Approximate Globally Optimal Energy Management Strategy for Fuel Cell Hybrid Mining Trucks Based on Rule-Interposing Balance Cost Minimization
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Chen, Huicui & Pei, Pucheng & Song, Mancun, 2015. "Lifetime prediction and the economic lifetime of Proton Exchange Membrane fuel cells," Applied Energy, Elsevier, vol. 142(C), pages 154-163.
- Yan, Qing-dong & Chen, Xiu-qi & Jian, Hong-chao & Wei, Wei & Wang, Wei-da & Wang, Heng, 2022. "Design of a deep inference framework for required power forecasting and predictive control on a hybrid electric mining truck," Energy, Elsevier, vol. 238(PC).
- Peng, Jiankun & He, Hongwen & Xiong, Rui, 2017. "Rule based energy management strategy for a series–parallel plug-in hybrid electric bus optimized by dynamic programming," Applied Energy, Elsevier, vol. 185(P2), pages 1633-1643.
- Feng, Yanbiao & Dong, Zuomin, 2020. "Integrated design and control optimization of fuel cell hybrid mining truck with minimized lifecycle cost," Applied Energy, Elsevier, vol. 270(C).
- Changqing Du & Shiyang Huang & Yuyao Jiang & Dongmei Wu & Yang Li, 2022. "Optimization of Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles Based on Dynamic Programming," Energies, MDPI, vol. 15(12), pages 1-25, June.
- Lin, Xinyou & Huang, Hao & Xu, Xinhao & Xie, Liping, 2024. "Dynamic programming solutions extracted SOC-trajectory online learning generation algorithm based approximate global optimization control strategy for a fuel cell hybrid electric vehicle," Energy, Elsevier, vol. 295(C).
- Song, Ziyou & Li, Jianqiu & Han, Xuebing & Xu, Liangfei & Lu, Languang & Ouyang, Minggao & Hofmann, Heath, 2014. "Multi-objective optimization of a semi-active battery/supercapacitor energy storage system for electric vehicles," Applied Energy, Elsevier, vol. 135(C), pages 212-224.
- Song, Ziyou & Hou, Jun & Xu, Shaobing & Ouyang, Minggao & Li, Jianqiu, 2017. "The influence of driving cycle characteristics on the integrated optimization of hybrid energy storage system for electric city buses," Energy, Elsevier, vol. 135(C), pages 91-100.
- 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).
- Zhou, Yang & Ravey, Alexandre & Péra, Marie-Cecile, 2020. "Multi-mode predictive energy management for fuel cell hybrid electric vehicles using Markov driving pattern recognizer," Applied Energy, Elsevier, vol. 258(C).
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Mesa, Jaime A. & Hincapie-Florez, Diego & Bobadilla-Vasquez, Melkis & Corredor, Lesme & Pupo-Roncallo, Oscar & Gonzalez-Quiroga, Arturo, 2025. "Assessing technological trends in mining fleet energy management toward sustainable mineral extraction," Resources Policy, Elsevier, vol. 109(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.- Zheng, Weiguang & Ma, Mengcheng & Xu, Enyong & Huang, Qibai, 2024. "An energy management strategy for fuel-cell hybrid electric vehicles based on model predictive control with a variable time domain," Energy, Elsevier, vol. 312(C).
- Liu, Hanwu & Lei, Yulong & Fu, Yao & Li, Xingzhong, 2022. "A novel hybrid-point-line energy management strategy based on multi-objective optimization for range-extended electric vehicle," Energy, Elsevier, vol. 247(C).
- Zhou, Yang & Guo, Yansiqi & Yang, Fan & Chen, Bo & Ma, Ruiqing & Ma, Rui & Jiang, Wentao & Bai, Hao, 2025. "Speed-prediction-based hierarchical energy management and operating cost analysis for fuel cell hybrid logistic vehicles," Applied Energy, Elsevier, vol. 390(C).
- Huang, Yin & Kang, Zehao & Mao, Xuping & Hu, Haoqin & Tan, Jiaqi & Xuan, Dongji, 2023. "Deep reinforcement learning based energymanagement strategy considering running costs and energy source aging for fuel cell hybrid electric vehicle," Energy, Elsevier, vol. 283(C).
- Liu, Hanwu & Lei, Yulong & Sun, Wencai & Chang, Cheng & Jiang, Wei & Liu, Yuwei & Hu, Jianlong, 2024. "Research on approximate optimal energy management and multi-objective optimization of connected automated range-extended electric vehicle," Energy, Elsevier, vol. 306(C).
- Sanghyun Yun & Jinwon Yun & Jaeyoung Han, 2023. "Development of a 470-Horsepower Fuel Cell–Battery Hybrid Xcient Dynamic Model Using Simscape TM," Energies, MDPI, vol. 16(24), pages 1-22, December.
- Jiajun Liu & Tianxu Jin & Li Liu & Yajue Chen & Kun Yuan, 2017. "Multi-Objective Optimization of a Hybrid ESS Based on Optimal Energy Management Strategy for LHDs," Sustainability, MDPI, vol. 9(10), pages 1-18, October.
- 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).
- 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).
- Zhu, Tao & Wills, Richard G.A. & Lot, Roberto & Kong, Xiaodan & Yan, Xingda, 2021. "Optimal sizing and sensitivity analysis of a battery-supercapacitor energy storage system for electric vehicles," Energy, Elsevier, vol. 221(C).
- Lü, Xueqin & Zhu, Changan & Li, Yan & Zhang, Yu & Zhai, Xinrui & Qian, Shenchen, 2026. "Multi objective optimization of energy management for fuel cell electric vehicles under different driving conditions based on based on improved double Q-network algorithm," Energy, Elsevier, vol. 344(C).
- Dong, Peng & Zhao, Junwei & Liu, Xuewu & Wu, Jian & Xu, Xiangyang & Liu, Yanfang & Wang, Shuhan & Guo, Wei, 2022. "Practical application of energy management strategy for hybrid electric vehicles based on intelligent and connected technologies: Development stages, challenges, and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
- Huang, Hao & Lin, Xinyou & Huang, Qiang, 2026. "Enhancing adaptive health-conscious energy management control strategy with self-learning power correction for fuel cell hybrid electric vehicles," Applied Energy, Elsevier, vol. 402(PB).
- Huang, Xuejin & Zhang, Jingyi & Ou, Kai & Huang, Yin & Kang, Zehao & Mao, Xuping & Zhou, Yujie & Xuan, Dongji, 2024. "Deep reinforcement learning-based health-conscious energy management for fuel cell hybrid electric vehicles in model predictive control framework," Energy, Elsevier, vol. 304(C).
- Ruan, Jiageng & Song, Qiang & Yang, Weiwei, 2019. "The application of hybrid energy storage system with electrified continuously variable transmission in battery electric vehicle," Energy, Elsevier, vol. 183(C), pages 315-330.
- Feng, Yanbiao & Dong, Zuomin, 2020. "Integrated design and control optimization of fuel cell hybrid mining truck with minimized lifecycle cost," Applied Energy, Elsevier, vol. 270(C).
- Wu, Huiduo & Min, Haitao & Zhao, Honghui & Sun, Weiyi, 2025. "A novel EMS for FCV combined with condition-adaptive search ranges of decision variables based on the spatial and temporal traffic characteristics," Energy, Elsevier, vol. 335(C).
- Zhang, Feitie & Yang, Fuyuan & Xue, Dianlun & Cai, Yuanchun, 2019. "Optimization of compound power split configurations in PHEV bus for fuel consumption and battery degradation decreasing," Energy, Elsevier, vol. 169(C), pages 937-957.
- Liu, Huanlong & Chen, Guanpeng & Li, Dafa & Wang, Jiawei & Zhou, Jianyi, 2021. "Energy active adjustment and bidirectional transfer management strategy of the electro-hydrostatic hydraulic hybrid powertrain for battery bus," Energy, Elsevier, vol. 230(C).
- Zhang, Yahui & Wang, Zimeng & Tian, Yang & Wang, Zhong & Kang, Mingxin & Xie, Fangxi & Wen, Guilin, 2024. "Pre-optimization-assisted deep reinforcement learning-based energy management strategy for a series–parallel hybrid electric truck," Energy, Elsevier, vol. 302(C).
Corrections
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:17:y:2025:i:4:p:1412-:d:1587054. 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 The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address (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.
Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i4p1412-d1587054.html