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

Automobile battery capacity prediction method, automobile battery life prediction method, automobile battery life prediction device and storage medium

A technology for battery capacity and car battery, which is applied in measuring devices, measuring electrical variables, measuring electricity, etc., and can solve problems such as low battery capacity prediction accuracy.

Pending Publication Date: 2021-09-10
GAC MITSUBISHI MOTORS
View PDF7 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The present invention provides an automobile battery capacity prediction method, life prediction method, device and storage medium to solve the problem of low prediction accuracy of the existing automobile battery capacity

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
  • Automobile battery capacity prediction method, automobile battery life prediction method, automobile battery life prediction device and storage medium
  • Automobile battery capacity prediction method, automobile battery life prediction method, automobile battery life prediction device and storage medium
  • Automobile battery capacity prediction method, automobile battery life prediction method, automobile battery life prediction device and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0072] like figure 1 As shown, the present embodiment provides a method for predicting the capacity of an automobile battery, including:

[0073] S1: Obtain the historical operation data sent to the remote monitoring platform by the vehicle to be tested;

[0074] S2: Use historical operating data to classify the vehicle to be tested;

[0075] S3: Obtain the theoretical value of the battery capacity of the vehicle under test based on the ampere-hour integration method;

[0076] S4: Input the theoretical value of the battery capacity of the vehicle to be tested into the pre-trained battery capacity estimation model corresponding to its use classification to obtain the predicted value of the battery capacity.

[0077] A method for predicting the capacity of an automobile battery provided by this embodiment will be described in detail below in conjunction with an example.

[0078] Take a brand model A as an example to introduce: First, select 2000 cars of model A as the researc...

Embodiment 2

[0104] Such as Figure 5 As shown, the present embodiment provides a method for predicting the life of an automobile battery (SOH), including:

[0105] B1: Using the month as the time unit, use the above-mentioned automobile battery capacity prediction method to predict the battery capacity prediction value of the vehicle under test for multiple consecutive months;

[0106] B2: Use the 3σ method to clean the battery capacity prediction value, and use the previous battery capacity prediction value to overwrite the abnormal value;

[0107] B3: Take the month as the abscissa, and the predicted value of the battery capacity of the vehicle to be tested is the ordinate, and use the least square method to perform polynomial fitting to obtain the battery capacity decay curve;

[0108] B4: Battery life prediction based on battery capacity decay curve.

[0109] In order to further understand the method for predicting the service life (SOH) of an automobile battery provided by this emb...

Embodiment 3

[0115] This embodiment provides a vehicle battery capacity prediction device, including:

[0116] The data acquisition module is used to acquire the historical operation data sent to the remote monitoring platform by the vehicle to be tested;

[0117] The use classification module is used to classify the use of the vehicle to be tested based on historical operating data;

[0118] The theoretical value acquisition module is used to obtain the theoretical value of the battery capacity of the vehicle under test based on the ampere-hour integration method;

[0119] The battery capacity prediction module is used to input the theoretical value of the battery capacity of the vehicle to be tested into the pre-trained battery capacity estimation model corresponding to its use classification, to obtain the predicted value of the battery capacity.

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 an automobile battery capacity prediction method, an automobile battery life prediction method, an automobile battery life prediction device and a storage medium. The method comprises the following steps: acquiring historical operation data sent to a remote monitoring platform by a to-be-detected vehicle; performing purpose classification on the to-be-detected vehicle based on the historical operation data; obtaining a battery capacity theoretical value of the to-be-detected vehicle based on an ampere-hour integral method; and inputting the battery capacity theoretical value of the to-be-detected vehicle into a pre-trained battery capacity estimation model corresponding to the purpose classification of the to-be-detected vehicle to obtain a battery capacity predicted value. According to the scheme, under the condition of a small amount of electric vehicle battery experiment data, the battery capacities of the electric vehicles in the market can be predicted according to the purposes based on the new energy remote monitoring data, the cost is saved, and the prediction precision is improved.

Description

technical field [0001] The present invention relates to the technical field of battery capacity prediction, in particular to a method for predicting the capacity of an automobile battery, a life expectancy method, a device and a storage medium. Background technique [0002] As the power source of electric vehicles, power batteries have a capacity decay that is closely related to factors such as vehicle usage characteristics and the external environment. It is difficult to directly calculate the remaining capacity of power batteries through a simple mathematical model. [0003] The traditional ampere-hour integration method calculates the remaining capacity of the power battery by calculating the battery capacity change and SOC change during the charging process, but this method is affected by factors such as the data sampling frequency of the remote monitoring platform, current sampling accuracy, and SOC self-correction. influence, resulting in a large error between the calc...

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 Applications(China)
IPC IPC(8): G01R31/3832G01R31/392
CPCG01R31/3832G01R31/392
Inventor 伍兴罗志雄杨超余大中张鸿展姚小海
Owner GAC MITSUBISHI MOTORS
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