Optimal Control of Proton Exchange Membrane Fuel Cell Based on Particle Swarm Optimization and Genetic Algorithm

Abstract

Since the operation of a Proton Exchange Membrane Fuel Cell (PEMFC) is extremely nonlinear process as well as its parameters change when it is operating, a designer can’t easily to control it; accordingly conventional controllers cannot satisfy the control objectives as well as the intelligent controllers. Thus, in this paper an intelligent controller is proposed for fuel cell stack control system based on Particle Swarm Optimization (PSO). In order to analyze the efficiency of this method, the results are compared with other intelligent controller based on Genetic Algorithm (GA). The simulation results demonstrate the high performance capability of both proposed controllers in terms of precise and convergence speed

Keywords

• Intelligent controller, Genetic Algorithm, Particle swarm optimization, Proton exchange membrane fuel cell

References

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