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Co-optimization of speed planning and energy management for intelligent fuel cell hybrid vehicle considering complex traffic conditions

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  • Nie, Zhigen
  • Jia, Yuan
  • Wang, Wanqiong
  • Chen, Zheng
  • Outbib, Rachid

Abstract

Fuel cell hybrid vehicles (FCHVs) offer great opportunities to reduce vehicle's operation cost and mitigate environmental impact. However, high-quality real-time energy management of FCHV is a difficult task due to different influences from complex traffic environments, such as dynamic changes of preceding and rear vehicle state, road slope and road coefficient. To address this problem, a cooperative control strategy is designed to achieve simultaneous speed planning and energy management promotion in this study. The upper control layer leverages a gradient-based model prediction control (GRAMPC) based on the fast projection gradient method to plan the speed sequence according to the information of future driving conditions as well as the real-time state of the preceding and rear vehicles. The bottom layer applies model prediction control (MPC) to achieve real-time preferable energy allocation, and a multi-objective control function is considered for the total cost minimization of energy management in terms of hydrogen consumption and battery life extension. The simulation results reveal that under the constraints of a dynamic environment, the proposed control strategy in planning state can reduce the traction power, hydrogen consumption, global cost, and battery degradation by 2.65%, 1.9%, 2.39%, and 8.14%, respectively.

Suggested Citation

  • Nie, Zhigen & Jia, Yuan & Wang, Wanqiong & Chen, Zheng & Outbib, Rachid, 2022. "Co-optimization of speed planning and energy management for intelligent fuel cell hybrid vehicle considering complex traffic conditions," Energy, Elsevier, vol. 247(C).
    • Handle: RePEc:eee:energy:v:247:y:2022:i:c:s0360544222003796
    DOI: 10.1016/j.energy.2022.123476
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    as
    1. 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).
    2. Shaobo Xie & Huiling Li & Zongke Xin & Tong Liu & Lang Wei, 2017. "A Pontryagin Minimum Principle-Based Adaptive Equivalent Consumption Minimum Strategy for a Plug-in Hybrid Electric Bus on a Fixed Route," Energies, MDPI, vol. 10(9), pages 1-22, September.
    3. Ettihir, K. & Boulon, L. & Agbossou, K., 2016. "Optimization-based energy management strategy for a fuel cell/battery hybrid power system," Applied Energy, Elsevier, vol. 163(C), pages 142-153.
    4. Hou, Jun & Song, Ziyou, 2020. "A hierarchical energy management strategy for hybrid energy storage via vehicle-to-cloud connectivity," Applied Energy, Elsevier, vol. 257(C).
    5. Mahmoodi-k, Mehdi & Montazeri, Morteza & Madanipour, Vahid, 2021. "Simultaneous multi-objective optimization of a PHEV power management system and component sizing in real world traffic condition," Energy, Elsevier, vol. 233(C).
    6. 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.
    7. 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.
    8. 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.
    9. Kim, Youngki & Figueroa-Santos, Miriam & Prakash, Niket & Baek, Stanley & Siegel, Jason B. & Rizzo, Denise M., 2020. "Co-optimization of speed trajectory and power management for a fuel-cell/battery electric vehicle," Applied Energy, Elsevier, vol. 260(C).
    10. Tribioli, Laura & Cozzolino, Raffaello & Chiappini, Daniele & Iora, Paolo, 2016. "Energy management of a plug-in fuel cell/battery hybrid vehicle with on-board fuel processing," Applied Energy, Elsevier, vol. 184(C), pages 140-154.
    11. Zhang, LiPeng & Liu, Wei & Qi, BingNan, 2020. "Energy optimization of multi-mode coupling drive plug-in hybrid electric vehicles based on speed prediction," Energy, Elsevier, vol. 206(C).
    12. Sun, Chao & Sun, Fengchun & He, Hongwen, 2017. "Investigating adaptive-ECMS with velocity forecast ability for hybrid electric vehicles," Applied Energy, Elsevier, vol. 185(P2), pages 1644-1653.
    13. Hu, Xiaosong & Zhang, Xiaoqian & Tang, Xiaolin & Lin, Xianke, 2020. "Model predictive control of hybrid electric vehicles for fuel economy, emission reductions, and inter-vehicle safety in car-following scenarios," Energy, Elsevier, vol. 196(C).
    14. Shuxian Li & Minghui Hu & Changchao Gong & Sen Zhan & Datong Qin, 2018. "Energy Management Strategy for Hybrid Electric Vehicle Based on Driving Condition Identification Using KGA-Means," Energies, MDPI, vol. 11(6), pages 1-16, June.
    15. Zhang, Bo & Zhang, Jiangyan & Xu, Fuguo & Shen, Tielong, 2020. "Optimal control of power-split hybrid electric powertrains with minimization of energy consumption," Applied Energy, Elsevier, vol. 266(C).
    16. Wang, Siyang & Lin, Xianke, 2020. "Eco-driving control of connected and automated hybrid vehicles in mixed driving scenarios," Applied Energy, Elsevier, vol. 271(C).
    17. Gao, Zhiming & LaClair, Tim & Ou, Shiqi & Huff, Shean & Wu, Guoyuan & Hao, Peng & Boriboonsomsin, Kanok & Barth, Matthew, 2019. "Evaluation of electric vehicle component performance over eco-driving cycles," Energy, Elsevier, vol. 172(C), pages 823-839.
    18. Zeng, Tao & Zhang, Caizhi & Zhang, Yanyi & Deng, Chenghao & Hao, Dong & Zhu, Zhongwen & Ran, Hongxu & Cao, Dongpu, 2021. "Optimization-oriented adaptive equivalent consumption minimization strategy based on short-term demand power prediction for fuel cell hybrid vehicle," Energy, Elsevier, vol. 227(C).
    19. Herr, Nathalie & Nicod, Jean-Marc & Varnier, Christophe & Jardin, Louise & Sorrentino, Antonella & Hissel, Daniel & Péra, Marie-Cécile, 2017. "Decision process to manage useful life of multi-stacks fuel cell systems under service constraint," Renewable Energy, Elsevier, vol. 105(C), pages 590-600.
    20. Hongwen, He & Jinquan, Guo & Jiankun, Peng & Huachun, Tan & Chao, Sun, 2018. "Real-time global driving cycle construction and the application to economy driving pro system in plug-in hybrid electric vehicles," Energy, Elsevier, vol. 152(C), pages 95-107.
    21. Shen, Peihong & Zhao, Zhiguo & Zhan, Xiaowen & Li, Jingwei & Guo, Qiuyi, 2018. "Optimal energy management strategy for a plug-in hybrid electric commercial vehicle based on velocity prediction," Energy, Elsevier, vol. 155(C), pages 838-852.
    22. Xu Chen & Guangdi Hu & Feng Guo & Mengqi Ye & Jingyuan Huang, 2020. "Switched Energy Management Strategy for Fuel Cell Hybrid Vehicle Based on Switch Network," Energies, MDPI, vol. 13(1), pages 1-23, January.
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    3. Qian Zhang & Shaopeng Tian, 2023. "Energy Consumption Prediction and Control Algorithm for Hybrid Electric Vehicles Based on an Equivalent Minimum Fuel Consumption Model," Sustainability, MDPI, vol. 15(12), pages 1-17, June.
    4. 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).

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