Optimal Rule-Interposing Reinforcement Learning-Based Energy Management of Series—Parallel-Connected Hybrid Electric Vehicles
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Shi, Dehua & Liu, Sheng & Cai, Yingfeng & Wang, Shaohua & Li, Haoran & Chen, Long, 2021. "Pontryagin’s minimum principle based fuzzy adaptive energy management for hybrid electric vehicle using real-time traffic information," Applied Energy, Elsevier, vol. 286(C).
- Han, Lijin & Yang, Ke & Ma, Tian & Yang, Ningkang & Liu, Hui & Guo, Lingxiong, 2022. "Battery life constrained real-time energy management strategy for hybrid electric vehicles based on reinforcement learning," Energy, Elsevier, vol. 259(C).
- Yang, Ningkang & Ruan, Shumin & Han, Lijin & Liu, Hui & Guo, Lingxiong & Xiang, Changle, 2023. "Reinforcement learning-based real-time intelligent energy management for hybrid electric vehicles in a model predictive control framework," Energy, Elsevier, vol. 270(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Zhang, Yagang & Wang, Hui & Wang, Jingchao & Cheng, Xiaodan & Wang, Tong & Zhao, Zheng, 2024. "Ensemble optimization approach based on hybrid mode decomposition and intelligent technology for wind power prediction system," Energy, Elsevier, vol. 292(C).
- Gao, Kai & Luo, Pan & Xie, Jin & Chen, Bin & Wu, Yue & Du, Ronghua, 2023. "Energy management of plug-in hybrid electric vehicles based on speed prediction fused driving intention and LIDAR," Energy, Elsevier, vol. 284(C).
- Yang, Ningkang & Han, Lijin & Bo, Lin & Liu, Baoshuai & Chen, Xiuqi & Liu, Hui & Xiang, Changle, 2023. "Real-time adaptive energy management for off-road hybrid electric vehicles based on decision-time planning," Energy, Elsevier, vol. 282(C).
- da Silva, Samuel Filgueira & Eckert, Jony Javorski & Corrêa, Fernanda Cristina & Silva, Fabrício Leonardo & Silva, Ludmila C.A. & Dedini, Franco Giuseppe, 2022. "Dual HESS electric vehicle powertrain design and fuzzy control based on multi-objective optimization to increase driving range and battery life cycle," Applied Energy, Elsevier, vol. 324(C).
- Nie, Zifei & Farzaneh, Hooman, 2022. "Real-time dynamic predictive cruise control for enhancing eco-driving of electric vehicles, considering traffic constraints and signal phase and timing (SPaT) information, using artificial-neural-netw," Energy, Elsevier, vol. 241(C).
- Kerbel, Lindsey & Ayalew, Beshah & Ivanco, Andrej, 2024. "Shared learning of powertrain control policies for vehicle fleets," Applied Energy, Elsevier, vol. 365(C).
- Huang, Ruchen & He, Hongwen & Zhao, Xuyang & Wang, Yunlong & Li, Menglin, 2022. "Battery health-aware and naturalistic data-driven energy management for hybrid electric bus based on TD3 deep reinforcement learning algorithm," Applied Energy, Elsevier, vol. 321(C).
- 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).
- Wang, Shaohua & Zhang, Kaimei & Shi, Dehua & Li, Meng & Yin, Chunfang, 2024. "Research on economical shifting strategy for multi-gear and multi-mode parallel plug-in HEV based on DIRECT algorithm," Energy, Elsevier, vol. 286(C).
- Fabrizio Donatantonio & Alessandro Ferrara & Pierpaolo Polverino & Ivan Arsie & Cesare Pianese, 2022. "Novel Approaches for Energy Management Strategies of Hybrid Electric Vehicles and Comparison with Conventional Solutions," Energies, MDPI, vol. 15(6), pages 1-22, March.
- 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).
- Zhang, Hao & Lei, Nuo & Liu, Shang & Fan, Qinhao & Wang, Zhi, 2023. "Data-driven predictive energy consumption minimization strategy for connected plug-in hybrid electric vehicles," Energy, Elsevier, vol. 283(C).
- Elsisi, Mahmoud & Amer, Mohammed & Dababat, Alya’ & Su, Chun-Lien, 2023. "A comprehensive review of machine learning and IoT solutions for demand side energy management, conservation, and resilient operation," Energy, Elsevier, vol. 281(C).
- Gao, Renjing & Zhou, Guangli & Wang, Qi, 2024. "Real-time three-level energy management strategy for series hybrid wheel loaders based on WG-MPC," Energy, Elsevier, vol. 295(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).
- Kunyu Wang & Rong Yang & Yongjian Zhou & Wei Huang & Song Zhang, 2022. "Design and Improvement of SD3-Based Energy Management Strategy for a Hybrid Electric Urban Bus," Energies, MDPI, vol. 15(16), pages 1-21, August.
- Jinquan, Guo & Hongwen, He & Jianwei, Li & Qingwu, Liu, 2021. "Real-time energy management of fuel cell hybrid electric buses: Fuel cell engines friendly intersection speed planning," Energy, Elsevier, vol. 226(C).
- Yang, Chao & Du, Xuelong & Wang, Weida & Yuan, Lijuan & Yang, Liuquan, 2024. "Variable optimization domain-based cooperative energy management strategy for connected plug-in hybrid electric vehicles," Energy, Elsevier, vol. 290(C).
- Piras, M. & De Bellis, V. & Malfi, E. & Novella, R. & Lopez-Juarez, M., 2024. "Hydrogen consumption and durability assessment of fuel cell vehicles in realistic driving," Applied Energy, Elsevier, vol. 358(C).
- Penghui Qiang & Peng Wu & Tao Pan & Huaiquan Zang, 2022. "Real-Time Energy Management Strategy Based on Driving Conditions Using a Feature Fusion Extreme Learning Machine," Energies, MDPI, vol. 15(12), pages 1-22, June.
More about this item
Keywords
series–parallel HEVs; energy management; reinforcement learning; connected environment;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:16:p:6848-:d:1453345. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.