压力降
钒
传质
氧化还原
机械
流量(数学)
流量系数
螺旋(铁路)
下降(电信)
明渠流量
材料科学
化学
工程类
电气工程
机械工程
冶金
物理
作者
Yuwei Chai,Dawei Qu,Luyan Fan,Yating Zheng,Fan Yang
标识
DOI:10.1016/j.est.2023.110278
摘要
Flow field optimization is an important approach to enhance the performance of vanadium redox flow batteries, with a focus on improving uniform electrolyte distribution while minimizing pumping losses. In this study, we propose a novel double-spiral flow channel design which differs from the widely-used serpentine and interdigitated flow fields by introducing different flow patterns within VRFB. Two flow fields are achieved by adjusting inlets and outlets positions on the new flow channel, namely, double-spiral flow field with inlets at the center (DSFF(IC)) and double-spiral flow field with outlets at the center (DSFF(OC)). To evaluate the performance of VRFB with the new flow channel, we compare it with other flow channels, including serpentine, interdigitated, and single-spiral flow channels. Bipolar plates with different flow channels are assembled into VRFB single cell for capacity testing, cycling testing, pressure drop testing. Besides, we built a model to visualize VRFBs with different flow channels. The findings demonstrate the superior performance of VRFBs with DSFF(IC) and DSFF(OC). Compared to the serpentine flow channel, the pressure drop caused by the new channel is reduced by 33 % when the flow rate is set at 100 mL/min. Additionally, the charge and discharge tests indicate higher discharge voltage and improved system efficiency in VRFB with double-spiral flow fields. The modeling reveals that DSFF(OC) enhances convective mass transport of the electrolyte within the electrode, improving the concentration and uniformity of active species in the electrode. Impedance spectroscopy and polarization curve tests indicate that DSFF(OC) exhibits lower charge transfer resistance and mass transfer resistance compared to DSFF(IC). Under the same potential, DSFF(OC) demonstrates a higher discharge current density and achieves a peak power density of 321.5 mW/cm2, which is 13.8 % higher than that of DSFF(IC).
科研通智能强力驱动
Strongly Powered by AbleSci AI