Predicting Cell Cycling in Redox Flow Batteries Using Low-Dimensional Models

With increasing adoption of renewable energy sources, redox flow batteries (RFBs) offer an attractive solution to resolving their intermittent and stochastic nature. Compared to traditional batteries (e.g., Li-ion), RFBs have distinctive advantages for grid storage applications, including decoupled energy and power, design flexibility, and scalability. However, cost and reliability continue to present major hurdles to widespread commercialization. To improve RFB viability, materials discovery and cell engineering efforts typically aim to enhance device performance while reducing capital costs. Nevertheless, complex tradeoffs between various material properties, operating conditions, and performance metrics frustrate the identification of optimal system designs. Better understanding these functional relationships may improve materials selection criteria and provide critical insights into future engineering efforts.

In this work, we developed a low-dimensional model for translating fundamental material properties to cell performance. Our model, which leverages generalized assumptions about the redox flow cell geometry, can rapidly measure long-term cell performance metrics, including the capacity retention and energy efficiency. Using this approach, we explore the role of several key processes(e.g., mass transfer losses, ohmic losses, species crossover, and homogenous decay) under galvanostatic operation for one-electron redox couples. Because of its robust framework and rapid computation time, this model can be applied to optimization schemes, including parameter estimation and techno-economic analyses, thus taking a step further towards practical realization of RFBs.