CN-121994901-A - Data analysis method, device, electronic equipment, storage medium and program product

CN121994901ACN 121994901 ACN121994901 ACN 121994901ACN-121994901-A

Abstract

The application provides a data analysis method, a data analysis device, electronic equipment, a storage medium and a program product, and relates to the technical field of data analysis. According to the method, the mass spectrum data of the gas product and the voltage change data of the voltage along with time generated in the charge and discharge process of the battery device are obtained, and then the mass spectrum data and the voltage change data are analyzed, so that the association relation between the voltage and the mass spectrum data of the gas product in the time dimension can be analyzed, the performance of the battery can be estimated more comprehensively and accurately, and the data support is provided for optimizing the design of the battery and the like.

Inventors

LI SHENGNAN
CHEN FANGYUN
LI HAORAN
FENG XIN

Assignees

宁德时代新能源科技股份有限公司

Dates

Publication Date: 20260508
Application Date: 20241106

Claims (13)

1. A method of data analysis, the method comprising: acquiring mass spectrum data and voltage change data, wherein the mass spectrum data refers to mass spectrum data of a gas product generated in a charging and discharging process of a battery device, and the voltage change data refers to change data of voltage of the battery device along with time in the charging and discharging process; And analyzing the mass spectrum data and the voltage change data to obtain the association relation of the mass spectrum data and the voltage change data in the time dimension.
2. The method according to claim 1, wherein analyzing the mass spectrum data and the voltage variation data to obtain an association relationship between the mass spectrum data and the voltage variation data in a time dimension comprises: Analyzing a rate of generation of a gas product during the charge and discharge based on the mass spectrometry data; And analyzing the generation rate and the voltage change data to obtain the association relation between the generation rate and the voltage change data in the time dimension.
3. The method of claim 2, wherein analyzing the rate of production of gas products during the charge and discharge based on the mass spectrometry data comprises: Determining concentration data of a gas product in the charge-discharge process according to the mass spectrum data; And determining the generation rate of the gas product in the charging and discharging process according to the carrier gas rate, the carrier gas concentration and the concentration data.
4. A method according to claim 3, wherein said determining the rate of formation of gaseous products during said charging and discharging based on the carrier gas rate, carrier gas concentration and said concentration data comprises: determining a scale factor based on the carrier gas rate and the carrier gas concentration; And calculating the generation rate of the gas product in the charge and discharge process according to the scale factor and the concentration data.
5. A method according to claim 3, wherein the mass spectrometry data comprises signal strength of a gas product, and the determining concentration data of the gas product during the charge and discharge from the mass spectrometry data comprises: and determining concentration data of the gas product in the charging and discharging process according to the signal intensity.
6. The method of claim 5, wherein said determining concentration data of a gas product during said charging and discharging based on said signal strength comprises: acquiring a corresponding relation between signal intensity and concentration data, wherein the corresponding relation is obtained by fitting the signal intensity of a gas product generated in the charge and discharge processes of a plurality of battery devices and the corresponding concentration data in advance; And determining concentration data of the gas product in the charging and discharging process according to the corresponding relation.
7. The method according to claim 2, wherein the generation rate includes time-dependent data of a rate of a gas product during the charge and discharge, and the analyzing the generation rate and the voltage-dependent data to obtain an association relationship between the generation rate and the voltage-dependent data in a time dimension includes: generating a correlation graph of the voltage variation data and the generation rate in a time dimension; and determining the association relation between the generation rate and the voltage change data in the time dimension according to the association curve graph.
8. The method of claim 7, wherein after generating the plot of the voltage change data and the rate of generation associated in the time dimension, further comprising: And outputting the association graph.
9. The method according to any one of claims 1 to 8, wherein analyzing the mass spectrum data and the voltage variation data to obtain an association relationship between the mass spectrum data and the voltage variation data in a time dimension includes: and calling a preset Excel macro, and analyzing the mass spectrum data and the voltage change data to obtain the association relation of the mass spectrum data and the voltage change data in the time dimension.
10. A data analysis device, the device comprising: The data acquisition module is used for acquiring mass spectrum data and voltage change data, wherein the mass spectrum data refers to mass spectrum data of a gas product generated in a charging and discharging process of the battery device, and the voltage change data refers to change data of voltage of the battery device along with time in the charging and discharging process; and the joint analysis module is used for analyzing the mass spectrum data and the voltage change data to obtain the association relation of the mass spectrum data and the voltage change data in the time dimension.
11. An electronic device comprising a processor and a memory storing computer readable instructions that, when executed by the processor, perform the method of any of claims 1-9.
12. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, performs the method according to any of claims 1-9.
13. A computer program product comprising computer program instructions which, when read and executed by a processor, perform the method of any of claims 1-9.

Description

Data analysis method, device, electronic equipment, storage medium and program product Technical Field The present application relates to the field of data analysis technologies, and in particular, to a data analysis method, apparatus, electronic device, storage medium, and program product. Background Differential Electrochemical Mass Spectrometry (DEMS) in situ gas production characterization is a technique based on microreactor and mass Spectrometry techniques that performs on-line detection and analysis of gases generated during in situ chemical reactions. The DEMS technology is widely applied to researches in the fields of chemistry, environment, materials and the like, for example, in the field of gas production detection of electrochemical batteries, can analyze trace gas generated or consumed by the batteries in situ, and can analyze and detect the gas consumption or generation condition of the battery in the operation stage during the secondary reaction gas production of energy storage devices such as lithium ion batteries, lithium metal batteries, sodium ion batteries and the like in the charge and discharge process. By analyzing the gas production of the battery, although the potential problems in the battery design can be identified, the battery design can be optimized, and the battery performance can be improved, if the analysis is performed only based on the DEMS technology, the performance of the battery can be difficult to evaluate more comprehensively and accurately. Disclosure of Invention An object of the embodiments of the present application is to provide a data analysis method, apparatus, electronic device, storage medium and program product, which are used for improving the existing manner to perform analysis based on DEMS technology only, and it is difficult to evaluate the performance of a battery more comprehensively and accurately. In a first aspect, an embodiment of the present application provides a data analysis method, where the method includes: acquiring mass spectrum data and voltage change data, wherein the mass spectrum data refers to mass spectrum data of a gas product generated in a charging and discharging process of a battery device, and the voltage change data refers to change data of voltage of the battery device along with time in the charging and discharging process; And analyzing the mass spectrum data and the voltage change data to obtain the association relation of the mass spectrum data and the voltage change data in the time dimension. In the implementation process, the mass spectrum data of the gas product and the voltage change data of the voltage along with time generated in the charge and discharge process of the battery device are obtained, and then the mass spectrum data and the voltage change data are analyzed, so that the association relationship between the voltage and the mass spectrum data of the gas product in the time dimension can be analyzed, the performance of the battery can be evaluated more comprehensively and accurately, and the data support is provided for optimizing the design of the battery and the like. Optionally, the analyzing the mass spectrum data and the voltage variation data to obtain an association relationship between the mass spectrum data and the voltage variation data in a time dimension includes: Analyzing a rate of generation of a gas product during the charge and discharge based on the mass spectrometry data; And analyzing the generation rate and the voltage change data to obtain the association relation between the generation rate and the voltage change data in the time dimension. In the implementation process, the generation rate of the gas product in the charge and discharge process can indicate possible side reactions in the battery, so that the safety risk of the battery can be identified, the health state of the battery in the charge and discharge process can be estimated by the battery change data, and therefore, the generation rate and the voltage change data are subjected to joint analysis, and the battery performance can be estimated more comprehensively and accurately. Optionally, the analyzing the generation rate of the gas product in the charge-discharge process based on the mass spectrum data includes: Determining concentration data of a gas product in the charge-discharge process according to the mass spectrum data; And determining the generation rate of the gas product in the charging and discharging process according to the carrier gas rate, the carrier gas concentration and the concentration data. In the above implementation, since the gas product is carried out by the carrier gas, the generation rate of the gas product can be more accurately quantitatively analyzed with the carrier gas rate and the carrier gas concentration as reference standards. Optionally, the determining the generation rate of the gas product in the charge-discharge process according to the carrier gas rate, the carrier gas concentra