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A PARAMETER IDENTIFICATION APPROACH OF A PEM FUEL CELL STACK USING PARTICLE SWARM OPTIMIZATION

机译:PEM燃料电池堆的参数识别方法使用粒子群优化

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The fear of fossil fuels depletion as well as the constantly increasing pollution rates motivated most of today's engineers and researchers towards focusing on renewable energies and their applications. Fuel Cells are one of the green technologies that are being explored extensively around the world. The work of this paper was done on the 3kW ElectraGen? fuel cell system under study for domestic use in the United Arab Emirates (UAE). Several experiments were conducted at different operating points and relatively high ambient temperatures. The experimental Ⅰ/Ⅴ characteristics of the system are matched by identifying 13 different modeling parameters using basic fitting. The obtained model is then further optimized using Particle Swarm Optimization (PSO). The resulting model is validated experimentally and was found to highly resemble the system's Ⅰ/Ⅴ characteristics yielding less than 1.5 Y H_∞ norm of the error.
机译:对化石燃料的恐惧耗尽以及不断增加的污染利率在今天的大多数工程师和研究人员上专注于可再生能源及其应用。燃料电池是在世界各地广泛探索的绿色技术之一。本文的工作是在3kW Electragen完成的?在阿拉伯联合酋长国国内使用的燃料电池系统(阿联酋)。在不同的操作点和相对高的环境温度下进行了几个实验。通过使用基本配件识别13种不同的建模参数,可以匹配系统的实验Ⅰ/ⅴ特性。然后使用粒子群优化(PSO)进一步优化所获得的模型。得到的模型经过实验验证,并发现对系统的Ⅰ/ⅴ特性非常类似于误差的规范。

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