Article: Predicting remaining lithium-ion battery life based on multi-cycle time series models Journal: International Journal of Information and Communication Technology (IJICT) 2025 Vol.26 No.1 pp.55 - 72 Abstract: We propose a novel deep learning-based model for predicting the remaining life of lithium-ion batteries. Existing methods merely model the remaining life's temporal changes, overlooking inherent time series periodicity and compromising prediction accuracy. Our model capitalises on multi-cycle features in time series analysis, using well-designed 2D temporal blocks to handle uncertainties in battery remaining useful life changes. It extracts complex patterns within charge and discharge cycles, achieving high-precision predictions of future battery states. On multiple common battery datasets, it surpasses existing methods in accuracy and robustness, validating its effectiveness. Inderscience Publishers - linking academia, business and industry through research

Title: Predicting remaining lithium-ion battery life based on multi-cycle time series models

Authors: Peide Xu; Jie Li

Addresses: School of Power Engineering, Fujian Polytechnic of Water Conservancy and Electric Power, Yongan, Fujian, 366000, China ' School of Electric Power, South China University of Technology, Guangdong, Guangzhou, 510641, China

Abstract: We propose a novel deep learning-based model for predicting the remaining life of lithium-ion batteries. Existing methods merely model the remaining life's temporal changes, overlooking inherent time series periodicity and compromising prediction accuracy. Our model capitalises on multi-cycle features in time series analysis, using well-designed 2D temporal blocks to handle uncertainties in battery remaining useful life changes. It extracts complex patterns within charge and discharge cycles, achieving high-precision predictions of future battery states. On multiple common battery datasets, it surpasses existing methods in accuracy and robustness, validating its effectiveness.

Keywords: lithium-ion battery; remaining useful life prediction; multi-cycle time series.

DOI: 10.1504/IJICT.2025.144016

International Journal of Information and Communication Technology, 2025 Vol.26 No.1, pp.55 - 72

Received: 24 Sep 2024
Accepted: 25 Nov 2024
Published online: 20 Jan 2025 *

Title: Predicting remaining lithium-ion battery life based on multi-cycle time series models

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