Lithium ion battery online capacity prediction method and system, equipment, and storage medium

A lithium-ion battery and capacity technology, which is applied in the direction of prediction, measurement of electrical variables, and measurement of electricity, can solve problems such as the complexity of the implementation process, and achieve the effects of avoiding feature engineering, avoiding cumulative errors, and reducing complexity

Pending Publication Date: 2021-12-03
XI AN JIAOTONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this method requires feature engineering, and the implementation process is more complicated.

Method used

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  • Lithium ion battery online capacity prediction method and system, equipment, and storage medium
  • Lithium ion battery online capacity prediction method and system, equipment, and storage medium
  • Lithium ion battery online capacity prediction method and system, equipment, and storage medium

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Embodiment 1

[0036] refer to figure 1 , the method for lithium-ion battery online capacity prediction of the present invention comprises the following steps:

[0037] 1) Obtain the historical flow data of the battery, the historical flow data of the battery includes the historical capacity, charge voltage curve and discharge voltage curve of the battery;

[0038] 2) Intercept the historical capacity, charge voltage curve and discharge voltage curve of the battery to a length of l (1) , l (2) , l (3) and use it as a training sample;

[0039] 3) using the training samples obtained in step 2) to train the DNN model;

[0040] 4) Use the trained DNN model to predict the online capacity of lithium-ion batteries.

[0041] Described DNN model comprises MLP layer, Attention layer and Embdding layer;

[0042] The working process of the Embedding layer is:

[0043] Let the training samples be the flow data of N historical cycles, and use the training samples to construct the training set X t ...

Embodiment 2

[0081] The system of lithium-ion battery online capacity prediction of the present invention comprises:

[0082] The acquisition module is used to acquire the historical flow data of the battery;

[0083] The preprocessing module is used to preprocess the historical flow data of the battery to obtain training samples;

[0084] A training module, configured to train the DNN model using training samples;

[0085] The prediction module is used to predict the online capacity of the lithium-ion battery using the trained DNN model.

Embodiment 3

[0087] A computer device, comprising a memory, a processor, and a computer program stored in the memory and operable on the processor, when the processor executes the computer program, the online capacity prediction of the lithium-ion battery is realized The steps of the method, wherein, the memory may include a memory, such as a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk memory, etc.; the processor, the network interface, and the memory are connected to each other through an internal bus, the The internal bus can be an industry standard architecture bus, a peripheral component interconnection standard bus, an extended industry standard architecture bus, etc. The bus can be divided into an address bus, a data bus, a control bus, and the like. The memory is used to store programs, specifically, the programs may include program codes, and the program codes include computer operation instructions. Storage, which can incl...

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PUM

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Abstract

The invention discloses a lithium ion battery online capacity prediction method and system, equipment, and a storage medium. The method comprises the following steps: obtaining historical flow data of a battery; preprocessing the historical flow data of the battery to obtain a training sample; and training the DNN model by using the training sample. The trained DNN model is used for predicting the online capacity of the lithium ion battery, the method, the system, the equipment and the storage medium can accurately predict the online capacity of the lithium ion battery, and operation is convenient.

Description

technical field [0001] The present invention relates to a method, system, device and storage medium for capacity prediction, in particular to a method, system, device and storage medium for online capacity prediction of a lithium ion battery. Background technique [0002] The aging phenomenon of lithium-ion batteries is a major problem encountered in its application. As the number of cycles increases, the maximum usable capacity of Li-ion batteries continues to decrease. Therefore, online prediction of lithium-ion battery capacity is particularly important. [0003] At present, it is a common method to calculate the battery capacity based on the current integration. The calculated value of the battery capacity can be obtained by using the sensor to collect the current signal and integrating it with time. However, this method is greatly affected by the accuracy of the current sensor, and integration will also bring about the influence of accumulated errors that are difficu...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06N3/04G06K9/62G01R31/367
CPCG06Q10/04G01R31/367G06Q50/06G06N3/045G06F18/214
Inventor 陈欣张亚东邹晨晔
Owner XI AN JIAOTONG UNIV
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