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Forecasting the sustainable classified recycling of used lithium batteries by gray Graphical Evaluation and Review Technique

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  • Zeng, Jing
  • Liu, Sifeng

Abstract

The recycling of used lithium batteries not only protects the environment but also alleviates the resource constraints. In this work, enterprises for cascade utilization of lithium batteries are categorized as remanufacturers, energy storage centers, and valuable metal recycling centers. The waste generated during the recycling process is disposed of by waste treatment stations. Based on the recycling process, a gray Graphical Evaluation and Review Technique(GERT) model is proposed to predict the time, probability, and economic benefits of lithium battery recycling. Due to the introduction of gray parameters, the solution results inevitably produce grayness. In the case that the grayness cannot be calculated directly, a calculation method is proposed to determine the interval of gray parameter based on the practical situation. The solution results of the gray GERT network are uncertain and should be made to better match the needs of practical applications. Gray GERT model solves the uncertainty and randomness of recycling process, which can adjust the parameters according to the differences of recycling technology and the change of economic environment to enhance the adaptability of the model. This work provides a reference value for the recycling system construction and cascade utilization of battery.

Suggested Citation

  • Zeng, Jing & Liu, Sifeng, 2023. "Forecasting the sustainable classified recycling of used lithium batteries by gray Graphical Evaluation and Review Technique," Renewable Energy, Elsevier, vol. 202(C), pages 602-612.
    • Handle: RePEc:eee:renene:v:202:y:2023:i:c:p:602-612
    DOI: 10.1016/j.renene.2022.11.018
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    References listed on IDEAS

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    1. Zongwei Liu & Xinglong Liu & Han Hao & Fuquan Zhao & Amer Ahmad Amer & Hassan Babiker, 2020. "Research on the Critical Issues for Power Battery Reusing of New Energy Vehicles in China," Energies, MDPI, vol. 13(8), pages 1-19, April.
    2. Zhou, Li & Xie, Jiaping & Gu, Xiaoyu & Lin, Yong & Ieromonachou, Petros & Zhang, Xiaole, 2016. "Forecasting return of used products for remanufacturing using Graphical Evaluation and Review Technique (GERT)," International Journal of Production Economics, Elsevier, vol. 181(PB), pages 315-324.
    3. Shahjalal, Mohammad & Roy, Probir Kumar & Shams, Tamanna & Fly, Ashley & Chowdhury, Jahedul Islam & Ahmed, Md. Rishad & Liu, Kailong, 2022. "A review on second-life of Li-ion batteries: prospects, challenges, and issues," Energy, Elsevier, vol. 241(C).
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    Cited by:

    1. Sun, Yufeng & Shi, Dongming & Liu, Hengyu & Liu, Mingyang & Ying, Jilai & Guo, Xiaohan & Li, Jingzu & Liu, Qinglei & Kong, Ing, 2025. "Evaluation the environmental carrying capacity of lithium-ion battery recycling using emergy analysis," Energy, Elsevier, vol. 341(C).
    2. Li, Jingkui & Liu, Xiaona & Lu, Yuze & Wang, Hanzheng, 2024. "Reliability analysis on energy storage system combining GO-FLOW methodology with GERT network," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    3. Tripathy, Satchidananda & Kumar, Akhilesh & Mahanty, Biswajit, 2023. "Short-lived product returns forecasting when customers are unwilling to return the product: A grey-graphical evaluation and review technique," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    4. Calise, Francesco & Cappiello, Francesco Liberato & Cimmino, Luca & Dentice d’Accadia, Massimo & Vicidomini, Maria, 2023. "Renewable smart energy network: A thermoeconomic comparison between conventional lithium-ion batteries and reversible solid oxide fuel cells," Renewable Energy, Elsevier, vol. 214(C), pages 74-95.

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