基于二维网络电路法研究MEA电流密度分布特性及故障诊断

As the reliability of fuel cells, an online diagnostic method for detection of operation malfunctions, as well as the early detection of failures in the fuel cells, is necessary. For this purpose, locally resolved current density measurement is an important tool, but the interpretation of the data related to the detection of malfunctions or failures is not straightforward. Based on the high precision, real-time and controllable advantages of two-dimentional network circuit method, it is applied to on-line investigate the internal local current density distributions, temperature and error detection of the fuel cell in this study. Current density distributions are further used to determine the signature of pinhole formation in the membrane under driving cycles. Through the evolution of leakages in the fuel cell, a malfunction can be detected at an early stage and thereby catastrophic failure of the whole stack may be avoided or anticipated. In the meanwhile, the mechanism of the degradation and on-site error detection of fuel cell are achieved at the early diagnosis and control..The design of flow field and the humidity of membrane affect the internal mass transfer and local electrochemical reaction. The electrochemical reaction mechanisms for the local performance differences are induced and deduced to implement the stable operation, which provide theoretical and experimental supports for the uniformally distributed internal current density. A mathematics model is constructed by simulating and simplifying the parameters of flow field structure, relative humidity of membrane electrode, local mass concentration, etc. The fitting between simulation and experimental results is analyzed to implement the homogeneity and high performance of membrane electrode assembly. This study not only provides the scientific basis and practical methods for the optimization of fuel call performance, but also showes the direction of preparation of uniform and high performance MEA.

研究燃料电池内部局部电流密度的分布有助于理解电池内部的传热和传质现象，从而为改进电池的结构和优化性能提供重要的参考。本研究基于二维网络电路法高精度、实时、可控的优点，在线测量燃料电池内部局部电流密度和温度分布特性及故障诊断。重点研究流场、膜增湿度等条件对燃料电池内部物质传递与局部电化学反应的影响，归纳和演绎局部性能差异存在的内在电化学反应机理，最终实现燃料电池的稳定运行及性能优化，为内部电流密度均匀化提供理论支持和实验支撑；通过模拟流场结构、膜电极相对湿度、局部传质浓度等参数进行数学建模，探索模拟结果与实验结果的吻合度，实现均一、高性能的膜电极集合体的设计；研究燃料电池寿命衰减的机理及故障的现场诊断，最终实现故障的早期诊断和控制。本研究不仅为燃料电池性能的优化及寿命的延长提供了科学的依据和可行的方法，也为制备均一高性能的膜电极指明方向，并提升对燃料电池内在反应本质的认识。

研究燃料电池内部局部电流密度的分布有助于理解电池内部的传热和传质现象，从而为改进电池的结构和优化性能提供重要的参考。本研究按照项目计划，研制了一款燃料电池多功能二维网络电路板，并在此基础上开发了一种燃料电池分区在线测试系统。.通过该平台，探究了多种操作参数对燃料电池局部性能的影响，例如：使用二维网络电路探究不同温度对燃料电池性能的影响，结果发现：分区测试显示随着温度升高，电流密度分布的均匀性也随之提高，但当温度超过90℃后，均匀性开始下降。.利用二维网络电路，开展了模拟工况对燃料电池耐久性影响的实验，结果表明：200循环后，单电池性能下降明显，电池的气体入口与出口区域，衰减程度明显高于电池的中间部位。通过启停控制策略的探索，研究施加保护的启停策略对电池耐久性的影响，结果表明：采用辅助负载降载耗气的方式，有效防止了恒定辅助负载时造成的局部气体饥饿现象，避免了局部反极对燃料电池性能的影响。.在燃料电池二维网络电路上进行了快速冷启动测试实验，结果表明：在电池达到最高电流时，中间区域的电流密度最高；利用二维网络电路,分析电池内部在冷启动过程中电流密度和温度分布的变化，从而更好地优化冷启动策略，最终，实现了单电池在-20℃下启动成功。.基于二维网络电路对燃料电池膜电极电流密度分布特性进行燃料电池操作过程中的氢渗透机理的研究，测试发现：不同膜厚度MEA在不同相对湿度下性能随相对湿度增大而增大。.建立仿真模型，利用二维网络电路对仿真结果进行验证，实验发现:普通平行流场下阳极侧发生饥饿与真空效应,这与仿真结果一致，之后用仿真结果优化了流场结构，使用了楔形流场，有效抑制了燃料饥饿的现象。.通过本课题的研究，开发出的燃料电池内部反应情况可视化监测系统，为探究燃料电池内部反应机理、故障快速诊断、操作参数优化、局部设计改进等方面提供了有效的研究手段，对提高燃料电池性能及延长寿命起到了重要的作用。