An Efficient MPP Tracker Based on Flower Pollination Algorithm to Capture Maximum Power from PEM Fuel Cell

The maximum power point (MPP) location in the power-current curve of the Proton Exchange Membrane Fuel Cell (PEMFC) is significantly influenced by the temperature of the cell and the water content of the membrane. Accordingly, the utilization of the MPP Tracker is very important for improving the energy efficiency of the fuel cell (FC). This paper presents an efficient MPP tracker based on Flower Pollination (FP) algorithm for PEMFCs. The proposed FP-based MPP tracking (MPPT) algorithm is employed to capture the maximum power from PEMFC under different operating conditions. The proposed FP algorithm is compared with Particle Swarm Optimization (PSO) algorithm for various FC temperatures as well as various membrane water contents. Simulation results demonstrate that the proposed FP-based MPPT algorithm has better performance in terms of tracking accuracy, convergence speed, and robustness compared to the PSO algorithm. Furthermore, the FP algorithm has lower steady-state fluctuations than the PSO algorithm for different operating conditions.