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In this paper, two maximum power point tracking (MPPT) methods for Fuel Cell(FC) systems based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) andImperialist Competitive Algorithm trained Neural Network (ICANN) are presented.The first operation voltage of the fuel cell corresponding to maximum powerpoint is determined based on the data, and then the duty cycle of a DC/DCconverter is adjusted using fuzzy logic controller to force the system thatoperates in conditions which match up with its maximum power point, in order tominimize the fuel consumption. The proposed systems and conventional fuzzycontroller system are simulated in the MATLAB environment and results showacceptable operation under fast variation of conditions as well as normalconditions in minimum time.

New Hybrid Maximum Power Point Tracking Methods for Fuel Cell using Artificial Intelligent