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

Battery remaining life prediction method and device, electronic device and storage medium

A life prediction and life expectancy technology, which is applied in the field of devices, electronic equipment and storage media, and lithium battery life prediction methods, can solve problems such as poor user experience, complexity, and inability to obtain more accurate conclusions from mechanism models, achieving fast processing speed, high precision effect

Inactive Publication Date: 2019-01-11
DONGGUAN UNIV OF TECH +1
View PDF0 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The existing lithium battery life prediction methods are mainly two categories: mechanism model and data-driven. Among them, the mechanism model is mainly to establish a mathematical model of system dynamics or degradation evolution mechanism. Commonly used models include empirical degradation model and lumped circuit model. , due to the existence of many unpredictable factors in the degradation process of lithium batteries, the mechanism model cannot obtain more accurate conclusions to a certain extent
The data-driven method mainly realizes prediction through lithium battery capacity, but the existing data-driven method is relatively complicated, especially for electronic products such as mobile phones, each prediction process will occupy a large amount of memory and CPU of consumers, resulting in poor user experience The problem

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
  • Battery remaining life prediction method and device, electronic device and storage medium
  • Battery remaining life prediction method and device, electronic device and storage medium
  • Battery remaining life prediction method and device, electronic device and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0051] Please refer to figure 1 Shown, a kind of lithium battery life prediction method, comprises the following steps:

[0052]110. Collect actual capacity information of the lithium battery at intervals of a preset period, where the actual capacity information constitutes a historical data set.

[0053] The actual capacity information of lithium batteries can be detected by hardware or software. Hardware such as lithium battery capacity monitors, software such as 91 assistants, 360 assistants and Aisi, etc. The actual capacity information of lithium batteries is the remaining capacity of lithium batteries. The loss during use, the longer it is used, the smaller its actual capacity. The preset period can be set according to the usage frequency or theoretical life of the lithium battery, which can be 5 days, 7 days, 10 days, 30 days, etc.

[0054] In a preferred embodiment of the present invention, the number of actual capacity information in the historical data set is m, wh...

Embodiment 2

[0084] Embodiment 2 discloses a lithium battery life prediction device corresponding to the above embodiment, which is the virtual device structure of the above embodiment, please refer to figure 2 shown, including:

[0085] The collection module 210 is used to collect the actual capacity information of the lithium battery at an interval of a preset period, and the actual capacity information constitutes a historical data set;

[0086] The first building module 220 is used to construct a prediction model through a multiple regression equation according to the historical data set, so as to obtain a predicted data set under the expected variable state of the historical data set under the assumption that the life of the lithium battery is not terminated, the predicted data set The interval between two adjacent prediction data within is the preset period;

[0087] The second construction module 230 is configured to construct a logistic regression model through the prediction dat...

Embodiment 3

[0109] image 3 A schematic structural diagram of an electronic device provided in Embodiment 3 of the present invention, such as image 3 As shown, the electronic device includes a processor 310, a memory 320, an input device 330, and an output device 340; the number of processors 310 in a computer device may be one or more, image 3 Take a processor 310 as an example; the processor 310, memory 320, input device 330 and output device 340 in the electronic device can be connected by bus or other methods, image 3 Take connection via bus as an example.

[0110] The memory 320, as a computer-readable storage medium, can be used to store software programs, computer-executable programs and modules, such as program instructions / modules corresponding to the lithium battery life prediction method in the embodiment of the present invention (for example, lithium battery life prediction device The collection module 210, the first building module 220 and the second building module 230 ...

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 discloses a battery remaining life prediction method, which comprises the following steps: collecting the actual capacity information of the lithium battery by an interval time of a preset period, wherein the actual capacity information constitutes a historical data set; constructing a prediction model according to the historical data set through a multiple regression equation to obtain a prediction data set in a state of a desired variable of the historical data set assuming that the life of the lithium battery is not terminated, wherein an interval time between two adjacent prediction data in the prediction data set is the preset period; constructing a logistic regression model through that prediction data set to predict the life of the lithium battery. The invention also discloses a lithium battery life prediction device, an electronic device and a computer-readable storage medium. The invention combines multiple linear regression and logical regression to predict thelife of the lithium battery, and improves the processing speed and the user experience.

Description

technical field [0001] The invention relates to the technical field of lithium battery performance detection, in particular to a lithium battery life prediction method, device, electronic equipment and storage medium. Background technique [0002] Lithium-ion batteries (referred to as lithium batteries) are widely used in aerospace, ships, vehicles, and consumer electronics such as mobile phones, notebooks, mobile power supplies, and cameras. The performance of lithium batteries directly affects the operation safety of products, the completion of tasks and the quality of life of consumers. In order to prolong the service life of lithium batteries, a lot of research has been carried out, such as new electrode and electrolyte materials, new lithium battery structures, and the evolution mechanism of lithium battery performance. [0003] For lithium battery users, if they can obtain the life of the lithium battery at any time, they can judge whether their corresponding needs ca...

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): G06F17/18
CPCG06F17/18
Inventor 邓君赖树明甄超孙德凤徐进
Owner DONGGUAN 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