IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v246y2022ics0360544222002122.html
   My bibliography  Save this article

Co-optimization strategy of unmanned hybrid electric tracked vehicle combining eco-driving and simultaneous energy management

Author

Listed:
  • Guo, Lingxiong
  • Zhang, Xudong
  • Zou, Yuan
  • Han, Lijin
  • Du, Guodong
  • Guo, Ningyuan
  • Xiang, Changle

Abstract

Combining eco-driving optimization and simultaneous proper energy management, this paper proposes an efficient co-optimization strategy of unmanned hybrid electric tracked vehicles (HETVs) based on a hierarchical control framework to achieve accurate path tracking and optimal energy management simultaneously. Constrained by a pre-known reference path, a deep Q-learning (DQL) algorithm with the AMSGrad optimizer is designed in the upper layer to optimize the velocity of both side tracks to find the best trade-off between energy economy and accurate path tracking. Based on the optimal velocity profile obtained from the upper layer, an explicit model predictive control method is designed in the lower layer to distribute the power between the engine generator and battery in real time to achieve approximate optimal fuel economy. Simulation results verify that the designed DQL method only requires 0.67 s on average for real-time velocity planning, which is markedly lower than the dynamic programming algorithm. In addition, the proposed method also exhibits higher rapidity and optimality for velocity planning than the traditional DQL algorithm. Compared with the model predictive control, dynamic programming and a process without velocity planning, the proposed co-optimization strategy achieves good fuel economy, accurate path tracking and high computational efficiency.

Suggested Citation

  • Guo, Lingxiong & Zhang, Xudong & Zou, Yuan & Han, Lijin & Du, Guodong & Guo, Ningyuan & Xiang, Changle, 2022. "Co-optimization strategy of unmanned hybrid electric tracked vehicle combining eco-driving and simultaneous energy management," Energy, Elsevier, vol. 246(C).
    • Handle: RePEc:eee:energy:v:246:y:2022:i:c:s0360544222002122
    DOI: 10.1016/j.energy.2022.123309
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222002122
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.123309?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Guo, Lingxiong & Zhang, Xudong & Zou, Yuan & Guo, Ningyuan & Li, Jianwei & Du, Guodong, 2021. "Cost-optimal energy management strategy for plug-in hybrid electric vehicles with variable horizon speed prediction and adaptive state-of-charge reference," Energy, Elsevier, vol. 232(C).
    2. Liu, Teng & Tan, Wenhao & Tang, Xiaolin & Zhang, Jinwei & Xing, Yang & Cao, Dongpu, 2021. "Driving conditions-driven energy management strategies for hybrid electric vehicles: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    3. Guo, Ningyuan & Zhang, Xudong & Zou, Yuan & Guo, Lingxiong & Du, Guodong, 2021. "Real-time predictive energy management of plug-in hybrid electric vehicles for coordination of fuel economy and battery degradation," Energy, Elsevier, vol. 214(C).
    4. 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).
    5. Song, Ke & Wang, Xiaodi & Li, Feiqiang & Sorrentino, Marco & Zheng, Bailin, 2020. "Pontryagin’s minimum principle-based real-time energy management strategy for fuel cell hybrid electric vehicle considering both fuel economy and power source durability," Energy, Elsevier, vol. 205(C).
    6. Xie, Shaobo & Hu, Xiaosong & Liu, Teng & Qi, Shanwei & Lang, Kun & Li, Huiling, 2019. "Predictive vehicle-following power management for plug-in hybrid electric vehicles," Energy, Elsevier, vol. 166(C), pages 701-714.
    7. Huang, Yuhan & Ng, Elvin C.Y. & Zhou, John L. & Surawski, Nic C. & Chan, Edward F.C. & Hong, Guang, 2018. "Eco-driving technology for sustainable road transport: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 596-609.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yu, Xiao & Lin, Cheng & Xie, Peng & Liang, Sheng, 2022. "A novel real-time energy management strategy based on Monte Carlo Tree Search for coupled powertrain platform via vehicle-to-cloud connectivity," Energy, Elsevier, vol. 256(C).
    2. Liu, Yonggang & Huang, Bin & Yang, Yang & Lei, Zhenzhen & Zhang, Yuanjian & Chen, Zheng, 2022. "Hierarchical speed planning and energy management for autonomous plug-in hybrid electric vehicle in vehicle-following environment," Energy, Elsevier, vol. 260(C).
    3. Liu, Rui & Liu, Hui & Nie, Shida & Han, Lijin & Yang, Ningkang, 2023. "A hierarchical eco-driving strategy for hybrid electric vehicles via vehicle-to-cloud connectivity," Energy, Elsevier, vol. 281(C).
    4. Guo, Lingxiong & Liu, Hui & Han, Lijin & Yang, Ningkang & Liu, Rui & Xiang, Changle, 2023. "Predictive energy management strategy of dual-mode hybrid electric vehicles combining dynamic coordination control and simultaneous power distribution," Energy, Elsevier, vol. 263(PA).
    5. 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).

    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.
    1. 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).
    2. 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).
    3. Iqbal, Mehroze & Laurent, Julien & Benmouna, Amel & Becherif, Mohamed & Ramadan, Haitham S. & Claude, Frederic, 2022. "Ageing-aware load following control for composite-cost optimal energy management of fuel cell hybrid electric vehicle," Energy, Elsevier, vol. 254(PA).
    4. Badji, Abderrezak & Abdeslam, Djaffar Ould & Chabane, Djafar & Benamrouche, Nacereddine, 2022. "Real-time implementation of improved power frequency approach based energy management of fuel cell electric vehicle considering storage limitations," Energy, Elsevier, vol. 249(C).
    5. Guo, Xiaokai & Yan, Xianguo & Chen, Zhi & Meng, Zhiyu, 2022. "Research on energy management strategy of heavy-duty fuel cell hybrid vehicles based on dueling-double-deep Q-network," Energy, Elsevier, vol. 260(C).
    6. Wang, Yue & Li, Keqiang & Zeng, Xiaohua & Gao, Bolin & Hong, Jichao, 2022. "Energy consumption characteristics based driving conditions construction and prediction for hybrid electric buses energy management," Energy, Elsevier, vol. 245(C).
    7. Cui, Wei & Cui, Naxin & Li, Tao & Cui, Zhongrui & Du, Yi & Zhang, Chenghui, 2022. "An efficient multi-objective hierarchical energy management strategy for plug-in hybrid electric vehicle in connected scenario," Energy, Elsevier, vol. 257(C).
    8. Huang, Ying & Wang, Shilong & Li, Ke & Fan, Zhuwei & Xie, Haiming & Jiang, Fachao, 2023. "Multi-parameter adaptive online energy management strategy for concrete truck mixers with a novel hybrid powertrain considering vehicle mass," Energy, Elsevier, vol. 277(C).
    9. Li, Jie & Wu, Xiaodong & Xu, Min & Liu, Yonggang, 2022. "Deep reinforcement learning and reward shaping based eco-driving control for automated HEVs among signalized intersections," Energy, Elsevier, vol. 251(C).
    10. Du, Yi & Cui, Naxin & Cui, Wei & Li, Tao & Ren, Fei & Zhang, Chenghui, 2023. "AGRU and convex optimization based energy management for plug-in hybrid electric bus considering battery aging," Energy, Elsevier, vol. 277(C).
    11. Guo, Lingxiong & Zhang, Xudong & Zou, Yuan & Guo, Ningyuan & Li, Jianwei & Du, Guodong, 2021. "Cost-optimal energy management strategy for plug-in hybrid electric vehicles with variable horizon speed prediction and adaptive state-of-charge reference," Energy, Elsevier, vol. 232(C).
    12. Wu, Yue & Huang, Zhiwu & Hofmann, Heath & Liu, Yongjie & Huang, Jiahao & Hu, Xiaosong & Peng, Jun & Song, Ziyou, 2022. "Hierarchical predictive control for electric vehicles with hybrid energy storage system under vehicle-following scenarios," Energy, Elsevier, vol. 251(C).
    13. Zhang, Hao & Fan, Qinhao & Liu, Shang & Li, Shengbo Eben & Huang, Jin & Wang, Zhi, 2021. "Hierarchical energy management strategy for plug-in hybrid electric powertrain integrated with dual-mode combustion engine," Applied Energy, Elsevier, vol. 304(C).
    14. Saeed Vasebi & Yeganeh M. Hayeri, 2021. "Collective Driving to Mitigate Climate Change: Collective-Adaptive Cruise Control," Sustainability, MDPI, vol. 13(16), pages 1-30, August.
    15. Xie, Shaobo & Qi, Shanwei & Lang, Kun & Tang, Xiaolin & Lin, Xianke, 2020. "Coordinated management of connected plug-in hybrid electric buses for energy saving, inter-vehicle safety, and battery health," Applied Energy, Elsevier, vol. 268(C).
    16. Jaller, Miguel & Pahwa, Anmol & Zhang, Michael, 2021. "Cargo Routing and Disadvantaged Communities," Institute of Transportation Studies, Working Paper Series qt9qg2318x, Institute of Transportation Studies, UC Davis.
    17. Bi, Huibo & Shang, Wen-Long & Chen, Yanyan & Wang, Kezhi & Yu, Qing & Sui, Yi, 2021. "GIS aided sustainable urban road management with a unifying queueing and neural network model," Applied Energy, Elsevier, vol. 291(C).
    18. Taghavifar, Hadi, 2021. "Fuel cell hybrid range-extender vehicle sizing: Parametric power optimization," Energy, Elsevier, vol. 229(C).
    19. Ma, Yan & Hu, Fuyuan & Hu, Yunfeng, 2023. "Energy efficiency improvement of intelligent fuel cell/battery hybrid vehicles through an integrated management strategy," Energy, Elsevier, vol. 263(PE).
    20. Zhang, Bo & Zhang, Jiangyan & Shen, Tielong, 2022. "Optimal control design for comfortable-driving of hybrid electric vehicles in acceleration mode," Applied Energy, Elsevier, vol. 305(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:eee:energy:v:246:y:2022:i:c:s0360544222002122. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.