Adaptive Estimation of Quasi-Empirical Proton Exchange Membrane Fuel Cell Models Based on Coot Bird Optimizer and Data Accumulation

Abstract

The ambitious spread of fuel cell usage is facing the aging problem, which has a significant impact on the cells’ output power. Therefore, it is necessary to develop reliable techniques that are capable of accurately characterizing the cell throughout its life. This paper proposes an adaptive parameter estimation technique to develop a robust proton exchange membrane fuel cell (PEMFC) model over its lifespan. This is useful for accurate monitoring, analysis, design, and control of the PEMFC and increasing its life. For this purpose, fair comparisons of nine recent optimization algorithms were made by implementing them for a typical quasi-empirical PEMFC model estimation problem. Investigating the best competitors relied on two conceptual factors, the solution accuracy and computational burden (as a novel assessment factor in this study). The computational burden plays a great role in accelerating the model parameters’ update process. The proposed techniques were applied to five commercial PEMFCs. Moreover, a necessary statistical analysis of the results was performed to make a solid comparison with the competitors. Among them, the proposed coot-bird-algorithm (CBO)-based technique achieved a superior and balanced performance. It surpassed the closest competitors by a difference of 16.01% and 62.53% in the accuracy and computational speed, respectively.

Network performance oriented study of sensor nodes combining improved COOT and MOAHA algorithms

“…In order to improve this shortcoming, the study utilizes multi-strategies such as the Lé vy flight perturbation strategy and the reverse learning strategy to improve COOT. Lé vy flight is a random wandering search that obeys the Lé vy distribution, and perturbing COOT through the Lé vy flight strategy helps to increase the population diversity [8]. The inverse learning strategy, on the other hand, guides the algorithm to explore different search paths from non-optimal solutions, thus increasing the possibility of finding the global optimal solution [9].…”

PEMFC Current Control Using a Novel Compound Controller Enhanced by the Black Widow Algorithm: A Comprehensive Simulation Study

“…The PEMFC work principle can be summarized in Figure 1. At the PEMFC core, which is an acidic solid membrane, two electrochemical reactions take place successively [34].…”

“…At the level of the anode, in the presence of platinum, a catalytic oxidation occurs and the hydrogen dissociates from its electrons [34]:…”

“…At the level of the cathode, in the presence of platinum, a catalytic reduction occurs: the oxygen combines with the protons that have crossed the electrolyte membrane and the electrons arriving from the external circuit. The reaction produces heat and water [34]: A single PEMFC voltage can be described as follows [34]:…”