Parameters determination of proton exchange membrane fuel cell stack electrical model by employing the hybrid water cycle moth‐flame optimization algorithm

Summary In order to properly control the operation of a fuel cell (FC), it is essential to have a precise model of the FC. In this paper, we merged the hybrid water cycle moth‐flame optimization (WCMFO) algorithm and the notion of measurement uncertainty to extract the parameters of the proton exchange membrane fuel cell (PEMFC) by using current‐voltage characteristics (I‐V). The integration of the notion of uncertainty made the proposed approach more robust to disturbance. Consequently, a curve (I‐V) of the model estimated more precise and very similar to the real curve. To validate the performance of our approach, three commercial PEMFCs with their empirical data (I‐V) are examined as Ballard, NedSstack PS6, and BCS 500‐W. The problem of PEMFC models with seven parameters was investigated. The performance analysis is carried out by applying the sum of the squared error (SSE) and the root mean squared error (RMSE) to compare the calculated and empirical data, our approach is affirmed by its large superiority (SSE and RMSE are in the order of 10−29 and 10−15, respectively) compared to other methods recently published in Literature (SSE and RMSE are in the order of 10−2 and 10−2, respectively). This article treats the estimation problem of the parameters PEMFC models using the WCMFO algorithm. The main contribution is the combination between the WCMFO algorithm and the notion of uncertainty. Our results are widely better compared to the existing work in the literature.