基于回声状态网络的燃料电池剩余使用寿命预测

S. Morando, S. Jemei, R. Gouriveau, N. Zerhouni, D. Hissel
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引用次数: 37

摘要

氢能载体是国际能源机构(iea)宣布的解决未来能源危机的可能方案之一。然而,各种各样的瓶颈,无论是技术上的还是社会上的,减缓了对这项技术的工业兴趣,因此燃料电池的大规模生产。在这些可能被提及的锁中,有一个与燃料电池仍然有限的使用寿命有关。为了改善这一生命周期,现有的方法之一是使用PHM(预后和健康管理)学科。该学科旨在通过使用诊断或预测算法来提高系统控制和维护操作的效率。本文介绍了PHM应用于PEMFC的预测方面,使用基于油藏计算学科工具的算法来预测剩余使用寿命。
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Fuel Cells Remaining Useful Lifetime Forecasting Using Echo State Network
The Hydrogen energy vector is one of the possible solutions to overcome future energy crisis announced by the International Energy Agency. However, various bottleneck, whether technological or societal, slow the industrial interest for this technology and therefore the mass production of fuel cells. Among these locks that may be mentioned one relating to the still limited useful lifetime of the fuel cells. To improve this lifetime, one of the existing approaches is to use the discipline of PHM (for Prognostics and Health Management). This discipline aims to improve the efficiency of control and maintenance operations on the system by using diagnostic or prognostics algorithms. This article covers the prognostics aspect of PHM applied to a PEMFC using an algorithm based on a tool from the reservoir computing discipline to predict the Remaining Useful Lifetime.
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