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Joint Estimation of State of Charge and Capacity throughout the Full Service Life Cycle for Li-Ion Batteries Kunming University of Science and Technology
- Format:
- Book
- Conference/Event
- Author/Creator:
- Liu, Weiqiang, author.
- Conference Name:
- SAE 2025 International Conference on Battery Safety and Reliability (2025-10-23 : Shanghai, China)
- Language:
- English
- Physical Description:
- 1 online resource cm
- Place of Publication:
- Warrendale, PA SAE International 2026
- Summary:
- Accurate SOC and capacity estimation is essential for the safe operation of lithium-ion batteries. However, model parameters drift due to temperature variations and aging. This study proposes a migration-model-based method for joint estimation of SOC and capacity over a wide range of temperatures and degradation levels. The WSPF algorithm identifies migration factors in real time and applies them to estimate SOC and capacity under nonlinear, non-Gaussian conditions. Validation under various test conditions demonstrates clear advantages. Compared to EKF, the migration-model-based algorithm reduces the maximum RMSE of SOC estimation to 0.55%. For capacity estimation, it achieves a maximum RMSE of 1.15%. The estimation accuracy remains high throughout temperature changes and aging, highlighting the robustness and applicability of the proposed method for real-world battery management systems
- Notes:
- Vendor supplied data
- Publisher Number:
- 2026-01-7021
- Access Restriction:
- Restricted for use by site license
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