Apparatus and method for diagnosing battery

Abstract

An apparatus for diagnosing a battery according to an embodiment of the present invention comprises: a data acquisition unit configured to acquire diagnostic data including at least one of battery information about a target battery for a predetermined period from a diagnostic reference time or driving information about a vehicle including the target battery; and a control unit configured to set a threshold value on the basis of reference data corresponding to the predetermined period and a preset model, calculate a diagnostic value on the basis of the diagnostic data and the model, and diagnose the state of the target battery on the basis of the threshold value and the diagnostic value.

Description

Battery diagnostic device and method

[0001] This application is a priority claim application for Korean Patent Application No. 10-2024-0139422 filed on October 14, 2024, and all contents disclosed in the specification and drawings of said application are incorporated into this application by reference.

[0002] The present invention relates to a battery diagnostic device and method capable of predicting and diagnosing the future state of a battery.

[0003] Recently, as the demand for portable electronic products such as laptops, video cameras, and mobile phones has increased rapidly, and the development of electric vehicles, energy storage batteries, robots, and satellites has accelerated, research on high-performance batteries capable of repeated charging and discharging is actively underway.

[0004] Currently commercialized batteries include nickel-cadmium, nickel-hydrogen, nickel-zinc, and lithium batteries. Among these, lithium batteries are gaining attention for their advantages, such as the ability to freely charge and discharge with almost no memory effect compared to nickel-based batteries, a very low self-discharge rate, and high energy density.

[0005] While extensive research is being conducted on these batteries in terms of increasing capacity and density, improving lifespan and safety is also crucial. To enhance battery safety, technology capable of accurately diagnosing the battery's condition is required.

[0006] The present invention was devised to solve the above-mentioned problems and aims to provide a battery diagnostic device and method capable of predicting and diagnosing the future state of a battery.

[0007] Other objects and advantages of the present invention may be understood from the following description and will become more clearly apparent from the embodiments of the present invention. Furthermore, it will be readily apparent that the objects and advantages of the present invention can be realized by the means and combinations thereof set forth in the claims.

[0008] A battery diagnostic device according to one aspect of the present invention may include: a data acquisition unit configured to acquire diagnostic data comprising at least one of battery information of a target battery and driving information of a vehicle including the target battery during a predetermined period from a diagnostic reference point; and a control unit configured to set a threshold value based on reference data corresponding to the predetermined period and a preset model, calculate a diagnostic value based on the diagnostic data and the model, and diagnose the state of the target battery based on the threshold value and the diagnostic value.

[0009] The control unit may be configured to diagnose the state of the target battery at a point in time after a predetermined period from the diagnostic reference point, based on the threshold value and the diagnostic value.

[0010] The control unit may be configured to compare the threshold value and the diagnostic value, and to diagnose the state of the target battery based on the comparison result.

[0011] The control unit may be configured to calculate the error-specific ratio of the reference data using the model, calculate a sum error based on the calculated error-specific ratio, and set the calculated sum error to the threshold value.

[0012] The above reference data may be provided in multiple quantities.

[0013] The control unit above may be configured to input a plurality of reference data into the model to calculate a sum error and to set the calculated sum error to the threshold value.

[0014] The control unit may be configured to calculate the average ratio of each error of the plurality of reference data using the model, and to calculate the sum error based on the calculated average ratio of each error.

[0015] The control unit may be configured to calculate the error-specific ratio of the diagnostic data using the model, calculate a sum error based on the calculated error-specific ratio, and set the calculated sum error as the diagnostic value.

[0016] The above control unit may be configured to set the data corresponding to the predetermined period among a plurality of preset data as the reference data.

[0017] The control unit may be configured to determine data corresponding to a diagnostic item of the target battery among the plurality of data, and to set the reference data among the determined data.

[0018] The above model can be composed of a Recurrent Neural Network (RNN)-based model.

[0019] A battery pack according to another aspect of the present invention may include a battery diagnostic device according to one aspect of the present invention.

[0020] An automobile according to another aspect of the present invention may include a battery diagnostic device according to one aspect of the present invention.

[0021] A server according to another aspect of the present invention may include a battery diagnostic device according to one aspect of the present invention.

[0022] A battery diagnostic method according to another aspect of the present invention may include: a data acquisition step of acquiring diagnostic data comprising at least one of battery information of a target battery and driving information of a vehicle including the target battery during a predetermined period from a diagnostic reference point; a threshold setting step of setting a threshold value based on reference data corresponding to the predetermined period and a preset model; a diagnostic value setting step of calculating a diagnostic value based on the diagnostic data and the model; and a diagnostic step of diagnosing the state of the target battery based on the threshold value and the diagnostic value.

[0023] A computer-readable recording medium according to another aspect of the present invention may store a computer program for executing a battery diagnosis method comprising: a data acquisition step of acquiring diagnostic data including at least one of battery information of a target battery and driving information of a vehicle including said target battery during a predetermined period from a diagnostic reference point; a threshold setting step of setting a threshold value based on reference data corresponding to said predetermined period and a preset model; a diagnostic value setting step of calculating a diagnostic value based on said diagnostic data and said model; and a diagnostic step of diagnosing the state of said target battery based on said threshold value and said diagnostic value.

[0024] According to one aspect of the present invention, the battery diagnostic device has the advantage of being able to predict and diagnose the future state of a target battery after a predetermined period.

[0025] The effects of the present invention are not limited to those mentioned above, and other unmentioned effects will be clearly understood by those skilled in the art from the description in the claims.

[0026] The following drawings attached to this specification serve to further enhance understanding of the technical concept of the invention in conjunction with the detailed description of the invention set forth below; therefore, the invention should not be interpreted as being limited only to the matters described in such drawings.

[0027] FIG. 1 is a schematic diagram illustrating a battery diagnostic device according to one embodiment of the present invention.

[0028] FIG. 2 is a diagram schematically illustrating the time-dependent error of reference data according to one embodiment of the present invention.

[0029] FIG. 3 is a diagram schematically illustrating the ratio of reference data by error according to one embodiment of the present invention.

[0030] FIG. 4 is a diagram schematically illustrating the ratio of diagnostic data by error according to one embodiment of the present invention.

[0031] FIG. 5 is a diagram schematically illustrating the average ratio of reference data by error according to one embodiment of the present invention.

[0032] FIG. 6 is a schematic diagram illustrating a battery pack according to another embodiment of the present invention.

[0033] FIG. 7 is a schematic drawing illustrating an automobile according to another embodiment of the present invention.

[0034] FIG. 8 is a schematic diagram illustrating a server according to another embodiment of the present invention.

[0035] FIG. 9 is a schematic diagram illustrating a battery diagnostic method according to another embodiment of the present invention.

[0036] Terms and words used in this specification and claims should not be interpreted as being limited to their ordinary or dictionary meanings, but should be interpreted in a meaning and concept consistent with the technical spirit of the invention, based on the principle that the inventor can appropriately define the concept of the terms to best describe his invention.

[0037] Therefore, the embodiments described in this specification and the configurations illustrated in the drawings are merely the most preferred embodiments of the present invention and do not represent all of the technical ideas of the present invention; thus, it should be understood that various equivalents and modifications that can replace them may exist at the time of filing this application.

[0038] In addition, in describing the present invention, if it is determined that a detailed description of related known components or functions may obscure the essence of the invention, such detailed description is omitted.

[0039] Terms including ordinal numbers, such as first, second, etc., are used for the purpose of distinguishing one of the various components from the rest, and are not used to limit the components by such terms.

[0040] Throughout the specification, when a part is described as "including" a certain component, this means that, unless specifically stated otherwise, it does not exclude other components but may include additional components.

[0041] Additionally, throughout the specification, when it is said that a part is "connected" to another part, this includes not only cases where they are "directly connected," but also cases where they are "indirectly connected" with other components in between.

[0042]

[0043] Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the attached drawings.

[0044] FIG. 1 is a schematic diagram illustrating a battery diagnostic device (100) according to one embodiment of the present invention.

[0045] Referring to FIG. 1, the battery diagnostic device (100) may include a data acquisition unit (110) and a control unit (120).

[0046] The data acquisition unit (110) may be configured to acquire diagnostic data including at least one of battery information of the target battery and driving information of the vehicle containing the target battery during a predetermined period from the diagnostic reference point.

[0047] Here, a battery refers to a single independent cell that is physically separable and equipped with a negative terminal and a positive terminal. For example, a lithium-ion battery or a lithium-polymer battery may be considered a battery. Additionally, the type of battery may be cylindrical, prismatic, or pouch type. Furthermore, a battery may refer to a battery bank, battery module, or battery pack in which a plurality of cells are connected in series and / or parallel.

[0048] Specifically, the data acquisition unit (110) can acquire battery information regarding the voltage and current of the battery over a predetermined period from an external source. For example, if the battery is included in a vehicle, the data acquisition unit (110) can acquire battery information regarding the hourly voltage and hourly current of the battery measured during the operation of the vehicle over a predetermined period.

[0049] For example, the data acquisition unit (110) can acquire battery information by directly measuring the voltage and current of the battery. As another example, the data acquisition unit (110) can acquire battery information by receiving battery information from an external source connected to enable communication.

[0050] Additionally, the data acquisition unit (110) can acquire driving information regarding the speed of a vehicle containing a battery from an external source. For example, the data acquisition unit (110) can acquire driving information regarding the speed at different times measured during the operation of the vehicle over a predetermined period.

[0051] The control unit (120) may be configured to set a threshold value based on reference data corresponding to a predetermined period and a preset model.

[0052] Specifically, the control unit (120) may be configured to set data corresponding to a predetermined period among a plurality of preset data as reference data.

[0053] More specifically, the control unit (120) may set reference data to correspond to the period of the diagnostic data in order to compare the diagnostic data and reference data under the same period conditions. For example, if the diagnostic data corresponds to a first period, the control unit (120) may set the data corresponding to the first period among a plurality of preset data as reference data.

[0054] Preferably, reference data is data that serves as a standard for diagnosing the condition of the battery. Accordingly, reference data may include prior data for a predetermined period based on the time of the occurrence of an anomaly.

[0055] For example, assume that an abnormality occurred at time t1 and a predetermined period is △t. The control unit (120) can set the data from time t1-△t+1 to time t1 among the plurality of data as reference data.

[0056] As a more specific example, assume that an abnormality occurred at time 100 and the predetermined period is 60. The control unit (120) can set the data from time 41 to time 100 as reference data.

[0057] Next, the control unit (120) can be configured to calculate the error-by-error ratio of the reference data using a model.

[0058] First, the control unit (120) inputs reference data into a model to calculate the error ratio of the reference data and obtains data regarding the error of the reference data per unit time from the model. Here, the model may be pre-configured to output the error per unit time for the input data. For example, the model may divide the input data into unit times and compare each of the divided data with the pre-trained data to output an error for each unit time.

[0059] FIG. 2 is a schematic diagram illustrating the hourly error of reference data according to an embodiment of the present invention. For example, the hourly error of FIG. 2 can be represented as an XY graph in which the X-axis is set as time and the Y-axis is set as error. In the embodiment of FIG. 2, the predetermined period is from 0 to 100. Accordingly, the control unit (120) can obtain data regarding the hourly error of reference data corresponding to time from 0 to 100.

[0060] Next, the control unit (120) may be configured to calculate the error-specific ratio based on the time-specific error of the reference data. Specifically, the control unit (120) may calculate the error-specific ratio by considering the error-specific frequency over a predetermined period.

[0061] For example, assume that a predetermined period is divided into a total of 100 unit times, and that the error corresponding to 50 unit times is 0.025 and the error corresponding to 10 unit times is 0.01. In this case, the ratio of the error 0.025 is 0.5 and the ratio of the error 0.01 is 0.1. In this way, the control unit (120) can calculate the ratio of each error based on the time-based error of the reference data.

[0062] FIG. 3 is a schematic diagram illustrating the ratio of error-specific reference data according to an embodiment of the present invention. In the embodiment of FIG. 3, the ratio of error-specific data can be represented as an XY graph where the X-axis is set as the error and the Y-axis is set as the ratio. In the embodiment of FIG. 3, the total sum of the ratios of error-specific data is 1. The control unit (120) can calculate the ratio for each error based on the time-specific error of FIG. 2.

[0063] The control unit (120) may be configured to calculate the sum error based on the calculated error-by-error ratio.

[0064] Specifically, the control unit (120) can calculate a sum error representing the reference data based on the error-specific ratio. For example, the sum error is a weighted error calculated based on the error-specific ratio. The control unit (120) can calculate the weighted error by multiplying each of the multiple errors by the corresponding ratio and adding all the multiplied values ​​together. For example, the control unit (120) can calculate the sum error based on the following formula.

[0065] [Formula 1]

[0066]

[0067] Here, E i is the error corresponding to unit time i, and P i is the ratio corresponding to unit time i. E t is the sum of errors over all unit times (e.g., weighted errors).

[0068] Additionally, the control unit (120) may be configured to set the calculated sum error as a threshold value. Specifically, the control unit (120) may set a threshold value from reference data by considering a predetermined period corresponding to the diagnostic data. That is, since the threshold value is determined according to a predetermined period corresponding to the diagnostic data, the control unit (120) may adaptively set a threshold value suitable for the predetermined period.

[0069] The control unit (120) may be configured to calculate a diagnostic value based on diagnostic data and a model. Here, since the diagnostic data is data corresponding to a predetermined period, the control unit (120) can calculate a diagnostic value from the diagnostic data acquired by the data acquisition unit (110).

[0070] Specifically, the control unit (120) may be configured to calculate the error-by-error ratio of the diagnostic data using a model. That is, the control unit (120) may calculate the error-by-error ratio of the diagnostic data using a model in the same manner as calculating the error-by-error ratio of the reference data by inputting reference data into the model. For example, the control unit (120) may input diagnostic data into the model and obtain data regarding the error of the diagnostic data per unit time from the model. Then, the control unit (120) may calculate the error-by-error ratio based on the error per time of the diagnostic data. For example, the control unit (120) may calculate the error-by-error ratio by considering the frequency of error-by-error over a predetermined period.

[0071] FIG. 4 is a schematic diagram illustrating the ratio of diagnostic data by error according to an embodiment of the present invention. In the embodiment of FIG. 4, the ratio by error can also be represented as an XY graph in which the X-axis is set as the error and the Y-axis is set as the ratio. In the embodiment of FIG. 4, the total sum of the ratios by error is 1.

[0072] The control unit (120) may be configured to calculate the sum error based on the calculated error-by-error ratio.

[0073] Specifically, the control unit (120) can calculate a sum error representing the diagnostic data based on the error-specific ratio. For example, the sum error is a weighted error calculated based on the error-specific ratio. The control unit (120) can calculate a sum error for multiple errors using Equation 1.

[0074] Additionally, the control unit (120) may be configured to set the calculated sum error as a diagnostic value. Specifically, since the diagnostic value and the threshold value calculated by the control unit (120) are both values ​​corresponding to a predetermined period, they are values ​​with common temporal consistency.

[0075] The control unit (120) can be configured to diagnose the state of the target battery based on a threshold value and a diagnostic value.

[0076] Specifically, the control unit (120) may be configured to compare a threshold value and a diagnostic value, and to diagnose the state of the target battery based on the comparison result. The control unit (120) may compare the magnitude of the threshold value and the diagnostic value, and diagnose the state of the battery as normal or abnormal depending on the comparison result. For example, if the diagnostic value is less than the threshold value, the control unit (120) may diagnose the state of the battery as normal. As another example, if the diagnostic value is greater than or equal to the threshold value, the control unit (120) may diagnose the state of the battery as abnormal.

[0077] Preferably, the control unit (120) may be configured to diagnose the state of the target battery at a predetermined time after the diagnosis reference point, based on a threshold value and a diagnosis value. That is, the control unit (120) can predict and diagnose the future state of the battery based on the result of comparing the threshold value and the diagnosis value.

[0078] Here, the diagnostic reference point refers to the most recent point in time corresponding to the diagnostic data. In other words, the diagnostic data refers to data up to a predetermined period prior to the diagnostic reference point.

[0079] Specifically, the threshold value is set based on reference data for a predetermined period from the time an abnormality occurs, and the diagnostic value is set based on diagnostic data for a predetermined period from the diagnostic reference time. Accordingly, the battery diagnostic device (100) has the advantage of being able to predict and diagnose the future state of the target battery after a predetermined period by using a temporal indicator of a predetermined period.

[0080]

[0081] Meanwhile, the data acquisition unit (110) and / or control unit (120) provided in the battery diagnostic device (100) may optionally include a processor, an application-specific integrated circuit (ASIC), other chipsets, logic circuits, registers, communication modems, data processing devices, etc., known in the art, to execute various control logics performed in the present invention. Additionally, when the control logic is implemented in software, the data acquisition unit (110) and / or control unit (120) may be implemented as a set of program modules. In this case, the program modules may be stored in memory and executed by the data acquisition unit (110) and / or control unit (120). The memory may be located inside or outside the data acquisition unit (110) and / or control unit (120) and may be connected to the data acquisition unit (110) and / or control unit (120) by various well-known means.

[0082] Additionally, the battery diagnostic device (100) may further include a storage unit (130). The storage unit (130) may store data or programs necessary for each component of the battery diagnostic device (100) to perform operations and functions, or data generated during the process of performing operations and functions. The storage unit (130) is not subject to any special restrictions on its type as long as it is a known information storage means capable of recording, erasing, updating, and reading data. As an example, the information storage means may include RAM, flash memory, ROM, EEPROM, registers, etc. Additionally, the storage unit (130) may store program codes that define processes executable by each component of the battery diagnostic device (100).

[0083]

[0084] Meanwhile, the model can be composed of a Recurrent Neural Network (RNN)-based model. Here, the RNN is a model suitable for processing time-series or sequential data, employing a structure that processes data sequentially and learns by remembering information from previous steps. Representative RNN-based models include Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). Furthermore, the RNN is a model capable of tracking changes over time or learning patterns by dividing and processing time-series data into fixed intervals according to chronological order. For instance, the RNN can divide time-series data into unit times (e.g., timesteps) and analyze the characteristics at each unit time.

[0085] Specifically, the model may be an RNN-based time-series encoder-decoder model. An encoder-decoder structure is a model architecture that extracts features through the process of encoding (compressing) data and then decoding (restoring) it. Seq2Seq (Sequence to Sequence) and autoencoders are examples of models that adopt an encoder-decoder structure.

[0086] For example, the battery diagnostic device (100) may use an LSTM autoencoder model. An LSTM autoencoder is a model that learns the characteristics of data through a process of efficiently encoding and decoding input data based on an LSTM network. Accordingly, the battery diagnostic device (100) can calculate the error per unit time of the diagnostic data and reference data using an LSTM autoencoder, and calculate a threshold value and a diagnostic value by considering the ratio of the calculated error.

[0087]

[0088] In one embodiment, reference data may be provided in multiple quantities. For example, if multiple reference batteries serving as the basis for the reference data are provided, each of the data corresponding to the multiple reference batteries may be set as reference data.

[0089] The control unit (120) can input multiple reference data into the model to calculate the sum error.

[0090] Specifically, the control unit (120) may be configured to calculate the average ratio of each error of multiple reference data using a model. First, the control unit (120) may input each of the multiple reference data into the model to calculate the error per unit time of each of the multiple reference data. Then, the control unit (120) may calculate the ratio of each error of each of the multiple reference data by considering the calculated error per unit time. Finally, the control unit (120) may calculate the average ratio for each error.

[0091] FIG. 5 is a schematic diagram illustrating the average ratio of reference data by error according to an embodiment of the present invention. In the embodiment of FIG. 5, the average ratio by error can be represented as an XY graph in which the X-axis is set as the error and the Y-axis is set as the average ratio. For example, when n reference data are provided, the average ratio of an error of 0.00 for the n reference data is approximately 0.1.

[0092] And, the control unit (120) may be configured to calculate the sum error based on the average ratio of the calculated error.

[0093] Specifically, the control unit (120) can calculate a sum error representing multiple reference data based on an average ratio for each error. For example, the sum error is a weighted error calculated based on an average ratio for each error. The control unit (120) can calculate a sum error for multiple errors using Equation 1. For example, P representing the ratio corresponding to unit time i in Equation 1 i The average ratio is substituted into it, and the sum of the errors based on the average ratios for each error can be calculated.

[0094] The control unit (120) may be configured to set the calculated sum error as a threshold value. That is, the control unit (120) may set a threshold value that serves as a criterion for diagnosing the state of the battery based on a plurality of reference data.

[0095] A battery diagnostic device (100) according to one embodiment of the present invention can set a threshold value by comprehensively considering a plurality of reference data and diagnose the condition of a target battery by comparing the set threshold value with the diagnostic value of the target battery. That is, according to the battery diagnostic device (100), since the threshold value for a plurality of reference data is considered, the condition of the battery can be diagnosed more accurately.

[0096]

[0097] The control unit (120) may be configured to determine data corresponding to the diagnostic item of the target battery among a plurality of data.

[0098] For example, the diagnostic items can be set in various ways, such as available lithium loss, positive electrode capacity loss, negative electrode capacity loss, battery capacity loss, insulation breakdown, short circuit, open circuit, and low voltage. The control unit (120) determines a diagnostic item to be diagnosed among several diagnostic items and can determine data corresponding to the determined diagnostic item among a plurality of data.

[0099] As a specific example, assume that the diagnostic item is available lithium loss. The control unit (120) can select only the data corresponding to the available lithium loss from among a plurality of data.

[0100] The control unit (120) can be configured to set reference data among the determined data.

[0101] Specifically, the control unit (120) can specify the time at which available lithium loss occurred in each of the determined data, extract only the data prior to a predetermined period from the specified time, and set the extracted data as reference data.

[0102] Preferably, in order to maintain temporal consistency between the diagnostic data and the reference data, the control unit (120) may not set as reference data any data that is not prior to a predetermined period from a specific point in time among the determined data.

[0103] For example, in the preceding embodiment, it is assumed that a predetermined period is set to 100. In data where the time at which available lithium loss occurred is less than 100, there is no data prior to the time at which available lithium loss occurred that is a predetermined period prior to the time at which available lithium loss occurred. Therefore, the control unit (120) may not set these data as reference data.

[0104] Since the battery management device selects reference data from multiple data based on diagnostic items and a predetermined period, it has the advantage of being able to more accurately predict and diagnose the condition of the battery.

[0105]

[0106] The battery diagnostic device (100) according to the present invention may be applied to a Battery Management System (BMS). That is, the BMS according to the present invention may include the battery diagnostic device (100) described above. In this configuration, at least some of the components of the battery diagnostic device (100) may be implemented by supplementing or adding the functions of the components included in a conventional BMS. For example, the data acquisition unit (110), control unit (120), and storage unit (130) of the battery diagnostic device (100) may be implemented as components of the BMS.

[0107] In one embodiment, the battery diagnostic device (100) can control the charging and / or discharging of the battery based on the diagnostic results of the battery. Specifically, the control unit (120) can control the charging and / or discharging of the battery so that the charging and / or discharging optimized for the battery can proceed by utilizing the diagnostic results.

[0108] In another embodiment, the battery diagnostic device (100) may change various state conditions set for the battery based on the diagnosis results of the battery to prevent further degradation of the battery. For example, the control unit (120) may set at least one of the battery's upper charge limit SOC, upper charge limit voltage, upper charge limit C-rate, lower discharge limit SOC, lower discharge limit voltage, upper discharge limit C-rate, and upper limit temperature. For convenience of explanation, the state conditions that can be set by the battery diagnostic device (100) have been listed above, but it should be noted that any state condition that can be set using the diagnosis results of the battery to delay the degradation of the battery may be applied without limitation.

[0109]

[0110] In addition, the battery diagnostic device (100) according to the present invention may be provided in a battery pack. That is, the battery pack according to the present invention may include the battery diagnostic device (100) described above and one or more battery cells. In addition, the battery pack may further include electrical components (relays, fuses, etc.) and a case, etc.

[0111] FIG. 6 is a schematic diagram illustrating a battery pack (10) according to another embodiment of the present invention.

[0112] A battery set (11) may include a plurality of battery cells electrically connected in series and / or parallel. For example, a plurality of battery cells may be provided directly in a battery pack (10). As another example, a plurality of battery cells may be included in a battery bank and / or battery module, and the battery bank and / or battery module may be included in the battery pack (10).

[0113] The positive terminal of the battery assembly (11) can be connected to the positive terminal (P+) of the battery pack (10), and the negative terminal of the battery assembly (11) can be connected to the negative terminal (P-) of the battery pack (10).

[0114] The measuring unit (12) can be connected to the first sensing line (SL1), the second sensing line (SL2), and the third sensing line (SL3). Specifically, the measuring unit (12) can be connected to the positive terminal of the battery assembly (11) via the first sensing line (SL1) and to the negative terminal of the battery assembly (11) via the second sensing line (SL2). The measuring unit (12) can measure the voltage of the battery assembly (11) based on the voltage measured at each of the first sensing line (SL1) and the second sensing line (SL2).

[0115] Additionally, the measuring unit (12) can be connected to a current measuring unit (A) via a third sensing line (SL3). For example, the current measuring unit (A) may be an ammeter or a shunt resistor capable of measuring the charging current and discharging current of the battery assembly (11). The measuring unit (12) can calculate the charging amount by measuring the charging current of the battery assembly (11) via the third sensing line (SL3). Furthermore, the measuring unit (12) can calculate the discharging amount by measuring the discharging current of the battery assembly (11) via the third sensing line (SL3).

[0116] The data acquisition unit (110) receives battery information measured by the measurement unit and can transmit the received battery information to the control unit (120).

[0117] The control unit (120) may be connected to communicate with an external device (20). Specifically, the external device (20) is a device capable of providing driving information of a vehicle containing a battery pack (10) to the control unit (120). For example, the external device (20) is not particularly limited to a device such as an electronic control unit (ECU) or a user terminal of a vehicle, as long as it is a device capable of transmitting driving information to the control unit (120).

[0118] The control unit (120) can diagnose the state of the battery pack (10) based on battery information received from the data acquisition unit (110) and driving information received from the external device (20).

[0119]

[0120] FIG. 7 is a schematic drawing illustrating a vehicle (700) according to another embodiment of the present invention.

[0121] Referring to FIG. 7, a battery pack (710) according to an embodiment of the present invention may be included in a vehicle (700), such as an electric vehicle (EV) or a hybrid vehicle (HV). The battery pack (710) can drive the vehicle (700) by supplying power to a motor through an inverter provided in the vehicle (700). Here, the battery pack (710) may include a battery diagnostic device (100). That is, the vehicle (700) may include a battery diagnostic device (100). In this case, the battery diagnostic device (100) may be an on-board device included in the vehicle (700).

[0122]

[0123] FIG. 8 is a schematic diagram illustrating a server (800) according to another embodiment of the present invention.

[0124] A server (800) according to another embodiment of the present invention may include a battery diagnostic device (100) according to one embodiment of the present invention.

[0125] Specifically, the server (800) may be connected to communicate with a device via wired and / or wireless. For example, in the embodiment of FIG. 8, the server (800) may be connected to communicate with an information providing device (810), such as a vehicle and / or a user terminal. Here, the server (800) may be connected without limitation as long as it is a device capable of transmitting battery information and driving information.

[0126] The server (800) receives battery information and driving information from the information providing device (810) and can diagnose the state of the battery based on the received battery information and driving information. Then, the server (800) can provide the diagnosis result to the corresponding information providing device (810). That is, the information providing device (810) can receive the battery state diagnosis result from the server (800).

[0127] Additionally, the server (800) can store data regarding the status of the diagnosed battery. And, an authorized user can access the server (800) and refer to the data regarding the status of the battery.

[0128]

[0129] FIG. 9 is a schematic diagram illustrating a battery diagnostic method according to another embodiment of the present invention.

[0130] Referring to FIG. 9, the battery diagnostic method may include a data acquisition step (S100), a threshold setting step (S200), a diagnostic value setting step (S300), and a diagnostic step (S400).

[0131] Preferably, each step of the battery diagnostic method can be performed by a battery diagnostic device (100). For convenience of explanation, details that overlap with previously described content will be omitted or briefly explained below.

[0132] The data acquisition step (S100) can be performed by the data acquisition unit (110) as a step of diagnostic data including at least one of battery information of the target battery and driving information of the vehicle containing the target battery during a predetermined period from the diagnostic reference point.

[0133] For example, the data acquisition unit (110) can acquire battery information by directly measuring the voltage and current of the battery. As another example, the data acquisition unit (110) can acquire battery information by receiving battery information from an external source connected to enable communication.

[0134] Additionally, the data acquisition unit (110) can acquire driving information regarding the speed of a vehicle containing a battery from an external source. For example, the data acquisition unit (110) can acquire driving information regarding the speed at different times measured during the operation of the vehicle over a predetermined period.

[0135] The threshold setting step (S200) is a step of setting a threshold based on reference data corresponding to a predetermined period and a preset model, and can be performed by the control unit (120).

[0136] For example, the control unit (120) may set data corresponding to a predetermined period among a plurality of preset data as reference data and calculate the error ratio of the reference data using a model. Then, the control unit (120) may calculate a sum error based on the calculated error ratio and set the calculated sum error as a threshold value.

[0137] The diagnostic value setting step (S300) is a step of calculating a diagnostic value based on diagnostic data and a model, and can be performed by the control unit (120).

[0138] For example, the control unit (120) can calculate the error-by-error ratio of the diagnostic data using a model. Then, the control unit (120) can calculate the sum error based on the calculated error-by-error ratio and set the calculated sum error as the diagnostic value.

[0139] The diagnosis step (S400) is a step of diagnosing the state of the target battery based on a threshold value and a diagnosis value, and can be performed by the control unit (120).

[0140] Specifically, the control unit (120) may be configured to diagnose the state of the target battery at a point in time after a predetermined period from the diagnosis reference point, based on a threshold value and a diagnosis value. For example, if the diagnosis value is less than the threshold value, the control unit (120) may diagnose the state of the battery at a point in time after a predetermined period from the diagnosis reference point as normal. As another example, if the diagnosis value is greater than or equal to the threshold value, the control unit (120) may diagnose the state of the battery as abnormal.

[0141]

[0142] The embodiments of the present invention described above are not limited to implementation through devices and methods, but may also be implemented through a program that realizes a function corresponding to the configuration of the embodiments of the present invention or a recording medium on which such a program is recorded. Such implementation can be easily achieved by a person skilled in the art to which the present invention pertains, based on the description of the embodiments described above.

[0143] Another embodiment of the present invention may provide a computer-readable recording medium having a program recorded thereon for executing the various embodiments described above on a computer.

[0144] A program may be implemented as hardware components, software components, and / or a combination of hardware and software components. A program may be executed by any system capable of executing computer-readable instructions.

[0145] Software may include computer programs, code, instructions, or a combination thereof, and may configure a processing unit to operate as desired or command the processing unit independently or collectively.

[0146] Software can be implemented as a computer program containing instructions stored on a computer-readable storage medium. Examples of computer-readable storage media include magnetic storage media (e.g., ROM (read-only memory), RAM (random-access memory), floppy disks, hard disks, etc.) and optical reading media (e.g., CD-ROMs, DVDs (Digital Versatile Discs)). Computer-readable storage media can be distributed across networked computer systems, allowing computer-readable code to be stored and executed in a distributed manner. The storage medium is readable by a computer, stored in memory, and can be executed by a processor.

[0147] Computer-readable recording media may be provided in the form of non-transitory recording media. Here, 'non-transitory storage media' simply means that it is a tangible device and does not contain a signal (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently and cases where it is stored temporarily. For example, 'non-transitory storage media' may include a buffer in which data is stored temporarily.

[0148] In addition, the program may be provided by being included in a computer program product. A computer program product may be traded between a seller and a buyer as a product.

[0149] A computer program product may include a software program or a computer-readable recording medium on which the software program is stored. For example, a computer program product may include a product in the form of a software program that is distributed electronically through a manufacturer of an electronic device or an electronic market (e.g., a downloadable application). For electronic distribution, at least a portion of the software program may be stored on a recording medium or temporarily created. In this case, the recording medium may be a server of the manufacturer of the electronic device, a server of the electronic market, or a recording medium of a relay server that temporarily stores the software program.

[0150] Although the present invention has been described above by limited embodiments and drawings, the present invention is not limited thereto, and it is obvious that various modifications and variations are possible within the scope of the technical spirit of the present invention and the equivalent scope of the claims described below by those skilled in the art to which the present invention belongs.

[0151] Furthermore, since the present invention described above allows for various substitutions, modifications, and changes within the scope of the technical concept of the present invention to those skilled in the art without departing from the technical spirit of the present invention, it is not limited by the aforementioned embodiments and attached drawings, but rather all or part of each embodiment may be selectively combined to allow for various modifications.

[0152] (Explanation of symbols)

[0153] 10: Battery pack

[0154] 11: Battery assembly

[0155] 12: Measurement section

[0156] 20: External device

[0157] 100: Battery information providing device

[0158] 110: Data acquisition unit

[0159] 120: Control unit

[0160] 130: Storage section

[0161] 700: Car

[0162] 710: Battery pack

[0163] 800: Server

[0164] 810: Information providing device

Claims

1. A data acquisition unit configured to acquire diagnostic data including at least one of battery information of a target battery and driving information of a vehicle including the target battery during a predetermined period from a diagnostic reference point; and A battery diagnostic device comprising a control unit configured to set a threshold value based on reference data corresponding to the above-mentioned predetermined period and a preset model, calculate a diagnostic value based on the above-mentioned diagnostic data and the above-mentioned model, and diagnose the state of the target battery based on the threshold value and the above-mentioned diagnostic value.

2. In Paragraph 1, The above control unit is, A battery diagnostic device configured to diagnose the state of the target battery at a point in time after a predetermined period from the diagnostic reference point, based on the above threshold value and the above diagnostic value.

3. In Paragraph 2, The above control unit is, A battery diagnostic device configured to compare the above threshold value and the above diagnostic value, and to diagnose the state of the target battery based on the comparison result.

4. In Paragraph 1, The above control unit is, A battery diagnostic device configured to calculate the error ratio of the reference data using the above model, calculate a sum error based on the calculated error ratio, and set the calculated sum error to the above threshold value.

5. In Paragraph 1, The above reference data is provided in multiple quantities, and The above control unit is, A battery diagnostic device configured to input multiple reference data into the above model to calculate a sum error and set the calculated sum error to the above threshold.

6. In Paragraph 5, The above control unit is, A battery diagnostic device configured to calculate the average ratio of error by multiple reference data using the above model, and to calculate the sum error based on the calculated average ratio of error by the calculated error.

7. In Paragraph 1, The above control unit is, A battery diagnostic device configured to calculate the error-specific ratio of the diagnostic data using the above model, calculate a sum error based on the calculated error-specific ratio, and set the calculated sum error as the diagnostic value.

8. In Paragraph 1, The above control unit is, A battery diagnostic device configured to set data corresponding to a predetermined period among a plurality of preset data as the reference data.

9. In Paragraph 8, The above control unit is, A battery diagnostic device configured to determine data corresponding to a diagnostic item of the target battery among the plurality of data above, and to set the reference data among the determined data.

10. In Paragraph 1, The above model is, A battery diagnostic device composed of an RNN (Recurrent Neural Network) based model.

11. A battery pack comprising a battery diagnostic device according to any one of claims 1 to 10.

12. An automobile comprising a battery diagnostic device according to any one of paragraphs 1 through 10.

13. A server comprising a battery diagnostic device according to any one of paragraphs 1 through 10.

14. A data acquisition step for acquiring diagnostic data including at least one of battery information of a target battery and driving information of a vehicle including the target battery during a predetermined period from a diagnostic reference point; A threshold setting step for setting a threshold based on reference data corresponding to the above-mentioned predetermined period and a preset model; A diagnostic value setting step for calculating a diagnostic value based on the above diagnostic data and the above model; and A battery diagnostic method comprising a diagnostic step for diagnosing the state of the target battery based on the above threshold value and the above diagnostic value.

15. A data acquisition step for acquiring diagnostic data including at least one of battery information of a target battery and driving information of a vehicle including the target battery during a predetermined period from a diagnostic reference point; A threshold setting step for setting a threshold based on reference data corresponding to the above-mentioned predetermined period and a preset model; A diagnostic value setting step for calculating a diagnostic value based on the above diagnostic data and the above model; and A computer-readable recording medium storing a computer program for executing a battery diagnostic method comprising a diagnostic step of diagnosing the state of the target battery based on the above threshold value and the above diagnostic value.

Images