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Battery life prediction method, battery data server and battery data processing system

A battery data and battery life technology, applied in the direction of electrical digital data processing, database management system, special data processing applications, etc., can solve the problems of inconsistent battery life, low accuracy of battery life prediction, and failure to reflect battery health status, etc., to achieve High accuracy, the effect of improving accuracy

Active Publication Date: 2018-07-13
SHENZHEN KELIE TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, the current automobile battery life prediction method is based on the latest collected battery data for life prediction, and the latest collected battery data may not reflect the long-term overall health of the battery, relying on the latest collected battery data for life prediction , the predicted result may not match the actual life of the battery
[0005] Therefore, the automobile battery life prediction method in the prior art has the problem that the accuracy of the automobile battery life prediction is low

Method used

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  • Battery life prediction method, battery data server and battery data processing system
  • Battery life prediction method, battery data server and battery data processing system
  • Battery life prediction method, battery data server and battery data processing system

Examples

Experimental program
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Embodiment 1

[0069] figure 1 It is a flow chart of a battery life prediction method according to Embodiment 1 of the present invention. The method can be applied to a battery data server, and the method can specifically include the following steps:

[0070] Step 101, receiving a battery life prediction request; the battery life prediction request includes real-time battery data and user identification.

[0071] Firstly, it is explained that, in the embodiment of the present invention, it can be used to predict the battery life of an electric vehicle. A battery management user terminal may be preset on the electric vehicle, and the battery management user terminal may include a battery management module BMS and a data communication module.

[0072] The battery management module BMS can be used to collect battery data for the battery. Among them, the battery data can include data collection time, battery state of charge SOC (State of Charge, state of charge), battery health state SOH, batt...

Embodiment 2

[0092] figure 2 It is a flow chart of a battery life prediction method according to Embodiment 2 of the present invention. The method can be applied to a battery management user terminal, and the battery management user terminal is preset with a user ID. The method specifically includes the following steps:

[0093] Step 201, collecting real-time battery data.

[0094] In a specific implementation, the battery management module BMS in the battery management user terminal can collect data for the battery, and use the battery data collected in real time as the above-mentioned real-time battery data.

[0095] Step 202, generating a battery life prediction request for the real-time battery data and the user identifier.

[0096] In a specific implementation, the battery management user terminal may extract a preset user ID, and generate a battery life prediction request based on the user ID and real-time battery data.

[0097] Step 203, sending the battery life prediction reques...

Embodiment 3

[0103] image 3 It is a structural block diagram of a battery data server according to Embodiment 3 of the present invention. The battery data server 300 may specifically include the following modules:

[0104] Data aggregation module 301, data storage module 302 and data application module 303;

[0105] The data aggregation module 301 is configured to receive a battery life prediction request; the battery life prediction request includes real-time battery data and user identification;

[0106] The data storage module 302 is configured to extract historical battery data corresponding to the user identifier;

[0107] The data application module 303 is configured to obtain a battery life prediction result for the real-time battery data and the historical battery data, and send the battery life prediction result to a battery management user terminal.

[0108] Optionally, the battery data server is preset with a plurality of battery data and corresponding user identifiers to be ma...

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PUM

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Abstract

The embodiment of the invention provides a battery life prediction method, a battery data server, a battery management user terminal and a battery data processing system, the method comprises the following steps of receiving a battery life prediction request, wherein the battery life prediction request comprises real-time battery data and a user identifier; extracting historical battery data corresponding to the user identifier; acquiring a battery life prediction result according to the real-time battery data and the historical battery data; sending the battery life prediction result to the battery management user terminal. According to the embodiment of the invention, the battery life prediction accuracy is improved.

Description

technical field [0001] The present invention relates to the technical field of battery data processing, in particular to a battery life prediction method, a battery data server, a battery management user terminal, and a battery data processing system. Background technique [0002] At present, more and more users travel by electric vehicles. [0003] Electric vehicles use car batteries as power sources, and centrally manage and control the operation of car batteries through BMS (Battery Management System, battery management system). In order to ensure the normal operation of the BMS system, it is necessary to collect battery data such as current, voltage, temperature, and battery fault signals of the car battery at high frequency, and the battery data server will predict the life of the car battery based on the battery data. [0004] However, the current automobile battery life prediction method is based on the latest collected battery data for life prediction, and the lates...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/36G06F17/30
CPCG01R31/367G01R31/392G06F16/2465G06F16/25
Inventor 唐亮
Owner SHENZHEN KELIE TECH