A Spreadsheet-Based Redox Flow Battery Cell Cycling Model Enabled by Closed-Form Approximations

Bertrand J. Neyhouse, F. Brushett
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Abstract

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.
基于电子表格的氧化还原液流电池电池循环模型,采用闭式近似法
众多寄生过程--电压损失、交叉、衰减--之间复杂的相互作用给氧化还原液流电池(RFB)循环特性的解释带来了挑战。数学模型为测试前预测电池性能和解释实验测量的循环数据提供了一种方法,但大多数数学模型的实现需要大量的专业领域知识、编程知识和/或计算资源。在此,我们通过推导关键性能指标的闭式表达,扩展了之前开发的零维建模框架。由此产生的闭式模型简化了计算结构,并允许对细胞循环行为进行电子表格建模。然后,我们将该模型应用于分析我们小组和其他小组之前公布的实验数据,强调了该模型在大量诊断配置中的实用性--大量电解、成分不平衡的对称细胞循环和完全细胞循环。鉴于该建模工具包的易用性,它有可能成为 RFB 研究和教育中广泛使用的工具,有助于数据解释和性能预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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