Battery diagnostic system and method

Abstract

According to embodiments disclosed herein, a battery diagnostic system may include: an index calculation unit that constructs a database of battery data related to a battery and calculates diagnostic criteria for diagnosing a battery and diagnostic indices applied to the diagnostic criteria based on the battery data; and a diagnostic device that acquires diagnostic data related to a target battery installed in a vehicle, calculates the value of the diagnostic indices for the target battery based on the diagnostic data, and diagnoses the target battery based on the value of the diagnostic indices and the diagnostic criteria.

Description

Technical Field

[0001] This application claims the benefit of priority based on Korean Patent Application No. 10-2024-0039709 filed on March 22, 2024 and Korean Patent Application No. 10-2023-0066910 filed on May 24, 2023, and all the contents disclosed in the documents of the patent applications are incorporated herein by reference in their entirety. The embodiments disclosed in this document relate to a battery diagnosis system and method.

Background Art

[0002] In recent years, research and development on secondary batteries have been actively conducted. Here, a secondary battery is a battery capable of charging and discharging, and includes both conventional Ni / Cd batteries, Ni / MH batteries, etc. and recent lithium-ion batteries in the broad sense. Among secondary batteries, lithium-ion batteries have the advantage of having a much higher energy density compared to conventional Ni / Cd batteries, Ni / MH batteries, etc. In addition, since lithium-ion batteries can be manufactured in a small size and light weight, they are used as a power source for mobile devices, and in recent years, their usage range has been extended to the power source of electric vehicles and they have attracted attention as a next-generation energy storage medium.

[0003] Also, a secondary battery can generally be used as a battery pack including a battery module in which a plurality of battery cells are connected in series and / or in parallel. And a secondary battery can be used as a battery rack including a plurality of battery modules and a rack frame for housing such battery modules.

[0004] Such battery cells, battery modules, battery packs, or battery racks can be used in a variety of devices. For example, batteries can be used not only in mobile devices such as mobile phones, laptop computers, smartphones, and smartpads, but also in electric vehicles (EVs, HEVs, PHEVs) and large-capacity energy storage systems (ESS). Because such batteries are rechargeable and used after repeated charging, periodic diagnostics are necessary. [Overview of the Initiative] [Problems that the invention aims to solve]

[0005] On the other hand, the battery diagnostic process often requires additional steps, such as charging and discharging for diagnostic purposes, making it difficult to diagnose batteries in a short period of time. Therefore, there is a need for a method to quickly diagnose batteries, especially for managing multiple batteries and for user convenience. One objective of the embodiments disclosed herein is to provide a battery diagnostic system and method capable of short-term battery diagnosis.

[0006] The technical problems of the embodiments disclosed in this document are not limited to those mentioned above, and other technical problems not mentioned can be clearly understood by those skilled in the art from the following description. [Means for solving the problem]

[0007] According to embodiments disclosed herein, a battery diagnostic system may include: an index calculation unit that constructs a database of battery data related to a battery and calculates diagnostic criteria for diagnosing a battery and diagnostic indices applied to the diagnostic criteria based on the battery data; and a diagnostic device that acquires diagnostic data related to a target battery installed in a vehicle, calculates the value of the diagnostic indices for the target battery based on the diagnostic data, and diagnoses the target battery based on the value of the diagnostic indices and the diagnostic criteria.

[0008] According to embodiments disclosed herein, a battery diagnostic method may include the steps of: building a database of battery data related to a battery; calculating diagnostic criteria for diagnosing a battery and diagnostic indices applied to the diagnostic criteria based on the battery data; acquiring diagnostic data related to a target battery installed in a vehicle; calculating the value of the diagnostic indices for the target battery based on the diagnostic data; and diagnosing the target battery based on the value of the diagnostic indices and the diagnostic criteria. [Effects of the Invention]

[0009] The battery diagnostic system and method according to the embodiments disclosed herein enable short-term diagnosis of batteries. In addition, this document can provide various effects that can be understood directly or indirectly. [Brief explanation of the drawing]

[0010] [Figure 1] This figure shows the structure of a battery diagnostic system according to one embodiment disclosed in this document. [Figure 2] This figure shows an example of calculating diagnostic indicators and diagnostic criteria according to one embodiment disclosed in this document. [Figure 3a] This figure shows an example of determining the replacement history of a target battery according to one embodiment disclosed in this document. [Figure 3b] This figure shows an example of determining the replacement history of a target battery according to one embodiment disclosed in this document. [Figure 4] This figure shows an example of calculating the mileage after replacement according to one embodiment disclosed in this document and correcting the degree of deterioration. [Figure 5a] This figure shows an example of calculating diagnostic criteria for abnormality diagnosis according to one embodiment disclosed in this document. [Figure 5b] This figure shows an example of calculating diagnostic criteria for abnormality diagnosis according to one embodiment disclosed in this document. [Figure 6]This is a flowchart illustrating a battery diagnostic method according to one embodiment disclosed in this document. [Figure 7] This is a flowchart illustrating an example of the process for calculating diagnostic criteria according to one embodiment disclosed in this document. [Figure 8] This is a flowchart illustrating an example of the process for correcting the degree of degradation according to one embodiment disclosed in this document. [Figure 9] This is a block diagram showing the hardware configuration of a computing system for performing a battery diagnostic method according to one embodiment disclosed in this document. [Modes for carrying out the invention]

[0011] Various embodiments of the present invention are described below with reference to the accompanying drawings. However, this should be understood not as limiting the present invention to any particular embodiment, but rather as including various modifications, equivalents, and / or alternatives to the embodiments of the present invention.

[0012] In this text, the singular form of a noun corresponding to an item may include one or more of the item unless the context clearly indicates otherwise. In this text, each phrase 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” may include any one of the items listed together in the phrase, or any possible combination thereof. Terms such as “first,” “second,” “first,” or “second” may be used merely to distinguish one component from other components and not to limit the component in any other respect (e.g., importance or order). When one (e.g., the first) component is referred to as being "connected" or "linked" to another (e.g., the second) component, with or without the terms "functionally" or "communically," this means that the first component may be connected to the other component directly (e.g., by wire), wirelessly, or via the third component.

[0013] Each component (e.g., module or program) described herein may include one or more individuals. According to various embodiments, one or more components or operations of the component 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 a single component. In this case, the integrated component may perform one or more functions of each of the multiple components identical or similar to those performed by the components of the multiple components before the integration. According to various embodiments, operations performed by modules, programs, or other components may be performed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be performed in a different order, omitted, or one or more other operations may be added.

[0014] As used herein, the term "module" or "... section" may include units implemented in hardware, software, or firmware, and may be used interchangeably with terms such as, for example, logic, logic block, component, or circuit. A module may be an integrally configured component, or may be the smallest unit or a part of the above components that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an ASIC (application-specific integrated circuit).

[0015] Various embodiments of this document may be implemented as software (e.g., a program or an application) including one or more instruction words stored in a machine-readable storage medium (e.g., a memory). For example, a processor of a device may call at least one instruction from the one or more instruction words stored in the storage medium and execute it. This enables the device to be operated to perform at least one function according to the at least one called instruction word. The one or more instruction words may include code generated by a compiler or code executable by an interpreter. The machine-readable storage medium may be provided in the form of a non-transitory storage medium. Here, "non-transitory" only means that the storage medium is a tangible device and does not include a signal (e.g., an electromagnetic wave), and this term does not distinguish between cases where data is stored semi-permanently and temporarily in the storage medium.

[0016] FIG. 1 is a diagram showing the structure of a battery diagnosis system according to an embodiment disclosed in this document. Referring to FIG. 1, the battery diagnosis system 100 may include an index calculation unit 110 and a diagnosis device 120.

[0017] The battery diagnosis system 100 can acquire diagnostic data related to a battery to be diagnosed mounted on the vehicle 10, and perform diagnosis of the target battery using diagnostic criteria and diagnostic indicators calculated from the cumulative battery data stored in the database 111.

[0018] For this purpose, the battery diagnosis system 100 can acquire and accumulate battery data related to various batteries to construct a database 111 related to the battery data, and analyze a huge amount of battery data stored in the database 111 to calculate diagnostic indicators and diagnostic criteria for battery diagnosis. For example, the diagnostic indicators and diagnostic criteria can be calculated by statistical analysis of the battery data in the database 111.

[0019] Since the battery diagnosis system 100 analyzes a huge amount of data to calculate diagnostic indicators and diagnostic criteria, it can calculate diagnostic indicators and diagnostic criteria that are general and generally applicable to any target battery.

[0020] Generally, in order to diagnose the state of a battery such as the degree of deterioration of the battery, an additional process such as applying a current to perform actual charge and discharge is required, and therefore, it has been necessary for a long time to diagnose the battery. In contrast, the battery diagnosis system 100 analyzes a huge amount of data to calculate diagnostic indicators and diagnostic criteria, and when diagnosing an actual target battery, it can calculate the value of the diagnostic indicator from the data acquired in a short period and perform diagnosis of the battery. Thereby, the battery diagnosis system 100 can enable short-term diagnosis of the battery.

[0021] The index calculation unit 110 and the diagnostic device 120 can be connected by wire and / or wireless. In one embodiment, the connection between the index calculation unit 110 and the diagnostic device 120 may be a communication connection via a wired and / or wireless network. For example, the wired network may be based on LAN (local area network) communication or power line communication. In one embodiment, the wireless network may be based on a local area network (e.g., Bluetooth®, WiFi (wireless fidelity), or IrDA (infrared data association)) or a wide area network (cellular network, 4G network, 5G network).

[0022] In other embodiments, the connection between the index calculation unit 110 and the diagnostic device 120 may be via a communication method between devices (for example, a bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)).

[0023] The index calculation unit 110 can be implemented in various computing devices such as servers, workstations, clouds, data drives, and data stations.

[0024] The indicator calculation unit 110 may include a communication circuit for acquiring battery data, a memory including a database 111 for storing, classifying, and managing the acquired battery data, and a processor for analyzing the battery data and calculating diagnostic indicators and diagnostic criteria.

[0025] For example, the communication circuit of the indicator calculation unit 110 can establish a wired communication channel and / or a wireless communication channel with the diagnostic device 120, and can send and receive data with the diagnostic device 120 via the established communication channel. Similarly, the communication circuit of the indicator calculation unit 110 can establish a communication channel with various external devices that can acquire battery data (e.g., battery BMS, vehicle BMS, charger, charger / discharger, etc.), and can acquire battery data via the communication channel.

[0026] The index calculation unit 110 can construct a database 111 containing battery data related to the battery. The index calculation unit 110 can acquire battery data from various configurations such as a Battery Management System (BMS) installed in each battery, a vehicle BMS, a charger, or a charger / discharger.

[0027] The indicator calculation unit 110 can store the acquired battery data and build a database 111. The database 111 can be continuously updated, and for example, diagnostic data acquired when diagnosing a target battery can be acquired from the diagnostic device 120 and stored in the database 111.

[0028] The index calculation unit 110 can acquire various data related to the battery as battery data. For example, battery data related to the battery may include data related to the state of the battery, data related to the state of the electronic device in which the battery is installed, etc. As an example, the index calculation unit 110 may include battery voltage, current, resistance, SOC (state of charge), SOH (state of health), temperature, etc. as data related to the state of the battery.

[0029] The indicator calculation unit 110 can calculate diagnostic indicators and diagnostic criteria for battery diagnosis based on battery data. The indicator calculation unit 110 can collect battery data and analyze it to calculate statistical diagnostic indicators and diagnostic criteria. For example, the indicator calculation unit 110 can construct big data related to battery data and calculate diagnostic indicators and diagnostic criteria for a big database.

[0030] The index calculation unit 110 can calculate an index that can be used for diagnosing the battery of the diagnostic device 120 in the process of analyzing battery data and calculating diagnostic criteria. The diagnostic criteria may include, for example, a degradation degree criterion for diagnosing the degree of battery degradation, or an abnormality criterion for diagnosing the presence or absence of a battery abnormality.

[0031] In one embodiment, the index calculation unit 110 can calculate diagnostic indices and diagnostic criteria by analyzing the correlations between various battery-related factors included in the battery data. For example, in order to calculate degradation criteria, the index calculation unit 110 can analyze the correlation between factors expected to be related to degradation or already known to be related to degradation (e.g., cumulative mileage) and degradation.

[0032] According to one embodiment, the index calculation unit 110 can analyze the correlation between cumulative mileage and degradation level and the correlation between charging habits and degradation level, and calculate a degradation level standard and a diagnostic index applicable to the degradation level standard. In one embodiment, the charging habits may include the fast charging ratio of the battery.

[0033] For example, the index calculation unit 110 can statistically analyze the correlation between cumulative mileage and degree of deterioration and derive a correlation graph showing the degree of deterioration based on cumulative mileage. If a correlation between cumulative mileage and degree of deterioration is derived, the index calculation unit 110 can calculate the cumulative mileage as a diagnostic index and calculate the correlation graph as a diagnostic criterion for diagnosis. Similarly, the index calculation unit 110 can analyze the correlation between charging habits and the degree of deterioration and reflect it in a correlation graph showing the degree of deterioration based on cumulative mileage.

[0034] In one embodiment, the index calculation unit 110 calculates diagnostic criteria such that the cumulative mileage and the degree of deterioration are basically in a negative correlation. However, even with the same cumulative mileage, the diagnostic criteria can be set so that different degrees of deterioration are observed depending on the charging habits. For example, the degree of deterioration criteria can be calculated so that the degree of deterioration decreases as the cumulative mileage increases, and even with the same cumulative mileage, the degree of deterioration decreases as the rapid charging ratio increases.

[0035] According to the embodiment, the index calculation unit 110 can calculate diagnostic indicators and diagnostic criteria according to the type of vehicle. For example, the index calculation unit 110 can classify battery data according to the type of vehicle from which it was acquired, and can analyze the classified battery data to calculate diagnostic indicators and diagnostic criteria according to the type of vehicle.

[0036] Since the correlation with the diagnostic purpose (e.g., degree of degradation) may differ depending on the type of vehicle in which the battery is installed, even if the same index is used, the index calculation unit 110 can calculate diagnostic indexes and diagnostic criteria according to the type of vehicle from which the battery data is acquired.

[0037] According to the embodiment, the index calculation unit 110 can estimate diagnostic criteria for other vehicles based on the charging habits and storage voltage of each vehicle. Here, the charging habits can be calculated based on the ratio of cumulative power to cumulative current as described above, and the storage voltage can mean the voltage applied when the battery is idle, and can be calculated based on the ratio of cumulative discharge power to cumulative discharge current.

[0038] As mentioned above, when calculating the degradation criteria, if a correlation between cumulative current, cumulative power, and rapid charging ratio and the degradation level is derived, the index calculation unit 110 can compare vehicle-specific data to derive a new index that can be used for degradation diagnosis. For example, the index calculation unit 110 can determine whether or not the storage voltage can be used as a diagnostic index for degradation diagnosis.

[0039] In this way, the index calculation unit 110 can analyze the correlation between each of these parameters and the degree of battery degradation according to the vehicle's rapid charging ratio and storage voltage, and using the derived correlation trend, it can calculate diagnostic indexes and diagnostic criteria for diagnosing the degree of degradation even for vehicles or batteries for which no battery data history exists.

[0040] According to the embodiment, the index calculation unit 110 can calculate diagnostic indicators and diagnostic criteria for diagnosing battery abnormalities based on battery data. According to the embodiment, the diagnostic criteria may include, but are not limited to, criteria for at least one of voltage deviation, temperature deviation, and insulation resistance.

[0041] According to the embodiment, the index calculation unit 110 can analyze battery data and derive the charge rate and open-circuit voltage as diagnostic indicators for voltage deviation diagnosis. The index calculation unit 110 can derive the relationship between the charge rate and open-circuit voltage included in the battery data and calculate diagnostic criteria for abnormality diagnosis.

[0042] According to the embodiment, the index calculation unit 110 can calculate a graph showing the relationship between the charge level and the open-circuit voltage. The index calculation unit 110 can analyze data related to the charge level and data related to the open-circuit voltage and calculate a graph showing the correlation between them.

[0043] Subsequently, the index calculation unit 110 can shift the graph at a pre-set interval. Here, shifting the graph at a pre-set interval may mean moving the graph along at least one axis. For example, the index calculation unit 110 can move the graph along the axis representing the charge level in order to analyze the voltage deviation.

[0044] According to the embodiment, the index calculation unit 110 can calculate a diagnostic criterion for voltage deviation due to charge level based on the difference before and after shifting the graph. The index calculation unit 110 can calculate the voltage deviation due to charge level by shifting the graph relating to the charge level and open-circuit voltage and calculating the difference before and after the shift.

[0045] According to the embodiment, the index calculation unit 110 can set a diagnostic criterion using the voltage deviation value calculated based on the charge rate in this manner as a threshold. For example, if the voltage deviation with respect to charge rate a is calculated as b, b may be a threshold for diagnosing an abnormal voltage deviation in the battery.

[0046] The example of calculating the diagnostic criteria mentioned above is for diagnosing voltage deviation abnormalities, and diagnostic criteria for diagnosing temperature deviation abnormalities and insulation resistance abnormalities can be calculated using the same method.

[0047] For example, when the index calculation unit 110 calculates diagnostic criteria for diagnosing temperature deviation abnormalities, it can analyze the correlation between at least two factors related to the temperature deviation and derive a graph showing these correlations. Subsequently, the diagnostic criteria for diagnosing temperature deviations can be calculated using the calculated graph.

[0048] The diagnostic device 120 can be implemented using various computing devices such as servers, workstations, clouds, data drives, and data stations.

[0049] The diagnostic device 120 may include a communication circuit for acquiring diagnostic data, a memory for storing the acquired diagnostic data, and a processor for analyzing the diagnostic data and calculating diagnostic results. The diagnostic device 120 may further include other components, and at least one component may be omitted.

[0050] The diagnostic device 120 can acquire diagnostic data of the battery to be diagnosed and diagnose the battery. The diagnostic device 120 can be implemented physically separate from the index calculation unit 110. For example, the diagnostic device 120 and the index calculation unit 110 can be implemented on separate servers that are physically separated and connected by a network.

[0051] In some cases, the diagnostic device 120 can be implemented with the same physical configuration as the index calculation unit 110. For example, the diagnostic device 120 and the index calculation unit 110 may be components of the same server.

[0052] The diagnostic device 120 can acquire diagnostic data of a target battery installed in a vehicle. The target battery may be any battery that is the subject of the diagnosis. The diagnostic device 120 can acquire diagnostic data without going through any additional diagnostic processes, such as separating the target battery from the vehicle or performing another charge / discharge on the target battery. For example, the diagnostic device 120 can acquire diagnostic data in a short time while the target battery is operating.

[0053] According to the embodiment, the diagnostic device 120 can acquire diagnostic data from an OBD (On-Board Diagnostic) device 11 installed in the vehicle 10. The OBD device 11 is installed in the vehicle 10 and can acquire vehicle data and battery data as diagnostic data from configurations related to the vehicle 10 and configurations such as the battery management system of the target battery. For example, the diagnostic data may include the cumulative mileage of the vehicle, the cumulative current of the target battery, and the cumulative power. As an example, the cumulative current and cumulative power of the target battery may be recorded in the battery management system of the target battery. The OBD device 11 can acquire battery-related data recorded in the battery storage system of the target battery as diagnostic data.

[0054] The OBD device 11 can transmit diagnostic data to the diagnostic device 120. For example, a communication network can be formed between the OBD device 11 and the diagnostic device 120, and the diagnostic device 120 can receive diagnostic data from the OBD device 11.

[0055] In one embodiment, the OBD device 11 can acquire data about the vehicle and / or battery as diagnostic data in a short time. For example, the OBD device 11 can acquire diagnostic data in a short time of less than one minute.

[0056] In this case, since the diagnostic data is acquired over a short period, it does not include data that can be obtained through other charge / discharge processes or other processes. In other words, the diagnostic data may include information that can be obtained simply from data stored in the battery management system or through short-term monitoring. For example, the diagnostic data does not include the State of Health (SOH) information of the target battery.

[0057] According to the embodiment, the diagnostic device 120 can calculate the value of the diagnostic index of the target battery based on the diagnostic data. The diagnostic device 120 can receive the diagnostic index and diagnostic criteria from the index calculation unit 110 and can calculate the value of the diagnostic index from the diagnostic data.

[0058] According to the embodiment, the diagnostic device 120 can diagnose the degree of degradation of the target battery by using the battery's usage characteristics and the vehicle's cumulative mileage as diagnostic indicators. According to one embodiment, the diagnostic device 120 can calculate usage characteristics for the target battery based on the diagnostic data. Here, usage characteristics may refer to characteristics related to the cumulative use of the target battery, and may include, for example, charging habits, usage patterns, and replacement history.

[0059] According to the embodiment, the diagnostic device 120 can calculate usage characteristics based on the cumulative power and cumulative current of the target battery included in the diagnostic data. Cumulative power refers to the charge / discharge power accumulated during the charge / discharge process of the target battery, and cumulative current may refer to the charge / discharge current accumulated during the charge / discharge process of the target battery.

[0060] According to the embodiment, the usage characteristics may include the charging habits of the target battery. Since battery degradation may be accelerated depending on the battery's charging habits, the diagnostic device 120 can calculate the charging habits based on the usage characteristics of the target battery.

[0061] According to the embodiment, the charging habits of the target battery include a fast-charging ratio, and the diagnostic device 120 can calculate the fast-charging ratio based on the ratio of cumulative power to cumulative current (= cumulative power / cumulative current). A high ratio of cumulative power to cumulative current means that the average operating voltage of the battery is high, and a high average operating voltage may mean that the fast-charging ratio is high.

[0062] If the average operating voltage of the target battery is high, the battery's charging current is high, or the battery's SOC usage area is high, which can accelerate the battery's degradation. Therefore, the diagnostic device 120 can calculate the rapid charging ratio from the ratio of cumulative power to cumulative current.

[0063] In other embodiments, cumulative power may include cumulative charging power and cumulative discharging power, and cumulative current may include cumulative charging current and cumulative discharging current. In this case, the diagnostic device 120 can calculate the rapid charging ratio based on the difference between the ratio of cumulative charging power to cumulative charging current (= cumulative charging power / cumulative charging current) and the ratio of cumulative discharging power to cumulative discharging current (= cumulative discharging power / cumulative discharging current). This is due to the fact that statistically, the larger the value of the battery data, the greater the rapid charging ratio.

[0064] According to the embodiment, the diagnostic device 120 determines whether the target battery has been replaced, calculates the mileage since replacement, corrects the degree of degradation of the target battery, and enables a more accurate diagnosis.

[0065] According to the embodiment, the diagnostic device 120 can determine whether or not the target battery has a replacement history based on at least one of the cumulative current and cumulative mileage. In other words, the diagnostic device 120 can calculate whether or not the target battery has a replacement history as a battery usage characteristic.

[0066] If the target battery has a replacement history, the relationship between the target battery's cumulative mileage and cumulative current and / or cumulative power may differ, which could lead to an inaccurate deterioration diagnosis. Therefore, the diagnostic device 120 can determine whether or not the target battery has been replaced.

[0067] According to the embodiment, the diagnostic device 120 can determine whether or not the target battery has a replacement history based on the change in cumulative current over time. Since the cumulative current of a battery increases proportionally with its operating time, the diagnostic device 120 can determine whether or not the target battery has a replacement history from the change in cumulative current over time. For example, the cumulative current over time may be stored in the battery management system of the target battery, and the diagnostic device 120 can acquire the data stored in the battery management system as diagnostic data and determine whether or not the target battery has a replacement history. In one embodiment, the diagnostic device 120 can determine that the target battery has a history of replacement if the accumulated current decreases sharply at a specific point in time.

[0068] Since the cumulative current increases over time unless the battery is replaced, if the cumulative current decreases at a particular point in time, the diagnostic device 120 can determine that the battery has been replaced.

[0069] According to the embodiment, the diagnostic device 120 can determine whether or not the target battery has a replacement history based on the ratio of cumulative mileage to cumulative current (= cumulative mileage / cumulative current). For example, the diagnostic device 120 can determine whether or not the target battery has a replacement history by comparing the ratio of cumulative mileage to cumulative current with a specific value, or by analyzing a graph derived from the cumulative mileage and cumulative current values.

[0070] In one embodiment, the diagnostic device 120 can determine that the target battery has a replacement history if the ratio of cumulative mileage to cumulative current exceeds a threshold, or if the graph showing the relationship between cumulative mileage and cumulative current does not converge to the origin when extended.

[0071] When the ratio of cumulative mileage to cumulative current exceeds a threshold, it means that the cumulative mileage is far greater than the cumulative current, and therefore it can be determined that there is a history of replacement.

[0072] The diagnostic device 120 can acquire data on cumulative current and cumulative mileage as diagnostic data. For example, the battery management system of the target battery may store time-series data on cumulative current and cumulative mileage, and the diagnostic device 120 can acquire this data. The diagnostic device 120 can analyze the distribution of cumulative current and cumulative mileage and derive a graph showing the relationship between cumulative mileage and cumulative current.

[0073] If there is no history of battery replacement, when the battery is first installed in the vehicle, both the cumulative current and cumulative mileage are 0. Therefore, when the graph showing the relationship between cumulative mileage and cumulative current is extended, it will converge to the origin. Accordingly, the diagnostic device 120 can determine that the battery in question has a history of replacement if the extended graph does not converge to the origin.

[0074] According to the embodiment, if the diagnostic device 120 determines that the target battery has a replacement history, it can calculate the mileage traveled since the time of the target battery's replacement. For example, the diagnostic device 120 can obtain the cumulative current and cumulative mileage of the target battery from the diagnostic data and represent them on a two-dimensional plane with each as an axis. In this case, if it is determined that the battery has a replacement history, the mileage traveled after the replacement can be calculated as the difference between the y-axis intercept and the y-coordinate value when the slope is extended.

[0075] According to the embodiment, the diagnostic device 120 can correct the degree of deterioration based on the mileage traveled since the time of replacement. This can be understood as recalculating the degree of deterioration by comparing the mileage traveled after replacement and the usage characteristics (more specifically, the rapid charging ratio) with the diagnostic criteria.

[0076] According to the embodiment, the diagnostic device 120 can diagnose the target battery based on the value of the diagnostic index and the diagnostic criteria. The diagnostic device 120 can calculate the value of the diagnostic index from the diagnostic data and diagnose the target battery in a short period of time using the diagnostic criteria.

[0077] According to the embodiment, the diagnostic device 120 can diagnose the degree of battery degradation by comparing usage characteristics, the vehicle's cumulative mileage, and diagnostic criteria. In this case, the vehicle's cumulative mileage can be included in the diagnostic data. For example, the vehicle's cumulative mileage can be recorded in the battery management system, and the diagnostic device 120 can acquire the vehicle's cumulative mileage.

[0078] For example, as mentioned above, the index calculation unit 110 can analyze the relationship between cumulative mileage, usage characteristics, and degree of deterioration to set diagnostic criteria, and the diagnostic device 120 can diagnose the degree of deterioration of the target battery using the set diagnostic criteria.

[0079] For example, the index calculation unit 110 can calculate diagnostic criteria in the form of a function of the diagnostic index, and the diagnostic device 120 can input the value of the diagnostic index into the diagnostic function and output the degree of deterioration.

[0080] According to the embodiment, the diagnostic device 120 can diagnose abnormalities in a battery using abnormality diagnosis criteria. For example, the diagnostic device 120 can diagnose abnormal temperature deviations in a target battery using criteria for temperature deviation.

[0081] For example, diagnostic criteria for each abnormality can be defined by setting a threshold for each abnormality diagnosis, and the diagnostic device 120 can perform an abnormality diagnosis of the target battery by comparing the value of the diagnostic index calculated from the diagnostic data with the threshold.

[0082] According to the embodiment, the diagnostic device 120 can transmit diagnostic results for the target battery to an external device. For example, the diagnostic device 120 can transmit the diagnostic results to an OBD device 11 that acquires diagnostic data. In this case, the OBD device 11 may include components that can display the diagnostic results. For example, the OBD device 11 may include an interface for displaying the diagnostic results.

[0083] As another example, the diagnostic device 120 can transmit diagnostic results to a device that manages the location where vehicles equipped with the target battery are inspected, or to a user terminal of a user who manages vehicles equipped with the target battery.

[0084] Figure 2 shows an example of calculating diagnostic indicators and diagnostic criteria according to one embodiment disclosed in this document. Referring to Figure 2, Graph 210 illustrates the correlation between the rapid charging ratio and the ratio of cumulative power to cumulative current, and Graph 220 illustrates the diagnostic criteria calculated considering the correlation.

[0085] First, referring to 210 in Figure 2, the relationship between the ratio of cumulative power to cumulative current and the average charging power can be statistically analyzed based on the battery data stored in the database 111. Here, a high average charging power means that the battery is charged quickly, which can mean that the rapid charging ratio of the battery is high. Therefore, it can be confirmed that there is a correlation between a larger ratio of cumulative power to cumulative current and a charging habit with a high rapid charging ratio. In this case, since a higher rapid charging ratio can lead to a lower degree of battery degradation, the index calculation unit 110 can calculate the rapid charging ratio (or cumulative power and cumulative current) as a diagnostic index.

[0086] The index calculation unit 110 can calculate diagnostic criteria for battery degradation diagnosis by considering the correlation between the ratio of cumulative power to cumulative current and charging habits. For example, the index calculation unit 110 can statistically analyze the correlation between cumulative mileage and degradation from battery data stored in the database and calculate a reference graph showing the degree of battery degradation based on cumulative mileage. Subsequently, the index calculation unit 110 can set diagnostic criteria so that the reference graph changes according to the rapid charging ratio by considering the correlation between the ratio of cumulative power to cumulative current and the rapid charging ratio.

[0087] For example, as shown in Figure 2, 220, the index calculation unit 110 can analyze the degree of deterioration based on cumulative mileage and derive minimum deterioration graph L1 and maximum deterioration graph L2 as diagnostic criterion graphs. Furthermore, the index calculation unit 110 can make the degree of deterioration fluctuate between L1 and L2 depending on the rapid charging ratio.

[0088] For example, the degradation level corresponding to location P1 with a low fast-charging ratio can be represented as P3, which is close to the minimum degradation graph L1, while the degradation level corresponding to location P2 with a high fast-charging ratio can be represented as P4, which is close to the maximum degradation graph L2.

[0089] Figures 3a and 3b show an example of determining the replacement history of a target battery according to one embodiment disclosed in this document. First, referring to Figure 3a, graphs 310 and 320 are shown, illustrating examples of changes in battery data when a battery is replaced.

[0090] First, referring to 310 in Figure 3a, an illustrative graph of the cumulative discharge current over time is shown. The cumulative discharge current over time can be obtained, for example, from the battery's battery management system. In 310 in Figure 3a, L3 shows the cumulative discharge current of the battery before replacement, and L4 shows the cumulative discharge current of the battery after replacement.

[0091] Comparing L3 and L4, it can be confirmed that a pause occurred during the time the battery was replaced in the process from L3 to L4, causing a sharp decrease in the accumulated discharge current. Therefore, the diagnostic device 120 can determine whether or not a battery replacement history exists by checking the point in time when the battery's accumulated current decreases sharply.

[0092] Figure 3a, part 320, illustrates a graph showing the relationship between cumulative discharge current and cumulative mileage. As illustrated in Figure 3a, part 320, the diagnostic device 120 can acquire time-series data of cumulative discharge current and mileage over time, and can represent the relationship between cumulative discharge current and cumulative mileage in a two-dimensional graph. In this case, the diagnostic device 120 can calculate the slope of graph L5 showing the relationship between cumulative mileage and cumulative discharge current, and can check whether the graph converges to the origin when extended by the calculated slope. If the extended graph does not converge to the origin, the diagnostic device 120 can determine that there is a history of battery replacement.

[0093] Figure 3b shows a graph illustrating the relationship between the cumulative discharge current and cumulative mileage stored in the database. Referring to Figure 3b, the diagnostic device 120 can determine that there is a replacement history if the slope of the cumulative discharge current and cumulative mileage exceeds a threshold.

[0094] For example, in Figure 3b, graph C1 shows a case where there is no battery replacement history, graph C2 shows a case where the cumulative discharge current decreases rapidly, and graph C3 exemplifies a case where the graph does not converge to the origin when extended.

[0095] The diagnostic device 120 can determine that there is a history of battery replacement if the ratio of cumulative mileage to cumulative discharge current exceeds a threshold. Figure 3b shows an example of data analysis for setting the threshold.

[0096] Referring to 340 in Figure 3b, it is possible to analyze the energy consumption of repeatedly acquired battery data and set a threshold for determining the battery replacement history. In 340, each column represents the vehicle model from which the data was acquired, the number of times the data was acquired, the average energy consumption, the standard deviation, the minimum energy consumption, the bottom 25th percentile of the energy consumption distribution, the bottom 50th percentile of the energy consumption distribution, the bottom 75th percentile of the energy consumption distribution, and the maximum energy consumption. In this case, it can be confirmed that the average energy consumption and the bottom 75th percentile of the energy consumption distribution have the most similar values ​​for all vehicle models, and thus the diagnostic device 120 can set the threshold to, for example, 75% (0.75).

[0097] Figure 4 shows an example of calculating the mileage after replacement and correcting the degree of deterioration according to one embodiment disclosed in this document. Referring to Figure 4, if the diagnostic device 120 determines that the target battery has been replaced, it can calculate the mileage since the replacement and correct the degree of deterioration.

[0098] In Figure 4, at 410, Vehicle A represents a vehicle whose battery has been determined to have been replaced, and Vehicle B represents a vehicle whose battery has not been determined to have been replaced. In the case of Vehicle B, since the battery has not been replaced, the acquired cumulative mileage data X can be used as is.

[0099] In the case of vehicle A, since the battery has been replaced, the mileage after the replacement can be calculated. At this time, the acquired cumulative mileage Z can be concatenated using the average energy consumption (slope) to obtain the intercept value y. It should be noted that the average energy consumption can be obtained from the time-series data of the cumulative mileage and cumulative discharge current of the battery installed in vehicle A, and is a different value from the 75% slope value used to distinguish between vehicle A and vehicle B. The diagnostic device 120 can calculate the mileage after the replacement for vehicle A as zy.

[0100] Figure 4, section 420, shows the degradation distribution based on cumulative mileage. The white circles indicate the SOH diagnostic results when no decision was made regarding battery replacement, the black circles indicate the SOH diagnostic results when a decision was made regarding battery replacement, and the triangular points indicate the SOH deviation before and after the decision was made regarding battery replacement. As a result, as shown in Figure 4, section 420, it can be confirmed that the diagnosed degradation value improves.

[0101] Therefore, the battery diagnostic system 100 can determine the battery replacement history and improve the accuracy of the actual SOH diagnosis. It can also eliminate losses due to premature replacement and user dissatisfaction that occur when the replacement history is not determined and the SOH of the battery is diagnosed as lower than the actual degree of degradation.

[0102] Figures 5a and 5b show examples of calculating diagnostic criteria for abnormality diagnosis according to one embodiment disclosed in this document. Figure 5a shows an example of calculating voltage deviation diagnostic criteria, and the index calculation unit 110 can acquire cumulative data on voltage deviation and SOC. From the data on voltage deviation and SOC, the index calculation unit 110 can derive a voltage deviation distribution 610 over time and a voltage deviation distribution 620 based on SOC. The index calculation unit 110 can match the voltage deviation data over time and SOC at their respective points in time and acquire the voltage deviation distribution 620 based on SOC.

[0103] Referring to Figure 5b, the index calculation unit 110 can derive the open-circuit voltage distribution 630 based on the SOC from the battery data and derive a graph G1 showing the relationship between SOC and open-circuit voltage. The index calculation unit 110 can shift graph G1 and obtain the shifted graph G2. For example, as shown in 640 of Figure 6, the graph can be shifted by 10% of the SOC.

[0104] Subsequently, the index calculation unit 110 can obtain graph G3, which shows the difference between graph G1 and the shifted graph G2. In this case, graph G3 may be a graph relating to voltage deviation due to SOC, and the index calculation unit 110 can calculate graph G3 as a diagnostic criterion for determining voltage deviation abnormalities due to SOC.

[0105] For example, as shown in 660 of Figure 5b, data distributed in the region on graph G3 calculated as a diagnostic criterion can be identified as a voltage deviation anomaly. In this case, the voltage deviation distribution calculated by SOC used in 660 may be the same as the distribution shown in 620.

[0106] Figure 6 is a flowchart illustrating a battery diagnostic method according to one embodiment disclosed in this document. Referring to Figure 6, the battery diagnostic method may include the steps of: building a database of battery data related to the battery and calculating diagnostic criteria for diagnosing the battery based on the battery data (S100); acquiring diagnostic data for the target battery installed in the vehicle (S200); calculating usage characteristics for the target battery from the diagnostic data (S300); and diagnosing the target battery based on the usage characteristics, diagnostic data, and diagnostic criteria (S400).

[0107] In step S100, the index calculation unit 110 can build a database of battery data. The index calculation unit 110 can calculate diagnostic indicators and diagnostic criteria for diagnosing the battery. For example, the diagnostic criteria may include criteria for diagnosing the degree of battery degradation, criteria for diagnosing the presence or absence of abnormalities, etc.

[0108] In step S200, the diagnostic device 120 can acquire diagnostic data for the target battery. In this embodiment, the diagnostic device 120 can acquire diagnostic data from an OBD device installed in the vehicle, and the diagnostic data may be data acquired over a short period of time.

[0109] In step S300, the diagnostic device 120 can calculate the value of the diagnostic index for the target battery based on the diagnostic data. For example, the diagnostic device 120 can receive the diagnostic index from the index calculation unit 110 and calculate the value of the diagnostic index from the diagnostic data.

[0110] In step S400, the diagnostic device 120 can diagnose the target battery based on the values ​​of the diagnostic indicators and the diagnostic criteria. The diagnostic device 120 can diagnose the target battery using only diagnostic data acquired in a short period of time using the diagnostic criteria already calculated by the indicator calculation unit 110.

[0111] Figure 7 is a flowchart illustrating an example of the process for calculating diagnostic criteria according to one embodiment disclosed in this document. Referring to Figure 7, the index calculation unit 110 can calculate diagnostic criteria by analyzing the relationships between factors included in the battery data.

[0112] In one embodiment, the index calculation unit 110 can calculate a graph showing the relationship between the charge rate and the open-circuit voltage included in the battery data (S110). The index calculation unit 110 can shift the graph showing the relationship between the charge level and the open-circuit voltage by a pre-set interval (S120). The index calculation unit 110 can calculate an abnormality diagnosis criterion for voltage deviation due to charge rate based on the difference before and after shifting the graph (S130).

[0113] Figure 8 is a flowchart illustrating an example of the process for correcting the degree of degradation according to one embodiment disclosed in this document. Referring to Figure 8, the diagnostic device 120 can determine the replacement history of the target battery and correct the degree of degradation. The process by which the diagnostic device 120 corrects the degree of degradation based on whether or not the target battery has a replacement history may include the steps of: determining whether or not the target battery has a replacement history based on at least one of the cumulative current and cumulative mileage (S310); calculating the mileage since the time of replacement of the target battery if it is determined that the target battery has a replacement history (S320); and correcting the degree of degradation based on the mileage since the time of replacement (S330).

[0114] In step S310, the diagnostic device 120 can determine whether or not the target battery has a replacement history. In one embodiment, the diagnostic device 120 can determine whether or not the target battery has a replacement history based on at least one of the target battery's cumulative current and cumulative mileage.

[0115] In step S320, the diagnostic device 120 can calculate the mileage since the time the target battery was replaced. In step S330, the diagnostic device 120 can correct the degree of deterioration based on the mileage since the time of replacement. For example, the diagnostic device 120 can calculate the degree of deterioration by substituting the mileage since the time of replacement and the usage habits into the diagnostic criteria.

[0116] Figure 9 is a block diagram showing the hardware configuration of a computing system for performing a battery diagnostic method according to one embodiment disclosed in this document. Referring to Figure 9, the computing system 1000 according to one embodiment disclosed in this document may include an MCU 1010, a memory 1020, an input / output interface 1030, and a communication interface 1040.

[0117] The MCU1010 may be a processor that executes various programs stored in memory 1020, processes various information through these programs, and performs the functions of the battery diagnostic system shown in Figure 1 above.

[0118] Memory 1020 can store various programs, such as a diagnostic criteria calculation program, a usage characteristics calculation program, and a diagnostic program. Memory 1020 can also store various information, such as diagnostic data and diagnostic results.

[0119] Multiple such memory 1020s may be provided as needed. Memory 1020 may be volatile memory or non-volatile memory. As volatile memory, RAM, DRAM, SRAM, etc., can be used for memory 1020. As non-volatile memory, ROM, PROM, EAROM, EPROM, EEPROM, flash memory, etc., can be used for memory 1020. The examples of memory 1020 listed above are merely illustrative and are not limiting.

[0120] The input / output interface 1030 can provide an interface that connects input devices (not shown), such as keyboards, mice, and touch panels, with output devices (not shown), such as displays, and the MCU 1010, enabling data transmission and reception. The communication interface 1040 is configured to send and receive various types of data with the server, and may be various devices that support wired or wireless communication.

[0121] Thus, the computer program according to one embodiment disclosed in this document may be recorded in memory 1020 and processed by MCU 1010 to be implemented as a module that performs, for example, the functions shown in Figure 1.

[0122] Although all components constituting the embodiments disclosed in this document have been described as operating either as a single unit or in combination, the embodiments disclosed in this document are not necessarily limited to such embodiments. That is, within the scope of the purpose of the embodiments disclosed in this document, all components may operate in combination of one or more units.

[0123] Furthermore, terms such as “includes,” “constitutes,” or “possesses,” as described above, mean that they may contain the component in question, and not exclude other components, unless otherwise specified. All terms, including technical or scientific terms, have the same meaning as those generally understood by a person of ordinary skill in the art to which the embodiments disclosed herein belong, unless otherwise specified. Commonly used terms, such as those defined in dictionaries, should be interpreted to be consistent with their meaning in the context of the relevant technology, and not to be interpreted in an ideal or overly formal sense unless explicitly defined herein.

[0124] The above description is merely illustrative of the technical concept disclosed herein, and any person with ordinary skill in the art to which the embodiments disclosed herein belong can make various modifications and variations without departing from the essential characteristics of the embodiments disclosed herein. Therefore, the embodiments disclosed herein are for illustrative purposes only, not to limit the technical concept of the embodiments disclosed herein, and the scope of the technical concept disclosed herein is not limited by such embodiments. The scope of protection of the technical concept disclosed herein must be interpreted according to the claims described below, and all technical concepts within an equivalent scope should be interpreted as being included in the scope of rights of this document.

Claims

1. A database of battery-related data is constructed, and an index calculation unit calculates diagnostic criteria for diagnosing batteries and diagnostic indicators applicable to those diagnostic criteria based on the battery data. We acquire diagnostic data related to the target battery installed in the vehicle. Based on the diagnostic data, the value of the diagnostic index for the target battery is calculated. A diagnostic device for diagnosing the target battery based on the value of the diagnostic index and the diagnostic criteria, A battery diagnostic system, including a battery diagnostic system.

2. The diagnostic indicators include battery usage characteristics and the vehicle's cumulative mileage. The diagnostic device is Based on the cumulative power and cumulative current of the target battery included in the diagnostic data, the usage characteristics are calculated. A battery diagnostic system according to claim 1, which diagnoses the degree of degradation of the target battery by comparing the usage characteristics and the cumulative mileage with the diagnostic criteria.

3. The aforementioned usage characteristics include the rapid charging ratio of the target battery, The diagnostic device is The battery diagnostic system according to claim 2, which calculates the rapid charging ratio based on the ratio of the cumulative power to the cumulative current.

4. The cumulative power includes cumulative charging power and cumulative discharging power. The cumulative current includes the cumulative charging current and the cumulative discharging current. The diagnostic device is The battery diagnostic system according to claim 3, wherein the rapid charge ratio is calculated based on the difference between the ratio of the cumulative charging power to the cumulative charging current and the ratio of the cumulative discharge power to the cumulative discharge current.

5. The diagnostic device is The battery diagnostic system according to claim 2, which determines whether or not the target battery has a replacement history based on at least one of the cumulative current and the cumulative mileage.

6. The diagnostic device is The battery diagnostic system according to claim 5, which determines whether or not the target battery has a replacement history based on the change in the cumulative current over time.

7. The diagnostic device is The battery diagnostic system according to claim 6, wherein if the cumulative current decreases sharply at a specific point in time, it is determined that the target battery has a history of replacement.

8. The diagnostic device is The battery diagnostic system according to claim 5, which determines whether or not the target battery has a replacement history based on the ratio of the cumulative mileage and the cumulative current.

9. The diagnostic device is The battery diagnostic system according to claim 8, wherein if the ratio of the cumulative mileage to the cumulative current exceeds a threshold, or if the graph showing the relationship between the cumulative mileage and the cumulative current does not converge to the origin when extended, it is determined that the target battery has a replacement history.

10. The diagnostic device is If it is determined that the aforementioned battery has a history of being replaced, A battery diagnostic system according to any one of claims 5 to 9, comprising calculating the mileage traveled since the time of replacement of the target battery and correcting the degree of deterioration based on the mileage traveled since the time of replacement.

11. The aforementioned index calculation unit, A battery diagnostic system according to any one of claims 2 to 9, which analyzes the correlation between the cumulative mileage and the degree of degradation, and the correlation between charging habits and the degree of degradation, in order to calculate the diagnostic criteria and diagnostic index.

12. The aforementioned index calculation unit, The diagnostic indicators and diagnostic criteria are calculated according to the type of vehicle. The battery diagnostic system according to claim 11, which estimates diagnostic criteria and diagnostic indicators for other vehicles based on the charging habits and storage voltage of each vehicle.

13. The aforementioned index calculation unit, A battery diagnostic system according to any one of claims 1 to 9, which calculates diagnostic criteria and diagnostic indicators for diagnosing battery abnormalities based on the aforementioned battery data.

14. The battery diagnostic system according to claim 13, wherein the diagnostic criteria include a criterion for at least one of voltage deviation, temperature deviation, and insulation resistance.

15. The diagnostic indicators include the charge level and the open-circuit voltage. The aforementioned index calculation unit, A graph showing the relationship between the charge level and the open-circuit voltage is calculated. The aforementioned graph is shifted at the previously set interval, The battery diagnostic system according to claim 13, wherein the diagnostic criteria for the voltage deviation due to the charge rate are calculated based on the difference before and after shifting the graph.

16. The battery diagnostic system according to any one of claims 1 to 9, wherein the diagnostic data is data acquired in a short time from an OBD device installed in the vehicle.

17. The diagnostic device is A battery diagnostic system according to any one of claims 1 to 9, wherein the diagnostic results for the target battery are transmitted to an external device.

18. The steps include: constructing a database of battery-related data, and calculating diagnostic criteria for diagnosing batteries and diagnostic indicators applicable to those diagnostic criteria based on the battery data; Steps include obtaining diagnostic data related to the target battery installed in the vehicle, A step of calculating the value of the diagnostic index of the target battery based on the diagnostic data, A step of diagnosing the target battery based on the value of the diagnostic index and the diagnostic criteria, Battery diagnostic methods, including those mentioned above.

19. The diagnostic indicators include battery usage characteristics and the vehicle's cumulative mileage. The step of calculating the value of the aforementioned diagnostic index is: The method is characterized by calculating the usage characteristics based on the cumulative power and cumulative current of the target battery included in the diagnostic data. The step of diagnosing the aforementioned battery is: The battery diagnostic method according to claim 18, comprising diagnosing the degree of degradation of the target battery by comparing the usage characteristics and the cumulative mileage with the diagnostic criteria.

20. The step of diagnosing the aforementioned battery is: A step of determining whether or not the target battery has a replacement history based on at least one of the cumulative current and the cumulative mileage, If it is determined that the aforementioned battery has been replaced, the steps include calculating the mileage since the time the aforementioned battery was replaced, A battery diagnostic method according to claim 19, comprising the step of correcting the degree of deterioration based on the distance traveled since the time of replacement.

21. The diagnostic indicators include the charge level and the open-circuit voltage. The step of calculating the diagnostic criteria and the diagnostic indicators applied to the diagnostic criteria is: The steps include: calculating a graph showing the relationship between the charge level and the open-circuit voltage; The steps include shifting the aforementioned graph at a predetermined interval, A battery diagnostic method according to any one of claims 18 to 20, comprising the step of calculating a diagnostic criterion for diagnosing an abnormality in the battery with respect to the voltage deviation due to the charge level, based on the difference before and after shifting the graph.

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