Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Lithium ion battery charging curve reconstruction and state estimation method based on artificial intelligence

A lithium-ion battery, charging curve technology, applied in the field of lithium-ion battery state estimation, to achieve the effect of improving accuracy

Active Publication Date: 2021-02-19
BEIJING INSTITUTE OF TECHNOLOGYGY
View PDF3 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in practical applications, the battery is often not fully charged or fully discharged, and the battery management system can only collect part of the charging curve.

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
  • Lithium ion battery charging curve reconstruction and state estimation method based on artificial intelligence
  • Lithium ion battery charging curve reconstruction and state estimation method based on artificial intelligence
  • Lithium ion battery charging curve reconstruction and state estimation method based on artificial intelligence

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0019] The above is only an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0020] The charging curve reconstruction and state estimation method provided by the present invention is as attached figure 1 As shown, it specifically includes the following parts:

[0021] Step 1. Obtain the complete charging curve of the battery as training data, specifically including: using common charging schemes such as constant current charging, constant current and constant voltage charging, multi-stage constant current charging, and pulse charging. Through battery testing, battery management system sampling and other methods, the daily charging curves of batteries in different aging states are obtained, including battery charging current, voltage, temperature and other...

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 provides a lithium ion battery charging curve reconstruction method based on artificial intelligence, so that estimation of multiple states of a battery can be achieved. According to themethod, charging segment data is used as input, a complete charging curve is reconstructed by using a deep learning method, and then multiple states of the battery, including the maximum capacity, the maximum energy, the state of charge, the energy state, the power state, the capacity increment curve and the like of the battery, can be extracted from the complete charging curve. The battery stateestimation method provided by the invention can be self-adaptively updated along with the change of the working state of the battery.

Description

technical field [0001] The invention relates to the field of battery systems, in particular to state estimation of lithium ion batteries. Background technique [0002] During the actual operation of the lithium-ion battery, since the battery management system can only collect fragments of the battery's voltage, current, temperature and other signals, the internal state of the battery cannot be directly measured, so its state can only be estimated based on the measured signal. Existing state estimation methods can only focus on certain specific states, and assume that other states are known, so there is a big limitation in the globality of the estimation. For example, the estimation of battery capacity often only focuses on the establishment of the relationship between capacity and charging curve characteristics, while ignoring the estimation of other states. In fact, the battery charging curve (the relationship between the charging voltage and the charged power) reflects a ...

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
IPC IPC(8): G01R31/367G01R31/378G01R31/392
CPCG01R31/367G01R31/378G01R31/392
Inventor 熊瑞田金鹏段砚州
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com