Energy Management Strategies for Hybrid Loaders: Classification, Comparison and Prospect
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- Li, Tianyu & Liu, Huiying & Wang, Hui & Yao, Yongming, 2020. "Hierarchical predictive control-based economic energy management for fuel cell hybrid construction vehicles," Energy, Elsevier, vol. 198(C).
- Li, Tianyu & Liu, Huiying & Ding, Daolin, 2018. "Predictive energy management of fuel cell supercapacitor hybrid construction equipment," Energy, Elsevier, vol. 149(C), pages 718-729.
- 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.
- Zhang, Haoxiang & Wang, Feng & Xu, Bing & Fiebig, Wieslaw, 2022. "Extending battery lifetime for electric wheel loaders with electric-hydraulic hybrid powertrain," Energy, Elsevier, vol. 261(PB).
- Wei Zhang & Jixin Wang & Shaofeng Du & Hongfeng Ma & Wenjun Zhao & Haojie Li, 2019. "Energy Management Strategies for Hybrid Construction Machinery: Evolution, Classification, Comparison and Future Trends," Energies, MDPI, vol. 12(10), pages 1-26, May.
- Xiaoliang Lai & Cheng Guan, 2013. "A Parameter Matching Method of the Parallel Hydraulic Hybrid Excavator Optimized with Genetic Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-6, September.
- 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.
- Zhang, Wei & Wang, Jixin & Liu, Yong & Gao, Guangzong & Liang, Siwen & Ma, Hongfeng, 2020. "Reinforcement learning-based intelligent energy management architecture for hybrid construction machinery," Applied Energy, Elsevier, vol. 275(C).
- Jixiang Yang & Yongming Bian & Meng Yang & Jie Shao & Ao Liang, 2021. "Parameter Matching of Energy Regeneration System for Parallel Hydraulic Hybrid Loader," Energies, MDPI, vol. 14(16), pages 1-26, August.
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- Dapai Shi & Junjie Guo & Kangjie Liu & Qingling Cai & Zhenghong Wang & Xudong Qu, 2023. "Research on an Improved Rule-Based Energy Management Strategy Enlightened by the DP Optimization Results," Sustainability, MDPI, vol. 15(13), pages 1-13, July.
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Keywords
energy management strategy; hybrid loaders; rule-based strategy; optimization-based strategy;All these keywords.
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