An Online Lithium-ion Battery Capacity Estimation Method Based on Support Vector Regression

Abstract

The invention relates to an online estimation method of lithium ion battery capacity based on support vector regression. The method comprises the following steps: S1. Test the cycle life of the lithium-ion battery to obtain the corresponding DC equivalent internal resistance spectrum; S2. Extract potential health factors that can reflect the performance degradation of the lithium-ion battery based on the DC equivalent internal resistance spectrum. It conducts correlation analysis; S3. Constructs a capacity estimation model based on the support vector regression algorithm; S4. Obtains the current charging data of the battery to be estimated and the charging equivalent internal resistance curve; S5. According to the established capacity estimation model, the extracted health The factor parameter value determines the current capacity of the battery. The method solves the problem of online estimation of the capacity of the lithium-ion battery under different cycle working conditions, and has high estimation accuracy and strong adaptability.

Description

technical field [0001] This application relates to the field of battery management and battery state analysis, in particular to an online estimation method of lithium-ion battery capacity based on support vector regression. Background technique [0002] Lithium-ion batteries are widely used in the field of electric vehicles due to their high energy density, long cycle life, and high safety. As the number of cycles of lithium-ion batteries increases during use, their external characteristics will deteriorate in all aspects, specifically manifested as a decrease in effective capacity and an increase in the internal resistance of charge and discharge. [0003] Lithium-ion battery capacity estimation is one of the core issues of battery management. It is of great significance in judging the current deterioration state of the battery, estimating the remaining service life of the battery, and avoiding premature battery failure. However, in practical applications, the capacity of ...

AI Technical Summary

Problems solved by technology

However, in practical applications, the capacity of the battery is generally obtained through the offline test method of fully charging and discharging the battery, and it is impossible to update the real-time capacity change of the battery.

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