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Battery fault diagnosis method and system based on GM (1, 1) grey model

A battery fault and gray model technology, applied in the direction of measuring electricity, measuring electrical variables, instruments, etc., can solve a large number of problems with high data sampling density requirements, achieve low computing costs, save data storage space, and maintain diagnostic sensitivity.

Pending Publication Date: 2021-02-12
SHANDONG UNIV
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Problems solved by technology

This method can diagnose multiple types of early battery failures at the same time, and can predict the failure time, but requires a large amount of voltage sample data, and has a high requirement for data sampling density (usually 0.01s to collect one data)

Method used

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  • Battery fault diagnosis method and system based on GM (1, 1) grey model
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  • Battery fault diagnosis method and system based on GM (1, 1) grey model

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Embodiment Construction

[0038] The present disclosure will be further described below in conjunction with the accompanying drawings and embodiments.

[0039] It should be noted that the following detailed description is exemplary and intended to provide further explanation of the present disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.

[0040] It should be noted that the terminology used herein is only for describing specific embodiments, and is not intended to limit the exemplary embodiments according to the present disclosure. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinations thereof.

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Abstract

The invention provides a battery fault diagnosis method and system based on a GM (1, 1) gray model. The method comprises the steps of building a battery GM (1, 1) voltage prediction model based on a gray system theory according to the fluctuation characteristics of a voltage during the charging and discharging of a battery, setting secondary battery voltage data for prediction through the latest current working condition, obtaining a prediction value, and calculating the difference between a voltage measurement value and the prediction value. Potential faults of the battery are diagnosed according to difference changes, early diagnosis of multiple faults of the battery under different working conditions is achieved, fault types and fault time can be accurately predicted, the requirement for data density is low, and the voltage of the battery only needs to be collected once in one second. The method is simple and easy to implement and good in robustness, and has a great practical value.

Description

technical field [0001] The disclosure belongs to the field of new energy vehicle power battery fault diagnosis, and relates to a battery fault diagnosis method and system based on a GM (1, 1) gray model. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] In order to promote the development of sustainable energy and the increasing demand for energy, the development of electric vehicles has attracted worldwide attention. Lithium battery (lithium-ion power battery) has become one of the core technologies of electric vehicles due to its outstanding advantages such as high specific energy / specific power, long cycle life and no memory effect, and its performance directly affects the performance of electric vehicles. safety and economy. However, the safety issue caused by battery failure has become a key technical difficulty facing the developmen...

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Application Information

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IPC IPC(8): G01R31/367
CPCG01R31/367
Inventor 商云龙鲁高鹏张承慧张奇段彬康永哲周忠凯
Owner SHANDONG UNIV
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