Energy management strategies based on soft actor critic reinforcement learning with a proper reward function design based on battery state of charge constraints-Reference-Cited by-同舟云学术

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Energy management strategies based on soft actor critic reinforcement learning with a proper reward function design based on battery state of charge constraints

Published:2024-06 Issue: Volume:90 Page:111797
ISSN:2352-152X
Container-title:Journal of Energy Storage
language:en
Short-container-title:Journal of Energy Storage

Author:

Bäumler Antoine^ORCID,Benterki Abdelmoudjib,Meng Jianwen,Azib Toufik^ORCID,Boukhnifer Moussa^ORCID

Publisher

Elsevier BV

Reference52 articles.

1. A review of key issues for control and management in battery and ultra-capacitor hybrid energy storage systems;Wang;eTransportation,2020

2. An investigation of fuel economy potential of hybrid vehicles under real-world driving conditions in bangkok;Pitanuwat;Energy Procedia,2015

3. Production of greenhouse gas free hydrogen by thermocatalytic decomposition of methane – A review;Ashik;Renew. Sustain. Energy Rev.,2015

4. Power management optimization in plug-in hybrid electric vehicles subject to uncertain driving cycles;Zhang;eTransportation,2020

5. Review on health-conscious energy management strategies for fuel cell hybrid electric vehicles: Degradation models and strategies;Yue;Int. J. Hydrogen Energy,2019

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A cloud-fog computing framework for real-time energy management in multi-microgrid system utilizing deep reinforcement learning;Journal of Energy Storage;2024-09

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