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Energy-efficient speed profile optimization for medium-speed maglev trains

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Listed:
  • Lai, Qingying
  • Liu, Jun
  • Haghani, Ali
  • Meng, Lingyun
  • Wang, Yihui

Abstract

This study addresses the problem of reducing the energy consumption of the medium-speed maglev (MSM) system by optimizing the train speed profile. Auxiliary stopping areas, the nonlinear resistance caused by the linear motor, and the suspension energy consumption are considered in the formulation of the speed profile optimization problem. Next, dynamic programming and mixed-integer linear programming (MILP) approaches that utilize these characteristics are proposed to solve the problem. The numerical results show that both approaches ensure MSM train safety and energy-efficient operation. Furthermore, the MILP approach could be used for emergency trajectory planning due to its shorter computational time.

Suggested Citation

  • Lai, Qingying & Liu, Jun & Haghani, Ali & Meng, Lingyun & Wang, Yihui, 2020. "Energy-efficient speed profile optimization for medium-speed maglev trains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
  • Handle: RePEc:eee:transe:v:141:y:2020:i:c:s136655452030658x
    DOI: 10.1016/j.tre.2020.102007
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    References listed on IDEAS

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    1. Jeong-Min Jo & Jin-Ho Lee & Young-Jae Han & Chang-Young Lee & Kwan-Sup Lee, 2017. "Development of Propulsion Inverter Control System for High-Speed Maglev based on Long Stator Linear Synchronous Motor," Energies, MDPI, vol. 10(2), pages 1-9, February.
    2. Albrecht, Amie & Howlett, Phil & Pudney, Peter & Vu, Xuan & Zhou, Peng, 2016. "The key principles of optimal train control—Part 2: Existence of an optimal strategy, the local energy minimization principle, uniqueness, computational techniques," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 509-538.
    3. Liu, Rongfang (Rachel) & Golovitcher, Iakov M., 2003. "Energy-efficient operation of rail vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(10), pages 917-932, December.
    4. 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.
    5. Haahr, Jørgen Thorlund & Pisinger, David & Sabbaghian, Mohammad, 2017. "A dynamic programming approach for optimizing train speed profiles with speed restrictions and passage points," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 167-182.
    6. Scheepmaker, Gerben M. & Goverde, Rob M.P. & Kroon, Leo G., 2017. "Review of energy-efficient train control and timetabling," European Journal of Operational Research, Elsevier, vol. 257(2), pages 355-376.
    7. Yang, Lixing & Li, Keping & Gao, Ziyou & Li, Xiang, 2012. "Optimizing trains movement on a railway network," Omega, Elsevier, vol. 40(5), pages 619-633.
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    Cited by:

    1. 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).
    2. Zhou, Wenliang & Huang, Yu & Deng, Lianbo & Qin, Jin, 2023. "Collaborative optimization of energy-efficient train schedule and train circulation plan for urban rail," Energy, Elsevier, vol. 263(PA).

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