US 11,959,970 B2 · Method and device for capacity degradation prediction of lithium-ion battery

Abstract

One or more embodiments of the present specification provide a method and device for capacity degradation prediction of a lithium-ion battery. The method comprises the following steps: 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; inputting the respective frequency signals into a pre-constructed capacity prediction model to obtain capacity prediction results corresponding to the respective frequency signals; selecting capacity prediction result that satisfies a predetermined relevance condition corresponding to the respective frequency signals; and reconstructing the finally predicted battery discharge capacity according to the capacity prediction result that satisfies the predetermined relevance condition.

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:
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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.

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Method and device for capacity degradation prediction of lithium-ion battery

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Method and device for capacity degradation prediction of lithium-ion battery

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Abstract

Claims4