System for diagnosing and managing state of electric vehicle battery for used-vehicle transaction

Abstract

Disclosed is a system for diagnosing and managing the state of an electric vehicle battery. A system for diagnosing and managing the state of an electric vehicle battery, according to one embodiment of the present invention, comprises: a signal acquisition unit collecting data generated from an electric vehicle in real time; a data processing unit capable of generating operation-based continuous data (flow data); a data transmission unit transmitting data to a server and a Web or an app for a driver via a wireless communication network (long-term evolution, LTE); a data collection unit including an anomaly detection unit detecting an abnormal condition, and a data storage unit storing operation-based continuous data; an artificial intelligence analysis unit predicting the state of the battery by applying a machine learning model using the operation-based continuous data as input features; an actual vehicle inspection request unit generating an actual vehicle inspection request and transmitting notification to a Web or an app for a driver; a data integrity management unit verifying the integrity of operation and inspection data and enabling storage and transaction on a blockchain basis; and a server including a carbon reduction and NFT management unit converting electric vehicle operation records into a carbon reduction amount and a reduced cost, and enabling storage as an NFT and management of transaction.

Description

A system for diagnosing and managing the condition of electric vehicle batteries for second-hand trading

[0001] The present invention relates to a system that supports vehicle maintenance and life cycle management by diagnosing the battery condition of an electric vehicle in real time and predicting the degradation trend and remaining lifespan of the battery. In particular, it relates to a technology that collects continuous data based on the operation of an electric vehicle, evaluates the battery condition by applying artificial intelligence analysis techniques, provides optimal inspection services to the driver through real-time anomaly detection and maintenance linkage, and supports reliable battery condition information and fair value assessment by linking with a used car trading platform.

[0002] The following descriptions are intended to aid in understanding the technical significance of the invention and are not based on the premise that they were publicly known prior to the filing. Therefore, the fact that a description is included in the background technology of the invention should not be regarded as publicly known technology in itself.

[0003] As the adoption of electric vehicles expands, the importance of technologies for accurately assessing and managing battery conditions is becoming increasingly prominent. Conventional technologies have primarily monitored battery status by simply collecting basic voltage, current, and temperature data generated during vehicle operation. This data is collected through Battery Management Systems (BMS) or in-vehicle control units, and the collected information is analyzed within the vehicle to a limited extent or used to identify simple anomalies. Some systems adopt methods that predict battery replacement timing based on driving data or periodically check battery performance using diagnostic equipment. Furthermore, research has been conducted on methods to estimate battery degradation trends under specific driving conditions or to detect signs of severe degradation or failure by monitoring voltage imbalances between cells.

[0004] However, these conventional technologies have limitations in precisely analyzing battery status in real-time in response to various situations that occur during operation. Because the types of collected data are limited and data interpretation is rule-based, complex degradation patterns or signs of abnormality often fail to be detected early. Furthermore, simple statistical-based diagnostics do not adequately reflect the battery's diverse usage environments (charge / discharge rates, temperature changes, driving patterns, etc.), resulting in discrepancies with the actual battery degradation state. Drivers must rely on visits to repair shops or specialized equipment to check battery status or identify abnormalities; consequently, there is a risk that battery performance degradation will not be detected early, potentially leading to severe deterioration or accidents.

[0005] Furthermore, even if conventional technology collects battery status data, it lacks the capability to structure it for long-term management or to systematically manage the entire battery lifecycle by combining it with the driver's driving history. Driving data is primarily managed at the vehicle level, making it difficult to perform detailed analysis or customized management for individual drivers. Consequently, drivers find it difficult to understand the impact of their driving habits on battery degradation and are not provided with the information necessary to adjust optimal driving methods or charging habits. As a result, negative consequences such as shortened battery life, performance degradation, and increased maintenance costs are inevitable.

[0006] Conventional technology lacks features to guide maintenance after anomaly detection or to support maintenance scheduling. Even when signs of anomalies are detected, drivers are not provided with specific inspection recommendations, or inspections are conducted primarily through reactive measures, resulting in the preventive maintenance system failing to function properly. In particular, the absence of a structure capable of early detection of rapid deterioration or accident signs during operation, and of recommending inspections to drivers in real-time in coordination with repair shops, presents limitations in terms of accident risk management.

[0007] Furthermore, used car trading companies are facing a situation where they cannot adequately respond to not only currently distributed electric vehicles but also continuously released new models and their installed battery systems due to the lack of systematic data collection and analysis methods for the evaluation and trading of electric vehicle batteries. Specifically, although electric vehicle battery performance serves as a critical factor in determining vehicle value, reliable evaluations cannot be achieved during transactions because there is no standardized framework for collecting and interpreting data such as remaining battery life, degradation status, charge / discharge history, and signs of abnormalities. In particular, the absence of an integrated platform capable of collecting and analyzing battery management system structures and data formats that differ across various manufacturers and models makes it virtually impossible to perform consistent performance comparisons and valuations for individual vehicles. Consequently, used car trading companies struggle to determine prices based on objective and reliable information regarding battery condition or to prevent disputes between buyers and sellers, which ultimately acts as an obstacle to the credibility and revitalization of the used electric vehicle market.

[0008] To address these issues, technology must be improved to precisely analyze real-time battery status based on driving data, detect abnormal patterns early, and provide driver-tailored battery management services. In other words, it is essential to restructure the system to comprehensively manage the battery lifecycle by reflecting the driver's driving history and habits, enabling preventive responses through early inspections.

[0009] To overcome the limitations of conventional technology and enhance the safety and reliability of electric vehicle batteries, a new technological approach integrating real-time analysis, precise prediction, and driver-customized management functions is required. Furthermore, from the perspective of used car trading companies, such a battery diagnostic system based on real-time driving data must enhance transaction transparency by providing reliable condition assessments of electric vehicles for sale, and be able to present valuation results to both buyers and sellers based on objective and consistent standards.

[0010] The present invention aims to accurately analyze changes in the state of a battery in real time during the operation of an electric vehicle, detect degradation trends and lifespan reduction at an early stage, and provide guidance on the timing for preventive maintenance and battery replacement.

[0011] In addition, the present invention aims to provide optimized battery performance maintenance and user-customized management services throughout the vehicle lifecycle by integrally managing the driver's driving history and changes in battery status.

[0012] Furthermore, the present invention aims to enhance transaction trust between sellers and buyers and support the revitalization of the used electric vehicle market by linking with a used car trading platform based on battery condition analysis results to provide reliable battery condition information and fair valuation standards for electric vehicle listings.

[0013] However, the technical problem that this embodiment aims to solve is not limited to the technical problem described above, and other technical problems may exist.

[0014] A system for diagnosing and managing the battery status of an electric vehicle according to an embodiment of the present invention comprises a data collection device, a server, and a Web or App for a driver, wherein the data collection device includes: a signal collection unit that receives a Controller Area Network (CAN) signal generated from an electric vehicle and collects data on battery pack voltage, battery pack current, battery pack temperature, charge / discharge amount, driving distance, and driving time in real time; a data processing unit that sorts the data collected from the signal collection unit in chronological order, removes outliers based on a preset threshold value, and normalizes input values ​​to a range from 0 to 1 to generate operation-based continuous data (Flow data); a data transmission unit that transmits the operation-based continuous data to a server and a Web or App for a driver via a wireless communication network (Long-Term Evolution, LTE); and an outlier detection unit that monitors the collected data in real time to detect the occurrence of an outlier, transmits a notification to a Web or App for a driver when an outlier occurs, and simultaneously transmits the outlier situation to a server.

[0015] The server may include: a data storage unit that stores continuous operation-based data; an artificial intelligence analysis unit that predicts the State of Health (SOH), degradation tendency index, and Estimated Remaining Useful Life (RUL) of a battery by applying a machine learning model using the continuous operation-based data stored in the data storage unit as input characteristics; a vehicle inspection request unit that generates a vehicle inspection request based on the prediction results of the artificial intelligence analysis unit and anomaly occurrence data received from an anomaly detection unit, and notifies a Web or App for drivers; a data integrity management unit that verifies the integrity of operation and inspection data and stores and trades it based on blockchain; and a carbon reduction and NFT management unit that converts electric vehicle operation records into carbon reduction amounts and savings amounts, and manages storage and trading as NFTs.

[0016] According to one embodiment, the signal collection unit can additionally collect State of Charge (SOC), cumulative charge / discharge amount, voltage and cell temperature data for each battery cell from a Battery Management System (BMS) via a vehicle communication control network.

[0017] According to one embodiment, the signal collection unit can calculate cell-to-cell variation based on collected voltage and temperature data for each battery cell and include it in operation-based continuous data and transmit it to a server and a Web or App for the driver.

[0018] According to one embodiment, the data processing unit samples the collected data at a time interval of less than 1 second, removes noise by applying a moving average filter, and can accumulate and store the entire collected data over the lifecycle.

[0019] According to one embodiment, the data processing unit can identify rapid acceleration, rapid deceleration, and high-speed charging events by applying a peak detection algorithm after moving average filtering, and store the event occurrence time and duration as metadata on a server.

[0020] According to one embodiment, the anomaly detection unit detects an anomaly when one or more of the battery pack voltage, battery pack temperature, or voltage per cell exceeds or falls below a set threshold, and can transmit an anomaly occurrence notification to a Web or App for drivers and a server.

[0021] According to one embodiment, the anomaly detection unit can transmit an anomaly occurrence notification and, at the same time, assign a warning flag to the operation-based continuous data and store it on the server.

[0022] According to one embodiment, the actual vehicle inspection request unit of the server, upon receiving a notification of an anomaly, communicates with a contracted maintenance company or support server according to a predefined logic to generate an actual vehicle inspection request and can transmit the request to the driver through a Web or App for the driver.

[0023] According to one embodiment, the vehicle inspection request unit can recommend an optimal repair shop and provide a reservation function by considering real-time traffic conditions, vehicle location information, and repair shop availability information.

[0024] According to one embodiment, the data integrity management unit records operation-based continuous data and certificate data on a blockchain-based distributed ledger to prevent tampering and can verify in real time whether the data has been changed.

[0025] According to one embodiment, the data integrity management unit generates a transaction hash value for operation-based continuous data recorded on a blockchain network, and can automatically verify whether the data has been tampered with when viewed by a driver, a repair shop, or a used car trading platform.

[0026] According to one embodiment, the carbon reduction and NFT management unit analyzes operation-based continuous data to calculate the amount of carbon reduction resulting from the operation of an electric vehicle, calculates the amount of carbon reduction based on the amount of carbon reduction, and then generates the amount of carbon reduction and the amount of carbon reduction in the form of an NFT (Non-Fungible Token) and registers them on the blockchain.

[0027] According to one embodiment, the carbon reduction and NFT management unit may include a function that enables the generated NFT to be transferred to an external carbon emission rights exchange or a personal wallet.

[0028] According to one embodiment, the artificial intelligence analysis unit uses past driving data and predicted data during a future window as input to train a model to maximize the cumulative signal-to-noise ratio (SNR) gain, and can predict battery degradation trends by considering driving habits, driving routes, and environmental conditions.

[0029] According to one embodiment, the artificial intelligence analysis unit can provide battery replacement timing, maintenance recommendation timing, and driving habit improvement guides through a Web or App for drivers based on the results of predicting degradation trends.

[0030] According to one embodiment, the data storage unit can accumulate, store, and manage flow data collected over the entire vehicle lifecycle of operation-based continuous data.

[0031] According to one embodiment, the data storage unit can generate a statistical index by classifying rapid acceleration, rapid deceleration, high-speed charging, extreme temperature conditions, and other abnormal events included in the lifecycle flow data by driving section.

[0032] According to one embodiment, after the server receives information regarding an anomaly, the vehicle inspection request unit can propose the assignment of a mechanic and an on-site inspection schedule to the driver within a set time by linking with a nearby maintenance company.

[0033] According to one embodiment, the vehicle inspection request unit can provide the driver with the maintenance progress status in real time via a Web or App for the driver after a mechanic has been assigned.

[0034] According to one embodiment, a Web or App for drivers can be configured to provide battery status, in addition to enabling integrated viewing of predicted future battery life changes based on lifecycle flow data, accumulated carbon reductions, maintenance history, and certificate history.

[0035] According to one embodiment, in addition to anomaly notifications, a Web or App for drivers can periodically provide reminder notifications to drivers by managing the driver's previously registered maintenance reservation schedule, vehicle inspection cycle, certificate renewal timing, etc.

[0036] According to one embodiment, the system can provide continuous condition evaluation and driver-customized lifecycle management services based on Flow data collected throughout the entire vehicle lifecycle.

[0037] According to the present invention, the health status, degradation trend, and remaining lifespan of an electric vehicle battery can be accurately predicted and provided to the driver in real time, and abnormal conditions can be detected early to induce timely maintenance.

[0038] In addition, according to the present invention, by integrally managing the driver's driving data and battery status history, battery performance can be optimized throughout the vehicle's lifecycle, and this can contribute to reducing maintenance costs and improving driver convenience.

[0039] In addition, according to the present invention, by linking with a used car trading platform based on battery condition analysis results to provide reliable battery condition information and fair value assessment standards for electric vehicle listings, it is possible to improve transaction trust between sellers and buyers and support the revitalization of the used electric vehicle market.

[0040] However, the effects obtainable through the present invention are not limited to those described above, and other unmentioned technical effects will be clearly understood by a person skilled in the art from the description of the invention below.

[0041] FIG. 1 is a block diagram showing the overall configuration of a system for diagnosing and managing the condition of an electric vehicle battery according to one embodiment of the present invention.

[0042] Figure 2 is a block diagram showing the internal configuration of the data acquisition device of Figure 1.

[0043] Figure 3 is a block diagram showing the server configuration of Figure 1.

[0044] The present invention is capable of various modifications and may have various embodiments, and specific embodiments are illustrated in the drawings and described in detail in the detailed description. However, this is not intended to limit the invention to specific embodiments, and it should be understood that the invention includes all modifications, equivalents, and substitutions that fall within the spirit and scope of the invention.

[0045] To clearly explain the present invention, parts unrelated to the description have been omitted from the drawings, and similar parts throughout the specification have been given similar reference numerals. Furthermore, while describing with reference to the drawings, even components indicated by the same name may have different drawing numbers depending on the drawing, and drawing numbers are provided merely for the convenience of explanation; the concept, feature, function, or effect of each component is not to be interpreted restrictively by the corresponding drawing number.

[0046] Similar reference numerals are used for similar components when describing each drawing. Terms such as "first," "second," etc., may be used to describe various components, but said components should not be limited by said terms. These terms are used solely for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be named the second component, and similarly, the second component may be named the first component. Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as generally understood by those skilled in the art to which the present invention pertains.

[0047] Terms such as those defined in commonly used dictionaries should be interpreted as having meanings consistent with their meanings in the context of the relevant technology, and should not be interpreted in an ideal or overly formal sense unless explicitly defined in this application.

[0048] Throughout the specification, when a part is described as being "connected" to another part, this includes not only cases where they are "directly connected" but also cases where they are "electrically connected" with other elements interposed between them. Furthermore, when a part is described as "comprising" a certain component, this means that, unless specifically stated otherwise, it does not exclude other components but rather allows for the inclusion of additional components; it should be understood that this does not preclude the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0049] In this specification, "part" or "module" means a software or hardware component. However, "part" or "module" is not limited to hardware and software. "Part" or "module" may be configured to reside in an addressable storage medium or configured to run on one or more processors. Accordingly, by example, "part" or "module" includes components such as software components, object-oriented software components, class components, and task components, as well as processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The components and functions provided within the "part" or "module" may be combined into a smaller number of components and "parts" or "modules," or separated into additional components and "parts" or "modules."

[0050] Referring to the drawings below, a system for performing electric vehicle battery status diagnosis and management, comprising a data collection device, a server, and a Web or App for a driver according to an embodiment of the present invention, will be described in detail.

[0051] FIG. 1 is a block diagram showing the overall configuration of a system for diagnosing and managing the condition of an electric vehicle battery according to an embodiment of the present invention, FIG. 2 is a block diagram showing the internal configuration of a data collection device of FIG. 1, and FIG. 3 is a block diagram showing the server configuration of FIG. 1.

[0052] Referring to FIGS. 1 to 3, a system (10) for diagnosing and managing the condition of an electric vehicle battery may include an electric vehicle (100) including a data collection device (110), a server (120), a Web or App for drivers (130), and a vehicle repair shop (140). Here, the data collection device (110) may include a signal collection unit (111), a data processing unit (112), a data transmission unit (113), and an anomaly detection unit (114), and the server (120) may include a data storage unit (121), an artificial intelligence analysis unit (122), a vehicle inspection request unit (123), a data integrity management unit (124), and a carbon reduction and NFT management unit (125).

[0053] First, to describe the configuration of the data collection device (110), the signal collection unit (111) can receive signals from a Controller Area Network (CAN) to collect various driving-related data generated from the electric vehicle (110) in real time. Here, the Controller Area Network (CAN) is a standard protocol that supports high-speed communication between electronic control units within a vehicle, and refers to a network system designed to integrally exchange and manage data generated from various sensors and controllers. The CAN network is connected to the Battery Management System (BMS), Vehicle Control Unit (VCU), Driving Control Module, etc., inside the electric vehicle, and constantly transmits various physical parameters essential for driving, and the signal collection unit (111) can collect signals by directly connecting to this CAN bus.

[0054] In some embodiments, the signal collection unit (111) may collect data on battery pack voltage, battery pack current, battery pack temperature, charge / discharge amount, driving distance, and driving time. Here, battery pack voltage refers to the voltage applied to the entire high-voltage battery module of the electric vehicle and may indicate the charge state and output capability of the battery system. Battery pack current refers to the current value being charged or discharged, where the positive direction indicates charging and the negative direction indicates discharging. Battery pack temperature is an indicator of the thermal stability of the high-voltage battery system; since a rise above a certain temperature may lead to degradation or fire hazards, continuous monitoring is required. The charge / discharge amount is the integral of the accumulated charge current and discharge current, representing the accumulated usage state of battery energy, and may have a close relationship with the battery's remaining capacity (State of Charge, SOC) and the degree of degradation. Driving distance refers to information on the accumulated distance actually driven by the vehicle and can be used for predicting battery life and setting maintenance cycles, while driving time refers to the accumulated time the vehicle was actually in a driving state and can be used as an indicator to evaluate the usage history of the vehicle and battery system.

[0055] In some embodiments, the signal collection unit (111) may assign a time stamp to the collected data in real time and organize it into a data packet for transmission to the data processing unit (112). Additionally, the signal collection unit (111) may be designed to include a buffer memory to prevent data loss and to set the collection cycle to 100 milliseconds (ms) or less depending on the vehicle condition, thereby enabling accurate data collection even in high-speed driving environments.

[0056] The signal collection unit (111) may be configured to apply an electromagnetic compatibility (EMC) design to ensure stable operation even with changes in the operating environment, and to be equipped with an error management function that detects and recovers CAN bus errors, and additionally to support the vehicle fault diagnosis communication standard (On-Board Diagnostics, OBD-II) to collect standardized diagnostic data together.

[0057] In this way, the signal collection unit (111) can stably and accurately collect battery and driving-related data generated during the operation of the electric vehicle, and the collected data can be used as base data for various subsequent services, such as diagnosing the driver's battery status, server-based artificial intelligence analysis, issuing certificates, requesting actual vehicle inspection, calculating carbon reduction amount, and issuing NFTs, after undergoing normalization and anomaly detection processing in the data processing unit (112).

[0058] The data processing unit (112) can preprocess raw data related to operation collected from the signal collection unit (111) to make it suitable for subsequent analysis and storage. The data processing unit (112) first sorts the battery pack voltage, battery pack current, battery pack temperature, charge / discharge amount, driving distance, and driving time data received in real time from the signal collection unit (111) in chronological order. Here, chronological sorting is performed based on the timestamp assigned to each data, and is intended to prevent sequence errors between data collection points and to ensure accurate continuity. Subsequently, the data processing unit (112) can perform outlier removal based on a pre-set threshold value, which is intended to improve data quality by filtering out abnormal rapid value changes or signal distortion caused by sensor errors. Outlier removal can typically be implemented by means and standard deviation-based Z-Score filtering or by removing values ​​that exceed a pre-defined maximum / minimum allowable range. After the removal of outliers is completed, the data processing unit (112) performs normalization processing for each data item to adjust the range of the input values ​​to between 0 and 1. Through the normalization process, data with various physical units are adjusted to the same scale, so that processing such as machine learning-based analysis or threshold comparison can be performed consistently thereafter.

[0059] The data processing unit (112) generates operation-based continuous data (Flow data) through such sorting, outlier removal, and normalization processes, and the generated Flow data is ready to be transmitted to the server (120) and the driver's Web or App (130) in real-time or batch mode.

[0060] In some embodiments, the data processing unit (112) may additionally incorporate a peak detection algorithm that detects major driving events such as rapid acceleration, rapid deceleration, and high-speed charging, generate metadata regarding the time of event occurrence and duration, and transmit it to the server (120) along with driving-based continuous data. This peak detection algorithm may operate by detecting signal changes that exceed a specific fluctuation threshold after undergoing moving average filtering, and when an event occurs, it may insert a separate flag into the data or create an event index table to manage it separately.

[0061] In some embodiments, the data processing unit (112) may incorporate various exception handling logic to maintain stable data quality even in high-speed operation, rapid environmental changes, or sensor error situations, and may also improve transmission efficiency through data compression and packet optimization.

[0062] The data processing unit (112) transmits the finally generated operation-based continuous data to the data transmission unit (113), and can subsequently provide data for performing subsequent functions of the present invention, such as server-based artificial intelligence analysis, generation of actual vehicle inspection requests, blockchain recording, calculation of carbon reduction amount, and NFT issuance.

[0063] The data transmission unit (113) can transmit the operation-based continuous data generated by the data processing unit (112) to the server (120) and / or the driver's Web or App (130).

[0064] In some embodiments, the data transmission unit (113) may be configured to perform data transmission using a wireless communication network (Long-Term Evolution, LTE), and may also support 5th generation mobile communication (5G) or a vehicle-to-everything communication protocol (V2X, Vehicle-to-Everything) as needed. Since continuous driving data is collected and processed in real time, the data transmission unit (113) may be optimized to minimize data transmission latency and lower the transmission packet loss rate. To this end, the data transmission unit (113) may include a function to buffer a certain amount of data before transmission or to dynamically adjust the transmission cycle based on events. For example, when the vehicle is driving at a constant speed, data transmission is performed at 30-second intervals, and when abnormal events such as rapid acceleration, rapid deceleration, or high-speed charging occur, the transmission cycle is shortened to 1-second intervals so that data can be quickly delivered to the server (120) and the driver's Web or App (130). The data transmission unit (113) can support accurate operation history analysis on the server (120) by transmitting metadata such as the time of event occurrence, event type, and duration included in the transmitted data.

[0065] In addition, the data transmission unit (113) is equipped with a packet transmission error detection and retransmission function to maintain data integrity even when a communication failure occurs, and can apply TLS (Transport Layer Security) based encrypted communication as needed to enhance the confidentiality and security of the operation data.

[0066] In some embodiments, the data transmission unit (113) can perform a deferred transmission function to optimize the amount of data transmitted or delay data transmission by considering the driver's terminal status (network connection status, battery level, etc.) when transmitting data to the driver's Web or App (130). The driving-based continuous data transmitted to the server (120) is used for long-term storage in the data storage unit (121) and as input to the artificial intelligence analysis unit (122), and the data transmitted to the driver's Web or App (130) is provided so that the driver can monitor the vehicle battery status and whether an abnormality has occurred in real time. In this way, the data transmission unit (113) can perform an essential role in smoothly connecting the entire service flow of the present invention, such as real-time diagnosis, predictive analysis, certificate generation, and maintenance request notification, by transmitting the collected and processed driving data to the server (120) and the driver in a timely and stable manner.

[0067] The anomaly detection unit (114) can detect whether an anomaly has occurred by monitoring in real time the operation-based continuous data collected and organized through the signal collection unit (111) and the data processing unit (112). The anomaly detection unit (114) continuously analyzes battery pack voltage, battery pack current, battery pack temperature, charge / discharge amount, and voltage and temperature data for each battery cell, and recognizes an anomaly when it exceeds or falls below a preset threshold or reference pattern. The threshold comparison method can be implemented, for example, by detecting cases where the battery pack voltage drops below a set minimum allowable voltage or the battery temperature rises above the maximum allowable temperature. Additionally, if the cell-to-cell variation exceeds a reference range, the imbalance state of individual cells can be determined as an anomaly. In addition to this threshold-based detection method, the anomaly detection unit (114) can more precisely detect anomalies based on pattern changes as well as simple fluctuations by additionally applying a moving average, an exponential moving average, a time series anomaly detection algorithm, etc.

[0068] When an anomaly is detected, the anomaly detection unit (114) can generate and record metadata regarding the detected anomaly and simultaneously send a real-time notification to the driver's Web or App (130) to immediately notify the driver of the anomaly status. In addition, the anomaly detection result is simultaneously transmitted to the server (120) and used as basic data for generating a vehicle inspection request at the server (120), and subsequently serves as a starting point for providing maintenance reservation and inspection services. When transmitting an anomaly detection notification, the anomaly detection unit (114) includes the type of notification (e.g., overvoltage, overtemperature, rapid cell degradation, etc.), the time of occurrence, the duration, and the level of severity to support the driver and the server (120) in quickly understanding the situation and responding appropriately.

[0069] In some embodiments, the anomaly detection unit (114) may incorporate a continuous algorithm correction and threshold readjustment function to minimize the false positive rate and false negative rate, and may also provide an anomaly detection sensitivity adjustment function according to the vehicle driving environment (e.g., ambient temperature, altitude change). In this way, the anomaly detection unit (114) can detect anomalies early in real time in the battery and driving system of an electric vehicle and notify the driver and server (120) of this, thereby realizing various technical effects such as accident prevention, protection of battery life, reduction of maintenance costs, and enhancement of user safety.

[0070] Next, regarding the configuration of the server (120), the data storage unit (121) can perform the function of long-term storage and management of operation-based continuous data transmitted from the data collection device (110). The data storage unit (121) stores not only operation-based continuous data but also major operation events such as rapid acceleration, rapid deceleration, high-speed charging, and extreme temperature rise in the form of metadata, and records the chronological order of the data and the event history in a structured form. Since the operation-based continuous data is assigned a timestamp at each collection point, the data storage unit (121) can build an accurate time series database based on this. The stored data may include not only original data but also various types of data such as values ​​normalized by the data processing unit (112), abnormal occurrence notification data generated by the abnormality detection unit (114), actual vehicle inspection request history, and certificate generation history. To efficiently manage such complex data, a relational database or a non-relational database (NoSQL) structure may be applied.

[0071] In some embodiments, the data storage unit (121) may perform hash verification of transmission packets to ensure the integrity of continuous data based on operation, and periodically check for data tampering or loss. Additionally, to optimize data capacity, it may perform periodic data compaction and create a data index centered on important events to improve search and analysis efficiency. For example, sections where a sudden acceleration event occurred during driving, sections where a high-speed charging event occurred, or sections where a high-temperature condition persisted may be managed by assigning separate tags, and such event-centered indexing can be advantageous for improving data learning and prediction accuracy in the artificial intelligence analysis unit (122) thereafter.

[0072] In some embodiments, the data storage unit (121) integrates additional data, such as certificate issuance history, carbon reduction calculation results, and NFT creation and transaction history, in addition to continuous operation-based data, thereby supporting data analysis and report generation by vehicle, driver, and period. When necessary, the stored data is transmitted to a blockchain-based data integrity management unit (124) and registered in a distributed storage system for preventing data tampering and external verification. The data storage unit (121) may also provide a data provision interface (API) in conjunction with a driver's Web or App (130) to allow the driver to easily view past operation history, battery status change trends, and accumulated carbon reduction amounts.

[0073] The artificial intelligence analysis unit (122) can predict the battery state of health (SOH), degradation trend index, and estimated remaining useful life (RUL) by using continuous operation-based data stored in the data storage unit (121) as input.

[0074] In some embodiments, the artificial intelligence analysis unit (122) can quantitatively evaluate changes in battery performance and predict future degradation trends by applying a machine learning or deep learning model based on time-series driving data called from the data storage unit (121). The driving-based continuous data includes battery pack voltage, current, temperature, charge / discharge amount, voltage deviation between cells, rapid acceleration and rapid deceleration events, and high-speed charging records, and the artificial intelligence analysis unit (122) performs a complex state prediction by considering these multidimensional input characteristics together.

[0075] The artificial intelligence analysis unit (122) first independently predicts the battery capacity fade rate and internal resistance growth rate, respectively, and then integrates these results to calculate a degradation trend index. The degradation trend index is a composite indicator that quantifies patterns such as voltage drop, reduced charging speed, and increased cell temperature during a specific driving section, and can objectively express the battery aging state. In addition, the artificial intelligence analysis unit (122) can improve the precision of degradation prediction by training a model in a direction that maximizes the cumulative signal-to-noise ratio (SNR) gain by reflecting not only past driving history but also expected driving conditions during a future window.

[0076] Driver-specific characteristics such as driving habits, driving route, average driving speed, ambient temperature, and charging patterns (frequency of fast charging, ratio of slow charging) are also utilized as additional input values ​​to generate user-customized prediction results, thereby allowing for a more precise reflection of the correlation between the driver's usage environment and the battery degradation trend. The artificial intelligence analysis unit (122) enables tracking changes in battery SOH over time based on the prediction results and can calculate the time when battery replacement or maintenance is required within a certain period based on the predicted RUL information.

[0077] The predicted SOH, degradation trend index, and RUL information are generated as certificate data and provided to the Web or App (130) for drivers, and are also utilized for various subsequent services such as battery value assessment, carbon reduction calculation, and pre-maintenance recommendations during used car transactions. The artificial intelligence analysis unit (122) is designed to periodically retrain the model (Continuous Learning) to gradually improve prediction accuracy as driving data accumulates, and to maintain robust prediction performance even when abnormal data occurs.

[0078] As such, the artificial intelligence analysis unit (122) diagnoses the battery condition in real time based on electric vehicle operation data and predicts future degradation trends, thereby providing a customized battery management service for the user, enhancing safety, reducing maintenance costs, and optimizing battery life.

[0079] The vehicle inspection request unit (123) can generate a vehicle inspection request to the driver based on abnormal occurrence data received from the abnormal detection unit (114) and battery status information predicted from the artificial intelligence analysis unit (122), and notify the driver via Web or App (130).

[0080] In some embodiments, the vehicle inspection request unit (123) evaluates the impact of a received abnormal event on battery safety according to a predefined logic and immediately issues a vehicle inspection request if it is determined that the risk level is higher than a certain standard. The evaluation criteria may be set separately for various types of abnormalities, such as a sudden drop in battery pack voltage, intensification of voltage imbalance between cells, excessive charge / discharge current, and a sudden rise in battery temperature, and the urgency of the inspection request may be differentiated by assigning a Level of Risk to each abnormal event.

[0081] In some embodiments, the vehicle inspection request unit (123) may recommend an optimal inspection route and reservation schedule by considering the driver's current location, vehicle status, and repair shop availability information together when generating an inspection request. Specifically, the server searches for a list of repair shops located within a distance the driver can travel, and supports the selection of the most suitable repair shop by analyzing real-time traffic conditions, the availability of appointments at repair shops, and the availability of mechanics. The selected repair shop information is transmitted to the driver's Web or App (130) along with the inspection request, and the driver can immediately proceed with a reservation through the recommended repair shop.

[0082] The actual vehicle inspection request unit (123) includes detailed information such as items of abnormality, expected causes, and risk levels in the notification message when an inspection request is notified, so that the driver can intuitively recognize the severity of the problem, and the inspection request history is automatically recorded in the data storage unit (121) and used for future history management and service improvement. In addition, after an inspection request is issued, a message exchange function to support communication between the driver and the repair shop may be provided, and subsequent procedures such as whether the repair reservation is confirmed and notification of inspection completion may be managed through the server.

[0083] As such, the vehicle inspection request unit (123) prompts the driver to quickly and accurately inspect the vehicle based on an abnormality detected in real time while driving, and enables a rapid response in conjunction with a repair shop, thereby bringing about the effects of accident prevention, improved maintenance efficiency, and enhanced driver safety.

[0084] The data integrity management unit (124) is included in the server (120) and can perform integrity verification and prevention of tampering on all data stored and utilized within the server, such as operation-based continuous data, certificate data, data on anomalies, and inspection request history.

[0085] In some embodiments, the data integrity management unit (124) performs a hash operation on each data item recorded in the data storage unit (121) and records the generated hash value in a blockchain-based distributed ledger, thereby enabling verification of whether the data has been tampered with by comparing the original data with the hash value recorded in the blockchain when the data is subsequently retrieved. A high-reliability hash algorithm, such as SHA-256 (Secure Hash Algorithm 256-bit), is generally applied to generate the hash value, and through this process, the uniqueness and immutability of the data can be secured.

[0086] In some embodiments, the data integrity management unit (124) can collectively apply integrity management to various data types, such as actual vehicle inspection request history, battery status certificate, carbon reduction amount, and NFT issuance history, as well as continuous data based on operation, and separately create a transaction for each data item and record it on the blockchain. This transaction is composed of data identifier, creation time, hash value, and signature information, and through this structure, it supports multiple stakeholders, such as drivers, repair shops, and used car trading platforms, to independently verify the authenticity of the data. In particular, the used car trading platform can secure fair price calculation and transaction safety based on reliable information regarding the condition and residual value of the electric vehicle battery, and by utilizing real-time battery status data and authentication information with verified integrity, it can resolve information asymmetry issues that may occur during the transaction process, enhance buyer trust, and support the revitalization of the used electric vehicle trading market.

[0087] The data integrity management unit (124) provides an interface that allows the driver to request data integrity verification at any time desired via the driver's Web or App (130) after data recording is completed, and intuitively displays whether the data is intact based on the verification result. In addition, the blockchain network is operated through consensus among authorized nodes, and by adopting a permissioned blockchain architecture, data security and system operation efficiency can be secured simultaneously.

[0088] In some embodiments, the data integrity management unit (124) may also include a data change history (Audit Trail) function to prevent attempts to manipulate data in advance, and is designed so that when a request for data modification or deletion occurs, the request itself is recorded on the blockchain, allowing all manipulation records to be tracked completely and transparently. In this way, the data integrity management unit (124) technically guarantees the reliability of electric vehicle operation data and can secure the authenticity and reliability of data in various fields such as used car trading, maintenance record management, and carbon reduction certification.

[0089] The carbon reduction and NFT management unit (125) can analyze continuous data based on operation and driving history by driver to calculate the carbon reduction amount and the corresponding carbon reduction amount resulting from the operation of the electric vehicle, and can generate and manage NFTs (Non-Fungible Tokens) based on this.

[0090] In some embodiments, the carbon reduction and NFT management unit (125) calculates the carbon emissions reduced by operating an electric vehicle by comprehensively analyzing the vehicle's driving distance, charge / discharge history, electricity consumption, average driving habits, etc., and comparing this with the expected carbon emissions that could have occurred when operating an internal combustion engine vehicle under the same conditions. The carbon reduction amount can be calculated by applying a carbon emission coefficient stipulated by country or region, and the calculated carbon reduction amount is further converted into a monetary value by applying a price standard recognized in the carbon market.

[0091] In some embodiments, the carbon reduction and NFT management unit (125) issues the calculated carbon reduction amount and reduction amount in the form of a blockchain-based NFT along with metadata, and the generated NFT is recorded including carbon reduction history, creation date and time, driver information, etc., along with a unique identifier. The generated NFT may be transferred to the driver's personal wallet or provided in a form that can be traded in conjunction with an external carbon credit marketplace, and the transaction and movement history is permanently recorded on the blockchain so that it can be verified later.

[0092] In some embodiments, the carbon reduction and NFT management unit (125) is linked with a Web or App (130) for drivers to enable drivers to view their carbon reduction performance and owned NFTs in real time, and may also provide additional functions such as setting carbon reduction goals, comparing history, and monitoring transaction status. In addition, it may encourage drivers to drive eco-friendly by linking with additional services, such as providing incentives to drivers who achieve a certain amount of carbon reduction performance over a certain period or issuing certification badges.

[0093] In some embodiments, the carbon reduction and NFT management unit (125) is linked with the data integrity management unit (124) to ensure the integrity of the driving data and performs hash value verification for the driving history and NFT creation data, thereby technically ensuring driver reliability and transparency of the carbon reduction amount calculation process.

[0094] A Web or App (130) for a driver may be configured as a client interface that displays to the driver driving-based continuous data, battery status certificate data, anomaly occurrence notifications, and actual vehicle inspection request information received from the server (120), and supports the driver in checking this in real time.

[0095] The server (120) generates various information necessary for the driver based on the analysis results of the artificial intelligence analysis unit (122) of the data collected from the data collection device (110), and transmits the generated information to the driver's Web or App (130). The driver's Web or App (130) classifies and visualizes the received driving-based continuous data by time, section, and event, and intuitively provides the driver with battery pack voltage, current, temperature, charge / discharge amount, cell deviation, and details of rapid acceleration and high-speed charging event occurrences.

[0096] Additionally, the server (120) periodically predicts the battery State of Health (SOH), degradation trend index, and Estimated Remaining Useful Life (RUL), generates these in the form of a certificate, and transmits them to a Web or App (130) for drivers, allowing drivers to comprehensively check their battery status through the certificate. The certificate includes not only information at a single point in time but also a history based on flow data of the entire driving lifecycle, which can be used as objective data for evaluating residual value during used car transactions.

[0097] In some embodiments, when the anomaly detection unit (114) and the vehicle inspection request unit (123) detect an anomaly during vehicle operation or identify a situation requiring inspection, they generate notification and request data through the server (120) and notify the driver's Web or App (130). The driver can check detailed information such as the item of the anomaly, the time of occurrence, and the severity through the received notification, and upon receiving a vehicle inspection request, can view a list of optimal repair shops recommended by the server and available schedules, and proceed with the inspection reservation. The reservation process is also managed by the server (120), and the driver's Web or App (130) performs the role of displaying this information on the terminal and transmitting the driver's selection input to the server (120).

[0098] The Web or App (130) for drivers also receives vehicle maintenance schedule data from the server (120), displays maintenance reservation schedules, vehicle inspection cycles, and certificate renewal scheduled dates in a calendar format, and periodically displays reminder notifications when the schedules arrive. The notifications are sent based on schedule data generated in advance on the server, and through this, the driver can manage the timing of necessary inspections or certificate renewals without missing them.

[0099] The driver's Web or App (130) is configured to allow viewing of carbon reduction performance and NFT issuance data received from the carbon reduction and NFT management unit (125), and the driver can check their eco-friendly driving history through the received data and view the ownership history and transaction status of carbon reduction NFTs in real time. The carbon reduction amount and NFT data are also calculated and generated on the server and provided to the driver's Web or App (130), and the driver's terminal performs only the function of displaying and managing information without separate calculations.

[0100] Overall, the Web or App (130) for drivers focuses on the role of a client that receives and displays various driving and battery status information generated and managed by the server (120) to the driver terminal, and can function as a user interface platform of the present invention that dramatically improves driver convenience, such as vehicle status monitoring, response to abnormal occurrences, checking maintenance schedules, and viewing carbon reduction performance.

[0101] The vehicle maintenance shop (140) can provide actual vehicle inspection and repair services to respond to abnormal conditions of the battery and vehicle system that may occur during the operation of the electric vehicle, manages maintenance schedules linked to the driver according to actual vehicle inspection requests received from the server (120), and supports designated mechanics in inspecting the electric vehicle or performing repairs if necessary.

[0102] Specifically, the server (120) analyzes driving data and abnormal occurrence data through the abnormal detection unit (114) and the actual vehicle inspection request unit (123), identifies situations requiring inspection, generates an actual vehicle inspection request, and notifies the vehicle maintenance shop (140). Based on the inspection request information received from the server (120), the vehicle maintenance shop (140) manages the most efficient inspection reservation by considering the driver's current location, real-time traffic conditions, and vehicle status data together, and provides the driver with real-time information on available inspection time slots, mechanic assignment status, maintenance shop location, and estimated time required.

[0103] When an inspection reservation is confirmed, the vehicle repair shop (140) prepares for a designated mechanic to inspect the vehicle, and during the inspection process, a detailed inspection is performed on various items such as battery pack voltage imbalance, cell temperature abnormalities, charge / discharge circuit abnormalities, and high-voltage relay operation abnormalities. Unlike conventional technology, where the driver simply visits the repair shop to receive a basic diagnosis, in the present invention, the mechanic can perform an optimized inspection protocol based on prior analysis using pre-inspection data (history of abnormal occurrences, battery degradation estimates, etc.) transmitted from the server (120). As a result, the time required for inspection is shortened, and efficient inspection and maintenance can be performed focusing on major abnormal areas.

[0104] After the inspection is completed, the vehicle repair shop (140) transmits the inspection result data to the server (120) in real time, and the server (120) transmits the received results to the driver's Web or App (130) to provide the driver with an inspection completion notification and a detailed report. The inspection report includes items that have been inspected, items with defects found, whether repairs have been made, and recommended actions. Based on this, the driver can decide whether to perform additional maintenance or establish a mid-to-long-term vehicle management plan. In particular, parts replaced during the inspection process and repair details are recorded in a blockchain-based system through the data integrity management unit (124) to prevent tampering, and the vehicle repair shop (140) can ensure the transparency and reliability of the maintenance history by registering the generated inspection data in the form of a transaction on the blockchain network.

[0105] In addition, the vehicle repair shop (140) can perform the role of analyzing the performance of improved energy efficiency or additional carbon reduction effects achieved through repairs in conjunction with the carbon reduction and NFT management department (125) after the inspection is completed, and updating the performance results if necessary to reflect them in the driver's carbon reduction NFT information. Unlike conventional repair shop systems that were limited to simple vehicle repairs, this function can provide an expanded service that manages carbon reduction value and connects it to digital assets.

[0106] The vehicle maintenance shop (140) is a field service provider that supports the entire process of receiving a request for actual vehicle inspection from a driver via a server (120) and proceeding with the reservation and repair process. It clearly establishes a system of role division in which the server (120) performs data analysis and judgment, the driver manages information provision and reservations via Web or App (130), and the vehicle maintenance shop executes the actual inspection and repair. Through this structure, a rapid and systematic response to vehicle condition abnormalities becomes possible, and effects such as enhanced driver safety, optimized battery life, and reduced maintenance costs can be realized.

[0107] In addition, according to one embodiment of the present invention, a used car trading platform (not shown) can be utilized to resolve information asymmetry between sellers and buyers during the trading process of used electric vehicles, and to ensure the safety and transparency of transactions by providing reliable condition evaluation and value calculation results for electric vehicle batteries. Unlike existing systems that merely provide listing information, the present invention configures such a used car trading platform to collect and manage various forms of data in real time, such as continuous operation-based data, actual vehicle inspection history, battery condition certificates, carbon reduction amounts, and NFT issuance records.

[0108] In particular, the data integrity management unit (124) can create a separate transaction for each data item and record it on the blockchain, and this transaction can support independent verification of data authenticity by including data identifier, creation time, hash value, signature information, etc. The used car trading platform can utilize the integrity verification data recorded on the blockchain in this way to combine battery condition diagnosis results and driving history data for a specific electric vehicle and provide this to the buyer in a reliable form.

[0109] A used car trading platform can calculate vehicle prices based on precise evaluation results for detailed items such as remaining battery capacity, degradation status, and detection of abnormalities. Additionally, sellers can secure objective reliability regarding the value of their vehicles by providing a battery condition certificate according to the present invention through the platform. Furthermore, the used car trading platform systematizes data collection and verification procedures starting from the vehicle listing stage, thereby identifying battery abnormalities in advance prior to the transaction and preventing disputes that may arise after the transaction.

[0110] The structure of such a used car trading platform can be designed to go beyond simple static diagnosis based on BMS data and to integrally reflect the operation-based flow data collection and real-time abnormal pattern detection proposed in the present invention. Through this, the used car trading platform can provide condition evaluations based on consistent standards for electric vehicles of various manufacturers and with various battery specifications, and can flexibly respond to new electric vehicles and high-performance battery systems in the future. A used car trading platform equipped with a data integrity management unit (124) and a real-time data analysis function according to the present invention can fundamentally improve the reliability of the used electric vehicle market and support all stakeholders, such as sellers, buyers, repair shops, and certification bodies, in conducting safe and transparent transactions. Ultimately, a used car trading platform based on the present invention can optimize the value of the electric vehicle lifecycle and contribute to the creation of a sustainable electric vehicle ecosystem.

[0111] Although the embodiments have been described above with reference to limited examples and drawings, those skilled in the art can make various modifications and variations from the description above. For example, suitable results can be achieved even if the described techniques are performed in a different order than described, and / or the components of the described system, structure, device, circuit, etc. are combined or assembled in a form different from described, or replaced or substituted by other components or equivalents.

[0112] Therefore, other implementations, other embodiments, and equivalents to the claims also fall within the scope of the claims set forth below.

[0113] [Explanation of the symbol]

[0114] 10: System for diagnosing and managing electric vehicle battery status

[0115] 100: Electric vehicle 110: Data collection device

[0116] 111: Signal acquisition unit 112: Data processing unit

[0117] 113: Data transmission unit 114: Anomaly detection unit

[0118] 120: Server 121: Data storage unit

[0119] 122: AI Analysis Unit 123: Vehicle Inspection Request Unit

[0120] 124: Data Integrity Management Department 125: Carbon Reduction and NFT Management Department

[0121] 130: Web / App for Drivers 140: Vehicle Repair Shop

Claims

1. A system for performing electric vehicle battery status diagnosis and management, comprising a data collection device, a server, and a Web or App for a driver, The above data collection device is, A signal collection unit that receives a Controller Area Network (CAN) signal generated from the electric vehicle and collects data on battery pack voltage, battery pack current, battery pack temperature, charge / discharge amount, driving distance, and operating time in real time; A data processing unit that sorts data collected from the signal acquisition unit according to chronological order, removes outliers based on a preset threshold, and normalizes input values ​​to a range from 0 to 1 to generate operation-based continuous data (Flow data); A data transmission unit that transmits the above-mentioned operation-based continuous data to the above-mentioned server and driver's Web or App via a wireless communication network (Long-Term Evolution, LTE); An anomaly detection unit that monitors the collected data in real time to detect anomalies, transmits a notification to the driver's Web or App when an anomaly occurs, and simultaneously transmits the anomaly situation to a server; The above server includes a data storage unit that stores the above-mentioned operation-based continuous data; An artificial intelligence analysis unit that predicts the State of Health (SOH), degradation trend index, and Estimated Remaining Useful Life (RUL) of a battery by applying a machine learning model using continuous operation-based data stored in the above data storage unit as input characteristics; A vehicle inspection request unit that generates a vehicle inspection request based on the prediction result of the artificial intelligence analysis unit and abnormal occurrence data received from the abnormal detection unit, and notifies the driver's Web or App; A data integrity management unit that verifies the integrity of the above-mentioned operation and inspection data and stores and trades it based on blockchain; Carbon Reduction and NFT Management Department that converts electric vehicle driving records into carbon reduction amounts and monetary savings, and manages storage and trading of these as NFTs; A system that performs electric vehicle battery status diagnosis and management, including 2. In Paragraph 1, A system for performing electric vehicle battery condition diagnosis and management, characterized in that the signal collection unit further collects State of Charge (SOC), cumulative charge / discharge amount, voltage and cell temperature data for each battery cell from a Battery Management System (BMS) via the vehicle communication control network.

3. In Paragraph 2, A system for performing electric vehicle battery status diagnosis and management, characterized in that the signal collection unit calculates cell-to-cell variation based on collected voltage and temperature data for each battery cell, includes this in the driving-based continuous data, and transmits it to the server and the driver's Web or App.

4. In Paragraph 1, A system for performing electric vehicle battery status diagnosis and management, characterized in that the data processing unit samples the collected data at a time interval of less than 1 second, removes noise by applying a moving average filter, and accumulates and stores the entire collected data over the lifecycle.

5. In Paragraph 4, A system for diagnosing and managing the state of an electric vehicle battery, characterized in that the data processing unit identifies rapid acceleration, rapid deceleration, and high-speed charging events by applying a peak detection algorithm after moving average filtering, and stores the event occurrence time and duration as metadata on a server.

6. In Paragraph 2, A system for performing electric vehicle battery status diagnosis and management, characterized in that the above-mentioned abnormality detection unit detects an abnormality when one or more of the battery pack voltage, the battery pack temperature, or the voltage per cell exceeds or falls below a set threshold, and transmits an abnormality occurrence notification to the driver's Web or App and server.

7. In Paragraph 6, A system for performing electric vehicle battery status diagnosis and management, characterized in that the above-mentioned abnormality detection unit transmits the above-mentioned abnormality occurrence notification and simultaneously assigns a warning flag to the above-mentioned operation-based continuous data and stores it in a server.

8. In Paragraph 1, A system for diagnosing and managing the status of an electric vehicle battery, characterized in that the actual vehicle inspection request unit of the above-mentioned server, upon receiving the above-mentioned abnormal occurrence notification, communicates with a contracted maintenance company or support server according to a predefined logic to generate an actual vehicle inspection request, and transmits the request to the driver through the above-mentioned Web or App for the driver.

9. In Paragraph 8, The above-mentioned vehicle inspection request unit is a system for performing electric vehicle battery status diagnosis and management, characterized by recommending a repair shop and providing a reservation function by considering real-time traffic conditions, vehicle location information, and repair shop availability information.

10. In Paragraph 1, A system for performing electric vehicle battery status diagnosis and management, characterized by the above-mentioned data integrity management unit recording the above-mentioned operation-based continuous data and certificate data in a blockchain-based distributed ledger to prevent tampering and forgery, and verifying in real time whether the data has been changed.

11. In Paragraph 10, A system for performing electric vehicle battery status diagnosis and management, characterized in that the data integrity management unit generates a transaction hash value for the operation-based continuous data recorded on the blockchain network and automatically verifies whether the data has been tampered with when viewed by a driver, a repair shop, or a used car trading platform.

12. In Paragraph 1, A system for diagnosing and managing the condition of an electric vehicle battery, characterized in that the carbon reduction and NFT management unit analyzes the operation-based continuous data to calculate the amount of carbon reduction resulting from the operation of the electric vehicle, calculates the amount of carbon reduction based on the amount of carbon reduction, and then generates the amount of carbon reduction and the amount of carbon reduction in the form of an NFT (Non-Fungible Token) and registers it on a blockchain.

13. In Paragraph 12, A system for performing electric vehicle battery status diagnosis and management, characterized in that the above-mentioned carbon reduction and NFT management unit additionally includes a function that supports the transfer of generated NFTs to an external carbon emission rights exchange or a personal wallet.

14. In Paragraph 1, The above-mentioned artificial intelligence analysis unit is characterized by using past driving data and predicted data during a future window as input to train a model to maximize the cumulative signal-to-noise ratio (SNR) gain, and predicting battery degradation trends by considering driving habits, driving routes, and environmental conditions, thereby performing electric vehicle battery condition diagnosis and management.

15. In Paragraph 14, A system for performing electric vehicle battery condition diagnosis and management, characterized in that the above-mentioned artificial intelligence analysis unit provides battery replacement timing, maintenance recommendation timing, and driving habit improvement guides via a driver's Web or App based on the above-mentioned degradation trend prediction results.

16. In Paragraph 1, A system for performing electric vehicle battery status diagnosis and management, characterized in that the above data storage unit accumulates, stores, and manages flow data collected over the entire vehicle lifecycle of the above-described operation-based continuous data.

17. In Paragraph 16, A system for performing electric vehicle battery condition diagnosis and management, characterized in that the data storage unit classifies rapid acceleration, rapid deceleration, high-speed charging, extreme temperature conditions, and other abnormal events included in the lifecycle flow data by driving section to generate a statistical index.

18. In Paragraph 17, A system for diagnosing and managing the status of an electric vehicle battery, characterized in that the above-mentioned driver Web or App is configured to enable integrated viewing of predicted future battery life changes based on the above-mentioned lifecycle flow data, accumulated carbon reductions, maintenance history, and certificate history, in addition to providing battery status.

19. In Paragraph 1, The above-mentioned vehicle inspection request unit is a system for diagnosing and managing the condition of an electric vehicle battery, characterized by the fact that after the server receives the above-mentioned abnormality information, it links with a nearby repair shop to propose a repair technician assignment and on-site inspection schedule to the driver within a set time.

20. In Paragraph 19, A system for performing electric vehicle battery status diagnosis and management, characterized by the above-mentioned vehicle inspection request unit providing the driver with the maintenance progress status in real time via a driver's Web or App after a mechanic has been assigned.

21. In Paragraph 1, A system for diagnosing and managing the condition of an electric vehicle battery, characterized in that the above-mentioned Web or App for drivers, in addition to anomaly notifications, manages the driver's pre-registered maintenance reservation schedule, vehicle inspection cycle, certificate renewal timing, etc., to periodically provide reminder notifications to the driver.

22. In Paragraph 1, The above system is a system for performing electric vehicle battery condition diagnosis and management, characterized by providing continuous condition evaluation and driver-customized lifecycle management services based on Flow data collected throughout the entire vehicle lifecycle.

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