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

Method for predicting health state of lithium battery based on SREKF

A technology of health status and prediction method, applied in the direction of measuring electricity, measuring devices, measuring electrical variables, etc., can solve the problems of large estimation error, low precision, and poor robustness.

Active Publication Date: 2019-07-26
XIAN UNIV OF TECH
View PDF12 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a method for predicting the state of health of lithium batteries based on SREKF, which solves the problems of large estimation errors, low precision and poor robustness when the traditional Kalman filter algorithm (EKF) estimates the internal resistance of lithium batteries question

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
  • Method for predicting health state of lithium battery based on SREKF
  • Method for predicting health state of lithium battery based on SREKF
  • Method for predicting health state of lithium battery based on SREKF

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0065] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0066] The method for predicting the state of health of lithium batteries based on SREKF of the present invention, the specific operation process includes the following steps:

[0067] Step 1, establish a mathematical model of the state parameters of the lithium battery, and obtain the state equation of the ohmic internal resistance of the lithium battery system and the observation equation of the ohmic internal resistance;

[0068] The specific process of step 1 is as follows:

[0069] like figure 1 As shown, U c is the terminal voltage of the lithium battery; U oc is the open circuit voltage of the battery; R 0 Is the ohmic internal resistance of the lithium battery; I is the working current of the battery; R s 、C s Respectively, the electrochemical polarization internal resistance and polarization capacitance of the battery represent...

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 method for predicting the health state of a lithium battery based on SREKF. The method comprises the following steps: firstly, establishing a mathematical model of a state parameter of the lithium battery, and obtaining a state equation of ohmic internal resistance and an observation equation of the ohmic internal resistance; secondly, identifying an offline parameter of alithium battery model, and obtaining an initial value of the SREKF; meanwhile, obtaining an output sequence of a predicted end voltage Uc; then improving EKF to obtain the SREKF; and finally, inputting the measured voltage, current and margin sequence of the lithium battery into the SREKF to no update the state equation and the observation equation, updating an optimal value of the current stateof the lithium battery system of the SREKF by using the output sequence of the predicted end voltage Uc and a measured end voltage sequence, iterating the SREKF according to the number of experiment measured values to obtain a predicted value sequence of the ohmic internal resistance, that is, the quantity of state of the health state of the lithium battery. By adoption of the method disclosed bythe invention, when the internal resistance of the lithium battery is estimated by the traditional EKF, the problems of large estimation errors, low precision and poor robustness are solved.

Description

technical field [0001] The invention belongs to the field of battery management systems for electric vehicles, and in particular relates to a method for predicting the health state of lithium batteries based on SREKF. Background technique [0002] Lithium-ion batteries have the advantages of high discharge platform, long cycle life, environmental protection and safety, and have become an important source of power for electric vehicles. Battery state estimation is not only the core and basis of management, but also provides data basis for vehicle energy management. The internal state of the battery mainly includes state of charge (SOC) and state of health (SOH). In order to optimize system operation, it is crucial to accurately estimate the SOC and SOH of the system. In particular, the accurate estimation of battery SOH can fully and rationally use the battery and avoid the inconvenience caused by sudden battery failure, which is of great significance for battery management....

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): G01R31/367G01R31/392G01R31/389
CPCG01R31/367G01R31/389G01R31/392
Inventor 张志禹张凤珠马文涛
Owner XIAN UNIV OF TECH
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