Abstract
Nowadays, Fuel Cells are considered a viable alternative to the traditional sources of energy. Proton Exchange Membrane Fuel Cell (PEMFC) stack is the most common and famous kind between various kinds of fuel cell stacks. The PEMFC mathematical model is a very vital problem to understand the main performance and electrochemical features of the fuel cell. In this research paper, a new optimization algorithm called Tunicate Swarm Algorithm (TSA) is used to extract the unknown parameters of PEMFC mathematical model. Three different types of PEMFCs stacks, namely, 250W, BCS 500W and Temasek 1kW are used to validate the viability and accurateness of the TAS in solving this optimization problem. Furthermore, statistical measures based on various metrics has been performed and calculated to prove the reliability of TSA in dealing with this PEMFC's problem. The simulation results of TSA are compared with Tree growth Algorithm (TGA), Harris Hawks Optimizer (HHO) and other recent metaheuristic optimization algorithms. The optimized unknown parameters of PEMFC stacks are used to study the performance of the PEMFC in case of different temperature and pressures. The achieved results confirm the stability and precision of TSA in identifying the PEMFC's unknown parameters compared to TGA, HHO and other recent algorithms.