Metaheuristic-based energy management strategies for fuel cell emergency power unit in electrical aircraft

Abstract This paper aims at presenting a comparative analysis of different metaheuristic algorithms in the application of energy management for fuel cell-based hybrid emergency power unit within electrical aircraft. Two energy management conventional strategies are employed while optimizing the operating temperature. Both the external energy maximization and the equivalent consumption minimization strategies are dealt with. The most efficient up-to-date metaheuristic techniques such as the artificial bee colony, the grey wolf optimization, the cuckoo search, the mine blast algorithm, the whale optimization algorithm, the moth swarm algorithm, the harmony search, the modified flower pollination algorithm and the electromagnetic field optimization are considered. The overall index of optimization performance is considered as a function of hydrogen consumption, overall system efficiency, variations of states of charge and stresses in different energy sources. The numerical simulations, through Matlab™/Simulink, highlights the capability of the different metaheuristic optimization techniques towards reducing the amount of consumed hydrogen in fuel cell-based emergency power unit in electrical aircrafts. The electromagnetic field optimization method results in significant hydrogen consumption reduction in comparison with the other proposed techniques.