CN111974709A - Retired power lithium battery screening method and system based on temperature change cluster analysis - Google Patents
Retired power lithium battery screening method and system based on temperature change cluster analysis Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
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- B07C5/344—Sorting according to other particular properties according to electric or electromagnetic properties
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/34—Sorting according to other particular properties
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- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
- H01M10/4207—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells for several batteries or cells simultaneously or sequentially
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
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Abstract
The invention discloses a retired power lithium battery screening method based on temperature change cluster analysis, which is used for designing a test working condition aiming at a retired power lithium battery screening process; extracting the battery capacity from the test process, and carrying out first-level screening; extracting the internal resistance of the battery and carrying out second-level screening; on the basis, the change of the temperature in the testing process is recorded by using infrared thermal imaging, the variation coefficient and the information entropy are respectively calculated according to the change characteristics of the temperature, and the screening of the third level is completed by clustering operation analysis to obtain the retired battery cell with better consistency of electrical and thermal characteristics. The retired power lithium battery screening system based on temperature change cluster analysis comprises a data acquisition module, an infrared imaging module, a calculation module and a screening module. The invention can select the battery monomers with more uniform thermal characteristics to form the battery pack on the basis of ensuring the consistent electrical characteristics of the retired power lithium batteries, so as to improve the efficiency of utilizing the battery pack in a gradient manner.
Description
Technical Field
The invention belongs to the field of gradient utilization of retired power lithium batteries, and particularly relates to a retired power lithium battery screening method based on temperature change cluster analysis.
Background
In recent years, the holding quantity of domestic new energy automobiles is rapidly increased, and China becomes a main market of global new energy automobiles. As the most important energy storage element of a new energy automobile, a power lithium battery is inevitably and continuously aged in the use process. The potential safety risk can also be produced to the lithium cell of overusing in new energy automobile. Therefore, the power battery with the capacity retention rate lower than the specific value should be retired from the new energy automobile in time to ensure the use safety of the automobile. Therefore, the large number of new energy automobiles also means that a large number of retired power lithium batteries are generated in the future.
The retired power lithium battery still has a certain potential application value, and the retired lithium battery from the new energy automobile still has the potential value of being continuously used in scenes such as low-speed vehicles and fixed energy storage. However, the aging degree of the retired battery cells is often not uniform, and the first step of performing echelon utilization on the power lithium battery is to screen all the retired cells, find out the cells with better performance and consistency, and form a new battery pack. The key technology of the echelon utilization link for the retired power lithium battery is that currently, screening for the retired power lithium battery is carried out only according to the electrical characteristics of the retired power lithium battery, if: capacity, internal resistance, etc., without taking into account the thermal characteristics of the battery. The batteries with better electrical characteristics cannot be sorted out completely and accurately, and battery monomers with more uniform thermal characteristics are not convenient to find. The difficulty of thermal management of the subsequent retired power lithium battery pack can not be reduced while the consistency of the battery monomers is guaranteed.
Disclosure of Invention
The invention provides a retired power lithium battery screening method based on temperature change cluster analysis, and solves the technical problem that thermal characteristics of batteries are not considered during retired power lithium battery screening.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows: a retired power lithium battery screening method based on temperature change cluster analysis comprises the following steps:
designing a test working condition, and acquiring original data of the retired power lithium battery to be screened in the test process, wherein the original data comprises battery capacity, battery direct-current internal resistance and battery temperature change;
extracting battery capacity from the original data, and performing first-level screening;
extracting the direct current internal resistance of the battery based on the first-level screening, and performing second-level screening;
and recording a temperature change curve of the battery in the test process based on the second-level screening, respectively calculating the variation coefficient and the information entropy of the temperature change according to the temperature change curve, performing cluster analysis, completing the third-level screening, and obtaining the required retired power lithium battery monomer.
Further, the test working condition comprises a charge-discharge test on the retired power lithium battery to be screened; in the testing process, collecting the current and the voltage of the retired power lithium battery to be screened through a data acquisition module, wherein the current and the voltage are used for calculating the battery capacity and the direct current internal resistance of the battery; and in the test process, the temperature change of the battery is obtained through the infrared imaging module.
Further, the battery capacity is tested in a standard constant current and constant voltage charging process; the method for obtaining the direct current internal resistance of the battery comprises the following steps: after the battery is discharged to a charge state, measuring the direct current internal resistance under each current multiplying power by adopting short-time current pulse combination with different amplitudes, and solving an average value to obtain the direct current internal resistance of the battery; the temperature change of the battery is specifically as follows: and injecting bipolar current pulses into the battery temperature change in the process of decommissioning the power battery.
Further, the calculation formula of the battery capacity is as follows
In the formula: qiCalculated capacity, t, for the ith cell1Is the starting time of the constant current and constant voltage charging process,t2the cut-off time of the constant-current constant-voltage charging process, i (t), is the current of the charging process.
Further, the calculation formula of the direct current internal resistance under each current multiplying power is as follows
In the formula: rnCFor the direct current internal resistance under each current multiplying power, the delta U and the delta I are respectively the variation of the current and the voltage corresponding to the two ends of the battery at the current pulse jumping moment.
Further, the calculation formula of the coefficient of variation is as follows
In the formula, CvThat is, the coefficient of variation, σ is the standard deviation of the temperature variation, and μ is the average value of the temperature variation.
Further, the calculation formula of the information entropy is as follows
In the formula: hTFor information entropy, p (T)i) Truncate T for data roundingiProbability of occurrence, [ T1，T1+ΔT]Temperature variation range, T, for retired power lithium batteriesiThe original measurement data of the temperature is rounded and truncated to the temperature change interval corresponding to the delta T unit step size.
Further, said p (T)i) Is calculated as follows
In the formula: n is a radical oftNumber of total sampling points for temperature change, ntiMeasured for battery temperature variationTo the number of data points.
A retired power lithium battery screening system based on temperature change cluster analysis comprises
The data acquisition module is used for collecting the current and the voltage of the retired power lithium battery to be screened;
the infrared imaging module is used for acquiring the temperature change of the battery;
the calculation module is used for calculating the battery capacity, the battery direct-current internal resistance and the temperature change characteristics of the retired power lithium battery to be screened;
and the screening module is used for screening out the required retired power lithium battery meeting the requirement.
Further, the temperature variation characteristics include a variation coefficient and information entropy of the temperature variation.
The invention achieves the following beneficial effects: by designing a specific test working condition, recording the temperature change process of the lithium battery by using infrared imaging, extracting temperature characteristics on the basis of screening the capacity and the internal resistance of the battery, and screening the thermal characteristics of the retired power lithium battery. By using the screening method provided by the invention, battery monomers with more uniform thermal characteristics can be selected to form the battery pack on the basis of ensuring the consistency of the electrical characteristics of the retired power lithium battery, so that the efficiency of utilizing the battery pack in a gradient manner is improved, and the difficulty of thermal management of the battery pack is reduced. The invention has important significance for the echelon utilization of the retired power lithium battery.
Drawings
FIG. 1 is a schematic diagram of a battery screening method according to an embodiment of the present invention;
FIG. 2 is a test condition diagram of the screening of the retired power lithium battery in the embodiment of the invention;
FIG. 3 is a schematic diagram of a battery screening system according to an embodiment of the invention.
Detailed Description
The invention is further described below. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
As shown in fig. 1, a retired power lithium battery screening method based on temperature change cluster analysis includes the following steps:
designing a test working condition, and acquiring original data of the retired power lithium battery to be screened in the test process, wherein the original data comprises battery capacity, battery direct-current internal resistance and battery temperature change;
extracting battery capacity from the original data, and performing first-level screening;
extracting the direct current internal resistance of the battery based on the first-level screening, and performing second-level screening;
and recording a temperature change curve of the battery in the test process based on the second-level screening, respectively calculating a variation coefficient and an information entropy according to the temperature change curve, performing cluster analysis, completing third-level screening, and obtaining the required retired power lithium battery monomer.
Examples 1,
As shown in fig. 2, the numbers in the figure represent the corresponding steps. This embodiment provides the concrete step of test operating mode:
1. charging the battery to an allowable maximum voltage V at a constant current of 1Cmax；
2. Maintaining the terminal voltage of the battery at VmaxContinuing to charge until the current is less than 0.02A, and stopping charging;
3. standing the battery for 2 hours;
4. discharging the battery to a state of charge SOC of 50% at a current rate of 1/3C;
5. standing the battery for 1 hour;
6. charging the battery with 1/4C current pulses for 20 seconds;
7. standing the battery for 10 minutes;
8. discharging the battery at current multiplying power of 1/4C for 20 seconds;
9. standing the battery for 10 minutes;
10. charging the battery with 1/2C current pulses for 20 seconds;
11. standing the battery for 10 minutes;
12. discharging the battery with 1/2C current pulses for 20 seconds;
13. standing the battery for 10 minutes;
14. charging the battery with a 1C current pulse for a duration of 20 seconds;
15. standing the battery for 10 minutes;
16. discharging the battery with 1C current pulse for 20 seconds;
17. the cell was left for 1 hour and the temperature of the cell was recorded as T1；
18. Applying a frequency f to the cellIWhen the battery temperature changes by more than delta T, stopping current pulse injection;
19. standing the battery, recording the temperature change until the temperature of the battery is recovered to T1。
In this embodiment, the operating conditions mainly include a discharging process for testing the battery capacity, a mixed pulse test for testing the internal resistance of the battery, and a bipolar current injection for exciting the battery to generate a corresponding temperature change. The capacity test is a standard constant-current constant-voltage charging process of 1C current, and the direct-current internal resistance test is to charge the battery to SOCm50 percent; then, a series of short-time current pulse combinations with different amplitudes are adopted, the direct current internal resistance under each current multiplying power is measured, and the direct current internal resistance of the battery is obtained by averaging; finally, the frequency f is selectedIAnd injecting bipolar current square wave pulses of 10Hz into the retired power battery for heating until the temperature of the battery rises by delta T to 5 ℃.
Examples 2,
The embodiment provides a retired power lithium battery screening method based on temperature change cluster analysis, which comprises the following steps of:
1) screening the retired power lithium battery in the first layer: and (5) screening the battery capacity. Before the constant-current constant-voltage charging of the battery, the battery is discharged to a cut-off voltage, and the capacity of the battery is calculated according to the following formula
In the formula, QiCalculated capacity, t, for the ith cell1For constant current and voltage chargingStarting time of course, t2The cut-off time of the constant-current constant-voltage charging process, i (t), is the current of the charging process.
According to the calculated integral distribution of all retired power lithium battery capacities, selecting [ Q ]min,Qmax]N within the rangeQBlock retired power lithium battery, wherein NQThe number of the single cells M required by the battery grouping in the subsequent echelon utilization is larger than that.
2) And (3) screening the retired power lithium battery at a second level: and (4) screening direct current internal resistance of the battery. After the battery is discharged to a charge state, calculating the direct current internal resistance of the battery corresponding to each current pulse by adopting short-time current pulse combination with different amplitudes, wherein the specific calculation method is shown as the following formula:
in the formula, RnCFor the direct current internal resistance under each current multiplying power, the delta U and the delta I are respectively the variation of the current and the voltage corresponding to the two ends of the battery at the current pulse jumping moment.
From the above formula, R can be calculated from the measurement data obtainedI1、RI2And RI3. In order to avoid measurement errors as much as possible, the internal resistance of the battery used by the invention is an average value of the internal resistance of the battery obtained by measurement under different multiplying powers.
Ri＝(RI1+RI2+RI3)/3
In the formula, RiThe calculated average value of the internal resistances of the batteries is obtained.
Selecting [ R ] according to the calculated integral distribution of the direct current internal resistances of all the retired power lithium batteriesmin,Rmax]N within the rangeRBlock retired power lithium battery, wherein NRThe number of the single cells M required by the battery grouping in the subsequent echelon utilization is larger than that.
3) And (3) screening the retired power lithium battery in a third level: and (6) screening temperature characteristics. Recording a curve of battery temperature change caused in the process of injecting bipolar current pulses into the retired power lithium battery, calculating the statistical characteristics of the temperature change of the curve, using the statistical characteristics as input characteristic vectors of a clustering algorithm, and screening the finally needed retired power lithium battery monomer with better consistency through corresponding clustering operation. The temperature variation statistical characteristics are coefficient of variation and information entropy.
The coefficient of variation is defined as the ratio of standard deviation to mean, and is a description of the degree of discretization of the data, and is defined as follows:
in the formula, CvThat is, the coefficient of variation, σ is the standard deviation of the temperature variation, and μ is the average value of the temperature variation. As can be seen from the above formula, the coefficient of variation has integrated the information of both the standard deviation and the mean value during the temperature variation process.
The information entropy can reflect the uncertainty of the curve, and the temperature change range of the retired power lithium battery in the embodiment is [ T [ ]1，T1+ΔT]The total number of sampling points of temperature change is NtSelecting TstepFor statistical unit step sizes, each unit step size T can be obtainedstepIn the divided interval, the number n of data points obtained by measuring the temperature change of the batterytiSimultaneously rounding and truncating the original temperature measurement data to an interval corresponding to each step length, and recording the interval as Ti. The information entropy of the temperature change is then:
in the formula: p (T)i) Truncate T for data roundingiProbability of occurrence, HTIs the information entropy calculated by the temperature variation process.
Through the calculation, the mth decommissioned power lithium can be obtainedInput feature vector F for clustering by batterym＝[Cv,HT]m. Therefore, screening of the retired power lithium battery is achieved by using a K-Means clustering algorithm. After the cluster analysis of the temperature change process of the retired power lithium battery is completed, the retired batteries in the same classification set can be selected to be grouped according to the result, so that the electrical and thermal characteristics are better consistent.
The method for screening the temperature change of the retired power lithium battery through the K-Means clustering algorithm comprises the following steps:
1. normalizing each variable in the input feature vector, which is specifically shown as the following formula:
in the formula, X is a corresponding index, XminIs the minimum value of each index, XmaxIs the maximum value of each index, XnormIs an index after normalization. Obtaining normalized input feature vector Fm_norm＝[Cv_norm,HT_norm]m。
2. Setting K classifications Ci＝{C1，C2，…，Ck}, randomly initializing centroid ui(i ═ 1,2, … k), the distance of each feature vector from the centroid is calculated. In this embodiment, Euclidean distance is used as a metric, and each feature vector FmWith the centre of mass uiThe specific calculation of the distance is shown below:
f is to bem_normAnd classifying into the class to which the centroid closest to the centroid belongs.
3. According to each classification CiAnd recalculating the centroid of each classification for all the feature vectors, which is specifically shown as the following formula:
wherein L isiThe number of feature vectors in each class.
4. If the centroid change is smaller than a certain specific value delta x, the clustering is considered to be finished; otherwise, jumping to the step 2, and continuously calculating the Euclidean distance and the centroids of the K classifications.
After cluster analysis of the temperature change process of the retired power lithium battery, retired batteries in the same class can be selected as much as possible to be grouped according to results so as to ensure better consistency in electrical and thermal characteristics.
Examples 3,
The embodiment provides a retired power lithium battery screening system based on temperature change cluster analysis, which as shown in fig. 3, includes
The data acquisition module is used for collecting the current and the voltage of the retired power lithium battery to be screened;
the infrared imaging module is used for acquiring the temperature change of the battery;
the calculation module is used for calculating the battery capacity, the battery direct-current internal resistance and the temperature change characteristics of the retired power lithium battery to be screened;
and the screening module is used for screening out the required retired power lithium battery meeting the requirement.
Specifically, a specific test working condition is set in the power unit in advance, and the retired power lithium battery is subjected to charge and discharge tests. On the basis, measurement data such as current and voltage of the retired power lithium battery are collected through a data acquisition system and are used for calculating the capacity and the internal resistance of the battery. Meanwhile, the temperature change condition of the lithium battery is obtained by utilizing an infrared imaging technology, and the temperature data is transmitted to an upper computer. The upper computer completes screening of the retired power lithium battery through three main links of capacity screening, internal resistance screening and temperature characteristic screening respectively based on the data information so as to facilitate gradient utilization of the subsequent retired battery.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A retired power lithium battery screening method based on temperature change cluster analysis is characterized by comprising the following steps:
designing a test working condition, and acquiring original data of the retired power lithium battery to be screened in the test process, wherein the original data comprises battery capacity, battery direct-current internal resistance and battery temperature change;
extracting battery capacity from the original data, and performing first-level screening;
extracting the direct current internal resistance of the battery based on the first-level screening, and performing second-level screening;
and recording a temperature change curve of the battery in the test process based on the second-level screening, respectively calculating the variation coefficient and the information entropy of the temperature change according to the temperature change curve, performing cluster analysis, completing the third-level screening, and obtaining the required retired power lithium battery monomer.
2. The method for screening retired dynamic lithium battery based on temperature change cluster analysis according to claim 1, wherein the test condition comprises a charge-discharge test of the retired dynamic lithium battery to be screened; in the testing process, collecting the current and the voltage of the retired power lithium battery to be screened through a data acquisition module, wherein the current and the voltage are used for calculating the battery capacity and the direct current internal resistance of the battery; and in the test process, the temperature change of the battery is obtained through the infrared imaging module.
3. The method for screening retired dynamic lithium battery based on temperature change cluster analysis according to claim 1, wherein the battery capacity is tested in a standard constant-current constant-voltage charging process; the method for obtaining the direct current internal resistance of the battery comprises the following steps: after the battery is discharged to a charge state, measuring the direct current internal resistance under each current multiplying power by adopting short-time current pulse combination with different amplitudes, and solving an average value to obtain the direct current internal resistance of the battery; the temperature change of the battery is specifically as follows: and injecting bipolar current pulses into the battery temperature change in the process of decommissioning the power battery.
4. The method for screening retired dynamic lithium battery based on temperature change cluster analysis as claimed in claim 1, wherein the calculation formula of battery capacity is as follows
In the formula: qiCalculated capacity, t, for the ith cell1Is the starting time of the constant current and constant voltage charging process, t2The cut-off time of the constant-current constant-voltage charging process, i (t), is the current of the charging process.
5. The method for screening retired power lithium battery based on temperature change cluster analysis as claimed in claim 1, wherein the direct current internal resistance under each current rate is calculated according to the following formula
In the formula: rnCFor the direct current internal resistance under each current multiplying power, the delta U and the delta I are respectively the variation of the current and the voltage corresponding to the two ends of the battery at the current pulse jumping moment.
6. The method for screening retired dynamic lithium battery based on temperature change cluster analysis as claimed in claim 1, wherein the coefficient of variation is calculated as follows
In the formula, CvThat is, the coefficient of variation, σ is the standard deviation of the temperature variation, and μ is the average value of the temperature variation.
7. The method for screening retired dynamic lithium battery based on temperature change cluster analysis as claimed in claim 1, wherein the formula for calculating the entropy of information is as follows
In the formula: hTFor information entropy, p (T)i) Truncate T for data roundingiProbability of occurrence, [ T1，T1+ΔT]Temperature variation range, T, for retired power lithium batteriesiThe original measurement data of the temperature is rounded and truncated to the temperature change interval corresponding to the delta T unit step size.
8. The method for screening retired dynamic lithium battery based on temperature change cluster analysis of claim 7, wherein p (T) isi) Is calculated as follows
In the formula: n is a radical oftNumber of total sampling points for temperature change, ntiThe number of data points is obtained for the battery temperature change measurement.
9. A retired power lithium battery screening system based on temperature change cluster analysis is characterized by comprising
The data acquisition module is used for collecting the current and the voltage of the retired power lithium battery to be screened;
the infrared imaging module is used for acquiring the temperature change of the battery;
the calculation module is used for calculating the battery capacity, the battery direct-current internal resistance and the temperature change characteristics of the retired power lithium battery to be screened;
and the screening module is used for screening out the required retired power lithium battery meeting the requirement.
10. The retired dynamic lithium battery screening system based on temperature change cluster analysis of claim 9, wherein the temperature change characteristics comprise a variation coefficient and an information entropy of temperature change.
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| CN114833097A (en) * | 2022-05-05 | 2022-08-02 | 合肥工业大学 | Sorting method and device for gradient utilization of retired power batteries |
| CN115166563A (en) * | 2022-08-17 | 2022-10-11 | 山东大学 | Power battery aging state evaluation and decommissioning screening method and system |
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