Chuanyu Bie

Chuanyu Bie


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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31 October 2025 in Rare Metals
Verified
Journal Article
Closed access
PDF file
XBXi‐Yan Bao
Xi‐Yan Bao
YZYu‐Tong Zhang
Yu‐Tong Zhang
JPJiang‐Tao Pan
Jiang‐Tao Pan
JLJing‐Yu Li
Jing‐Yu Li
LLLin Lv
Lin Lv
HWHouzhao Wan
Houzhao Wan

2 December 2022 in Energies
Verified
Journal Article
Open access
PDF file
HLHongling Liu
Hongling Liu
CBChuanyu Bie
Chuanyu Bie
FLFan Luo
Fan Luo
JKjianqiang Kang
jianqiang Kang
YZYuping Zhang
Yuping Zhang
In order to solve the problems of long-time consumption and high energy consumption in existing capacity detection methods of retired Ni-MH batteries, a fast and reliable capacity prediction method for retired Ni-MH batteries by multi-parameter driven analysis was proposed in this paper. This method mainly obtains several parameters through short-time measurement and pulse rapid nondestructive testing. Then, Pearson correlation coefficient and KS-test were used to analyze the correlation between the two parameters and verify the same distribution. Finally, SVR was used to predict the battery discharge capacity. The results show that the volume expansion thickness difference Δd, AC internal resistance R, terminal voltage U of the battery, charge and discharge polarization internal resistance Rf1 and Rf2 and pulse charging power P2 of the battery are strongly negatively correlated with the discharge capacity, and these characteristic parameters can effectively and reliably reflect the internal structural characteristics of the battery. Additionally, the mean relative error of the established capacity model is 5.87%, and the lowest error is 1.32%. The prediction effect is good, which provides a certain reference value for the subsequent consistent sorting method.