Rapid lithium battery capacity degradation identification method and device
An identification method and a technology for identifying devices, which are applied to measuring devices, measuring electrical variables, and measuring electricity, can solve the problems of waste of test costs, impact of overall life analysis, and long time consumption, and achieve stable calculation results.
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[0060] In practice, lithium-ion battery capacity degradation data contains a lot of noise. These noises show the characteristics of local fluctuations in the degradation curve, but have no significant impact on the long-term degradation trend. Therefore, in order to ensure the robustness of data processing, it is necessary to perform smoothing and denoising preprocessing on capacity degraded data. In the present invention, the locally weighted scatter-point regression smoothing (LOWESS) method is used to process the capacity degradation data, and the long-term trend is retained while removing the local fluctuation in the degradation process. The specific implementation is as follows:
[0061] 1. Take a point x 1 As the center, determine a data with an interval length of f, which depends on q=fn, where q is the number of observations participating in local regression, f is the number of observations participating in local regression to the number of observations Proportion, ...
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[0101] The present invention uses the test data of Ningde Times New Energy Technology Co., Ltd. to verify the feasibility and effectiveness of the proposed lithium-ion battery life prediction method (note: the battery used in the test is a pouch battery specially used in the product design stage , which differ from the batteries used in the company's real products).
[0102] Lithium battery samples under 25°C test conditions are selected for analysis and verification. This method uses four samples for case analysis, including two diving samples and two normal samples. The numbers of the four samples are marked as follows:
[0103] Normal samples: N1, N2
[0104] Diving samples: D1, D2
[0105] The original degradation curves of the four battery samples are as Figure 5 Shown:
[0106] Both the diving recognition and labeling based on the characteristic angle and the diving recognition method based on the characteristic angle trend need to smooth and denoise the battery cap...
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