Accurate information of supercapacitor (SC), also called electric double layer capacitor, leakage current is vital for effective State-of-Charge (SOC) estimation in Wireless Sensor Network (WSN) applications having long rest phase. In addition to improving accuracy of SOC estimation, real-time information on leakage current is highly beneficial for SC health monitoring. On the other hand, accurate mapping of SC open circuit voltage (OCV) vs. SOC significantly contributes towards accurate SOC estimation. Inaccuracies in either of these two information, i.e. leakage and OCV-SOC map, lead to inaccuracies in estimated SOC. In this paper, we propose a real-time estimation framework for accurate estimation of SOC under uncertain leakage and OCV-SOC map. Specifically, the proposed approach co-estimates leakage and part of OCV-SOC map in real-time along with SOC. The estimation framework utilizes Unscented Kalman Filter (UKF) along with an Equivalent Circuit Model (ECM) which captures SC leakage phenomenon. We identify the ECM parameters based on a Maxwell 25 F commercial SC. The experimentally identified ECM is subsequently used to perform simulation and experimental studies to validate the proposed framework. Finally, the robustness of the proposed framework with respect to parametric and measurement uncertainties is verified.
All Science Journal Classification (ASJC) codes
- Renewable Energy, Sustainability and the Environment
- Energy Engineering and Power Technology
- Physical and Theoretical Chemistry
- Electrical and Electronic Engineering