HOLT-WINTERS BASED PREDICTION OF LITHIUM-ION BATTERY CAPACITY FADING

Wu Weili; Lu Shuangshuang; Li Lei

doi:10.19912/j.0254-0096.tynxb.2023-1550

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (1) : 309-318. DOI: 10.19912/j.0254-0096.tynxb.2023-1550

HOLT-WINTERS BASED PREDICTION OF LITHIUM-ION BATTERY CAPACITY FADING

Wu Weili^1,2, Lu Shuangshuang^1,2, Li Lei^1,2

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Abstract

Aiming at the problem of low accuracy and poor tracking effect of the current battery capacity long-term decline trend prediction method, a battery capacity prediction method based on sequence decomposition and cubic exponential smoothing is proposed, which realizes the effective tracking of the degradation trend in the rapid decline stage of battery capacity. For the battery capacity sequence with capacity recovery phenomenon, firstly, the adaptive white noise complete ensemble empirical mode decomposition （CEEMDAN） is used to decompose it into fluctuation component and trend component, and then Holt-Winters seasonal and linear models are built for each component to predict. Finally, the prediction results are superimposed to realize the capacity degradation trend prediction. The Holt-Winters non-seasonal model is directly built to predict the capacity sequence with weak capacity recovery. A variety of different battery degradation datasets are used to verify the performance of the algorithm. The results show that the proposed method has good robustness and the prediction accuracy is greatly improved, which provides a technical reference for the prediction of the degradation trend of lithium-ion battery capacity.

Key words

lithium-ion battery / capacity prediction / empirical mode decomposition / Holt-Winters

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Wu Weili, Lu Shuangshuang, Li Lei. HOLT-WINTERS BASED PREDICTION OF LITHIUM-ION BATTERY CAPACITY FADING[J]. Acta Energiae Solaris Sinica. 2025, 46(1): 309-318 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1550

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