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首页> 外文期刊>Renewable & Sustainable Energy Reviews >Comprehensive diagnosis methodology for faults detection and identification, and performance improvement of Air-Cooled Polymer Electrolyte Fuel Cells
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Comprehensive diagnosis methodology for faults detection and identification, and performance improvement of Air-Cooled Polymer Electrolyte Fuel Cells

机译:风冷聚合物电解质燃料电池故障检测和识别以及性能改善的综合诊断方法

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This paper presents a comprehensive practical diagnosis methodology for the detection and identification of faults in Air-Cooled Polymer Electrolyte Fuel Cells (AC-PEFCs). The proper operation of an AC-PEFC depends on many factors to ensure the electrochemical process in the stack and the electricity generation from hydrogen and air. However, the stack performance depends on several factors like state of its cells, stack cooling state, stack operating and non-operating time, hydrogen and air supply pressure, hydrogen and airflow rates, and load demand. So, the diagnosis methodologies development is very helpful as part of the AC-PEFCs advanced monitoring and control systems, and of course for predictive maintenance. The developed diagnosis methodology in this paper can be understood like a diagnosis tree, in the sense that it implies an structured framework tests over the AC-PEFC: hydrogen line, air/cooling subsystem, electrical circuit and even in the stack itself. The developed diagnosis methodology allows to analysis and improving the performance of an AC-PEFC, and consequently its durability, helping to achieve this challenge, perhaps the main, to bring the fuel cells into the market.
机译:本文提出了一种全面的实用诊断方法,用于检测和识别风冷聚合物电解质燃料电池(AC-PEFC)的故障。 AC-PEFC的正确运行取决于许多因素,以确保电池组中的电化学过程以及氢和空气产生的电能。但是,电池组的性能取决于几个因素,例如电池的状态,电池组的冷却状态,电池组的工作和不工作时间,氢气和空气供应压力,氢气和气流速率以及负载需求。因此,作为AC-PEFC先进监控系统的一部分,诊断方法的发展非常有帮助,当然,对于预测性维护也是如此。从某种意义上说,它意味着对AC-PEFC的结构化框架测试:氢气管线,空气/冷却子系统,电路甚至是电池堆本身,都可以像诊断树一样理解本文中开发的诊断方法。先进的诊断方法可以分析和改善AC-PEFC的性能,并因此提高其耐用性,有助于应对这一挑战,也许是将燃料电池推向市场的主要挑战。

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