TY - JOUR
T1 - A Novel Model-Based Estimation Scheme for Battery-Double-Layer Capacitor Hybrid Energy Storage Systems
AU - Dey, Satadru
AU - Mohon, Sara
AU - Ayalew, Beshah
AU - Arunachalam, Harikesh
AU - Onori, Simona
N1 - Funding Information:
Manuscript received September 23, 2017; accepted November 26, 2017. Date of publication December 28, 2017; date of current version February 8, 2019. Manuscript received in final form December 4, 2017. This work was supported by the U.S. Department of Energy GATE Program under Grant DE-EE0005571. Recommended by Associate Editor L. Wang. (Corresponding author: Satadru Dey.) S. Dey is with the Department of Electrical Engineering, University of Colorado Denver, Denver, CO 80204 USA (e-mail: satadru.dey@ucdenver.edu).
Publisher Copyright:
© 1993-2012 IEEE.
PY - 2019/3
Y1 - 2019/3
N2 - Battery-double-layer capacitor (DLC) units are becoming popular hybrid energy storage systems (HESS) for vehicle propulsion, auxiliary power units, and renewable energy applications. Safe and optimal operation of the HESS requires real-time monitoring of its constituent subsystems. In this paper, we use a model-based approach to monitor HESS behavior and propose an online combined state and parameter estimation scheme using coupled electrical-thermal dynamical models for each subsystem. In particular, we focus on an HESS composed of a lead-acid (PbA) battery and a DLC for which experiments have been designed to identify the initial model parameters. The estimation scheme uses a novel cascaded observer-based structure which: 1) is designed based on sliding mode methodology and 2) exploits the coupling of the electrical and thermal dynamics. Using Lyapunov's arguments, theoretical conditions are derived which characterize the convergence of the state and parameter estimates in the presence of uncertainties. The effectiveness of the estimation scheme is evaluated via simulation and experimental studies on the PbA battery, the DLC, and the HESS system.
AB - Battery-double-layer capacitor (DLC) units are becoming popular hybrid energy storage systems (HESS) for vehicle propulsion, auxiliary power units, and renewable energy applications. Safe and optimal operation of the HESS requires real-time monitoring of its constituent subsystems. In this paper, we use a model-based approach to monitor HESS behavior and propose an online combined state and parameter estimation scheme using coupled electrical-thermal dynamical models for each subsystem. In particular, we focus on an HESS composed of a lead-acid (PbA) battery and a DLC for which experiments have been designed to identify the initial model parameters. The estimation scheme uses a novel cascaded observer-based structure which: 1) is designed based on sliding mode methodology and 2) exploits the coupling of the electrical and thermal dynamics. Using Lyapunov's arguments, theoretical conditions are derived which characterize the convergence of the state and parameter estimates in the presence of uncertainties. The effectiveness of the estimation scheme is evaluated via simulation and experimental studies on the PbA battery, the DLC, and the HESS system.
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U2 - 10.1109/TCST.2017.2781650
DO - 10.1109/TCST.2017.2781650
M3 - Article
AN - SCOPUS:85041196607
VL - 27
SP - 689
EP - 702
JO - IEEE Transactions on Control Systems Technology
JF - IEEE Transactions on Control Systems Technology
SN - 1063-6536
IS - 2
M1 - 8241461
ER -
