质子交换膜燃料电池诊断的监督分类方法

2019 IEEE 12th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED) Pub Date : 2019-08-01 DOI:10.1109/DEMPED.2019.8864841

E. Pahon, S. Jemei, D. Hissel

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引用次数: 1

摘要

本文讨论了一种用于诊断PEMFC系统的监督分类方法。目的是基于电化学阻抗测量来检测和隔离燃料电池系统发生的故障。空压机故障、燃油中毒和烟囱过热是本文研究的故障。在两个相似的堆栈上进行了一些实验测试(只有功率变化)。k近邻是监督分类方法，它以其效率和实现的简单性而闻名。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Supervised classification approach dedicated to proton exchange membrane fuel cell diagnostic

This paper deals with a supervised classification approach dedicated to diagnose a PEMFC system. The purpose is to detect and isolate a fault occurring on a fuel cell system based on electrochemical impedance measurements. The air compressor failure, fuel poisoning and stack overheating are the faults considered in this study. Some experimental tests are performed on two similar stacks (only the power changes). The k-nearest neighbors is the supervised classification method that is used as it is well known for its efficiency and simplicity of implementation.

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来源期刊

2019 IEEE 12th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED)

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