Feature Selection and Model Fusion for Lithium-Ion Battery Pack SOC Prediction

Wenqiang Yang, Chong Li, Qinglin Miao, Yonggang Chen and Fuquan Nie ()
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Wenqiang Yang: School of Mechanical and Electrical Engineering, Henan Institute of Science and Technology, Xinxiang 453003, China
Chong Li: School of Mechanical and Electrical Engineering, Henan Institute of Science and Technology, Xinxiang 453003, China
Qinglin Miao: School of Mechanical and Electrical Engineering, Henan Institute of Science and Technology, Xinxiang 453003, China
Yonggang Chen: School of Mathematics and Statistics, Xinyang Normal University, Xinyang 464000, China
Fuquan Nie: School of Mechanical and Electrical Engineering, Henan Institute of Science and Technology, Xinxiang 453003, China

Energies, 2025, vol. 18, issue 20, 1-27

Abstract: Accurate prediction of the state of charge (SOC) of a battery pack is essential to improve the operational efficiency and safety of energy storage systems. In this paper, we propose a novel lithium-ion battery (Lib) pack SOC prediction framework that combines redundant control correlation downscaling with Adaptive Error Variation Weighting Mechanism (AVM) fusion mechanisms. By integrating redundancy feature selection based on correlation analysis with global sensitivity analysis, the dimensionality of the input features was reduced by 81.25%. The AVM merges BiGRU’s ability to model short-term dynamics with Informer’s ability to capture long-term dependencies. This approach allows for complementary information exchange between multiple models. Experimental results indicate that on both monthly and quarterly slice datasets, the RMSE and MAE of the fusion model are significantly lower than those of the single model. In particular, the proposed model shows higher robustness and generalization ability in seasonal generalization tests. Its performance is significantly better than the traditional linear and classical filtering methods. The method provides reliable technical support for accurate estimation of SOC in battery management systems under complex environmental conditions.

Keywords: state of charge; lithium-ion battery pack; redundant control; correlation analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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