Novel flow field design for redox flow battery using algorithmic channel generation and self-adaptive network model and experimental verification

Flow fields play a vital role in redox flow batteries (RFBs) to increase the power density. Traditional design for flow field usually employs CFD simulations with substantial computational costs and adopts enumeration and trial-and-error methods based on designers’ subjectivity, which have become a bottleneck in flow field design. In this study, a novel research paradigm is employed for flow field design in vanadium redox flow battery (VRFB), i.e., an adaptive three-dimensional equivalent network model is developed and a self-developed flow channel generation algorithm is employed to obtain optimum flow field through comparison and screening. Firstly, a flow channel library consisting of 18,135 flow fields is generated by self-developed flow channel generation algorithm. Secondly, the electrolyte flow, species transport and charge transport with various flow fields is researched by the self-adaptive equivalent network model with low computational costs due to eliminated meshing. Thirdly, pressure drop and voltage efficiency are employed to evaluate different flow fields for the aim of obtaining high-performance flow field structures through comparison and screening. The obtained high-performance flow field is fabricated and its high performance is confirmed by comprehensive experimental validation. The energy efficiency of the high-performance flow field is 4 % higher than that of the serpentine flow field investigated at 100 mA cm⁻². This work employs adaptive equivalent network model to generate and optimize flow channel for the first time, which provides a reference for flow channel selection and design.