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Guidelines for designing a digital twin for Li-ion battery: A reference methodology

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  • Semeraro, Concetta
  • Aljaghoub, Haya
  • Abdelkareem, Mohammad Ali
  • Alami, Abdul Hai
  • Dassisti, Michele
  • Olabi, A.G.

Abstract

The integration of digital technologies is causing a significant change in the energy sector. These innovations have transformed traditional energy grids into intelligent grids. As a result, the digital replica of Battery Energy Storage Systems (BESS) has become one of the most crucial components in the energy sector. Digital twin technology enables the seamless integration of BESS into intelligent grids and offers numerous benefits, such as easy identification and prediction of faults, real-time system monitoring, optimization, temperature regulation, and estimation of parameters. As a result, the overall performance of BESS is improved by the digital twin technology. Consequently, this paper discusses the general guidelines that must be followed to develop a digital twin for a Li-ion BESS successfully. The main function is to define how to design a digital twin able to optimize the system and facilitate early and predictive fault detection and diagnosis.

Suggested Citation

  • Semeraro, Concetta & Aljaghoub, Haya & Abdelkareem, Mohammad Ali & Alami, Abdul Hai & Dassisti, Michele & Olabi, A.G., 2023. "Guidelines for designing a digital twin for Li-ion battery: A reference methodology," Energy, Elsevier, vol. 284(C).
    • Handle: RePEc:eee:energy:v:284:y:2023:i:c:s0360544223020935
    DOI: 10.1016/j.energy.2023.128699
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    as
    1. Huang, Yufeng & Tao, Jun & Sun, Gang & Wu, Tengyun & Yu, Liling & Zhao, Xinbin, 2023. "A novel digital twin approach based on deep multimodal information fusion for aero-engine fault diagnosis," Energy, Elsevier, vol. 270(C).
    2. Eklas Hossain & Hossain Mansur Resalat Faruque & Md. Samiul Haque Sunny & Naeem Mohammad & Nafiu Nawar, 2020. "A Comprehensive Review on Energy Storage Systems: Types, Comparison, Current Scenario, Applications, Barriers, and Potential Solutions, Policies, and Future Prospects," Energies, MDPI, vol. 13(14), pages 1-127, July.
    3. Burston, Martin & Ranasinghe, Kavindu & Gardi, Alessandro & Parezanović, Vladimir & Ajaj, Rafic & Sabatini, Roberto, 2022. "Design principles and digital control of advanced distributed propulsion systems," Energy, Elsevier, vol. 241(C).
    4. Li, Hongcheng & Yang, Dan & Cao, Huajun & Ge, Weiwei & Chen, Erheng & Wen, Xuanhao & Li, Chongbo, 2022. "Data-driven hybrid petri-net based energy consumption behaviour modelling for digital twin of energy-efficient manufacturing system," Energy, Elsevier, vol. 239(PC).
    5. Semeraro, Concetta & Aljaghoub, Haya & Abdelkareem, Mohammad Ali & Alami, Abdul Hai & Olabi, A.G., 2023. "Digital twin in battery energy storage systems: Trends and gaps detection through association rule mining," Energy, Elsevier, vol. 273(C).
    6. Koo, Bonchan & Chang, Seungjoon & Kwon, Hweeung, 2023. "Digital twin for natural gas infrastructure operation and management via streaming dynamic mode decomposition with control," Energy, Elsevier, vol. 274(C).
    7. Yu, Jianxi & Petersen, Nils & Liu, Pei & Li, Zheng & Wirsum, Manfred, 2022. "Hybrid modelling and simulation of thermal systems of in-service power plants for digital twin development," Energy, Elsevier, vol. 260(C).
    8. Chen, Ziyue & Huang, Lizhen, 2021. "Digital twins for information-sharing in remanufacturing supply chain: A review," Energy, Elsevier, vol. 220(C).
    9. Chen, Kang & Zhu, Xu & Anduv, Burkay & Jin, Xinqiao & Du, Zhimin, 2022. "Digital twins model and its updating method for heating, ventilation and air conditioning system using broad learning system algorithm," Energy, Elsevier, vol. 251(C).
    10. Sanjay Jain & Guodong Shao & Seung-Jun Shin, 2017. "Manufacturing data analytics using a virtual factory representation," International Journal of Production Research, Taylor & Francis Journals, vol. 55(18), pages 5450-5464, September.
    11. Bondarenko, Oleksiy & Fukuda, Tetsugo, 2020. "Development of a diesel engine’s digital twin for predicting propulsion system dynamics," Energy, Elsevier, vol. 196(C).
    12. Wei He & Michael Pecht & David Flynn & Fateme Dinmohammadi, 2018. "A Physics-Based Electrochemical Model for Lithium-Ion Battery State-of-Charge Estimation Solved by an Optimised Projection-Based Method and Moving-Window Filtering," Energies, MDPI, vol. 11(8), pages 1-23, August.
    13. Mahmood, Anzar & Javaid, Nadeem & Razzaq, Sohail, 2015. "A review of wireless communications for smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 248-260.
    14. Zhao, Guanjia & Cui, Zhipeng & Xu, Jing & Liu, Wenhao & Ma, Suxia, 2022. "Hybrid modeling-based digital twin for performance optimization with flexible operation in the direct air-cooling power unit," Energy, Elsevier, vol. 254(PC).
    15. Kang, Yongzhe & Duan, Bin & Zhou, Zhongkai & Shang, Yunlong & Zhang, Chenghui, 2020. "Online multi-fault detection and diagnosis for battery packs in electric vehicles," Applied Energy, Elsevier, vol. 259(C).
    16. Ziming Xu & Jun Xu & Zhechen Guo & Haitao Wang & Zheng Sun & Xuesong Mei, 2022. "Design and Optimization of a Novel Microchannel Battery Thermal Management System Based on Digital Twin," Energies, MDPI, vol. 15(4), pages 1-20, February.
    17. Lilia Tightiz & Hyosik Yang, 2020. "A Comprehensive Review on IoT Protocols’ Features in Smart Grid Communication," Energies, MDPI, vol. 13(11), pages 1-24, June.
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