Parameter identification algorithm for dynamic modeling of industrial-scale vanadium redox flow batteries

Abstract

In this work, we propose a two-stage parameter identification algorithm for the zero-dimensional model of vanadium redox flow battery (VRFB) based on the fitting of the available experimental data. Specifically, in the first stage, the parameters of overpotentials are obtained from the discharge polarization curve at the state of charge of 50%. In the second stage, the parameters of capacity loss and crossover are identified by the minimization of square error between the predicted and experimental charge-discharge curves at a certain value of load current. The algorithm allows to assess the degree of degradation of the battery components, and capture the effects associated with crossover and mass transfer limitations at high load currents and low flow rates. We verify this algorithm with a reference simulation considering the most interesting practical cases of battery use and validate it with three experimental VRFB systems with power and capacity ratings in the range of 5–10 kW and 5–100 kWh, correspondingly. The results show a good agreement with experimental data having an average error value of less than 1%. The results of the study are an important step in further developments of advanced control algorithms for large-scale energy storage systems.