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An Improved Energy Management Strategy for Hybrid Energy Storage System in Light Rail Vehicles

Author

Listed:
  • Long Cheng

    (National Active Distribution Network Technology Research Center, Beijing Jiaotong University, Beijing 100044, China)

  • Wei Wang

    (National Active Distribution Network Technology Research Center, Beijing Jiaotong University, Beijing 100044, China)

  • Shaoyuan Wei

    (National Active Distribution Network Technology Research Center, Beijing Jiaotong University, Beijing 100044, China)

  • Hongtao Lin

    (National Active Distribution Network Technology Research Center, Beijing Jiaotong University, Beijing 100044, China)

  • Zhidong Jia

    (National Active Distribution Network Technology Research Center, Beijing Jiaotong University, Beijing 100044, China)

Abstract

A single-objective optimization energy management strategy (EMS) for an onboard hybrid energy storage system (HESS) for light rail (LR) vehicles is proposed. The HESS uses batteries and supercapacitors (SCs). The main objective of the proposed optimization is to reduce the battery and SC losses while maintaining the SC state of charge (SOC) within specific limits based on the distance between consecutive LR stations. To do this, a series of optimized SOC limits is used to prevent the SC from becoming exhausted prematurely instead of the standard SC SOC penalty term in the cost function. Meanwhile, a rule-based EMS (RB-EMS) is used to give the SCs charging priority over the batteries when the vehicle is braking. Moreover, a simplified method for the optimization is proposed to reduce the computational burden. Simulation and experimental results for the proposed EMS and a standard SC SOC penalty-based cost function optimization are provided to evaluate losses. As a result, it is shown that the proposed EMS, compared with standard SC SOC penalty-based cost function optimization, decreases losses and prevents the SOC from reach the discharging limits.

Suggested Citation

  • Long Cheng & Wei Wang & Shaoyuan Wei & Hongtao Lin & Zhidong Jia, 2018. "An Improved Energy Management Strategy for Hybrid Energy Storage System in Light Rail Vehicles," Energies, MDPI, vol. 11(2), pages 1-15, February.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:2:p:423-:d:131569
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    References listed on IDEAS

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    Cited by:

    1. Ying Yang & Weige Zhang & Shaoyuan Wei & Zhenpo Wang, 2020. "Optimal Sizing of On-Board Energy Storage Systems and Stationary Charging Infrastructures for a Catenary-Free Tram," Energies, MDPI, vol. 13(23), pages 1-21, November.
    2. Mario Marchesoni & Massimiliano Passalacqua & Luis Vaccaro, 2020. "A Refined Loss Evaluation of a Three-Switch Double Input DC-DC Converter for Hybrid Vehicle Applications," Energies, MDPI, vol. 13(1), pages 1-13, January.
    3. Ali Saleh Aziz & Mohammad Faridun Naim Tajuddin & Mohd Rafi Adzman & Makbul A. M. Ramli & Saad Mekhilef, 2019. "Energy Management and Optimization of a PV/Diesel/Battery Hybrid Energy System Using a Combined Dispatch Strategy," Sustainability, MDPI, vol. 11(3), pages 1-26, January.
    4. Xingyue Jiang & Jianjun Hu & Meixia Jia & Yong Zheng, 2018. "Parameter Matching and Instantaneous Power Allocation for the Hybrid Energy Storage System of Pure Electric Vehicles," Energies, MDPI, vol. 11(8), pages 1-18, July.
    5. Danijel Pavković & Mihael Cipek & Zdenko Kljaić & Tomislav Josip Mlinarić & Mario Hrgetić & Davor Zorc, 2018. "Damping Optimum-Based Design of Control Strategy Suitable for Battery/Ultracapacitor Electric Vehicles," Energies, MDPI, vol. 11(10), pages 1-26, October.
    6. Mihai Machedon-Pisu & Paul Nicolae Borza, 2019. "Are Personal Electric Vehicles Sustainable? A Hybrid E-Bike Case Study," Sustainability, MDPI, vol. 12(1), pages 1-24, December.
    7. Ma, Qian & Huang, Xiang & Wang, Feng & Xu, Chao & Babaei, Reza & Ahmadian, Hossein, 2022. "Optimal sizing and feasibility analysis of grid-isolated renewable hybrid microgrids: Effects of energy management controllers," Energy, Elsevier, vol. 240(C).
    8. Hongtao Liao & Fu Jiang & Cheng Jin & Yue Wu & Heng Li & Yongjie Liu & Zhiwu Huang & Jun Peng, 2020. "Lithium-Ion Battery SoC Equilibrium: An Artificial Potential Field-Based Method," Energies, MDPI, vol. 13(21), pages 1-15, October.

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