CN-121998613-A - Battery maintenance decision method, device, vehicle and storage medium

CN121998613ACN 121998613 ACN121998613 ACN 121998613ACN-121998613-A

Abstract

The application relates to the technical field of battery management, in particular to a battery maintenance decision method, a device, a vehicle and a storage medium, wherein the method comprises the steps of obtaining historical operation data of a fault battery, preprocessing the data, extracting characteristics of the preprocessed historical operation data to obtain maintenance decision characteristic parameters of the fault battery, determining the fault type of the fault battery according to the maintenance decision characteristic parameters, and further determining a maintenance strategy of the fault battery according to the fault type so as to maintain the fault battery according to the maintenance strategy of the fault battery. Therefore, the problems that in the related art, the battery fault can only be subjected to blind maintenance decision by means of personal experience, excessive maintenance or insufficient maintenance and the like are solved, the recoverability of the fault battery is intelligently judged by automatically analyzing the historical operation data of the fault battery, and the maintenance strategy of on-line maintenance or replacement of a single unit is automatically matched, so that the operation and maintenance of the fuel cell system are accurate and intelligent.

Inventors

ZHANG ZHIYUN
LUO YANHUI
ZHANG SHUANLU
QIN ZHIDONG
YAN KANGKANG
DI JINRUI
WANG QI
ZHU TIANLONG

Assignees

北京卡文新能源汽车有限公司

Dates

Publication Date: 20260508
Application Date: 20260105

Claims (10)

1. A method for making a maintenance decision on a battery, comprising the steps of: Acquiring historical operation data of a fault battery; Performing data preprocessing on the historical operation data, and performing feature extraction on the data preprocessed historical operation data to obtain maintenance decision feature parameters of the fault battery; And determining the fault type of the fault battery according to the maintenance decision feature parameters, determining the maintenance strategy of the fault battery according to the fault type, and maintaining the fault battery according to the maintenance strategy of the fault battery.
2. The method of claim 1, further comprising, prior to acquiring the historical operating data of the failed battery: Judging whether the fault battery is in an isolated state or not; and if the fault battery is in the isolated state, triggering a maintenance decision instruction of the fault battery.
3. The method of claim 1, wherein the feature extracting the data-preprocessed historical operating data to obtain the maintenance decision feature parameters of the faulty battery comprises: Calculating the historical operation data after the data preprocessing, and determining the voltage recovery capacity, the fault duration time, the abnormal temperature peak value and the historical isolation frequency of the historical operation data after the data preprocessing; And obtaining maintenance decision feature parameters of the fault battery based on the voltage recovery capability, the fault duration, the temperature abnormal peak value and the historical isolation frequency.
4. A method according to claim 1 or 3, wherein said determining the fault type of the faulty battery according to the maintenance decision feature parameter comprises: Judging whether the voltage recovery capability of the fault battery is in a target recovery state, whether the fault duration time of the fault battery is smaller than a preset duration time threshold value, whether the abnormal temperature peak value of the fault battery is smaller than a preset temperature peak value, and whether the historical isolation frequency of the fault battery is smaller than a preset isolation accumulation frequency; and if the voltage recovery capability of the fault battery is in the target recovery state, the fault duration of the fault battery is smaller than the preset duration threshold, the abnormal temperature peak value of the fault battery is smaller than the preset temperature peak value, and the historical isolation frequency of the fault battery is smaller than the preset accumulated isolation frequency, judging that the fault type of the fault battery is a recoverable fault type.
5. The method of claim 4, wherein said determining a fault type for the faulty battery based on the maintenance decision feature parameter further comprises: And if the voltage recovery capability of the fault battery is not in the target recovery state, or the fault duration of the fault battery is greater than or equal to the preset duration threshold, or the abnormal temperature peak value of the fault battery is greater than or equal to the preset temperature peak value, or the historical isolation frequency of the fault battery is greater than or equal to the preset isolation accumulated times, judging that the fault type of the fault battery is an unrecoverable fault type.
6. The method of claim 5, wherein determining the repair strategy for the failed battery based on the fault type and repairing the failed battery based on the repair strategy for the failed battery comprises: if the fault type of the fault battery is the recoverable fault type, the fault battery is maintained online; If the fault type of the fault battery is the unrecoverable fault type, generating a structural maintenance work order, and sending a maintenance instruction to operation and maintenance personnel so as to remind the operation and maintenance personnel to replace a fault component of the fault battery.
7. A battery service decision making apparatus, comprising: The acquisition module is used for acquiring historical operation data of the fault battery; The feature extraction module is used for carrying out data preprocessing on the historical operation data and carrying out feature extraction on the historical operation data after the data preprocessing to obtain maintenance decision feature parameters of the fault battery; And the maintenance module is used for determining the fault type of the fault battery according to the maintenance decision feature parameters, determining the maintenance strategy of the fault battery according to the fault type, and maintaining the fault battery according to the maintenance strategy of the fault battery.
8. The apparatus of claim 7, wherein the acquisition module, prior to acquiring the historical operating data of the failed battery, further comprises: The judging unit is used for judging whether the fault battery is in an isolated state or not; And the instruction triggering unit is used for triggering a maintenance decision instruction of the fault battery if the fault battery is in the isolated state.
9. A vehicle comprising a memory, a processor and a computer program stored on the memory and capable of running on the processor, the processor executing the program to implement the method of making a maintenance decision for a battery as claimed in any one of claims 1 to 6.
10. A computer readable storage medium having stored thereon a computer program, characterized in that the program is executed by a processor for implementing a method of maintenance decision of a battery according to any of claims 1-6.

Description

Battery maintenance decision method, device, vehicle and storage medium Technical Field The application relates to the technical field of new energy, in particular to a battery maintenance decision method, a device, a vehicle and a storage medium. Background In the operation process of the fuel cell, the fuel cell system has single-cell-level fault on-line isolation capability, and the fuel cell stack can isolate fault units under the condition of no shutdown so as to realize fault-tolerant operation and ensure task continuity. In the related art, after a fault battery is isolated, when a maintainer faces the isolated fault battery, effective data and support for judging the root cause of the fault battery and the reversibility of the fault battery are lacking, so that blind maintenance decisions can be carried out only by means of personal experience, and the problems of excessive maintenance or insufficient maintenance and the like can occur, and finally, the problems of low maintenance efficiency, high cost and urgent need to be solved are caused. Disclosure of Invention The application provides a battery maintenance decision method, a device, a vehicle and a storage medium, which are used for solving the problems that in the related art, the battery fault can only be subjected to blind maintenance decision by means of personal experience, so that excessive maintenance or insufficient maintenance and the like occur. An embodiment of a first aspect of the present application provides a method for making a maintenance decision for a battery, including the steps of: Acquiring historical operation data of a fault battery; Performing data preprocessing on the historical operation data, and performing feature extraction on the data preprocessed historical operation data to obtain maintenance decision feature parameters of the fault battery; And determining the fault type of the fault battery according to the maintenance decision feature parameters, determining the maintenance strategy of the fault battery according to the fault type, and maintaining the fault battery according to the maintenance strategy of the fault battery. According to one embodiment of the present application, before acquiring the historical operation data of the faulty battery, further includes: Judging whether the fault battery is in an isolated state or not; and if the fault battery is in the isolated state, triggering a maintenance decision instruction of the fault battery. According to an embodiment of the present application, the feature extraction of the historical operation data after the data preprocessing to obtain the maintenance decision feature parameter of the faulty battery includes: Calculating the historical operation data after the data preprocessing, and determining the voltage recovery capacity, the fault duration time, the abnormal temperature peak value and the historical isolation frequency of the historical operation data after the data preprocessing; And obtaining maintenance decision feature parameters of the fault battery based on the voltage recovery capability, the fault duration, the temperature abnormal peak value and the historical isolation frequency. According to one embodiment of the present application, the determining the fault type of the faulty battery according to the maintenance decision feature parameter includes: Judging whether the voltage recovery capability of the fault battery is in a target recovery state, whether the fault duration time of the fault battery is smaller than a preset duration time threshold value, whether the abnormal temperature peak value of the fault battery is smaller than a preset temperature peak value, and whether the historical isolation frequency of the fault battery is smaller than a preset isolation accumulation frequency; and if the voltage recovery capability of the fault battery is in the target recovery state, the fault duration of the fault battery is smaller than the preset duration threshold, the abnormal temperature peak value of the fault battery is smaller than the preset temperature peak value, and the historical isolation frequency of the fault battery is smaller than the preset accumulated isolation frequency, judging that the fault type of the fault battery is a recoverable fault type. According to one embodiment of the present application, the determining the fault type of the faulty battery according to the maintenance decision feature parameter further includes: And if the voltage recovery capability of the fault battery is not in the target recovery state, or the fault duration of the fault battery is greater than or equal to the preset duration threshold, or the abnormal temperature peak value of the fault battery is greater than or equal to the preset temperature peak value, or the historical isolation frequency of the fault battery is greater than or equal to the preset isolation accumulated times, judging that the fault type of the fault batter