Pang, Xiaoqiong https://orcid.org/0000-0002-7968-3582
Zhang, Xiaotong https://orcid.org/0009-0000-2403-2603
Guo, Ziyao
Jia, Jianfang https://orcid.org/0000-0001-6117-6649
Wen, Jie https://orcid.org/0000-0003-0302-4123
Shi, Yuanhao
Zeng, Jianchao
Funding for this research was provided by:
Graduate Education Innovation Program Project (2024AL20)
Natural Science Foundation of Shanxi Province (202403021211088)
Article Title: TFDDA: a time-frequency deep domain adaptation method for cross-domain state of health estimation of lithium-ion batteries
Journal Title: Engineering Research Express
Article Type: paper
Copyright Information: © 2026 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.
Publication dates
Date Received: 2025-10-31
Date Accepted: 2026-02-09
Online publication date: 2026-02-20