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Data center storage battery capacity prediction method, device and equipment

A battery capacity and data center technology, applied in the direction of measuring devices, measuring electrical variables, measuring electricity, etc., can solve the problems of low model construction efficiency and model prediction accuracy, and achieve the goal of improving prediction accuracy, improving prediction efficiency, and improving construction efficiency Effect

Pending Publication Date: 2022-05-13
ALIBABA (CHINA) CO LTD
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Problems solved by technology

[0005] This application provides a method for constructing a prediction model of battery capacity attenuation coefficient to solve the problems of low model construction efficiency and model prediction accuracy existing in the prior art

Method used

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  • Data center storage battery capacity prediction method, device and equipment
  • Data center storage battery capacity prediction method, device and equipment
  • Data center storage battery capacity prediction method, device and equipment

Examples

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no. 1 example

[0067] Please refer to figure 1 , which is a flow chart of the method for constructing the battery capacity decay coefficient prediction model of the present application. In this embodiment, the method may include the following steps:

[0068] Step S101: Obtain historical state monitoring data during charging and discharging of the storage battery.

[0069] A storage battery is an electrochemical device that directly converts chemical energy into electrical energy. The specific characteristics of the battery are as follows: after discharge, the internal active material can be regenerated by charging, that is, the electrical energy is stored as chemical energy; when it needs to be discharged, the chemical energy is converted into electrical energy again. For example, mobile phone batteries commonly used in daily life, batteries used in automobiles (commonly known as batteries), and data center batteries.

[0070] Taking the storage battery in the data center as an example, t...

no. 2 example

[0104] In the above-mentioned embodiments, a method for constructing a prediction model for the capacity decay coefficient of a battery is provided, and correspondingly, the present application also provides a device for constructing a prediction model for the capacity decay coefficient of a battery. The device corresponds to the embodiment of the above-mentioned method. Since the device embodiment is basically similar to the method embodiment, the description is relatively simple, and for relevant parts, refer to the part of the description of the method embodiment. The device embodiments described below are illustrative only.

[0105] The present application further provides a device for constructing a battery capacity attenuation coefficient prediction model, including: a historical data acquisition unit, a battery selection unit, a training data generation unit, and a model training unit.

[0106] The historical data acquisition unit is used to acquire the historical stat...

no. 3 example

[0116] In the foregoing embodiments, a method for constructing a prediction model for a battery capacity decay coefficient is provided, and correspondingly, the present application also provides an electronic device. The device corresponds to the embodiment of the above-mentioned method. Since the device embodiment is basically similar to the method embodiment, the description is relatively simple, and for related parts, please refer to part of the description of the method embodiment. The device embodiments described below are illustrative only.

[0117] An electronic device according to this embodiment, the electronic device includes: a processor and a memory; the memory is used to store a program for implementing a method for constructing a prediction model for a battery capacity decay coefficient, and the device is powered on and runs the program of the method through the processor Afterwards, the following steps are performed: obtain the historical state monitoring data ...

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Abstract

The invention discloses a data center storage battery capacity detection method and a storage battery capacity attenuation coefficient prediction model construction method. According to the model construction method, battery capacity attenuation coefficient data and corresponding battery state characteristics are obtained based on state monitoring data in the historical charging and discharging process of a storage battery, and a storage battery capacity attenuation coefficient prediction model is obtained through learning from the data. Therefore, additional experiments or additional sensors are not needed, the workload is small, implementation is easy, and therefore the model building efficiency can be effectively improved. Meanwhile, the processing mode fully considers the influence of factors such as battery internal resistance, temperature, voltage, use time, use times, battery model and the like on the actual capacity of the battery, so that the model prediction precision can be effectively improved.

Description

technical field [0001] The present application relates to the technical field of battery management, in particular to a method and device for constructing a battery capacity attenuation coefficient prediction model, a data center battery capacity prediction method and device, and electronic equipment. Background technique [0002] The actual capacity of the battery is an important basic data in the process of data center operation and maintenance. According to the battery capacity, it can calculate the discharge time of the battery, the state of charge of the battery and other indicators. It can also find out the battery whose actual capacity is too low and replace it, so as to improve the stability of the battery in the data center. The calculation method of the actual capacity of the battery is mainly to estimate the attenuation coefficient of the battery capacity first, and then calculate the product of the rated capacity of the battery and the attenuation coefficient of ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/382
CPCG01R31/382
Inventor 潘兵王加龙理栈
Owner ALIBABA (CHINA) CO LTD
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