Energy Sustainability: Using Particle Swarm Optimization to Evaluate Hydrogen Exchange Membrane Fuel Cells in altering instances

In the race for renewable energy, Protons-Exchange Membrane Fuel Cells (PEMFCs) stand out as an intriguing rival due to their low environmental footprint and superior energy conversion efficiency. However, enhancing the efficiency of power tracking in PEMFCs remains challenging, especially when dealing with unpredictable operational factors like changes in pressure or temperature. This research investigates the potential to identify the optimal operating conditions for hydrogen exchange membranes in fuel cells utilizing PSO or, (Particle Swarm Optimization). For the purpose of learning more about the complex relationship between temperature, pressure, and output tracking efficiency. Thorough evaluations demonstrate that PSO enhances power tracking performance in many settings, resulting in more efficient and reliable energy systems using PEMFCs.