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

Abstract

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.

Keywords

• Vanadium redox flow battery modelling
• state of charge estimation
• non-linear model tuning from experimental data
• particle swarm optimization
• sliding mode observer