期刊论文

Xia, XY

英文

Electronics

2079-9292

2025

14

7

1462-

10.3390/electronics14071462

Conceptualization, T.X. and J.Y.; methodology, T.X.; software, Y.G.; formal analysis, Y.G.; investigation, X.X.; resources, J.T.; writing—original draft preparation, T.X.; writing—review and editing, T.X. and J.Y.; visualization, L.W.; supervision, X.X.; project administration, X.X.; funding acquisition, X.X.; All authors have read and agreed to the published version of the manuscript. This study was supported by the Natural Science Foundation of Hunan Province of China, grant number 2025JJ50231.

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Accurate prediction of the State of Charge (SOC) of lithium-ion batteries is the foundation for the stable and efficient operation of battery management systems. This paper proposes a lithium-ion battery SOC estimation method based on the Dung Beetle Optimizer (DBO), optimizing the second-order Kalman filter algorithm (DBO-DKF). Leveraging the DBO's fast convergence speed and strong global search capability, this method optimizes the Kalman filter algorithm in the parameter identification stage and the extended Kalman filter algorithm in the SOC estimation stage to address the issue of insuffi...