Hierarchical Energy Management and Energy Saving Potential Analysis for Fuel Cell Hybrid Electric Tractors
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- Bao, Shuyue & Sun, Ping & Zhu, Jianxin & Ji, Qian & Liu, Junheng, 2022. "Improved multi-dimensional dynamic programming energy management strategy for a vehicle power-split hybrid powertrain," Energy, Elsevier, vol. 256(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.
- Das, Himadry Shekhar & Tan, Chee Wei & Yatim, A.H.M., 2017. "Fuel cell hybrid electric vehicles: A review on power conditioning units and topologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 268-291.
- Simone Pascuzzi & Katarzyna Łyp-Wrońska & Katarzyna Gdowska & Francesco Paciolla, 2024. "Sustainability Evaluation of Hybrid Agriculture-Tractor Powertrains," Sustainability, MDPI, vol. 16(3), pages 1-17, January.
- Ren, Xiaoxia & Ye, Jinze & Xie, Liping & Lin, Xinyou, 2024. "Battery longevity-conscious energy management predictive control strategy optimized by using deep reinforcement learning algorithm for a fuel cell hybrid electric vehicle," Energy, Elsevier, vol. 286(C).
- Meng Yang & Xiaoxu Sun & Xiaoting Deng & Zhixiong Lu & Tao Wang, 2023. "Extrapolation of Tractor Traction Resistance Load Spectrum and Compilation of Loading Spectrum Based on Optimal Threshold Selection Using a Genetic Algorithm," Agriculture, MDPI, vol. 13(6), pages 1-20, May.
- Francesco Mocera & Aurelio Somà & Salvatore Martelli & Valerio Martini, 2023. "Trends and Future Perspective of Electrification in Agricultural Tractor-Implement Applications," Energies, MDPI, vol. 16(18), pages 1-36, September.
- Wu, Jinglai & Zhang, Yunqing & Ruan, Jiageng & Liang, Zhaowen & Liu, Kai, 2023. "Rule and optimization combined real-time energy management strategy for minimizing cost of fuel cell hybrid electric vehicles," Energy, Elsevier, vol. 285(C).
- Yifan Zhao & Liyou Xu & Chenhui Zhao & Haigang Xu & Xianghai Yan, 2024. "Research on Energy Management Strategy for Hybrid Tractors Based on DP-MPC," Energies, MDPI, vol. 17(16), pages 1-22, August.
- Li, Xian-zhe & Zhang, Ming-zhu & Yan, Xiang-hai & Liu, Meng-nan & Xu, Li-you, 2023. "Power allocation strategy for fuel cell distributed drive electric tractor based on adaptive multi-resolution analysis theory," Energy, Elsevier, vol. 284(C).
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- Hanwen Wu & Long Quan & Yunxiao Hao & Zhijie Pan & Songtao Xie, 2025. "Research on the Characteristics of a Range-Extended Hydraulic–Electric Hybrid Drive System for Tractor Traveling Systems," Energies, MDPI, vol. 18(8), pages 1-19, April.
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Keywords
fuel cell; hybrid electric tractors; energy management strategy; hierarchical instantaneous optimization; dynamic programming; optimal energy consumption;All these keywords.
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