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Toward safe carbon–neutral transportation: Battery internal short circuit diagnosis based on cloud data for electric vehicles

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  • Qiao, Dongdong
  • Wei, Xuezhe
  • Fan, Wenjun
  • Jiang, Bo
  • Lai, Xin
  • Zheng, Yuejiu
  • Tang, Xiaolin
  • Dai, Haifeng

Abstract

To promote electrified transportation and achieve carbon neutrality, Li-ion batteries with excellent energy storage performance are widely adopted in electric vehicles (EVs). However, internal short circuit (ISC) of batteries is a serious safety hazard of EVs. ISC diagnosis using the powerful storage and computing capabilities of the cloud platform is a promising method to enhance the safety performance of battery packs in EVs, but the recording period of cloud data is larger than that of battery management systems in EVs, which brings great challenges to the existing ISC diagnosis methods. In this paper, the new mean-normalization is employed to amplify the voltage characteristics of the ISC cell in the battery pack. The adaptive Kalman filter algorithm is deployed to filter the mean-normalization values to obtain the vivid ISC features. Furthermore, the density-based spatial clustering of applications with noise algorithm is exploited to automatically detect and locate the ISC cell. Even with the 40 s sparse data in the real vehicle, the ISC cell also can be timely diagnosed within 2.51 h.

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  • Qiao, Dongdong & Wei, Xuezhe & Fan, Wenjun & Jiang, Bo & Lai, Xin & Zheng, Yuejiu & Tang, Xiaolin & Dai, Haifeng, 2022. "Toward safe carbon–neutral transportation: Battery internal short circuit diagnosis based on cloud data for electric vehicles," Applied Energy, Elsevier, vol. 317(C).
    • Handle: RePEc:eee:appene:v:317:y:2022:i:c:s0306261922005402
    DOI: 10.1016/j.apenergy.2022.119168
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    1. Qiao, Dongdong & Wang, Xueyuan & Lai, Xin & Zheng, Yuejiu & Wei, Xuezhe & Dai, Haifeng, 2022. "Online quantitative diagnosis of internal short circuit for lithium-ion batteries using incremental capacity method," Energy, Elsevier, vol. 243(C).
    2. Feng, Xuning & Weng, Caihao & Ouyang, Minggao & Sun, Jing, 2016. "Online internal short circuit detection for a large format lithium ion battery," Applied Energy, Elsevier, vol. 161(C), pages 168-180.
    3. Joeri Rogelj & Daniel Huppmann & Volker Krey & Keywan Riahi & Leon Clarke & Matthew Gidden & Zebedee Nicholls & Malte Meinshausen, 2019. "A new scenario logic for the Paris Agreement long-term temperature goal," Nature, Nature, vol. 573(7774), pages 357-363, September.
    4. Bi, Huibo & Shang, Wen-Long & Chen, Yanyan & Wang, Kezhi & Yu, Qing & Sui, Yi, 2021. "GIS aided sustainable urban road management with a unifying queueing and neural network model," Applied Energy, Elsevier, vol. 291(C).
    5. Zhao, Yang & Liu, Peng & Wang, Zhenpo & Zhang, Lei & Hong, Jichao, 2017. "Fault and defect diagnosis of battery for electric vehicles based on big data analysis methods," Applied Energy, Elsevier, vol. 207(C), pages 354-362.
    6. Jiang, Bo & Dai, Haifeng & Wei, Xuezhe, 2020. "Incremental capacity analysis based adaptive capacity estimation for lithium-ion battery considering charging condition," Applied Energy, Elsevier, vol. 269(C).
    7. Wen-Long Shang & Yanyan Chen & Chengcheng Song & Washington Y. Ochieng, 2020. "Robustness Analysis of Urban Road Networks from Topological and Operational Perspectives," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-12, August.
    8. Zhang, Guangxu & Wei, Xuezhe & Tang, Xuan & Zhu, Jiangong & Chen, Siqi & Dai, Haifeng, 2021. "Internal short circuit mechanisms, experimental approaches and detection methods of lithium-ion batteries for electric vehicles: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    9. Yang, Zaoli & Shang, Wen-Long & Zhang, Haoran & Garg, Harish & Han, Chunjia, 2022. "Assessing the green distribution transformer manufacturing process using a cloud-based q-rung orthopair fuzzy multi-criteria framework," Applied Energy, Elsevier, vol. 311(C).
    10. Da Li & Zhaosheng Zhang & Peng Liu & Zhenpo Wang, 2019. "DBSCAN-Based Thermal Runaway Diagnosis of Battery Systems for Electric Vehicles," Energies, MDPI, vol. 12(15), pages 1-15, August.
    11. Wang, Zhenpo & Hong, Jichao & Liu, Peng & Zhang, Lei, 2017. "Voltage fault diagnosis and prognosis of battery systems based on entropy and Z-score for electric vehicles," Applied Energy, Elsevier, vol. 196(C), pages 289-302.
    12. Zhou, Junfeng & Zhang, Yanhui & Zhang, Yubo & Shang, Wen-Long & Yang, Zhile & Feng, Wei, 2022. "Parameters identification of photovoltaic models using a differential evolution algorithm based on elite and obsolete dynamic learning," Applied Energy, Elsevier, vol. 314(C).
    13. Xiong, Rui & Sun, Wanzhou & Yu, Quanqing & Sun, Fengchun, 2020. "Research progress, challenges and prospects of fault diagnosis on battery system of electric vehicles," Applied Energy, Elsevier, vol. 279(C).
    14. Shang, Wen-Long & Chen, Jinyu & Bi, Huibo & Sui, Yi & Chen, Yanyan & Yu, Haitao, 2021. "Impacts of COVID-19 pandemic on user behaviors and environmental benefits of bike sharing: A big-data analysis," Applied Energy, Elsevier, vol. 285(C).
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    5. Siyi Tao & Bo Jiang & Xuezhe Wei & Haifeng Dai, 2023. "A Systematic and Comparative Study of Distinct Recurrent Neural Networks for Lithium-Ion Battery State-of-Charge Estimation in Electric Vehicles," Energies, MDPI, vol. 16(4), pages 1-17, February.
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