Device and method for controlling a battery

Abstract

The present disclosure provides an apparatus comprising one or more processors, wherein the one or more processors receive, from a scanner, first information about one or more images generated by scanning a battery, generate, on the basis of the first information, second information about a three-dimensional image of the battery, generate, on the basis of the first information, third information by identifying a feature of the battery, generate, on the basis of the second information and the third information, fourth information in which the three-dimensional image of the battery is labeled with information about the feature of the battery, and transmit the fourth information to an external apparatus that performs a disassembly operation for the battery.

Description

Device and method for managing a battery

[0001] The present disclosure relates to a technology for managing batteries.

[0002] This research is the result of a project conducted under the "Technology Development Project for Enhancing the Circularity of Secondary Batteries" by the Ministry of Environment and the Korea Environmental Industry & Technology Institute. [Project Title: Development of Demonstration Technology for Automated Dismantling, Separation, and Resource Recovery of Multi-Type Waste Secondary Batteries Based on Eco-friendly Pre-lithium Extraction, Project No.: 00339705]

[0003] Recently, batteries used in electric vehicles are lithium-ion batteries, which consist of four main components: a cathode, anode, electrolyte, and separator. Among these, lithium-ion batteries are classified into various forms depending on the material used as the cathode. These include nickel ternary (e.g., nickel-cobalt-manganese (NCM), nickel-cobalt-aluminum (NCA)) and cobalt-based (e.g., lithium cobalt oxide (LCO)) and manganese-based (e.g., lithium manganese oxide (LMO)) batteries, as well as lithium iron phosphate (LFP) batteries that utilize iron to replace cobalt. Furthermore, in the future, various types of batteries, including solid-state batteries, are expected to be used to reduce the risk of fire associated with liquid electrolytes.

[0004] Secondary batteries account for 30% of the carbon footprint of the entire electric vehicle production lifecycle, and metal raw materials such as nickel, cobalt, and manganese account for a high proportion of the carbon footprint. Greenhouse gases, such as carbon dioxide, are mostly generated during the mining and refining processes of secondary battery raw materials, and the reuse and recycling of secondary batteries can make a significant contribution to reducing greenhouse gas emissions for the transition to a carbon-neutral society by 2050.

[0005] With the growth of the electric vehicle market, the scale of waste batteries discarded after several years of use is expanding, leading to the activation of the battery recycling industry for the recycling and reuse of waste batteries. Through this battery recycling, valuable metals (nickel, cobalt, manganese, copper, lithium, etc.) that are essential for battery manufacturing can be recovered and recycled, thereby generating resource recycling and economic benefits, as well as reducing environmental pollution caused during the process of extracting these metals.

[0006] At least one embodiment of the present disclosure may provide a technology for efficiently dismantling batteries, such as battery packs, modules, and cells, for recycling.

[0007] At least one embodiment of the present disclosure may provide a technology for automating the disassembly process of a battery based on a three-dimensional image of the battery.

[0008] At least one embodiment of the present disclosure may provide a technology that determines whether a battery is defective and does not perform disassembly work on the battery.

[0009] The technical problems of the present disclosure are not limited to those mentioned above, and other unmentioned technical problems will be clearly understood by a person skilled in the art from the description in the specification.

[0010] An apparatus according to one embodiment of the present disclosure may be configured to include one or more processors and one or more memories in which instructions to be executed by the one or more processors are stored, and when the instructions are executed, the one or more processors receive first information regarding one or more images generated by scanning a target battery from a scanner, generate second information regarding a three-dimensional image of the target battery based on the first information, generate third information by identifying features of the target battery based on the first information, generate fourth information in which information regarding features of the target battery is labeled on the three-dimensional image of the target battery based on the second information and the third information, and transmit the fourth information to an external device that performs a dismantling operation on the target battery.

[0011] In one embodiment, the one or more processors may be configured to generate point cloud information corresponding to the surface of the target battery for each of the one or more images in generating the second information, and to generate the three-dimensional image of the target battery based on the point cloud information.

[0012] In one embodiment, the one or more processors may be configured to generate the third information by inputting the first information into an artificial neural network trained to identify battery features from an image of a battery, obtaining prediction information for the target battery as the output of the artificial neural network, and generating the third information based on the prediction information.

[0013] In one embodiment, the one or more processors may be configured to generate learning information by labeling features regarding the target battery based on the first information, and to further train the artificial neural network based on the learning information.

[0014] In one embodiment, the third information may be information indicating a feature regarding the manufacturer of the target battery.

[0015] In one embodiment, the third information may be information indicating any one of an electric vehicle, a hybrid electric vehicle, a fuel cell electric vehicle, or an energy storage system, as a characteristic regarding the field in which the target battery is used.

[0016] In one embodiment, the third information may be information indicating a feature of one or more components constituting the target battery.

[0017] In one embodiment, the third information may be information indicating one of a cylindrical, prismatic, or pouch type as a characteristic regarding the packaging form of the target battery.

[0018] In one embodiment, the third information may be information indicating a feature regarding a defect in the target battery.

[0019] In one embodiment, the one or more processors may be further configured to associate the second information and the third information with each other and store them in the one or more memories.

[0020] In one embodiment, the one or more processors may be configured to generate the fourth information by determining a location corresponding to the feature on the three-dimensional image of the second information and labeling information regarding the feature at the location.

[0021] In one embodiment, the external device includes one or more automation devices, and the one or more processors may be configured to determine, based on the third information, a target automation device among the one or more automation devices that performs a dismantling operation related to the feature, and to transmit the fourth information to the target automation device.

[0022] In one embodiment, the third information is information indicating a first type among the product types of batteries, and the one or more processors may be configured to determine an automation device that performs a dismantling operation for the first type of battery as the target automation device when determining the target automation device.

[0023] In one embodiment, the third information is information indicating a first part among one or more parts constituting a battery, and the one or more processors may be configured to determine an automation device that performs a dismantling operation on the first part as the target automation device when determining the target automation device.

[0024] In one embodiment, the third information is information indicating the characteristic regarding the defective state of the battery, and the one or more processors may be configured to determine, based on the third information, whether the defective state of the target battery corresponds to a predetermined first reference state, and to generate and transmit to the external device fifth information indicating that the target battery is not moved to the automation device in accordance with the determination that the defective state is the first reference state.

[0025] A method according to one embodiment of the present disclosure may be a method performed in a device comprising one or more processors and one or more memories in which instructions to be executed by the one or more processors are stored, wherein the one or more processors may include the steps of: receiving first information regarding one or more images generated by photographing a target battery from a camera; generating second information regarding a three-dimensional image of the target battery based on the first information; generating third information by identifying features of the target battery based on the first information; generating fourth information in which information regarding features of the target battery is labeled on the three-dimensional image of the target battery based on the second information and the third information; and transmitting the fourth information to an external device that performs a dismantling operation on the target battery.

[0026] According to one embodiment of the present disclosure, a technology for efficiently dismantling batteries, such as battery packs, modules, and cells, for recycling can be provided.

[0027] According to one embodiment of the present disclosure, a technology can be provided to automate the disassembly process of a battery based on a three-dimensional image of the battery.

[0028] According to one embodiment of the present disclosure, a technology can be provided that determines whether a battery is defective and does not perform disassembly work on the battery.

[0029] The effects according to the technical concept of the present disclosure are not limited to those mentioned above, and other unmentioned effects will be clearly understood by a person skilled in the art of the present disclosure from the description in the specification.

[0030] FIG. 1 illustrates an environment in which a device according to one embodiment of the present disclosure can be applied.

[0031] FIG. 2 illustrates an example in which a device according to one embodiment of the present disclosure is implemented.

[0032] FIG. 3 illustrates a flowchart showing a method according to one embodiment of the present disclosure.

[0033] FIG. 4 illustrates an example of a work environment in which a dismantling operation of a battery is performed, which may be referenced in various embodiments of the present disclosure.

[0034] FIG. 5 illustrates another example of a work environment in which a dismantling operation of a battery is performed, which may be referenced in various embodiments of the present disclosure.

[0035] FIG. 6 illustrates a flowchart illustrating an example of a method for transmitting a fourth piece of information from a device to an external device in various embodiments of the present disclosure.

[0036] FIG. 7 illustrates a flowchart illustrating an example of a method for transmitting fourth information from a device to a first automation device in various embodiments of the present disclosure.

[0037] FIG. 8 illustrates a flowchart illustrating an example of a method for transmitting fourth information from a device to a second automation device in various embodiments of the present disclosure.

[0038] FIG. 9 illustrates a flowchart illustrating an example of a method for transmitting fourth information from a device to a third automation device in various embodiments of the present disclosure.

[0039] FIG. 10 illustrates a flowchart illustrating a method according to one embodiment of the present disclosure.

[0040] The various embodiments described in this disclosure are illustrative for the purpose of clearly explaining the technical concept of this disclosure and are not intended to limit it to specific embodiments. The technical concept of this disclosure includes various modifications, equivalents, alternatives, and embodiments selectively combined from all or part of each embodiment described in this disclosure. Furthermore, the scope of the technical concept of this disclosure is not limited to the various embodiments presented below or the specific descriptions thereof.

[0041] Terms used in this disclosure, including technical or scientific terms, may have the meaning generally understood by those skilled in the art to which this disclosure pertains, unless otherwise defined.

[0042] Expressions used in this disclosure, such as “comprising,” “may compose,” “possessing,” “possessing,” “having,” and “possessing,” mean that the subject feature (e.g., function, operation, or component, etc.) exists and do not exclude the existence of other additional features. That is, such expressions should be understood as open-ended terms implying the possibility of including other embodiments.

[0043] Singular expressions used in this disclosure may include the meaning of the plural form unless otherwise indicated by the context, and this applies likewise to singular expressions described in the claims.

[0044] Expressions such as "first," "second," or "first," "second," etc., used in this disclosure are used to distinguish one object from another when referring to a plurality of objects of the same kind, unless otherwise indicated in the context, and do not limit the order or importance of the objects.

[0045] Expressions used in the present disclosure, such as “A, B and C,” “A, B or C,” “at least one of A, B and C,” or “at least one of A, B or C,” may mean each of the listed items or all possible combinations of the listed items. For example, “at least one of A or B” may refer to (1) at least one A, (2) at least one B, and (3) at least one A and at least one B.

[0046] The expression “based on” as used in this disclosure is used to describe one or more factors affecting an act or action of a decision or judgment described in the phrase or sentence containing this expression, and this expression does not exclude additional factors affecting said act or action of a decision or judgment.

[0047] As used in the present disclosure, the expression that a certain component (e.g., a first component) is "connected" or "connected" to another component (e.g., a second component) may mean that the said certain component is not only directly connected or connected to the said other component, but is also connected or connected through a new other component (e.g., a third component).

[0048] As used in this disclosure, the expression "configured to" may have meanings such as "set to," "capable of," "modified to," "made to," or "capable of." This expression is not limited to the meaning of "specifically designed in hardware." For example, a processor configured to perform a specific operation may mean a generic-purpose processor capable of performing that specific operation by executing software, or a special-purpose computer structured through programming to perform that specific operation.

[0049] Hereinafter, various embodiments described in this disclosure will be explained with reference to the attached drawings. In the attached drawings and the description thereof, identical or substantially equivalent components may be given the same reference numerals. Furthermore, in the description of the various embodiments below, the description of identical or corresponding components may be omitted, but this does not mean that such components are not included in the embodiments.

[0050] FIG. 1 illustrates an environment (100) to which a device (110) according to one embodiment of the present disclosure may be applied. Such an environment (100) may include a device (110), a scanner (120), and / or an external device (130). FIG. 1 illustrates only one embodiment for achieving the purpose of the present disclosure, and some components may be added as needed. For example, a user terminal used by a user who is the subject managing the device (110), a transfer device that performs a transfer operation on a battery, a worker terminal used by a worker who performs a scanning operation on a battery, etc. may be added to the environment (100).

[0051] As used in this specification, the term "battery" may mean any one of a battery pack, a battery module, or a battery cell, and may mean any one of a set of one or more battery modules or a set of one or more battery cells connected through various components; however, it is not limited thereto and includes batteries of various forms and units that can be understood by a person skilled in the art. Accordingly, the term "battery" mentioned in this specification is not limited to a specific product, form, or unit, but may be interpreted as a concept encompassing batteries of various structures and configurations. For example, "battery" may be a battery of various structures and configurations used in various application fields, such as electric vehicles, as well as hybrid electric vehicles, fuel cell electric vehicles, and energy storage systems. Furthermore, in this specification, "battery" may also refer to a waste battery that has completed its use and is subject to disposal or recycling.

[0052] The device (110) may be a server device for managing the storage of the battery, the transfer of the battery, and / or the dismantling of the battery. By executing the method, etc. according to the present disclosure, the device (110) may generate and store various information regarding the battery and transmit the generated information to an external device (130) so that the external device (130) can perform a dismantling operation on the battery.

[0053] The device (110) may be implemented as one or more computing devices. For example, all functions of the device (110) may be implemented in a single computing device. As another example, a first function of the device (110) may be implemented in a first computing device, and a second function may be implemented in a second computing device. As a specific example, if the device (110) is a server device that manages a battery, a first function that generates information about the battery may be implemented in a first computing device, and a second function that is distinct from the first function may be implemented in a second computing device. Even if these first computing device and second computing device exist physically separated, the first computing device and the second computing device may be referred to as the device (110) as an abstract concept that integrates them.

[0054] The aforementioned computing device may be, for example, a desktop computer, a laptop computer, an application server, a proxy server, or a cloud server, but is not limited thereto, and any type of device equipped with computing functions may be a computing device.

[0055] The scanner (120) can obtain first information by scanning the battery. For example, the scanner (120) may include an optical system, a signal processing module, and / or a data output interface, which can cooperate to perform a scan of a target object to be photographed. The optical system may include a light source configured to irradiate light onto the target object and a receiver that receives light reflected from the target object. For example, the light source may be a laser or an LED (Light Emitting Diode) light source, and the receiver may be a photodiode or a CMOS (Complementary Metal Oxide Semiconductor) image sensor. The signal processing module may be configured to convert an analog signal acquired from the receiver into a digital signal to generate an image of the target object. The output interface may be configured to transmit information read from the signal processing module to an external device (130). Such transmission may use a USB (Universal Serial Bus), Bluetooth, or a wireless communication protocol. However, it should be understood that the structure of the scanner (120) is not limited thereto and that components may be added, deleted, or modified to scan the target object.

[0056] The first information may include one or more images of a target battery that is the subject of the shooting. Each of the one or more images may be an image taken of the target battery from a different direction. For example, the scanner (120) may move so that the target battery is scanned from a different direction, and the scanner (120) may scan the target battery at regular intervals to generate one or more images. As another example, the target battery may be rotated on the scanning area that the scanner (120) scans, and the scanner (120) may scan the rotating target battery at regular intervals to generate one or more images.

[0057] The device (110) can receive first information from the scanner (120) via a network. Based on the first information, the device (110) can generate second information in which the target battery is represented as a three-dimensional image. In one embodiment, the second information may be reverse engineering information generated by inversely designing the shape of the target battery through one or more images generated by scanning the target battery. For example, the device (110) can generate second information in which the shape of the target battery is represented as a three-dimensional image on a three-dimensional spatial coordinate plane implemented on a computing device using CAD (Computer-Aided Design) software.

[0058] The external device (130) may be a device for performing a dismantling operation to dismantle the battery. For example, the external device (130) may include an automation device for performing a dismantling operation to the battery. For example, the automation device may dismantle the battery using a robot arm and various tools mounted on the robot arm (e.g., a bolt driver, a laser cutter, a clamp, a saw, etc.). The automation device may be equipped with a laser cutting tool, a bolting processing tool, a cable cutting tool, a cover handling tool, a scrap handling tool, a cable handling tool, etc., and the automation device may replace the tool attached to the robot arm as needed. The automation device may be configured to transport components separated from the battery pack to another location. The automation device may transfer parts dismantled from the battery pack (top cover, bottom cover, wiring, connector, temperature sensor module, BMS (Battery Management System) module, battery module, battery cell, bolt, nut, etc.) to a storage box (e.g., top cover storage box, bottom cover storage box, cell box, dismantling box, etc.).

[0059] In one embodiment, the automation device may acquire information regarding the battery from the device (110) and perform a dismantling operation on the target battery based on this information. For example, the automation device may include a control device that controls the automation device by analyzing a three-dimensional image of the target battery acquired from the device (110). The robot arm of the automation device may be driven by the control device, and the control device may be designed to set a dismantling path for the target battery components based on the three-dimensional image of the target battery and perform a dismantling operation accordingly. For example, the control device may create a virtual three-dimensional model of the target battery based on the three-dimensional image, identify the location and connection status of each component constituting the battery on the three-dimensional model, and calculate an optimal dismantling path to separate the connections of each component according to a preset algorithm. While the dismantling operation is being performed, the status of each step of the dismantling operation may be transmitted from the automation device to the device (110) via a network, and the user of the device (110) may monitor the dismantling operation on the target battery in real time.

[0060] In one embodiment, the external device (130) may include a plurality of automation devices. Each of the plurality of automation devices may perform a different operation. In one embodiment, each automation device may be a device for performing disassembly operations on a battery of a specific manufacturer. For example, in the case of a battery pack of a first manufacturer, it may include battery cells arranged in a special arrangement used by the first manufacturer, and the first automation device may include an automation tool specially designed to separate the battery cells arranged in this special arrangement from the battery pack. For example, in the case of a battery pack of a second manufacturer, it may include parts such as a special cover, case, coolant, sealant, cable, connector, etc. used by the second manufacturer, and the second automation device may include an automation tool specially designed to separate these parts from the battery pack. For example, in the case of a battery pack of a third manufacturer, it may include a unique battery cell arrangement or unique components used by the third manufacturer, and the third automation device may include an automation tool designed to be optimized for disassembling the unique battery cell arrangement or unique components. In various embodiments of the present disclosure, the device (110) transmits a three-dimensional image generated for a target battery to an automation device, and the automation device can perform the dismantling of the target battery using a battery dismantling algorithm optimized for dismantling a battery of a specific manufacturer.

[0061] In one embodiment, each automation device may be a device for performing disassembly operations on a battery having a specific product name. For example, in the case of a battery pack having a first product name, it may include a first component, and the first automation device may include an automation tool specially designed to separate the first component from the battery pack. For example, in the case of a battery pack having a second product name, it may include a second component, and the second automation device may include an automation tool specially designed to separate the second component from the battery pack. For example, in the case of a battery pack having a third product name, it may include a third component, and the third automation device may include an automation tool specially designed to separate the third component from the battery pack. In various embodiments of the present disclosure, the device (110) transmits a three-dimensional image generated for the target battery to the automation device, and the automation device may perform disassembly operations on the target battery using a battery disassembly algorithm optimized for disassembling the battery having a specific product name.

[0062] In one embodiment, each automation device may be a device for performing disassembly operations on specific parts constituting a battery. For example, a first automation device may be designed to be suitable for separating a first part constituting a battery from the battery, a second automation device may be designed to be suitable for separating a second part, and a third automation device may be designed to be suitable for separating a third part. In one embodiment, the first automation device may disassemble a part of the battery, and the second automation device or the third automation device may additionally disassemble the partially disassembled battery. In various embodiments of the present disclosure, the device (110) transmits a three-dimensional image generated for the target battery to the automation device, and the automation device may perform disassembly operations on the target battery using a battery disassembly algorithm optimized for disassembling specific parts of the battery.

[0063] Consequently, in various embodiments of the present disclosure, the device (110) transmits information about the target battery to an automation device, and the automation device can perform the dismantling of the target battery using a battery dismantling algorithm optimized for the dismantling of the target battery. Accordingly, by automating the dismantling of the target battery, the speed and safety of the battery dismantling operation can be improved, and the productivity of the battery recycling process can be increased.

[0064] According to various embodiments of the present disclosure, a plurality of automation devices may each be designed to perform a unique function. For example, a first automation device may be optimized for the separation of lithium-ion battery cells, and a second automation device may be optimized for the recovery and sorting of electrode materials. In this way, automation devices with different functions may operate complementarily to contribute to improving the overall productivity and efficiency of the battery dismantling process.

[0065] According to various embodiments of the present disclosure, dismantling operations can be performed independently in each of a plurality of automated devices. Accordingly, dismantling operations for a plurality of target batteries can be carried out simultaneously in parallel in each of the plurality of automated devices. For example, a first automated device can perform a dismantling operation for a first target battery while a second automated device performs a dismantling operation for a second target battery. That is, according to various embodiments of the present disclosure, by performing dismantling operations for a plurality of batteries simultaneously, the efficiency of the dismantling operations for multiple target batteries can be maximized, and the work time can be shortened, thereby improving productivity in battery dismantling operations.

[0066] In one embodiment, the external device (130) may additionally include various sensors for fire detection and a non-combustible firewall to effectively block the spread of fire. An example of a sensor is a carbon dioxide detection sensor, which can rapidly detect whether a fire has occurred by monitoring changes in the concentration of carbon dioxide that may occur when the battery is dismantled or damaged in real time. For example, the sensor may be an off-gas detection sensor for detecting off-gas, which is a combustible gas generated from a lithium-ion battery. By using the off-gas detection sensor, the external device (130) can prevent a fire by performing additional actions to prevent fire occurrence, such as stopping the dismantling of the battery and activating sprinklers placed around the battery, upon detection of off-gas even before a fire occurs. In addition, the sensor may include a smoke detection sensor, a temperature detection sensor, and a flame detection sensor, each of which can provide a function to detect a fire early based on changes in the concentration of fine particles, a rapid rise in temperature, and the occurrence of flames. Meanwhile, the non-combustible firewall may be composed of aramid fibers, glass fibers, and / or other flame-retardant materials, which can have the effect of preventing fire spread to adjacent battery cells or surrounding structures by physically blocking the spread of fire in the event of a fire. The external device (130) uses various sensors to detect whether a fire occurs during battery dismantling operations, and if a fire is detected, the non-combustible firewall can be used to prevent the fire from spreading to the surrounding environment or surrounding devices.

[0067] The device (110), scanner (120) and / or external device (130) can communicate through a network. This network can be implemented as any kind of wired or wireless network, such as, for example, a Local Area Network (LAN), a Wide Area Network (WAN), a Mobile Radio Communication Network (MRCN), or WiBro (Wireless Broadband).

[0068] FIG. 2 illustrates an example in which a device (110) according to one embodiment of the present disclosure is implemented. The device (110) may include one or more processors (210) and one or more memories (220). The device (110) may further include a communication circuit (230). In one embodiment, some components may be omitted from the device (110) or other components (e.g., a display or an input device, etc.) may be added to the device (110). Additionally, some components may be implemented by being integrated or by being implemented as a single or multiple entities. In the present disclosure, one or more processors (210) may be referred to as processors (210). Unless the context clearly indicates otherwise, the term processors (210) may mean a set of one or more processors. Also, in the present disclosure, one or more memories (220) may be referred to as memories (220). The term "memory" (220) may mean a set of one or more memories (220) unless the context clearly indicates otherwise.

[0069] The processor (210) can perform operations or information processing regarding the control or communication of each component of the device (110). Specifically, the processor (210) can control at least one component of the device (110) connected to the processor (210) by running software (or computer program) received from another component. As an example, the processor (210) can load instructions (e.g., instructions, code, or code segments) or information into memory (220), process instructions or information stored in memory (220), and store result information resulting from the processing in memory (220). Additionally, the processor (210) can be operatively connected to the components of the device (110) to perform various operations such as operations, processing, generation, or processing related to the present disclosure.

[0070] The memory (220) may store various information. The information stored in the memory (220) may include software, which is information acquired, processed, or used by at least one component of the device (110). The software may include one or more instructions that cause the processor (210) to perform operations according to various embodiments of the present disclosure when loaded into the memory (220). That is, the processor (210) may perform operations according to various embodiments of the present disclosure by executing the one or more instructions mentioned above. The memory (220) may include, for example, volatile or non-volatile memory. In one embodiment, the program may be software stored in the memory (220) and may include an operating system for controlling the resources of the device (110), an application, or middleware that provides various functions to the application so that the application can utilize the resources of the device (110).

[0071] A communication circuit (230) can establish a wired or wireless communication channel with another device and transmit and receive various information with that other device. In one embodiment, the communication circuit (230) may include at least one port for connecting to another device via a wired cable in order to communicate with another device via a wired connection. In this case, the communication circuit (230) can perform communication with another device that is wired through at least one port. In one embodiment, the communication circuit (230) may be configured to include a cellular communication module to be connected to a cellular network (e.g., 3G, LTE, 5G, Wibro, or Wimax). In one embodiment, the communication circuit (230) may include a short-range communication module to transmit and receive information with another device using short-range communication (e.g., Wi-Fi, Bluetooth, Bluetooth Low Energy (BLE), UWB). In one embodiment, the communication circuit (230) may include a contactless communication module for contactless communication. Contactless communication may include at least one contactless proximity communication technology, such as, for example, NFC (Near Field Communication) communication, RFID (Radio Frequency Identification) communication, or MST (Magnetic Secure Transmission) communication. In addition to the various examples described above, the device (110) may be implemented in various known ways for communicating with other devices, and the scope of the present disclosure is not limited by the examples described above.

[0072] The processor (210), memory (220), and communication circuit (230) are connected to each other via a bus, GPIO (General Purpose Input / Output), SPI (Serial Peripheral Interface), or MIPI (Mobile Industry Processor Interface), etc., so that they can give or receive information or signals.

[0073] In one embodiment, the device (110) may further include a display. The display may display various screens based on the control of the processor (210). For example, a web browser or a dedicated application may be installed on the device (110) to display screens with various interfaces applied to the display. Additionally, the display may be configured to interact with a user and may receive input from the user. Such a display may be implemented in the form of a touch sensor panel (TSP) capable of recognizing contact or proximity of various external objects (e.g., a finger or a stylus).

[0074] In one embodiment, the device (110) may further include an input device (e.g., a mouse or a keyboard). The input device may receive information to be used in a component of the device (110) from outside the device (110).

[0075] Hereinafter, methods according to various embodiments of the present disclosure will be described in detail. It should be noted that although operations are illustrated in a specific order in the drawings below, the operations must not necessarily be executed in the specific order illustrated or in a sequential order, or all illustrated operations must be executed to obtain the desired result.

[0076] Additionally, the operation of the method described below with reference to the drawings may be performed by a computing device. In other words, the operation of the method may be implemented by one or more instructions executed by the processor (210) of the computing device. All operations included in this method may be performed by a single physical computing device, but the first operation of the method may be performed by the first computing device and the second operation of the method may be performed by the second computing device.

[0077] In the following, the explanation will continue assuming that the operation of the aforementioned method is performed by the device (110). Additionally, for the convenience of explanation, the subject of the operation included in the method may be omitted, but unless otherwise indicated by the context, it should be interpreted that the operation is performed by the device (110).

[0078] FIG. 3 illustrates a flowchart illustrating a method according to one embodiment of the present disclosure. The method may include a series of operations performed by a device (110) in conjunction with a scanner (120) and / or an external device (130).

[0079] In step S310, the processor (210) may receive first information regarding one or more images generated by scanning a target battery from the scanner (120). The scanner (120) may scan the target battery to generate an image regarding the target battery, and the processor (210) may receive the image from the scanner (120) via a network.

[0080] In one embodiment, the scanner (120) may scan the target battery at regular intervals to generate one or more images. Each of the one or more images may be an image taken from a different direction with respect to the target battery. For example, one or more images may be generated by scanning the target battery at regular intervals while the scanner (120) moves around the target battery while the target battery is stationary. As another example, the scanner (120) may scan the target battery on the scanning area at regular intervals while the target battery is stationary, and one or more images may be generated as the target battery rotates on the scanning area.

[0081] In one embodiment, the fixed time interval may be a predetermined interval. For example, the scanner (120) may be pre-set to scan the target battery at intervals of 0.01 seconds. For example, if the scanner (120) scans the target battery for 1 second, the scan is performed at intervals of 0.01 seconds, and 100 images may be generated in 1 second.

[0082] In one embodiment, the scanner (120) can be controlled so that a certain time interval is set smaller than a predetermined interval. For example, the processor (210) can control the scanner (120) so that a certain time interval is set to 0.005 seconds, which is smaller than a predetermined interval of 0.01 seconds. In this case, more images can be acquired during the same time period, and accordingly, when generating a three-dimensional image of the target battery described later, the shape of the battery in the three-dimensional image can be more similar to the shape of the actual target battery.

[0083] In one embodiment, the scanner (120) can be controlled so that a certain time interval is set smaller than a predetermined interval. For example, the processor (210) can control the scanner (120) so that a certain time interval is set to 0.02 seconds, which is larger than the predetermined interval of 0.01 seconds. In this case, fewer images can be acquired during the same period of time, and accordingly, as the amount of images processed by the processor (210) is reduced in generating a three-dimensional image of the target battery described later, the time required to generate the three-dimensional image can be reduced.

[0084] In one embodiment, a user of the device (110) can input user input through the input device of the device (110), and the processor (210) can adjust a certain time interval based on the user input.

[0085] In step S320, the processor (210) may generate second information regarding a three-dimensional image of the target battery based on the first information. For example, the second information may include coordinate information for one or more points corresponding to the surface of the target battery on a three-dimensional spatial coordinate plane. For example, the second information may be information in which the surface of the target battery on the three-dimensional spatial coordinate plane is represented in a mesh data format.

[0086] In one embodiment, the processor (210) can generate point cloud information corresponding to the surface of the target battery using each of one or more images. Based on the point cloud information, the processor (210) can generate a three-dimensional image of the target battery. Based on the point cloud information corresponding to each of one or more images, the processor (210) can generate the shape of the target battery on a three-dimensional spatial coordinate plane by connecting points corresponding to the same point on the surface of the target battery in each image. For example, the processor (210) can further process information so that the shape of the target battery on the spatial coordinate plane is expressed in a mesh data format. This mesh data is composed of polygonal faces and can generally be composed of triangular elements. As the shape of the target battery is expressed in a mesh data format, the processor (210) can reproduce the shape and contour of the surface of the target battery. However, it is not limited thereto, and the second information may be information of various structures that represent the target battery as a three-dimensional image.

[0087] In step S330, the processor (210) may generate third information by identifying one or more features of the target battery based on the first information. In one embodiment, the processor (210) may input the first information into an artificial neural network trained to identify one or more features of the battery from an image of the battery, thereby obtaining prediction information about the target battery as the output of the artificial neural network. The processor (210) may generate third information based on the prediction information.

[0088] For example, an artificial neural network may be a supervised learning-based classification model. The artificial neural network may be generated by learning from images of one or more batteries, and may be designed to identify one or more features of the batteries from the images.

[0089] For the training of an artificial neural network, a label indicating a class and an input image can be used as training data as a pair. Additionally, evaluation data for evaluating the training of the artificial neural network may be provided separately from the training data.

[0090] In one embodiment, an artificial neural network may be generated by learning a label indicating the manufacturer and an image of the battery to identify the manufacturer of the battery. Specifically, "Image A" of a battery whose manufacturer is Manufacturer A and "Manufacturer A" as a label may be used as a pair of first training data, "Image B" of a battery whose manufacturer is Manufacturer B and "Manufacturer B" as a label may be used as a pair of second training data, and "Image C" of a battery whose manufacturer is C and "Manufacturer C" as a label may be used as a pair of third training data. Accordingly, as the image of the target battery is input, the artificial neural network may output information indicating the manufacturer of the target battery as predicted information. The third information may include information regarding the manufacturer of the battery indicated in the predicted information.

[0091] In one embodiment, an artificial neural network may be generated by learning a label indicating a product name and an image of a battery to identify the product name of the battery. Specifically, "Image A" of a battery whose product name is Product Name A and "Product Name A" as a label may be used as a pair of first training data, "Image B" of a battery whose product name is Product Name B and "Product Name B" as a label may be used as a pair of second training data, and "Image C" of a battery whose product name is C and "Product Name C" as a label may be used as a pair of third training data. Accordingly, as an image of a target battery is input, the artificial neural network may output information indicating the product name of the target battery as prediction information. The third information may include information regarding the product name of the battery indicated in the prediction information.

[0092] In one embodiment, an artificial neural network may be generated by learning an image of a battery and a label indicating the field of use of the battery to identify the field in which the battery is used. Specifically, "Image A" of a battery used in the "electric vehicle" field and the label "electric vehicle" may be used as a pair of first training data; "Image B" of a battery used in the "hybrid electric vehicle" field and the label "hybrid" may be used as a pair of second training data; "Image C" of a battery used in the "fuel cell electric vehicle" field and the label "fuel cell electric vehicle" may be used as a pair of third training data; and "Image D" of a battery used in the "energy storage system" field and the label "energy storage system" may be used as a pair of fourth training data. Accordingly, as the image of the target battery is input, the artificial neural network can output information regarding the field in which the target battery is used as predicted information. The third information may include information regarding the field in which the battery is used indicated in the predicted information.

[0093] In one embodiment, an artificial neural network may be generated by learning a label indicating a component and an image of the battery to identify the components constituting the battery. For example, the components constituting the battery may include any one of an upper cover, a lower cover, wiring, a connector, a temperature sensor module, a Battery Management System (BMS) module, a battery module, a battery cell, a bolt, a nut, etc. As a specific example, "Image A" of a battery whose component is wiring and "Wiring" as a label may be used as a pair of first training data, "Image B" of a battery whose component is a battery module and "Battery Module" as a label may be used as a pair of second training data, and "Image C" of a battery whose component is a BMS module and "BMS Module" as a label may be used as a pair of third training data. Accordingly, as an image of the target battery is input, the artificial neural network may output information indicating the components of the target battery as prediction information. In one embodiment, the prediction information may further include information indicating the location of the component identified by the artificial neural network. The third information may include information regarding the battery components and / or the location of the battery components indicated in the prediction information.

[0094] In one embodiment, an artificial neural network may be generated by learning a label indicating the packaging type and an image of the battery to identify the packaging type of the battery. For example, the packaging type may include any one of cylindrical, prismatic, or pouch types. As a specific example, "Image A" of a battery with a cylindrical packaging type and a label "cylindrical" may be used as a pair of first training data, "Image B" of a battery with a prismatic packaging type and a label "prismatic" may be used as a pair of second training data, and "Image C" of a battery with a pouch packaging type and a label "pouch type" may be used as a pair of third training data. Accordingly, as an image of the target battery is input, the artificial neural network may output information indicating the packaging type of the target battery as prediction information. The third information may include information regarding the packaging type of the battery indicated in the prediction information.

[0095] In one embodiment, an artificial neural network may be generated by learning a label indicating information regarding defects and an image of a battery to identify information regarding defects. For example, information regarding defects may refer to types of defects such as defects caused by impact, defects caused by poor component connections, defects caused by fire, or defects caused by missing components. As a specific example, "Image A" of a battery with defect A and "Defect A" as a label may be used as a pair of first training data, "Image B" of a battery with defect B and "Defect B" as a label may be used as a pair of second training data, and "Image C" of a battery with defect C and "Defect C" as a label may be used as a pair of third training data. Accordingly, as an image of a target battery is input, the artificial neural network may output information indicating defects of the target battery as prediction information. The third information may include information regarding defects of the battery indicated in the prediction information.

[0096] In one embodiment, an artificial neural network may be generated by learning an image of a battery and a label indicating the presence or absence of a defect to identify whether a defect exists in the battery. Specifically, "Image A" of a defective battery and the label "Defective" may be used as a pair of first training data, and "Image B" of a non-defective battery and the label "No Defect" may be used as a pair of second training data. Accordingly, as the image of the target battery is input, the artificial neural network may output information indicating whether the target battery has a defect as prediction information. The third information may include information regarding the presence or absence of the battery defect indicated in the prediction information.

[0097] An artificial neural network can derive regularities from multiple training data during the learning process and classify a new image into a corresponding label when the image is input. Various known technologies may be referenced in this disclosure for the implementation of such an artificial neural network.

[0098] In one embodiment, the artificial neural network may be stored in memory (220) in a state where training is complete, and this may be implemented using various forms of storage means including semiconductor memory devices, flash memory, or magnetic storage devices. In one embodiment, the artificial neural network may be implemented through a computing device such as a neuromorphic processor. A neuromorphic processor is a dedicated processor for hardware-accelerating the computation of a neural network and may be designed to efficiently perform parallel computations by mimicking the functions of human brain neurons and synapses. In one embodiment, the artificial neural network may be implemented in an optimized form through a hardware accelerator such as a Field-Programmable Gate Array (FPGA) or an Application-Specific Integrated Circuit (ASIC), and such a hardware accelerator can significantly improve the learning and inference speed of the neural network. According to various embodiments of the present disclosure, the artificial neural network may be stored and implemented through various types of storage media and computing devices, thereby improving the performance and efficiency of the neural network.

[0099] In one embodiment, learning information can be generated by labeling features regarding the target battery in the first information. Based on the learning information, the processor (210) can further train an artificial neural network.

[0100] In various embodiments of the present disclosure, steps S320 and S330 may be performed in parallel on at least one processor (210), and according to other embodiments, these steps may be performed sequentially. The order in which each step is performed may not be limited to a specific order. That is, steps S320 and S330 may be performed simultaneously or independently as needed, taking into account the performance and capacity of the processor (210).

[0101] In step S340, the processor (210) may generate fourth information in which information regarding one or more features of the target battery is labeled on a three-dimensional image regarding the target battery, based on the second information and the third information. Here, labeling specific information on the three-dimensional image may mean that specific information corresponds to a specific area or a specific location of the three-dimensional image. For example, the processor (210) may generate any metadata that tags specific information on a part of the three-dimensional image or a specific location, marks specific information as an annotation, or corresponds specific information to a specific location.

[0102] In one embodiment, if the third information indicates a feature regarding the manufacturer of the battery, the processor (210) may generate the fourth information by labeling the battery manufacturer information on a three-dimensional image. In one embodiment, if the third information indicates a feature regarding the product name of the battery, the processor (210) may generate the fourth information by labeling the battery product name information on a three-dimensional image.

[0103] In one embodiment, when the third information indicates a feature regarding a component of a battery, the processor (210) may generate fourth information by labeling the component information of the battery onto a three-dimensional image. For example, the processor (210) may determine the location of the component of the battery on the three-dimensional image and label the component information so that it corresponds to the determined location. Accordingly, the fourth information may include information indicating the component of the battery and information indicating the location of the component of the battery.

[0104] In one embodiment, when the third information indicates a feature regarding a defect in the battery, the processor (210) may generate fourth information by labeling the defect information of the battery onto a three-dimensional image. For example, the processor (210) may determine the type and location of the defect in the battery on the three-dimensional image and label the determined location so that information indicating the type of defect corresponds to it. Accordingly, the fourth information may include information indicating the type of defect (or, type of defect) of the battery and information indicating the location of the defect in the battery.

[0105] In step S350, the processor (210) may transmit the fourth information to an external device (130) that performs dismantling operations on the target battery. In one embodiment, the external device (130) may include one or more automation devices. The processor (210) may transmit the fourth information to any one of the one or more automation devices.

[0106] In one embodiment, the processor (210) may associate the second information and the third information with each other and store them in one or more memories (220). When the second information and the third information are generated for one or more target batteries, the processor (210) may associate the second information and the third information for each of the one or more target batteries. For example, the second information and the third information generated for the first target battery may be associated, and the second information and the third information generated for the second target battery may be associated. As the second information and the third information are associated for each of the one or more target batteries and stored in the memory (220), the characteristics of various batteries can be built into a database, and by systematically storing and managing various information regarding various batteries, it is possible to easily refer to the information required when dismantling or recycling batteries.

[0107] FIG. 4 illustrates an example of a work environment in which a dismantling operation of a battery is performed, which may be referenced in various embodiments of the present disclosure. The work environment of FIG. 4 may include a scanner (120a), a storage device (410), a transfer device (420), first to third work tables (441, 442, 443), and first to third automation devices (131, 132, 133).

[0108] The storage device (410) may include a storage rack for storing one or more batteries. For example, the storage rack may include one or more shelves, and each shelf is structured to allow the batteries to be placed stably. Each shelf may be designed in an adjustable form according to the size and shape of the batteries and may additionally include supports or clips for securing the batteries. One or more batteries may be arranged on each shelf. The spacing between shelves in the storage rack may be adjustable, thereby accommodating batteries of various sizes. Additionally, to increase user convenience, the storage rack may be designed to have movable wheels or a foldable structure, and may be equipped with a cover or door to protect the batteries from environmental factors as needed.

[0109] The transfer device (420) may be a device that moves batteries stored in the storage device (410) to a workbench. In various embodiments of the present disclosure, the transfer device (420) for transferring batteries may be implemented in various forms. For example, the transfer device (420) may include a forklift, an Automated Guided Vehicle (AGV), etc. For example, a forklift may be configured to safely and efficiently transport batteries of various sizes and weights by being equipped with specially designed forks or carriers for loading batteries. For example, an AGV may automatically transport loaded batteries along a pre-programmed path and may include a function to detect and avoid obstacles through sensors.

[0110] In one embodiment, the unmanned transport vehicle can transport a battery from a starting point to a destination under the control of the device (110). For example, the device (110) can transmit information to the unmanned transport vehicle indicating the location of a storage rack as the starting point and the location of a target automation device among one or more automation devices as the destination, and accordingly, the unmanned transport vehicle can transport the battery from the storage rack to the automation device.

[0111] In one embodiment, an unmanned transport vehicle can transport a battery from a starting point to a destination under the control of an external server. For example, the device (110) transmits location information of the starting point and the destination to an external server, and the external server can control the unmanned transport vehicle to move from the starting point to the destination upon receiving the location information.

[0112] Each of one or more automation devices can perform dismantling operations on batteries at different workbenches. In one embodiment, the first automation device (131) can perform dismantling operations on batteries manufactured by a specific manufacturer at the first workbench (441). In one embodiment, the second automation device (132) can perform dismantling operations on batteries having a specific product name at the second workbench (442). In one embodiment, the third automation device (133) can perform dismantling operations to separate components constituting the battery from the battery at the third workbench (443).

[0113] The transfer device (420) can transport the battery to any one of the first workbench (441) to the third workbench (443). In one embodiment, the device (110) can generate fourth information regarding the target battery, determine a target automation device suitable for the dismantling operation of the target battery among the first automation device (131) to the third automation device (133), and transmit the fourth information to the target automation device. In one embodiment, the device (110) may be further configured to control the transfer device (420). The device (110) can control the transfer device (420) to transport the battery to the workbench corresponding to the target automation device to which the fourth information is transmitted.

[0114] In one embodiment, the scanner (120a) may be provided in a portable form. For example, the scanner (120a) may include a handle designed to allow the operator to easily carry it. The operator can scan batteries from various angles by physically moving the scanner (120a). Specifically, the operator can continuously scan multiple batteries stored in the rack while holding the scanner (120a) in their hand and moving along the storage rack, and the device (110) can receive information regarding images of each of the multiple batteries being scanned from the scanner (120a). Such scanning operations may be particularly useful in warehouses or logistics centers managing large quantities of batteries. In one embodiment, the scanner (120a) can transmit scanned data to the device (110) in real time via a network, and accordingly, the device (110) can monitor and manage the inventory and status of the scanned batteries in real time.

[0115] In one embodiment, the scanner (120a) may be installed on a transport device. For example, the scanner (120a) may be designed to be positioned at various locations on the unmanned transport vehicle to perform automated scanning operations. For example, the scanner may be installed on the upper part of the fork of the unmanned transport vehicle to scan batteries during the process of storing or taking out batteries from a storage rack. Additionally, the scanner may include a structure attached to the side or bottom of the carrier of the unmanned transport vehicle to scan batteries loaded on the carrier. Furthermore, the scanner may be positioned at the top of the unmanned transport vehicle to simultaneously scan multiple batteries loaded on the unmanned transport vehicle while the vehicle is in motion, thereby providing the function of rapidly scanning multiple batteries during the process of transporting batteries. Moreover, the scanner may transmit information generated from the scan results to the device (110) in real time via a network. In various embodiments of the present disclosure, scanning operations may be automated according to the placement and structure of such a scanner (120a), thereby reducing the workload of the operator performing the scanning operation and improving work efficiency.

[0116] FIG. 5 illustrates another example of a work environment in which a dismantling operation of a battery is performed, which may be referenced in various embodiments of the present disclosure. Hereinafter, descriptions of elements substantially identical to those described in FIG. 4 will be omitted, and the differences will be described in detail. The work environment of FIG. 5 may include a scanner (120b), a storage device (410), a first transfer device (521), a scanning work table (530), a second transfer device (522), first to third work tables (441, 442, 443), and first to third automation devices (131, 132, 133). The first transfer device (521) can transport one or more batteries stored in the storage device (410) to the scanning work table (530). In one embodiment, the second transfer device (522) can transfer the battery (535), which has been scanned at the scan workbench (530), to one of the first to third workbenches (441, 442, 443).

[0117] In one embodiment, the scanner (120b) may be provided in a fixed form. A rotatable turntable may be mounted on the scanning workbench (530) on which the scanner (120b) is placed. A specific target object, such as a battery, is loaded onto the turntable, and as the turntable rotates, the object moves circumferentially within the field of view of the scanner (120b). The scanner (120b) can capture the entire external shape of the target object from various angles using this mechanical rotational motion, thereby enabling precise scanning of the object's three-dimensional shape information. The rotational speed and direction of the turntable can be controlled by a control device, allowing for efficient and flexible scanning operations tailored to various scanning requirements. In various embodiments of the present disclosure, due to the structural characteristics in which the scanner (120b) is fixed on the scanning workbench (530), the impact of vibrations occurring during scanning operations can be minimized, thereby increasing the precision of the image acquired by the scanner (120b).

[0118] However, the structure and / or arrangement of the scanner (120b) is not limited thereto, and the scanner (120b) may scan the battery on the scan workbench (530) while rotating or moving while the scan workbench (530) is fixed. For example, the scanner (120b) may be designed to rotate 360 ​​degrees around the battery or move in a hemispherical shape on the upper side of the battery to scan the front of the battery. In various embodiments of the present disclosure, the battery can be scanned precisely from various angles due to the structural characteristics of the scanner (120b) moving on the scan workbench (530). As such, the rotation and movement method of the scanner can be appropriately adjusted according to the shape and size of the battery located on the scan workbench, and an optimal scan path can be provided based on the structural characteristics of the target battery being scanned.

[0119] FIG. 6 illustrates a flowchart illustrating a method of transmitting fourth information from a device (110) to an external device (130) in various embodiments of the present disclosure. The external device (130) may include one or more automated devices. The flowchart of FIG. 6 may be an example of a method of handling third information and / or fourth information generated by performing the method (300) of FIG. 3 on a target battery in various embodiments of the present disclosure.

[0120] In step S610, the processor (210) may determine, based on the third information, a target automation device that performs dismantling operations related to one or more features of the target battery among one or more automation devices. In step S620, the processor (210) may transmit the fourth information to the target automation device.

[0121] In one embodiment, the memory (220) may store information corresponding to various automation devices for performing a battery dismantling operation. This information may include information regarding the type of automation device corresponding to each automation device, the type of battery suitable for dismantling in the automation device, and the type of part suitable for dismantling in the automation device. Based on the third information and the information stored in the memory (220), the processor (210) may determine a target automation device among one or more target automation devices.

[0122] FIG. 7 illustrates a flowchart illustrating a method of transmitting fourth information from a device (110) to a first automation device in various embodiments of the present disclosure. In step S710, the processor (210) of the device (110) may obtain third information indicating the manufacturer of the target battery. In one embodiment, the third information may be information indicating the first manufacturer of the battery.

[0123] In step S720, the processor (210) of the device (110) may determine, among one or more automation devices, an automation device optimized for dismantling a battery manufactured by the first manufacturer as the target automation device. For example, the memory (220) of the device (110) may store information indicating the first automation device as an automation device suitable for dismantling the battery of the first manufacturer, and the processor (210) may use this information to determine the first automation device as the target automation device.

[0124] In step S730, as the first automation device is determined to be the target automation device, the device (110) can transmit the fourth information to the first automation device. In one embodiment, as the device (110) transmits the fourth information to the first automation device, it can control an unmanned transport vehicle to move the target battery by the unmanned transport vehicle to a first workbench where the first automation device performs dismantling work.

[0125] In step S740, the first automation device may perform a dismantling operation on the target battery based on the fourth information. The fourth information may include a three-dimensional image of the target battery. The first automation device may perform a dismantling operation on the target battery by utilizing the three-dimensional image of the target battery.

[0126] FIG. 8 illustrates a flowchart illustrating a method of transmitting fourth information from a device (110) to a second automation device in various embodiments of the present disclosure. In step S810, the device (110) may obtain third information indicating the product name of a target battery. In one embodiment, the third information may be information indicating the specific product name of the battery.

[0127] In step S820, the processor (210) of the device (110) may determine an automation device optimized for dismantling a battery having a specific product name among one or more automation devices as the target automation device. For example, the memory (220) of the device (110) may store information indicating a second automation device as an automation device suitable for dismantling a battery of a specific product name, and the processor (210) may use this information to determine the second automation device as the target automation device.

[0128] In step S830, as the second automation device is determined to be the target automation device, the device (110) can transmit the fourth information to the second automation device. In one embodiment, as the device (110) transmits the fourth information to the second automation device, it can control an unmanned transport vehicle to move the target battery by the unmanned transport vehicle to a second workbench where the second automation device performs dismantling work.

[0129] In step S840, the second automation device may perform a dismantling operation on the target battery based on the fourth information. The fourth information may include a three-dimensional image of the target battery. The second automation device may perform a dismantling operation on the target battery by utilizing the three-dimensional image of the target battery.

[0130] FIG. 9 illustrates a flowchart illustrating a method of transmitting fourth information from a device (110) to a third automation device in various embodiments of the present disclosure. In step S910, the device (110) may obtain third information indicating one or more parts of a target battery. For example, the third information may be obtained indicating a first part.

[0131] In step S920, the processor (210) of the device (110) may determine, among one or more automation devices, an automation device optimized for dismantling a first component of the battery as the target automation device. For example, the memory (220) of the device (110) may store information indicating a third automation device as an automation device suitable for the dismantling operation of the first component, and the processor (210) may use this information to determine the third automation device as the target automation device.

[0132] In step S930, as the third automation device is determined to be the target automation device, the device (110) can transmit the fourth information to the third automation device. In one embodiment, as the device (110) transmits the fourth information to the third automation device, it can control an unmanned transport vehicle to move the target battery by the unmanned transport vehicle to a third workbench where the third automation device performs dismantling work.

[0133] In step S940, the third automation device may perform a dismantling operation on the target battery based on the fourth information. The fourth information may include a three-dimensional image of the target battery. In one embodiment, the fourth information may be information tagged with information indicating a first part at a location corresponding to the first part on the three-dimensional image. The third automation device may perform a dismantling operation on the target battery by utilizing the three-dimensional image of the target battery and the information indicating the location of the first part.

[0134] FIG. 10 illustrates a flowchart illustrating a method according to one embodiment of the present disclosure. The method according to FIG. 10 may be a method for determining whether to perform a dismantling operation on a target battery according to a defect state of the target battery identified in third information.

[0135] In step S1010, the processor (210) can determine, based on the third information, whether the defect state of the target battery corresponds to a predetermined first reference state.

[0136] In one embodiment, a predetermined first reference state may be a state in which the battery is defective. For example, upon obtaining third information indicating that the target battery is defective, the processor (210) may determine that the defective state of the target battery corresponds to the first reference state.

[0137] In one embodiment, a predetermined first reference state may be a state in which the battery has a first type of defect. For example, upon obtaining third information indicating that the target battery has a first type of defect, the processor (210) may determine that the defect state of the target battery corresponds to the first reference state. As another example, upon obtaining third information indicating that the target battery has a defect but is of a type other than the first type (e.g., a second type), the processor (210) may determine that the defect state of the target battery does not correspond to the first reference state. For example, the first type of defect may be a defect indicating that the battery has discolored due to fire, and the second type of defect may be a defect indicating that the battery has distorted in appearance due to impact. Thus, in various embodiments of the present disclosure, depending on the type of defect indicated in the third information, the processor (210) may determine whether the defect state of the target battery is the first reference state.

[0138] In step S1020, based on the determination that the defect state is a first reference state, the processor (210) may generate and transmit to an external device (130) fifth information indicating that the target battery is not to be moved to an automated device. The external device (130) may include a transfer device. In one embodiment, upon receiving the fifth information, the external device (130) may not perform dismantling operations on the target battery. For example, the external device (130) may control the transfer device to transport the target battery to an area for storing batteries to be discarded.

[0139] In various embodiments of the present disclosure, by preventing defective or fire-risk batteries from entering the automated dismantling device, the risk of fire that may occur during the dismantling process can be prevented in advance. Accordingly, damage to the automated device can be prevented during the process of performing dismantling operations on the battery.

[0140] In the flowcharts of the present disclosure, the operations of the method or algorithm are described in a sequential order, but may be performed in any combination other than sequentially. The description of the flowcharts of the present disclosure does not exclude changes or modifications to the method or algorithm and does not imply that any operation is essential or desirable. In one embodiment, at least some operations may be performed in parallel, iteratively, or heuristically. In another embodiment, at least some operations may be omitted or other operations may be added.

[0141] Various embodiments of the present disclosure may be implemented as software on a machine-readable storage medium (MRSM). The software may be software for implementing various embodiments of the present disclosure. The software may be inferred from the various embodiments of the present disclosure by programmers in the art to which the present disclosure belongs. For example, the software may be a computer program containing instructions that can be read by a computing device. A computing device is a device capable of operating according to instructions called from a storage medium, and may be referred to interchangeably with, for example, an electronic device. In one embodiment, a processor (210) of a computing device may execute a called instruction to cause components of the computing device to perform functions corresponding to the instruction. A storage medium may refer to any type of recording medium in which information is stored that can be read by a device. A storage medium may include, for example, ROM, RAM, CD-ROM, magnetic tape, floppy disk, or optical information storage device. In one embodiment, the storage medium may be implemented in a distributed form in a networked computer system, etc. In this case, the software may be stored and executed in a distributed manner in a computer system, etc. In another embodiment, the storage medium may be a non-transitory storage medium. A non-transitory storage medium refers to a medium that exists regardless of whether information is stored semi-permanently or temporarily, and does not include signals that are transmitted transitorily.

[0142] Although the technical concept according to the present disclosure has been described by various embodiments above, the technical concept according to the present disclosure includes various substitutions, modifications, and changes that can be made within the scope of understanding of a person skilled in the art to which the present disclosure pertains. Furthermore, it should be understood that such substitutions, modifications, and changes may be included within the scope of the appended claims.

Claims

1. A device comprising: one or more processors; and one or more memory devices that store instructions executed by one or more processors, wherein, when one or more processors execute instructions, one or more processors are configured to: receiving from the scanner first information associated with one or more images generated by scanning the target battery, generating, based on the first information, second information associated with the three-dimensional image of the target battery, generating, based on the first information, a third information by identifying one or more characteristics of the target battery, generating, based on the second information and the third information, a fourth information in which information related to one or more characteristics of the target battery is marked on the three-dimensional image of the target battery, and transmitting the fourth information to an external device configured to perform a disassembly operation for the target battery.

2. The device according to paragraph 1, characterized in that one or more processors are configured to, when generating the second information: generating point cloud information for each of one or more images corresponding to the surface of the target battery, and generating a three-dimensional image of the target battery based on the point cloud information.

3. The device according to paragraph 1, characterized in that one or more processors are configured to, when generating third information: obtaining, by inputting first information into an artificial neural network that is trained to identify one or more characteristics of a battery from an image of the battery, predictive information regarding a target battery as output data of the artificial neural network, and generating third information based on predictive information.

4. The device according to paragraph 3, characterized in that one or more processors are configured to: generating, based on the first information, training information by labeling one or more characteristics of the target battery and learning, based on information for learning, artificial neural network in addition.

5. The device of claim 3, wherein the third information is information indicating one or more characteristics associated with the manufacturer of the target battery.

6. The device of claim 3, wherein the third information is information indicating, as one or more characteristics related to the field in which the target battery is used, any of an electric vehicle, a hybrid electric vehicle, a fuel cell electric vehicle, or an energy storage system.

7. The device of claim 3, wherein the third information is information indicating one or more characteristics associated with one or more components that make up the target battery.

8. The device of claim 3, wherein the third information is information indicating, as one or more characteristics associated with the packaging shape of the target battery, any of a cylindrical shape, a prismatic shape, or a bag-shaped shape.

9. The device of claim 3, wherein the third information is information indicating one or more characteristics associated with a defect in the target battery.

10. The device according to claim 1, characterized in that one or more processors are configured to compare the second information and the third information with each other and store the second information and the third information in one or more storage devices.

11. The device according to paragraph 1, characterized in that one or more processors are configured to, when generating the fourth information: determining one or more locations corresponding to one or more characteristics on a three-dimensional image of the second information, and generating fourth information by marking information associated with one or more characteristics in one or more locations.

12. The device according to item 1, characterized in that the external device contains one or more automated devices, and wherein one or more processors are configured to, when transmitting the fourth information: determining, on the basis of the third information, a target automated device configured to perform a disassembly operation associated with one or more characteristics, among one or more automated devices, and transmission of the fourth information to the target automated device.

13. The device of claim 12, wherein the third information is information indicating a first type among one or more types of battery products, and wherein one or more processors are configured to, when determining a target automated device, determine from among the one or more automated devices an automated device configured to perform a disassembly operation for a battery of the first type, as the target automated device.

14. The device of claim 12, wherein the third information is information indicating a first component among one or more components constituting the battery, and wherein one or more processors are configured to, when determining the target automated device, determine an automated device from among one or more automated devices configured to perform the disassembly operation for the first component, as the target automated device.

15. The device according to claim 1, characterized in that the third information is information indicating a characteristic associated with the battery fault condition, and wherein one or more processors are configured to: determining, based on the third information, whether the fault state of the target battery corresponds to a predetermined first reference state, and generating, in response to determining that the fault condition corresponds to the first reference condition, fifth information indicating not to move the target battery to the automated device, and transmitting the fifth information to the external device.

16. A method performed by a device comprising one or more processors and one or more memory devices storing instructions executable by the one or more processors, the method including, by means of the one or more processors: receiving from the scanner first information associated with one or more images generated by scanning the target battery; generating, based on the first information, second information associated with a three-dimensional image of the target battery; generating, based on the first information, third information by identifying one or more characteristics of the target battery; generating, based on the second information and the third information, a fourth information in which information related to one or more characteristics of the target battery is marked on the three-dimensional image of the target battery; and transmitting the fourth information to an external device configured to perform a disassembly operation for the target battery.

17. The method according to claim 16, characterized in that generating the second information includes, by means of one or more processors: generating point cloud information for each of one or more images corresponding to the surface of the target battery, and generating a three-dimensional image of the target battery based on the point cloud information.

18. The method according to claim 16, characterized in that generating the third information includes, by means of one or more processors: obtaining, by inputting first information into an artificial neural network that is trained to identify one or more characteristics of a battery from an image of the battery, predictive information regarding a target battery as output data of the artificial neural network, and generating third information based on predictive information.

19. The method of claim 18, wherein the third information is information indicating one or more characteristics associated with the manufacturer of the target battery.

20. The method of claim 18, wherein the third information is information indicating one or more characteristics associated with one or more components making up the target battery.