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State of Health Estimation of On-Board Lithium-Ion Batteries Using Temporal Convolutional Network Optimized by Improved Self-Adaptive Honey Badger Algorithm
Power Generation Technology   Vol. 46, Issue 6, Pages: 1154-1163(2025)
Energy Storage|Updated:2026-06-29
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    • State of Health Estimation of On-Board Lithium-Ion Batteries Using Temporal Convolutional Network Optimized by Improved Self-Adaptive Honey Badger Algorithm

    • “A lithium-ion battery SOH estimation method considering battery capacity recovery was proposed, and its research progress in the field of battery management was introduced. The team established a data preprocessing system that integrates median absolute deviation and Savitzky Golay filtering, and explored the topic of improving the adaptive honey badger algorithm to optimize the time convolutional network. This provides a solution to the problem of traditional methods neglecting capacity recovery and insufficient feature effectiveness.”
    • DOI:10.12096/j.2096-4528.pgt.24068    

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    • Revised:2024-07-20,

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