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Online monitoring of fuel starvation and water management in an operating polymer electrolyte membrane fuel cell by a novel diagnostic tool based on total harmonic distortion analysis

机译:通过基于总谐波失真分析的新型诊断工具,在线监测运行中的聚合物电解质膜燃料电池中的燃料不足和水管理

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摘要

The present study deals with a novel diagnostic tool for fuel and water management problems by analyzing the harmonics on an operating polymer electrolyte membrane fuel cell. In this method, a low frequency signal is applied to the fuel cell and the total harmonic distortion contained in the resulting signal is observed under different conditions. The total harmonic distortion is used to monitor and identify the conditions online such as anode drying, anode flooding, hydrogen starvation and cathode flooding prevailing in the cell. This is done by identifying a set of indicator frequencies correspond to the aforementioned critical conditions. Through empirical studies, it is shown that frequency responses lead to a high total harmonic distortion value indicating critical conditions and provide an accurate diagnostic method to detect an even slightly degraded state. These results successfully demonstrate the promise of the proposed method in overcoming performance losses by efficient online monitoring of fuel cells. The relation between the health of the fuel cell and the variations in the harmonics present in the studied signal is characterized and utilized for the diagnostic studies of polymer electrolyte membrane fuel cell.
机译:本研究通过分析运行中的聚合物电解质膜燃料电池上的谐波,针对燃料和水管理问题提供了一种新颖的诊断工具。在该方法中,将低频信号施加到燃料电池,并且在不同条件下观察到包含在所得信号中的总谐波失真。总谐波失真用于在线监测和识别条件,例如电池中普遍存在的阳极干燥,阳极溢流,氢饥饿和阴极溢流。这是通过识别与上述关键条件相对应的一组指示器频率来完成的。通过经验研究表明,频率响应会导致高的总谐波失真值,从而指示出临界条件,并提供了一种精确的诊断方法来检测甚至稍微退化的状态。这些结果成功地证明了所提出的方法通过有效在线监测燃料电池克服性能损失的前景。表征燃料电池的健康状况和所研究信号中存在的谐波变化之间的关系,并将其用于聚合物电解质膜燃料电池的诊断研究。

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