CN114210604B - Multi-characteristic echelon utilization power battery sorting method, device and storage medium - Google Patents
Multi-characteristic echelon utilization power battery sorting method, device and storage medium Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 46
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- 238000012216 screening Methods 0.000 claims abstract description 28
- 238000012360 testing method Methods 0.000 claims abstract description 24
- 238000012545 processing Methods 0.000 claims abstract description 19
- 238000005070 sampling Methods 0.000 claims description 69
- 238000007599 discharging Methods 0.000 claims description 4
- 230000000694 effects Effects 0.000 abstract description 7
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 description 7
- 229910052744 lithium Inorganic materials 0.000 description 7
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- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 description 1
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- 230000037427 ion transport Effects 0.000 description 1
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- 229910001416 lithium ion Inorganic materials 0.000 description 1
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- 239000007773 negative electrode material Substances 0.000 description 1
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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
- 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
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Abstract
The invention relates to a multi-characteristic echelon utilization power battery sorting method, a device and a storage medium, wherein the method comprises the following steps: acquiring resistance parameters, open-circuit voltage parameters and capacity parameters of a battery to be tested; screening a first sorting battery from the batteries to be tested according to the resistance parameter, the open circuit voltage parameter and the capacity parameter; performing charge and discharge tests on the first sorting batteries to determine a voltage change curve and a current change curve; and processing the voltage change curve and the current change curve by using a clustering algorithm, and screening out a second sorting battery from the first sorting battery. The invention utilizes various parameters of the battery to be tested to carry out multiple sorting, has the characteristics of high efficiency, time saving and labor saving, fully utilizes the accuracy of a clustering algorithm, ensures the sorting effect, and is suitable for a large number of battery sorting scenes with various types.
Description
Technical Field
The invention relates to the technical field of battery sorting, in particular to a multi-feature echelon utilization power battery sorting method, a device and a storage medium.
Background
Before lithium batteries can be used in a cascade, detection and sorting are necessary. The battery recycling, namely the actual echelon utilization process, can be used for various batteries to be tested with different performances. The battery to be tested is influenced by factors of different application environments, maintenance habits and application time periods in the use process, and the performance of the battery to be tested is also different.
In the use process of the electric automobile, due to factors such as driving conditions, driving habits of an automobile owner, charging and maintenance modes, temperature and the like, the performance of the retired lithium battery can be greatly different, and the inconsistency problems in the aspects of capacity, internal resistance, voltage and the like are presented. These problems are closely related to the health state and performance decay mechanism of the lithium battery itself, such as lithium ion transport, SEI film transport, structural stability of positive and negative electrode active materials, and the like. And then the battery state and the degree of performance decay will change continuously during the actual echelon utilization. Therefore, lithium batteries need to be subjected to effective detection and sorting in echelon utilization, and lithium batteries with qualified performance and good consistency can be recombined and applied to the echelon utilization neighborhood, so that safe and long-term reliable operation is ensured. Therefore, how to perform efficient and accurate lithium battery cascade utilization sorting is a problem to be solved.
Disclosure of Invention
In view of the foregoing, it is necessary to provide a multi-feature cascade utilization power battery sorting method, device and storage medium for overcoming the problem of low cascade utilization sorting accuracy of lithium batteries in the prior art.
The invention provides a multi-characteristic echelon utilization power battery sorting method, which comprises the following steps:
acquiring resistance parameters, open-circuit voltage parameters and capacity parameters of a battery to be tested;
screening a first sorting battery from the batteries to be tested according to the resistance parameter, the open-circuit voltage parameter and the capacity parameter;
performing charge and discharge tests on the first sorting batteries to determine a voltage change curve and a current change curve;
and processing the voltage change curve and the current change curve by using a clustering algorithm, and screening out a second sorting battery from the first sorting battery.
Further, the screening the first sorted battery from the batteries to be tested according to the resistance parameter, the open circuit voltage parameter and the capacity parameter includes:
judging whether a first preset condition is met or not according to the resistance parameter;
judging whether a second preset condition is met or not according to the open-circuit voltage parameter;
judging whether a third preset condition is met or not according to the capacity parameter;
and if the first preset condition, the second preset condition and the third preset condition are all met, the corresponding battery to be tested is screened as the first sorting battery.
Further, the first preset condition includes that the resistance parameter meets a preset resistance range; the second preset condition includes that the open circuit voltage parameter meets a preset voltage range; the third preset condition includes that the capacity parameter satisfies a preset capacity range.
Further, before the first sorted battery is screened out from the batteries to be tested according to the resistance parameter, the open circuit voltage parameter and the capacity parameter, the method further comprises:
and automatically identifying the battery type of the battery to be detected, and determining the corresponding preset resistance range, preset voltage range and preset capacity range according to the battery type.
Further, the performing a charge-discharge test on the first sorting battery to determine a voltage change curve and a current change curve includes: and carrying out charging test and discharging test on the first sorting batteries, and carrying out corresponding pretreatment to obtain the voltage change curve and the current change curve.
Further, the processing the voltage change curve and the current change curve by using a clustering algorithm, and screening the second sorting battery from the first sorting battery includes:
sampling the voltage change curve and the current change curve respectively to form corresponding voltage sampling data and current sampling data;
processing the voltage sampling data and the current sampling data by using a clustering algorithm to obtain a first classification result and a second classification result;
and screening the second sorting batteries from the first sorting batteries according to the first sorting result and the second sorting result.
Further, the processing the voltage sampling data and the current sampling data by using a clustering algorithm to obtain a first classification result and a second classification result includes:
clustering the voltage sampling data by using a clustering algorithm, performing distance operation with a preset voltage sample, and classifying the voltage sampling data into the preset voltage sample with the nearest distance, wherein the first classification result is the type of the voltage sampling data, and the type of the voltage sampling data is the type of the preset voltage sample;
and clustering the current sampling data by using a clustering algorithm, performing distance operation with a preset current sample, and classifying the current sampling data into the preset current sample with the nearest distance, wherein the second classification result is the class of the current sampling data, and the class of the current sampling data is the class of the preset current sample to which the current sampling data belongs.
Further, the screening the second sorting battery from the first sorting battery according to the first sorting result and the second sorting result includes:
and if the first classification result and the second classification result are consistent and are qualified, screening the second classification battery from the first classification battery.
The invention also provides a multi-characteristic echelon utilization power battery sorting device, which comprises:
the acquisition unit is used for acquiring resistance parameters, open-circuit voltage parameters and capacity parameters of the battery to be tested;
the first sorting unit is used for sorting first sorting batteries from the batteries to be tested according to the resistance parameter, the open-circuit voltage parameter and the capacity parameter; the method is also used for carrying out charge and discharge tests on the first sorting batteries to determine a voltage change curve and a current change curve;
and the second sorting unit is used for processing the voltage change curve and the current change curve by using a clustering algorithm and screening out the second sorting batteries from the first sorting batteries.
The present invention also provides a computer-readable storage medium having stored thereon an executable program which, when executed by a processor, implements the multi-feature echelon utilization power cell sorting method as described above.
Compared with the prior art, the invention has the beneficial effects that: firstly, effectively acquiring resistance parameters, open-circuit voltage parameters and capacity parameters; then, carrying out first sorting by using the resistance parameter, the open circuit voltage parameter and the capacity parameter, and effectively determining a first sorted battery; further, performing charge and discharge tests on the first sorting batteries, and determining corresponding voltage change curves and current change curves to obtain various change characteristics of the first sorting batteries; and finally, processing the voltage change curve and the current change curve by utilizing the clustering characteristic of a clustering algorithm, screening out a second sorting battery from the first sorting battery, and ensuring the sorting accuracy and the sorting efficiency. In conclusion, the method utilizes various parameters of the battery to be tested to carry out multiple sorting, has the characteristics of high efficiency, time saving and labor saving, fully utilizes the accuracy of a clustering algorithm, ensures the sorting effect, and is suitable for sorting scenes of a large number of various batteries.
Drawings
FIG. 1 is a schematic view of an embodiment of an application system of a multi-feature echelon utilization power cell sorting method provided by the present invention;
FIG. 2 is a schematic flow chart of an embodiment of a multi-feature echelon utilization power cell sorting method provided by the present invention;
FIG. 3 is a flowchart illustrating an embodiment of the step S2 in FIG. 2 according to the present invention;
FIG. 4 is a flowchart illustrating an embodiment of step S3 in FIG. 2 according to the present invention;
fig. 5 is a schematic structural diagram of an embodiment of a multi-feature cascade utilization power cell sorting apparatus provided by the present invention.
Detailed Description
Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form a part hereof, and together with the description serve to explain the principles of the invention, and are not intended to limit the scope of the invention.
In the description of the present invention, the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. Furthermore, the meaning of "a plurality of" means at least two, such as two, three, etc., unless specifically defined otherwise.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly understand that the described embodiments may be combined with other embodiments.
The invention provides a multi-feature echelon utilization power battery sorting method, a multi-feature echelon utilization power battery sorting device and a storage medium, establishes a connection between multiple features and sorted second sorted batteries, and provides a new idea for further improving the efficiency and accuracy of battery sorting. Specific embodiments are described in detail below:
an embodiment of the present invention provides an application system of a multi-feature cascade power battery sorting method, and fig. 1 is a schematic view of a scenario of an embodiment of an application system of a multi-feature cascade power battery sorting method provided by the present invention, where the system may include a server 100, and a multi-feature cascade power battery sorting device, such as the server in fig. 1, is integrated in the server 100.
The server 100 in the embodiment of the present invention is mainly used for:
acquiring resistance parameters, open-circuit voltage parameters and capacity parameters of a battery to be tested;
screening a first sorting battery from the batteries to be tested according to the resistance parameter, the open-circuit voltage parameter and the capacity parameter;
performing charge and discharge tests on the first sorting batteries to determine a voltage change curve and a current change curve;
and processing the voltage change curve and the current change curve by using a clustering algorithm, and screening out a second sorting battery from the first sorting battery.
In the embodiment of the present invention, the server 100 may be an independent server, or may be a server network or a server cluster formed by servers, for example, the server 100 described in the embodiment of the present invention includes, but is not limited to, a computer, a network host, a single network server, a plurality of network server sets, or a cloud server formed by a plurality of servers. Wherein the Cloud server is composed of a large number of computers or web servers based on Cloud Computing (Cloud Computing).
It will be appreciated that the terminal 200 used in embodiments of the present invention may be a device that includes both receive and transmit hardware, i.e., a device having receive and transmit hardware capable of performing bi-directional communications over a bi-directional communication link. Such a device may include: a cellular or other communication device having a single-line display or a multi-line display or a cellular or other communication device without a multi-line display. The specific terminal 200 may be a desktop computer, a portable computer, a web server, a palm computer (Personal Digital Assistant, PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, an embedded device, etc., and the embodiment is not limited to the type of the terminal 200.
It will be appreciated by those skilled in the art that the application environment shown in fig. 1 is merely an application scenario of the present invention, and is not limited to the application scenario of the present invention, and other application environments may include more or fewer terminals than those shown in fig. 1, for example, only 2 terminals are shown in fig. 1, and it will be appreciated that the application system of the multi-feature ladder using the power battery sorting method may further include one or more other terminals, which is not limited herein in particular.
In addition, as shown in fig. 1, the application system of the multi-feature cascade power battery sorting method may further include a memory 200 for storing data such as a resistance parameter, an open circuit voltage parameter, a capacity parameter, a voltage variation curve, a current variation curve, and the like.
It should be noted that, the schematic view of the scenario of the application system of the multi-feature cascade power battery sorting method shown in fig. 1 is only an example, and the application system and the scenario of the multi-feature cascade power battery sorting method described in the embodiment of the present invention are for more clearly describing the technical solution of the embodiment of the present invention, and do not constitute a limitation of the technical solution provided by the embodiment of the present invention, and as one of ordinary skill in the art can know, along with the evolution of the application system of the multi-feature cascade power battery sorting method and the appearance of a new service scenario, the technical solution provided by the embodiment of the present invention is equally applicable to similar technical problems.
The embodiment of the invention provides a multi-feature echelon utilization power battery sorting method, and as seen in combination with fig. 2, fig. 2 is a schematic flow chart of an embodiment of the multi-feature echelon utilization power battery sorting method provided by the invention, which comprises steps S1 to S4, wherein:
in step S1, obtaining a resistance parameter, an open circuit voltage parameter and a capacity parameter of a battery to be tested;
in step S2, a first sorting battery is selected from the batteries to be tested according to the resistance parameter, the open circuit voltage parameter and the capacity parameter;
in step S3, a charge-discharge test is performed on the first sorting battery, and a voltage change curve and a current change curve are determined;
in step S4, the voltage change curve and the current change curve are processed by using a clustering algorithm, and a second sorting battery is selected from the first sorting battery.
In the embodiment of the invention, firstly, the resistance parameter, the open-circuit voltage parameter and the capacity parameter are effectively obtained; then, carrying out first sorting by using the resistance parameter, the open circuit voltage parameter and the capacity parameter, and effectively determining a first sorted battery; further, performing charge and discharge tests on the first sorting batteries, and determining corresponding voltage change curves and current change curves to obtain various change characteristics of the first sorting batteries; and finally, processing the voltage change curve and the current change curve by utilizing the clustering characteristic of a clustering algorithm, screening out a second sorting battery from the first sorting battery, and ensuring the sorting accuracy and the sorting efficiency.
As a preferred embodiment, as seen in fig. 3, fig. 3 is a flow chart of an embodiment of step S2 in fig. 2 provided by the present invention, where step S2 includes steps S201 to S204, and the step S201 includes:
in step S201, whether a first preset condition is satisfied is determined according to the resistance parameter;
in step S202, whether a second preset condition is satisfied is determined according to the open circuit voltage parameter;
in step S203, whether a third preset condition is satisfied is determined according to the capacity parameter;
in step S204, if the first preset condition, the second preset condition, and the third preset condition are all satisfied, the corresponding battery to be tested is screened as the first sorted battery.
In the embodiment of the invention, different preset conditions are set, and effective first sorting is performed from a plurality of characteristics.
As a preferred embodiment, the first preset condition includes that the resistance parameter satisfies a preset resistance range; the second preset condition includes that the open circuit voltage parameter meets a preset voltage range; the third preset condition includes that the capacity parameter satisfies a preset capacity range.
In a specific embodiment, the preset resistance range is 0.1 ohm to 0.2 ohm, and it is understood that the preset resistance range is set according to a specific application scenario and is not limited to the above range.
In a specific embodiment, the preset voltage range is 0.5v to 1v, and it is understood that the preset voltage range is set according to a specific application scenario and is not limited to the above range.
In a specific embodiment, the preset capacity range is 20 to 30, and it is understood that the preset capacity range is set according to a specific application scenario and is not limited to the above range.
In the embodiment of the invention, corresponding first preset conditions, second preset conditions and third preset conditions are set, and the resistance parameter, the open-circuit voltage parameter and the capacity parameter are judged in a targeted manner.
As a preferred embodiment, before the first sorted battery is selected from the batteries to be tested according to the resistance parameter, the open circuit voltage parameter and the capacity parameter, the method further comprises: and automatically identifying the battery type of the battery to be detected, and determining the corresponding preset resistance range, preset voltage range and preset capacity range according to the battery type.
In the embodiment of the invention, different categories are judged in advance, and the parameter ranges corresponding to the different categories are stored for targeted judgment.
As a preferred embodiment, the performing a charge-discharge test on the first sorting battery to determine a voltage change curve and a current change curve includes: and carrying out charging test and discharging test on the first sorting batteries, and carrying out corresponding pretreatment to obtain the voltage change curve and the current change curve.
In the embodiment of the invention, the first sorting battery is effectively subjected to charge and discharge test, and a more accurate voltage change curve and current change curve are obtained by pretreatment.
As a preferred embodiment, as seen in fig. 4, fig. 4 is a flow chart of an embodiment of step S3 in fig. 2 provided by the present invention, where step S3 includes steps S301 to S303, and the step S301 includes:
in step S301, the voltage change curve and the current change curve are sampled respectively to form corresponding voltage sampling data and current sampling data;
in step S302, the voltage sampling data and the current sampling data are respectively processed by using a clustering algorithm to obtain a first classification result and a second classification result;
in step S303, the second sorting battery is selected from the first sorting batteries according to the first sorting result and the second sorting result.
In the embodiment of the invention, the voltage sampling data and the current sampling data are respectively processed by using a clustering algorithm, and the second sorting battery is effectively screened out from the first sorting battery.
As a preferred embodiment, the processing the voltage sampling data and the current sampling data by using a clustering algorithm to obtain a first classification result and a second classification result includes:
clustering the voltage sampling data by using a clustering algorithm, performing distance operation with a preset voltage sample, and classifying the voltage sampling data into the preset voltage sample with the nearest distance, wherein the first classification result is the type of the voltage sampling data, and the type of the voltage sampling data is the type of the preset voltage sample;
and clustering the current sampling data by using a clustering algorithm, performing distance operation with a preset current sample, and classifying the current sampling data into the preset current sample with the nearest distance, wherein the second classification result is the class of the current sampling data, and the class of the current sampling data is the class of the preset current sample to which the current sampling data belongs.
In the embodiment of the invention, the clustering algorithm is effectively utilized to cluster respectively, and the clustering algorithm is compared with the center distance of a preset sample, so that each voltage sampling data and each current sampling data are classified, and the accurate class is obtained.
In a preferred embodiment, the clustering algorithm may be at least one of a K-MEANS clustering algorithm, a Mean shift (Mean shift) clustering algorithm, a DBSCAN clustering algorithm, a Expectation Maximization (EM) clustering algorithm using a Gaussian Mixture Model (GMM). It can be understood that the clustering algorithm used in the present invention includes, but is not limited to, the above algorithm, and only the corresponding clustering effect can be achieved.
In a more specific embodiment, the results of a plurality of clustering algorithms are combined, the duty ratio of the result of a certain clustering algorithm in all the clustering algorithms is calculated, and the clustering point with the highest duty ratio and the duty ratio larger than the preset duty ratio is the final clustering point. If the clustering point of the A clustering algorithm is A, the clustering point of the B clustering algorithm is A, the clustering point of the C clustering algorithm is A, the clustering point of the D clustering algorithm is B, the ratio of the clustering point A in the results of all the clustering algorithms is highest and is larger than the preset ratio of 75%, and the clustering point A is the final clustering point. Therefore, the accuracy of the clustering points is ensured by utilizing various clustering algorithms.
As a preferred embodiment, the step S4 specifically includes:
and if the first classification result and the second classification result are consistent and are qualified, screening the second classification battery from the first classification battery.
In the embodiment of the invention, the sorting category is determined together from the sorting result of the voltage sampling data and the current sampling data, so that the accuracy is ensured.
The embodiment of the invention also provides a multi-feature cascade utilization power battery sorting device, and as seen with reference to fig. 5, fig. 5 is a schematic structural diagram of an embodiment of the multi-feature cascade utilization power battery sorting device provided by the invention, and the multi-feature cascade utilization power battery sorting device 500 includes:
an obtaining unit 501, configured to obtain a resistance parameter, an open circuit voltage parameter, and a capacity parameter of a battery to be tested;
a first sorting unit 502, configured to sort a first sorted battery from the batteries to be tested according to the resistance parameter, the open circuit voltage parameter, and the capacity parameter; the method is also used for carrying out charge and discharge tests on the first sorting batteries to determine a voltage change curve and a current change curve;
and the second sorting unit 503 is configured to process the voltage variation curve and the current variation curve by using a clustering algorithm, and screen out a second sorting battery from the first sorting battery.
For a more specific implementation of each unit of the multi-feature cascade utilization power battery sorting apparatus, reference may be made to the description of the multi-feature cascade utilization power battery sorting method described above, and the similar advantageous effects will be provided, and will not be described herein.
The embodiment of the invention also provides multi-feature echelon utilization power battery sorting equipment, which comprises a memory and a processor, wherein the memory stores an executable program, and the processor realizes the multi-feature echelon utilization power battery sorting method when executing the executable program.
For a more specific implementation of each unit of the multi-feature cascade utilization power battery sorting apparatus, reference may be made to the description of the multi-feature cascade utilization power battery sorting method described above, and the similar advantageous effects will be provided, and will not be described herein.
The embodiment of the invention also provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the multi-feature echelon utilization power battery sorting method as described above.
In general, the computer instructions for carrying out the methods of the present invention may be carried in any combination of one or more computer-readable storage media. The non-transitory computer-readable storage medium may include any computer-readable medium, except the signal itself in temporary propagation.
The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
Computer program code for carrying out operations of the present invention may be written in one or more programming languages, or combinations thereof, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" language or similar programming languages, and in particular, the Python language suitable for neural network computing and TensorFlow, pyTorch-based platform frameworks may be used. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
The embodiment of the invention also provides a computing device which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the multi-characteristic gradient power battery sorting method.
The computer readable storage medium and the computing device according to the above embodiments of the present invention may be implemented with reference to what is specifically described in the implementation of the multi-feature cascade power battery sorting method according to the present invention, and have similar advantageous effects as those of the multi-feature cascade power battery sorting method according to the present invention, and will not be described herein.
The invention discloses a multi-characteristic echelon utilization power battery sorting method, a device and a storage medium, wherein firstly, resistance parameters, open-circuit voltage parameters and capacity parameters are effectively obtained; then, carrying out first sorting by using the resistance parameter, the open circuit voltage parameter and the capacity parameter, and effectively determining a first sorted battery; further, performing charge and discharge tests on the first sorting batteries, and determining corresponding voltage change curves and current change curves to obtain various change characteristics of the first sorting batteries; and finally, processing the voltage change curve and the current change curve by utilizing the clustering characteristic of a clustering algorithm, screening out a second sorting battery from the first sorting battery, and ensuring the sorting accuracy and the sorting efficiency.
According to the technical scheme, multiple parameters of the battery to be tested are utilized for multiple sorting, the method has the characteristics of high efficiency, time saving and labor saving, the accuracy of a clustering algorithm is fully utilized, the sorting effect is ensured, and the method is suitable for a large-batch and multi-type battery sorting scene.
The present invention is not limited to the above-mentioned embodiments, and any changes or substitutions that can be easily understood by those skilled in the art within the technical scope of the present invention are intended to be included in the scope of the present invention.
Claims (6)
1. A multi-feature echelon utilization power cell sorting method, comprising:
acquiring resistance parameters, open-circuit voltage parameters and capacity parameters of a battery to be tested;
screening a first sorting battery from the batteries to be tested according to the resistance parameter, the open-circuit voltage parameter and the capacity parameter;
performing charge and discharge tests on the first sorting batteries to determine a voltage change curve and a current change curve;
processing the voltage change curve and the current change curve by using a clustering algorithm, and screening out a second sorting battery from the first sorting battery;
the step of performing charge and discharge tests on the first sorting battery to determine a voltage change curve and a current change curve comprises the following steps: performing charging test and discharging test on the first sorting batteries, and performing corresponding pretreatment to obtain the voltage change curve and the current change curve;
the step of processing the voltage change curve and the current change curve by using a clustering algorithm, and screening out a second sorting battery from the first sorting battery comprises the following steps:
sampling the voltage change curve and the current change curve respectively to form corresponding voltage sampling data and current sampling data;
processing the voltage sampling data and the current sampling data by using a clustering algorithm to obtain a first classification result and a second classification result;
screening the second sorting batteries from the first sorting batteries according to the first sorting result and the second sorting result;
the step of processing the voltage sampling data and the current sampling data by using a clustering algorithm to obtain a first classification result and a second classification result, includes:
clustering the voltage sampling data by using a clustering algorithm, performing distance operation with a preset voltage sample, and classifying the voltage sampling data into the preset voltage sample with the nearest distance, wherein the first classification result is the type of the voltage sampling data, and the type of the voltage sampling data is the type of the preset voltage sample;
clustering the current sampling data by using a clustering algorithm, performing distance operation with a preset current sample, and classifying the current sampling data into the preset current sample with the nearest distance, wherein the second classification result is the class of the current sampling data, and the class of the current sampling data is the class of the preset current sample to which the current sampling data belongs;
the screening the second sorting battery from the first sorting battery according to the first sorting result and the second sorting result comprises the following steps:
and if the first classification result and the second classification result are consistent and are qualified, screening the second classification battery from the first classification battery.
2. The multi-feature echelon utilization power cell sorting method according to claim 1, wherein the screening the first sorted cell among the cells to be tested according to the resistance parameter, the open circuit voltage parameter, and the capacity parameter comprises:
judging whether a first preset condition is met or not according to the resistance parameter;
judging whether a second preset condition is met or not according to the open-circuit voltage parameter;
judging whether a third preset condition is met or not according to the capacity parameter;
and if the first preset condition, the second preset condition and the third preset condition are all met, the corresponding battery to be tested is screened as the first sorting battery.
3. The multi-feature echelon utilization power cell sorting method according to claim 2, wherein the first preset condition includes the resistance parameter satisfying a preset resistance range; the second preset condition includes that the open circuit voltage parameter meets a preset voltage range; the third preset condition includes that the capacity parameter satisfies a preset capacity range.
4. The multi-feature echelon utilization power cell sorting method according to claim 3, further comprising, before said sorting a first sorted cell among said cells to be tested according to said resistance parameter, said open circuit voltage parameter, and said capacity parameter:
and automatically identifying the battery type of the battery to be detected, and determining the corresponding preset resistance range, preset voltage range and preset capacity range according to the battery type.
5. A multi-feature echelon utilization power cell sorting device, comprising:
the acquisition unit is used for acquiring resistance parameters, open-circuit voltage parameters and capacity parameters of the battery to be tested;
the first sorting unit is used for sorting first sorting batteries from the batteries to be tested according to the resistance parameter, the open-circuit voltage parameter and the capacity parameter; the method is also used for carrying out charge and discharge tests on the first sorting batteries to determine a voltage change curve and a current change curve;
the second sorting unit is used for processing the voltage change curve and the current change curve by using a clustering algorithm and screening out a second sorting battery from the first sorting battery;
the step of performing charge and discharge tests on the first sorting battery to determine a voltage change curve and a current change curve comprises the following steps: performing charging test and discharging test on the first sorting batteries, and performing corresponding pretreatment to obtain the voltage change curve and the current change curve;
the step of processing the voltage change curve and the current change curve by using a clustering algorithm, and screening out a second sorting battery from the first sorting battery comprises the following steps:
sampling the voltage change curve and the current change curve respectively to form corresponding voltage sampling data and current sampling data;
processing the voltage sampling data and the current sampling data by using a clustering algorithm to obtain a first classification result and a second classification result;
screening the second sorting batteries from the first sorting batteries according to the first sorting result and the second sorting result;
the step of processing the voltage sampling data and the current sampling data by using a clustering algorithm to obtain a first classification result and a second classification result, includes:
clustering the voltage sampling data by using a clustering algorithm, performing distance operation with a preset voltage sample, and classifying the voltage sampling data into the preset voltage sample with the nearest distance, wherein the first classification result is the type of the voltage sampling data, and the type of the voltage sampling data is the type of the preset voltage sample;
clustering the current sampling data by using a clustering algorithm, performing distance operation with a preset current sample, and classifying the current sampling data into the preset current sample with the nearest distance, wherein the second classification result is the class of the current sampling data, and the class of the current sampling data is the class of the preset current sample to which the current sampling data belongs;
the screening the second sorting battery from the first sorting battery according to the first sorting result and the second sorting result comprises the following steps:
and if the first classification result and the second classification result are consistent and are qualified, screening the second classification battery from the first classification battery.
6. A computer-readable storage medium having stored thereon an executable program, wherein the executable program when executed by a processor implements the multi-feature gradient power battery sorting method of any one of claims 1 to 4.
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