A journal of IEEE and CAA , publishes
high-quality papers in English on original
theoretical/experimental research
and development in all areas of automation
Volume 12
Issue 12
IEEE/CAA Journal of Automatica Sinica
| Citation: | K. Liu, S. Zhao, Q. Peng, J. Wang, B. Duan, X. Li, and C. Zhang, “Prior-data fitted network with impedance spectroscopy for smart short circuit diagnosis in sodium-ion batteries of power systems,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 12, pp. 2630–2632, Dec. 2025. doi: 10.1109/JAS.2025.125606
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| [1] |
Y. Jin, P. M. Le, P. Gao, et al., “Low-solvation electrolytes for high-voltage sodium-ion batteries,” Nature Energy, vol. 7, no. 8, pp. 718−725, 2022.
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| [2] |
K. Liu, Y. Liu, Q. Peng, et al., “Interpretable data-driven learning with fast ultrasonic detection for battery health estimation,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 1, pp. 267−269, 2025.
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| [3] |
D. Ji, Z. Wei, C. Tian, H. Cai, and J. Zhao, “Deep transfer ensemble learning-based diagnostic of lithium-ion battery,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 9, pp. 1899−1901, 2022.
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| [4] |
G. Wang, G. Zhao, J. Xie, and K. Liu, “Ensemble learning-based correlation coefficient method for robust diagnosis of voltage sensor and short-circuit faults in series battery packs,” IEEE Trans. Power Electronics, vol. 38, no. 7, pp. 9143−9156, 2023.
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| [5] |
A. Joshi, S. Capezza, A. Alhaji, et al., “Survey on AI and machine learning techniques for microgrid energy management systems,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 7, pp. 1513−1529, 2023.
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| [6] |
X. Zhang, Y. Hu, C. Gong, et al., “Artificial intelligence technique-based EV powertrain condition monitoring and fault diagnosis: A review,” IEEE Sensors J., vol. 23, no. 15, pp. 16481–16500, 2023.
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