Maximum Power Extraction from Polymer Electrolyte Membrane (PEM) Fuel Cell Based on Deterministic Particle Swarm Optimization Algorithm

In the power-current curve of Polymer Electrolyte Membrane Fuel Cell (PEMFC), the maximum power point (MPP) locus is substantially impacted by the cell temperature and membrane water content. Consequently, the MPP Tracker is significant for enhancing fuel cell (FC) energy efficiency. In this work, for the first time, the Deterministic Particle Swarm Optimization (DPSO) technique is implemented to follow the MPP under various FC temperatures and water contents. The PEMFC model based on the DPSO technique is set up on Matlab/Simulink and compared to standard PSO (SPSO) to confirm the FC stack operation under different operating parameters. Simulation results show that both techniques can track the MPP of the FC stack under different conditions. Although the SPSO method can trace the MPP, the DPSO program outstanding it with higher convergence speed and lower power oscillation around the MPP.