Dual Extended Kalman Filter for State of Charge Estimation of Lithium–Sulfur Batteries

Lithium-Sulfur is a promising technology for the next generation of batteries and research efforts for early-stage prototype implementation increased in recent years. For the development of a suitable Battery Management System, a state estimator is required; however, lithium-sulfur behavior presents...

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Bibliographic Details
Published in:Energies (Basel) 2022-10, Vol.15 (19), p.6989
Main Authors: Trilla, Lluís, Canals Casals, Lluc, Jacas, Jordi, Paradell, Pol
Format: Article
Language:English
Subjects:
Accuracy
Aging
Algorithms
Analysis
Batteries
Battery Management System
cell model
Extended Kalman filter
Lithium
Lithium sulfur batteries
lithium–sulfur battery
Observability (systems)
Parameter estimation
SoC estimation
State estimation
State of charge
Sulfur
Sulfur compounds
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Summary:Lithium-Sulfur is a promising technology for the next generation of batteries and research efforts for early-stage prototype implementation increased in recent years. For the development of a suitable Battery Management System, a state estimator is required; however, lithium-sulfur behavior presents a large non-observable region that may difficult the convergence of the state estimation algorithm leading to large errors or even instability. A dual Extended Kalman Filter is proposed to circumvent the non-observability region. This objective is achieved by combining a parameter estimation algorithm with a cell model that includes non-linear behavior such as self-discharge and cell degradation. The resulting dual Kalman filter is applied to lithium–sulfur batteries to estimate their State-of-Charge incorporating the effects of degradation, temperature, and self-discharge deviations.
ISSN:1996-1073
1996-1073
DOI:10.3390/en15196989