KR20220133695A - Method for detecting anomaly in charger/discharger based on charger/discharger data for manufacturing or evaluating lithium-ion battery - Google Patents

Abstract

This disclosure relates to a method for detecting abnormal charge-discharger based on charge-discharge data for manufacturing or evaluating a lithium-ion battery, which is executed by at least one processor. The method for detecting an abnormal charge-discharger includes the steps of: collecting charger and discharger evaluation data of one or more charge-discharger; detecting an anomaly in at least one channel among a plurality of channels included in one or more charger-discharger, based on the collected charge-discharger evaluation data; and performing a predetermined action on at least one channel in which an abnormality is detected.

Description

METHOD FOR DETECTING ANOMALY IN CHARGER/DISCHARGER BASED ON CHARGER/DISCHARGER DATA FOR MANUFACTURING OR EVALUATING LITHIUM-ION BATTERY

The present disclosure relates to a method for detecting a charger/discharger abnormality based on charger/discharger data for manufacturing or evaluating a lithium ion battery, and specifically, by collecting charger/discharging evaluation data of one or more chargers/dischargers and includes them in one or more chargers/dischargers The present invention relates to a method of detecting an anomaly for at least one channel among a plurality of channels, and performing a predetermined action on at least one channel in which the anomaly is detected.

In general, lithium ion batteries use a lithium compound as a positive electrode active material, and use carbon or graphite as a negative electrode active material. As a battery using an organic solvent as an electrolyte, it is more efficient than a nickel-cadmium battery, so it is widely used in portable devices. Lithium-ion batteries with higher capacity last longer and have better efficiency, but be careful as they can explode at high temperatures. In manufacturing/evaluating a lithium ion battery, the temperature may rise due to a rapid chemical reaction of the battery during charging/discharging due to a battery abnormality or a charging/discharging equipment abnormality. These anomalies can lead to the generation of harmful gases, combustible gases, and even fires and explosions. In addition, when the lithium ion battery is manufactured with a charger and discharger and the evaluation is repeated, the internal short circuit of the battery does not have a large characteristic at the beginning, and as the battery deteriorates, the characteristic begins to gradually develop. It may lead to fire or explosion.

The conventional charging/discharging equipment of a lithium ion battery may detect heat and smoke caused by a fire by using a temperature sensor, a smoke sensor, and the like in the charger/discharger. When a temperature sensor or smoke sensor in the charger/discharger is used, the sensor operates at a time when the risk such as a fire is extremely high, so it is difficult for workers to cope with it, and on holidays and at night, it may spread to a large fire. In addition, an abnormal alarm and an alarm sound may be generated or an alarm sound may not be generated due to a malfunction due to a failure of the charging/discharging device.

The present disclosure provides a method for detecting an abnormality in a charger and discharger, a computer program stored in a recording medium, and an apparatus (system) for solving the above problems.

The present disclosure may be implemented in various ways including a method, an apparatus (system), or a computer program stored in a readable storage medium.

According to an embodiment of the present disclosure, a method of detecting an abnormality in a charger/discharger based on charger/discharger data for manufacturing or evaluating a lithium ion battery, executed by at least one processor, may include charge/discharger evaluation data of one or more chargers/dischargers. Collecting, based on the collected charger/discharger evaluation data, detecting an anomaly with respect to at least one channel among a plurality of channels included in one or more chargers/dischargers, and at least one channel in which the abnormality is detected. performing a predetermined action on the

According to an embodiment of the present disclosure, the one or more chargers/dischargers includes a plurality of chargers/dischargers, and the collecting may include converting evaluation data in one or more formats generated from the plurality of chargers/dischargers into data in an analytic form. and collecting the converted data in a form that can be analyzed as charging/discharging evaluation data.

According to an embodiment of the present disclosure, the detecting may include, based on the charger/discharger evaluation data, whether the evaluation data associated with at least one channel among a plurality of channels included in the one or more chargers/dischargers satisfies a predetermined safety condition generating a determination result for , and determining an anomaly for at least one channel in real time based on the generated determination result.

According to an embodiment of the present disclosure, the detecting may include, based on the collected charger/discharger evaluation data, an internal short of a lithium ion battery associated with at least one channel among a plurality of channels included in one or more chargers/dischargers. generating a determination result of whether or not and detecting an abnormality in at least one channel based on the generated determination result.

According to an embodiment of the present disclosure, generating a determination result as to whether or not an internal short circuit of a lithium ion battery associated with at least one channel among a plurality of channels is performed may include sub-evaluation data collected from at least one channel. generating a voltage model, calculating a difference between the generated sub-voltage model and a standard voltage model associated with the one or more chargers/dischargers, and based on the calculated difference and the threshold, the interior of the lithium ion battery associated with at least one channel and determining whether or not there is a short circuit.

According to an embodiment of the present disclosure, the standard voltage model is generated by clustering voltage models of each of a plurality of channels included in one or more chargers/dischargers into a plurality of groups.

According to an embodiment of the present disclosure, the threshold value is automatically changed based on the charge/discharger evaluation data of one or more chargers/dischargers.

According to an embodiment of the present disclosure, the step of performing a predetermined action on at least one channel in which the abnormality is detected may include: In response to detecting the abnormality in the at least one channel, the at least one channel in which the abnormality is detected immediately shutting down the operation of the

According to an embodiment of the present disclosure, the step of performing a predetermined action on at least one channel in which the abnormality is detected may include: In response to detecting the abnormality in the at least one channel, the at least one channel in which the abnormality is detected and outputting an abnormal occurrence notification for the .

There is provided a computer program stored in a computer-readable recording medium to execute the above-described charging/discharging abnormality detection method according to an embodiment of the present disclosure in a computer.

According to some embodiments of the present disclosure, risks such as fire can be prevented in advance by collecting, storing, and analyzing data measured during manufacturing and evaluation of a lithium ion battery to detect an abnormality in a lithium ion battery and an abnormality in a charging/discharging device in advance.

According to some embodiments of the present disclosure, by monitoring whether an abnormality occurs in the charger/discharger in real time, appropriate measures may be quickly taken with respect to the charger/discharger in which the abnormality occurs. In addition, even when a hardware primary protection function is inoperable due to a failure of a charging/discharging device (eg, a temperature sensor, etc.), a secondary protection function may be performed by software.

According to some embodiments of the present disclosure, the processor may automatically collect the evaluation data in various formats by converting it into data in an analytic form (eg, text data). In addition, a file of a different format for each charger/discharger company may be converted into a file of one format. Accordingly, it is possible to simultaneously monitor whether an abnormality has occurred in a plurality of chargers and dischargers of different charger/discharger companies.

The effect of the present disclosure is not limited to the above-mentioned effects, and other effects not mentioned are those of ordinary skill in the art to which the present disclosure belongs from the description of the claims (hereinafter referred to as 'person of ordinary skill') can be clearly understood by

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Embodiments of the present disclosure will be described with reference to the accompanying drawings described below, wherein like reference numerals denote like elements, but are not limited thereto.
1 is a diagram illustrating an example of detecting an abnormality in a charger/discharger based on charger/discharger data for manufacturing or evaluating a lithium ion battery according to an embodiment of the present disclosure.
2 is a block diagram illustrating an internal configuration of an information processing system according to an embodiment of the present disclosure.
3 is a functional block diagram illustrating an internal configuration of a processor according to an embodiment of the present disclosure.
4 is a flowchart illustrating a method for detecting an abnormality in a charger/discharger according to an embodiment of the present disclosure.
5 is a diagram illustrating an example of collecting charging/discharging evaluation data according to an embodiment of the present disclosure.
6 is a diagram illustrating an example of a functional configuration for detecting an abnormality in at least one channel among a plurality of channels included in the charger/discharger according to an embodiment of the present disclosure in real time.
7 is a diagram illustrating an example of a functional configuration for detecting in real time a safety condition abnormality for at least one channel among a plurality of channels included in the charger/discharger according to an embodiment of the present disclosure.
8 is a diagram illustrating an example of a functional configuration for detecting in real time a Level II or higher of at least one channel among a plurality of channels included in the charger/discharger according to an embodiment of the present disclosure.
9 is a graph showing voltage values according to time measured during discharging of a lithium ion battery according to an embodiment of the present disclosure.

Hereinafter, specific contents for carrying out the present disclosure will be described in detail with reference to the accompanying drawings. However, in the following description, if there is a risk of unnecessarily obscuring the gist of the present disclosure, detailed descriptions of well-known functions or configurations will be omitted.

In the accompanying drawings, identical or corresponding components are assigned the same reference numerals. In addition, in the description of the embodiments below, overlapping description of the same or corresponding components may be omitted. However, even if description regarding components is omitted, it is not intended that such components are not included in any embodiment.

Advantages and features of the disclosed embodiments, and methods of achieving them, will become apparent with reference to the embodiments described below in conjunction with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below, but may be implemented in various different forms, and only the present embodiments allow the present disclosure to be complete, and the present disclosure provides those skilled in the art with the scope of the invention. It is provided for complete information only.

Terms used in this specification will be briefly described, and the disclosed embodiments will be described in detail. The terms used in the present specification have been selected as currently widely used general terms as possible while considering the functions in the present disclosure, but these may vary depending on the intention or precedent of a person skilled in the art, the emergence of new technology, and the like. In addition, in a specific case, there is a term arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the description of the corresponding invention. Therefore, the terms used in the present disclosure should be defined based on the meaning of the term and the contents of the present disclosure, rather than the simple name of the term.

Expressions in the singular herein include plural expressions unless the context clearly dictates the singular. Also, the plural expression includes the singular expression unless the context clearly dictates the plural. In the entire specification, when a part includes a certain component, this means that other components may be further included, rather than excluding other components, unless otherwise stated.

In addition, the term 'module' or 'unit' used in the specification means a software or hardware component, and 'module' or 'unit' performs certain roles. However, 'module' or 'unit' is not meant to be limited to software or hardware. A 'module' or 'unit' may be configured to reside on an addressable storage medium or may be configured to reproduce one or more processors. Thus, as an example, a 'module' or 'unit' refers to components such as software components, object-oriented software components, class components, and task components, and processes, functions, and properties. , procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, database, data structures, tables, arrays or at least one of variables . Components and 'modules' or 'units' are the functions provided within are combined into a smaller number of components and 'modules' or 'units' or additional components and 'modules' or 'units' can be further separated.

According to an embodiment of the present disclosure, a 'module' or a 'unit' may be implemented with a processor and a memory. 'Processor' should be construed broadly to include general purpose processors, central processing units (CPUs), microprocessors, digital signal processors (DSPs), controllers, microcontrollers, state machines, and the like. In some contexts, a 'processor' may refer to an application specific semiconductor (ASIC), a programmable logic device (PLD), a field programmable gate array (FPGA), or the like. 'Processor' refers to a combination of processing devices, such as, for example, a combination of a DSP and a microprocessor, a combination of a plurality of microprocessors, a combination of one or more microprocessors in combination with a DSP core, or any other such configurations. You may. Also, 'memory' should be construed broadly to include any electronic component capable of storing electronic information. 'Memory' means random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), programmable read-only memory (PROM), erase-programmable read-only memory (EPROM); may refer to various types of processor-readable media, such as electrically erasable PROM (EEPROM), flash memory, magnetic or optical data storage, registers, and the like. A memory is said to be in electronic communication with the processor if the processor is capable of reading information from and/or writing information to the memory. A memory integrated in the processor is in electronic communication with the processor.

In the present disclosure, a 'charger/discharger' may refer to a facility capable of repeatedly performing charging and/or discharging of a lithium ion battery in order to manufacture/evaluate it. For example, one charger/discharger may include a plurality of channels, and each channel may charge and discharge one battery. Accordingly, one charger/discharger may charge and/or discharge a plurality of batteries. In addition, the charger/discharger may have different specifications, safety conditions, etc. for each charger/discharger manufacturer and/or each evaluation target battery. In the present disclosure, a charging/discharging device may refer to a charging/discharging device, and the charging/discharging device may refer to a charging/discharging device.

In the present disclosure, 'evaluation data' may refer to data measured through a charger/discharger, data about a battery associated with a charger/discharger, data calculated for evaluation, data calculated to detect abnormality, and the like. Here, 'evaluation data' may refer to 'charger/discharger evaluation data', and 'charger/discharger evaluation data' may refer to 'evaluation data'.

1 is a diagram illustrating an example of detecting an abnormality in a charger/discharger based on charger/discharger data for manufacturing or evaluating a lithium ion battery according to an embodiment of the present disclosure. The information processing system (not shown, for example, at least one processor of the information processing system) collects, stores, and analyzes data during manufacturing and evaluation of lithium ion batteries to detect lithium ion battery abnormalities and charger/discharge equipment abnormalities in advance. Risks such as fire can be prevented in advance. In one embodiment, the processor collects charger/discharge data measured during manufacturing/evaluation of lithium ion batteries, detects anomaly of the charger/discharger in real time (Anomaly Detection), stores the charger/discharger data, and takes actions for the charger/discharger abnormality can be done According to an embodiment, the information processing system may include a real-time anomaly detection unit 120 , a storage unit 130 , and an action unit 140 .

To detect charger/discharger abnormality, the information processing system may collect charger/discharger evaluation data of one or more chargers/dischargers. In one embodiment, the information processing system may collect the charger evaluation data of one or more chargers/dischargers by receiving data from the Data PCs 110_1, 110_2, 110_3 associated with each charger/discharger company. Here, the one or more chargers/dischargers may include a plurality of channels. As shown, each charging/discharging company may have one or more charging/discharging equipment, and through the Data PC (eg, through the collection agent installed in the Data PC), the charger/discharger evaluation of the charger/discharger equipment it has data can be provided. For example, company P may have five chargers and dischargers (units B-1 to B-5), and through the Data PC (110_1) of company P, it is possible to provide charge/discharger evaluation data of five chargers and dischargers of company P. can In addition, Company H may have four chargers and dischargers (Units K-1 to Units K-4), and may provide charge/discharger evaluation data of the four chargers and dischargers through the Data PC 110_2 of Company H. Similarly, company T may have six chargers and dischargers (units P-1 to P-4), and may provide charge/discharger evaluation data of six chargers and dischargers through the company T's Data PC 110_3. That is, the information processing system can simultaneously collect the charging/discharging evaluation data of each charging/discharging company in real time. Each of the chargers and dischargers shown in FIG. 1 may include one or more channels.

The real-time anomaly detection unit 120 of the information processing system may detect an anomaly with respect to at least one channel among a plurality of channels included in one or more chargers/dischargers based on the collected charger/discharger evaluation data. In an embodiment, the real-time anomaly detection unit 120 determines whether at least one channel satisfies a safety condition (eg, within a reference value, above/below a threshold, etc.) based on the collected charger/discharger evaluation data. By doing so, it is possible to detect whether an abnormality has occurred in the corresponding channel. Additionally or alternatively, the real-time abnormality detection unit 120 determines whether or not the battery associated with at least one channel (ie, the manufacturing/evaluation target battery of the corresponding channel) is shorted based on the collected charger/discharger evaluation data. , it is possible to detect whether an abnormality has occurred in the corresponding channel. The information processing system may monitor whether an abnormality has occurred by building (floor), by charging/discharging unit unit, by charging/discharging unit unit unit channel, and by abnormal item.

The storage unit 130 of the information processing system may store the data associated with the charging/discharging equipment, the collected charging/discharging evaluation data, and/or the abnormal detection result data in the database DB. For example, the storage unit 130 stores basic information such as date, charger/discharger number, channel number, evaluation title, and/or safety condition information such as maximum/minimum voltage, maximum/minimum current, and maximum temperature in the database. can Alternatively or additionally, the storage unit 130 includes evaluation summary information and/or real-time abnormality detection information (eg, indicating whether abnormality has occurred) such as charging capacity, discharging capacity, charging time, discharging time, temperature, and raw data. Event values (0 or 1)) can be stored in the database.

The action unit 140 of the information processing system may perform a predetermined action on at least one channel in which an abnormality is detected. In one embodiment, the action unit 140 may immediately stop the operation of the at least one channel in which the abnormality is detected in response to detecting the abnormality with respect to the at least one channel. In another embodiment, in response to detecting an abnormality with respect to at least one channel, the action unit 140 may output an abnormality occurrence notification for at least one channel in which an abnormality is detected. For example, for at least one channel in which an abnormality is detected, the operation of the charging/discharging equipment of the corresponding channel is immediately stopped, and the corresponding channel's person in charge 150_1, the manager 150_2 and/or the STAFF 150_3 detects the detected abnormality. You can send an e-mail about abnormalities or send out a warning sound. Thereafter, the person in charge 150_1 , the manager 150_2 , and/or the STAFF 150_3 may perform an operation for the charging/discharging equipment abnormality.

In FIG. 1 , it is illustrated that charge/discharger evaluation data is provided through one Data PC in association with one Data PC for each charger/discharger company, but is not limited thereto. For example, one charger/discharger company may be associated with a different number of Data PCs, and may provide charge/discharger evaluation data through the associated Data PCs.

2 is a block diagram illustrating an internal configuration of the information processing system 200 according to an embodiment of the present disclosure. The information processing system 200 may include a memory 210 , a processor 220 , a communication module 230 , and an input/output interface 240 . As shown in FIG. 2 , the information processing system 200 may be configured to communicate information and/or data through a network using the communication module 230 . For example, the real-time abnormality detection unit 120 and the action unit 140 of FIG. 1 may be operated by the processor 220 of the information processing system 200 .

The memory 210 may include any non-transitory computer-readable recording medium. According to one embodiment, the memory 210 is a non-volatile mass storage device such as random access memory (RAM), read only memory (ROM), disk drive, solid state drive (SSD), flash memory, etc. mass storage device). As another example, a non-volatile mass storage device such as a ROM, an SSD, a flash memory, a disk drive, etc. may be included in the information processing system 200 as a separate permanent storage device that is distinct from the memory. In addition, the memory 210 includes an operating system and at least one program code (eg, a code for collecting charger/discharging evaluation data installed and driven in the information processing system 200 , detecting abnormality in a channel, performing an action, etc.) can be saved.

These software components may be loaded from a computer-readable recording medium separate from the memory 210 . Such a separate computer-readable recording medium may include a recording medium directly connectable to the information processing system 200, for example, a floppy drive, a disk, a tape, a DVD/CD-ROM drive, a memory card, etc. may include a computer-readable recording medium of As another example, the software components may be loaded into the memory 210 through the communication module 230 rather than a computer-readable recording medium. For example, the at least one program is a computer program (eg, charger/discharger evaluation data collection) that is installed by the files provided through the communication module 230 by the file distribution system that distributes the installation files of developers or applications. , a program for detecting an abnormality with respect to a channel, performing an action, etc.) may be loaded into the memory 210 .

The processor 220 may be configured to process instructions of a computer program by performing basic arithmetic, logic, and input/output operations. The command may be provided to a user terminal (not shown) or another external system by the memory 210 or the communication module 230 . For example, the processor 220 may be configured to execute a received instruction according to program code stored in a recording device such as the memory 210 .

The communication module 230 may provide a configuration or function for a user terminal (not shown) (eg, a user terminal of a person in charge) and the information processing system 200 to communicate with each other through a network, and the information processing system ( 200) may provide a configuration or function for communicating with an external system (eg, a charger/discharger system, a separate cloud system, etc.). In one embodiment, a control signal, command, data, etc. provided under the control of the processor 220 of the information processing system 200 pass through the communication module 230 and the network to communicate with the user terminal and/or the communication module of the external system. may be transmitted to a user terminal and/or an external system through For example, the information processing system 200 may transmit an abnormal occurrence notification, a channel operation stop command, etc. to the user terminal and/or an external system through the communication module 230 and the network. In another embodiment, the processor 220 of the information processing system 200 may receive a control signal, command, data, etc. from a user terminal and/or an external system through the communication module 230 and a network. For example, the processor 220 of the information processing system 200 may receive the charger/discharger evaluation data from the user terminal and/or an external system through the communication module 230 and the network.

In addition, the input/output interface 240 of the information processing system 200 is connected to the information processing system 200 or means for interfacing with a device (not shown) for input or output that the information processing system 200 may include. can be Although the input/output interface 240 is illustrated as an element configured separately from the processor 220 in FIG. 2 , the present invention is not limited thereto, and the input/output interface 240 may be configured to be included in the processor 220 . The information processing system 200 may include more components than those of FIG. 2 . However, there is no need to clearly show most of the prior art components.

The processor 220 of the information processing system 200 may be configured to manage, process and/or store information and/or data received from a plurality of user terminals and/or a plurality of external systems. For example, the processor 220 collects charging/discharging evaluation data of one or more chargers/dischargers, and based on the collected charging/discharging evaluation data, abnormality for at least one channel among a plurality of channels included in one or more chargers/dischargers (anomaly) can be detected. Also, the processor 220 may perform a predetermined action on at least one channel in which an abnormality is detected.

3 is a functional block diagram illustrating an internal configuration of a processor 220 according to an embodiment of the present disclosure. As shown, the processor 220 may include a data collection unit 310 , a real-time abnormality detection unit 320 , an abnormality action unit 330 , and the like. In this case, the processor 220 may communicate with the database 340 and the like to exchange data and/or information for detecting an abnormality in the charger/discharger. For example, the processor 220 communicates with the database 340 and the like in real time or periodically, or when new data is generated, communicates with the database 340 and the like, and transmits data and/or information for detecting an abnormality of the charger/discharger. can be exchanged

The data collection unit 310 may collect charge/discharger evaluation data of one or more chargers/dischargers. In one embodiment, when the charger/discharger evaluation data is received from a plurality of chargers and dischargers, the data collection unit 310 converts the evaluation data of one or more formats generated from the plurality of chargers/dischargers into data in an analytic form, and converts Data in a form that can be analyzed can be collected as charge/discharger evaluation data. In another embodiment, the data collection unit 310 may collect data associated with one or more chargers and dischargers. For example, basic information and/or information on safety conditions of one or more chargers and dischargers may be collected.

The real-time anomaly detection unit 320 may detect an anomaly with respect to at least one channel among a plurality of channels included in the one or more chargers/dischargers based on the collected charger/discharger evaluation data. In one embodiment, the real-time anomaly detection unit 320, based on the charger/discharger evaluation data, whether the evaluation data associated with at least one channel among a plurality of channels included in one or more chargers/dischargers satisfies a predetermined safety condition judgment results can be generated. Then, the real-time anomaly detection unit 320 may determine an anomaly for at least one channel in real time, based on the generated determination result.

In another embodiment, the real-time abnormality detection unit 320, based on the collected charger/discharger evaluation data, an internal short of a lithium ion battery associated with at least one channel among a plurality of channels included in one or more chargers/dischargers It is possible to generate a judgment result as to whether or not For example, the real-time anomaly detection unit 320 generates a sub-voltage model by using the sub-evaluation data received from at least one channel, and generates a sub-voltage model between the generated sub-voltage model and the standard voltage model associated with one or more chargers and dischargers. The difference may be calculated, and based on the calculated difference and the threshold, it may be determined whether the lithium ion battery associated with the at least one channel has an internal short circuit. Here, the standard voltage model may be generated by clustering voltage models of each of a plurality of channels including one or more chargers/dischargers into a plurality of groups. In addition, the threshold value may be automatically changed based on the charging/discharging evaluation data of one or more chargers/dischargers. Thereafter, the real-time anomaly detection unit 320 may determine an anomaly for at least one channel in real time, based on the generated determination result.

The abnormality action unit 330 may perform a predetermined action on at least one channel in which an abnormality is detected. In an embodiment, in response to detecting the abnormality of the at least one channel, the abnormality action unit 330 may immediately stop the operation of the at least one channel in which the abnormality is detected. In another embodiment, in response to detecting an abnormality with respect to at least one channel, the abnormality action unit 330 may output an abnormality occurrence notification for at least one channel in which the abnormality is detected.

Although the configuration of the processor 220 has been described separately for each function in FIG. 3 , it does not necessarily mean that the processor 220 is physically separated. For example, although the data collection unit 310 and the real-time anomaly detection unit 320 have been separately described above, this is provided to help the understanding of the present invention, and the present invention is not limited thereto. In addition, in FIG. 3 , the processor 220 is configured to include all of the data collection unit 310 , the real-time abnormality detection unit 320 , and the abnormality action unit 330 , but is not limited thereto. For example, the data collection unit 310 may not be included in the processor 220 but may be included in the processor of the Data PC of each charger/discharger company to perform a function.

4 is a flowchart illustrating a method 400 for detecting an abnormality in a charger/discharger according to an embodiment of the present disclosure. According to an embodiment, the charging/discharging abnormality detecting method 400 may be performed by a processor (eg, at least one processor of an information processing system). As shown, the charging/discharging abnormality detection method 400 may be initiated by the processor collecting charging/discharging evaluation data of one or more chargers/dischargers (S410). For example, the processor may convert the evaluation data in one or more formats generated from the plurality of chargers/dischargers into data in an analytic form, and collect the converted data in an analytic form as the charger evaluation data.

The processor may detect an anomaly with respect to at least one channel among a plurality of channels included in the one or more chargers/dischargers based on the collected charger/discharger evaluation data (S420). In an embodiment, the processor may generate a determination result as to whether evaluation data associated with at least one channel among a plurality of channels included in the one or more chargers/dischargers satisfies a predetermined safety condition, based on the charger/discharger evaluation data. can Then, based on the generated determination result, the processor may determine an anomaly for at least one channel in real time.

In another embodiment, the processor generates a determination result as to whether an internal short circuit of a lithium ion battery associated with at least one channel among a plurality of channels included in one or more chargers/dischargers is based on the collected charger/discharger evaluation data can do. For example, the processor generates a sub-voltage model using the sub-evaluation data received from at least one channel, calculates a difference between the generated sub-voltage model and a standard voltage model associated with one or more chargers/dischargers, and the calculated Based on the difference and the threshold, it may be determined whether the lithium ion battery associated with the at least one channel has an internal short. Here, the standard voltage model may be generated by clustering voltage models of each of a plurality of channels included in one or more chargers/dischargers into a plurality of groups. In addition, the threshold value may be automatically changed based on the charging/discharging evaluation data of one or more chargers/dischargers. Then, based on the generated determination result, the processor may determine an anomaly for at least one channel in real time.

The processor may perform a predetermined action on at least one channel in which an abnormality is detected (S430). In an embodiment, in response to detecting an anomaly with respect to the at least one channel, the processor may immediately stop operation of the at least one channel for which the anomaly is detected. In another embodiment, the processor may output an abnormality occurrence notification for at least one channel in which an abnormality is detected.

The processor may monitor in real time whether an abnormality occurs in the charger/discharger by repeating the above-described series of operations. Also, a process in which such a series of operations are performed once may be referred to as one evaluation cycle.

5 is a diagram illustrating an example of collecting charging/discharging evaluation data according to an embodiment of the present disclosure. In order to detect a charger/discharger abnormality, the processor (eg, at least one processor of the information processing system) may collect charger/discharger evaluation data measured in a lithium ion battery manufacturing/evaluation process through the charger/discharger. In an embodiment, the processor may collect charge/discharger evaluation data of one or more chargers/dischargers from the DATA PC of each charger/discharger company in real time or at predetermined intervals. For example, an automatic collector (Agent) (e.g., a code for data collection/transmission, program, system, etc.) is installed, and the processor can automatically collect the charger/discharger evaluation data in real time by receiving the charger/discharger evaluation data from the Data PC through the automatic collector. Alternatively, the automatic collector may be installed in a separate device so that the data PC can be accessed through wired/wireless communication. Here, the charger/discharger evaluation data received from the Data PC may be configured in a different format for each manufacturer, for each model of the charger and/or discharger, and/or for each model of the lithium ion battery to be manufactured/evaluated.

The processor can automatically collect the evaluation data in various formats generated from a number of charger/discharger companies and various types of chargers/dischargers into data in a form that can be analyzed. In an embodiment, the processor may convert the evaluation data of one or more formats generated from the plurality of chargers/dischargers into data in an analytic form, and collect the converted data as the charger/discharger evaluation data. For example, the processor may convert the charger/discharger evaluation data in the form of binary data received from the Data PC into text data in a form that can be analyzed through reverse engineering, and collect the data converted into text data as the charger/discharger evaluation data. .

As shown, the automatic collector (AGENT) 510 may collect the charging/discharging evaluation data from the Data PC and provide it to the BinaryParser 520 . The BinaryParser 520 may decode the charger/discharger evaluation data generated/stored in the form of a unique file of each charger/discharger company. That is, the BinaryParser 520 may convert the charger/discharger evaluation data in the form of a file unique to the charger/discharger company into data in a form that can be analyzed. Thereafter, the converted charger/discharger evaluation data may be provided to the Core 530 . The Core 530 detects an abnormality of the charger/discharger (eg, an abnormality with respect to at least one channel among a plurality of channels included in the charger/discharger) using the received converted charger/discharger evaluation data, and the abnormal detection result can be printed out. Charger/discharger evaluation data and/or abnormality detection results may be updated in a database.

Agent 510, BinaryParser 520, and/or Core 530 shown in FIG. 5 collects charger/discharger evaluation data, and code components and programs (eg, information processing system) for detecting charger/discharger abnormality. It may correspond to a component of a program running on a PC and/or a program running on a Data PC, etc.) and/or some functional component of a processor.

6 is a diagram illustrating an example of a functional configuration for detecting an abnormality in at least one channel among a plurality of channels included in the charger/discharger according to an embodiment of the present disclosure in real time. The processor (eg, at least one processor of the information processing system) may detect an abnormality with respect to at least one channel among a plurality of channels included in the one or more chargers/dischargers based on the collected charger/discharger evaluation data. In one embodiment, the real-time abnormality detection unit 320 of the processor detects an abnormality in at least one channel among a plurality of channels included in one or more chargers/dischargers based on the charger/discharger evaluation data input through the input unit 610 . can detect For example, when it is determined that an abnormality has occurred in at least one channel, the real-time abnormality detection unit 320 outputs 1 as an Event value indicating whether abnormality has occurred in the corresponding channel, and it is determined that abnormality does not occur. In this case, by outputting 0 as the event value, it is possible to output in real time whether an abnormality has occurred for the corresponding channel.

The safety condition abnormality detection unit 620 of the real-time abnormality detection unit 320 may determine whether evaluation data associated with at least one channel among a plurality of channels satisfies a predetermined safety condition. The safety condition abnormality detection unit 620 detects abnormality of the safety condition for at least one channel among a plurality of channels by using the automatically collected information on the safety condition (eg, safety condition setting item) and the charger/discharger evaluation data. can detect For example, the safety condition abnormal detection unit 620 may include data such as Time(t), Current(I), Voltage(V), Temperature(T) of the charger/discharger input through the input unit 610 (for example, , using the evaluation data collected from each of a plurality of channels included in the charger/discharger) to detect in real time a channel that is out of the safety condition of the charger/discharger (eg, voltage/current/temperature upper/lower limits, amount of change, etc.) can do.

In addition, the Level II detection unit 630 of the real-time abnormality detection unit 320 may determine whether an internal short circuit occurs in the lithium ion battery associated with one channel. For example, the Level II sensing unit 630 may detect in real time whether a short circuit occurs inside the lithium ion battery due to repeated charge/discharge evaluation. The internal short circuit of the battery can be divided into three stages: Level I, Level II, and Level III. In Level I, the voltage gradually drops due to slow self-discharge and there is no noticeable heat generation, and it is possible to respond with electrical measures. Level III may represent a stage where large-scale heat is released by a chemical reaction, and it is too late to take any action. The Level II sensing unit 630 may detect a Level II internal short of the lithium ion battery.

In FIG. 6 , the input unit 610 is illustrated as an external component of the real-time anomaly detection unit 320 , but the present invention is not limited thereto, and the input unit 610 may be included in some components of the processor of the information processing system. For example, the input unit 610 may be included in the data collection unit 310 and/or the real-time abnormality detection unit 320 .

7 is a diagram illustrating an example of a functional configuration for detecting in real time a safety condition abnormality for at least one channel among a plurality of channels included in the charger/discharger according to an embodiment of the present disclosure. A hardware configuration (eg, a temperature sensor, etc.) that detects an abnormality according to a safety condition and performs a primary protection function may be included in the charging/discharging device itself. According to an embodiment of the present disclosure, even when the primary protection function is inoperable due to a failure of the charging/discharging equipment, the secondary protection function in software may be performed. In an embodiment, the processor (eg, at least one processor of the information processing system) may include, based on the charger/discharger evaluation data, evaluation data associated with at least one channel among a plurality of channels included in the one or more chargers/dischargers in advance. A determination result as to whether the determined safety condition is satisfied may be generated. Then, based on the generated determination result, the processor may determine an anomaly for at least one channel in real time.

Safety conditions A safety condition as a standard for detecting an abnormality in the abnormality detection unit 620 may be set in advance in the charging/discharging equipment during manufacturing/evaluation of the lithium ion battery. The items of these safety conditions are, when the charger/discharger evaluation data (or a value calculated based on the charger/discharger evaluation data) reaches a set value (eg, a threshold value), immediately stop the charging/discharging equipment or make an alarm, etc. It corresponds to the items to protect the facility by sending For example, safety condition items include voltage (high/low limit voltage, voltage change amount, CC (constant current) section voltage change during charging step), current (upper/low limit current, current change amount), capacity (upper/lower limit) capacity, capacity change amount), temperature (upper/lower limit temperature, temperature change amount), etc. may be included.

By the input unit 610, data such as Time(t), Current(I), Voltage(V), Temperature(T) associated with at least one channel among a plurality of channels included in the charger/discharger is detected by the safety condition abnormality detection unit It may be input as 620 . The calculation unit 710 of the safety condition abnormality detection unit 620 is based on the input data, the voltage change amount (ΔV) of the corresponding channel, the current change amount (ΔI), the charge CC voltage change amount (ΔVcc), the temperature change amount (ΔT) , max/min voltage (Vmax, Vmin), max/min current (Imax, Imin), max/min capacity (Cmax, Cmin), and/or max/min temperature (Tmax, Tmin).

Thereafter, the determination unit 720 of the safety condition abnormality detection unit 620 determines whether the evaluation data associated with the corresponding channel satisfies the predetermined safety condition based on the calculated data and/or the input data. can create For example, when the calculated values of ΔV, ΔI, ΔVcc, and/or ΔT are greater than or equal to the safety condition value of the charging/discharging equipment, the determination unit 720 may determine that the evaluation data associated with the channel does not satisfy the safety condition. can be judged as As another example, when the calculated values of Vmin, Imin, Cmin, and/or Tmin are less than or equal to the safety condition value of the charging/discharging equipment, the determination unit 720 may determine that the evaluation data associated with the channel does not satisfy the safety condition. can be judged as As another example, when the calculated Vmax, Imax, Cmax and/or Tmax is greater than or equal to the safety condition value of the charging/discharging facility, the determination unit 720 determines that the evaluation data associated with the channel does not satisfy the safety condition. can be judged.

Based on the determination result, the determination unit 720 may determine an abnormality with respect to the corresponding channel in real time. For example, according to the determination result, the determination unit 720 outputs 1 as an Event value indicating whether an abnormality has occurred for a channel in which an abnormality has occurred, and outputs 0 as an Event value for a channel in which an abnormality does not occur, Whether an abnormality has occurred for each channel can be output in real time.

8 is a diagram illustrating an example of a functional configuration for detecting in real time a Level II or higher for at least one channel among a plurality of channels included in the charger/discharger according to an embodiment of the present disclosure. In general, when an internal short of a lithium-ion battery occurs due to a physical accident such as mechanical shock or vibration, it leads to an electrical problem, accompanies heat, and goes through a pattern that leads to thermal runaway. , may lead to an explosion. Sudden hard shorts in lithium-ion battery manufacturing can be detected through standard tests before shipment. induced, so it is difficult to detect. These naturally occurring internal shorts can be caused by contamination or defects in manufacturing.

In an embodiment, the processor generates a determination result as to whether an internal short circuit of a lithium ion battery associated with at least one channel among a plurality of channels included in the one or more chargers/dischargers based on the collected charger/discharger evaluation data can do. For example, the processor generates a sub-voltage model using the sub-evaluation data received from at least one channel, calculates a difference between the generated sub-voltage model and a standard voltage model associated with one or more chargers/dischargers, and the calculated Based on the difference and the threshold, it may be determined whether the lithium ion battery associated with the at least one channel has an internal short. Here, the standard voltage model may be generated by clustering voltage models of each of a plurality of channels included in one or more chargers/dischargers into a plurality of groups. In addition, the threshold value may be automatically changed based on the charging/discharging evaluation data of one or more chargers/dischargers. Then, based on the generated determination result, the processor may determine an anomaly for at least one channel in real time.

The Level II detection unit 630 generates a voltage model (eg, a sub-voltage model) of the corresponding channel based on the evaluation data of the anomaly detection target channel, and compares the generated voltage model and the standard voltage model with the abnormal event (Event). ) can be detected. For example, by the input unit 610, data such as Time(t), Current(I), Voltage(V), Temperature(T), Capacity(C) associated with a plurality of channels included in one or more chargers/dischargers may be input to the Level II sensing unit 630 . Thereafter, the modeling unit 810 of the Level II sensing unit 630 may perform parameter modeling for generating a sub-voltage model for at least one channel among a plurality of channels. For example, the modeling unit 810 uses the sub-evaluation data collected from at least one channel among the input data to calculate a voltage value (t-V) according to time and a voltage change amount (Vt2-Vt1) according to a unit time. A sub-voltage model for the corresponding channel can be generated based on it. In addition. The modeling unit 810 uses the sub-evaluation data collected from at least one channel to model the current for the corresponding channel based on the current value (t-I) over time and the amount of change in current over time (It2-It1) over time (It2-It1) can create

The modeling unit 810 may perform standard voltage modeling for generating a standard voltage model that is a model for all channels in order to detect Level II or higher. That is, the standard voltage model may be generated based on input evaluation data of all channels of the entire charging/discharging equipment. Here, the evaluation data of all channels of the entire charging/discharging facility may include the charging/discharging evaluation data collected in the current evaluation cycle, the charging/discharging evaluation data collected in the previous evaluation cycle, and the charging/discharging evaluation data stored in the database. can

In an embodiment, the modeling unit 810 generates a voltage model of each of a plurality of channels based on the charger evaluation data collected from each of a plurality of channels included in one or more chargers and dischargers, and the voltage of each of the plurality of channels. By clustering the model into a plurality of groups, a standard voltage model can be generated. For example, the standard voltage model includes a design and manufacturing method of a target battery in which the charging/discharging equipment evaluates the voltage model of each of the plurality of channels, a manufacturing/evaluation target battery model, the degree of deterioration of the target battery, the size of the target battery, It may be generated by clustering into a plurality of groups according to the size of the charge/discharge voltage/current/capacity, charge/discharge time, temperature, and the like. The modeling unit 810 may determine a center value of each of the plurality of clustered groups as a standard voltage model for each of the plurality of groups.

Thereafter, the determination unit 820 may detect Level II or higher based on the standard voltage model and the sub-voltage model. For example, when the difference between the sub-voltage model and the standard voltage model is greater than or equal to the threshold, the determination unit 820 may determine that there is Level II or higher in the channel associated with the corresponding sub-voltage model. Here, the threshold value serving as a criterion of Level II or higher may be automatically changed based on the charging/discharging device evaluation data of one or more chargers/dischargers. That is, the threshold is adaptively learned by the input charger/discharger evaluation data, and may be automatically updated as the data is accumulated. For example, the threshold value may be determined based on the charger/discharger evaluation data (or a value calculated based on the charger/discharger evaluation data) of previous evaluation cycles (eg, the previous 3 cycles) determined to have no abnormality. have. As another example, the threshold may be determined as an average of differences between the sub-voltage model and the standard voltage model in previous evaluation cycles (eg, the previous 3 cycles) in which it is determined that there is no abnormality.

9 is a graph showing voltage values according to time measured during discharging of a lithium ion battery according to an embodiment of the present disclosure; In one embodiment, the processor (eg, at least one processor of the information processing system) generates an abnormality (eg, Level II or higher) with respect to a specific channel when the amount of voltage change in each evaluation cycle rapidly increases for a specific channel. can be judged as The processor may quantify the voltage drop of the anomaly detection target channel by using the voltage difference between the standard voltage model and the sub voltage model. The processor may determine that an abnormality has occurred when a voltage difference between the standard voltage model and the sub voltage model is greater than a threshold value.

In the graph shown, a long dashed line - a dotted line may represent a standard voltage model, and a broken line may represent a sub-voltage model of an anomaly detection target channel. According to the graph shown, the dashed line (ie, the sub-voltage model) is discharged faster than the long dashed-dotted line (ie, the standard voltage model). When the voltage difference (or the difference in voltage change amount) between the standard voltage model and the sub voltage model is within a threshold value, it may be determined as a general voltage drop of the battery associated with the corresponding channel. On the other hand, when the voltage difference between the standard voltage model and the sub voltage model is equal to or greater than a threshold, it may be determined that an abnormality such as an internal short circuit of a battery associated with the corresponding channel has occurred.

Thereafter, in response to detecting the abnormality in the at least one channel, the processor immediately stops the operation of the at least one channel in which the abnormality is detected or outputs an abnormality occurrence notification for the at least one channel in which the abnormality is detected. can That is, by notifying the person in charge of the channel in which the abnormality is detected that the abnormality has occurred in the corresponding channel, it is possible to induce the person in charge to supplement and repair the problem in the corresponding channel in advance before a fatal problem such as a fire occurs.

A computer program stored in a computer-readable recording medium may be provided to execute the above-described method in a computer. The medium may continuously store a computer executable program, or may be a temporary storage for execution or download. In addition, the medium may be various recording means or storage means in the form of a single or several hardware combined, it is not limited to a medium directly connected to any computer system, and may exist distributed on a network. Examples of the medium include a hard disk, a magnetic medium such as a floppy disk and a magnetic tape, an optical recording medium such as CD-ROM and DVD, a magneto-optical medium such as a floppy disk, and those configured to store program instructions, including ROM, RAM, flash memory, and the like. In addition, examples of other media may include recording media or storage media managed by an app store that distributes applications, sites that supply or distribute various other software, or servers.

The method, operation, or techniques of this disclosure may be implemented by various means. For example, these techniques may be implemented in hardware, firmware, software, or a combination thereof. Those of ordinary skill in the art will appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design requirements imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementations should not be interpreted as causing a departure from the scope of the present disclosure.

In a hardware implementation, the processing units used to perform the techniques include one or more ASICs, DSPs, digital signal processing devices (DSPDs), programmable logic devices (PLDs). ), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, electronic devices, other electronic units designed to perform the functions described in this disclosure. , a computer, or a combination thereof.

Accordingly, the various illustrative logic blocks, modules, and circuits described in connection with this disclosure are suitable for use in general purpose processors, DSPs, ASICs, FPGAs or other programmable logic devices, discrete gate or transistor logic, discrete hardware components, or the present disclosure. It may be implemented or performed in any combination of those designed to perform the functions described in A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, eg, a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other configuration.

In firmware and/or software implementations, the techniques include random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), PROM ( on computer-readable media such as programmable read-only memory), erasable programmable read-only memory (EPROM), electrically erasable PROM (EEPROM), flash memory, compact disc (CD), magnetic or optical data storage devices, etc. It may be implemented as stored instructions. The instructions may be executable by one or more processors, and may cause the processor(s) to perform certain aspects of the functionality described in this disclosure.

Although the embodiments described above have been described utilizing aspects of the presently disclosed subject matter in one or more standalone computer systems, the present disclosure is not limited thereto and may be implemented in connection with any computing environment, such as a network or distributed computing environment. . Still further, aspects of the subject matter in this disclosure may be implemented in a plurality of processing chips or devices, and storage may be similarly affected across the plurality of devices. Such devices may include PCs, network servers, and portable devices.

Although the present disclosure has been described in connection with some embodiments herein, various modifications and changes can be made without departing from the scope of the present disclosure that can be understood by those skilled in the art to which the present disclosure pertains. Further, such modifications and variations are intended to fall within the scope of the claims appended hereto.

110_1, 110_2, 110_3: Data PC
120: real-time anomaly detection unit
130: storage
140: abnormal action unit

Claims (10)

A method of detecting an abnormality in a charger/discharger based on charger/discharger data for manufacturing or evaluating a lithium ion battery, which is executed by at least one processor,
collecting charge/discharger evaluation data of one or more chargers/dischargers;
detecting an anomaly with respect to at least one channel among a plurality of channels included in the one or more chargers/dischargers based on the collected charger/discharger evaluation data; and
performing a predetermined action on at least one channel in which the anomaly is detected
A method for detecting abnormalities in the charger/discharger comprising a.
According to claim 1,
The at least one charger/discharger includes a plurality of chargers/dischargers,
The collecting step is
converting the evaluation data in one or more formats generated from the plurality of chargers and dischargers into data in an analytic form; and
Collecting the converted data in the form of analysis possible as the charging/discharging evaluation data
A method for detecting abnormalities in the charger/discharger comprising a.
According to claim 1,
The sensing step is
generating a determination result as to whether evaluation data associated with at least one channel among a plurality of channels included in the one or more chargers and dischargers satisfies a predetermined safety condition, based on the evaluation data of the charger and discharger; and
Determining an anomaly for the at least one channel in real time based on the generated determination result
A method for detecting abnormalities in the charger/discharger comprising a.
According to claim 1,
The sensing step is
generating a determination result as to whether or not an internal short circuit of a lithium ion battery associated with at least one channel among a plurality of channels included in the one or more chargers/dischargers based on the collected charger/discharger evaluation data; and
Detecting an abnormality with respect to the at least one channel based on the generated determination result
A method for detecting abnormalities in the charger/discharger comprising a.
5. The method of claim 4,
Generating a determination result as to whether the internal short (short) of the lithium ion battery associated with at least one channel of the plurality of channels,
generating a sub-voltage model using the sub-evaluation data collected from the at least one channel;
calculating a difference between the generated sub voltage model and a standard voltage model associated with the one or more chargers and dischargers; and
Based on the calculated difference and the threshold, determining whether an internal short circuit of the lithium ion battery associated with the at least one channel
A method for detecting abnormalities in the charger/discharger comprising a.
6. The method of claim 5,
The standard voltage model is
A charging/discharging abnormality detection method that is generated by clustering voltage models of each of a plurality of channels included in the one or more chargers/dischargers into a plurality of groups.
6. The method of claim 5,
The threshold is
Automatically changed based on the charging/discharging evaluation data of the one or more chargers/dischargers, a charging/discharging abnormality detection method.
According to claim 1,
The step of performing a predetermined action on at least one channel in which the abnormality is detected,
In response to detecting an anomaly with respect to the at least one channel, the method comprising the step of immediately stopping operation of the at least one channel for which the anomaly is detected.
According to claim 1,
The step of performing a predetermined action on at least one channel in which the abnormality is detected,
In response to detecting an abnormality with respect to the at least one channel, outputting an abnormality occurrence notification for the at least one channel in which the abnormality is detected, a charging/discharging abnormality detection method.
A computer program stored in a computer-readable recording medium to execute the method for detecting an abnormality in a charger/discharger according to any one of claims 1 to 9 in a computer.

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