Horned Lizard Defense Tactics Optimization Algorithm for Precise Identification of PEMFC Parameters

Abstract

Proton exchange membrane fuel cells (PEMFCs) are emerging as a promising alternative power source, converting hydrogen and oxygen into clean energy. Accurate mathematical modeling of PEMFCs is essential for their simulation, evaluation, optimization, and effective management. This study introduces a newly developed metaheuristic algorithm, the Horned Lizard Defense Tactics Optimization Algorithm (HLDTOA), for parameter identification in PEMFC mathematical models, leveraging semi-empirical equations to enhance precision. The HLDTOA is applied to determine the unknown design parameters of various PEMFCs under diverse operating conditions of pressure and temperature. The HLDTOA achieved a 37.23% improvement in min sum of squared error (SSE) (0.64193093 opposed to 1.0227417), an 18.37% improvement (0.09653342 compared to 0.11827), a 3.32% improvement (1.05636977 compared to 1.0926766), and a 27.32% improvement (1.50432678 opposed to 2.07) for H-12, 250 W PEMFC SR-12, for Nedstack, respectively. Statistical analyses further demonstrate the robustness and superiority of HLDTOA. The high correlation between derived and experimentally measured I–V polarization curves underscores its precision and reliability. Additionally, the dynamic characteristics of PEMFCs are evaluated to test the optimized parameters under varying reactant pressures and cell temperatures. The HLDTOA offers exceptional accuracy and reliability in identifying unknown PEMFC parameters, marking a significant advancement in fuel cell modeling and optimization.