CN-121995220-A - Method, device, equipment, medium and product for predicting residual life of lithium battery

CN121995220ACN 121995220 ACN121995220 ACN 121995220ACN-121995220-A

Abstract

The embodiment of the application provides a method, a device, equipment, a medium and a product for predicting the residual life of a lithium battery, and relates to the technical field of lithium batteries. In the method, a preset two-stage aging model processes the current performance parameters and the environmental temperature of the lithium battery to obtain the capacity attenuation accumulated value of the lithium battery under the current charge and discharge accumulated times. According to the capacity attenuation value, a residual life prediction result comprising the first charge and discharge accumulation times corresponding to the end life EoL point can be obtained. Wherein the two-stage aging model is a pseudo two-dimensional P2D model constructed based on the cumulative value of the determined volumetric attenuation of active lithium loss due to solid electrolyte interface film SEI and active lithium loss due to lithium deposition. By the method, the prediction accuracy of the residual life of the lithium battery can be improved.

Inventors

LV HAICHAO
JIANG LONG
JI DONGDONG
LI LIWEI
LI LE
LIU XIAOXU
SU HANG

Assignees

中国石油天然气集团有限公司
中国石油集团工程材料研究院有限公司

Dates

Publication Date: 20260508
Application Date: 20241106

Claims (10)

1. A method for predicting remaining life of a lithium battery, comprising: Acquiring the current performance parameters of the lithium battery; According to the performance parameters and the environmental temperature of the lithium battery, a preset two-stage aging model is adopted to process the performance parameters and the environmental temperature, and a capacity attenuation accumulated value of the lithium battery under the current charge and discharge accumulated times is obtained; Obtaining a residual life prediction result according to the capacity attenuation accumulated value, wherein the residual life prediction result comprises a first charge and discharge accumulated time corresponding to an end life EoL point; Wherein the two-stage aging model is a pseudo two-dimensional P2D model constructed to determine the cumulative value of capacity fade based on active lithium loss due to solid electrolyte interface film SEI and active lithium loss due to lithium deposition.
2. The method according to claim 1, wherein the remaining life prediction result further comprises a second charge/discharge cumulative number corresponding to a Knee point of the lithium battery; The method further comprises the steps of: And if the current charge-discharge accumulated times reach the second charge-discharge accumulated times, outputting a lithium battery using strategy, wherein the battery using strategy comprises at least one using mode for slowing down the aging of the lithium battery.
3. The method according to claim 2, wherein the method further comprises: Inputting the performance parameters and the environmental temperature of the lithium battery into the two-stage aging model to obtain a first capacity attenuation accumulated value and a second capacity attenuation accumulated value of the lithium battery under the current charge and discharge accumulated times, wherein the first capacity attenuation accumulated value is used for representing the total capacity attenuation value of the lithium battery caused by the solid electrolyte interface film SEI, and the second capacity attenuation accumulated value is used for representing the total capacity attenuation value of the lithium battery caused by lithium deposition; Calculating a first capacity fading variation value and a second capacity fading variation value between adjacent charge and discharge times according to the first capacity fading integration value and the second capacity fading integration value; If the first capacity attenuation change value is smaller than the second capacity attenuation change value, determining the current charge and discharge accumulated times as the second charge and discharge accumulated times; And if the total capacity attenuation accumulated value between the first capacity attenuation accumulated value and the second capacity attenuation accumulated value is larger than or equal to the preset capacity attenuation threshold value of the lithium battery, determining the current charge and discharge accumulated times as the first charge and discharge accumulated times.
4. The method of claim 1, wherein the two-stage aging model acquisition process comprises: acquiring a preset pseudo two-dimensional P2D model; Determining a target coefficient configuration scheme of a target fitting function in the pseudo two-dimensional P2D model; and configuring coefficients in the target fitting function according to the target coefficient configuration scheme to obtain the two-stage aging model.
5. The method of claim 4, wherein determining the target coefficient configuration scheme for the target fitting function in the pseudo two-dimensional P2D model comprises: determining a target fitting function of a coefficient to be optimized; And determining the target coefficient configuration scheme according to the modified fitting function and the target fitting function, wherein the modified fitting function is the sum of a first fitting function, a second fitting function, a third fitting function, a fourth fitting function, a fifth fitting function, a sixth fitting function, a seventh fitting function and an eighth fitting function, wherein the first fitting function, the second fitting function, the third fitting function, the fourth fitting function, the fifth fitting function, the sixth fitting function, the seventh fitting function and the eighth fitting function correspond to the anode capacity and cathode capacity ratio correspond to the ambient temperature.
6. The method of claim 5, wherein the process of obtaining the modified fitting function comprises: acquiring a historical aging data set of the lithium battery, wherein the historical aging data set comprises a historical ambient temperature aging data set, a historical charging rate aging data set, a historical charge state aging data set and a historical negative electrode capacity and positive electrode capacity ratio aging data set; Acquiring a first initial fitting function, a second initial fitting function, a third initial fitting function, a fourth initial fitting function, a fifth initial fitting function, a sixth initial fitting function, a seventh initial fitting function and an eighth initial fitting function of coefficients to be determined; Determining coefficients to be determined in the first initial fitting function and the second initial fitting function according to a historical environmental temperature aging data set and a least square fitting method, and obtaining the first fitting function and the second fitting function; determining coefficients to be determined in the third initial fitting function and the fourth initial fitting function according to the historical charge rate aging data set and the least square fitting method, and obtaining the third fitting function and the fourth fitting function; Determining coefficients to be determined in the fifth initial fitting function and the sixth initial fitting function according to the historical state-of-charge aging data set and the least square fitting method, and obtaining the fifth fitting function and the sixth initial fitting function; And determining coefficients to be determined in the seventh initial fitting function and the eighth initial fitting function according to the historical cathode capacity and anode capacity ratio aging data set and a least square fitting method, and obtaining the seventh fitting function and the eighth fitting function.
7. The method of claim 6, wherein the process of obtaining the historical aging dataset comprises: Initializing a charging rate, a charge state, a negative electrode capacity and a positive electrode capacity ratio in the pseudo two-dimensional P2D model, and inputting different environment temperatures into the pseudo two-dimensional P2D model to obtain a historical environment temperature aging data set, wherein the historical environment temperature aging data set comprises the different environment temperatures, charge and discharge accumulated times of the lithium battery at the different environment temperatures, a capacity attenuation accumulated value caused by the SEI, a capacity attenuation accumulated value caused by the lithium deposition and charge and discharge accumulated times corresponding to a Knee point; initializing the environment temperature, the charge state, the negative electrode capacity and the positive electrode capacity ratio in the pseudo two-dimensional P2D model, and inputting different charge multiplying powers into the pseudo two-dimensional P2D model to obtain the historical charge multiplying power aging data set, wherein the historical charge multiplying power aging data set comprises the different charge multiplying powers, charge and discharge accumulated times of the lithium battery under the different charge multiplying powers, capacity attenuation accumulated values caused by the SEI, capacity attenuation accumulated values caused by the lithium deposition and charge and discharge accumulated times corresponding to a Knee point; Initializing the environment temperature, the charging rate, the cathode capacity and the anode capacity ratio in the pseudo two-dimensional P2D model, and inputting different charge states into the pseudo two-dimensional P2D model to obtain the historical charge state aging data set, wherein the historical charge state aging data set comprises the different charge states, the charge and discharge accumulated times of the lithium battery under the different charging rates, the capacity attenuation accumulated value caused by the SEI, the capacity attenuation accumulated value caused by the lithium deposition and the charge and discharge accumulated times corresponding to a Knee point; Initializing the environment temperature, the charging rate and the state of charge in the pseudo two-dimensional P2D model, and inputting different anode capacity and cathode capacity ratios into the pseudo two-dimensional P2D model to obtain the historical anode capacity and cathode capacity ratio aging data set, wherein the historical anode capacity and cathode capacity ratio aging data set comprises the different anode capacity and cathode capacity ratios, the charge and discharge accumulated times of the lithium battery under the different anode capacity and cathode capacity ratios, the capacity attenuation accumulated value caused by the SEI, the capacity attenuation accumulated value caused by lithium deposition and the charge and discharge accumulated times corresponding to a Knee point.
8. A device for predicting remaining life of a lithium battery, comprising: The acquisition module is used for acquiring the current performance parameters of the lithium battery; The processing module is used for processing the performance parameters by adopting a preset two-stage aging model according to the performance parameters and the environmental temperature of the lithium battery to obtain a capacity attenuation accumulated value of the lithium battery under the current charge and discharge accumulated times; The processing module is further configured to obtain a remaining life prediction result according to the capacity attenuation accumulated value, where the remaining life prediction result includes a first charge-discharge accumulated number corresponding to an end life EoL point; Wherein the two-stage aging model is a pseudo two-dimensional P2D model constructed to determine the cumulative value of capacity fade based on active lithium loss due to solid electrolyte interface film SEI and active lithium loss due to lithium deposition.
9. The computer equipment is characterized by comprising a transceiver, a processor and a memory, wherein the memory is in communication connection with the processor; The processor executes the computer-executable instructions stored in the memory to implement the method for predicting remaining life of a lithium battery as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, wherein computer-executable instructions are stored in the computer-readable storage medium, which when executed by a processor, are configured to implement the method for predicting remaining life of a lithium battery as claimed in any one of claims 1 to 7.

Description

Method, device, equipment, medium and product for predicting residual life of lithium battery Technical Field The application relates to the technical field of lithium batteries, in particular to a method, a device, equipment, a medium and a product for predicting the residual life of a lithium battery. Background With the rapid development of lithium batteries, predicting the remaining life of lithium batteries by using a battery aging model has become an important research hotspot in the field of lithium batteries. The existing battery aging model mainly uses empirical values or tangent points in an analysis lithium battery aging curve to determine turning points of a linear aging stage and a nonlinear aging stage, and uses the determined turning points and a preset mathematical formula to calculate the residual life of the lithium battery. However, the existing battery aging model does not consider the aging mechanism of the lithium battery, resulting in lower prediction accuracy of the remaining life of the lithium battery. Disclosure of Invention The embodiment of the application provides a method, a device, equipment, a medium and a product for predicting the residual life of a lithium battery, which are used for improving the prediction accuracy of the residual life of the lithium battery. In a first aspect, an embodiment of the present application provides a method for predicting a remaining life of a lithium battery, including: Acquiring the current performance parameters of the lithium battery; According to the performance parameters and the environmental temperature of the lithium battery, a preset two-stage aging model is adopted to process the performance parameters and the environmental temperature, and a capacity attenuation accumulated value of the lithium battery under the current charge and discharge accumulated times is obtained; Obtaining a residual life prediction result according to the capacity attenuation accumulated value, wherein the residual life prediction result comprises a first charge and discharge accumulated time corresponding to an end life EoL point; Wherein the two-stage aging model is a pseudo two-dimensional P2D model constructed to determine the cumulative value of capacity fade based on active lithium loss due to solid electrolyte interface film SEI and active lithium loss due to lithium deposition. In one possible design of the first aspect, the remaining life prediction result further includes a second charge-discharge accumulated number corresponding to a Knee point of the lithium battery; The method further comprises the steps of: And if the current charge-discharge accumulated times reach the second charge-discharge accumulated times, outputting a lithium battery using strategy, wherein the battery using strategy comprises at least one using mode for slowing down the aging of the lithium battery. In one possible design of the first aspect, the method further comprises: Inputting the performance parameters and the environmental temperature of the lithium battery into the two-stage aging model to obtain a first capacity attenuation accumulated value and a second capacity attenuation accumulated value of the lithium battery under the current charge and discharge accumulated times, wherein the first capacity attenuation accumulated value is used for representing the total capacity attenuation value of the lithium battery caused by the solid electrolyte interface film SEI, and the second capacity attenuation accumulated value is used for representing the total capacity attenuation value of the lithium battery caused by lithium deposition; Calculating a first capacity fading variation value and a second capacity fading variation value between adjacent charge and discharge times according to the first capacity fading integration value and the second capacity fading integration value; If the first capacity attenuation change value is smaller than the second capacity attenuation change value, determining the current charge and discharge accumulated times as the second charge and discharge accumulated times; And if the total capacity attenuation accumulated value between the first capacity attenuation accumulated value and the second capacity attenuation accumulated value is larger than or equal to the preset capacity attenuation threshold value of the lithium battery, determining the current charge and discharge accumulated times as the first charge and discharge accumulated times. In one possible design of the first aspect, the two-stage aging model obtaining process includes: acquiring a preset pseudo two-dimensional P2D model; Determining a target coefficient configuration scheme of a target fitting function in the pseudo two-dimensional P2D model; and configuring coefficients in the target fitting function according to the target coefficient configuration scheme to obtain the two-stage aging model. In one possible design of the first aspect, the determining a target c