IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v281y2023ics0360544223016912.html
   My bibliography  Save this article

Integrated optimization of driving strategy and energy management for hybrid diesel multiple units

Author

Listed:
  • Zhang, Chi
  • Zeng, Guohong
  • Wu, Jian
  • Wei, Shaoyuan
  • Zhang, Weige
  • Sun, Bingxiang

Abstract

Hybrid diesel multiple units (HDMU) are considered an effective way to reduce fuel consumption and pollution emissions in regional non-electrified railways. To minimize the fuel consumption of HDMU, this paper formulates an integrated optimization of driving strategy and energy management. By introducing convex relaxation and linearization, we propose a second-order cone programming method to solve this integrated optimization. Case studies of multiple scenarios validate the effectiveness and robustness of the proposed method. In addition, the simulation results show that compared with the sequential optimization with the step-by-step improvement of driving strategy and energy management, the integrated optimization considers the battery characteristics when optimizing the driving strategy and reduces the electric braking power of the train, thus allowing the battery to absorb more braking energy and reduce fuel consumption.

Suggested Citation

  • Zhang, Chi & Zeng, Guohong & Wu, Jian & Wei, Shaoyuan & Zhang, Weige & Sun, Bingxiang, 2023. "Integrated optimization of driving strategy and energy management for hybrid diesel multiple units," Energy, Elsevier, vol. 281(C).
    • Handle: RePEc:eee:energy:v:281:y:2023:i:c:s0360544223016912
    DOI: 10.1016/j.energy.2023.128297
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223016912
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.128297?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. Liu, Weisheng & Lin, Boqiang, 2021. "Electrification of rails in China: Its impact on energy conservation and emission reduction," Energy, Elsevier, vol. 226(C).
    2. Cipek, Mihael & Pavković, Danijel & Krznar, Matija & Kljaić, Zdenko & Mlinarić, Tomislav Josip, 2021. "Comparative analysis of conventional diesel-electric and hypothetical battery-electric heavy haul locomotive operation in terms of fuel savings and emissions reduction potentials," Energy, Elsevier, vol. 232(C).
    3. Liu, Hui & Li, Xunming & Wang, Weida & Han, Lijin & Xiang, Changle, 2018. "Markov velocity predictor and radial basis function neural network-based real-time energy management strategy for plug-in hybrid electric vehicles," Energy, Elsevier, vol. 152(C), pages 427-444.
    4. Zhang, Shuo & Xiong, Rui & Zhang, Chengning, 2015. "Pontryagin’s Minimum Principle-based power management of a dual-motor-driven electric bus," Applied Energy, Elsevier, vol. 159(C), pages 370-380.
    5. Cipek, Mihael & Pavković, Danijel & Kljaić, Zdenko & Mlinarić, Tomislav Josip, 2019. "Assessment of battery-hybrid diesel-electric locomotive fuel savings and emission reduction potentials based on a realistic mountainous rail route," Energy, Elsevier, vol. 173(C), pages 1154-1171.
    6. Kapetanović, Marko & Núñez, Alfredo & van Oort, Niels & Goverde, Rob M.P., 2021. "Reducing fuel consumption and related emissions through optimal sizing of energy storage systems for diesel-electric trains," Applied Energy, Elsevier, vol. 294(C).
    7. Li, Xiang & Lo, Hong K., 2014. "An energy-efficient scheduling and speed control approach for metro rail operations," Transportation Research Part B: Methodological, Elsevier, vol. 64(C), pages 73-89.
    8. Peng, Hujun & Li, Jianxiang & Löwenstein, Lars & Hameyer, Kay, 2020. "A scalable, causal, adaptive energy management strategy based on optimal control theory for a fuel cell hybrid railway vehicle," Applied Energy, Elsevier, vol. 267(C).
    9. Albrecht, Amie & Howlett, Phil & Pudney, Peter & Vu, Xuan & Zhou, Peng, 2016. "The key principles of optimal train control—Part 1: Formulation of the model, strategies of optimal type, evolutionary lines, location of optimal switching points," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 482-508.
    Full references (including those not matched with items on IDEAS)

    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. Marko Kapetanović & Mohammad Vajihi & Rob M. P. Goverde, 2021. "Analysis of Hybrid and Plug-In Hybrid Alternative Propulsion Systems for Regional Diesel-Electric Multiple Unit Trains," Energies, MDPI, vol. 14(18), pages 1-29, September.
    2. Chen, Shuang & Hu, Minghui & Lei, Yanlei & Kong, Linghao, 2023. "Novel hybrid power system and energy management strategy for locomotives," Applied Energy, Elsevier, vol. 348(C).
    3. Zhan, Shuguang & Wang, Pengling & Wong, S.C. & Lo, S.M., 2022. "Energy-efficient high-speed train rescheduling during a major disruption," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    4. Luan, Xiaojie & Wang, Yihui & De Schutter, Bart & Meng, Lingyun & Lodewijks, Gabriel & Corman, Francesco, 2018. "Integration of real-time traffic management and train control for rail networks - Part 2: Extensions towards energy-efficient train operations," Transportation Research Part B: Methodological, Elsevier, vol. 115(C), pages 72-94.
    5. Yin, Jiateng & Yang, Lixing & Tang, Tao & Gao, Ziyou & Ran, Bin, 2017. "Dynamic passenger demand oriented metro train scheduling with energy-efficiency and waiting time minimization: Mixed-integer linear programming approaches," Transportation Research Part B: Methodological, Elsevier, vol. 97(C), pages 182-213.
    6. Wang, Xuekai & Tang, Tao & Su, Shuai & Yin, Jiateng & Gao, Ziyou & Lv, Nan, 2021. "An integrated energy-efficient train operation approach based on the space-time-speed network methodology," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
    7. Jie Yang & Limin Jia & Shaofeng Lu & Yunxiao Fu & Ji Ge, 2016. "Energy-Efficient Speed Profile Approximation: An Optimal Switching Region-Based Approach with Adaptive Resolution," Energies, MDPI, vol. 9(10), pages 1-27, September.
    8. Miguel Angel Rodriguez-Cabal & Diego Alejandro Herrera-Jaramillo & Juan David Bastidas-Rodriguez & Juan Pablo Villegas-Ceballos & Kevin Smit Montes-Villa, 2022. "Methodology for the Estimation of Electrical Power Consumed by Locomotives on Undocumented Railroad Tracks," Energies, MDPI, vol. 15(12), pages 1-23, June.
    9. Ning, Jingjie & Zhou, Yonghua & Long, Fengchu & Tao, Xin, 2018. "A synergistic energy-efficient planning approach for urban rail transit operations," Energy, Elsevier, vol. 151(C), pages 854-863.
    10. Zdenko Kljaić & Danijel Pavković & Mihael Cipek & Maja Trstenjak & Tomislav Josip Mlinarić & Mladen Nikšić, 2023. "An Overview of Current Challenges and Emerging Technologies to Facilitate Increased Energy Efficiency, Safety, and Sustainability of Railway Transport," Future Internet, MDPI, vol. 15(11), pages 1-44, October.
    11. Canca, David & Zarzo, Alejandro, 2017. "Design of energy-Efficient timetables in two-way railway rapid transit lines," Transportation Research Part B: Methodological, Elsevier, vol. 102(C), pages 142-161.
    12. Huang, Yu & Zhou, Wenliang & Qin, Jin & Deng, Lianbo, 2023. "Optimization of energy-efficiency train schedule considering passenger demand and rolling stock circulation plan of subway line," Energy, Elsevier, vol. 275(C).
    13. Wang, Pengling & Goverde, Rob M.P., 2019. "Multi-train trajectory optimization for energy-efficient timetabling," European Journal of Operational Research, Elsevier, vol. 272(2), pages 621-635.
    14. Yang, Songpo & Liao, Feixiong & Wu, Jianjun & Timmermans, Harry J.P. & Sun, Huijun & Gao, Ziyou, 2020. "A bi-objective timetable optimization model incorporating energy allocation and passenger assignment in an energy-regenerative metro system," Transportation Research Part B: Methodological, Elsevier, vol. 133(C), pages 85-113.
    15. Hegde, Bharatkumar & Ahmed, Qadeer & Rizzoni, Giorgio, 2022. "Energy saving analysis in electrified powertrain using look-ahead energy management scheme," Applied Energy, Elsevier, vol. 325(C).
    16. Zhaoxiang Tan & Shaofeng Lu & Kai Bao & Shaoning Zhang & Chaoxian Wu & Jie Yang & Fei Xue, 2018. "Adaptive Partial Train Speed Trajectory Optimization," Energies, MDPI, vol. 11(12), pages 1-33, November.
    17. Wang, Weida & Chen, Yincong & Yang, Chao & Li, Ying & Xu, Bin & Xiang, Changle, 2022. "An enhanced hypotrochoid spiral optimization algorithm based intertwined optimal sizing and control strategy of a hybrid electric air-ground vehicle," Energy, Elsevier, vol. 257(C).
    18. Emrani, Anisa & Berrada, Asmae & Bakhouya, Mohamed, 2022. "Optimal sizing and deployment of gravity energy storage system in hybrid PV-Wind power plant," Renewable Energy, Elsevier, vol. 183(C), pages 12-27.
    19. Kapetanović, Marko & Núñez, Alfredo & van Oort, Niels & Goverde, Rob M.P., 2021. "Reducing fuel consumption and related emissions through optimal sizing of energy storage systems for diesel-electric trains," Applied Energy, Elsevier, vol. 294(C).
    20. Anselma, Pier Giuseppe, 2022. "Computationally efficient evaluation of fuel and electrical energy economy of plug-in hybrid electric vehicles with smooth driving constraints," Applied Energy, Elsevier, vol. 307(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:281:y:2023:i:c:s0360544223016912. 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.