Fused HI equivalence lithium ion battery degradation prediction method based on principal component analysis

Abstract

The invention provides a fused HI (Health Index) equivalence lithium ion battery degradation prediction method based on principal component analysis (PCA). GRA (Grey Relational Analysis) is performed on a discharge cut-off voltage as a benchmark HI and the capacity directly characterizing the degradation parameter, and a GLM (Generalized Linear Model) is used to carry out transform modeling. If the relevancy between the transform result and the capacity is larger than 0.7, it can be judged that it is reasonable to use the discharge cut-off voltage as an HI. Then, a variety of indirect HIs are constructed according to the measured parameters of a battery, and the HIs are fused through PCA to get a fused HI. The relation between the fused HI and the discharge cut-off voltage is analyzed using the GLM. If the relevance of the GLM is larger than 0.7 and RMSE is smaller than 0.004, it can be judged that the error is small, the precision of fitting is high, and the fused HI can be used as a substitute parameter of the discharge cut-off voltage. Moreover, GLM can be used to get the relation between the HI and the direct degradation parameter effectively to determine the failure threshold and increase the relevancy between sequences by more than 50%. The constructed fused HI can be used to complete indirect degradation condition prediction and predict the degradation condition of a lithium ion battery based on direct measurement data.

Description

technical field [0001] The invention relates to a fusion HI equivalence degradation prediction method based on principal component analysis, and belongs to the technical field of fusion HI equivalence degradation prediction methods. Background technique [0002] As the lithium-ion battery continues to charge and discharge cycles, there are complex irreversible electrochemical reactions such as electrolyte oxidation and lithium ion deactivation inside the lithium-ion battery, resulting in the performance degradation of the lithium-ion battery, one of which is specifically manifested as the lithium-ion battery. A constant decrease in the maximum capacity available. The lithium-ion battery capacity estimation method based on the data-driven method can solve the problem that it is difficult to construct a physical model of lithium-ion battery capacity degradation under different working environment conditions. The performance degradation of lithium-ion batteries can be intuitiv...

AI Technical Summary

Problems solved by technology

Lithium-ion battery capacity estimation method based on data-driven method can solve the problem that it is difficult to construct a physical model of lithium-ion battery capacity degradation under different working environment conditions

The performance degradation of lithium-ion batteries can be intuitively represented by the capacity, but because the capacity is difficult to accurately measure in practical applications, the accuracy of the traditional ampere-hour integral estimation method is greatly affected by the current sampling accuracy and the initial value of the integral, so it is necessary to use available external measurement parameters , such as temperature, voltage, current, etc., to construct the HI that characterizes the capacity degradation of lithium-ion batteries, indirectly estimate the capacity degradation of lithium-ion batteries, and then characterize the degree of performance degradation of lithium-ion batteries

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