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Modeling and operation optimization of a proton exchange membrane fuel cell system for maximum efficiency

机译:质子交换膜燃料电池系统的建模和操作优化,以实现最高效率

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摘要

This paper presents an operation optimization method and demonstrates its application to a proton exchange membrane fuel cell system. A constrained optimization problem was formulated to maximize the efficiency of a fuel cell system by incorporating practical models derived from actual operations of the system. Empirical and semi-empirical models for most of the system components were developed based on artificial neural networks and semi-empirical equations. Prior to system optimizations, the developed models were validated by comparing simulation results with the measured ones. Moreover, sensitivity analyses were performed to elucidate the effects of major operating variables on the system efficiency under practical operating constraints. Then, the optimal operating conditions were sought at various system power loads. The optimization results revealed that the efficiency gaps between the worst and best operation conditions of the system could reach 1.2-5.5% depending on the power output range. To verify the optimization results, the optimal operating conditions were applied to the fuel cell system, and the measured results were compared with the expected optimal values. The discrepancies between the measured and expected values were found to be trivial, indicating that the proposed operation optimization method was quite successful for a substantial increase in the efficiency of the fuel cell system. (C) 2016 Elsevier Ltd. All rights reserved.
机译:本文提出了一种运行优化方法,并论证了其在质子交换膜燃料电池系统中的应用。通过合并从系统的实际操作中得出的实用模型,制定了一个约束优化问题,以使燃料电池系统的效率最大化。基于人工神经网络和半经验方程,开发了大多数系统组件的经验模型和半经验模型。在进行系统优化之前,通过将仿真结果与实测结果进行比较来验证所开发的模型。此外,进行了敏感性分析,以阐明在实际操作约束下主要操作变量对系统效率的影响。然后,在各种系统功率负载下寻求最佳工作条件。优化结果表明,取决于功率输出范围,系统在最差和最佳运行条件之间的效率差距可能达到1.2-5.5%。为了验证优化结果,将最佳运行条件应用于燃料电池系统,并将测量结果与预期最佳值进行比较。发现测量值与期望值之间的差异很小,表明所提出的操作优化方法对于大幅提高燃料电池系统的效率非常成功。 (C)2016 Elsevier Ltd.保留所有权利。

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