The Effect of Input Parameter Variation on the Accuracy of a Vanadium Redox Flow Battery Simulation Model

Accurately predicting battery behavior, while using low input data, is highly desirable in embedded simulation architectures like grid or integrated energy system analysis. Currently, the available vanadium redox flow battery (VRFB) models achieve highly accurate predictions of electrochemical behav...

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Bibliographic Details
Published in:Batteries (Basel) 2021-01, Vol.7 (1), p.7
Main Authors: Zugschwert, Christina, Dundálek, Jan, Leyer, Stephan, Hadji-Minaglou, Jean-Régis, Kosek, Juraj, Pettinger, Karl-Heinz
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Alternative energy sources
Circuits
Control algorithms
Current loss
Data reduction
Efficiency
Electrochemical analysis
Energy resources
energy storage
grey box simulation model
Integrated energy systems
Mathematical models
Model accuracy
modeling
Open circuit voltage
Optimization
Parameter estimation
parameter optimization process
Parameterization
Process parameters
Rechargeable batteries
redox flow battery
Renewable resources
Simulation
Storage capacity
Systems analysis
Vanadium
vanadium redox flow battery
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Summary:Accurately predicting battery behavior, while using low input data, is highly desirable in embedded simulation architectures like grid or integrated energy system analysis. Currently, the available vanadium redox flow battery (VRFB) models achieve highly accurate predictions of electrochemical behavior or control algorithms, while the optimization of the required input data scope is neglected. In this study, a parametrization tool for a DC grey box simulation model is developed using measurements with a 10 kW/100 kWh VRFB. An objective function is applied to optimize the required input data scope while analyzing simulation accuracy. The model is based on a differential-algebraic system, and an optimization process allows model parameter estimation and verification while reducing the input data scope. Current losses, theoretical storage capacity, open circuit voltage, and ohmic cell resistance are used as fitting parameters. Internal electrochemical phenomena are represented by a self-discharge current while material related losses are represented by a changing ohmic resistance. Upon reducing input data the deviation between the model and measurements shows an insignificant increase of 2% even for a 60% input data reduction. The developed grey box model is easily adaptable to other VRFB and is highly integrable into an existing energy architecture.
ISSN:2313-0105
2313-0105
DOI:10.3390/batteries7010007