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A Degradation-Informed Battery-Swapping Policy for Fleets of Electric or Hybrid-Electric Vehicles

Author

Listed:
  • Ahmad Almuhtady

    (Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan 48109)

  • Seungchul Lee

    (Department of Human and Systems Engineering, Ulsan National Institute of Science and Technology, Ulsan, 689-798, Korea)

  • Edwin Romeijn

    (Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan 48109)

  • Michael Wynblatt

    (Eaton Corporation-Innovation Center, Southfield, Michigan 48076)

  • Jun Ni

    (Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan 48109)

Abstract

Motivated by high oil prices, several large fleet companies initiated future plans to hybridize their fleets to establish immunity of their optimized business models against severe oil price fluctuations, and adhere to increasing awareness of environmentally friendly solutions. The hybridization projects increased maintenance costs especially for costly and degradable components such as Li-ion batteries. This paper introduces a degradation-based resource allocation policy to optimally utilize batteries on fleet level. The policy, denoted as degradation-based swapping optimization, incorporates optimal implementation of swapping and substitution actions throughout a plan of finite-time horizon to minimize projected maintenance costs. The swapping action refers to the interchange in the placement of two batteries within a fleet. The substitution action refers to the replacement of degraded batteries with new ones. The policy takes advantage of the different degradation rates of the state of health of the batteries because of different loading conditions, achieving optimal placement at different time intervals throughout the plan horizon. A mathematical model for the policy is provided. The optimization of the generated model is studied through several algorithms. Numerical results for sample problems are obtained to illustrate the capability of the proposed policy in establishing substantial savings in the projected maintenance costs compared to other policies.

Suggested Citation

  • Ahmad Almuhtady & Seungchul Lee & Edwin Romeijn & Michael Wynblatt & Jun Ni, 2014. "A Degradation-Informed Battery-Swapping Policy for Fleets of Electric or Hybrid-Electric Vehicles," Transportation Science, INFORMS, vol. 48(4), pages 609-618, November.
    • Handle: RePEc:inm:ortrsc:v:48:y:2014:i:4:p:609-618
    DOI: 10.1287/trsc.2013.0494
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    References listed on IDEAS

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    Cited by:

    1. Hu, Jiawen & Chen, Piao, 2020. "Predictive maintenance of systems subject to hard failure based on proportional hazards model," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    2. Zhu, Xiaoyan & Hao, Yaqian, 2021. "Component rearrangement and system replacement for a system with stochastic degradation processes," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    3. Ma, Chenyang & Wang, Qiyu & Cai, Zhiqiang & Si, Shubin & Zhao, Jiangbin, 2021. "Component reassignment for reliability optimization of reconfigurable systems considering component degradation," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    4. Zou, Bipan & Xu, Xianhao & Gong, Yeming (Yale) & De Koster, René, 2018. "Evaluating battery charging and swapping strategies in a robotic mobile fulfillment system," European Journal of Operational Research, Elsevier, vol. 267(2), pages 733-753.
    5. Fu, Yuqiang & Zhu, Xiaoyan & Ma, Xiaoyang, 2020. "Optimum component reallocation and system replacement maintenance for a used system with increasing minimal repair cost," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    6. Wang, Liying & Song, Yushuang & Zhang, Wenhua & Ling, Xiaoliang, 2023. "Condition-based inspection, component reallocation and replacement optimization of two-component interchangeable series system," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    7. Fu, Yuqiang & Zhu, Xiaoyan, 2023. "A joint age-based system replacement and component reallocation maintenance policy: Optimization, analysis and resilience," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    8. Konstantina Valogianni & Wolfgang Ketter & John Collins & Dmitry Zhdanov, 2020. "Sustainable Electric Vehicle Charging using Adaptive Pricing," Production and Operations Management, Production and Operations Management Society, vol. 29(6), pages 1550-1572, June.
    9. Mark M. Nejad & Lena Mashayekhy & Daniel Grosu & Ratna Babu Chinnam, 2017. "Optimal Routing for Plug-In Hybrid Electric Vehicles," Transportation Science, INFORMS, vol. 51(4), pages 1304-1325, November.
    10. Fu, Yuqiang & Wang, Jun, 2022. "Optimum periodic maintenance policy of repairable multi-component system with component reallocation and system overhaul," Reliability Engineering and System Safety, Elsevier, vol. 219(C).

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