy and personal reasons.  
**Conflicts of Interest**: The authors declare no conflicts of interest.