Battery distribution method and device, equipment, storage medium and program product

Abstract

The invention provides a battery distribution method and device, equipment, a storage medium and a program product, and relates to the technical field of electric vehicles. In some embodiments of the invention, the method comprises the following steps: collecting performance parameters of to-be-sorted batteries; performing clustering operation on the to-be-sorted batteries according to the performance parameters to obtain a plurality of clustering results; grouping the batteries to be sorted according to the plurality of clustering results to obtain a plurality of battery packs; each battery pack is distributed to the new energy vehicle matched with each battery pack, efficient utilization of battery resources is achieved, the power performance and the cruising ability of the vehicle are enhanced, and compared with an existing manual battery sorting mode, the labor cost is reduced, and the battery distribution efficiency is improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of electric vehicles, and in particular to a battery distribution method, device, equipment, storage medium, and program product. Background Art

[0002] The rapid rise of the new energy vehicle industry marks a significant shift in the global automotive industry toward a more environmentally friendly and sustainable approach. As a core component of new energy vehicles, batteries directly impact key vehicle performance indicators such as range, power output, and service life. Unavoidable process variations and material properties during battery manufacturing lead to performance differences between individual cells. To ensure the consistency and reliability of battery packs and, therefore, enhance the overall performance of new energy vehicles, scientific and rational battery sorting is crucial.

[0003] Traditional battery sorting methods rely on manual screening and manual distribution of batteries to vehicles, which has high labor costs and low battery distribution efficiency. Summary of the Invention

[0004] The present disclosure provides a battery allocation method, apparatus, device, storage medium, and program product to at least solve the problems of high labor costs and low battery allocation efficiency in the prior art.

[0005] The technical solutions disclosed in this disclosure are as follows:

[0006] An embodiment of the present disclosure provides a battery allocation method, including:

[0007] Collect performance parameters of batteries to be sorted;

[0008] performing a clustering operation on the batteries to be sorted according to the performance parameters to obtain a plurality of clustering results;

[0009] Grouping the batteries to be sorted according to the plurality of clustering results to obtain a plurality of battery groups;

[0010] Each of the battery packs is allocated to a new energy vehicle corresponding to each of the battery packs.

[0011] Optionally, the performance parameters include at least one of the following: voltage, internal resistance, capacity, depth of discharge, discharge rate, and self-discharge rate. The collecting of the performance parameters of the battery to be sorted includes:

[0012] At least one of the voltage, internal resistance, capacity, discharge depth, discharge rate and self-discharge rate of the battery to be sorted is collected.

[0013] Optionally, clustering the batteries to be sorted according to the performance parameters to obtain multiple clustering results includes:

[0014] Preprocessing the performance parameters to obtain preprocessed performance parameters;

[0015] According to the number of cluster centers, the pre-processed performance parameters are input into a clustering algorithm to iteratively calculate the distance between the performance parameter of each battery to be sorted and the cluster center to obtain multiple clustering results.

[0016] Optionally, allocating each of the battery packs to a new energy vehicle corresponding to each of the battery packs includes:

[0017] According to each of the battery packs, a mapping relationship table between battery packs and new energy vehicles is queried to obtain the new energy vehicle corresponding to each of the battery packs.

[0018] Optionally, the battery pack includes: a first type battery pack, a second type battery pack and a third type battery pack;

[0019] The internal resistance of the first type of battery pack is smaller than the internal resistance of the second type of battery pack, and the internal resistance of the second type of battery pack is smaller than the internal resistance of the third type of battery pack;

[0020] The discharge rate of the first type of battery pack is greater than the discharge rate of the third type of battery pack, and the discharge rate of the third type of battery pack is greater than the discharge rate of the second type of battery pack;

[0021] The voltage of the third type of battery group is greater than the voltage of the first type of battery group, and the voltage of the first type of battery group is greater than the voltage of the second type of battery group;

[0022] The capacity of the third type of battery pack is greater than that of the first type of battery pack, and the capacity of the first type of battery pack is greater than that of the second type of battery pack;

[0023] The discharge depth of the third type battery group is greater than the discharge depth of the second type battery group, and the discharge depth of the second type battery group is greater than the discharge depth of the first type battery group;

[0024] The self-discharge rate of the third type battery group is greater than the self-discharge rate of the first type battery group, and the self-discharge rate of the first type battery group is greater than the self-discharge rate of the second type battery group.

[0025] Optionally, the battery pack includes: a first type battery pack, a second type battery pack, and a third type battery pack; allocating each of the battery packs to a new energy vehicle corresponding to each of the battery packs includes:

[0026] Allocate the first type of battery packs to ordinary family cars or small new energy buses;

[0027] Allocating the second type of battery pack to any one of a low-speed electric vehicle, an electric motorcycle, and an electric bicycle;

[0028] The third type of battery pack is allocated to any one of high-performance electric vehicles, electric buses and medium-sized passenger vehicles.

[0029] The present disclosure also provides a battery dispensing device, including:

[0030] Acquisition module, used to collect performance parameters of batteries to be sorted;

[0031] A clustering module, configured to perform a clustering operation on the batteries to be sorted according to the performance parameters to obtain a plurality of clustering results;

[0032] a grouping module, configured to group the batteries to be sorted according to the plurality of clustering results to obtain a plurality of battery groups;

[0033] A distribution module is used to distribute each of the battery packs to a new energy vehicle corresponding to each of the battery packs.

[0034] The present disclosure also provides an electronic device, including:

[0035] processor;

[0036] a memory for storing processor-executable instructions;

[0037] The processor is configured to execute instructions to implement each step in the above method.

[0038] The embodiment of the present disclosure further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, each step in the above method is implemented.

[0039] The embodiments of the present disclosure further provide a computer program product, including a computer program / instruction, which implements the steps in the above method when executed by a processor.

[0040] The technical solutions provided by the embodiments of the present disclosure bring at least the following beneficial effects:

[0041] In some embodiments of the present disclosure, performance parameters of batteries to be sorted are collected; clustering operations are performed on the batteries to be sorted according to the performance parameters to obtain multiple clustering results; the batteries to be sorted are grouped according to the multiple clustering results to obtain multiple battery groups; each battery group is allocated to a new energy vehicle compatible with each battery group, thereby achieving efficient utilization of battery resources, enhancing the vehicle's power performance and endurance, and reducing labor costs and improving battery allocation efficiency compared to existing manual battery sorting methods.

[0042] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute an improper limitation of the present disclosure.

[0044] Figure 1 A flowchart of a battery allocation method provided by an exemplary embodiment of the present disclosure;

[0045] Figure 2 A schematic structural diagram of a battery distribution device provided by an exemplary embodiment of the present disclosure;

[0046] Figure 3 A schematic structural diagram of an electronic device provided by an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0047] In order to enable ordinary persons in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.

[0048] It should be noted that the terms "first," "second," and the like in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the numbers used in this manner are interchangeable where appropriate so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure.

[0049] It should be noted that the user information involved in this disclosure includes but is not limited to: user device information and user personal information; the collection, storage, use, processing, transmission, provision and disclosure of user information in this disclosure comply with the relevant laws and regulations and do not violate public order and good morals.

[0050] In response to the above technical problems, in some embodiments of the present disclosure, the performance parameters of the batteries to be sorted are collected; the batteries to be sorted are clustered according to the performance parameters to obtain multiple clustering results; the batteries to be sorted are grouped according to the multiple clustering results to obtain multiple battery groups; each battery group is allocated to a new energy vehicle that is compatible with each battery group, thereby achieving efficient utilization of battery resources, enhancing the vehicle's power performance and endurance, and reducing labor costs and improving battery allocation efficiency compared to the existing manual battery sorting method.

[0051] The technical solutions provided by various embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0052] Figure 1 FIG. 1 is a flow chart of a battery allocation method provided by an exemplary embodiment of the present disclosure. Figure 1 As shown, the method includes:

[0053] S101: collecting performance parameters of batteries to be sorted;

[0054] S102: performing a clustering operation on the batteries to be sorted according to the performance parameters to obtain multiple clustering results;

[0055] S103: Grouping the batteries to be sorted according to the multiple clustering results to obtain multiple battery groups;

[0056] S104: Allocate each battery pack to a new energy vehicle corresponding to each battery pack.

[0057] In this embodiment, the execution subject of the above method may be a terminal device or a server.

[0058] Among them, terminal devices include but are not limited to mobile stations (MS), mobile terminals, mobile phones, handsets, and portable equipment. The terminal devices can communicate with one or more core networks via a radio access network (RAN). For example, the terminal devices can be mobile phones (or "cellular" phones), computers with wireless communication capabilities, etc. The terminal devices can also be computers with wireless transceiver capabilities, virtual reality (VR) terminal devices, AR terminal devices, wireless terminals in industrial control, wireless terminals in self-driving, wireless terminals in remote medical care, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, etc., and the operating systems installed on the terminal devices include but are not limited to: iOS, Android, Windows, Linux, Mac OS, etc. In different networks, a terminal may be called by different names, such as user equipment, mobile station, subscriber unit, station, cellular phone, personal digital assistant, wireless modem, wireless communication device, handheld device, laptop computer, cordless phone, wireless local loop station, television, etc. For the convenience of description, the terminal is referred to as terminal equipment in this embodiment.

[0059] In this embodiment, the server implementation is not limited. For example, the server can be a conventional server, a cloud server, a cloud host, a virtual center, or other server devices. The server components primarily include a processor, a hard disk, memory, a system bus, and other common computer architecture types.

[0060] It should be noted that the performance parameters disclosed herein include but are not limited to: voltage, internal resistance, capacity, discharge depth, discharge rate and self-discharge rate.

[0061] It should be noted that the new energy vehicles disclosed herein include, but are not limited to, ordinary family cars, small new energy passenger vehicles, low-speed electric vehicles, electric motorcycles, electric bicycles, high-performance electric vehicles, electric buses, and medium-sized passenger vehicles. High-performance electric vehicles are those that have high requirements for range and power performance, with high capacity and high voltage supporting long range, and high depth of discharge to help meet the power requirements of high-speed or intense driving.

[0062] In some embodiments of the present disclosure, performance parameters of the batteries to be sorted are collected. Specifically, the batteries to be sorted are subjected to performance testing, and performance parameters such as voltage, internal resistance, capacity, depth of discharge, discharge rate, and self-discharge rate of each battery to be sorted are collected. These parameters can fully reflect the performance characteristics of the battery and provide a data basis for subsequent cluster analysis.

[0063] In some embodiments of the present disclosure, clustering operations are performed on batteries to be sorted based on performance parameters to obtain multiple clustering results. One achievable method is to pre-process the performance parameters to obtain pre-processed performance parameters; based on the number of cluster centers, the pre-processed performance parameters are input into the clustering algorithm to iteratively calculate the distance between the performance parameters of each battery to be sorted and the cluster center to obtain multiple clustering results. The present disclosure pre-processes the collected battery performance parameters to eliminate the impact of differences in different parameter dimensions and magnitudes, improve the consistency and accuracy of the data, and lay a solid foundation for subsequent cluster analysis. Subsequently, based on the set number of cluster centers, the pre-processed performance parameters are input into the clustering algorithm, and the distance between each battery and each cluster center is iteratively calculated to dynamically divide the battery categories, and finally obtain multiple clustering results with highly similar performance characteristics.

[0064] In the above embodiment, the performance parameters are preprocessed to obtain preprocessed performance parameters. The preprocessing of the collected battery performance parameter data includes operations such as data cleaning and mean normalization. Data cleaning is used to remove abnormal data and missing values ​​to ensure data accuracy and integrity; mean normalization converts data of different dimensions and orders of magnitude to the same scale, improving the performance and stability of the clustering algorithm.

[0065] In the above embodiment, the preprocessed performance parameters are input into a clustering algorithm to iteratively calculate the distance between the performance parameters of each battery to be sorted and the cluster center, based on the number of cluster centers, to obtain multiple clustering results. One possible implementation method is to determine the optimal K value (i.e., the number of cluster centers) using a method such as the elbow method, input the preprocessed performance parameters into a K-means clustering algorithm, and iteratively calculate the distance between each battery data point and the cluster center, classifying the batteries into the category belonging to the closest cluster center until the cluster center no longer changes or the set number of iterations is reached.

[0066] In some embodiments of the present disclosure, each battery pack is assigned to the new energy vehicle corresponding to each battery pack. One achievable method is to query the mapping relationship table between the battery pack and the new energy vehicle according to each battery pack to obtain the new energy vehicle corresponding to each battery pack. The present disclosure achieves accurate matching of each sorted battery pack to the corresponding new energy vehicle by establishing a mapping relationship table between the battery pack and the new energy vehicle. This method is based on the intelligent matching of the comprehensive performance characteristics of the battery pack with the battery performance requirements of different vehicle models, ensuring that the actual performance of the battery pack is highly compatible with the requirements of the entire vehicle, and can also enhance the power performance, endurance and usage stability of the new energy vehicle.

[0067] In one embodiment, each battery pack is assigned to a corresponding new energy vehicle. A possible implementation is to assign the first type of battery pack to an ordinary family car or a small new energy passenger car; the second type of battery pack to any one of low-speed electric vehicles, electric motorcycles, and electric bicycles; and the third type of battery pack to any one of high-performance electric vehicles, electric buses, and medium-sized passenger cars.

[0068] In some embodiments of the present disclosure, the battery pack includes: a first type battery pack, a second type battery pack and a third type battery pack; wherein, the internal resistance of the first type battery pack is smaller than the internal resistance of the second type battery pack, and the internal resistance of the second type battery pack is smaller than the internal resistance of the third type battery pack; the discharge rate of the first type battery pack is greater than the discharge rate of the third type battery pack, and the discharge rate of the third type battery pack is greater than the discharge rate of the second type battery pack; the voltage of the third type battery pack is greater than the voltage of the first type battery pack, and the voltage of the first type battery pack is greater than the voltage of the second type battery pack; the capacity of the third type battery pack is greater than the capacity of the first type battery pack, and the capacity of the first type battery pack is greater than the capacity of the second type battery pack; the discharge depth of the third type battery pack is greater than the discharge depth of the second type battery pack, and the discharge depth of the second type battery pack is greater than the discharge depth of the first type battery pack; the self-discharge rate of the third type battery pack is greater than the self-discharge rate of the first type battery pack, and the self-discharge rate of the first type battery pack is greater than the self-discharge rate of the second type battery pack.

[0069] For example, a Type I battery pack has low internal resistance, a medium-to-high discharge rate, a medium voltage, a medium-to-low capacity, a relatively low depth of discharge, and a medium self-discharge rate. This makes it suitable for ordinary family cars and small new energy buses. Ordinary family cars have certain requirements for power and range during daily driving. The low internal resistance and medium-to-high discharge rate of a Type I battery pack can meet these power needs, while the medium capacity can also meet the daily commuting needs.

[0070] The second type of battery pack has the lowest voltage, slightly higher internal resistance, lowest capacity, medium depth of discharge, lowest discharge rate, and lowest self-discharge rate. It is suitable for low-speed electric vehicles and electric motorcycles / bicycles. Low-speed electric vehicles, such as scenic area sightseeing vehicles and community patrol vehicles, do not require high speed and range. The low capacity and low discharge rate of the first type of battery pack match these requirements, meeting the needs of low-speed, short-distance travel at a lower cost.

[0071] Category III battery packs offer the highest voltage, highest internal resistance, highest capacity, highest depth of discharge, medium discharge rate, and highest self-discharge rate. They are suitable for high-performance electric vehicles and electric buses / mid-sized coaches. High-performance electric vehicles demand high range and power performance. The high capacity and high voltage of Category I battery packs support long range, while the high depth of discharge helps meet the power demands of high-speed or intense driving.

[0072] Figure 2 FIG. 2 is a schematic structural diagram of a battery dispensing device 20 provided by an exemplary embodiment of the present disclosure. Figure 2 As shown, the battery allocation device 20 includes: a collection module 21 , a clustering module 22 , a grouping module 23 and an allocation module 24 .

[0073] The acquisition module 21 is used to acquire the performance parameters of the batteries to be sorted;

[0074] A clustering module 22 is used to perform a clustering operation on the batteries to be sorted according to the performance parameters to obtain multiple clustering results;

[0075] A grouping module 23 is used to group the batteries to be sorted according to the multiple clustering results to obtain multiple battery groups;

[0076] The allocation module 24 is configured to allocate each battery pack to a new energy vehicle corresponding to each battery pack.

[0077] Optionally, the performance parameters include at least one of the following: voltage, internal resistance, capacity, depth of discharge, discharge rate, and self-discharge rate. When collecting the performance parameters of the battery to be sorted, the acquisition module 21 is used to:

[0078] At least one of the voltage, internal resistance, capacity, discharge depth, discharge rate and self-discharge rate of the battery to be sorted is collected.

[0079] Optionally, when the clustering module 22 performs a clustering operation on the batteries to be sorted according to the performance parameters and obtains multiple clustering results, it is configured to:

[0080] Preprocessing the performance parameters to obtain preprocessed performance parameters;

[0081] According to the number of cluster centers, the preprocessed performance parameters are input into the clustering algorithm to iteratively calculate the distance between the performance parameters of each battery to be sorted and the cluster center to obtain multiple clustering results.

[0082] Optionally, when allocating each battery pack to a new energy vehicle corresponding to each battery pack, the allocation module 24 is configured to:

[0083] According to each battery pack, the mapping relationship table between the battery pack and the new energy vehicle is queried to obtain the new energy vehicle corresponding to each battery pack.

[0084] Optionally, the battery pack includes: a first type battery pack, a second type battery pack, and a third type battery pack;

[0085] The internal resistance of the first type of battery pack is smaller than the internal resistance of the second type of battery pack, and the internal resistance of the second type of battery pack is smaller than the internal resistance of the third type of battery pack;

[0086] The discharge rate of the first type of battery group is greater than the discharge rate of the third type of battery group, and the discharge rate of the third type of battery group is greater than the discharge rate of the second type of battery group;

[0087] The voltage of the third type of battery pack is greater than the voltage of the first type of battery pack, and the voltage of the first type of battery pack is greater than the voltage of the second type of battery pack;

[0088] The capacity of the third category battery pack is greater than that of the first category battery pack, and the capacity of the first category battery pack is greater than that of the second category battery pack;

[0089] The depth of discharge of the third type of battery pack is greater than the depth of discharge of the second type of battery pack, and the depth of discharge of the second type of battery pack is greater than the depth of discharge of the first type of battery pack;

[0090] The self-discharge rate of the third type of battery pack is greater than the self-discharge rate of the first type of battery pack, and the self-discharge rate of the first type of battery pack is greater than the self-discharge rate of the second type of battery pack.

[0091] Optionally, the battery pack includes: a first type battery pack, a second type battery pack, and a third type battery pack; when allocating each battery pack to a new energy vehicle corresponding to each battery pack, the allocation module 24 is used to:

[0092] The first type of battery packs are allocated to ordinary family cars or small new energy buses;

[0093] Assigning the second type of battery pack to any one of a low-speed electric vehicle, an electric motorcycle, and an electric bicycle;

[0094] The third type of battery pack is assigned to any of high-performance electric vehicles, electric buses and medium-sized buses.

[0095] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0096] Figure 3 FIG. 1 is a structural diagram of an electronic device provided by an exemplary embodiment of the present disclosure. Figure 3 As shown, the electronic device includes: a memory 31 and a processor 32. In addition, the electronic device also includes a power supply component 33 and a communication component 34.

[0097] The memory 31 is used to store computer programs and can be configured to store various other data to support operations on the electronic device. Examples of such data include instructions for any application or method operating on the electronic device.

[0098] The memory 31 can be implemented by any type of volatile or non-volatile memory device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0099] The communication component 34 is used for data transmission with other devices.

[0100] The processor 32 can execute computer instructions stored in the memory 31 to: collect performance parameters of the batteries to be sorted; cluster the batteries to be sorted according to the performance parameters to obtain multiple clustering results; group the batteries to be sorted according to the multiple clustering results to obtain multiple battery groups; and assign each battery group to the new energy vehicle corresponding to each battery group.

[0101] Accordingly, the embodiment of the present disclosure further provides a computer-readable storage medium storing a computer program. When the computer-readable storage medium stores the computer program and the computer program is executed by one or more processors, the one or more processors are caused to execute Figure 1 Each step in the method embodiment.

[0102] Accordingly, the present disclosure also provides a computer program product, which includes a computer program / instruction, and the computer program / instruction is executed by a processor. Figure 1 Each step in the method embodiment.

[0103] above Figure 3The communication component is configured to facilitate wired or wireless communication between the device where the communication component is located and other devices. The device where the communication component is located can access a wireless network based on a communication standard, such as WiFi, 2G, 3G, 4G / LTE, 5G and other mobile communication networks, or a combination thereof. In an exemplary embodiment, the communication component receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0104] above Figure 3 The power supply component in a device provides power to various components of the device in which the power supply component is located. The power supply component may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the device in which the power supply component is located.

[0105] The electronic device also includes a display screen and an audio component.

[0106] The display screen includes a screen, which may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touches, slides, and gestures on the touch panel. The touch sensor can not only sense the boundaries of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.

[0107] The audio component can be configured to output and / or input audio signals. For example, the audio component includes a microphone (MIC), and when the device where the audio component is located is in an operating mode, such as call mode, recording mode, and voice recognition mode, the microphone is configured to receive external audio signals. The received audio signal can be further stored in a memory or sent via a communication component. In some embodiments, the audio component also includes a speaker for outputting audio signals.

[0108] Those skilled in the art will appreciate that the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0109] The present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0110] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0111] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0112] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0113] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0114] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory media such as modulated data signals and carrier waves.

[0115] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device that includes the element.

[0116] The above are merely specific embodiments of the present disclosure, intended to enable those skilled in the art to understand and implement the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure is not limited to these embodiments, but is to be construed in the broadest manner consistent with the principles and novel features disclosed herein.

Claims

1. A battery distribution method, characterized in that: include: Collect performance parameters of batteries to be sorted; performing a clustering operation on the batteries to be sorted according to the performance parameters to obtain a plurality of clustering results; Grouping the batteries to be sorted according to the plurality of clustering results to obtain a plurality of battery groups; Each of the battery packs is allocated to a new energy vehicle corresponding to each of the battery packs.

2. The method according to claim 1, characterized in that The performance parameters include at least one of the following: voltage, internal resistance, capacity, depth of discharge, discharge rate and self-discharge rate. The performance parameters of the battery to be sorted are collected, including: At least one of the voltage, internal resistance, capacity, discharge depth, discharge rate and self-discharge rate of the battery to be sorted is collected.

3. The method according to claim 1, characterized in that The clustering operation is performed on the batteries to be sorted according to the performance parameters to obtain multiple clustering results, including: Preprocessing the performance parameters to obtain preprocessed performance parameters; According to the number of cluster centers, the pre-processed performance parameters are input into a clustering algorithm to iteratively calculate the distance between the performance parameter of each battery to be sorted and the cluster center to obtain multiple clustering results.

4. The method according to claim 1, wherein The allocating each of the battery packs to a new energy vehicle corresponding to each of the battery packs includes: According to each of the battery packs, a mapping relationship table between battery packs and new energy vehicles is queried to obtain the new energy vehicle corresponding to each of the battery packs.

5. The method according to claim 1, wherein The battery pack includes: a first type battery pack, a second type battery pack and a third type battery pack; The internal resistance of the first type of battery pack is smaller than the internal resistance of the second type of battery pack, and the internal resistance of the second type of battery pack is smaller than the internal resistance of the third type of battery pack; The discharge rate of the first type of battery pack is greater than the discharge rate of the third type of battery pack, and the discharge rate of the third type of battery pack is greater than the discharge rate of the second type of battery pack; The voltage of the third type of battery group is greater than the voltage of the first type of battery group, and the voltage of the first type of battery group is greater than the voltage of the second type of battery group; The capacity of the third type of battery pack is greater than that of the first type of battery pack, and the capacity of the first type of battery pack is greater than that of the second type of battery pack; The discharge depth of the third type battery group is greater than the discharge depth of the second type battery group, and the discharge depth of the second type battery group is greater than the discharge depth of the first type battery group; The self-discharge rate of the third type battery group is greater than the self-discharge rate of the first type battery group, and the self-discharge rate of the first type battery group is greater than the self-discharge rate of the second type battery group.

6. The method according to claim 1, characterized in that The battery packs include: a first type battery pack, a second type battery pack, and a third type battery pack; allocating each of the battery packs to a new energy vehicle corresponding to each of the battery packs includes: Allocate the first type of battery packs to ordinary family cars or small new energy buses; Allocating the second type of battery pack to any one of a low-speed electric vehicle, an electric motorcycle, and an electric bicycle; The third type of battery pack is allocated to any one of high-performance electric vehicles, electric buses and medium-sized passenger vehicles.

7. A battery distribution device, characterized in that: include: Acquisition module, used to collect performance parameters of batteries to be sorted; A clustering module, configured to perform a clustering operation on the batteries to be sorted according to the performance parameters to obtain a plurality of clustering results; a grouping module, configured to group the batteries to be sorted according to the plurality of clustering results to obtain a plurality of battery groups; A distribution module is used to distribute each of the battery packs to a new energy vehicle corresponding to each of the battery packs.

8. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to execute instructions to implement each step in the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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