CN-121995228-A - Battery package life prediction method and device, electronic equipment and storage medium

CN121995228ACN 121995228 ACN121995228 ACN 121995228ACN-121995228-A

Abstract

The embodiment of the application provides a battery packaging life prediction method, a battery packaging life prediction device, electronic equipment and a storage medium, which are applied to the technical field of batteries. The method comprises the steps of responding to a prediction request of the battery packaging service life, establishing a decay model of the battery to be tested according to breathing fatigue experimental data and creep fatigue experimental data, inputting a target working condition into the decay model to obtain a decay curve, inputting the target working condition into an internal air pressure model to obtain an internal air pressure change curve, and determining the packaging service life of the battery to be tested according to the intersection point of the decay curve and the internal air pressure change curve. According to the scheme, the packaging reliability of the battery is affected by the respiratory fatigue and the creep fatigue, a decay model is built by combining the effects of the respiratory fatigue and the creep fatigue, the packaging service life is determined according to the target working condition, and the packaging reliability of the battery can be predicted according to the actual use scene of the battery, so that the prediction accuracy of the packaging effect is improved in the early stage of battery development.

Inventors

GAO MENGMENG
GAO PO
MA RUIJUN

Assignees

中创新航科技集团股份有限公司

Dates

Publication Date: 20260508
Application Date: 20260210

Claims (13)

1. A method for predicting battery package life, comprising: Responding to a prediction request of the packaging service life of the battery, and acquiring breathing fatigue experimental data, creep fatigue experimental data and an internal air pressure model of the battery to be tested, wherein the prediction request comprises target working conditions of the battery to be tested; Establishing a decay model of the battery to be tested according to the respiratory fatigue experimental data and the creep fatigue experimental data; Inputting the target working condition into the decay model to obtain a decay curve, and inputting the target working condition into the internal air pressure model to obtain an internal air pressure change curve; And determining the packaging service life of the battery to be tested according to the intersection point of the decay curve and the internal air pressure change curve.
2. The method of claim 1, wherein the step of determining the position of the substrate comprises, The respiratory fatigue experimental data comprise respiratory fatigue experimental data of an explosion-proof valve and respiratory fatigue experimental data of a welding line of the shell; The creep fatigue test data comprise explosion-proof valve creep fatigue test data and shell weld creep fatigue test data.
3. The method of claim 2, wherein establishing a degradation model of the battery under test from the respiratory fatigue experimental data and the creep fatigue experimental data comprises: Establishing an explosion-proof valve decay model according to the explosion-proof valve respiratory fatigue experimental data and the explosion-proof valve creep fatigue experimental data; Fitting the shell weld joint respiratory fatigue experimental data to obtain a first weld joint strength decay model of the shell weld joint; Fitting the shell weld creep fatigue experimental data to obtain a second weld strength decay model of the shell weld; Determining a shell weld joint decay model according to the first weld joint strength decay model and the second weld joint strength decay model; And determining the explosion-proof valve decay model and the shell weld decay model as decay models of the battery to be tested.
4. A method according to claim 3, wherein establishing an explosion-proof valve decay model from the explosion-proof valve breath fatigue experimental data and the explosion-proof valve creep fatigue experimental data comprises: Determining an explosion-proof valve upper limit sample and an explosion-proof valve lower limit sample according to the explosion-proof valve respiratory fatigue experimental data and the explosion-proof valve creep fatigue experimental data; Determining upper-limit breath fatigue experimental data corresponding to the upper-limit sample of the explosion-proof valve and lower-limit breath fatigue experimental data corresponding to the lower-limit sample of the explosion-proof valve from the breath fatigue experimental data of the explosion-proof valve; Determining upper limit creep fatigue experimental data corresponding to the upper limit sample of the explosion-proof valve and lower limit creep fatigue experimental data corresponding to the lower limit sample of the explosion-proof valve from the creep fatigue experimental data of the explosion-proof valve; determining an upper limit valve opening pressure decay model according to the upper limit respiratory fatigue experimental data and the upper limit creep fatigue experimental data; determining a lower limit valve opening pressure decay model according to the lower limit respiratory fatigue experimental data and the lower limit creep fatigue experimental data; and determining the upper limit opening valve pressure decay model and the lower limit opening valve pressure decay model as the explosion-proof valve decay model.
5. The method of claim 4, wherein determining an upper limit open valve pressure decay model from the upper limit respiratory fatigue experimental data and the upper limit creep fatigue experimental data comprises: determining a plurality of test conditions; according to the plurality of test working conditions, data extraction is carried out from the upper limit respiratory fatigue experimental data to obtain a plurality of first experimental data; Fitting the plurality of first experimental data to obtain a first decay model, wherein the first decay model is used for representing the mapping relation between valve opening pressure decay values and cycle numbers under different test working conditions; according to the plurality of test working conditions, data extraction is carried out from the upper limit creep fatigue test data to obtain a plurality of second test data; Fitting the plurality of second experimental data to obtain a second decay model, wherein the second decay model is used for representing the mapping relation between valve opening pressure decay values and duration under different test working conditions; and determining the upper limit opening valve pressure decay model according to the first decay model and the second decay model.
6. The method of claim 5, wherein the target operating conditions include daily range and full range, and wherein determining the upper limit valve opening pressure decay model based on the first decay model and the second decay model comprises: determining the ratio of the daily driving mileage to the full-power driving mileage as the daily equivalent cycle number; Converting the first regression model according to the daily equivalent cycle number to obtain a conversion regression model, wherein the conversion regression model represents the mapping relation between a valve opening pressure regression value and the duration, the temperature and the respiratory pressure; and coupling the conversion decay model with the second decay model to obtain the upper limit opening valve pressure decay model.
7. The method of claim 1, wherein the process of creating the internal air pressure model comprises: Acquiring internal air pressure experimental data of a storage aging path and internal air pressure experimental data of a circulation aging path of a battery to be tested; Fitting the internal air pressure experimental data of the storage aging path to obtain a first internal air pressure model; fitting the internal air pressure experimental data of the cyclic aging path to obtain a second internal air pressure model; and establishing the internal air pressure model according to the first internal air pressure model and the second internal air pressure model.
8. The method of any one of claims 1-7, wherein inputting the target operating condition into the decay model to obtain a decay curve comprises: inputting the target working condition into an upper limit opening valve pressure decay model to obtain an upper limit explosion-proof valve decay curve; Inputting the target working condition into a lower limit opening valve pressure decay model to obtain a lower limit explosion-proof valve decay curve; Inputting the target working condition into a shell weld joint decay model to obtain a shell weld joint decay curve; and determining the upper limit explosion-proof valve decay curve, the lower limit explosion-proof valve decay curve and the shell weld decay curve as the decay curves.
9. The method of claim 8, wherein determining the package life of the battery under test based on the intersection of the decay curve and the internal gas pressure change curve comprises: determining an intersection point of the internal air pressure change curve and the lower limit explosion-proof valve decay curve as a first intersection point, and determining a first abscissa value corresponding to the first intersection point; Determining an intersection point of the shell weld joint decay curve and the upper limit explosion-proof valve decay curve as a second intersection point, and determining a second abscissa value corresponding to the second intersection point; and determining the minimum value of the first abscissa value and the second abscissa value as the package life.
10. The method of claim 9, further comprising, after determining the package life of the battery under test: collecting real-time working parameters of the battery to be tested; and carrying out correction processing on the fading model and the internal air pressure model according to the real-time working parameters.
11. A battery package life prediction apparatus, comprising: The acquisition module is used for responding to a prediction request of the battery packaging service life, acquiring breathing fatigue experimental data, creep fatigue experimental data and an internal air pressure model of the battery to be tested, wherein the prediction request comprises a target working condition of the battery to be tested; The establishing module is used for establishing a decay model of the battery to be tested according to the respiratory fatigue experimental data and the creep fatigue experimental data; The generating module is used for inputting the target working condition into the decay model to obtain a decay curve, and inputting the target working condition into the internal air pressure model to obtain an internal air pressure change curve; And the prediction module is used for determining the packaging service life of the battery to be tested according to the intersection point of the decay curve and the internal air pressure change curve.
12. An electronic device comprising a processor and a memory communicatively coupled to the processor; The memory stores computer-executable instructions; The processor executes computer-executable instructions stored in the memory to implement the method of any one of claims 1-10.
13. A non-transitory computer readable storage medium having stored therein computer executable instructions which when executed by a processor are adapted to carry out the method of any one of claims 1-10.

Description

Battery package life prediction method and device, electronic equipment and storage medium Technical Field The present application relates to the field of battery technologies, and in particular, to a method and apparatus for predicting a battery package lifetime, an electronic device, and a storage medium. Background With the development of battery technology, the battery can provide energy storage and energy supply functions in application scenes such as electric automobiles and communication. The internal components such as the battery core, electrolyte and the like of the battery are isolated from the external environment through the packaging technology, so that the battery can stably work. The reliability of the package affects the reliability of the battery. In the related art, the package life of a battery is predicted through a single test item and a fixed test condition to evaluate the package reliability of the battery. However, this method has a problem of low accuracy. Disclosure of Invention The embodiment of the application provides a battery packaging life prediction method, a battery packaging life prediction device, electronic equipment and a storage medium, which are used for improving the accuracy of battery packaging effect prediction. In a first aspect, an embodiment of the application provides a method for predicting a battery packaging life, which comprises the steps of responding to a battery packaging life prediction request, obtaining breathing fatigue experimental data, creep fatigue experimental data and an internal air pressure model of a battery to be tested, wherein the prediction request comprises target working conditions of the battery to be tested, establishing a decay model of the battery to be tested according to the breathing fatigue experimental data and the creep fatigue experimental data, inputting the target working conditions into the decay model to obtain a decay curve, inputting the target working conditions into the internal air pressure model to obtain an internal air pressure change curve, and determining the packaging life of the battery to be tested according to intersection points of the decay curve and the internal air pressure change curve. In a second aspect, an embodiment of the application provides a device for predicting a battery packaging life, which comprises an acquisition module, a building module, a generation module and a prediction module, wherein the acquisition module is used for responding to a prediction request of the battery packaging life, the prediction request comprises target working conditions of the battery to be tested, the building module is used for building a decay model of the battery to be tested according to the breath fatigue experimental data and the creep fatigue experimental data, the generation module is used for inputting the target working conditions into the decay model to obtain a decay curve, inputting the target working conditions into the internal air pressure model to obtain an internal air pressure change curve, and the prediction module is used for determining the packaging life of the battery to be tested according to intersection points of the decay curve and the internal air pressure change curve. In a third aspect, an embodiment of the present application provides a device for predicting a lifetime of a battery package, including a memory, a processor; The memory stores computer-executable instructions; the processor executes computer-executable instructions stored by the memory such that the processor performs the various possible implementations of the first aspect and/or the first aspect as described above. In a fourth aspect, embodiments of the present application provide a non-volatile computer-readable storage medium having stored therein computer-executable instructions which, when executed by a processor, are adapted to carry out the various possible implementations of the above first aspect and/or the first aspect. In a fifth aspect, embodiments of the present application provide a computer program product comprising a computer program which, when executed by a processor, implements the various possible implementations of the above first aspect and/or the first aspect. The method comprises the steps of responding to a prediction request of battery packaging service life, obtaining breathing fatigue experimental data, creep fatigue experimental data and an internal air pressure model of a battery to be tested, wherein the prediction request comprises target working conditions of the battery to be tested, establishing a decay model of the battery to be tested according to the breathing fatigue experimental data and the creep fatigue experimental data, inputting the target working conditions into the decay model to obtain a decay curve, inputting the target working conditions into the internal air pressure model to obtain an internal air pressure change curve, and determining the packaging service l