Temperature Control of Proton Exchange Membrane Fuel Cell Based on Machine Learning

Temperature Control of Proton Exchange Membrane Fuel Cell Based on Machine Learning

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) algorith...

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Bibliographic Details
Main Authors: Jiawen Li, Yaping Li, Tao Yu
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-09-01
Series:Frontiers in Energy Research
Subjects:
proton exchange membrane fuel cell
twin delayed deep deterministic policy gradient algorithm
stack temperature
PID controller
robustness
Online Access:https://www.frontiersin.org/articles/10.3389/fenrg.2021.763099/full

Internet

https://www.frontiersin.org/articles/10.3389/fenrg.2021.763099/full

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