Enhancing PEM fuel cell efficiency with flying squirrel search optimization and Cuckoo Search MPPT techniques in dynamically operating environments
Document Type
Article
Publication Date
6-1-2024
Abstract
This study looks into how to make proton exchange membrane (PEM) fuel cells work more efficiently in environments that change over time using new Maximum Power Point Tracking (MPPT) methods. We evaluate the efficacy of Flying Squirrel Search Optimization (FSSO) and Cuckoo Search (CS) algorithms in adapting to varying conditions, including fluctuations in pressure and temperature. Through meticulous simulations and analyses, the study explores the collaborative integration of these techniques with boost converters to enhance reliability and productivity. It was found that FSSO consistently works better than CS, achieving an average increase of 12.5% in power extraction from PEM fuel cells in a variety of operational situations. Additionally, FSSO exhibits superior adaptability and convergence speed, achieving the maximum power point (MPP) 25% faster than CS. These findings underscore the substantial potential of FSSO as a robust and efficient MPPT method for optimizing PEM fuel cell systems. The study contributes quantitative insights into advancing green energy solutions and suggests avenues for future exploration of hybrid optimization methods.
Keywords
Boost converter integration, Cuckoo Search (CS), Dynamically operating environments, Flying Squirrel Search Optimization (FSSO), Maximum power point tracking (MPPT), PEM fuel cell
Divisions
sch_ecs
Publication Title
Scientific Reports
Volume
14
Issue
1
Publisher
Nature Research
Publisher Location
HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY