Performance enhancement of autonomous system comprising proton exchange membrane fuel cells and switched reluctance motor

It is well-known that switched reluctance motor, as a non-linear load, is a source of current ripples which reduces the life time of proton exchange membrane fuel cells and significantly affects their performances. In this work, optimal operations of autonomous stacked proton membrane fuel cells serving a switched reluctance motor are anticipated. Overall model comprising proton exchange membrane fuel cells stack and switched reluctance motor along with necessary interface and control elements are implemented using MATLAB/SIMULINK. Three key objectives are adopted to be optimized either individually or simultaneously such as: i) proton exchange membrane fuel cells stack efficiency, ii) torque per ampere ratio, and iii) torque smoothness factor. Six decision controlling parameters e.g. fuel cells' temperature, air flow rate, air pressure, fuel pressure, and turn on/off angles of switched reluctance motor represent the search space of dragonfly algorithm. Numerical results indicate that the proposed dragonfly algorithm-based method is capable of increasing proton exchange membrane fuel cells stack energy saving, and reducing of hydrogen consumption, ripples in switched reluctance motor torque and current of proton exchange membrane fuel cells stack. Finally, results generated by the dragonfly algorithm are appraised compared to those obtained by genetic algorithm which signifies its value.