报告详情
A comparison of charging voltage image coding methods for lithium-ion battery state of health estimation
编号：173
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更新：2024-10-23 10:02:36 浏览：65次
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摘要
Accurate estimation of the state of health (SOH) of lithium-ion batteries is a key initiative to guarantee their service reliability in complex operating environments. Using one-dimensional time series data to transform two-dimensional image for battery degradation feature extraction can improve the accuracy of battery SOH evaluation, reduce the complexity of evaluation model and the demand for the amount of test data. Although existing studies have attempted to apply image coding techniques to enhance the degradation features of original data, the advantages and disadvantages of different image coding methods have not been systematically compared. Therefore, in this work, five commonly used image coding methods including recurrence plots, Gramian angular summation field, Gramian angular difference field, relative position matrix, and time series data folding are selected and comprehensively compared. Firstly, the original one-dimensional voltage signal is encoded into a two-dimensional image, which is then inputted into the CNN-GRU-based SOH prediction model, and finally the future battery SOH value is output. The experimental results show that there are differences in the applicable stages and conditions of different coding methods, so they need to be adapted with specific application scenarios, which is the next research direction.
关键词
State of health estimation, lithium-ion battery, charging voltage image coding
报告人
WangHang
Dr. Anhui University稿件作者
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重要日期
-
会议日期
10月31日
2024
至11月03日
2024
-
09月30日 2024
初稿截稿日期
-
11月12日 2024
注册截止日期
主办单位
Anhui University
Xi’an Jiaotong University
Harbin Institute of Technology
IEEE Instrumentation & Measurement Society
Xi’an Jiaotong University
Harbin Institute of Technology
IEEE Instrumentation & Measurement Society
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- ic******@163.com
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