Battery management device and method

Abstract

A battery management device according to one embodiment of the present invention may include a data acquisition unit that acquires at least one of battery information including voltage, current, and temperature, and a control unit that determines a data distribution of the battery based on the acquired battery information, determines a matching probability between a plurality of target experimental data acquired in advance and the data distribution, determines a score for each of the plurality of target experimental data based on the battery information, and calculates the matching probability corresponding to the score for each of the plurality of target experimental data to calculate a stress score for the battery.

Description

[Technical field]

[0001] The present invention claims the benefit of priority based on Korean Patent Application No. 10-2022-0042555, filed on April 5, 2022, and all contents disclosed in the documents of the Korean patent application are incorporated as part of this specification. The present invention relates to a battery management device and method. [Background technology]

[0002] In recent years, the demand for portable electronic products such as laptops, video cameras, and mobile phones has increased dramatically, and the development of electric vehicles, energy storage batteries, robots, satellites, and other products has progressed in earnest. As a result, research into high-performance batteries that can be repeatedly charged and discharged is being actively conducted.

[0003] Currently commercially available batteries include nickel-cadmium batteries, nickel-metal hydride batteries, nickel-zinc batteries, and lithium batteries. Among these, lithium batteries are attracting attention due to their advantages over nickel-based batteries, such as the almost complete absence of memory effect, which allows for free charging and discharging, a very low self-discharge rate, and a high energy density.

[0004] Although much research has been done on these batteries to increase their capacity and density, it is also important to improve their lifespan and safety. To achieve this, it is necessary to suppress the decomposition reaction with the electrolyte on the electrode surface and to prevent overcharging and overdischarging.

[0005] In order to prevent such overcharging and over-discharging and to improve the life and safety of batteries, it is necessary to develop a technology that can provide users with the current battery status and provide guidelines for it. Summary of the Invention [Problem to be solved by the invention]

[0006] The present invention has been devised to solve the above problems, and has an object to provide users with a score based on the life and safety of a battery.

[0007] Other objects and advantages of the present invention can be understood from the following description and can be more clearly understood from the embodiments of the present invention. Also, it can be easily understood that the objects and advantages of the present invention can be realized by the means and combinations thereof as set forth in the claims. [Means for solving the problem]

[0008] A battery management device according to one embodiment of the present invention is characterized in that it includes: a data acquisition unit configured to acquire at least one of battery information including voltage, current, and temperature; and a control unit configured to determine a data distribution of a battery based on the acquired battery information, determine a matching probability between a plurality of target experimental data acquired in advance and the data distribution, determine a score for each of the plurality of target experimental data based on the battery information, and calculate the matching probability corresponding to the score for each of the plurality of target experimental data to calculate a stress score for the battery.

[0009] A battery management device according to one embodiment of the present invention is characterized in that the control unit is configured to determine a type based on whether the acquired battery information is information while driving or information while charging, and to determine the multiple target experimental data corresponding to the determined type from among multiple experimental data acquired in advance.

[0010] In one aspect of the present invention, the battery management device is characterized in that the control unit is configured to calculate a frequency of each area of ​​the battery information to determine a data distribution of the battery.

[0011] A battery management device according to one embodiment of the present invention is characterized in that the control unit is configured to determine the matching probability for each of the plurality of target experimental data based on a frequency by region for the battery information and a frequency by region for each of the plurality of target experimental data.

[0012] A battery management device according to one embodiment of the present invention is characterized in that the control unit is configured to determine the matching probability for each region based on the similarity between the frequency of each target experimental data relative to the sum of the frequency of each region of the plurality of target experimental data and the frequency of each region for the battery information.

[0013] A battery management device according to one embodiment of the present invention is characterized in that the control unit is configured to add up one or more similarities calculated for each of the multiple target experimental data, and determine the matching probability corresponding to each of the multiple target experimental data.

[0014] A battery management device according to one aspect of the present invention is characterized in that the control unit is configured to determine the score based on a table for each of the plurality of target experimental data that is preset for each of the plurality of target experimental data.

[0015] In a battery management device according to one embodiment of the present invention, the table for each experimental condition is configured to be preset for experimental conditions including at least one of experimental temperature, charging current, discharging current, maximum State Of Charge (SOC), minimum SOC, and State Of Health (SOH) corresponding to the number of charge / discharge cycles of the target experimental data, and the control unit determines the score for the number of charge / discharge cycles at which the SOH reaches a threshold value.

[0016] A battery management device according to one aspect of the present invention is characterized in that when the control unit receives a request message for the stress score, it is configured to generate a response message including the stress score and output the generated response message.

[0017] A battery management device according to one embodiment of the present invention is characterized in that the control unit is configured to further include at least one of a driving guide and a charging guide corresponding to the stress score in the response message.

[0018] A battery pack according to an aspect of the present invention may include a battery management device according to an aspect of the present invention. A server according to an aspect of the present invention may include the battery management device according to an aspect of the present invention.

[0019] A battery management method according to one embodiment of the present invention includes the steps of acquiring at least one of battery information of voltage, current, and temperature, determining a data distribution of the battery based on the acquired battery information, determining a matching probability between a plurality of target experimental data acquired in advance and the data distribution, determining a score for each of the plurality of target experimental data based on the battery information, and calculating the matching probability corresponding to the score for each of the plurality of target experimental data to calculate a stress score for the battery. Effect of the Invention

[0020] According to one aspect of the present invention, the life and safety of a battery can be scored and provided to a user. According to another aspect of the present invention, advanced techniques such as normalization and / or statistically variable thresholds can be applied to calculate the stress score of a battery to accurately diagnose the life and safety of the battery.

[0021] In addition, according to another aspect of the present invention, time series data regarding stress scores determined based on a statistical variable threshold can be analyzed to precisely detect the time and / or period when battery stress occurs. The effects of the present invention are not limited to those mentioned above, and other effects not mentioned herein will be clearly understood by those skilled in the art from the description of the claims. [Brief description of the drawings]

[0022] The following drawings attached to this specification serve to further understand the technical concept of the present invention together with the detailed description of the invention described below, and therefore the present invention should not be interpreted as being limited only to the matters described in the drawings.

[0023] [Figure 1] FIG. 1 illustrates a battery system according to one embodiment disclosed herein. [Diagram 2] FIG. 1 is a block diagram illustrating a battery management device according to an embodiment of the present document. [Diagram 3] FIG. 1 is a diagram illustrating a method for determining a matching probability that is referred to in various embodiments disclosed herein. [Figure 4] FIG. 13 is a diagram for explaining a method for determining scores for each of a plurality of target experimental data referred to in various embodiments disclosed herein. [Diagram 5] FIG. 13 is a diagram for explaining a response message referenced in various embodiments disclosed in this document. [Figure 6] FIG. 11 is another diagram for explaining a response message referenced in various embodiments disclosed in this document. [Figure 7] FIG. 1 is a schematic diagram illustrating a battery management method according to an embodiment disclosed herein. [Figure 8] FIG. 2 illustrates an exemplary configuration of a battery pack including a battery management device according to an embodiment disclosed herein. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0024] The terms and words used in this specification and the claims should not be interpreted in a limited manner to their ordinary or dictionary meanings, but should be interpreted in a manner that is consistent with the technical idea of ​​the present invention, based on the principle that the inventors can appropriately define the concepts of terms in order to best describe their invention.

[0025] Therefore, it should be understood that the embodiment described in this specification and the configurations shown in the drawings are merely the most preferred embodiment of the present invention and do not represent the entire technical idea of ​​the present invention, and therefore there may be various equivalents and modifications that can replace them at the time of this application.

[0026] In addition, when describing the present invention, if it is determined that a detailed description of related known configurations or functions may unnecessarily obscure the gist of the present invention, the detailed description will be omitted.

[0027] Terms including ordinal numbers such as "first," "second," etc. are used to distinguish one of various components from the rest, and are not used to limit the components by the term.

[0028] Throughout the specification, when a part is said to include certain elements, this means that it may further include other elements, not excluding other elements, unless specifically stated to the contrary.

[0029] Furthermore, throughout the specification, when a part is said to be "connected" to another part, this includes not only "directly connected" but also "indirectly connected" through another element therebetween.

[0030] FIG. 1 is a diagram showing a battery system 1 according to an embodiment disclosed in the present document. Referring to FIG. 1, the battery system 1 may be configured to include a battery management device 100 and the like. However, this is merely a preferred embodiment for achieving the object of the present invention, and it goes without saying that some components may be added or deleted as necessary. In addition, it should be noted that each component of the battery system 1 shown in FIG. 1 shows a functional element that is functionally divided, and that multiple components may be realized in a form that is integrated with each other in an actual physical environment.

[0031] In the battery system 1, the battery management device 100 is a computing device that provides battery management based on stress scores to multiple users. Here, the computing device may be, but is not limited to, a notebook computer, a desktop computer, a laptop computer, etc., and may include all types of devices equipped with computing and communication functions. However, in the case of providing battery management to multiple users, it is preferable that the battery management device 100 is realized by a high-performance server computing device.

[0032] According to an embodiment, battery management may refer to a service provided to a user for improving the lifespan of a battery based on a stress score. Here, the stress score may refer to a score representing the impact of experiences and environments occurring in the charging and discharging state of a battery installed in a vehicle (e.g., the running state of the vehicle and / or the charging state of the battery) on the lifespan of the battery.

[0033] Generally, a battery cell refers to an independent cell that has a negative terminal and a positive terminal and can be physically separated. As an example, a lithium ion battery or a lithium polymer battery can be considered as a battery cell. A plurality of battery cells can be connected in series and / or parallel to form a battery module, and a plurality of battery modules can be connected in series and / or parallel to form a battery pack. The battery for which the stress score is calculated and provided by the battery management device 100 may be a battery pack provided in a vehicle.

[0034] According to an embodiment of the present invention, the battery management device 100 can receive battery information from a BMS (Battery Management System) 50 and calculate a stress score for the battery based on the battery information. The battery information may mean data including at least one of information on the voltage, current, and temperature of the battery. According to an embodiment of the present invention, the battery management device 100 can calculate a stress score based on a plurality of target experimental data previously acquired.

[0035] In the battery system 1, the BMS 50 is provided in a vehicle and can transmit information related to a battery provided in the vehicle. Specifically, the BMS 50 can transmit at least one of information on the voltage, current, and / or temperature of the battery to the battery management device 100. Depending on the embodiment, the BMS 50 may transmit information to the battery management device 100 in real time or at regular time intervals, but is not limited thereto.

[0036] The BMS 50 may be implemented in a computing device that is physically separate from the battery management device 100, or may be implemented in the battery management device 100, which may vary depending on the embodiment.

[0037] According to an embodiment, the battery management device 100 according to the present invention can be applied to a BMS. That is, the BMS according to the present invention can include the above-described battery management device 100. In such a configuration, at least a part of the components of the battery management device 100 can be realized by complementing or adding functions of components included in a conventional BMS. For example, the data acquisition unit 110 and / or the control unit 120 of the battery management device 100 described below can be realized as components of a BMS.

[0038] In the following, the explanation will be continued on the assumption that the BMS 50 is constructed in a computing device that is physically separate from the battery management device 100. In the battery system 1, the user terminal 30 is a computing device including a display that transmits a request for a stress score and outputs response data including the stress score. Here, the computing device may be, but is not limited to, a notebook computer, a desktop computer, a laptop computer, etc., and may include all types of devices equipped with computing and communication functions. The user terminal 30 may be constructed in a computing device that is physically independent from the battery management device 100, or may be constructed in the battery management device 100, which may vary depending on the embodiment. Hereinafter, the description will be continued assuming that the user terminal 30 is constructed in a computing device that is physically independent from the battery management device 100.

[0039] In one embodiment, the user terminal 30 may display response data that visualizes the stress score. The battery management device 100 may receive a request for a stress score via the user terminal, and provide response data including the stress score in response to the received request. In this case, the battery management device 100 may provide a predetermined user interface for the response data to induce user feedback, and the user may provide user feedback information regarding the satisfaction level of the response data via the interface. The battery management device 100 may improve user satisfaction when calculating the stress score by reflecting the user feedback information.

[0040] The components of the battery system 1 can communicate with each other via a network, which can be any type of wired / wireless network, such as a local area network (LAN), a wide area network (WAN), a mobile radio communication network, or Wibro (Wireless Broadband Internet).

[0041] Up to now, a battery system 1 according to one embodiment of the present invention has been described with reference to Fig. 1. Below, the configuration and operation of a battery management device 100 according to one embodiment of the present invention will be described with reference to Figs. 2 to 6.

[0042] 2 is a block diagram illustrating a battery management device 100 according to an embodiment of the present document. Referring to FIG. 2, the battery management device 100 according to an embodiment disclosed herein may include a data acquisition unit 110 and a control unit 120.

[0043] The data acquisition unit 110 may be configured to acquire at least one of the battery information: voltage, current, and temperature. Specifically, the data acquiring unit 110 may acquire information related to the battery for which the stress score is to be calculated. According to an embodiment, the data acquiring unit 110 may acquire information related to the battery for which the stress score is to be calculated from the BMS 50. The information related to the battery may include information related to at least one of the voltage, current, and temperature of the battery.

[0044] The data acquisition unit 110 may acquire information related to the battery from the BMS 50 in real time, or may acquire the information according to a set cycle. Alternatively, the data acquisition unit 110 may acquire information related to the battery from the BMS 50 when a previously set event occurs, but is not limited to this. If data is not acquired from the BMS 50, the data acquisition unit 110 can transmit a request to the BMS 50 for the provision of data.

[0045] The control unit 120 can determine the data distribution of the battery based on the acquired battery information. According to an embodiment, the control unit 120 may determine the data distribution of the battery by calculating the frequency of each area of ​​the battery information. Here, the frequency of each area may refer to the frequency of each area of ​​the battery information.

[0046] For example, it is assumed that the battery information includes voltage. The control unit 120 may divide the battery voltage range into predetermined units (e.g., 0.1 V) in a preset voltage range and calculate the frequency of each range to which the battery information belongs in each range. The control unit 120 may then determine the battery data distribution according to the calculated frequency of each range.

[0047] The control unit 120 may be configured to determine a matching probability between a plurality of previously acquired target experimental data and the data distribution. Specifically, the control unit 120 may determine a matching probability for each of the plurality of target experimental data based on the frequency of each region of the battery information and the frequency of each region of the plurality of target experimental data, which will be described in detail with reference to FIG.

[0048] FIG. 3 is a diagram for explaining a method for determining a matching probability referred to in various embodiments disclosed in this document. FIG. 3 shows a table showing the frequency of each region (f1 to f10) for a plurality of target experimental data (p1 to p4). Here, f1 to f10 may be regions in which the entire region (0% to 100%) is allocated at 10% each. For example, f1 may be a region that is 0% or more and less than 10% of the entire region, f2 may be a region that is 10% or more and less than 20% of the entire region, and f10 may be a region that is 90% or more and less than 100% of the entire region.

[0049] Before describing FIG. 3, it is assumed that the frequency of occurrence of each area of ​​the battery information is 10% for f1, 30% for f2, and 60% for f3. According to an embodiment, the control unit 120 can determine the matching probability for each of the multiple target experimental data (p1 to p4) using the frequency of each region for the battery information. For example, the frequency of each region for p1 is f1, which is 100%, and the remaining regions are all 0%. As another example, the frequency of each region for p2 is f1, which is 0%, and f2 and f3, which are each 50%.

[0050] According to an embodiment, the control unit 120 may determine a similarity between the frequency of each target experimental data relative to the sum of the frequencies of a plurality of target experimental data for each region and the frequency of the battery information, and may determine a matching probability based on the similarity.

[0051] Taking f1 as an example, the control unit 120 can determine the similarity of p1 to f1 by multiplying the frequency for the battery information by "(the frequency for p1 to f1)÷(the sum of the frequencies for p1 to p4 to f1)".

[0052] The sum of the frequency counts of multiple target experimental data for f1 is 100+0+0+0, which is 100, and the frequency count of p1 for f1 is 100. Since the frequency count for the battery information is assumed to be 10%, the control unit 120 can determine the value obtained by multiplying 10% by (100÷100) as the similarity of p1 for f1. Therefore, the control unit 120 can determine the similarity of p1 for f1 to be 10% or 0.1.

[0053] In a similar manner, the control unit 120 can determine the similarity of p2 to p4 to f1. Referring to Fig. 3, since the frequency of occurrence of p2 to p4 to f1 is 0, the control unit 120 can determine the similarity of p2 to p4 to f1 to be 0.

[0054] According to an embodiment, the control unit 120 may determine the matching probability corresponding to each of the plurality of target experimental data by summing up one or more similarities calculated for each of the plurality of target experimental data.

[0055] Taking p1 as an example, as described above, the control unit 120 can set the similarity to f1 to 0.1, and set the similarities to all of the remaining areas (f2 to f10) to 0, since the frequency counts of p1 for all of the remaining areas (f2 to f10) are 0. Therefore, when the similarities by region of p1 are added up, the control unit 120 can determine the matching probability of p1 to be 0.1.

[0056] In a similar manner, the control unit 120 can determine the matching probabilities of p2 to p4. Referring to Fig. 3, the control unit 120 can determine the matching probabilities of p2 to p4 to be 0.72, 0.09, and 0.09, respectively.

[0057] The operation of the control unit 120 for determining the matching probability has been described above in detail with reference to Fig. 3. The operation of the control unit will be described with reference to Fig. 2 again. The control unit 120 may determine a score for each of a plurality of target experimental data based on the acquired battery information.

[0058] According to an embodiment, the control unit 120 may determine a score for each of a plurality of target experimental data based on a preset table for each experimental condition.

[0059] Here, the table according to the preset experimental conditions may refer to a table for the result data of a battery deterioration experiment carried out in an environment limited by a specific condition. For example, the table according to the experimental conditions may refer to a table for battery deterioration experiment data carried out by giving conditions to at least one area of ​​the battery temperature, the charge current, the discharge current, the minimum SOC, the maximum SOC, and the SOH according to the number of charge and discharge cycles of the target experimental data. This will be described in detail with reference to FIG. 4.

[0060] 4 is a diagram for explaining a method of determining scores for each of a plurality of target experimental data referred to in various embodiments disclosed herein. In FIG. 4, an example diagram is shown in which data acquired from a battery deterioration experiment conducted in a restricted environment is converted into a table for each experimental condition.

[0061] According to an embodiment, the control unit 120 may process data acquired from a battery degradation experiment conducted in a restricted environment to generate a State Of Health (SOH) profile according to cycles. A cycle may refer to a value quantified by assuming one cycle of charging and discharging a battery.

[0062] For example, one cycle may mean that the battery was charged from 0% to 100% State Of Charge (SOC) and discharged from 100% to 0% SOC, i.e., one cycle may mean that the battery was fully charged and fully discharged.

[0063] As another example, 0.5 cycles may mean that the battery was charged so that its SOC increased by 50% and discharged so that its SOC decreased by 50%. That is, 0.5 cycles may mean that the battery was charged from the start-of-charge SOC to the end-of-charge SOC and discharged from the end-of-charge SOC to the start-of-charge SOC. Here, the SOC difference between the start-of-charge SOC and the end-of-charge SOC may be 50%.

[0064] According to an embodiment, the control unit 120 may determine a score for the number of charge / discharge cycles at which the calculated SOH reaches a threshold value. The threshold value may be a value determined for the battery or may be a value specified by a user. Alternatively, the threshold value may refer to, but is not limited to, a statistical variable value.

[0065] According to an embodiment, the control unit 120 may input a cycle value corresponding to a point where the SOH is a threshold value for each of a plurality of target experimental data into the table by experimental condition. The threshold value may be a value set according to the kind and / or type of battery, or may be a value set according to a user request. Alternatively, the threshold value may be, but is not limited to, a statistically variable threshold value. FIG. 4 illustrates a case where the threshold value is 95%.

[0066] Referring to FIG. 4, the control unit 120 may input a cycle value corresponding to a point where the SOH is 95% for each of a plurality of target experimental data, into a table for each experimental condition, using the SOH profile according to the cycle.

[0067] The control unit 120 may determine a score for each of the plurality of target experimental data using the input cycle value. According to an embodiment, the control unit 120 may determine a score by interpolating an experimental value for each of the plurality of target experimental data using a standard condition. For example, if the temperature of the standard condition is 25 degrees, the control unit 120 may determine a score by interpolating a value for temperature among experimental values ​​for each of the plurality of target experimental data based on 25 degrees. The standard condition may mean a condition that is a reference for evaluating experimental data. For example, FIG. 4 shows that the standard condition is a temperature of 25 degrees, a charging current and a discharging current of 1 / 3C, and an SOC between 0% and 100%.

[0068] The control unit 120 may determine the target experimental data (401) corresponding to the standard condition as standard data and assign a score of 50 to the standard data. The control unit 120 may assign a score of 100 to the target experimental data that is more than twice the cycle value of the standard data, as shown in FIG.

[0069] For example, in the embodiment of Figure 4, assume that the cycle value of the standard data is 667.70. Twice the cycle value of the standard data is 1335.4. Therefore, the number of target experimental data with cycle values ​​of 1335.4 or more can be determined to be 100 points.

[0070] 2, the control unit 120 may calculate a stress score for the battery by calculating a matching probability corresponding to a score for each of a plurality of target experimental data. According to an embodiment, the control unit 120 may calculate a stress score for each of a plurality of target experimental data by adding up all values ​​obtained by multiplying the score of each target experimental data by the matching probability.

[0071] According to an embodiment, the control unit 120 may classify target experimental data having a matching probability equal to or greater than a threshold among a plurality of target experimental data into a first group, and calculate a stress score by adding up a value obtained by multiplying the score for each target data included in the first group by the corresponding matching probability.

[0072] According to an embodiment, when the number of target experimental data included in the first group is less than the threshold, the control unit 120 may interpolate the matching probability value of the target data or adjust the threshold for the matching probability.

[0073] According to an embodiment, the control unit 120 may classify target experimental data whose region-specific similarity is equal to or greater than a threshold into a second group, and calculate a stress score by summing up a value obtained by multiplying the score for each target experimental data included in the second group by the corresponding matching probability.

[0074] According to an embodiment, when the number of target experimental data included in the second group is less than the threshold, the control unit 120 may interpolate similarity values ​​for each region of the target data or adjust a threshold for similarity values.

[0075] According to an embodiment, the control unit 120 may calculate a stress score for the first group as a first stress score and a stress score for the second group as a second stress score, and provide the first and second stress scores to the user. The control unit 120 calculates and provides different stress scores for different groups, thereby satisfying the various needs of users.

[0076] Meanwhile, the control unit 120 may selectively 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. Also, when the control logics are implemented in software, the control unit 120 may be implemented as a collection of program modules. In this case, the program modules may be stored in a memory and executed by the control unit 120. The memory may be internal or external to the control unit 120, and may be connected to the control unit by various known means.

[0077] The battery management device 100 may further include a storage unit (not shown). The storage unit may store data and programs required for each component of the battery management device 100 to operate and function, or data generated in the process of operating and functioning. The storage unit may be of any type as long as it is a known information storage means known to be capable of recording, erasing, updating, and reading data. As an example, the information storage means may include a RAM, a flash memory, a ROM, an EEPROM, a register, and the like. The storage unit may also store program code that defines a process executable by the control unit 120.

[0078] For example, the storage unit may include a plurality of experimental data and information related thereto, and the control unit 120 may access the storage unit to obtain a plurality of experimental data and tables for each experimental condition.

[0079] The control unit 120 can be configured to determine a matching probability between a plurality of previously acquired target experimental data and the data distribution. Here, the target experimental data may be experimental data selected by the control unit 120 from among the plurality of experimental data. According to an embodiment, the control unit 120 may determine the type of information based on whether the acquired battery information is information during driving or information during charging. Then, the control unit 120 may determine at least one data corresponding to the determined type from among the plurality of experimental data previously acquired as the target experimental data.

[0080] For example, if the acquired battery information is determined to be an information type of information on driving, the control unit 120 may determine only experimental data, of a plurality of previously acquired experimental data, whose information type is information on driving, as the target data.

[0081] The control unit 120 can score the matching probability regarding the information type during driving and the matching probability regarding the information type during charging, respectively. Then, the control unit 120 can calculate a stress score for the battery by combining the scores regarding the information types during driving and charging.

[0082] That is, the battery management unit 100 can calculate the stress score of the battery by taking into account the state of the battery (charging or discharging (vehicle running)). Therefore, the stress score calculated by the battery management unit 100 can more accurately reflect the current life state of the battery.

[0083] In addition, when the control unit 120 receives a request message for the stress score, the control unit 120 may generate a response message including the stress score, and may output the generated response message.

[0084] According to an embodiment, the control unit 120 may generate a response message further including a driving guide corresponding to the stress score. The driving guide may refer to a driving habit and / or a charging habit. According to an embodiment, the control unit 120 may determine a driving guide to be included in the response message from one or more pre-stored driving guides.

[0085] According to an embodiment, the control unit 120 may determine a driving guide based on the stress score and / or data included in the acquired battery information. For example, the control unit 120 may calculate values ​​for temperature, charging current, discharge rectification, and / or SOC based on data included in the acquired battery information, and determine a driving guide based on the calculated result value and the stress score. This will be described in detail with reference to FIGS. 5 and 6.

[0086] 5 is a diagram for explaining a response message referred to in various embodiments disclosed in this document, in which an example of a response message including a stress score and a driving guide is shown.

[0087] The control unit 120 may display the calculated stress score (501) together with the average stress score (avg, 502) of the battery. The control unit 120 may display and present a target stress score range (503) based on the average stress score.

[0088] The control unit 120 can calculate values ​​for temperature, charging current, discharging current, and / or SOC based on the data included in the acquired battery information, and determine driving guidance based on the calculated results and stress score. 5 shows a charging recommendation management message (511) and an SOC recommendation management message (512) as examples of operation guides. The charging recommendation management message (511) may include a recommendation to develop a habit of charging the vehicle at a slow speed with a normal charger rather than fast charging. The SOC recommendation management message (512) may include a recommendation to lower the target remaining battery capacity when the remaining battery capacity is very high.

[0089] 6 is another diagram for explaining a response message referred to in various embodiments disclosed herein, in which an example of a detailed message for a stress score is shown.

[0090] According to an embodiment, when the control unit 120 receives a request for a stress score, the control unit 120 may output a response message including a detail page together with the stress score.

[0091] According to an embodiment, when the control unit 120 receives a request for a stress score, it can output a response message including the stress score, and when it receives additional input regarding the stress score included in the output response message, it can output a detailed message. As shown in FIG. 6, the detailed message may include detailed information regarding an analysis of driving habits and an analysis of charging habits according to stress scores.

[0092] Hereinafter, the battery management method will be described in detail with reference to FIG. FIG. 7 is a schematic diagram illustrating a battery management method according to one embodiment disclosed herein.

[0093] Preferably, each step of the battery management method may be performed by the battery management device 100. Hereinafter, the contents that overlap with the above contents will be omitted or will be briefly described.

[0094] Referring to FIG. 7, a battery management method according to one embodiment disclosed in this document may include a step of acquiring battery information (S100), a step of determining a data distribution (S200), a step of determining a matching probability (S300), a step of determining a score (S400), and a step of calculating a stress score (S500).

[0095] Steps S100 to S500 will be specifically described below with reference to FIG. 1 and FIG. Step S100 is a step of acquiring at least one of battery information of voltage, current, and temperature, and can be performed by the data acquiring unit 110.

[0096] In step S100, the data acquisition unit 110 can acquire information related to the battery for which the stress score is to be calculated. According to an embodiment, the data acquisition unit 110 can acquire information related to the battery for which the stress score is to be calculated from the BMS 50.

[0097] The data acquisition unit 110 may acquire information about the battery from the BMS 50 in real time, or may acquire the information according to a set cycle. Alternatively, the data acquisition unit 110 may acquire the information when a previously set event occurs, but is not limited to this. If data is not acquired from the BMS 50, the data acquisition unit 110 can transmit a request for data provision to the BMS 50 or the user terminal 30.

[0098] Step S200 is a step of determining a data distribution of the battery based on the battery information acquired in step S100, and can be performed by the control unit 120.

[0099] In step S200, the control unit 120 may determine a data distribution of the battery based on the acquired battery information. According to an embodiment, the control unit 120 may determine a type of information based on whether the acquired battery information is information on a running state or information on a charging state. The control unit 120 may determine at least one data corresponding to the determined type among a plurality of experimental data previously acquired as target experimental data. For example, when the acquired battery information is determined to be an information type on a running state, the control unit 120 may determine experimental data having an information type of information on a running state among a plurality of experimental data previously acquired as target data. The control unit 120 determines the target experimental data based on the type of information, thereby improving accuracy in calculating the stress score.

[0100] According to an embodiment, the control unit 120 may determine the data distribution of the battery by calculating the frequency of each region of the battery information. The frequency of each region may mean the frequency of each region included in the battery information. For example, if the battery information includes information on voltage, current, and temperature, the frequency of each region may mean the frequency of each region of the voltage region, the current region, and the temperature region.

[0101] Step S300 is a step of determining a matching probability between a plurality of target experimental data previously acquired and a data distribution, and can be performed by the control unit 120.

[0102] In step S300, the control unit 120 may determine a matching probability for each of the plurality of target experimental data based on the frequency of each region of the battery information and the frequency of each region of each of the plurality of target experimental data.

[0103] According to an embodiment, the control unit 120 may determine a similarity between the frequency of each experimental data with respect to the sum of the frequencies of a plurality of target experimental data for each region and the frequency of the battery information, and may determine a matching probability based on the similarity.

[0104] According to an embodiment, the control unit 120 may determine the matching probability corresponding to each of the plurality of target experimental data by summing up one or more similarities calculated for each of the plurality of target experimental data.

[0105] Step S400 is a step of determining a score for each of the plurality of target experimental data based on the battery information, and can be performed by the control unit 120.

[0106] In step S400, the control unit 120 may determine a score for each of a plurality of target experimental data based on the acquired battery information. According to an embodiment, the control unit 120 may determine a score for each of a plurality of target experimental data based on a table for each of the plurality of target experimental data that is preset. The table for each of the preset experimental conditions may refer to result data from a battery deterioration experiment that is conducted in an environment limited by a specific condition. For example, the table for each of the experimental conditions may refer to a table for target experimental data from a battery deterioration experiment that is conducted by applying conditions to at least one of the following areas: battery temperature, charging current, discharging current, minimum SOC, maximum SOC, and SOH according to the number of charging and discharging of the target experimental data.

[0107] According to an embodiment, the control unit 120 may process data acquired from a battery degradation experiment conducted in a restricted environment to generate a SOH profile according to cycles.

[0108] The cycle may refer to a value quantified as one cycle of charging and discharging a battery. For example, one cycle may refer to one charge and discharge of a battery based on SOC 0% and SOC 100%.

[0109] According to an embodiment, the control unit 120 may determine a score for the number of charge / discharge cycles at which the calculated SOH reaches a threshold value. The threshold value may be a value determined for the battery or may be a value designated by the user.

[0110] According to an embodiment, the control unit 120 may input a cycle value corresponding to a point where the SOH is a threshold value for each of the plurality of target experimental data to the table for each experimental condition. The control unit 120 may determine a score for each of the plurality of target experimental data using the input cycle value.

[0111] According to an embodiment, the control unit 120 may determine scores by interpolating values ​​for each of a plurality of target experimental data using a standard condition. The standard condition may refer to a standard condition for evaluating the experimental data.

[0112] Step S500 is a step of calculating a score for each of a plurality of target experimental data and a corresponding matching probability to calculate a stress score for the battery, and can be performed by the control unit 120.

[0113] In step S500, the control unit 120 may calculate a matching probability corresponding to the scores for each of a plurality of target experimental data to calculate a stress score for the battery.

[0114] According to an embodiment, the control unit 120 may calculate a stress score for each of a plurality of target experimental data by summing up all values ​​obtained by multiplying the score of each target experimental data by the matching probability.

[0115] According to an embodiment, the control unit 120 may classify target experimental data having a matching probability equal to or greater than a threshold among a plurality of target experimental data into a first group, and calculate a stress score by adding up a value obtained by multiplying the score for each target data included in the first group by the corresponding matching probability.

[0116] According to an embodiment, when the number of target experimental data included in the first group is less than the threshold, the control unit 120 may interpolate the matching probability value of the target data or adjust the threshold for the matching probability.

[0117] According to an embodiment, the control unit 120 may classify target experimental data whose region-specific similarity is equal to or greater than a threshold into a second group, and calculate a stress score by summing up a value obtained by multiplying the score for each target experimental data included in the second group by the corresponding matching probability.

[0118] According to an embodiment, when the number of target experimental data included in the second group is less than the threshold, the control unit 120 may interpolate similarity values ​​for each region of the target data or adjust a threshold for similarity values.

[0119] According to an embodiment, the control unit 120 may calculate a stress score for the first group as a first stress score and a stress score for the second group as a second stress score, and provide the first and second stress scores to the user. The control unit 120 calculates and provides different stress scores for different groups, thereby satisfying the various needs of users.

[0120] The battery management device 100 according to the present invention can be provided in a battery pack 1000. That is, the battery pack according to the present invention can include the above-mentioned battery management device 100 and one or more battery cells. The battery pack can further include electrical components (relays, fuses, etc.), a case, etc.

[0121] 8 is a diagram showing an example configuration of a battery pack including a battery management device according to an embodiment disclosed herein. The positive terminal of the battery 10 can be connected to the positive terminal (P+) of the battery pack 1000, and the negative terminal of the battery 10 can be connected to the negative terminal (P-) of the battery pack 1000.

[0122] The measurement unit 200 may be connected to a first sensing line (SL1), a second sensing line (SL2), and a third sensing line (SL3). Specifically, the measurement unit 20 may be connected to a positive terminal of the battery 10 via the first sensing line (SL1) and to a negative terminal of the battery 10 via the second sensing line (SL2). The measurement unit 20 may measure the voltage of the battery 10 based on the voltages measured in the first sensing line (SL1) and the second sensing line (SL2), respectively.

[0123] The measurement unit 200 may be connected to the current measurement unit (A) via a third sensing line (SL3). For example, the current measurement unit (A) may be an ammeter or a shunt resistor capable of measuring the charging current and discharging current of the battery 10. The measurement unit 20 may measure the charging current of the battery 10 via the third sensing line (SL3) to calculate the charging amount. The measurement unit 200 may also measure the discharging current of the battery 10 via the third sensing line (SL3) to calculate the discharging amount.

[0124] The load 300 may have one end connected to the positive terminal (P+) of the battery pack 1000 and the other end connected to the negative terminal (P-) of the battery pack 1000. Thus, the positive terminal of the battery 10, the positive terminal (P+) of the battery pack 1000, the load 300, the negative terminal (P-) of the battery pack 1000, and the negative terminal of the battery 10 may be electrically connected to each other.

[0125] For example, the load 300 may be a charge / discharge device, or may be a motor of an electric vehicle that receives power from the battery 10. The data acquiring section 110 can acquire at least one of the battery information items of voltage, current, and temperature from the measuring section 200.

[0126] The embodiments of the present invention described above may be realized not only through an apparatus and a method, but also through a program that realizes functions corresponding to the configuration of the embodiments of the present invention or a recording medium on which the program is recorded. Such realization can be easily achieved by an expert in the technical field to which the present invention pertains from the description of the above-mentioned embodiments.

[0127] Although the present invention has been described above using limited embodiments and drawings, the present invention is not limited thereto, and it goes without saying that various modifications and variations can be made by a person having ordinary knowledge in the technical field to which the present invention pertains within the technical spirit of the present invention and the scope of the claims described below.

[0128] Furthermore, the present invention described above is not limited to the above-described embodiments and the accompanying drawings, as various substitutions, modifications, and changes can be made by a person having ordinary knowledge in the technical field to which the present invention pertains, without departing from the technical spirit of the present invention. Instead, the present invention may be configured by selectively combining all or part of each embodiment to effect various modifications.

[0129] Therefore, the embodiments disclosed in this document are intended to explain, not to limit, the technical ideas disclosed in this document, and such embodiments do not limit the scope of the technical ideas disclosed in this document. The scope of protection of the technical ideas disclosed in this document should be interpreted according to the claims below, and all technical ideas within the equivalent scope should be interpreted as being included in the scope of rights of this document.

Claims

1. a data acquisition unit that acquires at least one of battery information including voltage, current, and temperature; a control unit that determines a data distribution of a battery based on the acquired battery information, determines a matching probability between a plurality of target experimental data acquired in advance and the data distribution, determines a score for each of the plurality of target experimental data based on the battery information, and calculates the matching probability corresponding to the score for each of the plurality of target experimental data to calculate a stress score for the battery; A battery management device comprising:

2. The control unit is determining a type of the acquired battery information based on whether the acquired battery information is information during driving or information during charging; The battery management device according to claim 1 , further comprising: determining, from among a plurality of pieces of pre-acquired experimental data, the plurality of target experimental data corresponding to the determined type.

3. The control unit is The battery management device of claim 1 , further comprising: a frequency of occurrence for each area of ​​the battery information to determine a data distribution of the battery.

4. The control unit is The battery management device according to claim 3 , further comprising: determining the matching probability for each of the plurality of target experimental data based on a frequency of occurrence for each region of the battery information and a frequency of occurrence for each of the plurality of target experimental data.

5. The control unit is The battery management device according to claim 4 , wherein the matching probability is determined for each region based on a similarity between the frequency of each target experimental data relative to a sum of the frequencies of the target experimental data by region and the frequency of the battery information by region.

6. The control unit is The battery management device according to claim 5 , further comprising: a sum of one or more similarities calculated for each of the plurality of target experimental data to determine the matching probability corresponding to each of the plurality of target experimental data.

7. The control unit is The battery management device according to claim 1 , wherein the score is determined based on a table for each of the plurality of target experimental data that is preset according to experimental conditions.

8. The table for each experimental condition is preset for an experimental condition including at least one of an experimental temperature, a charging current, a discharging current, a maximum State Of Charge (SOC), a minimum SOC, and an SOH according to the number of charging and discharging of the target experimental data, The control unit is The battery management device according to claim 7 , wherein the score is determined for a number of charge / discharge cycles at which the calculated State Of Health (SOH) reaches a threshold value.

9. The control unit is When a request message for the stress score is received, a response message including the stress score is generated; The battery management device according to claim 1 , further comprising: a controller configured to output the generated response message.

10. The control unit is The battery management device according to claim 9 , further comprising at least one of a driving guide and a charging guide corresponding to the stress score in the response message.

11. A battery pack comprising the battery management device according to any one of claims 1 to 10.

12. A server comprising the battery management device according to any one of claims 1 to 10.

13. obtaining at least one of battery information of voltage, current, and temperature; determining a data distribution of the batteries based on the acquired battery information; determining a matching probability between a plurality of target experimental data previously acquired and the data distribution; determining a score for each of the plurality of target experimental data based on the battery information; calculating the matching probability corresponding to the scores for each of the plurality of target experimental data to calculate a stress score for the battery; A battery management method comprising:

Images