ArticleScientific reports2024
Enhancing PEM fuel cell efficiency with flying squirrel search optimization and Cuckoo Search MPPT techniques in dynamically operating environments.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Experimental validation of metaheuristic-optimized control for standalone DFIG dynamic performance enhancement.Scientific reports · 2026Article
- A smart single stage solar battery driven desalination system with hybrid MPPT and optimal control for brackish water treatment.Scientific reports · 2025Article
- A modified perturb and observe MPPT algorithm for PEMFC with rapid convergence and low power oscillation.Scientific reports · 2025Article
- A novel global MPPT method based on sooty tern optimization for photovoltaic systems under complex partial shading.Scientific reports · 2025Article
- A high-speed MPPT based horse herd optimization algorithm with dynamic linear active disturbance rejection control for PV battery charging system.Scientific reports · 2025Article
- A novel adaptive FOCV algorithm with robust IMRAC control for sustainable and high-efficiency MPPT in standalone PV systems: experimental validation and performance assessment.Scientific reports · 2024Article
- A fuzzy-predictive current control with real-time hardware for PEM fuel cell systems.Scientific reports · 2024Article
- Experimental validation of effective zebra optimization algorithm-based MPPT under partial shading conditions in photovoltaic systems.Scientific reports · 2024Article
- Chaotic self-adaptive sine cosine multi-objective optimization algorithm to solve microgrid optimal energy scheduling problems.Scientific reports · 2024Article
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Authors and funding
6 authors.
Funding
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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.
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