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Frequential identification of a Proton Exchange Membrane Fuel Cell (PEMFC) fractional order model

机译:质子交换膜燃料电池(PEMFC)分数阶模型的频繁识别

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The diagnosis of Proton Exchange Membrane Fuel Cells (PEMFC) is based on reliable models and methods able to follow the system operating state. Impedance spectroscopy is usually used to characterize FC systems and deduce impedance models. Indeed, the deformations of the FC impedance spectrum in the Nyquist plane translate eventual malfunctions or degradations of the system as the stack flooding or drying. This paper deals with the FC characterization using fractional order transfer function impedance model and uses frequency identification methods to identify the model's parameters. The originality of the presented model is that it uses fractional order derivatives, which make it more compact. A fractional order model can be identified either by a method estimating derivation orders and coefficients at the same time or by using a prior knowledge about derivation order and thus estimating only the coefficients of the derivation operators. In this article, parametric identification of PEMFC fractional order model is treated as a non-linear optimization problem where derivation orders are a priori fixed using Taylor approximation of Warburg impedance to deduce an explicit transfer function form.
机译:质子交换膜燃料电池(PEMFC)的诊断基于能够遵循系统运行状态的可靠模型和方法。阻抗谱通常用于表征FC系统并推导阻抗模型。实际上,奈奎斯特平面中的FC阻抗谱的变形会转化最终的故障或系统的故障,如烟囱泛滥或干燥。本文使用分数阶传递函数阻抗模型处理FC表征,并使用频率识别方法识别模型的参数。提出的模型的独创性是它使用分数阶导数,这使其更加紧凑。分数阶模型可以通过同时估算推导阶数和系数的方法来确定,也可以通过使用关于推导阶数的先验知识来确定,从而仅估算推导算子的系数。在本文中,将PEMFC分数阶模型的参数识别视为非线性优化问题,其中使用Warburg阻抗的泰勒逼近来推导阶数是先验固定的,以得出明确的传递函数形式。

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