Lithium-Ion Batteries state of charge estimation based on electrochemical impedance spectroscopy and convolutional neural network |
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| 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.
- Download:
- IMEKO-TC4-2022-17.pdf
- DOI:
- 10.21014/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