CN115889245A - Lithium battery consistency sorting method - Google Patents
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Abstract
The invention provides a lithium battery consistency sorting method, which comprises the following steps: s1: carrying out a charge-discharge experiment on the batteries to be sorted according to the normal charge-discharge multiplying power; s2: the measured static parameters of each battery and a fuzzy C-means (FCM) clustering algorithm are utilized to carry out primary sorting on the batteries; s3: and carrying out secondary sorting on various batteries subjected to primary sorting by utilizing the charge-discharge voltage curves of the batteries. This application easy operation only needs to carry out once and charges and discharges the experiment, need not to measure the internal resistance of battery. Compared with the traditional separation method, the separation effect is better, the capacity reduction phenomenon after the batteries are grouped is greatly reduced, the initial capacity of the battery pack is improved, and the voltage difference of each single battery in the charging and discharging process of the battery pack is greatly reduced.
Description
Technical Field
The invention relates to the field of lithium ion battery monomer sorting, in particular to a lithium battery consistency sorting method.
Background
At present, lithium ion batteries are widely applied to the fields of electric vehicles, power grid energy storage and the like due to superior performance of the lithium ion batteries so as to deal with increasingly serious environmental pollution and energy crisis. Due to the high requirements of application scenarios on voltage and power, a plurality of battery cells are generally required to be connected in series and in parallel to be used in a group. However, research and practice show that the performance and the service life of the lithium ion battery after being grouped are greatly attenuated compared with those of single batteries, and safety problems are more likely to occur, and the main reason is that consistency differences exist among the single batteries forming the battery pack, namely, differences of performance index parameters such as capacity, internal resistance, self-discharge rate, aging characteristics and electrical characteristics of electrodes among the single batteries.
There are three main methods of improving the uniformity of the battery pack in principle. Firstly, the production process is improved, the manufacturing level of the lithium ion battery is improved, and therefore the initial consistency difference between the lithium ion battery monomers is reduced. And secondly, carrying out consistency sorting on the single lithium ion batteries before grouping to group the single lithium ion batteries with small consistency difference. And finally, carrying out balanced management on the lithium ion battery pack, and ensuring that the consistency of the battery pack in the use process is not too low as much as possible. Since increasing the level of the production process greatly increases the production cost and cannot be realized in a short time, the latter two methods are mainly used at present.
For the sorting method of the lithium ion battery, the traditional sorting method used by the battery manufacturer at present is mainly to simply sort and match the battery according to the difference range among the set voltage, internal resistance and capacity of the battery, the operation is simple, but the performance characteristics of the battery cannot be comprehensively reflected, the sorting precision is limited, and the method has a great promotion space.
The sorting parameters used by the traditional sorting method are all static indexes of the battery, and the dynamic characteristics of the battery in working cannot be fully reflected. The charging and discharging curve of the lithium ion battery can comprehensively reflect the dynamic characteristics of the battery in the charging and discharging process, so that the secondary sorting of the battery is carried out according to the voltage curve in the charging and discharging process of the battery after the battery is sorted by using the static parameters, thereby improving the sorting effect.
Disclosure of Invention
In order to overcome the problems in the prior art, the invention provides a method for sorting lithium ion batteries with more consistent overall performance by using static parameters and dynamic characteristics of the lithium ion batteries simultaneously so as to form a battery pack with better performance.
In order to realize the purpose, the invention provides the following technical scheme: a lithium battery consistency sorting method comprises the following steps:
s1: carrying out a charge-discharge experiment on the batteries to be sorted according to the normal charge-discharge multiplying power; measuring static parameters of each battery and a charge-discharge voltage curve capable of reflecting the dynamic characteristics of the battery;
s2: preliminarily sorting the batteries by using the measured static parameters of each battery and a fuzzy C-means (FCM) clustering algorithm;
s3: and carrying out secondary sorting on various batteries which are preliminarily classified by utilizing the charging and discharging voltage curves of the batteries.
The invention is further configured to: the method specifically comprises the following steps that all batteries to be sorted are fully charged under the same condition, then the batteries are subjected to constant current discharge at the same multiplying power at room temperature, and the discharge is finished when the batteries are cut to the voltage after the discharge; standing for 10min; and similarly, constant-current constant-voltage charging is carried out at the same multiplying power at room temperature, the charging is finished when the charging current is reduced to 0.05 ℃, and the static parameters of each battery and a charging and discharging voltage curve capable of showing the dynamic characteristics of the batteries are measured.
The invention is further configured to: the static parameters comprise charge capacity, discharge capacity, charge energy, discharge energy, and the ratio of constant current charge capacity to constant voltage charge capacity.
The invention is further configured to: the step S2 specifically comprises the following steps:
each cell is first represented by a feature vector formed by five static parameters measured.
X i ＝(x i1 ，x i2 ，x i3 ，x i4 ，x i5 )
In the formula, X i Representing the eigenvector, x, of the ith lithium ion cell i1 ,x i2 ,x i3 ,x i4 ,x i5 Sequentially representing five parameters of the charge capacity, the discharge capacity, the charge energy, the discharge energy and the ratio of the constant-current charge capacity to the constant-voltage charge capacity of the lithium ion battery;
this also normalizes the above parameters to eliminate dimensional differences between the sorting parameters, the normalization formula being as follows:
in the formula (I), the compound is shown in the specification,
is the k parameter, x, of the normalized i battery feature vector ik The kth parameter, x, of the ith cell feature vector before normalization k,max Is the maximum value, x, of the kth parameter of all cells k,min The minimum value of the kth parameters of all the batteries;
at the moment, n batteries to be sorted can be converted into an n multiplied by 5 dimensional characteristic matrix, and the characteristic matrix is used as the input of an FCM algorithm;
setting a final clustering number according to the number of batteries to be sorted and the number of single batteries of the battery pack, initializing a membership matrix by random assignment of a computer, setting an algorithm iteration stop condition, and taking Euclidean distance as a distance calculation formula of the single batteries and a clustering center in the FCM clustering process:
in the formula (I), the compound is shown in the specification,
for the kth parameter of the normalized ith cell feature vector>
The k characteristic value of the jth clustering center in the FCM algorithm is obtained;
and iterating according to the FCM until an iteration stop condition is met, and classifying each battery into the type with the maximum membership according to the membership matrix of the last iteration, thereby finishing the primary classification of the batteries.
The invention is further configured to: the step S3 specifically includes the following steps:
s301, extracting curve characteristics;
s302, setting a sorting similarity threshold u, and simultaneously selecting a lithium ion battery as a first standard battery;
s303, selecting a battery with the minimum serial number from the remaining unsorted batteries as a current battery, and calculating the similarity between the battery and each standard battery;
s304, comparing the maximum similarity S max The similarity threshold u can be automatically determined according to the number of batteries to be sorted and the sorting required precision in actual application with the set similarity threshold u;
s305, judging whether unclassified batteries exist at present. If yes, returning to the step S302; if not, outputting a classification result;
the invention is further configured to: step S301 specifically includes:
supposing that n lithium ion batteries to be sorted are arranged, the total sampling point number is p; (ii) a The charging and discharging voltage curves of all the batteries can be converted into an n multiplied by p dimensional characteristic matrix, and the similarity degree between the charging and discharging voltage curves of the ith battery and the jth battery can be represented by the similarity degree between the ith row and the jth row in the matrix X;
here, the similarity between the batteries is calculated by using the euclidean distance:
because the performances of the batteries are different, the charging and discharging processes are different, and the measured overall charging and discharging voltage curve of each lithium ion battery is segmented into a charging stage voltage curve, a discharging stage voltage curve and a resting voltage curve. Because the curve itself can not be directly used for sorting, the voltage curve of each battery at the same stage is sampled at the same time interval to form a characteristic vector representing the charge and discharge curve of each battery. In order to ensure that the characteristic vectors of the charge and discharge curves of the batteries contain the same quantity of characteristic parameters and consider that the charge, discharge and rest stages of the grouped batteries are synchronous, the time for reaching the charge cut-off voltage and the discharge cut-off voltage in all the batteries is taken as the upper sampling limit of the charge stage and the discharge stage.
The invention is further configured to: s304 comparing the maximum similarity S max The size of the similarity threshold u is specifically as follows: if S is max If u, the current battery is considered to be similar to the standard battery i enough, and the current battery is classified as the type of the standard battery i; if S is max If u, the current battery is not similar to all the current standard batteries enough, namely the current battery cannot be classified into any current standard battery, and therefore the current battery is taken as a new standard battery so as to avoid the situation that the batteries classified into one type are only relatively similar but not absolutely similar.
In summary, the technical scheme of the invention has the following beneficial effects:
1. the application is simpler to realize, and compared with the traditional separation method, the method only needs to carry out a charge-discharge experiment once and does not need to measure the internal resistance of the battery. The method comprises the following steps of selecting five parameters of charge capacity, discharge capacity, charge energy, discharge energy and the ratio of constant-current charge capacity to constant-voltage charge capacity in the charging process as static sorting parameters of the lithium ion battery, wherein the charge capacity, the discharge energy and the charge energy are one of the most basic and important performance parameters of the battery, and the consistency of the parameters represents the consistency of the battery performance to a great extent.
2. The lithium ion battery sorting method and device have the advantages that the parameter of the ratio of the constant-current charging capacity to the constant-voltage charging capacity is used for replacing the conventional internal resistance parameter for sorting the lithium ion battery, so that the parameter is obtained simply and conveniently and is accurate. The lithium ion battery has the advantages that the constant current charging process is a process of generating polarization of the battery, the constant voltage charging process is a process of eliminating polarization, and the shorter the constant voltage process time is, the smaller the polarization generated in the constant current process is, and the more ideal the battery performance is. In addition, because the battery has large current and high efficiency during constant-current charging and has small current and low efficiency during constant-voltage charging, the parameter of the ratio of the constant-current charging capacity to the constant-voltage charging capacity can also reflect the charging efficiency of the battery, and is very suitable for being used as the sorting parameter of the lithium ion battery.
3. Compared with the traditional separation method, the separation effect is better, the capacity reduction phenomenon after the batteries are grouped is greatly reduced, the initial capacity of the battery pack is improved, and the voltage difference of each single battery in the charging and discharging process of the battery pack is greatly reduced.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a general flow diagram of a consistent lithium battery sorting method according to the present invention;
FIG. 2 is a flow chart of preliminary sorting based on lithium ion battery static parameters and FCM clustering algorithm;
FIG. 3 is a sorting flow chart based on a charging and discharging voltage curve of a lithium ion battery;
fig. 4 is a charge-discharge voltage curve of all IFR32700 lithium ion cells in example 2 of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the following description of the technical solutions of the present invention with reference to the accompanying drawings of the present invention is made clearly and completely, and other similar embodiments obtained by a person of ordinary skill in the art without any creative effort based on the embodiments in the present application shall fall within the protection scope of the present application. In addition, directional terms such as "upper", "lower", "left", "right", etc. in the following embodiments are directions with reference to the drawings only, and thus, the directional terms used are intended to illustrate rather than limit the invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.
As used herein, the singular forms "a", "an" and "the" may include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises/comprising," "includes" or "including," etc., specify the presence of stated features, integers, steps, operations, components, parts, or combinations thereof, but do not preclude the presence or addition of one or more other features, integers, steps, operations, components, parts, or combinations thereof. Also, the terminology used in this specification includes any and all combinations of the associated listed items.
The invention is further described with reference to the drawings and the preferred embodiments.
Example 1:
as shown in fig. 1, a lithium battery consistent sorting method, which is a preferred embodiment of the present application, includes the following steps:
s1, carrying out one-time charge and discharge experiment on the batteries to be sorted according to normal charge and discharge multiplying power. The specific charge-discharge experimental process is as follows: fully charging all batteries to be sorted under the same condition, then carrying out constant current discharge on the batteries at the same rate at room temperature, and finishing the discharge when the batteries are cut to voltage after the discharge; standing for 10min; constant current and constant voltage charging was also performed at room temperature at the same rate, and the charging was terminated when the charging current dropped to 0.05C. Measuring static parameters of each battery, including charge capacity, discharge capacity, charge energy, discharge energy, the ratio of constant-current charge capacity to constant-voltage charge capacity, and a charge-discharge voltage curve capable of showing the dynamic characteristics of the battery;
and S2, preliminarily sorting the batteries by using the measured static parameters of each battery and a fuzzy C-mean (FCM) clustering algorithm. The specific implementation steps are shown in fig. 2:
each cell is first represented by a feature vector formed by five static parameters measured.
X i ＝(x i1 ，x i2 ，x i3 ，x i4 ，x i5 )
In the formula, X i Representing the eigenvector, x, of the ith lithium ion cell i1 ,x i2 ,x i3 ,x i4 ,x i5 Sequentially representing five parameters of the charge capacity, the discharge capacity, the charge energy, the discharge energy and the ratio of the constant-current charge capacity to the constant-voltage charge capacity of the lithium ion battery;
at the same time, normalization is required to eliminate dimensional differences between the sorting parameters. The normalization formula is as follows:
in the formula (I), the compound is shown in the specification,
is the k parameter, x, of the normalized i battery feature vector ik The k parameter, x, of the ith battery feature vector before normalization k,max Is the maximum of the kth parameters, x, of all cells k,min The minimum of the kth parameter for all cells. .
At this time, n cells to be sorted can be converted into an n × 5 dimensional feature matrix, and the feature matrix is used as an input of the FCM algorithm.
And setting a final clustering number according to the number of the batteries to be sorted and the number of the battery pack monomers, initializing a membership matrix by adopting computer random assignment, and setting an algorithm iteration stopping condition. The Euclidean distance is taken as a distance calculation formula of a monomer and a clustering center in the FCM clustering process:
in the formula (I), the compound is shown in the specification,
for the kth parameter of the normalized ith battery feature vector>
The k characteristic value of the jth clustering center in the FCM algorithm is obtained;
and iterating according to the FCM algorithm until an iteration stop condition is met. And according to the membership matrix of the last iteration, classifying each battery into the class with the maximum membership, thereby finishing the primary classification of the batteries.
And S3, carrying out secondary sorting on various batteries subjected to primary sorting by using the charge-discharge voltage curves of the batteries. As shown in fig. 3, the method comprises the following steps:
s301, extracting curve characteristics. Because the performances of the batteries are different, the charging and discharging processes are different, and the measured overall charging and discharging voltage curve of each lithium ion battery is segmented into a charging stage voltage curve, a discharging stage voltage curve and a resting voltage curve. Because the curve itself cannot be directly used for sorting, the voltage curves of each battery at the same stage are sampled at the same time interval to form a characteristic vector representing the charge and discharge curves of each battery. In order to ensure that the characteristic vectors of the charge and discharge curves of the batteries contain the same quantity of characteristic parameters and consider that the charge, discharge and rest stages of the grouped batteries are synchronous, the time for reaching the charge cut-off voltage and the discharge cut-off voltage in all the batteries is taken as the upper sampling limit of the charge stage and the discharge stage.
Assuming that n lithium ion batteries to be sorted are arranged, the total sampling point number is p. All the battery charging and discharging voltage curves can be converted into a characteristic matrix with dimension of n multiplied by p. The degree of similarity between the charge and discharge voltage curves of the ith cell and the jth cell can be represented by the degree of similarity between the ith row and the jth row in the matrix X.
Here, the euclidean distance is used to calculate the similarity between the batteries:
s302, setting a sorting similarity threshold u, and simultaneously selecting a lithium ion battery as a first standard battery;
and S303, selecting one battery with the minimum serial number from the remaining unsorted batteries, marking the battery as the current battery, and calculating the similarity between the battery and each standard battery. Let the maximum similarity be S max And the corresponding standard battery is numbered as i.
S304, comparing the maximum similarity S max The similarity threshold u can be determined according to the number of batteries to be sorted and the sorting requirement precision in actual application with the set similarity threshold u. If S is max If u is greater than u, the current battery is considered to be similar to the standard battery i enough, and the current battery is classified as the type of the standard battery i; if S is max If u, the current battery is not similar to all the current standard batteries enough, namely the current battery cannot be classified into any current standard battery, so that the current battery is taken as a new standard battery to avoid the situation that the batteries classified into one type are only relatively similar but not absolutely similarThe method is described.
S305, judging whether unclassified batteries exist at present. If yes, returning to the step S302; if not, the classification result is output.
To sum up, this application utilizes the static characteristic and the dynamic characteristic of battery to select separately the battery simultaneously to it is higher to guarantee to select separately for the battery uniformity of a type, and the group battery performance of constitution is better.
Example 2:
as shown in fig. 4, the method of the present application is adopted to perform sorting, series connection and grouping, 36 brand new 6Ah IFR32700 are taken as experimental objects, and finally 4 batteries are selected to be connected in series to form a battery pack, and the batteries are fully charged under the same condition before grouping.
Wherein, the specific process of the series grouping experiment is as follows:
1) Performing constant current discharge on the sorted battery pack at room temperature by using 1C (6A) current, and stopping discharging once the voltage of the single battery reaches 2.0V;
2) Standing for 10min;
3) The lithium ion battery pack is charged at room temperature by a constant current of 1C (6A), and when the voltage of a single battery reaches 3.65V, the charging is stopped.
The discharge capacity of the battery pack is obtained by calculating the time integral of the discharge current of the battery pack; the battery pack discharge energy is obtained by the integral calculation of the product of the battery pack discharge current and the discharge voltage to the time; the average standard deviation SD and the average range SR can reflect the internal resistance difference of each single battery in the working process of the battery pack, and the calculation formula is as follows:
SR k ＝V max，k -V min，k
wherein i represents the number of the battery; v i，k Represents the voltage of the battery at the kth sampling point;
represents the average voltage of all the batteries in the battery pack at the k-th sampling point; n represents the number of grouped cells; n represents the total number of sample points.
Comparative example 1:
taking 36 brand new 6Ah IFR32700 as experimental objects, adopting a traditional sorting method, taking a discharge capacity as an example, firstly confirming median data through statistics, then confirming a range or variance value through range or variance statistics, and sorting by combining other technical indexes of products (the battery capacity difference is less than or equal to 3%, the internal resistance difference is less than or equal to 5%, and the average discharge voltage difference is less than or equal to 5%); and (4) performing charge and discharge performance of the battery pack after sorting and series connection grouping, finally selecting 4 batteries to form the battery pack in series connection, and fully charging the batteries under the same condition before grouping the batteries. The specific procedure of the tandem grouping experiment was identical to that of example 2.
The results obtained for example 2 and comparative example 1 are tabulated as follows:
TABLE 1
The performance of the batteries sorted into groups by adopting the lithium battery consistency sorting method is obviously superior to that of the batteries sorted by the traditional method, namely the sorting effect of the method is superior to that of the batteries sorted by the traditional method.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (9)
1. A lithium battery consistency sorting method is characterized by comprising the following steps:
s1: carrying out a charge-discharge experiment on the batteries to be sorted according to the normal charge-discharge multiplying power; measuring static parameters of each battery and a charge-discharge voltage curve capable of reflecting dynamic characteristics of the battery;
s2: preliminarily sorting the batteries by using the measured static parameters of each battery and a fuzzy C-means clustering algorithm;
s3: and carrying out secondary sorting on various batteries which are preliminarily classified by utilizing the charging and discharging voltage curves of the batteries.
2. The lithium battery consistency sorting method according to claim 1, wherein the step S1 specifically comprises: fully charging all batteries to be sorted under the same condition, then carrying out constant current discharge on the batteries at the same rate at room temperature, and ending the discharge when the batteries are discharged to the voltage cut-off; standing for 10min; and similarly, constant-current constant-voltage charging is carried out at the same multiplying power at room temperature, the charging is finished when the charging current is reduced to 0.05 ℃, and the static parameters of each battery and a charging and discharging voltage curve capable of showing the dynamic characteristics of the batteries are measured.
3. The lithium battery uniformity sorting method of claim 2, wherein the static parameters include charge capacity, discharge capacity, charge energy, discharge energy, ratio of constant current charge capacity to constant voltage charge capacity.
4. The lithium battery consistency sorting method according to claim 3, wherein the step S2 specifically comprises: importing parameters, and carrying out standardization processing to form a battery characteristic matrix;
at the moment, n batteries to be sorted can be converted into an n multiplied by 5 dimensional characteristic matrix, and the characteristic matrix is used as the input of an FCM algorithm;
setting a final clustering number according to the number of batteries to be sorted and the number of battery pack monomers, initializing a membership matrix by adopting computer random assignment, simultaneously setting an algorithm iteration stopping condition, and taking Euclidean distance as a distance calculation formula of the monomers and a clustering center in the FCM clustering process:
in the formula (I), the compound is shown in the specification,
for the kth parameter of the normalized ith battery feature vector>
The k characteristic value of the jth clustering center in the FCM algorithm is obtained;
and (4) performing iteration according to the FCM algorithm until an iteration stop condition is met, and classifying each battery into the class with the maximum membership according to the membership matrix of the last iteration so as to finish primary classification of the batteries.
5. The lithium battery consistency sorting method according to claim 4, wherein the standardization process specifically comprises:
each battery cell is firstly represented by a feature vector formed by five measured static parameters,
X i ＝|x i1 ，x i2 ，x i3 ，x i4 ，x i5 )
in the formula, X i Representing the eigenvector, x, of the ith lithium ion cell i1 ,x i2 ,x i3 ,x i4 ,x i5 Sequentially representing five parameters of the charge capacity, the discharge capacity, the charge energy, the discharge energy and the ratio of the constant-current charge capacity to the constant-voltage charge capacity of the lithium ion battery;
this also normalizes the above parameters to eliminate dimensional differences between the sorting parameters, the normalization formula being as follows:
in the formula (I), the compound is shown in the specification,
is the kth parameter, x, of the normalized ith cell feature vector ik The kth parameter, x, of the ith cell feature vector before normalization k,max Is the maximum value, x, of the kth parameter of all cells k,min The minimum of the kth parameter for all cells.
6. The lithium battery consistency sorting method according to claim 1, wherein the step S3 specifically comprises the following steps:
s301, extracting curve characteristics;
s302, setting a sorting similarity threshold u, and simultaneously selecting a lithium ion battery as a first standard battery;
s303, selecting a battery with the minimum serial number from the remaining unsorted batteries as a current battery, and calculating the similarity between the battery and each standard battery;
s304, comparing the maximum similarity S max The size of the similarity threshold u is set;
s305, judging whether unclassified batteries exist at present, and if yes, returning to the step S302; if not, the classification result is output.
7. The lithium battery consistency sorting method according to claim 6, wherein the step S301 specifically comprises:
supposing that n lithium ion batteries to be sorted are arranged, the total sampling point number is p; (ii) a The charging and discharging voltage curves of all the batteries can be converted into an n multiplied by p dimensional characteristic matrix, and the similarity degree between the charging and discharging voltage curves of the ith battery and the jth battery can be represented by the similarity degree between the ith row and the jth row in the matrix X;
and calculating the similarity between the batteries by adopting the Euclidean distance:
8. the lithium battery consistency sorting method as claimed in claim 6, wherein the comparing S304 is for comparing the maximum similarity S max The size of the similarity threshold u is specifically as follows: if S is max If u is greater than u, the current battery is considered to be similar to the standard battery i enough, and the current battery is classified as the type of the standard battery i; if S is max If u, the current battery is not similar to all the current standard batteries enough, namely the current battery cannot be classified into any current standard battery, and therefore the current battery is taken as a new standard battery so as to avoid the situation that the batteries classified into one type are only relatively similar but not absolutely similar.
9. The lithium battery consistency sorting method according to claim 8, wherein the similarity threshold u is determined according to the number of batteries to be sorted and the sorting requirement precision in actual application.
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| CN116577687B (en) * | 2023-07-14 | 2024-04-19 | 南昌航空大学 | Cell screening method and system for quick-charging battery pack, storage medium and computer |
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