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The complex interplay between numerous parasitic processes—voltage losses, crossover, decay—challenges interpretation of cycling characteristics in redox flow batteries (RFBs). Mathematical models offer a means to predict cell performance prior to testing and to interpret experimentally measured cycling data, however most implementations Require extensive domain expertise, programming knowledge, and/or computational resources. Here, we expand on our previously developed zero-dimensional modeling framework by deriving closed-form expressions for key performance metrics. The resulting closed-form model streamlines the computational structure and allows for spreadsheet modeling of cell cycling behavior, which we highlight by developing a simulation package in Microsoft® Excel®. We then apply this model to analyze previously published experimental data from our group and others, highlighting its utility in numerous diagnostic configurations—bulk electrolysis, compositionally unbalanced symmetric cell cycling, and full cell cycling. Given the accessibility of this modeling toolkit, it has potential to be a widely deployable tool for RFB research and education, aiding in data interpretation and performance prediction.
Neyhouse et al. (Mon,) studied this question.