One of the main issues with vanadium redox flow batteries is that vanadium ions travels across the membrane during operation which leads to a concentration imbalance and capacity loss after long-term cycling. Precise state of charge (SOC) monitoring allows the operator to effectively schedule electrolyte rebalancing and devise a control strategy to keep the battery running under optimal conditions. However, current SOC monitoring methods are too expensive and impractical to implement on commercial VRFB systems. Furthermore, physical models alone are neither reliable nor accurate enough to predict long-term capacity loss. In this paper, we present an application of using an extended Kalman filter (EKF) to estimate the total vanadium concentration in each half-cell by combining three voltage measurements and a state prediction model without crossover effects. Simulation results show that the EKF can accurately predict capacity loss for different crossover patterns over a few hundred cycles.
- Dynamic Systems and Control Division
Estimating the Concentration Imbalance of a Vanadium Redox Flow Battery With Crossover Using a Constrained Extended Kalman Filter
Yu, V, & Chen, D. "Estimating the Concentration Imbalance of a Vanadium Redox Flow Battery With Crossover Using a Constrained Extended Kalman Filter." Proceedings of the ASME 2013 Dynamic Systems and Control Conference. Volume 2: Control, Monitoring, and Energy Harvesting of Vibratory Systems; Cooperative and Networked Control; Delay Systems; Dynamical Modeling and Diagnostics in Biomedical Systems; Estimation and Id of Energy Systems; Fault Detection; Flow and Thermal Systems; Haptics and Hand Motion; Human Assistive Systems and Wearable Robots; Instrumentation and Characterization in Bio-Systems; Intelligent Transportation Systems; Linear Systems and Robust Control; Marine Vehicles; Nonholonomic Systems. Palo Alto, California, USA. October 21–23, 2013. V002T23A002. ASME. https://doi.org/10.1115/DSCC2013-3925
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