Overheating diagnosis method, overheating diagnosis device and battery system providing said method

Abstract

The present invention relates to an overheating diagnosis method, and an overheating diagnosis device and battery system that provide the method. The battery system of the present invention includes a battery including a plurality of battery cells, a measurement unit that measures the temperature of the battery for each diagnosis time point at which overheating of the battery is diagnosed, a storage unit that stores the temperature values ​​measured by the measurement unit, and a control unit that extracts, for each diagnosis time point, a plurality of previous diagnosis time points corresponding to a predetermined number of samples based on the diagnosis time point, calculates a moving average value that is an average of a plurality of temperature values ​​corresponding to each of the plurality of diagnosis time points, and compares the temperature value measured for each diagnosis time point with a reference value that is a predetermined value greater than the moving average value to diagnose overheating of the battery.

Description

[Technical field]

[0001] Cross-reference to related applications This application claims the benefit of priority based on Korean Patent Application No. 10-2022-0061919 dated May 20, 2022, and all contents disclosed in the documents of that Korean patent application are incorporated herein by reference.

[0002] The present invention relates to a method for diagnosing overheating in an object (e.g., a battery, etc.), and an overheating diagnosis device and a battery system that provide the method. [Background technology]

[0003] Recently, as the demand for portable electronic products such as laptops, video cameras, and mobile phones has increased dramatically and the development of electric vehicles, energy storage batteries, robots, satellites, etc. has progressed in earnest, research into high-performance batteries that can be repeatedly charged and discharged is being actively conducted.

[0004] Currently commercialized batteries include nickel-cadmium batteries, nickel-metal hydride batteries, nickel-zinc batteries, and lithium batteries. Of these, lithium batteries are in the spotlight due to their advantages of being free to charge and discharge as they have almost no memory effect compared to nickel-based batteries, as well as their extremely low self-discharge rate and high energy density.

[0005] Meanwhile, the temperature of a battery is a factor that has a significant impact on the performance of the battery. Generally, a battery can operate efficiently when its temperature is distributed at an appropriate temperature. For example, if the temperature of the battery is excessively high, the stability of the negative electrode crystal lattice of the battery may be reduced, resulting in a decrease in the performance of the battery or an accident such as an explosion. Therefore, it is necessary to accurately monitor the temperature of the battery.

[0006] Conventionally, the battery overheating was diagnosed by comparing the measured battery temperature with a preset reference value. The conventional method has a problem that it is difficult to take appropriate measures because the time interval between the diagnosis of an overheating event and the occurrence of a battery explosion is too short. In addition, the conventional method has a problem that it erroneously diagnoses a temperature increase due to aging of the battery as an overheating event. Summary of the Invention [Problem to be solved by the invention]

[0007] The present invention relates to an overheating diagnostic method capable of diagnosing abnormal heat generation behavior (hereinafter, "overheating") of an object quickly and accurately, and an overheating diagnostic device and battery system which provide the method. [Means for solving the problem]

[0008] According to one aspect of the present invention, an overheating diagnosis apparatus includes a measurement unit for measuring a temperature of an object for each diagnosis time point at which overheating of the object is diagnosed, a storage unit for storing temperature values ​​measured by the measurement unit, and a control unit for extracting, for each diagnosis time point, a plurality of previous diagnosis time points corresponding to a predetermined number of samples based on the diagnosis time point, calculating a moving average which is an average of a plurality of temperature values ​​corresponding to each of the plurality of diagnosis time points, and comparing the temperature value measured for each diagnosis time point with a reference value which is a predetermined value greater than the moving average value to diagnose overheating of the object.

[0009] The control unit can calculate a standard deviation average value, which is the average of multiple standard deviations corresponding to each of the multiple diagnosis time points, multiply the standard deviation average value by a predetermined multiple to calculate a first error value, and add the first error value to the moving average value to calculate the reference value.

[0010] If the average standard deviation value is smaller than a predetermined deviation reference value, the control unit can determine a predetermined correction value as a second error value, and calculate the reference value by adding the second error value to the moving average value.

[0011] The control unit may diagnose that an overheating event has occurred in the object if the measured temperature value exceeds the reference value.

[0012] According to another aspect of the present invention, a battery system includes a battery including a plurality of battery cells, a measurement unit that measures a temperature of the battery for each diagnosis time point for diagnosing overheating of the battery, a storage unit that stores temperature values ​​measured by the measurement unit, and a control unit that extracts, for each diagnosis time point, a plurality of previous diagnosis time points corresponding to a predetermined number of samples based on the diagnosis time point, calculates a moving average value that is an average of a plurality of temperature values ​​corresponding to each of the plurality of diagnosis time points, and compares the temperature value measured for each diagnosis time point with a reference value that is a predetermined value greater than the moving average value to diagnose overheating of the battery.

[0013] The control unit can calculate a standard deviation average value, which is the average of multiple standard deviations corresponding to each of the multiple diagnosis time points, multiply the standard deviation average value by a predetermined multiple to calculate a first error value, and add the first error value to the moving average value to calculate the reference value.

[0014] If the average standard deviation value is smaller than a predetermined deviation reference value, the control unit can determine a predetermined correction value as a second error value, and calculate the reference value by adding the second error value to the moving average value.

[0015] The control unit may diagnose that an overheating event has occurred in the battery if the measured temperature value exceeds the reference value.

[0016] According to another aspect of the present invention, an overheat diagnosis method includes a temperature data collecting step of collecting temperature values, which are temperature measurements of the battery, at a predetermined diagnosis time point for diagnosing overheating of a battery including a plurality of battery cells; a sample group determining step of extracting a plurality of previous diagnosis time points corresponding to a sample number based on the diagnosis time point; a reference value determining step of calculating a moving average value, which is an average of a plurality of temperature values ​​corresponding to each of the plurality of diagnosis time points, and a reference value that is greater than the moving average value by a predetermined value; and an overheat diagnosis step of comparing the temperature value with the reference value to diagnose overheating of the battery.

[0017] The reference value determination step can include calculating a standard deviation average value, which is the average of standard deviations corresponding to each of the multiple diagnostic time points, multiplying the standard deviation average value by a predetermined multiple to calculate a first error value, and adding the first error value to the moving average value to calculate the reference value.

[0018] The reference value determining step may include determining a predetermined correction value as a second error value if the average standard deviation is smaller than a predetermined deviation reference value, and calculating the reference value by adding the second error value to the moving average value.

[0019] The overheating diagnosis step may diagnose that an overheating event has occurred in the battery if the measured temperature value exceeds the reference value. Effect of the Invention

[0020] Unlike conventional methods that use a fixed reference value for diagnosis, the present invention calculates a reference value that reflects the temperature trend of an object at each time of overheating diagnosis, and performs overheating diagnosis by comparing the calculated reference value with the measured temperature, thereby enabling the occurrence of an overheating event to be quickly determined.

[0021] The present invention calculates a reference value reflecting the temperature trend of an object at each overheating diagnosis point, and performs overheating diagnosis by comparing the calculated reference value with the measured temperature, thereby preventing the problem of misdiagnosing a temperature increase due to aging of an object (e.g., a battery) as the occurrence of an overheating event. [Brief description of the drawings]

[0022] [Figure 1] 1 is a block diagram illustrating an overheating diagnostic device according to an embodiment; [Diagram 2] FIG. 11 is a block diagram illustrating a battery system according to another embodiment. [Diagram 3] 4 is a flowchart illustrating an overheating diagnosis method according to an embodiment. [Figure 4] 4 is a flowchart illustrating in detail the reference value determination step (S300) of FIG. 3. [Diagram 5] FIG. 4 is an exemplary diagram showing temperature changes of a non-defective battery in a charging mode. [Figure 6] FIG. 13 is an example diagram illustrating an overheat diagnosis performed on a defective battery in a charging mode. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0023] Hereinafter, the embodiments disclosed herein will be described in detail with reference to the attached drawings, and identical or similar components will be given the same or similar drawing numbers, and redundant description thereof will be omitted. The suffixes "module" and / or "part" for components used in the following description are given or mixed for the sake of ease of specification writing only, and do not have any meaning or role that is different from each other by themselves. In addition, in describing the embodiments disclosed herein, if it is determined that a detailed description of related known technology may obscure the gist of the embodiments disclosed herein, the detailed description will be omitted. In addition, the attached drawings are merely for the purpose of making the embodiments disclosed herein easily understandable, and the technical ideas disclosed herein are not limited by the attached drawings, and it is understood that the drawings include all modifications, equivalents, or alternatives included in the ideas and technical scope of the present invention.

[0024] Terms including ordinal numbers such as first, second, etc. may be used to describe various components, but the components are not limited to the terms. The terms are used only to distinguish one component from another.

[0025] When a component is referred to as being "coupled" or "connected" to another component, it is understood that the component may be directly coupled or connected to the other component, but there may be other components in between. Conversely, when a component is referred to as being "directly coupled" or "directly connected" to another component, it is understood that there are no other components in between.

[0026] In this application, the terms "comprise" or "have" and the like are intended to specify the presence of any feature, number, step, operation, component, part, or combination thereof set forth in the specification, and are understood not to preclude the presence or additional possibility of one or more other features, number, step, operation, component, part, or combination thereof.

[0027] FIG. 1 is a block diagram illustrating an overheat diagnostic device according to one embodiment.

[0028] Referring to FIG. 1, an overheat diagnostic device 1 includes a measurement unit 11, a storage unit 13, and a control unit 15.

[0029] The measurement unit 11 can measure the temperature of an object at each diagnosis time (hereinafter, diagnosis time) for diagnosing overheating of the object, and transmit the measurement result to the control unit 15. For example, the measurement unit 11 can include a temperature sensor for measuring the temperature of the object. In this case, the object can include, but is not limited to, a battery, and can include various devices that need to predict an overheating event before it occurs.

[0030] The storage unit 13 can store the temperature value of the object measured by the measurement unit 11 for each diagnosis time point. The storage unit 13 can also store the moving average (MA), standard deviation (SD), standard deviation average (SD_ave), and reference value (Th) calculated by the control unit 15 for each diagnosis time point. For example, the temperature value of the object, the moving average (MA), the standard deviation (SD), the standard deviation average (SD_ave), and the reference value (Th) corresponding to a predetermined diagnosis time point can be stored in the storage unit 13 in the form of a lookup table.

[0031] When a diagnosis time point according to a preset condition arrives, the control unit 15 calculates a moving average value (MA) and a reference value (Th) that is a predetermined value greater than the moving average value. For example, if the object is a battery, the diagnosis time point may be a time point when charging of the battery starts or a time point when discharging of the battery ends. However, the diagnosis time point is not limited thereto and may be set in various ways.

[0032] First, the control unit 15 may determine a sample group by extracting a plurality of diagnosis time points included in a preset number of samples (SN) when counting diagnosis time points in the direction of a previous diagnosis time point based on a current diagnosis time point (N). At this time, the number of samples (SN) is the number of diagnosis time points included in the sample group, and may be determined to be an optimal number based on an experiment, etc.

[0033] The sample population is a subpopulation of the parent population at multiple past diagnosis points, and may be a population for calculating a moving average (MA) and an average standard deviation (σ_ave), which will be described below.

[0034] [Table 1]

[0035] The above Table 1 shows an example of a lock-up table for the temperature (T), moving average (MA), standard deviation (SD), standard deviation average (SD_ave), and reference value (Th) of an object corresponding to each of a plurality of diagnosis time points. The reference value (Th) required for overheating diagnosis at the Nth diagnosis time point is as follows: N We will explain in detail how to calculate the sample size (SN) of 5.

[0036] For reference, in Table 1, at the initial diagnosis time point (1), there are no previous diagnosis time points constituting the sample population, so it may be difficult to directly calculate the moving average (MA), standard deviation (SD), standard deviation average (SD_ave), and reference value (Th) (therefore, the corresponding values ​​are displayed as blanks in Table 1). In addition, at a certain diagnosis time point (e.g., 2, 3, 4, 5) adjacent to the initial diagnosis time point (1), the number of multiple previous diagnosis time points constituting the sample population is insufficient, so it may be difficult to calculate the moving average (MA), standard deviation (SD), standard deviation average (SD_ave), and reference value (Th). In this case, the designer can provide values ​​calculated on average through experiments as the moving average (MA), standard deviation (SD), standard deviation average (SD_ave), and reference value (Th) at the initial diagnosis time point and adjacent diagnosis time points (e.g., 1, 2, 3, 4, 5).

[0037] When counting diagnosis times from the current diagnosis time point (N) toward the previous diagnosis time point, the control unit 15 can extract the N-1st diagnosis time point, the N-2nd diagnosis time point, the N-3rd diagnosis time point, the N-4th diagnosis time point, and the N-5th diagnosis time point, which correspond to 5 sample numbers (SN), to determine a sample group.

[0038] The control unit 15 can extract multiple diagnosis time points (N-1, N-2, N-3, N-4, N-5) to determine a sample population, and determine a reference value to be used for defect diagnosis based on the temperature values ​​measured at each of the multiple diagnosis time points within the sample population.

[0039] For example, if the object is a battery, the internal resistance of the battery increases with aging after a certain period of use, and the problem of misdiagnosing a temperature rise caused by the increase in internal resistance as an overheating event can be prevented. Also, the problem of misdiagnosing a temporary temperature rise as an overheating event can be solved.

[0040] Next, the control unit 15 calculates a reference value (Th) corresponding to the Nth diagnostic time point based on the temperature values ​​measured at each of the multiple diagnostic time points (N-1, N-2, N-3, N-4, N-5) belonging to the sample population. N ) to determine

[0041] According to an embodiment, the control unit 15 may determine the temperature value (T N ) to the reference value (Th N ) to diagnose whether the object is overheating. For example, referring to Table 1, the moving average (MA N ), and standard deviation mean (SD N _ave) is the reference value (Th N ) is a value required to calculate the standard deviation (SD N ) is not a value required when diagnosing an overheating state at the Nth diagnosis time point, but is required when diagnosing an overheating state at subsequent diagnosis times (N+1, N+2, ...), so it can be calculated at the Nth diagnosis time point and stored in the storage unit 13.

[0042] Below, referring to Table 1, the moving average value (MA N ), standard deviation (SD N ), standard deviation mean (SD N _ave), and the reference value (Th N ) will be explained.

[0043] The control unit 15 calculates the average (29.4°C+29.3°C+29.4°C+29.3°C+29.5°C / 5=29.38°C) of multiple temperature values ​​(29.4°C, 29.3°C, 29.4°C, 29.3°C, 29.5°C) corresponding to multiple diagnosis time points (N-5, N-4, N-3, N-2, N-1) belonging to the sample population, and calculates the moving average (MA) corresponding to the diagnosis time point (N). N, 29.38℃) can be calculated. In other words, if the sample size (SN) is assumed to be 5, the moving average (MA N ) can be calculated using the following formula (1).

[0044] MA N =(T N-5 +T N-4 +T N-3 +T N-2 +T N-1 ) / 5 … Equation (1)

[0045] Referring to Table 2 below, the control unit 15 calculates the temperature values ​​(T) corresponding to each of a plurality of diagnosis time points (N-5, N-4, N-3, N-2, N-1) belonging to the sample population and the moving average value (MA) calculated using the above formula (1). N ) corresponding to the Nth diagnosis time point N ) can be calculated.

[0046] [Table 2]

[0047] As explained above, the standard deviation (SD) corresponding to the Nth diagnosis time point N ) is not a value required for diagnosing an overheating state at the Nth diagnosis point, but is required for diagnosing whether the object is overheating at the subsequent diagnosis points (N+1, N+2, ...). Therefore, the standard deviation (SD N ) can be calculated at the Nth diagnosis point and stored in the storage unit 13.

[0048] [Table 3]

[0049] Referring to Table 3, the control unit 15 calculates a plurality of standard deviations (SD N-5 , S.D. N-4 , S.D. N-3 , S.D. N-2 , S.D.N-1 ) based on the standard deviation mean (SD N _ave, 0.0742) can be calculated.

[0050] The control unit 15 calculates the moving average value (MA N ) by a predetermined value. In some embodiments, the control unit 15 may calculate an error value (ER) by multiplying the standard deviation average value (SD_ave) by a preset multiple (Q), and may calculate the reference value (Th) by adding the error value (ER) to the moving average value (MA). At this time, the multiple (Q) is a value for setting a standard for whether or not an overheating event has occurred, and may be determined to various values ​​through experiments. Hereinafter, the multiple (Q) is assumed to be a natural number 3.

[0051] Temperature deviations of about ±0.5℃ may occur depending on the type of temperature sensor installed in overheating diagnosis devices to measure the temperature of objects and the type of ADC (Analog-Digital Converter) that converts the measured analog temperature value to a digital temperature value. For precise overheating diagnosis of objects, it is necessary to compensate for the temperature deviation that may occur due to the temperature sensor.

[0052] According to one embodiment, the standard deviation average value (SD_ave) is set to a predetermined deviation reference value (Th_ DV ), the control unit 15 can calculate the error value (ER) by multiplying the standard deviation average value (SD_ave) by a predetermined multiple. DV ) may be a reference value for reflecting errors that may occur during the temperature measurement process. For example, the deviation reference value (Th_ DV ) can be set to 0.5°C, but is not limited to this and can be determined to various values ​​through experiments, etc.

[0053] The standard deviation average value (SD_ave) is the specified deviation reference value (Th_ DV ), the control unit 15 can calculate the error value (ER) using the following formula (2).

[0054] ER = SD_ave × Q … Equation (2)

[0055] In another embodiment, the standard deviation average value (SD_ave) is set to a predetermined deviation reference value (Th_ DV ), the control unit 15 may determine a predetermined correction value (CB) as the error value (ER). At this time, the correction value (CB) may be a value for correcting an error that may occur during the temperature measurement process. For example, the correction value (CB) may be set to 0.5°C, but is not limited thereto and may be determined to various values ​​through experiments, etc.

[0056] ER=CB … Equation (3)

[0057] For example, referring to Table 3, the standard deviation average value (SD N The standard deviation average (SD _ave) corresponding to the Nth diagnosis point can be calculated as 0.0742. N _ave, 0.0742) is the specified deviation standard value (Th_ DV , 0.5) (0.0742<0.5), the control unit 15 can determine the predetermined correction value (CB, 0.5) as the error value (ER).

[0058] The control unit 15 can calculate the reference value (Th) by adding the error value (ER) to the moving average value (MA). For example, when the standard deviation average value (SD_ave) is greater than or equal to a predetermined deviation reference value (Th_ DV ), the control unit 15 can calculate the error value (ER) by multiplying the standard deviation average value (SD_ave) by a predetermined multiple, and can calculate the reference value (Th) by adding the error value (ER) to the moving average value (MA). DV), the control unit 15 determines the correction value (CB) as the error value (ER) and calculates the reference value (Th) by adding the error value (ER) to the moving average value (MA). The control unit 15 can calculate the reference value (Th) by using the following formula (4).

[0059] Th=MA+ER … Equation (4)

[0060] For example, referring to Table 3, the standard deviation average value (SD N _ave, 0.0742) is the deviation standard value (Th_ DV Since the moving average temperature (MA, 29.38) is smaller than the moving average temperature (CB, 0.5), the control unit 15 can determine a predetermined correction value (CB, 0.5) as the error value (ER). The control unit 15 can calculate the reference value (Th) by adding the error value (ER, 0.5°C) to the moving average temperature (MA, 29.38). In other words, the reference value (Th) may be 29.88°C (29.38°C + 0.5°C).

[0061] The control unit 15 determines the temperature (T N ) value and the reference value (Th N ) can be compared to diagnose whether an overheating event has occurred on the object.

[0062] For example, referring to Table 1, the temperature (T N Let us assume that the temperature (T N , 30℃) value corresponds to the reference value (Th N , 29.88° C.), the control unit 35 can diagnose that an overheating event has occurred.

[0063] [Table 4]

[0064] Table 4 above is another example of a look-up table for the object temperature (T), moving average (MA), standard deviation (SD), standard deviation average (SD_ave), and reference value (Th) corresponding to each of multiple diagnosis time points.

[0065] Referring to Table 4, the control unit 15 can determine a sample group by counting the diagnosis time points from the current diagnosis time point (N+1) toward the previous diagnosis time point and extracting the Nth diagnosis time point, the N-1th diagnosis time point, the N-2th diagnosis time point, the N-3th diagnosis time point, and the N-4th diagnosis time point, which correspond to 5 sample numbers (SN).

[0066] The control unit 15 can extract multiple diagnosis time points (N, N-1, N-2, N-3, N-4) to determine a sample population, and determine a reference value to be used for defect diagnosis based on the temperature values ​​measured at each of the multiple diagnosis time points within the sample population.

[0067] The control unit 15 calculates the moving average (MA) corresponding to the N+1th diagnosis time point using Tables 1 to 3 and Equations (1) to (4) described above. N+1 ), standard deviation (SD N+1 ), standard deviation mean (SD N+1 _ave), and the reference value (Th N+1 ) can be calculated.

[0068] FIG. 2 is a block diagram illustrating a battery system according to another embodiment.

[0069] Referring to FIG. 2, the battery system 2 includes a battery 10, a relay 20, and a battery management system (BMS) 30.

[0070] The battery 10 may include a plurality of battery cells connected in series and / or parallel. Although three battery cells connected in parallel are shown in FIG. 2, the battery 10 may include various numbers of battery cells connected in series and / or parallel. In some embodiments, the battery cells may be rechargeable secondary batteries.

[0071] For example, the battery 10 may have a predetermined number of battery cells connected in parallel to form a battery bank, and a predetermined number of battery banks connected in series to form a battery pack, thereby supplying a desired power to an external device. As another example, the battery 10 may have a predetermined number of battery cells connected in parallel to form a battery bank, and a predetermined number of battery banks connected in parallel to form a battery pack, thereby supplying a desired power to an external device. However, the battery 10 is not limited to such a connection, and may include a plurality of battery banks including a plurality of battery cells connected in series and / or parallel, and the plurality of battery banks may also be connected in series and / or parallel.

[0072] 2, a battery 10 is connected between two output terminals OUT1 and OUT2 of a battery system 2. In addition, a relay 20 is connected between the positive electrode of the battery system 2 and the first output terminal OUT1. The configurations and the connections between the configurations shown in FIG 2 are merely examples, and the present invention is not limited thereto.

[0073] The relay 20 controls an electrical connection between the battery system 2 and an external device. When the relay 20 is turned on, the battery system 2 and the external device are electrically connected to perform charging or discharging, and when the relay 20 is turned off, the battery system 2 and the external device are electrically separated. At this time, the external device may be a charger in a charging cycle in which the battery 10 is charged by supplying power to the battery 10, and may be a load in a discharging cycle in which the battery 10 discharges power to the external device.

[0074] The BMS 30 includes a measurement unit 31, a storage unit 33, and a control unit 35. The overheat diagnosis device 1 shown in FIG. 1 can correspond to the BMS 30 shown in FIG. 2. More specifically, the functions performed by the measurement unit 11, the storage unit 13, and the control unit 15 of the overheat diagnosis device 1 can correspond to the functions performed by the measurement unit 31, the storage unit 33, and the control unit 35 of the BMS 30, respectively. For example, the overheat diagnosis device 1 can be configured separately from the battery system 2. As another example, the BMS 30 can perform the function of the overheat diagnosis device 1 in the battery system 2 as shown in FIG. 2.

[0075] Hereinafter, the description of the functions of the measurement unit 31, storage unit 33, and control unit 35 of the BMS 30 will be replaced with the description of the functions of the measurement unit 11, storage unit 13, and control unit 15 of the overheating diagnosis apparatus 1.

[0076] FIG. 3 is a flowchart illustrating an overheating diagnosis method according to an embodiment, and FIG. 4 is a flowchart illustrating in detail the reference value determination step (S300) of FIG.

[0077] 1 to 4, an overheating diagnosis method, and an overheating diagnosis device 1 and a battery system 2 that provide the method will be described below. Although the following description will be given of a measurement unit 31, a storage unit 33, and a control unit 35 of a BMS 30, the same can be applied to the measurement unit 11, the storage unit 13, and the control unit 15 of an overheating diagnosis device 1. In addition, the description will be given of a battery 10, but the present invention is not limited to this and can be applied to various objects requiring temperature measurement.

[0078] First, the control unit 35 collects the measured temperature value of the battery 10 from the measurement unit 31 at a predetermined diagnosis time point for diagnosing overheating of the battery 10 (S100).

[0079] When a diagnosis time point according to a preset condition arrives, the measurement unit 31 can measure the temperature of the battery 10 and transmit the measurement result to the control unit 35. For example, the measurement unit 31 can include a temperature sensor to measure the temperature of the battery 10 at each diagnosis time point and transmit the measurement result to the control unit 35. As another example, the measurement unit 31 can receive a temperature value measured by the temperature sensor at a predetermined time interval or in real time, extract temperature data corresponding to the predetermined diagnosis time point, and transmit the temperature data to the control unit 35.

[0080] Next, the control unit 35 extracts a plurality of previous diagnosis time points corresponding to the number of samples (SN) based on the current diagnosis time point (N) to determine a sample group (S200).

[0081] Referring to Table 1, the control unit 35 can determine a sample group by counting the diagnosis time points from the current diagnosis time point (N) toward the previous diagnosis time point and extracting the N-1th diagnosis time point, the N-2th diagnosis time point, the N-3th diagnosis time point, the N-4th diagnosis time point, and the N-5th diagnosis time point, which correspond to 5 sample numbers (SN).

[0082] The control unit 35 extracts a plurality of diagnosis time points (N-1, N-2, N-3, N-4, and N-5) to determine a sample group, and determines a reference value (Th) to be used for defect diagnosis based on the temperature values ​​measured at each of the plurality of diagnosis time points in the sample group. N ) can be determined by the following method. N ) can prevent the problem of misdiagnosing a temperature rise due to battery aging as an overheating event. It can also solve the problem of misdiagnosing a temporary temperature rise as an overheating event.

[0083] Next, the control unit 35 calculates a reference value (Th) corresponding to the Nth diagnostic time point based on the temperature values ​​measured at each of the multiple diagnostic time points (N-1, N-2, N-3, N-4, N-5) belonging to the sample population. N ) is determined (S300).

[0084] Referring to FIG. 4, in step S300, the control unit 35 averages a plurality of temperature values ​​corresponding to a plurality of diagnosis time points belonging to the sample population to obtain a moving average value (MA) corresponding to the Nth diagnosis time point. N ) is calculated (S310).

[0085] Specifically, referring to Table 1, the control unit 35 calculates the average (29.4°C+29.3°C+29.4°C+29.3°C+29.5°C / 5=29.38°C) of multiple temperature values ​​(29.4°C, 29.3°C, 29.4°C, 29.3°C, 29.5°C) corresponding to multiple diagnosis time points (N-5, N-4, N-3, N-2, N-1) belonging to the sample population, and calculates a moving average (MA) corresponding to the Nth diagnosis time point. N , 29.38℃) can be calculated. In other words, if the sample size (SN) is assumed to be 5, the moving average (MA N ) can be calculated by the above formula (1).

[0086] In step S300, the control unit 35 averages a plurality of standard deviations corresponding to a plurality of diagnosis time points belonging to the sample population to obtain a standard deviation average (SD N _ave) and calculate the standard deviation mean (SD N _ave) (S320).

[0087] Specifically, referring to Table 3, the control unit 35 calculates a plurality of standard deviations (SD N-5 , S.D. N-4 , S.D. N-3 , S.D. N-2 , S.D. N-1 ) based on the standard deviation mean (SD N _ave, 0.0742) can be calculated.

[0088] Temperature deviations of about ±0.5℃ may occur depending on the type of temperature sensor installed in overheating diagnosis devices to measure the temperature of an object and the type of ADC (Analog-Digital Converter) that converts the measured analog temperature value to a digital temperature value. For precise overheating diagnosis of an object, it is necessary to compensate for the temperature deviation that may occur due to the temperature sensor.

[0089] According to one embodiment, the standard deviation average value (SD_ave) is set to a predetermined deviation reference value (Th_ DV ), the control unit 35 can calculate the error value (ER) by multiplying the standard deviation average value (SD_ave) by a predetermined multiple (Q). DV ) may be a reference value for reflecting errors that may occur during the temperature measurement process. For example, the deviation reference value (Th_ DV ) may be set to 0.5, but is not limited thereto and may be determined as various values ​​through experiments, etc. Specifically, the control unit 35 may calculate the error value (ER) using the above formula (2).

[0090] In another embodiment, the standard deviation average value (SD_ave) is set to a predetermined deviation reference value (Th_ DV ), the control unit 35 may determine a predetermined correction value (CB) as the error value (ER). At this time, the correction value (CB) may be a value for correcting an error that may occur during the temperature measurement process. For example, the correction value (CB) may be set to 0.5°C, but is not limited thereto, and may be determined as various values ​​through experiments, etc. Specifically, the control unit 35 may calculate the error value (ER) using the above formula (3).

[0091] For example, referring to Table 3, the control unit 35 calculates the standard deviation average value (SD N The standard deviation (SD _ave) corresponding to the Nth diagnosis point can be calculated as 0.0742. N_ave, 0.0742) is the specified deviation standard value (Th_ DV , 0.5), the control unit 35 can determine the predetermined correction value (CB, 0.5) as the error value (ER, 0.5).

[0092] In step S300, the control unit 35 calculates the reference value (Th) by adding the error value (ER) to the moving average value (MA) (S330).

[0093] For example, if the standard deviation average (SD_ave) is less than a given deviation reference value (Th_ DV ), the control unit 35 can calculate the error value (ER) by multiplying the standard deviation average value (SD_ave) by a predetermined multiple, and can calculate the reference value (Th) by adding the error value (ER) to the moving average value (MA). DV ), the control unit 35 determines the correction value (CB) as the error value (ER) and calculates the reference value (Th) by adding the error value (ER) to the moving average value (MA). The control unit 35 can calculate the reference value (Th) by using the above formula (4).

[0094] For example, referring to Table 3, the standard deviation mean (SD N _ave, 0.0742) is the deviation standard value (Th_ DV Since the moving average temperature (MA, 29.38) is smaller than the moving average temperature (CB, 0.5), the control unit 35 can determine a predetermined correction value (CB, 0.5) as the error value (ER). The control unit 35 can calculate the reference value (Th) by adding the error value (ER, 0.5°C) to the moving average temperature (MA, 29.38). That is, the reference value (Th) may be 29.88°C (29.38°C + 0.5°C).

[0095] Next, the control unit 35 calculates the temperature (T N ) value and the reference value (Th N ) to diagnose whether an overheating event has occurred in the battery 10 (S400).

[0096] Referring to FIG. 3, in step S400, the control unit 35 determines the temperature (T N ) value is the reference value (Th N ) is exceeded (S410).

[0097] If the result of the determination is that the threshold is exceeded (Yes in S410), the control unit 35 diagnoses that an overheating event has occurred in the battery 10 (S420).

[0098] For example, referring to Table 1, the temperature (T N Let us assume that the temperature (T N , 30℃) value corresponds to the reference value (Th N , 29.88° C.), the control unit 35 can diagnose that an overheating event has occurred.

[0099] If the determination result is that the temperature does not exceed the threshold (S410, No), the control unit 35 diagnoses the temperature of the battery 10 as normal (S430).

[0100] FIG. 5 is an example of a temperature change of a non-defective battery in a charging mode, and FIG. 6 is an example of an overheating diagnosis performed on a defective battery in a charging mode.

[0101] In Figures 5 and 6, the X-axis represents time (sec) and the Y-axis represents temperature (°C).

[0102] Referring to FIG. 5, there is shown an example of temperature change over time when a non-defective battery is charged at various external temperatures.

[0103] For example, when the ambient temperature is 25° C., in a charging mode in which the battery 10 is charged by the power of an external device, the temperature change of the battery 10 with time is shown in the first graph T A As another example, when the battery 10 is charged at an ambient temperature of 30° C., the temperature of the battery 10 changes over time as shown in the second graph T BSimilarly, the temperature change of the battery 10 at the atmospheric temperature of 35° C. and the atmospheric temperature of 40° C. is shown in the third graph T C and the fourth graph T D It can handle.

[0104] That is, in the case of a battery 10 that is in a normal state according to a predetermined standard or a new battery 10 that has not been used, the starting temperature value may differ if the external temperature changes, but the temperature change over time (i.e., the slope) may be constant, as shown in FIG. 5.

[0105] Referring to FIG. 6, an example of temperature change versus time when a defective battery is charged at a given external temperature is shown, which is a graph derived through an experiment.

[0106] In this case, the solid line FL is the actually measured temperature of the battery, and the dotted line DL shown close to the solid line FL is the reference line. The reference line may be constructed by connecting reference values ​​calculated at each diagnosis time point according to the embodiment. Referring to Figures 5 and 6, the temperature change of a non-defective battery forms a straight line graph as in Figure 5, while the temperature change of a defective battery may form a curved graph as in Figure 6.

[0107] Conventionally, if the temperature of the battery 10 exceeds a fixed reference value (e.g., 60° C.), an overheating event is diagnosed at that time. Referring to FIG 6, conventionally, overheating of the battery 10 can be first diagnosed at the second time point AD2.

[0108] However, according to an overheating diagnosis method according to an embodiment, it is possible to diagnose the occurrence of an overheating event in advance before the temperature of the battery 10 exceeds a fixed reference value (e.g., 60°C). As a result of an experiment, overheating of the battery 10 was first diagnosed at a first point in time AD1. Specifically, as a result of the diagnosis, an overheating event was continuously diagnosed at each diagnosis point in time from the first point in time AD1, where the solid line FL exceeds the dotted line DL, to the second point in time AD2.

[0109] 6, the experimental result shows that there is a time difference of about 1000 seconds (about 16 minutes) between the first point AD1 and the second point AD2. According to the overheating diagnosis method according to an embodiment, it is possible to recognize the occurrence of an overheating event of the battery 10 in advance and to prepare a countermeasure against the overheating event.

[0110] Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto, and various modifications and improvements made by a person having ordinary skill in the field to which the present invention belongs also fall within the scope of the present invention.

Claims

1. A measurement unit that measures the temperature of an object; A storage unit for storing the temperature value measured by the measurement unit; a control unit for extracting, for each diagnosis time point at which overheating of the object is diagnosed, a plurality of previous diagnosis time points corresponding to a predetermined number of samples based on the diagnosis time point, calculating a moving average value which is an average of a plurality of temperature values ​​corresponding to each of the plurality of diagnosis time points, and comparing the temperature value measured at each diagnosis time point with a reference value which is a predetermined value greater than the moving average value to diagnose overheating of the object, The control unit calculates a standard deviation average value, which is an average of multiple standard deviations corresponding to each of the multiple diagnosis time points, calculates a first error value by multiplying the standard deviation average value by a predetermined multiple, and calculates the reference value by adding the first error value to the moving average value.

2. 2. The overheating diagnosis device of claim 1, wherein if the average standard deviation value is smaller than a predetermined deviation reference value, the control unit determines a predetermined correction value as a second error value and calculates the reference value by adding the second error value to the moving average value.

3. The overheat diagnostic device of claim 1 or 2, wherein the control unit diagnoses that an overheat event has occurred in the object if the measured temperature value exceeds the reference value.

4. a battery including a plurality of battery cells; A measurement unit for measuring a temperature of the battery; A storage unit for storing the temperature value measured by the measurement unit; a control unit for extracting a plurality of previous diagnosis time points corresponding to a predetermined number of samples based on the diagnosis time point for each diagnosis time point at which overheating of the battery is diagnosed, calculating a moving average value which is an average of a plurality of temperature values ​​corresponding to each of the plurality of diagnosis time points, and comparing the temperature value measured at each diagnosis time point with a reference value which is a predetermined value greater than the moving average value to diagnose overheating of the battery, The control unit calculates a standard deviation average value which is an average of multiple standard deviations corresponding to each of the multiple diagnosis time points, multiplies the standard deviation average value by a predetermined multiple to calculate a first error value, and adds the first error value to the moving average value to calculate the reference value.

5. 5. The battery system of claim 4, wherein the control unit determines a predetermined correction value as a second error value when the standard deviation average value is smaller than a predetermined deviation reference value, and calculates the reference value by adding the second error value to the moving average value.

6. The battery system of claim 4 or 5, wherein the control unit diagnoses that an overheating event has occurred in the battery if the measured temperature value exceeds the reference value.

7. A temperature data collection step of collecting temperature values, which are temperature measurements of the battery, at a predetermined diagnosis time point for diagnosing overheating of the battery including a plurality of battery cells; A sample group determination step of extracting a plurality of previous diagnosis time points corresponding to a sample number based on the diagnosis time point; a reference value determining step of calculating a moving average value, which is an average of a plurality of temperature values ​​corresponding to each of the plurality of diagnosis time points, and a reference value which is greater than the moving average value by a predetermined value; and diagnosing overheating of the battery by comparing the temperature value with the reference value; The reference value determination step includes calculating an average standard deviation, which is an average of standard deviations corresponding to each of the multiple diagnosis time points, multiplying the average standard deviation by a predetermined multiple to calculate a first error value, and adding the first error value to the moving average value to calculate the reference value.

8. 8. The overheating diagnosis method according to claim 7, wherein, in the reference value determination step, if the average standard deviation is smaller than a predetermined deviation reference value, a predetermined correction value is determined as a second error value, and the reference value is calculated by adding the second error value to the moving average value.

9. The method of claim 7 or 8, wherein the overheating diagnosis step diagnoses that an overheating event has occurred in the battery if the measured temperature value exceeds the reference value.

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