Optimizing the Efficiency of a Fuel Cell – Supercapacitor Fed Open-End Winding Induction Motor

This research describes the model of an open-end winding induction motor powered by hybrid clean energy sources. The sources consist of a proton exchange membrane (PEM) fuel cell which is characterized by its high energy density and a supercapacitor which is characterized by its high power density. The fuel cell and supercapacitor power sources are directly connected to a dual classical inverter (DC/AC) to power an open-end winding induction motor (OEWIM). Such winding configuration results in enhanced reliability, efficiency, power quality, and redundancy compared to the conventional star/ delta configuration. The control of this system is realized by the implementation of a power-sharing algorithm between the sources. Moreover, the best-computed power-sharing configuration $(\alpha)$ is related to the maximum possible efficiency of the system. The paper aims to solve an optimization problem that effectively can identify the best power-sharing configuration $(\alpha)$ by maximizing the system’s efficiency taking into consideration two main parameters: power load profile and the state of charge (SOC) of the supercapacitor. This optimization problem is solved by the implementation of a single horizon finite set predictive control strategy. The simulation results show that the controller successfully tracks the maximum efficiency of the system to compute the best power-sharing configuration ($\alpha$). Additionally, the results underscore the benefits of the implementation of hybrid sources, demonstrating that the overall system efficiency consistently surpasses that of independent operating sources.