A method for estimating the state of health of lithium-ion batteries applied to battery management systems

Abstract

A lithium-ion battery health state estimation method applied to a battery management system relates to the field of lithium-ion battery health state estimation. The present invention aims to solve the problem that existing methods for estimating the state of health of a battery have difficulties. The invention can provide new degradation features for researchers to evaluate battery performance degradation. This method obtains the internal transfer function of the battery by establishing a lithium-ion battery model, and obtains the battery performance degradation characteristics based on the identification of the internal parameters of the transfer function based on the HPPC test of the battery. The correlation between the model parameters and the battery capacity is greater than 0.8 through the Pearson correlation coefficient analysis. , which verifies that the model parameters extracted by the proposed method can be directly applied to the battery performance degradation characterization. Finally, the battery parameters and battery SOH are mapped through the RVM model, and the SOH estimation model is obtained, and a good estimation effect is achieved.

Description

technical field [0001] The invention belongs to the field of lithium ion battery health state estimation. Background technique [0002] As the lithium-ion battery continues to cycle through charge and discharge, complex and irreversible electrochemical reactions such as solid electrolyte film thickening and lithium dendrite precipitation occur inside the lithium-ion battery, resulting in performance degradation of the lithium-ion battery. [0003] Lithium-ion battery health state estimation methods based on parameters such as capacity and internal resistance have high estimation accuracy, but in practical applications, these two types of parameters are difficult to measure online. [0004] The state of health estimation method based on monitorable parameters has higher requirements on the extraction conditions of degradation features (such as battery voltage, state of charge, etc. when extracting features); at the same time, it will bring additional computing requirements to...

AI Technical Summary

Problems solved by technology

[0005] The present invention aims to solve the problem that existing methods for estimating the state of health of batteries are difficult, and now provides a method for estimating the state of health of a lithium-ion battery applied to a battery management system

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