首页> 外文期刊>International journal of hydrogen energy >Rotary-gradient fitting algorithm for polarization curves of Proton Exchange Membrane Fuel Cells (PEMFCs)
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Rotary-gradient fitting algorithm for polarization curves of Proton Exchange Membrane Fuel Cells (PEMFCs)

机译:质子交换膜燃料电池极化曲线的旋转梯度拟合算法

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Experimental data obtained in electrochemistry traditionally have been fitted to models in order to obtain relevant parameters of the underlying processes. Polarization curves are among the most important representations of fuel cell performance, as they are useful tools for studying the performance of these cells in operation. On this basis, we developed an algorithm to fit the experimental polarization curves employing two different models. This algorithm combines different optimization techniques, such as rotary optimization and gradient optimization. Seven experimental polarization curves, obtained with different experimental proton exchange membrane fuel cell (PEMFC) membrane electrode assemblies (MEAs), are used to evaluate the proposed fitting techniques and theoretical models. The average quadratic errors of the models fitted by the algorithm are below 9 mV in all the curves, much less than the 750-1000 mV voltage variation in them. Therefore, we propose that the algorithm and the models are good options for use in fitting these data.
机译:传统上,将在电化学中获得的实验数据拟合到模型中,以获得潜在过程的相关参数。极化曲线是燃料电池性能最重要的代表之一,因为它们是研究运行中这些电池性能的有用工具。在此基础上,我们开发了一种使用两种不同模型拟合实验极化曲线的算法。该算法结合了不同的优化技术,例如旋转优化和梯度优化。使用不同的实验质子交换膜燃料电池(PEMFC)膜电极组件(MEA)获得的七个实验极化曲线,用于评估提出的拟合技术和理论模型。该算法拟合的模型的平均二次误差在所有曲线中均低于9 mV,远低于其中750-1000 mV的电压变化。因此,我们认为算法和模型是用于拟合这些数据的良好选择。

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