A lithium battery capacity and life prediction method based on generalized degradation model and multi-scale analysis

Abstract

The invention puts forward a lithium battery capacity and service life prediction method based on a generalized degradation model and multiscale analysis. The method comprises the following steps of: firstly, carrying out phase space reconstruction on historical capacity degradation data, utilizing reconstructed data to fit the generalized degradation model, obtaining a model parameter, and fitting a root-mean-square error; secondly, in multiple scales, carrying out forward estimation on a future capacity, and obtaining a forward prediction result through weighted integration; thirdly, adding a prediction result into a known sequence, and carrying out forward iterated prediction; and finally, judging whether a multi-step prediction result achieves a failure threshold value or not, and calculating remaining service life. By use of the generalized degradation model which is put forward by the invention, a complex combined degradation rule can be fit, and the model has the advantages of high universality, wide applicable range and small fitting error. On the basis of phase space reconstruction, multiscale prediction is carried out, a prediction result is obtained through the weighted integration, and the prediction result is unlikely to interfere by noise and is high in accuracy.

Description

technical field [0001] The invention relates to the technical field of lithium battery health management, in particular to a lithium battery capacity and remaining service life prediction method based on a generalized degradation model and multi-scale analysis. Background technique [0002] Lithium-ion battery is a new generation of green high-energy rechargeable battery. It has outstanding advantages such as high voltage, high energy density, good cycle performance, small self-discharge, and no memory effect. Even after a long period of discharge, it can also maintain a superior temperature. characteristics, good leak-proof performance, stable working voltage, and long working life, so it is widely used in aerospace, marine, automobile and consumer electronics products. [0003] During the long-term use of lithium-ion, its performance will gradually degrade and eventually fail completely. Performance degradation is caused by the gradual deterioration of the physical and ch...

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Problems solved by technology

[0005] The technical problem to be solved by the present invention is: the existing lithium battery prediction method based on the degradation evolution model needs to assume in advance that the battery to be predicted follows a certain specific degradation mode, and a model can only be applied to similar batteries with the same degradation law. The versatility is poor, and there is no dynamic adjustment ability in different degradation stages, and the accuracy of prediction results is poor

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