Patent ID: 11959970
Assignee: BEIJING INSTITUTE OF TECHNOLOGY
Field: Measurement (Instruments)
Classification: CPC G  Y | IPC G

Claim 0:
1. A method for capacity degradation prediction of a lithium-ion battery, comprising:
acquiring an original battery discharge capacity;
decomposing the original battery discharge capacity through a predetermined mode decomposition method to obtain battery discharge capacities composed of a plurality of different frequency signals, comprising:
decomposing an original battery discharge capacity S(t) through a CEEMDAN mode decomposition algorithm to obtain a battery discharge capacity composed of a plurality of high-frequency signals and a low-frequency signal, the battery discharge capacity being expressed as:

CEEMDAN(S(t))=Σi=1kdi(t)+rk(t)   (1)

in which k is a number of decomposed IMF components; di(t) is a high-frequency signal corresponding to the ith IMF component and rk(t) is a low-frequency signal corresponding to a residual signal;
inputting the respective frequency signals into a pre-constructed capacity prediction model to obtain capacity prediction results corresponding to the respective frequency signals;
selecting the capacity prediction result that satisfies a predetermined relevance condition from the capacity prediction results corresponding to the respective frequency signals, comprising:
calculating a correlation coefficient between each frequency signal and the original battery discharge capacity respectively; selecting the frequency signal whose correlation coefficient is greater than or equal to a preset correlation threshold; and taking the capacity prediction result corresponding to the selected frequency signal as a capacity prediction result that satisfies the predetermined relevance condition, wherein the correlation coefficient is expressed as:, ρ
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in which pw is a correlation coefficient between a wth frequency signal and the original battery discharge capacity; dw(t) is a frequency signal corresponding to the wth IMF component; dw(t)is a mean of dw(t); S(t) is the original battery discharge capacity; S(t)is a mean of S(t); and n is a total battery charge-discharge cycle time; and
reconstructing the predicted battery discharge capacity according to the capacity prediction result that satisfies the predetermined relevance condition, comprising: reconstructing the predicted battery discharge capacity according to the capacity prediction result that satisfies the predetermined relevance condition and the capacity prediction result corresponding to the low-frequency signal, the battery discharge capacity being expressed as:

S′(t)=Σm=1Nd′m(t)+rk′(t)   (16)

in which S′(t) is the reconstructed battery discharge capacity; N is a number of capacity prediction results that satisfy the predetermined relevance condition; d′m(t) is the mth capacity prediction result that satisfies the predetermined relevance condition; and r′k(t) is the capacity prediction result corresponding to the low-frequency signal.