DOI码：10.1016/j.est.2025.118714
发表刊物：Journal of Energy Storage
摘要：Redox flow batteries (RFBs) represent a crucial long-duration energy storage solution for renewable energy integration in future power grids. While flow field design critically determines RFB system efficiency, traditional optimization methods for convection-enhanced flow fields remain constrained by time-consuming simulations and labor-intensive experimental validation. Through comprehensive analysis of 110 digitized flow field simulations, we elucidate the fundamental trade-offs between longitudinal and transverse electrolyte distribution pathways and establish a data-driven predictive model with universal applicability across diverse flow field configurations and operational parameters. We introduce a key statistical descriptor that enables precise prediction of optimal flow field configurations for any given channel number. By incorporating the relative inlet-outlet positioning, the model is further extended to predict optimal designs within specified spatial constraints. The developed statistical framework provides a rational, high-efficiency strategy for flow field optimization, paving the way of the commercialization of high-performance RFB systems.
合写作者：Liu He,Yunfei Liu,Zhaoyang Xu
通讯作者：Zhejun Li*
论文编号：https://authors.elsevier.com/a/1luZ9,rUrFxnOd
卷号：138
页面范围：118714
是否译文：否
发表时间：2025-10-07
发表时间：2025-10-07