A method for rapid prediction of cycle life of lithium-ion batteries

Abstract

The invention relates to a method for fast predicting a cycle life of a lithium ion battery. The method for predicting a cycle life of a lithium ion battery comprises steps of performing a short period circulation performance test of different cycle times on a battery to be evaluated, recording different cycle times and a corresponding capacity conservation rate, performing disassembling on a battery in an empty state after various cycle times, scrapping off electrode powder on a negative electrode, using an XRD inner calibration method to test a graphitization degree of a graphite cathode material, performing fitting calculation according to three kinds of test data including cycle times, a capacity conservation rate and the graphitization degree and thus performing prediction on the cycle time of the battery. Compared with a routine cycle life test method, the method for fast predicting the cycle life of the lithium ion battery is easy to implement, greatly shortens a test cycle of the cycle life, and, compared with a pure theoretic calculation and experience model prediction, is more universal and more consistent with a practical test result.

Description

technical field [0001] The invention relates to the technical field of battery testing, in particular to a method capable of rapidly predicting the cycle life of lithium-ion batteries. Background technique [0002] Due to the advantages of high energy density, excellent rate and power performance, long cycle life, safety and environmental protection, lithium-ion batteries are widely used as important chemical power sources in our daily life. In addition to long-term use in traditional digital products such as mobile phones and portable computers, the application range of lithium-ion batteries has gradually expanded to high-tech fields such as electric vehicles, aerospace and energy storage. [0003] As a commercial product, lithium-ion batteries must pass various strict performance tests before they can be put into use, including high and low temperature performance tests, rate performance, long-term cycle performance, and safety performance tests. Long-term cycle performan...

AI Technical Summary

Problems solved by technology

These reported cycle life prediction methods have their own limitations. The first method only considers the relationship between electrolyte consumption and cycle capacity fading, ignoring the characteristics of the electrode material itself, especially the negative electrode material’s impact on the cycle life of lithium-ion batteries. The impact of life, resulting in a large deviation from the actual test results; the second method is based on the calculation structure of the theoretical model to predict battery life, the calculation is complex and not universal

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