Real-time energy management of fuel cell hybrid electric buses: Fuel cell engines friendly intersection speed planning
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DOI: 10.1016/j.energy.2021.120440
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Cited by:
- Tang, Xiaolin & Zhou, Haitao & Wang, Feng & Wang, Weida & Lin, Xianke, 2022. "Longevity-conscious energy management strategy of fuel cell hybrid electric Vehicle Based on deep reinforcement learning," Energy, Elsevier, vol. 238(PA).
- Jinquan, Guo & Hongwen, He & Jianwei, Li & Qingwu, Liu, 2022. "Driving information process system-based real-time energy management for the fuel cell bus to minimize fuel cell engine aging and energy consumption," Energy, Elsevier, vol. 248(C).
- Chen, Zheng & Wu, Simin & Shen, Shiquan & Liu, Yonggang & Guo, Fengxiang & Zhang, Yuanjian, 2023. "Co-optimization of velocity planning and energy management for autonomous plug-in hybrid electric vehicles in urban driving scenarios," Energy, Elsevier, vol. 263(PF).
- Hou, Shengyan & Yin, Hai & Xu, Fuguo & Benjamín, Pla & Gao, Jinwu & Chen, Hong, 2023. "Multihorizon predictive energy optimization and lifetime management for connected fuel cell electric vehicles," Energy, Elsevier, vol. 266(C).
- Zhou, Jianhao & Liu, Jun & Xue, Yuan & Liao, Yuhui, 2022. "Total travel costs minimization strategy of a dual-stack fuel cell logistics truck enhanced with artificial potential field and deep reinforcement learning," Energy, Elsevier, vol. 239(PA).
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Keywords
FCHEB; SUMO; Intersection speed planning; DP; MPC; Energy management;All these keywords.
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