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Lithium-Ion Batteries state of charge estimation based on electrochemical impedance spectroscopy and convolutional neural network

Emanuele Buchicchio, Alessio De Angelis, Francesco Santoni, Paolo Carbone
  • Abstract:
    Estimating the state of charge of batteries is a critical task for every battery-powered device. In this work, we propose a machine learning approach based on electrochemical impedance spectroscopy and convolutional neural networks. A case study based on Samsung ICR18650-26J lithium-Ion batteries is also presented and discussed in detail. A classification accuracy of 80% and top-2 classification accuracy of 95% were achieved on a test battery not used for model training.
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  • DOI:
    tc4-2022.17

Event details:

  • IMEKO TC:
    TC4
  • Event name:
    TC4 Symposium 2022
  • Title:

    25th IMEKO TC4 Symposium and 23nd International Workshop on ADC and DAC Modelling and Testing (IWADC)

  • Place:
    Brescia, ITALY
  • Time:
    12 September 2022 - 14 September 2022