文章基本信息

标题：Temperature Control of Proton Exchange Membrane Fuel Cell Based on Machine Learning
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作者：Jiawen Li ; Yaping Li ; Tao Yu 等
期刊名称：Frontiers in Energy Research
电子版ISSN：2296-598X
出版年度：2021
卷号：9
DOI：10.3389/fenrg.2021.763099
语种：English
出版社：Frontiers Media S.A.
摘要：In order to improve the proton exchange membrane fuel cell (PEMFC) working efficiency, we propose a deep-reinforcement-learning based PID controller for realizing optimal PEMFC stack temperature. For this purpose, we propose the Improved Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, a tuner of the PID controller, which can adjust the coefficients of the controller in real time. This algorithm accelerates the learning speed of an agent by continuously changing the soft update parameters during the training process, thereby improving the training efficiency of the agent, and further reducing training costs and obtaining a robust strategy. The effectiveness of the control algorithm is verified through a simulation in which it is compared against a group of existing algorithms.