Vanadium Redox Flow Battery State of Charge Estimation Using a Concentration Model and a Sliding Mode Observer

Clemente, A ; Montiel, M ; Barreras, F ; Lozano, A ; Costa-Castello, R

Resumen: Vanadium redox flow batteries are very promising technologies for large-scale, inter-seasonal energy storage. Tuning models from experimental data and estimating the state of charge is an important challenge for this type of devices. This work proposes a non-linear lumped parameter concentration model to describe the state of charge that differentiates the species concentrations in the different system components and allows to compute the effect of the most relevant over-potentials. Additionally, a scheme, based on the particle swarm global optimization methodology, to tune the model taking into account real experiments is proposed and validated. Finally, a novel state of charge estimation algorithm is proposed and validated. This algorithm uses a simplified version of previous models and a sliding mode control feedback law. All developments are analytically formulated and formally validated. Additionally, they have been experimentally validated in a home-made single vanadium redox flow battery cell. Proposed methods offer a constructive methodology to improve previous results in this field.

Idioma: Inglés

DOI: 10.1109/ACCESS.2021.3079382

Año: 2021

Publicado en: IEEE Access 9 (2021), 72368-72376
ISSN: 2169-3536

Factor impacto JCR: 3.476 (2021)

Categ. JCR: COMPUTER SCIENCE, INFORMATION SYSTEMS rank: 79 / 164 = 0.482 (2021) - Q2 - T2
Categ. JCR: TELECOMMUNICATIONS rank: 43 / 93 = 0.462 (2021) - Q2 - T2
Categ. JCR: ENGINEERING, ELECTRICAL & ELECTRONIC rank: 105 / 277 = 0.379 (2021) - Q2 - T2

Factor impacto CITESCORE: 6.7 - Engineering (Q1) - Computer Science (Q1) - Materials Science (Q1)

Factor impacto SCIMAGO: 0.927 - Computer Science (miscellaneous) (Q1) - Engineering (miscellaneous) (Q1)

Tipo y forma: Artículo (Versión definitiva)