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A random-effects model for long-term degradation analysis of solid oxide fuel cells

机译：固体氧化物燃料电池长期降解分析的随机效应模型

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摘要

Solid oxide fuel cells (SOFCs) are electrochemical devices converting the chemical energy into electricity with high efficiency and low pollutant emissions. Tough very promising, this technology is still in a developing phase, and degradation at the cell/stack level with operating time is still an issue of major concern. Methods to directly observe degradation modes and to measure their evolution over time are difficult to implement, and indirect performance indicators are adopted, typically related to voltage measurements in long-term tests. In order to describe long-term degradation tests, three components of the voltage measurements should be modelled: the smooth decay of voltage over time for each single unit; the variability of voltage decay among units; and the high-frequency small fluctuations of voltage due to experimental noise and lack of fit. In this paper, we propose an empirical random-effects regression model of polynomial type enabling to evaluate separately these three types of variability. Point and interval estimates are also derived for some performance measures, such as the mean voltage, the prediction of cell voltage, the reliability function and the cell-to-cell variability in SOFC stacks. Finally, the proposed methodology is applied to two real case-studies of long-term degradation tests of SOFC stacks. (C) 2015 Elsevier Ltd. All rights reserved.
机译：固体氧化物燃料电池（SOFC）是电化学装置，可将化学能高效转化为电能，并且污染物排放低。尽管这项技术非常有前途，但仍处于发展阶段，并且随着时间的推移，电池/电池组的退化仍然是一个主要问题。直接观察退化模式并测量其随时间变化的方法很难实现，因此采用了间接性能指标，通常与长期测试中的电压测量有关。为了描述长期的退化测试，应该对电压测量的三个组成部分建模：每个单元的电压随时间的平滑衰减；单元之间电压衰减的变化；以及由于实验噪声和缺乏拟合而导致的高频小电压波动。在本文中，我们提出了多项式类型的经验随机效应回归模型，能够分别评估这三种类型的变异性。还针对一些性能度量得出点和间隔估计，例如平均电压，电池电压的预测，可靠性函数以及SOFC电池组中的电池间变化。最后，将所提出的方法应用于SOFC烟囱的长期退化测试的两个实际案例研究。 （C）2015 Elsevier Ltd.保留所有权利。

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