CN-121997087-A - Sorting method, equipment and medium for retired lithium battery under multiple temperature areas

CN121997087ACN 121997087 ACN121997087 ACN 121997087ACN-121997087-A

Abstract

The application discloses a method, equipment and medium for sorting retired lithium batteries in multiple temperature areas, which relate to the field of battery recycling, and comprise the following steps: converting voltage-capacity data at each temperature into an incremental capacity curve for each retired lithium battery to extract IC features respectively; the method comprises the steps of constructing a temperature response differential feature set and a temperature stability index set according to IC features at each temperature, obtaining multi-temperature-domain feature vectors based on the temperature response differential feature set, the temperature stability index set and the IC features at each temperature, carrying out weighting treatment on each feature distribution weight in a multi-temperature-domain feature matrix to obtain a weighted feature matrix, carrying out abnormal recognition on a plurality of retired lithium batteries based on the weighted feature matrix to remove noise samples, carrying out clustering treatment on the rest of retired lithium batteries, and dividing the rest of retired lithium batteries into corresponding class labels, and enhancing the discrimination capability and the application range of the feature system and improving the accuracy and the stability of sorting results by incorporating the temperature dimensions into a sorting decision process.

Inventors

ZHANG ZHEMING
LUO ZHENYU
ZHUANG XUNING
JIAO XIAOJUAN
FAN GUOPING

Assignees

正通(深圳)循环科技有限公司

Dates

Publication Date: 20260508
Application Date: 20260408

Claims (10)

1. The method for sorting the retired lithium battery under the multi-temperature range is characterized by comprising the following steps of: Performing charge and discharge tests on a plurality of retired lithium batteries at different temperatures to obtain voltage-capacity data of each retired lithium battery at each temperature; converting the voltage-capacity data at each temperature into an incremental capacity curve to extract IC characteristics respectively, constructing a temperature response differential characteristic set and a temperature stability index set according to the IC characteristics at each temperature, and obtaining a multi-temperature domain characteristic vector based on the temperature response differential characteristic set, the temperature stability index set and the IC characteristics at each temperature; combining the multi-temperature-domain feature vectors of all the retired lithium batteries into a multi-temperature-domain feature matrix, and carrying out weighting treatment on each feature distribution weight in the multi-temperature-domain feature matrix to obtain a weighted feature matrix; And carrying out anomaly recognition on a plurality of retired lithium batteries based on the weighted feature matrix to remove noise samples, carrying out clustering processing on the rest plurality of retired lithium batteries, and dividing the rest plurality of retired lithium batteries into corresponding class labels.
2. The method of claim 1, wherein the IC characteristics include principal peak voltage, principal peak amplitude, peak-to-peak voltage difference, peak ratio, peak number, IC energy and capacity normalized peak.
3. The method for sorting retired lithium batteries in multiple temperature zones according to claim 1, wherein the temperature response differential feature set comprises a temperature differential feature set and a temperature response slope set; The calculation expression of the differential characteristic value in the temperature differential characteristic group is as follows: ; The calculation expression of the response slope value in the temperature response slope group is as follows: ; in the formula, As a specific one of the features of the IC, At a temperature of And temperature The following differential eigenvalues, representing the specific features The absolute amount of change with temperature change, At a temperature of Specific features measured below Is a function of the number of (c), At a temperature of Specific features measured below Is a function of the number of (c), Is characterized by Response slope value as a function of temperature.
4. The method for sorting out lithium batteries under multiple temperature ranges according to claim 1, wherein the temperature stability index value in the temperature stability index set is calculated as: ; in the formula, Is the first A temperature stability index value for a particular one of the IC features corresponding to the individual cells, For the purpose of the temperature index, As a total number of temperatures, Is the first The individual cells are at temperature The value of a particular one of the following IC features, Is the first One specific feature of each cell is the average value at all temperatures.
5. The method for sorting out retired lithium batteries in multiple temperature ranges according to claim 1, wherein the steps of identifying anomalies of the plurality of retired lithium batteries based on the weighted feature matrix to reject noise samples, clustering the remaining plurality of retired lithium batteries, and classifying the rest of retired lithium batteries into corresponding class labels specifically comprise: Based on the weighted feature matrix, performing anomaly identification by adopting a DBSCAN algorithm to obtain initial clustering labels of a plurality of retired lithium batteries, and removing samples with the labels being noise; Clustering a plurality of the retired lithium batteries remained after the noise sample is removed by adopting an FCM algorithm to obtain membership of each retired lithium battery relative to different clustering centers so as to divide each retired lithium battery into corresponding class labels.
6. The method of sorting retired lithium batteries in multiple temperature zones according to claim 5, further comprising, after the step of classifying each retired lithium battery into a corresponding class label: performing quality evaluation on clustering results of the rest plurality of retired lithium batteries by adopting profile coefficients and DB indexes; Constructing a comprehensive scoring function, and calculating comprehensive scoring values of the rest plurality of retired lithium batteries according to the comprehensive scoring function; And sequencing the rest plurality of retired lithium batteries according to the comprehensive grading value, and classifying the retired lithium batteries into different grades according to the sequencing result.
7. The method for sorting retired lithium batteries in multiple temperature zones according to claim 6, wherein the calculation expression of the comprehensive scoring function is: ; in the formula, A comprehensive score value for the ith battery, i being a battery sample index, For the average discharge capacity of the ith cell at multiple temperatures, For the average IC energy of the ith cell at multiple temperatures, Is the integrated temperature stability index of the ith cell, For the distance of the ith cell to the cluster center to which it belongs, , Is the feature vector of the i-th battery, Is that The cluster number to which the cluster belongs is given, Is that The cluster center of the cluster to which the cluster belongs, 、、 And Is a weight coefficient.
8. The method for sorting out of service lithium batteries under multiple temperature ranges according to claim 1, further comprising, before performing a charge-discharge test on the out of service lithium batteries: And performing appearance detection and performance detection on the retired lithium battery to remove the retired lithium battery with abnormal appearance and abnormal performance, wherein the performance detection comprises open circuit voltage detection and internal resistance detection.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the method of sorting retired lithium batteries in multiple temperature zones according to any one of claims 1-8.
10. A computer readable storage medium having stored thereon a computer program, which when executed by a processor, implements a method for sorting retired lithium batteries in a multi-temperature range according to any of claims 1-8.

Description

Sorting method, equipment and medium for retired lithium battery under multiple temperature areas Technical Field The application relates to the field of battery recovery, in particular to a method, equipment and medium for sorting retired lithium batteries in multiple temperature ranges. Background Along with acceleration of global energy structures to low carbonization and intelligent transformation, new energy automobiles become important forces for pushing energy revolution and reducing carbon emission in the traffic field. The lithium ion battery has become a core component of a power system of a new energy automobile by virtue of the advantages of high energy density, long cycle life, low self-discharge rate and the like. Most power cells will gradually decay in performance and safety over time during operation, typically reaching retirement standards after 8-10 years of operation. At present, the rapid development of new energy automobiles leads a large number of power batteries to be retired, and the retired batteries still generally have about 70% -80% of residual capacity, thus the new energy automobiles have remarkable economic value and resource potential. The safety and the economical efficiency of the comprehensive utilization system of the waste power batteries are highly dependent on the consistency sorting process of the retired batteries. Direct assembly without sorting can lead to low capacity utilization of the battery pack and large local temperature differences, thereby causing safety risks. In the traditional sorting method, the corresponding threshold value is set according to experience under the normal temperature environment to screen the battery, the response characteristic of the battery performance along with the temperature change under the actual working condition can not be reflected, and the rapid differentiation of the performance of the sorting result occurs due to insufficient temperature adaptability in the application process. Disclosure of Invention The application aims to provide a sorting method, equipment and medium for retired lithium batteries in multiple temperature ranges, which can solve the problems, and realize more reliable battery consistency sorting by analyzing and sorting performance characteristics of the batteries in multiple temperature ranges. In order to achieve the above object, the present application provides the following solutions: in a first aspect, the application provides a method for sorting retired lithium batteries in multiple temperature ranges, comprising: Performing charge and discharge tests on a plurality of retired lithium batteries at different temperatures to obtain voltage-capacity data of each retired lithium battery at each temperature; converting the voltage-capacity data at each temperature into an incremental capacity curve to extract IC characteristics respectively, constructing a temperature response differential characteristic set and a temperature stability index set according to the IC characteristics at each temperature, and obtaining a multi-temperature domain characteristic vector based on the temperature response differential characteristic set, the temperature stability index set and the IC characteristics at each temperature; combining the multi-temperature-domain feature vectors of all the retired lithium batteries into a multi-temperature-domain feature matrix, and carrying out weighting treatment on each feature distribution weight in the multi-temperature-domain feature matrix to obtain a weighted feature matrix; And carrying out anomaly recognition on a plurality of retired lithium batteries based on the weighted feature matrix to remove noise samples, carrying out clustering processing on the rest plurality of retired lithium batteries, and dividing the rest plurality of retired lithium batteries into corresponding class labels. In one embodiment, the IC characteristics include a main peak voltage, a main peak amplitude, a peak-to-peak voltage difference, a peak ratio, a number of peaks, an IC energy, and a capacity normalized peak. In one embodiment, the temperature response differential feature set includes a temperature differential feature set and a temperature response slope set; The calculation expression of the differential characteristic value in the temperature differential characteristic group is as follows: ; The calculation expression of the response slope value in the temperature response slope group is as follows: ; in the formula, As a specific one of the features of the IC,At a temperature ofAnd temperatureThe following differential eigenvalues, representing the specific featuresThe absolute amount of change with temperature change,At a temperature ofSpecific features measured belowIs a function of the number of (c),At a temperature ofSpecific features measured belowIs a function of the number of (c),Is characterized byResponse slope value as a function of temperature. In one embodiment, the