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 this Korean patent application are incorporated herein by reference. The present invention relates to a battery management device and method. [Background technology]

[0002] In recent years, demand for portable electronic products such as laptops, video cameras, and mobile phones has increased dramatically, and as the development of electric vehicles, energy storage batteries, robots, and satellites has gained momentum, 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 of being free to charge and discharge as they have almost no memory effect compared to nickel-based batteries, an extremely low self-discharge rate, and a high energy density.

[0004] While 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 between the electrolyte and the electrode surface, and to prevent overcharging and overdischarging.

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

[0006] The present invention has been developed to solve the above problems, and aims 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 become more apparent from the embodiments of the present invention. Also, it can be easily seen 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 by including: a data acquisition unit configured to acquire at least one of battery information of 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 plurality of target experimental data corresponding to the determined type from among the plurality of experimental data acquired in advance.

[0010] In a battery management device according to an aspect of the present invention, 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 aspect 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 the frequency by region for the battery information and the 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 sum up one or more similarities calculated for each of the plurality of target experimental data, and determine the matching probability corresponding to each of the plurality of 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 one embodiment of the battery management device of the present invention, the table for each experimental condition is configured to be pre-set 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 charging and discharging of the target experimental data, and the control unit determines the score for the number of charging and discharging 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 aspect 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. [Effects 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 a battery's stress score to accurately diagnose the battery's lifespan and safety.

[0021] 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 interval at which battery stress occurs. The effects of the present invention are not limited to those mentioned above, and other effects not mentioned above will be apparent to those skilled in the art from the claims. [Brief explanation of the drawings]

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

[0023] [Figure 1] FIG. 1 illustrates a battery system according to one embodiment disclosed herein. [Figure 2] FIG. 1 is a block diagram illustrating a battery management device according to an embodiment of the present document. [Figure 3] FIG. 10 is a diagram illustrating a method for determining a matching probability that is referenced in various embodiments disclosed herein. [Figure 4] FIG. 10 is a diagram illustrating a method for determining scores for each of a plurality of target experimental data items referred to in various embodiments disclosed herein. [Figure 5] FIG. 10 is a diagram for explaining a response message referred to in various embodiments disclosed herein. [Figure 6] FIG. 10 is another diagram for explaining a response message referred to in various embodiments disclosed herein. [Figure 7] FIG. 1 is a diagram illustrating a battery management method according to an embodiment disclosed herein. [Figure 8] 1 illustrates an exemplary configuration of a battery pack including a battery management device according to an embodiment disclosed herein. DETAILED DESCRIPTION OF THE INVENTION

[0024] The terms and words used in this specification and claims should not be interpreted in a limited way to their ordinary or dictionary meanings, but should be interpreted in a way 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 explain their inventions.

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

[0026] Furthermore, when describing the present invention, if it is determined that a detailed description of related publicly known structures 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 elements from the rest, and are not used to limit the elements by that term.

[0028] Throughout the specification, when a part is said to include certain elements, this means that it may further include other elements, but not to the exclusion of other elements, unless otherwise specified.

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

[0030] FIG. 1 is a diagram illustrating a battery system 1 according to one embodiment disclosed herein. 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. It should be noted that the components of the battery system 1 illustrated in FIG. 1 are functionally separated functional elements, and that multiple components may be integrated into one another 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 any type of device equipped with computing and communication functions. However, when providing battery management to multiple users, the battery management device 100 is preferably implemented as a high-performance server computing device.

[0032] According to an embodiment, battery management may refer to a service provided to a user to improve 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 status of a battery installed in a vehicle (e.g., vehicle driving status and / or battery charging status) on the lifespan of the battery.

[0033] Generally, a battery cell refers to a single 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 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 installed 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 refer to 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 the 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 unit 100. Depending on the embodiment, the BMS 50 may transmit information to the battery management unit 100 in real time or at regular time intervals, but is not limited to this.

[0036] The BMS 50 may be implemented in a computing device that is physically separate from the battery management unit 100, or may be implemented in the battery management unit 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 some 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] The following description will be made 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 any type of device equipped with computing and communication functions. The user terminal 30 may be implemented as a computing device 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. The following description will be continued assuming that the user terminal 30 is implemented as a computing device physically separate 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 through 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 through the interface. The battery management device 100 may reflect the user feedback information to improve user satisfaction when calculating the stress score.

[0040] The components of the battery system 1 can communicate with each other via a network, which can be any type of wired or 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 can be configured to acquire at least one of the battery information: voltage, current, and temperature. Specifically, the data acquisition unit 110 may acquire information related to the battery for which the stress score is to be calculated. According to an embodiment, the data acquisition 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 the battery-related information from the BMS 50 in real time, or may acquire the information according to a predetermined cycle. Alternatively, the data acquisition unit 110 may acquire the battery-related information from the BMS 50 when a pre-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 data provision.

[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, assuming 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. Then, the control unit 120 may 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 target experimental data previously acquired 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, as will be described in detail with reference to FIG.

[0048] FIG. 3 is a diagram illustrating a method for determining matching probability, which is referred to in various embodiments disclosed herein. FIG. 3 shows a table displaying frequency counts for regions (f1 to f10) for multiple target experimental data (p1 to p4). Here, f1 to f10 may be regions obtained by allocating 10% of the entire region (0% to 100%). For example, f1 may be a region between 0% and 10% of the entire region, f2 may be a region between 10% and 20% of the entire region, and f10 may be a region between 90% and 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 plurality of target experimental data (p1 to p4) using the frequency counts for each region of the battery information. For example, the frequency counts for each region of p1 are 100% for f1 and 0% for the remaining regions. As another example, the frequency counts for each region of p2 are 0% for f1 and 50% for f2 and f3.

[0050] According to an embodiment, the control unit 120 may determine the similarity between the frequency of each target experimental data relative to the sum of the frequency of multiple target experimental data and the frequency of the battery information for each region, and determine the 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 count for the battery information by "(the frequency count for p1 to f1) / (the sum of the frequencies for p1 to p4 to f1)".

[0052] The sum of the frequencies of multiple target experimental data for f1 is 100+0+0+0, which is 100, and the frequency of p1 for f1 is 100. Because the frequency 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 with respect to f1. Referring to Fig. 3, since the frequency count of p2 to p4 with respect to f1 is 0, the control unit 120 can determine the similarity of p2 to p4 with respect to f1 to be 0.

[0054] According to an embodiment, the control unit 120 may sum up 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.

[0055] Taking p1 as an example, as described above, the control unit 120 determines the similarity to f1 to be 0.1, and since the frequency counts of p1 for the remaining areas (f2 to f10) are all 0, the control unit 120 can determine the similarities to all of the remaining areas (f2 to f10) to be 0. Therefore, when the similarities by region of p1 are summed, 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 can determine a score for each of the plurality of target experimental data based on the acquired battery information.

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

[0059] Here, the "table for each preset experimental condition" may refer to a table for result data of a battery degradation experiment conducted under a restricted environment under specific conditions. For example, the "table for each experimental condition" may refer to a table for battery degradation experiment data conducted under conditions set for at least one of the battery temperature, charge current, discharge current, minimum SOC, maximum SOC, and SOH according to the number of charge / discharge cycles of the target experimental data. This will be described in detail with reference to FIG. 4.

[0060] 4 is a diagram illustrating a method for determining scores for each of a plurality of target experimental data items referred to in various embodiments disclosed herein. Fig. 4 shows an example of data obtained from a battery degradation experiment conducted in a restricted environment 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 based on cycles. A cycle may refer to a value quantified by assuming one cycle of charging and discharging of a battery.

[0062] For example, one cycle may mean that the battery was charged until its State Of Charge (SOC) was 0% to 100% and then discharged until its SOC was 100% to 0%. In other words, 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 assign a score to 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 represent, 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 for each 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 can 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 scores for each of the plurality of target experimental data using the input cycle value. According to an embodiment, the control unit 120 may determine scores by interpolating experimental values ​​for each of the plurality of target experimental data using standard conditions. For example, if the temperature of the standard conditions is 25°C, the control unit 120 may determine scores for the temperature values ​​among the experimental values ​​for each of the plurality of target experimental data by interpolating them based on 25°C. The standard conditions may refer to conditions that serve as a reference for evaluating experimental data. For example, FIG. 4 shows that the standard conditions are a temperature of 25°C, a charge current and a discharge 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 conditions as standard data and assign a score of 50 to the standard data. The control unit 120 may assign a score of 100 to 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 points for target experimental data with a cycle value of 1335.4 or greater can be set to 100.

[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 among a plurality of target experimental data whose matching probability is greater than or equal to a threshold into a first group, and calculate stress scores by adding up the values ​​obtained by multiplying the scores 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 greater than or equal to a threshold into a second group, and calculate stress scores by adding up the values ​​obtained by multiplying the scores 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 the similarity value for each region of the target data or adjust the threshold for the similarity value.

[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 stress score and the second stress score to the user. The control unit 120 calculates and provides stress scores for various groups separately, thereby satisfying various needs of users.

[0076] Meanwhile, the control unit 120 may optionally include a processor, an application-specific integrated circuit (ASIC), other chipsets, logic circuits, registers, a communication modem, a data processing device, etc., which are well known in the art, to execute various control logics performed in the present invention. Furthermore, 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 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 well-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 during the operation and function. The storage unit may be any known information storage means capable of recording, erasing, updating, and reading data. For example, the information storage means may include RAM, flash memory, ROM, EEPROM, registers, etc. The storage unit may also store program code defining processes executable by the control unit 120.

[0078] For example, the storage unit may contain a plurality of experimental data and related information, 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 may be configured to determine a matching probability between a plurality of target experimental data previously acquired and the data distribution. Here, the target experimental data may be experimental data selected by the control unit 120 from among a plurality of pieces 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 piece of data corresponding to the determined type from among a plurality of pieces of experimental data previously acquired as the target experimental data.

[0080] For example, if the acquired battery information is determined to be of the driving information type, the control unit 120 may determine only the experimental data of the information type of the driving information among the plurality of pre-acquired experimental data 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, and 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] Furthermore, 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 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 guide for driving habits and / or charging habits. 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, charge current, discharge rectification, and / or SOC based on the data included in the acquired battery information, and determine a driving guide based on the calculated result and the stress score. This will be described in detail with reference to FIGS. 5 and 6.

[0086] 5 is a diagram illustrating a response message referred to in various embodiments disclosed herein, showing an example of a response message including a stress score and a driving guide.

[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 driving guides. The charging recommendation management message (511) may include a recommendation to develop the habit of charging the vehicle slowly using 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, which shows an example of a detailed message for a stress score.

[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 along with the stress score.

[0091] According to an embodiment, when the control unit 120 receives a request for a stress score, it outputs 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 about the analysis of driving habits and charging habits according to stress scores.

[0092] The battery management method will be described in detail below with reference to FIG. FIG. 7 is a diagram that schematically illustrates a battery management method according to one embodiment disclosed herein.

[0093] Preferably, each step of the battery management method can be performed by the battery management device 100. Hereinafter, the overlapping content with the above content 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 data distribution (S200), a step of determining 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 FIGS. 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 acquisition 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, at a predetermined interval, or when a pre-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 the 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 battery data distribution based on the acquired battery information. According to an embodiment, the control unit 120 may determine the type of information based on whether the acquired battery information is information about a vehicle running or information about a vehicle charging. The control unit 120 may determine, as target experimental data, at least one piece of data corresponding to the determined type from among a plurality of pieces of pre-acquired experimental data. For example, if the acquired battery information is determined to be of the type of information about a vehicle running, the control unit 120 may determine, as target data, experimental data whose information type is information about a vehicle running from among a plurality of pieces of pre-acquired experimental data. The control unit 120 determines the target experimental data based on the type of information, thereby improving the accuracy of calculating the stress score.

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

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

[0102] In step S300, the control unit 120 can 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 the similarity between the frequency of each experimental data relative to the sum of the frequencies of a plurality of target experimental data and the frequency of the battery information for each region, and determine the matching probability based on the similarity.

[0104] According to an embodiment, the control unit 120 may sum up 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.

[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 the 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 the plurality of target experimental data based on a preset table for each of the plurality of target experimental data. The preset table for each experimental condition may refer to result data from a battery degradation experiment conducted in an environment limited by specific conditions. For example, the table for each experimental condition may refer to a table for target experimental data from a battery degradation experiment conducted under conditions set for at least one of battery temperature, charge current, discharge current, minimum SOC, maximum SOC, and SOH according to the number of charge / discharge cycles 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 cycle-based SOH profile.

[0108] The term "cycle" refers to a numerical value representing one cycle of charging and discharging a battery. For example, one cycle may refer to one charge and discharge of a battery based on an SOC of 0% and an SOC of 100%.

[0109] According to an embodiment, the control unit 120 may assign a score to 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 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 into the table for each experimental condition, and 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 standard conditions. The standard conditions may refer to conditions that serve as a reference for evaluating experimental data.

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

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

[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 among a plurality of target experimental data whose matching probability is greater than or equal to a threshold into a first group, and calculate stress scores by adding up the values ​​obtained by multiplying the scores 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 greater than or equal to a threshold into a second group, and calculate stress scores by adding up the values ​​obtained by multiplying the scores 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 the similarity value for each region of the target data or adjust the threshold for the similarity value.

[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 stress score and the second stress score to the user. The control unit 120 calculates and provides stress scores for various groups separately, thereby satisfying various needs of users.

[0120] The battery management device 100 according to the present invention can be included in a battery pack 1000. That is, the battery pack according to the present invention can include the above-described 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 exemplary configuration of a battery pack including a battery management device according to an embodiment disclosed herein. The positive terminal of the battery 10 may be connected to the positive terminal (P+) of the battery pack 1000, and the negative terminal of the battery 10 may be connected to the negative terminal (P-) of the battery pack 1000.

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

[0123] The measurement unit 200 may be connected to a 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 200 may measure the charging current of the battery 10 via the third sensing line (SL3) to calculate the charge amount. The measurement unit 200 may also measure the discharging current of the battery 10 via the third sensing line (SL3) to calculate the discharge amount.

[0124] One end of the load 300 may be connected to the positive terminal (P+) of the battery pack 1000, and the other end may be connected to the negative terminal (P-) of the battery pack 1000. Therefore, 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.

[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 from the measuring section 200: voltage, current, and temperature.

[0126] The embodiments of the present invention described above may be realized not only through devices and methods, 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 anyone skilled in the technical field to which the present invention pertains based on the description of the above-mentioned embodiments.

[0127] Although the present invention has been described above using limited embodiments and drawings, it should be understood that the present invention is not limited thereto, and that various modifications and variations can be made by those skilled in the art within the scope of the technical concept of the present invention and the scope of the claims set forth below.

[0128] Furthermore, the present invention described above is not limited to the above-described embodiments and accompanying drawings, and various substitutions, modifications, and alterations 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. Therefore, 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 illustrate, not 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 set forth below, and all technical ideas within the scope equivalent thereto 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 of voltage, current, and temperature; 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, calculates the matching probability corresponding to the score for each of the plurality of target experimental data, and calculates a stress score for the battery; A battery management device comprising:

2. The control unit determining a type 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 the plurality of target experimental data corresponding to the determined type from among a plurality of experimental data acquired in advance.

3. The control unit The battery management device of claim 1 , wherein the data distribution of the battery is determined by calculating a frequency of each area of ​​the battery information.

4. The control unit The battery management device according to claim 3 , wherein the matching probability for each of the plurality of target experimental data is determined based on a frequency by region for the battery information and a frequency by region for each of the plurality of target experimental data.

5. The control unit The battery management device according to claim 4, wherein the matching probability is determined 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 of the battery information.

6. The control unit The battery management device according to claim 5 , wherein the matching probability corresponding to each of the plurality of target experimental data is determined by adding up one or more similarities calculated for each of the plurality of target experimental data.

7. The control unit 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 for each of the plurality of target experimental data.

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 target experimental data, The control unit The battery management device according to claim 7 , wherein the score is determined for the number of charge / discharge cycles at which the calculated State of Health (SOH) reaches a threshold value.

9. The control unit 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 The battery management device of 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 including 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 battery 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 including:

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