A review of reinforcement learning based energy management systems for electrified powertrains: Progress, challenge, and potential solution
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DOI: 10.1016/j.rser.2021.111833
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- Xiaodong Liu & Hongqiang Guo & Xingqun Cheng & Juan Du & Jian Ma, 2022. "A Robust Design of the Model-Free-Adaptive-Control-Based Energy Management for Plug-In Hybrid Electric Vehicle," Energies, MDPI, vol. 15(20), pages 1-24, October.
- Huang, Ying & Wang, Shilong & Li, Ke & Fan, Zhuwei & Xie, Haiming & Jiang, Fachao, 2023. "Multi-parameter adaptive online energy management strategy for concrete truck mixers with a novel hybrid powertrain considering vehicle mass," Energy, Elsevier, vol. 277(C).
- Xue, Lin & Wang, Jianxue & Zhang, Yao & Yong, Weizhen & Qi, Jie & Li, Haotian, 2023. "Model-data-event based community integrated energy system low-carbon economic scheduling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
- Hua, Min & Zhang, Cetengfei & Zhang, Fanggang & Li, Zhi & Yu, Xiaoli & Xu, Hongming & Zhou, Quan, 2023. "Energy management of multi-mode plug-in hybrid electric vehicle using multi-agent deep reinforcement learning," Applied Energy, Elsevier, vol. 348(C).
- Hao, Zhaojun & Di Maio, Francesco & Zio, Enrico, 2023. "A sequential decision problem formulation and deep reinforcement learning solution of the optimization of O&M of cyber-physical energy systems (CPESs) for reliable and safe power production and supply," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
- Matteo Acquarone & Claudio Maino & Daniela Misul & Ezio Spessa & Antonio Mastropietro & Luca Sorrentino & Enrico Busto, 2023. "Influence of the Reward Function on the Selection of Reinforcement Learning Agents for Hybrid Electric Vehicles Real-Time Control," Energies, MDPI, vol. 16(6), pages 1-22, March.
- Huang, Ruchen & He, Hongwen & Gao, Miaojue, 2023. "Training-efficient and cost-optimal energy management for fuel cell hybrid electric bus based on a novel distributed deep reinforcement learning framework," Applied Energy, Elsevier, vol. 346(C).
- Dorian Skrobek & Jaroslaw Krzywanski & Marcin Sosnowski & Ghulam Moeen Uddin & Waqar Muhammad Ashraf & Karolina Grabowska & Anna Zylka & Anna Kulakowska & Wojciech Nowak, 2023. "Artificial Intelligence for Energy Processes and Systems: Applications and Perspectives," Energies, MDPI, vol. 16(8), pages 1-12, April.
- Alabi, Tobi Michael & Lawrence, Nathan P. & Lu, Lin & Yang, Zaiyue & Bhushan Gopaluni, R., 2023. "Automated deep reinforcement learning for real-time scheduling strategy of multi-energy system integrated with post-carbon and direct-air carbon captured system," Applied Energy, Elsevier, vol. 333(C).
- Hou, Zhuoran & Guo, Jianhua & Chu, Liang & Hu, Jincheng & Chen, Zheng & Zhang, Yuanjian, 2023. "Exploration the route of information integration for vehicle design: A knowledge-enhanced energy management strategy," Energy, Elsevier, vol. 282(C).
- Binbin Sun & Tianqi Gu & Mengxue Xie & Pengwei Wang & Song Gao & Xi Zhang, 2022. "Strategy Design and Performance Analysis of an Electromechanical Flywheel Hybrid Scheme for Electric Vehicles," Sustainability, MDPI, vol. 14(17), pages 1-17, September.
- Dong, Peng & Zhao, Junwei & Liu, Xuewu & Wu, Jian & Xu, Xiangyang & Liu, Yanfang & Wang, Shuhan & Guo, Wei, 2022. "Practical application of energy management strategy for hybrid electric vehicles based on intelligent and connected technologies: Development stages, challenges, and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
- Sorin Liviu Jurj & Tino Werner & Dominik Grundt & Willem Hagemann & Eike Möhlmann, 2022. "Towards Safe and Sustainable Autonomous Vehicles Using Environmentally-Friendly Criticality Metrics," Sustainability, MDPI, vol. 14(12), pages 1-52, June.
- Fang, Xiaolun & Wang, Yubin & Dong, Wei & Yang, Qiang & Sun, Siyang, 2023. "Optimal energy management of multiple electricity-hydrogen integrated charging stations," Energy, Elsevier, vol. 262(PB).
- Hu, Dong & Xie, Hui & Song, Kang & Zhang, Yuanyuan & Yan, Long, 2023. "An apprenticeship-reinforcement learning scheme based on expert demonstrations for energy management strategy of hybrid electric vehicles," Applied Energy, Elsevier, vol. 342(C).
- Daniel Egan & Qilun Zhu & Robert Prucka, 2023. "A Review of Reinforcement Learning-Based Powertrain Controllers: Effects of Agent Selection for Mixed-Continuity Control and Reward Formulation," Energies, MDPI, vol. 16(8), pages 1-31, April.
- Tang, Wenbin & Wang, Yaqian & Jiao, Xiaohong & Ren, Lina, 2023. "Hierarchical energy management strategy based on adaptive dynamic programming for hybrid electric vehicles in car-following scenarios," Energy, Elsevier, vol. 265(C).
- Hongtu Yang & Yan Sun & Changgao Xia & Hongdang Zhang, 2022. "Research on Energy Management Strategy of Fuel Cell Electric Tractor Based on Multi-Algorithm Fusion and Optimization," Energies, MDPI, vol. 15(17), pages 1-15, September.
- Cui, Wei & Cui, Naxin & Li, Tao & Cui, Zhongrui & Du, Yi & Zhang, Chenghui, 2022. "An efficient multi-objective hierarchical energy management strategy for plug-in hybrid electric vehicle in connected scenario," Energy, Elsevier, vol. 257(C).
- Fuwu Yan & Jinhai Wang & Changqing Du & Min Hua, 2022. "Multi-Objective Energy Management Strategy for Hybrid Electric Vehicles Based on TD3 with Non-Parametric Reward Function," Energies, MDPI, vol. 16(1), pages 1-17, December.
- Mudhafar Al-Saadi & Maher Al-Greer & Michael Short, 2023. "Reinforcement Learning-Based Intelligent Control Strategies for Optimal Power Management in Advanced Power Distribution Systems: A Survey," Energies, MDPI, vol. 16(4), pages 1-38, February.
- Ifaei, Pouya & Nazari-Heris, Morteza & Tayerani Charmchi, Amir Saman & Asadi, Somayeh & Yoo, ChangKyoo, 2023. "Sustainable energies and machine learning: An organized review of recent applications and challenges," Energy, Elsevier, vol. 266(C).
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Keywords
Electrified powertrain; Reinforcement learning; Energy management strategies; Deep reinforcement learning; Connected & autonomous vehicles;All these keywords.
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