AUTHOR=Li Jiawen , Li Yaping , Yu Tao TITLE=Distributed Imitation-Orientated Deep Reinforcement Learning Method for Optimal PEMFC Output Voltage Control JOURNAL=Frontiers in Energy Research VOLUME=9 YEAR=2021 URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2021.741101 DOI=10.3389/fenrg.2021.741101 ISSN=2296-598X ABSTRACT=
In order to improve the stability of proton exchange membrane fuel cell (PEMFC) output voltage, a data-driven output voltage control strategy based on regulation of the duty cycle of the DC-DC converter is proposed in this paper. In detail, an imitation-oriented twin delay deep deterministic (IO-TD3) policy gradient algorithm which offers a more robust voltage control strategy is demonstrated. This proposed output voltage control method is a distributed deep reinforcement learning training framework, the design of which is guided by the pedagogic concept of imitation learning. The effectiveness of the proposed control strategy is experimentally demonstrated.