重庆大学秦岩-- Y. Qin, C. Yuen* (IEEE Fellow), X. Yin, H. Biao (IEEE Fellow). A transferable multi-stage model with cycling discrepancy learning for Lithium-ion battery state of health estimation. IEEE Transactions on Industrial Informatics. vol. 19, no. 2, pp. 1933-1946, 2023.

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学术成果（期刊*代表通讯作者）

Y. Qin, C. Yuen* (IEEE Fellow), X. Yin, H. Biao (IEEE Fellow). A transferable multi-stage model with cycling discrepancy learning for Lithium-ion battery state of health estimation. IEEE Transactions on Industrial Informatics. vol. 19, no. 2, pp. 1933-1946, 2023.

发布时间：2023-03-23 点击次数：

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上一条：Y. Qin, C. Yuen* (IEEE Fellow), Y.M. Shao, B. Qin, and X. Li. Slow-varying dynamics-assisted temporal capsule network for machinery remaining useful life estimation. IEEE Transaction on Cybernetics. vol. 53, no. 1, pp. 592-606, 2023. 下一条：C. Gamanayake, Y. Qin*, C. Yuen (IEEE Fellow), and et al. A hybrid deep learning model based remaining useful life estimation for reed relay with degradation pattern clustering. IEEE Transactions on Industrial Informatics. (Early Access), pp. 1-13, DOI: 10.1109/TII.2022.3210250, 2022.

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