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Accurate estimation of state-of-charge of supercapacitor under uncertain leakage and open circuit voltage map
- Source :
- Journal of Power Sources. 434:226696
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- 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.
- Subjects :
- Supercapacitor
Renewable Energy, Sustainability and the Environment
Computer science
Energy Engineering and Power Technology
Hardware_PERFORMANCEANDRELIABILITY
02 engineering and technology
Kalman filter
010402 general chemistry
021001 nanoscience & nanotechnology
01 natural sciences
0104 chemical sciences
State of charge
Hardware_GENERAL
Robustness (computer science)
Hardware_INTEGRATEDCIRCUITS
Electronic engineering
Equivalent circuit
Electrical and Electronic Engineering
Physical and Theoretical Chemistry
0210 nano-technology
Wireless sensor network
Leakage (electronics)
Parametric statistics
Subjects
Details
- ISSN :
- 03787753
- Volume :
- 434
- Database :
- OpenAIRE
- Journal :
- Journal of Power Sources
- Accession number :
- edsair.doi...........040c63b327db0efd087bdb9b00c81c48
- Full Text :
- https://doi.org/10.1016/j.jpowsour.2019.226696