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.
Highlights
Redox flow batteries (RFBs) are electrochemical energy storage systems that have certain peculiarities compared to other equivalents such as rechargeable batteries or supercapacitors
This model can be written in state-space form as x = Ax + B1x · q1 + B2x · q2 + cj where q1 and q2 the flow rates of the anolyte and the catholyte parts, j is the vanadium redox flow battery (VRFB) current density and the state vector, x, is defined as x=[cc2, cc3, cc4, cc5, ct2, ct3, ct4, ct5]T ; where cki stands for the concentration of vanadium species i in the k, with k = {c, t} meaning concentration in the cell and the tank respectively
The state of charge (SOC) of the VRFB can be understood as the amount of energy stored in the tanks, which can be linked to the amount of V 2+, x5, and V 5+, x8, in the tanks
Summary
Redox flow batteries (RFBs) are electrochemical energy storage systems that have certain peculiarities compared to other equivalents such as rechargeable batteries or supercapacitors. The most widely used methods to estimate the state of charge (SOC) are based on measurements of the open circuit potential (OCP) [8], [9], conductivity [10], viscosity [11] or the colour of the electrolytes [12] These estimates are conditioned by the temperature dependence and the imbalance of electrolytes, so the precision decreases as they are degraded and the battery capacity fades. For SOC monitoring, the most commonly used are the electrochemical models that give a formulation for the chemical species involved in this type of systems In this scenario, Skyllas-Kazacos proposed a lumped parameter model to monitor the evolution of vanadium species inside the battery [16] based on a non-linear system; other approximations consider an equivalent electrical circuit to simplify the model [17], [18]. The work is organized as follows: section II describes the proposed VRFB model, section III describes the experimental setup, section IV describes the methodology used to tune the model, section V contains the observer formulation, section VI shows the experimental results and section VII presents the conclusions of the work
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