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A novel approach for fuel cell parameter estimation using simple Genetic Algorithm

机译:基于简单遗传算法的燃料电池参数估计新方法

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摘要

A new problem formulation for effective identification of fuel cell parameters is proposed. The proposed formulation is solved by applying Genetic Algorithm optimization technique. The algorithm steps are coded in MATLAB and the objective function is solved for PEM fuel cell. In order to estimate the performance of the proposed formulation; extensive simulations are performed with both the proposed and conventional objective functions and the results obtained are compared. Further, a comprehensive evaluation based on objective function value, convergence speed and absolute voltage error value is also made to prove the superiority of the proposed formulation over the conventional curve fitting approach.
机译:提出了有效识别燃料电池参数的新问题公式。通过应用遗传算法优化技术解决了提出的公式。算法步骤在MATLAB中编码,并求解了PEM燃料电池的目标函数。为了估计拟议配方的性能;使用建议的目标函数和常规的目标函数进行了广泛的仿真,并对获得的结果进行了比较。此外,还基于目标函数值,收敛速度和绝对电压误差值进行了综合评估,以证明所提出的公式优于常规曲线拟合方法。

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