TY - JOUR
T1 - Accurate estimation of state-of-charge of supercapacitor under uncertain leakage and open circuit voltage map
AU - Saha, Pankaj
AU - Dey, Satadru
AU - Khanra, Munmun
N1 - Funding Information:
This work is supported in part by Science for Equity, Empowerment & Development (SEED) Division, Department of Science & Technology, Ministry of Science and Technology, India under SYST; Ref. SP/YO/054/2016 .
Publisher Copyright:
© 2019 Elsevier B.V.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2019/9/15
Y1 - 2019/9/15
N2 - 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.
AB - 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.
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U2 - 10.1016/j.jpowsour.2019.226696
DO - 10.1016/j.jpowsour.2019.226696
M3 - Article
AN - SCOPUS:85067258258
VL - 434
JO - Journal of Power Sources
JF - Journal of Power Sources
SN - 0378-7753
M1 - 226696
ER -