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

A support vector regression and lithium-ion battery technology, applied in the direction of measuring electrical variables, measuring electricity, measuring devices, etc., can solve the problem of unable to update the real-time capacity change of the battery, and achieve high-dimensional problems, low computational complexity, and low generalization the effect of the error

Active Publication Date: 2021-08-17
SUN YAT SEN UNIV
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • An Online Lithium-ion Battery Capacity Estimation Method Based on Support Vector Regression
  • An Online Lithium-ion Battery Capacity Estimation Method Based on Support Vector Regression
  • An Online Lithium-ion Battery Capacity Estimation Method Based on Support Vector Regression

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0035] A method for online estimation of lithium-ion battery capacity based on support vector regression provided by the present invention, the overall flow chart is as follows figure 1 shown. According to an embodiment of the present invention, it specifically includes the following steps:

[0036] S1. The cycle life test is carried out on the lithium-ion battery, and the corresponding DC equivalent internal resistance spectrum is obtained.

[0037] During the cycle life test, it is necessary to control the charge and discharge rate, discharge interval, discharge depth and temperature conditions, and carry out uninterrupted cycle charge and discharge of the battery. For samples of the same type of lithium-ion battery under different working conditions, the charge-discharge rate is set to 0.5C, 1C; the discharge depth is set to 0.30, 0.60; ) and the lower segment (with an average SOC of 30%); the temperature condition was set to 40°C. The specific experimental conditions ar...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

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 ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/367G01R31/388
CPCG01R31/367G01R31/388
Inventor 谭晓军谭雨晴范玉千
Owner SUN YAT SEN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap