An imitation learning-based energy management strategy for electric vehicles considering battery aging
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DOI: 10.1016/j.energy.2023.128537
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- Wu, Yuankai & Tan, Huachun & Peng, Jiankun & Zhang, Hailong & He, Hongwen, 2019. "Deep reinforcement learning of energy management with continuous control strategy and traffic information for a series-parallel plug-in hybrid electric bus," Applied Energy, Elsevier, vol. 247(C), pages 454-466.
- Zou, Yuan & Liu, Teng & Liu, Dexing & Sun, Fengchun, 2016. "Reinforcement learning-based real-time energy management for a hybrid tracked vehicle," Applied Energy, Elsevier, vol. 171(C), pages 372-382.
- Yue Hu & Weimin Li & Hui Xu & Guoqing Xu, 2015. "An Online Learning Control Strategy for Hybrid Electric Vehicle Based on Fuzzy Q-Learning," Energies, MDPI, vol. 8(10), pages 1-20, October.
- Chen, Zheng & Hu, Hengjie & Wu, Yitao & Zhang, Yuanjian & Li, Guang & Liu, Yonggang, 2020. "Stochastic model predictive control for energy management of power-split plug-in hybrid electric vehicles based on reinforcement learning," Energy, Elsevier, vol. 211(C).
- Wu, Jingda & He, Hongwen & Peng, Jiankun & Li, Yuecheng & Li, Zhanjiang, 2018. "Continuous reinforcement learning of energy management with deep Q network for a power split hybrid electric bus," Applied Energy, Elsevier, vol. 222(C), pages 799-811.
- Xiong, Rui & Cao, Jiayi & Yu, Quanqing, 2018. "Reinforcement learning-based real-time power management for hybrid energy storage system in the plug-in hybrid electric vehicle," Applied Energy, Elsevier, vol. 211(C), pages 538-548.
- Xu, Bin & Rathod, Dhruvang & Zhang, Darui & Yebi, Adamu & Zhang, Xueyu & Li, Xiaoya & Filipi, Zoran, 2020. "Parametric study on reinforcement learning optimized energy management strategy for a hybrid electric vehicle," Applied Energy, Elsevier, vol. 259(C).
- Arumugam Manthiram, 2020. "A reflection on lithium-ion battery cathode chemistry," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
- Suri, Girish & Onori, Simona, 2016. "A control-oriented cycle-life model for hybrid electric vehicle lithium-ion batteries," Energy, Elsevier, vol. 96(C), pages 644-653.
- Xu, Bin & Shi, Junzhe & Li, Sixu & Li, Huayi & Wang, Zhe, 2021. "Energy consumption and battery aging minimization using a Q-learning strategy for a battery/ultracapacitor electric vehicle," Energy, Elsevier, vol. 229(C).
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- Juan Carlos Paredes-Rojas & Ramón Costa-Castelló & Rubén Vázquez-Medina & Juan Alejandro Flores-Campos & Christopher Rene Torres-San Miguel, 2025. "Experimental Study on Using Biodiesel in Hybrid Electric Vehicles," Energies, MDPI, vol. 18(7), pages 1-22, March.
- Liu, Weirong & Yao, Pengfei & Wu, Yue & Duan, Lijun & Li, Heng & Peng, Jun, 2025. "Imitation reinforcement learning energy management for electric vehicles with hybrid energy storage system," Applied Energy, Elsevier, vol. 378(PA).
- Wenna Xu & Hao Huang & Chun Wang & Shuai Xia & Xinmei Gao, 2025. "A Comparative Study of Energy Management Strategies for Battery-Ultracapacitor Electric Vehicles Based on Different Deep Reinforcement Learning Methods," Energies, MDPI, vol. 18(5), pages 1-18, March.
- Sun, Zhicheng & Hu, Jianjun & Yao, Zutang & Xue, Shouzhi, 2024. "Optimization of electromagnetic vibration for integrated electric drive systems based on electric vehicle driving cycle considering energy consumption," Energy, Elsevier, vol. 313(C).
- Gu, Jianqiang & Wu, Zhan & Song, Yubing & Nicolescu, Ana-Cristina, 2024. "A win-win relationship? New evidence on artificial intelligence and new energy vehicles," Energy Economics, Elsevier, vol. 134(C).
- Guan, Kaifu & Huang, Zhiwu & Gao, Yang & Wu, Yue & Li, Fei & Li, Heng, 2025. "Towards adaptive deep reinforcement learning energy management for electric vehicles: An online updating approach," Energy, Elsevier, vol. 325(C).
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