Data collection device and method of operation thereof

Abstract

A data collection device according to embodiments disclosed in the present document can include a memory for storing a plurality of coloration data, and a processor that determines a data set including the plurality of coloration data, and compresses and manages the data set.

Description

Technical Field

[0001] Cross-references to related applications

[0002] This application claims priority and benefit to Korean Patent Application No. 10-2023-0149701, filed on November 2, 2023, with the Korean Intellectual Property Office, the entire contents of which are incorporated herein by reference. Technical Field

[0003] The embodiments disclosed herein relate to data collection devices and methods of operation thereof. Background Technology

[0004] Recently, research and development on rechargeable batteries have been actively pursued. Rechargeable batteries are batteries capable of being charged and discharged, and include all recent lithium-ion batteries in addition to conventional Ni / Cd and Ni / MH batteries. Lithium-ion batteries have the advantage of significantly higher energy density than conventional Ni / Cd and Ni / MH batteries. Furthermore, because lithium-ion batteries can be manufactured in small and lightweight forms, they are used as power sources for mobile devices, and recently, due to their expanding applications in electric vehicles, lithium-ion batteries have attracted attention as a next-generation energy storage medium.

[0005] A standalone data collection device can be used to analyze the state of a battery. This device can be connected to the battery or a battery pack that includes it to collect data about the battery's state and send the collected data to a server, enabling analysis of the battery's condition.

[0006] Additionally, data collection devices for vehicles can be connected to the vehicle network (Controller Area Network (CAN)) to collect data from various controllers and send the data to a server. The vehicle network (CAN) is a bus method for communication between microcontrollers and performs data communication with the vehicle's electronic control unit (ECU), transmission control unit (TCU), anti-lock braking system (ABS) microcontroller, etc.

[0007] Due to the recent proliferation of vehicle data collection devices, the amount of data collected by these devices is likely to increase rapidly. Consequently, the communication costs and server storage costs for transmitting this data to servers may also increase. Therefore, it is necessary to manage the collected data to reduce communication and server storage costs. Summary of the Invention

[0008] Technical issues

[0009] The embodiments disclosed herein relate to providing a data collection device and a method of operating the same, wherein a method for managing data is provided to effectively utilize the storage space of the data collection device.

[0010] The embodiments disclosed herein also relate to providing a data collection device and a method of operating the same, wherein a method for managing data is provided to effectively perform communication between the data collection device and a server.

[0011] The technical objectives of the embodiments disclosed herein are not limited to the above-described technical objectives, and other objectives not described will be clearly understood by those skilled in the art from the following description.

[0012] Technical solution

[0013] A data collection device according to an embodiment disclosed herein may include: a memory configured to store a plurality of colorized data; and a processor configured to determine a dataset including the plurality of colorized data and to manage the dataset by compressing the dataset.

[0014] According to an implementation, the plurality of colored data may be data collected in the data collection device that has not yet been sent to the server.

[0015] According to an implementation, the processor can sort the plurality of coloring data in the chronological order in which they were generated, and determine the dataset based on the sorted plurality of coloring data.

[0016] According to an implementation, the processor can compress the plurality of colored data included in the dataset in a streaming manner.

[0017] According to an embodiment, the data collection device may further include a communication module, the communication module including a storage unit configured to store the compressed dataset.

[0018] According to an implementation, the processor may determine the dataset based on at least one of the size of the plurality of colored data, the capacity of the storage unit, and the compression ratio of the compression.

[0019] According to an implementation, the processor can determine the number of the plurality of coloring data included in the dataset such that the size of the dataset after compressing the plurality of coloring data included in the dataset at the compression ratio is less than the capacity of the storage unit.

[0020] According to an implementation, the communication module can be configured to send a communication request to a server, and when a response to the communication request is received from the server, to send the dataset stored in the storage unit to the server.

[0021] A method for collecting data according to an embodiment disclosed herein may include the steps of: determining a dataset comprising multiple colored data, and managing the dataset by compressing the dataset.

[0022] According to an implementation, the plurality of colored data may be data collected in the data collection device that has not yet been sent to the server.

[0023] According to an implementation method, the step of determining the dataset includes the following steps: sorting the plurality of colored data in the time order in which they were generated, and determining the dataset based on the sorted plurality of colored data.

[0024] According to an implementation, the step of managing the dataset by compressing the dataset may include the following steps: compressing the plurality of colored data included in the dataset in a streaming manner.

[0025] According to an embodiment, the method may further include storing the compressed dataset in the storage section of the communication module.

[0026] According to an implementation, the step of determining the dataset may include the following steps: determining the dataset based on at least one of the size of the plurality of colored data, the capacity of the storage unit, and the compression ratio of the compression.

[0027] According to an embodiment, the method may further include the following steps: determining the number of the plurality of coloring data included in the dataset, such that the size of the dataset after compressing the plurality of coloring data included in the dataset at the compression ratio is less than the capacity of the storage unit.

[0028] According to an embodiment, the method may further include the following steps: sending a communication request to a server, and when a response to the communication request is received from the server, sending the dataset stored in the storage unit to the server.

[0029] Beneficial effects

[0030] According to the data collection device and its operating method disclosed herein, the data can be used to effectively utilize the storage space of the data collection device.

[0031] According to the data collection device and its operation method disclosed herein, data can be managed to effectively perform communication between the data collection device and the server.

[0032] In addition, various effects that can be directly or indirectly identified through this document can be provided. Attached Figure Description

[0033] Figure 1 This is a block diagram illustrating a data collection system according to one embodiment disclosed herein.

[0034] Figure 2 This is a block diagram illustrating a data collection device according to one embodiment disclosed herein.

[0035] Figure 3 This is a flowchart of the operation of a data collection device according to one embodiment disclosed herein.

[0036] Figure 4 This is a flowchart of the operation of a data collection device according to one embodiment disclosed herein.

[0037] Figure 5 This is a block diagram illustrating the hardware configuration of a computing system for performing a method of operating a data collection device according to one embodiment disclosed herein. Detailed Implementation

[0038] In the following description, various embodiments of the present disclosure will be illustrated with reference to the accompanying drawings. However, it should be understood that this is not intended to limit the present disclosure to a particular embodiment, and includes various modifications, equivalents, and / or substitutions to the embodiments of the present disclosure.

[0039] It should be understood that the various embodiments and terminology used herein are not intended to limit the technical features described herein to specific embodiments, and include various modifications, equivalents, or substitutions of the corresponding embodiments. In the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more items unless the relevant context clearly specifies otherwise.

[0040] In this document, each of the phrases such as “A or B,” “at least one of A and B,” “at least one of A or B,” “A, B, or C,” “at least one of A, B, and C,” and “at least one of A, B, or C” can include any one of the items listed together in the corresponding phrases within these phrases, or all possible combinations thereof. Terms such as “first,” “second,” “first,” “second,” “A,” “B,” “(a),” or “(b)” can be used simply to distinguish one component from another, and do not limit the corresponding component in another respect (e.g., importance or order).

[0041] In this document, with or without the terms “functionally” or “communically”, when one (e.g., the first) component is described as “connected,” “coupled,” or “joined,” or “linked” or “connected” to another (e.g., the second) component, it means that one component can be connected to the other component directly (e.g., via a wire), wirelessly, or via a third component.

[0042] According to one embodiment, methods according to various embodiments disclosed herein can be provided by including them in a computer program product. The computer program product can be traded as a commodity between a seller and a buyer. The computer program product can be distributed in the form of a device-readable storage medium (e.g., an optical disc read-only memory (CD-ROM)), distributed through an app store (e.g., downloaded or uploaded), or distributed directly online between two user devices. In the case of online distribution, at least some of the computer program product can be at least temporarily stored or temporarily generated in a device-readable storage medium, such as the memory of a manufacturer's server, an app store's server, or a relay server.

[0043] According to various embodiments, each of the above components (e.g., a module or program) may include a single object or multiple objects, and some of the multiple objects may be separately located in another component. According to various embodiments, one or more of the corresponding components or their operations may be omitted, or one or more other components or operations may be added. Alternatively or additionally, multiple components (e.g., modules or programs) may be integrated into one component. In this case, the integrated component may perform one or more functions of each of the multiple components in the same or similar manner as the functions performed by the corresponding components of the multiple components prior to integration. According to various embodiments, the operations performed by modules, programs, or other components may be performed sequentially, in parallel, repeatedly, or heuristically, or one or more operations may be performed in a different order or omitted, or one or more other operations may be added.

[0044] Figure 1 This is a block diagram illustrating a data collection system according to one embodiment disclosed herein.

[0045] Reference Figure 1 According to one embodiment of the present disclosure, the data collection system 10 may include a vehicle 100, a data collection device 200, and a server 300.

[0046] Vehicle 100 may be an electric vehicle (EV) that receives driving force from a battery used for storing electricity, but the scope of this disclosure is not limited thereto, and the technical concepts of this disclosure may be applied to other electric transportation vehicles (e.g., electric scooters) instead of vehicle 100.

[0047] Vehicle 100 may include battery pack 110, vehicle controller 120 and vehicle network 130.

[0048] The battery pack 110 may include a battery (not shown) for storing the power required to drive the vehicle 100 and a battery management system (BMS) (not shown) for controlling the operation of the battery. Here, the BMS can control and / or manage the charging and discharging of the battery. Furthermore, according to embodiments, the BMS can generate battery data regarding the battery's state. For example, the BMS can send battery data to the vehicle network 130, including at least one of data acquired by sensing the battery (e.g., voltage, current, resistance, and temperature of the battery cells) and data generated by processing the acquired data (e.g., state of charge (SOC) and state of health (SOH)).

[0049] The vehicle controller 120 can control the operation and / or functions of the vehicle 100 and generate vehicle data. According to embodiments, in addition to the battery pack 110, the vehicle controller 120 can also control the operation of the vehicle 100 by controlling at least one sensor (e.g., a radar sensor or a temperature sensor) and at least one control device (e.g., a drive system, braking system, steering system, automated driving system (ADS), telematics system (TMS)) disposed in the vehicle 100. According to embodiments, the vehicle controller 120 can be an ECU for controlling some components of the vehicle 100.

[0050] According to the implementation method, the vehicle data may have a CAN message format. The vehicle data may include the status values, status change values, output signal values, etc. of the components included in the vehicle 100.

[0051] Furthermore, the vehicle controller 120 can store vehicle identification information unique to vehicle 100 and send the vehicle identification information in response to requests from external sources (e.g., data collection device 200). According to embodiments, the vehicle identification information may include a vehicle identification number (VIN). The vehicle controller 120 can communicate with other devices located inside or outside vehicle 100 via vehicle network 130.

[0052] Vehicle network 130 can provide a communication environment in which components within vehicle 100 can send and receive data. Vehicle network 130 may be a CAN where components within vehicle 100 can be connected in parallel to communicate with each other without a host, but the scope of this disclosure is not limited thereto. According to embodiments, vehicle network 130 may allow connection of external devices (e.g., data collection device 200) to provide an environment in which external devices can communicate with another device (e.g., battery pack 110) via vehicle network 130.

[0053] The data collection device 200 can collect data from the vehicle 100 and send the collected data to the server 300. According to one embodiment, the data collection device 200 can collect data from the battery pack 110 and / or the vehicle controller 120 of the vehicle 100. According to another embodiment, the data collection device 200 can be integrally formed with the vehicle 100 and implemented as a separate device, and connected to the vehicle 100 via an external connection device.

[0054] According to the implementation, the data collection device 200 is a device that can be installed on the vehicle 100 and connected to the vehicle network 130. For example, it can be an on-board diagnostic (OBD) device connected to an OBD port located on the vehicle 100. The data collection device 200 can connect to the vehicle network 130 to send and receive Unified Diagnostic Service (UDS) data to obtain data about the status of the vehicle 100 from components in the vehicle 100. Here, the data about the status of the vehicle 100 may include vehicle speed data, distance traveled data, travel time data, location data, and battery data.

[0055] According to the implementation, the data collection device 200 can send data about the vehicle 100 to the server 300. The data collection device 200 can send data to the server 300 via any wireless communication method. For example, the data collection device 200 can send data to the server 300 via the Long Term Evolution (LTE) communication method.

[0056] According to the implementation, the data collection device 200 for the vehicle 100 can send coloring data to the server 300. Here, the coloring data may be data collected by the data collection device 200 that was not sent to the server 300 due to reasons such as communication failure.

[0057] According to the implementation, the data collection device 200 can send the collected data to the server 300 in various ways. For example, the data collection device 200 can send the raw data of the collected data or send processed data and / or the collected data after processing.

[0058] However, due to the recent proliferation and development of data collection devices 200 installed on vehicle 100, the amount of data collected by data collection devices 200 is increasing. Furthermore, the amount of colored data, which is data not yet sent from data collection device 200 to server 300, is also increasing. Therefore, the communication costs and traffic required to send the data collected by data collection device 200 to server 300 may increase. Additionally, the storage space and storage costs for storing data in data collection device 200 and server 300 may also increase. Therefore, in order to reduce communication and storage costs, data collection device 200 must manage the collected data, and for this purpose, reference can be made to… Figure 2 Describe the operation of data collection device 200.

[0059] According to the implementation, server 300 can send and receive data with data collection device 200. Therefore, server 300 can receive data about vehicle 100 from data collection device 200, and store and analyze the data to provide management services for vehicle 100 or battery pack 110.

[0060] Server 300 can acquire data about vehicle 100 from data collection device 200. Server 300 can store the acquired data in a database. The data stored in the database can be used to analyze and / or manage the status of vehicle 100.

[0061] Server 300 can preset the data to be collected by data collection device 200 and manage data collection device 200. For example, before data collection device 200 collects data from vehicle 100, server 300 can select the target from which to collect data (e.g., battery pack 110 and / or vehicle controller 120), and set the data items to be collected from the selected target and the collection period, and send them to data collection device 200.

[0062] Figure 2 This is a block diagram illustrating a data collection device according to one embodiment disclosed herein.

[0063] Reference Figure 2 The data collection device 200 may include a data acquisition unit 210, a memory 220, a communication module 230, and a processor 240. However, this disclosure is not limited thereto, and some components may be omitted from the data collection device 200, or other common components may be further included in the data collection device 200. See also... Figure 1 To describe Figure 2 The following description.

[0064] Data acquisition unit 210 can be connected to vehicle network 130 to acquire and / or collect data from internal components of vehicle 100 (e.g., battery pack 110 and vehicle controller 120). Here, the data acquired from vehicle 100 can be referred to as raw data. According to an embodiment, data acquisition unit 210 can acquire data from vehicle 100 per unit time. For example, data acquisition unit 210 can collect data continuously based on data items or collect data at different collection periods.

[0065] The memory 220 can store data received from the vehicle 100 (i.e., raw data). For example, the memory 220 can store vehicle 100 speed data, travel distance data, travel time data, travel location data, and battery data. In addition, the memory 220 can store data collection setting information received from the server 300.

[0066] According to one embodiment, the memory 220 can divide the raw data acquired from the data acquisition unit 210 into multiple data files and store the data files. According to another embodiment, the memory 220 can divide the raw data into 5-minute files and store the 5-minute files.

[0067] According to the implementation, memory 220 can store one or more pieces of coloring data. Here, the coloring data can be data collected by data collection device 200 that was not sent to server 300 due to reasons such as communication failure. For example, the coloring data may include one or more 5-minute raw data files obtained from data acquisition unit 210. The coloring data can be stored in memory 220 of data collection device 200. Subsequently, when data collection device 200 enters a communication-available area, the coloring data stored in memory 220 can be sent to server 300.

[0068] According to one embodiment, memory 220 may store data used by at least one component of data collection device 200 (e.g., data acquisition unit 210, communication module 230, and processor 240). For example, the data may include software (or related instructions), input data, or output data. According to one embodiment, when executed by processor 240, the instructions may cause data collection device 200 to perform operations defined by the instructions.

[0069] According to an embodiment, memory 220 may include volatile memory and / or non-volatile memory. Here, memory 220 may include at least one storage medium selected from flash memory, hard disk, multimedia card micro, card-type memory (e.g., SD or XD memory), magnetic memory, magnetic disk, optical disk, random access memory (RAM), static RAM (SRAM), read-only memory (ROM), programmable ROM (PROM), and electrically erasable PROM (EEPROM).

[0070] The communication module 230 can establish a wireless communication channel between the data collection device 200 and the server 300, and send and receive data with the server 300 through the established communication channel. For example, the communication module 230 can send and receive data with another device based on at least one radio access technology (RAT). Here, RAT may include 3G (WCDMA, HSDPA, etc.), 4G (LTE, etc.), and 5G. According to the implementation, the communication module 230 may include a module that supports wireless Internet access, such as wireless LAN (WLAN), Wibro, Wi-Fi, WiMAX, or HSDPA.

[0071] In addition, the communication module 230 can send and receive data with internal components of the vehicle 100 (battery pack 110, vehicle controller 120, etc.) connected via the vehicle network 130.

[0072] According to an embodiment, the communication module 230 may include a storage unit 231. Here, the storage unit 231 may be a storage space different from the memory 220. For example, the storage unit 231 may be the RAM storage unit of the communication module 230. According to an embodiment, the communication module 230 can send data stored in the storage unit 231 to the server 300. Furthermore, the storage unit 231 of the communication module may store a set of compressed data, which will be described below.

[0073] The processor 240 can manage and / or control the operation and / or state of the data collection device 200. According to an embodiment, the processor 240 can control the data collection device 200 to perform reference... Figure 1 The operation of the data collection device 200 is described. Furthermore, the processor 240 can process various data and / or signals required to perform the operation of the data collection device 200.

[0074] According to the implementation, processor 240 can compress and manage data acquired from vehicle 100. Here, processor 240 can compress the data using any compression algorithm. For example, processor 240 can use a compression algorithm including the ZLIB compression library. When processor 240 uses the ZLIB compression library, memory 220 can be used minimally to compress data at high speed.

[0075] According to the implementation, the processor 240 can compress and manage the colorization data. Since the colorization data is not sent to the server 300 but stored in the memory 220, an increase in the amount of colorization data may lead to insufficient capacity in the memory 220. Therefore, the processor 240 can compress and manage the colorization data to efficiently manage the memory 220 of the data collection device 200.

[0076] According to one embodiment, processor 240 can manage multiple shaded data sets as a dataset. Here, a dataset can be a group of shaded data sets including one or more shaded data sets. According to one embodiment, processor 240 can group multiple shaded data sets into a dataset and compress the dataset. Therefore, processor 240 can store and manage multiple shaded data sets as a compressed dataset.

[0077] According to various implementations, various communication processes, such as communication network checks, communication requests, and responses, can be performed for each step in which the data collection device 200 sends colored data to the server 300. Here, communication requests and responses may include communication protocols such as TLS handshakes and REST APIs. However, as the amount of colored data increases, the communication process may unnecessarily increase in the number of steps required to send each piece of colored data. Therefore, the processor 240 can manage multiple pieces of colored data into a single dataset to reduce unnecessary data overhead.

[0078] According to one implementation, processor 240 can determine a dataset based on the chronological order in which multiple colored data were generated. According to another implementation, processor 240 can sort the multiple colored data according to the chronological order in which they were generated, and determine the dataset based on the sorted colored data. For example, processor 240 can determine the dataset to include the earliest generated colored data to the most recently generated colored data in chronological order. Therefore, processor 240 can increase the continuity and / or consistency of the multiple colored data in the dataset.

[0079] According to the implementation, the processor 240 can determine the dataset by considering the size of multiple coloring data, the capacity of the storage unit 231 of the communication module 230, and the compression ratio. For example, the processor 240 can determine the dataset such that the size of the compressed dataset is smaller than the capacity of the storage unit 231. Therefore, the processor 240 can allow the compressed dataset to be stored in the storage unit 231 without any loss.

[0080] According to the implementation, the processor 240 can determine the amount of colorized data to be included in the dataset such that the size of the dataset after compressing the multiple colorized data included in the dataset at a predetermined compression rate is less than the capacity of the storage unit 231. For example, when the size of an original colorized data is 750 KB and the minimum compression rate is 80%, the size of a compressed colorized data may be 150 KB. Therefore, the processor 240 can determine the amount of colorized data to be included in the dataset (e.g., 17) such that the size of the dataset in which multiple colorized data are compressed is less than the capacity of the storage unit 231 (e.g., 2.6 MB).

[0081] According to the implementation, processor 240 can determine the dataset such that the size of the compressed dataset is smaller than the capacity of storage unit 231 after excluding a safety margin. Here, the safety margin may include the capacity required to perform operations on storage unit 231 and / or the capacity of a buffer used to prevent data loss stored in storage unit 231. For example, when the size of an original coloring data is 750 KB and the minimum compression ratio is 80%, the size of a compressed coloring data may be 150 KB. Therefore, processor 240 can determine the number of coloring data to be included in the dataset (e.g., 15) such that the size of the dataset in which multiple coloring data are compressed is smaller than the capacity of storage unit 231 after excluding a safety margin (0.3 MB) (e.g., 2.6 MB). Therefore, processor 240 can ensure the stability of the compressed dataset.

[0082] According to the implementation, the processor 240 can compress the dataset in a streaming manner. Here, the streaming manner can be a method of reading and compressing the data to be compressed in real time. Therefore, the processor 240 can process the data in the time domain sequentially without downloading the entire dataset, which includes multiple shaded data.

[0083] According to one implementation, processor 240 can compress the dataset in a streaming manner. Alternatively, processor 240 can simultaneously stream data, package the data into predetermined sizes, and compress the packaged data. Here, data packaging can mean dividing the data into small units and managing the divided data. For example, processor 240 can compress multiple colored data units in 16KB units in a streaming manner. Therefore, processor 240 can divide a large dataset into small units in the time domain and compress and manage the divided dataset.

[0084] According to one embodiment, processor 240 can use one or more buffers to compress data in a streaming manner. For example, processor 240 can use an input buffer and an output buffer to compress a dataset in a streaming manner. According to one embodiment, processor 240 can package multiple colorized data files into a predetermined size (e.g., 16KB) and then copy the packaged data to the input buffer. Furthermore, processor 240 can compress the data in the input buffer and copy the compressed data to the output buffer. Here, processor 240 can check for errors during compression. When it is confirmed that no errors have occurred, processor 240 can store the compressed data from the output buffer as a compressed file.

[0085] According to the implementation, the processor 240 can store the compressed dataset in the memory 220 or the storage unit 231 of the communication module 230. Here, the compressed dataset can be data whose size is reduced to about 1 / 10 compared to the original data. Therefore, the processor 240 can store the compressed dataset in the memory 220 or the storage unit 231, which has been compressed with less computation than storing the original data. Therefore, the processor 240 can stabilize the load of the embedded system and improve the processing speed. In addition, the processor 240 can send the compressed dataset from the data collection device 200 to the server 300 to reduce the unnecessary communication cost with the server 300 by about 90%.

[0086] According to the implementation, the communication module 230 can connect to a service provider network and send a communication request before sending the dataset to the server 300. Here, the communication module 230 can connect to the service provider network and then connect to the server 300. Furthermore, the communication module 230 can send and receive communication requests and responses with the server 300. Here, the communication requests and responses can include any communication protocol (e.g., REST API requests and responses). When a response to a communication request is received from the server 300, the communication module 230 can send the dataset stored in the storage unit 231 to the server.

[0087] Therefore, the communication module 230 can send a dataset containing multiple colored data to the server 300 by sending and receiving a single communication request and response instead of sending and receiving multiple communication requests and responses. Thus, the data collection device 200 can reduce unnecessary data overhead and improve communication speed and efficiency.

[0088] Figure 3 This is a flowchart of the operation of a data collection device according to one embodiment disclosed herein.

[0089] Reference Figure 3The data collection device 200 can identify a dataset that includes multiple colored data (S101), and compress and manage the dataset (S102).

[0090] In operation S101, the processor 240 of the data collection device 200 can determine a dataset comprising multiple colored data (S101). For example, the processor 240 can sort the multiple colored data according to the time order in which they were generated to determine the dataset. Furthermore, the processor 240 can consider the capacity of the storage unit 231 when determining the dataset.

[0091] In operation S102, processor 240 can compress and manage the dataset (S102).

[0092] Figure 4 This is a flowchart of the operation of a data collection device according to one embodiment disclosed herein.

[0093] Reference Figure 4 The data collection device 200 can store the compressed dataset in the storage section of the communication module (S201), send a communication request to the server (S202), and when it receives a response to the communication request from the server, send the dataset stored in the storage section to the server (S203).

[0094] In operation S201, the processor 240 of the data collection device 200 can store the compressed dataset in the storage unit 231 of the communication module 230 (S201).

[0095] In operation S202, communication module 230 can send communication requests to server 300 (S202).

[0096] In operation S203, when a response to a communication request is received from server 300, communication module 230 can send the dataset stored in storage unit 231 to server 300 (S203).

[0097] Figure 5 This is a block diagram illustrating the hardware configuration of a computing system for performing a method of operating a data collection device according to one embodiment disclosed herein.

[0098] Reference Figure 5 The computing system 2000 according to one embodiment disclosed herein may include a microcontroller unit (MCU) 2010, a memory 2020, an input / output I / F 2030, and a communication I / F 2040.

[0099] The MCU 2010 can execute various programs stored in the memory 2020 (e.g., vehicle data collection program, latent variable extraction program, and compression program), through which it processes various information, including data about the vehicle 100, and performs tasks such as... Figures 1 to 4 The function of the processor 240 in the data collection device 200 shown.

[0100] The memory 2020 can store various programs, such as vehicle data collection programs, latent variable extraction programs, and compression programs. Furthermore, the memory 2020 can store various information, including data about vehicle 100.

[0101] Multiple memory units 2020 can be provided as needed. Memory units 2020 can be volatile or non-volatile. As volatile memory, memory units 2020 can use RAM, DRAM, SRAM, etc. As non-volatile memory, memory units 2020 can use ROM, PROM, EAROM, EPROM, EEPROM, flash memory, etc. For example, memory units 2020 can include SD cards. The examples of memory units 2020 listed above are merely illustrative and are not limited to these examples.

[0102] The input / output I / F 2030 can be an interface for connecting input devices (not shown) such as a keyboard, mouse, or touch panel and output devices such as a display (not shown) to the MCU 2010 and allowing the input and output devices to send and receive data with the MCU 2010.

[0103] The communication I / F 2040 is a component capable of sending and receiving various types of data to and from a server, and can be any device capable of supporting wired or wireless communication. For example, the data collection device 200 can send and receive various information, including the SOC, OCV, parameters, etc. of the battery cells, from a separately provided external server via the communication I / F 2040.

[0104] As described above, a computer program according to one embodiment disclosed herein can be implemented for execution, for example, by being recorded in memory 2020 and processed by MCU 2010. Figure 2 The module that provides the shown functions.

[0105] As stated above, although all components constituting the embodiments disclosed herein are described as operating by or in connection with each other, the embodiments disclosed herein are not necessarily limited to these embodiments. In other words, one or more of the components may operate by selective connection without departing from the purpose of the embodiments disclosed herein.

[0106] Furthermore, unless otherwise stated, terms such as “comprising,” “constituting,” or “having” above imply that the corresponding component may be inherent and should therefore be interpreted as further including rather than excluding another component. Unless otherwise defined, all terms including technical or scientific terms have the same meaning as commonly understood by one of ordinary skill in the art to which the embodiments disclosed herein pertain. Common terms, such as those defined in dictionaries, should be interpreted as consistent with the context of the relevant art and should not be interpreted in an ideal or overly formal sense unless explicitly defined herein.

[0107] The foregoing disclosure illustratively describes features of several embodiments, enabling those skilled in the art to better understand various aspects of this disclosure. Those skilled in the art will readily understand that this disclosure can serve as the basis for designing or modifying other structures to perform the same purposes or achieve the same advantages as the embodiments described herein. Furthermore, those skilled in the art will recognize that such equivalent configurations do not depart from the scope of this disclosure, and that various changes, substitutions, and modifications can be made herein without departing from the scope of this disclosure.

[0108] [Description of reference numerals in the attached figures]

[0109] 10: Data Collection System

[0110] 100: Vehicles

[0111] 110: Battery Pack

[0112] 120: Vehicle Controller

[0113] 130: Vehicle Network

[0114] 200: Data collection equipment

[0115] 210: Data Acquisition Unit

[0116] 220: Memory

[0117] 230: Communication Module

[0118] 231: Storage Department

[0119] 240: Processor

[0120] 300: Server

[0121] 2000: Computing Systems

[0122] 2010: MCU

[0123] 2020: Memory

[0124] 2030: Input / Output I / F

[0125] 2040: Communication I / F

Claims

1. A data collection device, the data collection device comprising: A memory configured to store multiple shader data; as well as A processor configured to determine a dataset comprising the plurality of colored data and to manage the dataset by compressing the dataset.

2. The data collection device according to claim 1, wherein, The multiple colored data are data collected in the data collection device that has not yet been sent to the server.

3. The data collection device according to claim 1, wherein, The processor sorts the plurality of colored data in the time order in which they were generated, and determines the dataset based on the sorted plurality of colored data.

4. The data collection device according to claim 1, wherein, The processor compresses the multiple colored data included in the dataset in a streaming manner.

5. The data collection device according to claim 1, wherein, The data collection device further includes a communication module, which includes a storage unit configured to store the compressed dataset.

6. The data collection device according to claim 5, wherein, The processor determines the dataset based on at least one of the size of the plurality of colored data, the capacity of the storage unit, and the compression ratio of the compression.

7. The data collection device according to claim 6, wherein, The processor determines the number of the plurality of colored data included in the dataset such that the size of the dataset after compressing the plurality of colored data included in the dataset at the compression rate is less than the capacity of the storage unit.

8. The data collection device according to claim 5, wherein, The communication module is configured as follows: Send a communication request to the server; and When a response to the communication request is received from the server, the dataset stored in the storage unit is sent to the server.

9. A method for collecting data, the method comprising the following steps: Identify a dataset that includes multiple colored data sets; as well as The dataset is managed by compressing it.

10. The method according to claim 9, wherein, The multiple colored data are data collected in the data collection device that has not yet been sent to the server.

11. The method according to claim 9, wherein, The steps to determine the dataset include the following: The multiple coloring data are sorted according to the time order in which they were generated; and The dataset is determined based on multiple sorted colored data.

12. The method according to claim 9, wherein, The steps of managing the dataset by compressing the dataset include the following steps: compressing the plurality of colored data included in the dataset in a streaming manner.

13. The method according to claim 9, further comprising the following step: The compressed dataset is stored in the storage section of the communication module.

14. The method according to claim 13, wherein, The steps of determining the dataset include the following: determining the dataset based on at least one of the size of the plurality of colored data, the capacity of the storage unit, and the compression ratio of the compression.

15. The method of claim 14, further comprising the step of: The number of the plurality of colored data included in the dataset is determined such that the size of the dataset after compressing the plurality of colored data included in the dataset at the compression rate is less than the capacity of the storage unit.

16. The method of claim 13, further comprising the step of: Send a communication request to the server; as well as When a response to the communication request is received from the server, the dataset stored in the storage unit is sent to the server.

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