Apparatus and method for diagnosing battery

Abstract

An apparatus for diagnosing a battery according to an embodiment of the present invention includes: a voltage information obtaining unit configured to obtain voltage information of each of a plurality of battery cells included in a battery pack; and a control unit configured to calculate entropies for a plurality of voltages measured during a first period, calculate an entropy distribution on the basis of a plurality of entropies calculated during a second period, compare the calculated entropy distribution with a preset baseline distribution, and diagnose the state of the battery pack on the basis of the comparison result.

Description

Battery diagnostic device and method

[0001] This application is a priority claim application for Korean Patent Application No. 10-2024-0122135 filed on September 9, 2024, and all contents disclosed in the specification and drawings of said application are incorporated into this application by reference.

[0002] The present invention relates to a battery diagnostic device and method, and more particularly, to a battery diagnostic device and method for diagnosing the state of a battery.

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

[0004] Currently commercialized batteries include nickel-cadmium batteries, nickel-hydrogen batteries, nickel-zinc batteries, and lithium batteries. Among these, lithium batteries are receiving attention for their advantages of being able to charge and discharge freely, having a very low self-discharge rate, and having a high energy density, as they have almost no memory effect compared to nickel-based batteries.

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

[0006] The present invention is devised to solve the above-mentioned problems and aims to provide a battery diagnostic device and method for diagnosing the state of a battery pack by considering the entropy of a plurality of battery cells.

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

[0008] A battery diagnosis device according to one aspect of the present invention may include a voltage information acquisition unit configured to acquire voltage information of each of a plurality of battery cells included in a battery pack; and a control unit configured to calculate entropy for a plurality of voltages measured during a first period, calculate an entropy distribution based on the plurality of entropies calculated during a second period, compare the calculated entropy distribution with a preset reference distribution, and diagnose a state of the battery pack based on the comparison result.

[0009] The control unit may be configured to calculate a reference voltage for the plurality of voltages and to calculate entropy for the plurality of reference voltages calculated during the first period.

[0010] The above control unit may be configured to calculate a voltage difference between a maximum voltage and a minimum voltage among the plurality of voltages, and calculate the calculated voltage difference as the reference voltage.

[0011] The above control unit may be configured to calculate a distribution difference between the entropy distribution and the reference distribution, and diagnose the state of the battery pack based on the calculated distribution difference.

[0012] The control unit may be configured to compare the calculated distribution difference with a preset threshold value and diagnose the state of the battery pack based on the comparison result.

[0013] The above reference distribution may include a reference normal distribution and a reference non-normal distribution.

[0014] The control unit may be configured to calculate the normal distribution difference between the entropy distribution and the reference normal distribution, calculate the abnormal distribution difference between the entropy distribution and the reference abnormal distribution, compare the normal distribution difference and the abnormal distribution difference, and diagnose the state of the battery pack based on the comparison result.

[0015] The control unit may be configured to diagnose the state of the battery pack as abnormal if the abnormal distribution difference is less than or equal to the normal distribution difference.

[0016] The control unit may be configured to diagnose the state of the battery pack as abnormal if, at a plurality of consecutive diagnostic points, the abnormal distribution difference is less than or equal to the normal distribution difference.

[0017] The control unit may be configured to determine the pattern of increase or decrease of the abnormal distribution difference at a plurality of consecutive diagnostic points, and to diagnose the state of the battery pack as an abnormal state when, at a plurality of consecutive diagnostic points, the abnormal distribution difference is less than or equal to the normal distribution difference and the pattern of increase or decrease is determined to be a decreasing pattern.

[0018] The second period may be preset as the entire period during which the entropy was calculated.

[0019] The above control unit may be configured to calculate Shannon entropy for the plurality of voltages.

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

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

[0022] A server according to another aspect of the present invention may include a battery diagnostic device according to one aspect of the present invention.

[0023] A battery diagnosis method according to another aspect of the present invention may include a voltage information acquisition step of acquiring voltage information of each of a plurality of battery cells included in a battery pack; an entropy calculation step of calculating entropy for a plurality of voltages measured during a first period; an entropy distribution calculation step of calculating an entropy distribution based on a plurality of entropies calculated during a second period; a comparison step of comparing the calculated entropy distribution with a preset reference distribution; and a diagnosis step of diagnosing a state of the battery pack based on a comparison result of the comparison step.

[0024] According to another aspect of the present invention, a computer-readable recording medium may store a computer program for executing a battery diagnosis method, the method comprising: a voltage information acquisition step of acquiring voltage information of each of a plurality of battery cells included in a battery pack; an entropy calculation step of calculating entropy for a plurality of voltages measured during a first period; an entropy distribution calculation step of calculating an entropy distribution based on a plurality of entropies calculated during a second period; a comparison step of comparing the calculated entropy distribution with a preset reference distribution; and a diagnosis step of diagnosing a state of the battery pack based on a comparison result of the comparison step.

[0025] According to one aspect of the present invention, the battery diagnostic device has the advantage of being able to statistically diagnose the state of a battery pack by probabilistically analyzing the voltage behavior of a plurality of battery cells included in the battery pack.

[0026] The effects of the present invention are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description of the claims.

[0027] The following drawings attached to this specification serve to further understand the technical idea 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 to the matters described in such drawings.

[0028] FIG. 1 is a schematic diagram illustrating a battery diagnostic device according to one embodiment of the present invention.

[0029] FIG. 2 is a schematic diagram illustrating the voltage measurement time and the entropy calculation period according to one embodiment of the present invention.

[0030] FIG. 3 is a schematic diagram illustrating voltage and entropy according to one embodiment of the present invention.

[0031] FIG. 4 is a schematic diagram illustrating the entropy distribution according to one embodiment of the present invention.

[0032] FIGS. 5 and 6 are schematic diagrams illustrating a reference distribution according to an embodiment of the present invention.

[0033] FIG. 7 is a schematic diagram illustrating an embodiment of a distribution difference according to an embodiment of the present invention.

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

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

[0036] FIG. 10 is a schematic drawing illustrating an automobile according to another embodiment of the present invention.

[0037] FIG. 11 is a schematic diagram illustrating a battery diagnostic method according to another embodiment of the present invention.

[0038] Terms or words used in this specification and claims should not be interpreted as limited to their usual or dictionary meanings, but should be interpreted as meanings and concepts that conform to the technical spirit of the present invention, based on the principle that the inventor can appropriately define the concept of the term to explain his or her own invention in the best possible manner.

[0039] Accordingly, the embodiments described in this specification and the configurations illustrated in the drawings are merely the most preferred embodiments of the present invention and do not represent all of the technical ideas of the present invention. Therefore, it should be understood that there may be various equivalents and modified examples that can replace them at the time of filing this application.

[0040] In addition, when describing the present invention, if it is determined that a detailed description of a related known configuration or function may obscure the gist of the present invention, the detailed description is omitted.

[0041] Terms that include ordinal numbers, such as first, second, etc., are used to distinguish one of the various components from the rest, and are not used to limit the components by such terms.

[0042] Throughout the specification, whenever a part is said to "include" a component, this does not mean that it excludes other components, but rather that it may include other components, unless otherwise stated.

[0043] Additionally, throughout the specification, when we say that a part is "connected" to another part, this includes not only cases where it is "directly connected" but also cases where it is "indirectly connected" with other elements in between.

[0044]

[0045] Hereinafter, a preferred embodiment of the present invention will be described in detail with reference to the attached drawings.

[0046] FIG. 1 is a schematic diagram illustrating a battery diagnostic device (100) according to one embodiment of the present invention.

[0047] Referring to FIG. 1, a battery diagnostic device (100) may include a voltage information acquisition unit (110) and a control unit (120).

[0048] Here, a battery refers to a single independent cell that is physically separable and equipped with a negative terminal and a positive terminal. For example, a lithium-ion battery or a lithium-polymer battery may be considered a battery. Additionally, the battery may be of the cylindrical, prismatic, or pouch type.

[0049] In addition, a battery may be provided in a battery pack in which multiple cells are connected in series and / or in parallel. Here, a battery pack refers to a group of cells containing multiple batteries and may also be expressed as a battery bank or a battery module.

[0050] For example, multiple batteries may be grouped into battery modules, and one or more battery modules may be mounted in a battery pack. As another example, cell-to-pack technology may be applied so that multiple batteries are directly mounted in a battery pack.

[0051] In the following, for convenience of explanation, it is assumed that multiple batteries are directly mounted on a battery pack.

[0052] The voltage information acquisition unit (110) can be configured to acquire voltage information of each of a plurality of battery cells included in the battery pack.

[0053] Specifically, the voltage information acquisition unit (110) can acquire information on the voltage of each of a plurality of battery cells measured according to a preset voltage measurement cycle. That is, the voltage information acquisition unit (110) can acquire information on the voltage of each of a plurality of battery cells according to a preset voltage acquisition cycle.

[0054] For example, the voltage information acquisition unit (110) can acquire voltage information of each of the plurality of battery cells by directly measuring the voltage of each of the plurality of battery cells. Specifically, the voltage information acquisition unit (110) can be electrically connected to each of the plurality of battery cells. In addition, the voltage information acquisition unit (110) can be configured to independently measure the voltage of each of the plurality of battery cells for each voltage measurement cycle. For example, in order for the voltage of each of the plurality of battery cells to be independently measured, the battery pack can include various components, such as a switching element that temporarily disconnects the electrical connection of the plurality of battery cells.

[0055] As another example, the voltage information acquisition unit (110) can acquire voltage information for each of the plurality of battery cells by receiving voltage information for each of the plurality of battery cells from the outside.

[0056] FIG. 2 is a schematic diagram illustrating the voltage measurement time and the entropy calculation period according to an embodiment of the present invention. FIG. 3 is a schematic diagram illustrating the voltage and entropy according to an embodiment of the present invention.

[0057] In the embodiment of FIG. 2, the voltage information acquisition unit (110) can acquire voltage information of each of the plurality of battery cells measured from the first time point (t1) to the ninth time point (t9). In addition, in the embodiment of FIG. 3, when the battery pack includes four battery cells (B1, B2, B3, B4), the voltage information acquisition unit (110) can acquire voltage information of each of the plurality of battery cells (B1, B2, B3, B4) measured from the first time point (t1) to the ninth time point (t9).

[0058] The voltage information acquisition unit (110) can be connected via wired and / or wireless means to communicate with the control unit (120). Additionally, the voltage information acquisition unit (110) can transmit voltage information of a plurality of battery cells to the control unit (120).

[0059] For example, the voltage information acquisition unit (110) can transmit battery information to the control unit (120) whenever it acquires voltage information of a plurality of battery cells. That is, the voltage acquisition cycle and the information transmission cycle may be the same.

[0060] As another example, the voltage information acquisition unit (110) can transmit voltage information of multiple battery cells acquired in multiple cycles to the control unit (120). That is, the information transmission cycle may be larger than the voltage acquisition cycle so as to be proportional to the voltage acquisition cycle.

[0061] The control unit (120) may be configured to calculate the entropy for a plurality of voltages measured during a first period.

[0062] Preferably, the period of the first period is longer than the voltage measurement period. Therefore, multiple voltages can be measured for each battery cell during the first period. For example, the voltage measurement period may be 1 second and the first period may be 24 hours.

[0063] The control unit (120) can calculate a reference voltage for a plurality of voltages measured for each voltage measurement cycle. Here, the reference voltage may be a representative value of a plurality of voltages measured in the same voltage measurement cycle. For example, the reference voltage may be an average value, a median value, or a voltage difference (the difference between the maximum voltage and the minimum voltage) of a plurality of voltages measured in the same voltage measurement cycle. In addition, the control unit (120) can calculate entropy for a plurality of reference voltages calculated during the first period.

[0064] Specifically, the control unit (120) may be configured to calculate Shannon entropy for a plurality of voltages.

[0065] Here, Shannon entropy refers to the uncertainty of a probabilistic event, and represents the average amount of information (i.e., uncertainty) of events that can occur within a given probability distribution. That is, the control unit (120) can calculate entropy representing a reference voltage and the occurrence probability of the reference voltage based on multiple reference voltages measured during the first period.

[0066] For example, the control unit (120) can calculate the Shannon entropy for a plurality of voltages using the following formula.

[0067] [formula]

[0068]

[0069] Here, H(x) is Shannon entropy, and p(x i ) is event x i It is the probability that it will occur. That is, the control unit (120) is the reference voltage (x i The probability that ) will occur (p(x i Based on ), the Shannon entropy (H(x)) for a plurality of reference voltages measured during the first period can be calculated.

[0070] For example, in the embodiment of FIG. 3, the control unit (120) can calculate reference voltages (V1, V2, V3) for the voltages of the first to fourth battery cells (V11 to V14, V21 to V24 and V31 to V34) measured at the first to third time points (t1, t2, t3), and calculate entropy (E1) for the calculated reference voltages (V1, V2, V3). Additionally, the control unit (120) can calculate reference voltages (V4, V5, V6) for the voltages of the first to fourth battery cells (V41 to V44, V51 to V54 and V61 to V64) measured at the fourth to sixth time points (t4, t5, t6), and calculate entropy (E2) for the calculated reference voltages (V4, V5, V6). Additionally, the control unit (120) can calculate a reference voltage (V7, V8, V9) for the voltages of the first to fourth battery cells (V71 to V74, V81 to V84 and V91 to V94) measured at the 7th to 9th time points (t7, t8, t9), and calculate an entropy (E3) for the calculated reference voltage (V7, V8, V9).

[0071] The control unit (120) may be configured to calculate an entropy distribution (p) based on a plurality of entropies calculated during a second period.

[0072] Preferably, the second period is longer than the first period. Therefore, during the second period, entropy can be calculated for each of the multiple first periods. For example, the first period may be 24 hours and the second period may be one month. The control unit (120) can calculate the distribution of entropy calculated for each first period during the second period.

[0073] Here, the entropy distribution (p) can be configured to represent the correspondence between the entropy calculated during the second period and the ratio of that entropy. That is, the ratio occupied by each entropy among the multiple entropies calculated during the second period can appear in the entropy distribution (p).

[0074] FIG. 4 is a diagram schematically illustrating an entropy distribution (p) according to one embodiment of the present invention. For example, in the embodiment of FIG. 4, the proportion of calculated entropies that are 0 among the calculated entropies is approximately 0.67. That is, the control unit (120) can quantify the uncertainty of the multiple voltages measured during the first period as entropy and calculate the distribution of the multiple quantified entropies during the second period.

[0075] The control unit (120) can be configured to compare the calculated entropy distribution (p) with a preset reference distribution.

[0076] Here, the reference distribution is pre-set as a reference distribution that is compared with the calculated entropy distribution (p). In particular, the reference distribution may include a reference normal distribution (rd1) that simulates a battery pack in a normal state and / or a reference abnormal distribution (rd2) that simulates a battery pack in an abnormal state.

[0077] Specifically, the control unit (120) can calculate the difference between the entropy distribution (p) and the reference distribution. To this end, the control unit (120) may be configured to calculate the difference in distribution between the entropy distribution (p) and the reference distribution.

[0078] For example, the control unit (120) can calculate the distribution difference between the entropy distribution (p) and the reference distribution by calculating the Kullback-Leibler divergence (KLD) of the entropy distribution (p) and the reference distribution. Here, since the Kullback-Leibler divergence is used to measure how different another probability distribution is based on one probability distribution, a detailed description thereof is omitted.

[0079] The control unit (120) may be configured to diagnose the state of the battery pack based on the comparison result. That is, the control unit (120) may be configured to calculate a distribution difference considering a plurality of voltages measured during a second period and to diagnose the state of the battery pack based on the calculated distribution difference.

[0080] Specifically, the control unit (120) may be configured to compare the calculated distribution difference with a preset threshold value. Preferably, the control unit (120) may compare the calculated distribution difference with the preset threshold value. Here, the threshold value may be preset as a value that serves as a criterion for distinguishing the state of the battery pack as normal or abnormal based on the calculated distribution difference. For example, the threshold value may be set experimentally and / or theoretically so that it can serve as a criterion for diagnosing the state of the battery pack.

[0081] The control unit (120) can be configured to diagnose the state of the battery pack based on the comparison result.

[0082] Specifically, the more similar the entropy distribution (p) is to the reference distribution, the lower the distribution difference is calculated, and the more different the entropy distribution (p) is from the reference distribution, the higher the distribution difference is calculated. That is, since the lower the distribution difference, the more similar the entropy distribution (p) is to the reference distribution, the control unit (120) can diagnose the state of the battery pack by considering the type of reference distribution (reference normal distribution (rd1) or reference abnormal distribution (rd2)).

[0083] For example, it is assumed that the reference distribution is a reference normal distribution (rd1) that simulates a battery pack in a normal state. The control unit (120) can diagnose the state of the battery pack as normal if the calculated distribution difference is below a threshold value.

[0084] Assume that the other reference distribution is a reference abnormal distribution (rd2) that simulates a battery pack in an abnormal state. The control unit (120) can diagnose the state of the battery pack as abnormal if the calculated distribution difference is below a threshold value.

[0085] A battery diagnostic device (100) according to one embodiment of the present invention can quantify the uncertainty (entropy) of the voltage of a plurality of battery cells measured over a predetermined period and diagnose the state of a battery pack based on the distribution of the quantified uncertainty (entropy distribution (p)). That is, the battery diagnostic device (100) has the advantage of being able to statistically diagnose the state of a battery pack by probabilistically analyzing the voltage behavior of a plurality of battery cells included in a battery pack.

[0086]

[0087] Meanwhile, the control unit (120) provided in the battery diagnostic device (100) may optionally include a processor, an ASIC (application-specific integrated circuit), another chipset, a logic circuit, a register, a communication modem, a data processing device, etc., known in the art, to execute various control logics performed in the present invention. Additionally, when the control logic is implemented in software, the control unit (120) may be implemented as a set of program modules. At this time, the program modules may be stored in memory and executed by the control unit (120). The memory may be located inside or outside the control unit (120) and may be connected to the control unit (120) by various well-known means.

[0088] Additionally, the battery diagnostic device (100) may further include a storage unit (130). The storage unit (130) may store data or programs necessary for each component of the battery diagnostic device (100) to perform operations and functions, or data generated during the process of performing operations and functions. The storage unit (130) is not subject to any special restrictions on its type as long as it is a known information storage means capable of recording, erasing, updating, and reading data. As an example, the information storage means may include RAM, flash memory, ROM, EEPROM, registers, etc. Additionally, the storage unit (130) may store program codes that define processes executable by each component of the battery diagnostic device (100).

[0089]

[0090] Preferably, the control unit (120) can calculate the voltage difference between the maximum voltage and the minimum voltage among a plurality of voltages measured at a given point in time as the reference voltage for that point in time. And, the control unit (120) can diagnose the state of the battery pack through a plurality of reference voltages measured during a second period.

[0091] Here, the voltage difference between the maximum and minimum voltages of multiple battery cells can serve as a measure for diagnosing imbalance among multiple battery cells. That is, the entropy distribution (p) of the reference voltage can indicate voltage imbalance among multiple battery cells included in the battery pack.

[0092] A battery diagnostic device (100) according to one embodiment of the present invention has the advantage of being able to diagnose the condition of a battery pack by statistically analyzing the voltage imbalance of a plurality of battery cells.

[0093]

[0094] The reference distribution may include a reference normal distribution (rd1) and a reference non-normal distribution (rd2).

[0095] Figures 5 and 6 are schematic diagrams illustrating reference distributions according to one embodiment of the present invention. The reference normal distribution (rd1) is a reference distribution established by simulating a battery pack in a normal state, and the reference abnormal distribution (rd2) is a reference distribution established by simulating a battery pack in an abnormal state.

[0096] For example, assume that the reference voltage is calculated as the difference between the maximum and minimum voltages of multiple battery cells. In this case, a normal battery pack is one in which the voltages of the multiple battery cells are balanced. Conversely, an abnormal battery pack is one in which the voltages of the multiple battery cells are unbalanced. In other words, the reference distribution can be preset to correspond to the diagnostic items of the battery pack.

[0097] The control unit (120) may be configured to calculate the normal distribution difference between the entropy distribution (p) and the reference normal distribution (rd1). In addition, the control unit (120) may be configured to calculate the abnormal distribution difference between the entropy distribution (p) and the reference abnormal distribution (rd2).

[0098] For example, the control unit (120) can calculate the normal distribution difference by calculating the KLD between the entropy distribution (p) and the reference normal distribution (rd1). In addition, the control unit (120) can calculate the abnormal distribution difference by calculating the KLD between the entropy distribution (p) and the reference abnormal distribution (rd2).

[0099] FIG. 7 is a schematic diagram illustrating an embodiment of a distribution difference according to an embodiment of the present invention.

[0100] In the embodiment of Fig. 7, it is assumed that the first period is 24 hours and the second period is set to one month. r71 to r731 represent July 1 to July 31, r81 to r831 represent August 1 to August 31, and r91 to r930 represent September 1 to September 30.

[0101] There are a total of 31 entropies calculated in July, E71 to E731. And, the normal distribution difference between the distribution of entropies (E71 to E731) calculated during the July period and the reference normal distribution (rd1) is D71. Also, the abnormal distribution difference between the distribution of entropies (E71 to E731) calculated during the July period and the reference abnormal distribution (rd2) is D72.

[0102] There are a total of 31 entropies calculated in August, E81 to E831. And, the normal distribution difference between the distribution of entropies (E81 to E831) calculated during the August period and the reference normal distribution (rd1) is D81. Also, the abnormal distribution difference between the distribution of entropies (E81 to E831) calculated during the August period and the reference abnormal distribution (rd2) is D82.

[0103] There are a total of 30 entropies calculated in September, ranging from E91 to E930. The normal distribution difference between the distribution of entropies (E91 to E930) calculated during the September period and the reference normal distribution (rd1) is D91. Additionally, the abnormal distribution difference between the distribution of entropies (E91 to E930) calculated during the September period and the reference abnormal distribution (rd2) is D92.

[0104] The control unit (120) can be configured to compare the normal distribution difference and the abnormal distribution difference.

[0105] Specifically, the control unit (120) can compare the normal distribution difference and the abnormal distribution difference calculated for each second period. If the normal distribution difference is smaller than the abnormal distribution difference, it means that the battery pack is more likely to be in a normal state during the second period. Conversely, if the normal distribution difference is larger than the abnormal distribution difference, it means that the battery pack is more likely to be in an abnormal state during the second period.

[0106] The control unit (120) can be configured to diagnose the state of the battery pack based on the comparison result.

[0107] As explained above, a smaller difference in distribution means that the similarity between the entropy distribution (p) and the reference distribution increases. Therefore, the control unit (120) can be configured to diagnose the state of the battery pack as abnormal if the difference in abnormal distribution is less than or equal to the difference in normal distribution.

[0108] For example, in the embodiment of FIG. 7, the control unit (120) can diagnose the state of the battery pack in July by comparing D71 and D72. If D71 is less than or equal to D72, the control unit (120) can diagnose the state of the battery pack in July as normal. Conversely, if D71 exceeds D72, the control unit (120) can diagnose the state of the battery pack in July as abnormal.

[0109] Likewise, in the embodiment of FIG. 7, the control unit (120) can diagnose the state of the battery pack in August based on the result of comparing D81 and D82, and diagnose the state of the battery pack in September based on the result of comparing D91 and D92.

[0110] Meanwhile, preferably, when the normal distribution difference and the abnormal distribution difference are the same, the control unit (120) can diagnose the state of the battery pack as an abnormal state. Here, the case where the normal distribution difference and the abnormal distribution difference are the same means that the probability of the battery pack being in a normal state and the probability of it being in an abnormal state are the same. If the state of the battery pack is misdiagnosed, the charging and discharging of the battery pack is not limited, so the possibility of the battery pack's state rapidly deteriorating becomes very high. Furthermore, a battery pack whose state has rapidly deteriorated may have a rapidly reduced lifespan, and unexpected accidents such as fire or explosion may occur. Therefore, in order to strictly diagnose the state of the battery pack, the control unit (120) can diagnose the state of the battery pack as an abnormal state.

[0111] A battery diagnostic device (100) according to one embodiment of the present invention can diagnose the state of a battery pack statistically and probabilistically by comparing a normal distribution difference and an abnormal distribution difference.

[0112]

[0113] In another embodiment, the control unit (120) may be configured to diagnose the state of the battery pack as abnormal if the abnormal distribution difference is less than or equal to the normal distribution difference at a plurality of consecutive diagnostic points.

[0114] Specifically, when the state of the battery pack is diagnosed as abnormal, at least one of the charge termination voltage, upper limit SOC (State of charge), discharge termination voltage, lower limit SOC, maximum charge C-rate, maximum discharge C-rate, and maximum allowable temperature of the battery pack may be limited to prevent rapid degradation of the battery pack. For example, the charge termination voltage and upper limit SOC of the battery pack may be reduced, and the maximum charge C-rate may be reduced.

[0115] That is, if the state of a battery pack in an abnormal state is misdiagnosed as normal, the deterioration of the battery pack may progress more rapidly than expected, whereas if the state of a battery pack in a normal state is misdiagnosed as abnormal, the usage efficiency of the battery pack may be reduced.

[0116] For example, suppose a battery pack in normal condition is misdiagnosed as abnormal, resulting in a reduced charge termination voltage and a reduced maximum charge C-rate. This reduces the usable capacity of the battery pack and limits faster charging, thereby reducing its usability.

[0117] Accordingly, the control unit (120) can diagnose the state of the battery pack as abnormal if the number of consecutive times the abnormal distribution difference is less than or equal to the normal distribution difference is greater than or equal to a preset reference number. For example, the control unit (120) can diagnose the state of the battery pack as abnormal if the abnormal distribution difference is less than or equal to the normal distribution difference for two consecutive times.

[0118] In the embodiment of FIG. 7, it is assumed that the reference number is pre-set to 2.

[0119] For example, if D72 is less than or equal to D71 and D82 is less than or equal to D81, the control unit (120) can diagnose the state of the battery pack as abnormal.

[0120] As another example, if D72 is less than or equal to D71 and D82 exceeds D81, the control unit (120) can diagnose the state of the battery pack as normal. Here, even if D92 is less than or equal to D91, the control unit (120) can diagnose the state of the battery pack as normal because the abnormal distribution difference is not less than or equal to the normal distribution difference for a consecutive number of times.

[0121] As another example, if D72 is identical to D71 and D82 is identical to D81, the control unit (120) can diagnose the state of the battery pack as abnormal. That is, in order to prevent the battery pack's lifespan from rapidly decreasing, the control unit (120) can diagnose the state of the battery pack as abnormal even if the abnormal distribution difference and the normal distribution difference are identical for a consecutive number of times.

[0122]

[0123] In another embodiment, the control unit (120) may be configured to determine the pattern of increase or decrease of the abnormal distribution difference at a plurality of consecutive diagnostic points.

[0124] Specifically, the control unit (120) can determine an increase / decrease pattern of the abnormal distribution difference to analyze the behavior of the abnormal distribution difference over time. Preferably, based on the magnitude of the abnormal distribution difference at multiple diagnostic points, the control unit (120) can determine the increase / decrease pattern of the abnormal distribution difference as an increase pattern or a decrease pattern.

[0125] Here, the increasing pattern refers to a pattern in which the abnormal distribution difference increases as the diagnosis time progresses. Conversely, the decreasing pattern refers to a pattern in which the abnormal distribution difference decreases or remains constant as the diagnosis time progresses. For example, if the abnormal distribution difference remains below the normal distribution difference, it may indicate that the voltage imbalance of the battery pack is continuously occurring. Furthermore, since it is certain that an imbalance has occurred, there may be no room for the abnormal distribution difference to decrease further. If, in this case, the pattern of increase or decrease of the abnormal distribution difference is determined as an increasing pattern, the condition of the battery pack may be misdiagnosed. Therefore, if the abnormal distribution difference remains unchanged at multiple diagnosis times, the control unit (120) may determine the pattern of increase or decrease of the abnormal distribution difference as a decreasing pattern.

[0126] For example, the control unit (120) can determine an increase / decrease pattern by comparing the magnitude of the difference in abnormal distribution between a predetermined number (e.g., 2) of past diagnosis points and the current diagnosis point.

[0127] As another example, the control unit (120) can calculate the average rate of change of the abnormal distribution difference calculated at multiple diagnostic points and determine the increase / decrease pattern based on the calculated average rate of change.

[0128] The control unit (120) may be configured to diagnose the state of the battery pack as an abnormal state when, at a plurality of consecutive diagnostic points, the abnormal distribution difference is less than or equal to the normal distribution difference and the increase / decrease pattern is determined to be a decrease pattern.

[0129] That is, at a number of consecutive diagnostic points, if the abnormal distribution difference is less than or equal to the normal distribution difference and the increase / decrease pattern of the abnormal distribution difference shows a decrease pattern, the control unit (120) can diagnose the state of the battery pack as an abnormal state.

[0130] A battery diagnostic device (100) according to one embodiment of the present invention can diagnose the condition of a battery pack more accurately by considering not only the difference between an abnormal distribution difference and a normal distribution difference, but also the behavioral pattern of the abnormal distribution difference.

[0131]

[0132] Hereinafter, an embodiment is described in which the second period is pre-set as the entire period in which entropy is calculated.

[0133] Specifically, the control unit (120) may be configured to calculate the normal distribution difference and the abnormal distribution difference for the entire period, rather than calculating the normal distribution difference and the abnormal distribution difference for each independent second period.

[0134] In this case, the normal distribution difference and the abnormal distribution difference can be calculated by reflecting the entropy over the entire period, rather than reflecting the entropy over a partial period. That is, the normal distribution difference and the abnormal distribution difference can be calculated by reflecting the accumulated entropy over the normal period. And, the control unit (120) can diagnose the state of the battery pack based on the normal distribution difference and the abnormal distribution difference that reflect the entropy over the entire period.

[0135] FIG. 8 is a schematic diagram illustrating another embodiment of a distribution difference according to one embodiment of the present invention.

[0136] For example, in the embodiment of FIG. 8, a normal distribution difference (D71) and an abnormal distribution difference (D72) can be calculated based on the entropy (E71 to E731) calculated in July.

[0137] In addition, based on the entropies calculated in July (E71 to E731) and the entropies calculated in August (E81 to E831), a normal distribution difference (D81) and an abnormal distribution difference (D82) can be calculated. That is, based on the total entropies calculated in July and August (E71 to E731 and E81 to E831), a distribution difference for the entire period (July and August) can be calculated.

[0138] In addition, based on the entropy calculated in July (E71 to E731), the entropy calculated in August (E81 to E831), and the entropy calculated in September (E91 to E930), a normal distribution difference (D91) and an abnormal distribution difference (D92) can be calculated. That is, based on the total entropy calculated in July to September (E71 to E731, E81 to E831, and E91 to E930), a distribution difference for the entire period (July, August, and September) can be calculated.

[0139] A battery diagnostic device (100) according to one embodiment of the present invention has the advantage of being able to diagnose the state of a battery pack over its entire life cycle by accumulating all the entropy calculated up to the current diagnostic period and diagnosing the state of the battery pack.

[0140]

[0141] The battery diagnostic device (100) according to the present invention can be applied to a Battery Management System (BMS). That is, the BMS according to the present invention may include the battery diagnostic device (100) described above. In this configuration, at least some of the components of the battery diagnostic device (100) may be implemented by supplementing or adding the functions of the components included in a conventional BMS. For example, the voltage information acquisition unit (110), control unit (120), and storage unit (130) of the battery diagnostic device (100) may be implemented as components of the BMS.

[0142] In addition, the battery diagnostic device (100) according to the present invention may be provided in a battery pack. That is, the battery pack according to the present invention may include the battery diagnostic device (100) described above and one or more battery cells. In addition, the battery pack may further include electrical components (relays, fuses, etc.) and a case, etc.

[0143] FIG. 9 is a schematic diagram illustrating a battery pack according to another embodiment of the present invention.

[0144] A battery pack (10) may include a first battery cell (11), a second battery cell (12), a third battery cell (13), and a fourth battery cell (14). For example, a plurality of battery cells (11, 12, 13, 14) may be provided in the battery pack. As another example, a plurality of battery cells (11, 12, 13, 14) may be grouped into one or more battery modules, and one or more battery modules may be provided in the battery pack.

[0145] A plurality of battery cells (11, 12, 13, 14) may be connected to each other in series and / or in parallel. For example, in the embodiment of FIG. 9, a plurality of battery cells (11, 12, 13, 14) may be connected to each other in series. In this case, the positive terminal of the first battery cell (11) may be connected to the positive terminal (P+) of the battery pack (10), and the negative terminal of the fourth battery cell (14) may be connected to the negative terminal (P-) of the battery pack (10).

[0146] The measuring unit (15) can be connected to a plurality of sensing lines. And, the measuring unit (15) can measure the voltage across each of the battery cells through the connected sensing lines.

[0147] In the embodiment of FIG. 9, the measuring unit (15) may be connected to the positive terminal of the first battery cell (11) through the first sensing line (SL1) and to the negative terminal of the first battery cell (11) through the second sensing line (SL2). The measuring unit (15) may be connected to the positive terminal of the second battery cell (12) through the second sensing line (SL2) and to the negative terminal of the second battery cell (12) through the third sensing line (SL3). The measuring unit (15) may be connected to the positive terminal of the third battery cell (13) through the third sensing line (SL3) and to the negative terminal of the third battery cell (13) through the fourth sensing line (SL4). The measuring unit (15) can be connected to the positive terminal of the fourth battery cell (14) through the fourth sensing line (SL4) and to the negative terminal of the fourth battery cell (14) through the fifth sensing line (SL5).

[0148] And, the measuring unit (15) can be connected to a current measuring unit (A) through the sixth sensing line (SL6). For example, the current measuring unit (A) may be an ammeter or a shunt resistor capable of measuring the charging current and discharging current of the battery pack (10).

[0149] An external device may be connected to the positive terminal (P+) and the negative terminal (P-) of the battery pack (10). For example, the external device may be a charging device or a load. Also, the positive terminal (P+) of the battery pack (10), the external device, and the negative terminal (P-) of the battery pack (10) may be electrically connected.

[0150] For example, the voltage information acquisition unit (110) is electrically connected to the measurement unit (15) and can receive voltage information of a plurality of battery cells (11, 12, 13, 14) from the measurement unit (15).

[0151] As another example, unlike the embodiment of FIG. 9, the voltage information acquisition unit (110) may directly acquire voltage information of a plurality of battery cells (11, 12, 13, 14) by directly measuring the voltage of a plurality of battery cells (11, 12, 13, 14).

[0152]

[0153] FIG. 10 is a schematic drawing illustrating an automobile (1000) according to another embodiment of the present invention.

[0154] Referring to FIG. 10, a battery pack (10) according to an embodiment of the present invention may be included in a vehicle (1000), such as an electric vehicle (EV) or a hybrid vehicle (HV). In addition, the battery pack (10) may drive the vehicle (1000) by supplying power to a motor through an inverter provided in the vehicle (1000). Here, the battery pack (10) may include a battery diagnostic device (100). That is, the vehicle (1000) may include a battery diagnostic device (100). In this case, the battery diagnostic device (100) may be an on-board device included in the vehicle (1000).

[0155]

[0156] A server (not shown) according to another embodiment of the present invention may include a battery diagnostic device (100) according to one embodiment of the present invention.

[0157] For example, the server may be connected to the outside world via wired and / or wireless communication. Furthermore, the server may receive voltage information for multiple battery cells contained in a battery pack from the outside world and store the received voltage information. Furthermore, the server may update the voltage information for the multiple battery cells periodically or aperiodically.

[0158] The server can diagnose the condition of the battery pack based on voltage information from multiple battery cells. Furthermore, upon an external request or the occurrence of a specific event, the server can provide battery pack condition diagnosis results. In other words, the battery pack condition diagnosis results stored on the server can be referenced by various external devices connected to the server.

[0159]

[0160] FIG. 11 is a schematic diagram illustrating a battery diagnostic method according to another embodiment of the present invention.

[0161] Referring to FIG. 11, the battery diagnosis method may include a voltage information acquisition step (S100), an entropy calculation step (S200), an entropy distribution calculation step (S300), a comparison step (S400), and a diagnosis step (S500).

[0162] Preferably, each step of the battery diagnosis method can be performed by a battery diagnosis device (100). In the following, for convenience of explanation, any content that overlaps with the previously described content will be omitted or briefly described.

[0163] The voltage information acquisition step (S100) is a step of acquiring voltage information of each of a plurality of battery cells included in a battery pack, and can be performed by a voltage information acquisition unit (110).

[0164] For example, the voltage information acquisition unit (110) can acquire voltage information of each of the plurality of battery cells by directly measuring the voltage of each of the plurality of battery cells. As another example, the voltage information acquisition unit (110) can acquire voltage information of each of the plurality of battery cells by receiving voltage information of each of the plurality of battery cells from the outside.

[0165] The entropy calculation step (S200) is a step of calculating the entropy for a plurality of voltages measured during a first period, and can be performed by the control unit (120).

[0166] The control unit (120) can calculate a reference voltage for a plurality of voltages. In addition, the control unit (120) can be configured to calculate entropy for a plurality of reference voltages measured during a first period.

[0167] The entropy distribution calculation step (S300) is a step of calculating an entropy distribution (p) based on multiple entropies calculated during the second period, and can be performed by the control unit (120).

[0168] The control unit (120) can calculate the ratio of each entropy among the plurality of entropies produced during the second period to produce an entropy distribution (p).

[0169] The comparison step (S400) is a step of comparing the calculated entropy distribution (p) with a preset reference distribution, and can be performed by the control unit (120).

[0170] The control unit (120) can calculate the distribution difference between the entropy distribution (p) and the reference distribution.

[0171] For example, the control unit (120) can calculate the normal distribution difference between the entropy distribution (p) and the reference normal distribution (rd1). As another example, the control unit (120) can calculate the abnormal distribution difference between the entropy distribution (p) and the reference abnormal distribution (rd2). As yet another example, the control unit (120) can calculate both the normal distribution difference and the abnormal distribution difference.

[0172] The diagnosis step (S500) is a step for diagnosing the status of the battery pack based on the comparison result of the comparison step (S400), and can be performed by the control unit (120).

[0173] The control unit (120) can diagnose the condition of the battery pack based on the results of comparing the calculated distribution difference with a threshold value or the results of comparing the calculated normal distribution difference with an abnormal distribution difference. Preferably, the control unit (120) can diagnose the condition of the battery pack strictly and conservatively within a range that does not excessively reduce the utilization efficiency of the battery pack.

[0174]

[0175] The embodiments of the present invention described above are not implemented only through devices and methods, but may also be implemented through a program that realizes a function corresponding to the configuration of the embodiments of the present invention or a recording medium on which the program is recorded, and such implementation can be easily implemented by an expert in the technical field to which the present invention belongs based on the description of the embodiments described above.

[0176] Another embodiment of the present invention can provide a computer-readable recording medium having recorded thereon a program for performing the various embodiments described above on a computer.

[0177] The program may be implemented as hardware components, software components, and / or a combination of hardware components and software components. The program may be executed by any system capable of executing computer-readable instructions.

[0178] Software may include computer programs, codes, instructions, or any combination thereof, which may configure a processing device to perform a desired operation or may independently or collectively command a processing device.

[0179] Software may be implemented as a computer program comprising instructions stored on a computer-readable storage medium. Examples of computer-readable storage media include magnetic storage media (e.g., read-only memory (ROM), random-access memory (RAM), floppy disks, hard disks, etc.) and optical reading media (e.g., CD-ROMs, Digital Versatile Discs (DVDs)). The computer-readable storage media may be distributed across network-connected computer systems, so that computer-readable code may be stored and executed in a distributed manner. The storage media may be readable by a computer, stored in a memory, and executed by a processor.

[0180] Computer-readable storage media may be provided in the form of non-transitory storage media. Here, the term "non-transitory storage media" simply means a tangible device that does not contain signals (e.g., electromagnetic waves). This term does not distinguish between cases where data is permanently stored on the storage media and cases where data is temporarily stored. For example, a "non-transitory storage medium" may include a buffer in which data is temporarily stored.

[0181] Additionally, the program may be provided as part of a computer program product. The computer program product may be traded as a commodity between sellers and buyers.

[0182] A computer program product may include a software program or a computer-readable storage medium storing the software program. For example, a computer program product may include a product in the form of a software program (e.g., a downloadable application) distributed electronically by an electronic device manufacturer or through an electronic marketplace. For electronic distribution, at least a portion of the software program may be stored on a storage medium or temporarily generated. In this case, the storage medium may be a storage medium of the electronic device manufacturer's server, an electronic marketplace server, or an intermediary server that temporarily stores the software program.

[0183] Although the present invention has been described above with reference to limited embodiments and drawings, the present invention is not limited thereto, and it is obvious that various modifications and variations are possible within the scope of the technical idea of ​​the present invention and the equivalent scope of the patent claims to be described below by a person having ordinary skill in the art to which the present invention pertains.

[0184] In addition, the present invention described above is not limited to the above-described embodiments and the attached drawings, and all or part of each embodiment may be selectively combined and configured so that various modifications can be made, as those skilled in the art can make various substitutions, modifications, and changes within the scope of the technical idea of ​​the present invention.

[0185] (Explanation of symbols)

[0186] 10: Battery pack

[0187] 11, 12, 13, 14: Battery cells

[0188] 15: Measurement section

[0189] 100: Battery Diagnostic Device

[0190] 110: Voltage information acquisition unit

[0191] 120: Control unit

[0192] 130: Storage

[0193] 1000: Car

Claims

A voltage information acquisition unit configured to acquire voltage information of each of a plurality of battery cells included in a battery pack; and A battery diagnostic device comprising a control unit configured to calculate entropy for a plurality of voltages measured during a first period, calculate an entropy distribution based on a plurality of entropies calculated during a second period, compare the calculated entropy distribution with a preset reference distribution, and diagnose the state of the battery pack based on the comparison result. . In paragraph 1, The above control unit, A battery diagnostic device configured to calculate a reference voltage for the plurality of voltages and to calculate the entropy for the plurality of reference voltages calculated during the first period. In the second paragraph, The above control unit, A battery diagnostic device configured to calculate the voltage difference between the maximum voltage and the minimum voltage among the plurality of voltages and to calculate the calculated voltage difference as the reference voltage. . In paragraph 1, The above control unit, A battery diagnostic device configured to calculate the difference in distribution between the above entropy distribution and the above reference distribution, and to diagnose the state of the battery pack based on the calculated difference in distribution. In paragraph 4, The above control unit, A battery diagnostic device configured to compare the above-calculated distribution difference with a preset threshold value and diagnose the state of the battery pack based on the comparison result. In paragraph 1, The above reference distribution includes a reference normal distribution and a reference non-normal distribution, and The above control unit, A battery diagnostic device configured to calculate the normal distribution difference between the above entropy distribution and the above reference normal distribution, calculate the abnormal distribution difference between the above entropy distribution and the above reference abnormal distribution, compare the normal distribution difference and the abnormal distribution difference, and diagnose the state of the battery pack based on the comparison result. In paragraph 6, The above control unit, A battery diagnostic device configured to diagnose the state of the battery pack as abnormal if the above abnormal distribution difference is less than or equal to the above normal distribution difference. In paragraph 6, The above control unit, A battery diagnostic device configured to diagnose the state of the battery pack as abnormal if the abnormal distribution difference is less than or equal to the normal distribution difference at a plurality of consecutive diagnostic points. In paragraph 6, The above control unit, Determining the pattern of increase or decrease of the above abnormal distribution difference at multiple consecutive diagnostic points, and A battery diagnostic device configured to diagnose the state of the battery pack as abnormal when, at the aforementioned consecutive multiple diagnostic points, the abnormal distribution difference is less than or equal to the normal distribution difference and the increase / decrease pattern is determined to be a decrease pattern. . In paragraph 1, The above second period is, A battery diagnostic device pre-set for the entire period in which the above entropy was calculated. In paragraph 1, The above control unit, A battery diagnostic device configured to calculate Shannon entropy for the above plurality of voltages. A battery pack comprising a battery diagnostic device according to any one of claims 1 to 11. An automobile comprising a battery diagnostic device according to any one of paragraphs 1 through 11. A server comprising a battery diagnostic device according to any one of paragraphs 1 through 11. A voltage information acquisition step for acquiring voltage information of each of a plurality of battery cells included in a battery pack; An entropy calculation step for calculating the entropy for a plurality of voltages measured during a first period; An entropy distribution calculation step for calculating an entropy distribution based on a plurality of entropies calculated during a second period; A comparison step for comparing the calculated entropy distribution with a preset reference distribution; and A battery diagnostic method comprising a diagnostic step for diagnosing the state of the battery pack based on the comparison result of the above comparison step. A voltage information acquisition step for acquiring voltage information of each of a plurality of battery cells included in a battery pack; An entropy calculation step for calculating the entropy for a plurality of voltages measured during a first period; An entropy distribution calculation step for calculating an entropy distribution based on a plurality of entropies calculated during a second period; A comparison step for comparing the calculated entropy distribution with a preset reference distribution; and A computer-readable recording medium storing a computer program for executing a battery diagnostic method comprising a diagnostic step of diagnosing the state of the battery pack based on the comparison result of the comparison step above.

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