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Statistical design of experiment approach for modeling and optimization of PEM fuel cell

机译：用于PEM燃料电池建模和优化的实验方法的统计设计

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摘要

Polymer electrolyte membrane (PEM) fuel cell has many input factors and it is very difficult to find which input factor affects response or output factor significantly. The general method of changing one factor at a time is statistically not correct because the interaction of the factors also affects the response in most of the cases. Mathematical and simulation models are important tools for designing and analysis of fuel cell-based systems. In this paper, first, a protocol for development of a 25-cm(2) active area, high performance, PEM fuel cell is presented and then its simulation model is developed using the first principle in MATLAB SIMULINK. Full factorial statistical design of experiment methodology is used to develop first- and second-order Metamodels (Mathematical model of simulation model) for PEM fuel cell to find which input factors affect the response variables significantly. Validation of the Metamodels is checked by various statistical tests, viz, normality, regression analysis, analysis of variance, and lack of fit. Steepest ascent method is used to find the maximum power delivered by PEM fuel cell within the defined ranges of input factors.
机译：聚合物电解质膜（PEM）燃料电池具有许多输入因子，很难找到哪个输入因子会显着影响响应或输出因子。一次更改一个因素的一般方法在统计上是不正确的，因为在大多数情况下，因素之间的相互作用也会影响响应。数学模型和仿真模型是用于设计和分析基于燃料电池的系统的重要工具。在本文中，首先，提出了开发25厘米（2）有效面积，高性能，PEM燃料电池的协议，然后使用MATLAB SIMULINK中的第一个原理开发了其仿真模型。实验方法的全因子统计设计用于开发PEM燃料电池的一阶和二阶元模型（模拟模型的数学模型），以找出哪些输入因子会显着影响响应变量。通过各种统计检验（即正常性，回归分析，方差分析和缺乏拟合）来检查元模型的有效性。最陡峭的上升方法用于在定义的输入因子范围内查找PEM燃料电池传递的最大功率。

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