Overheat diagnosis method, overheat diagnosis device that provides said method, and battery system

Abstract

To provide an overheat diagnosis method, an overheat diagnosis device that provides said method, and a battery system.SOLUTION: A battery system according to the present invention includes: a battery including a plurality of battery cells; a measurement unit for measuring the temperature of the battery at each diagnosis time at which overheating of the battery is diagnosed; a preservation unit for preserving the temperature value measured by the measurement unit; and a control unit that extracts, for said each diagnosis time, a plurality of prior diagnosis times corresponding to a prescribed number of samples, with said diagnosis time taken as a point of reference, calculates a moving average value representing the average of a plurality of temperature values corresponding to each of the plurality of diagnosis times, and compares the temperature value measured for said each diagnosis time with a reference value larger by a prescribed value than the moving average value, so as to diagnose the overheating of the battery.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] Cross-Citation of Related Applications This application claims the benefit of priority based on Korean Patent Application No. 10-2022-0061919 filed on May 20, 2022, and all contents disclosed in the documents of this Korean patent application are incorporated herein by reference.

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

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

[0004] Currently available commercial batteries include nickel-cadmium batteries, nickel-metal hydride batteries, nickel-zinc batteries, and lithium batteries. Of these, lithium batteries are attracting attention due to their advantages of being free to charge and discharge as they have almost no memory effect compared to nickel-based batteries, a very low self-discharge rate, and high energy density.

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

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

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

[0008] According to one aspect of the present invention, an overheating diagnosis apparatus includes a measurement unit that measures the temperature of an object at each diagnosis time point at which overheating of the object is diagnosed, a storage unit that stores the temperature values measured by the measurement unit, and a control unit that, for each diagnosis time point, extracts a plurality of previous diagnosis time points corresponding to a predetermined number of samples based on the diagnosis time point, calculates a moving average that is an average of the plurality of temperature values corresponding to each of the plurality of diagnosis time points, and compares the temperature value measured at each diagnosis time point with a reference value that is a predetermined value greater than the moving average 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 diagnostic 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 the temperature of the battery at each diagnosis time point for diagnosing overheating of the battery, a storage unit that stores the temperature values measured by the measurement unit, and a control unit that, for each diagnosis time point, extracts a plurality of previous diagnosis time points corresponding to a predetermined number of samples based on the diagnosis time point, calculates a moving average that is an average of the plurality of temperature values corresponding to each of the plurality of diagnosis time points, and compares the temperature value measured at each diagnosis time point with a reference value that is a predetermined value greater than the moving average 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 diagnostic 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 collection 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 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 determination step of 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 a reference value that is greater than the moving average 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 calculate an average standard deviation, which is the average of standard deviations corresponding to each of the multiple diagnostic time points, calculate a first error value by multiplying the average standard deviation by a predetermined multiple, and calculate the reference value by adding the first error value to the moving average value.

[0018] In the reference value determination step, if the average standard deviation is smaller than a predetermined deviation reference value, a predetermined correction value can be determined as a second error value, and the reference value can be calculated by adding the second error value to the moving average value.

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

[0020] Unlike conventional methods that use fixed reference values 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 quick determination of the occurrence of an overheating event.

[0021] The present invention calculates a reference value that reflects the temperature trend of an object at each time of overheating diagnosis, and compares the calculated reference value with the measured temperature to perform overheating diagnosis, 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 explanation of the drawings]

[0022] [Figure 1] 1 is a block diagram illustrating an overheat diagnostic device according to an embodiment. [Figure 2] FIG. 10 is a block diagram illustrating a battery system according to another embodiment. [Figure 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. [Figure 5] FIG. 10 is an exemplary diagram showing the temperature change of a non-defective battery in a charging mode. [Figure 6] FIG. 10 is an example diagram illustrating an overheat diagnosis performed on a defective battery in charging mode. DETAILED DESCRIPTION OF THE INVENTION

[0023] Hereinafter, the embodiments disclosed herein will be described in detail with reference to the accompanying drawings. Identical or similar components will be assigned the same or similar drawing numbers, and redundant descriptions thereof will be omitted. The suffixes "module" and / or "section" for components used in the following description are assigned or used interchangeably solely for ease of description and do not have any distinct meanings or functions. Furthermore, in describing the embodiments disclosed herein, if it is determined that a detailed description of related publicly known technology may obscure the gist of the embodiments disclosed herein, such a detailed description will be omitted. Furthermore, the accompanying drawings are merely intended to facilitate understanding of the embodiments disclosed herein, and the technical concepts disclosed herein should not be limited by the accompanying drawings, and all modifications, equivalents, or alternatives within the concept and technical scope of the present invention are to be understood.

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

[0025] When a component is said to be "coupled" or "connected" to another component, it is understood that the component may be directly coupled or connected to the other component, but that there may be other components in between. Conversely, when a component is said to be "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 stated in the specification, and are understood not to preclude the possible presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

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

[0028] Referring to FIG. 1, the 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, referred to as a 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 that measures 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 be predicted in advance before an overheating event occurs.

[0030] The storage unit 13 can store the temperature value of the object measured by the measurement unit 11 for each diagnostic 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 diagnostic time point. For example, the temperature value of the object, the moving average (MA), standard deviation (SD), standard deviation average (SD_ave), and reference value (Th) corresponding to a predetermined diagnostic 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 greater than the moving average value by a predetermined value. For example, if the object is a battery, the diagnosis time point may be the time point when charging of the battery starts or the time point when discharging of the battery ends. However, the diagnosis time point is not limited thereto and can be set in various ways.

[0032] First, the control unit 15 may determine a sample group by extracting a plurality of diagnostic time points included in a predetermined number of samples (SN) when counting diagnostic time points from the current diagnostic time point (N) toward the previous diagnostic time point. At this time, the number of samples (SN) is the number of diagnostic 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 the moving average (MA) and standard deviation average (σ_ave), which will be described below.

[0034] [Table 1]

[0035] The above Table 1 shows an example of a lookup 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 a plurality of diagnosis points. Below, the reference value (Th) required for overheat diagnosis at the Nth diagnosis point is N ) is calculated in detail. Also, the sample size (SN) is assumed to be 5.

[0036] For reference, at the initial diagnosis time point (1) in Table 1, there are no previous diagnosis time points that constitute 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). Furthermore, at certain diagnosis time points (e.g., 2, 3, 4, 5) adjacent to the initial diagnosis time point (1), there are an insufficient number of previous diagnosis time points that constitute the sample population, 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 by averaging 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 the diagnosis time points 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 five sample numbers (SN), to determine the sample group.

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

[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 this can prevent a problem of misdiagnosing a temperature increase due to the increase in internal resistance as an overheating event. Also, it can solve the problem of misdiagnosing a temporary temperature increase as an overheating event.

[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 group. 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 ) and diagnose whether the object is overheating. For example, referring to Table 1, N ), and standard deviation mean (SD N _ave) is the reference value (Th N ) is the value required to calculate the standard deviation (SD N ) is not a value required for diagnosing the overheating state at the Nth diagnostic time point, but is required for diagnosing the overheating state at subsequent diagnostic times (N+1, N+2, ...), so it can be calculated at the Nth diagnostic time point and stored in the storage unit 13.

[0042] Referring to Table 1, the moving average value (MA) calculated by the control unit 15 at the time of the Nth diagnosis is as follows: N ), standard deviation (SD N ), standard deviation mean (SD N _ave), and the reference value (Th N ) is explained.

[0043] The control unit 15 calculates the moving average value (MA) corresponding to the diagnosis time point (N) by averaging the multiple temperature values (29.4°C, 29.3°C, 29.4°C, 29.3°C, 29.5°C) corresponding to each of the multiple diagnosis time points (N-5, N-4, N-3, N-2, N-1) belonging to the sample population (29.4°C + 29.3°C + 29.4°C + 29.3°C + 29.5°C / 5 = 29.38°C). N, 29.38℃). That is, 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 the plurality of diagnostic time points (N-5, N-4, N-3, N-2, N-1) belonging to the sample group and the moving average value (MA) calculated using the above formula (1). N ) based on the standard deviation (SD) 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 condition 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 time 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) corresponding to the plurality of diagnostic time points (N-5, N-4, N-3, N-2, N-1) belonging to the sample population. 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) corresponding to the Nth diagnosis time point 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). In this case, 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°C can occur depending on the type of temperature sensor installed in overheating diagnostic devices to measure the temperature of an object, and the type of ADC (Analog-Digital Converter) that converts the measured analog temperature value into 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.

[0052] In 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 (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). In this case, 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 mean value (SD) corresponding to the Nth diagnosis point N The standard deviation (SD _ave) corresponding to the Nth diagnosis point can be calculated as 0.0742. N _ave, 0.0742) is the predetermined deviation standard value (Th_ DV , 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 calculates the error value (ER) by multiplying the standard deviation average value (SD_ave) by a predetermined multiple, and calculates 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) using the following formula (4).

[0059] Th=MA+ER … Equation (4)

[0060] For example, referring to Table 3, the standard deviation mean value (SD) corresponding to the Nth diagnosis point 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 in the object.

[0062] For example, referring to Table 1, the temperature (T N Let us assume that the temperature (T N , 30℃) value was 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 lookup 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 diagnostic time points.

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

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

[0067] The control unit 15 calculates the moving average (MA) corresponding to the N+1th diagnosis time point using the previously described Tables 1 to 3 and Equations (1) to (4). 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 (hereinafter referred to as BMS) 30.

[0070] Battery 10 may include a plurality of battery cells connected in series and / or parallel. While three battery cells connected in parallel are shown in FIG. 2, battery 10 is not limited to this and may include any number 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, or a predetermined number of battery banks connected in series to form a battery pack, thereby supplying 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, or a predetermined number of battery banks connected in parallel to form a battery pack, thereby supplying desired power to an external device. However, the battery 10 is not limited to such connections, and may include a plurality of battery banks, each 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. A relay 20 is connected between the positive terminal of the battery system 2 and the first output terminal OUT1. The configurations and connections between the configurations shown in FIG. 2 are merely examples, and the present invention is not limited thereto.

[0073] The relay 20 controls the electrical connection between the battery system 2 and the 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 disconnected. In this case, the external device may be a charger in a charging cycle that supplies power to the battery 10 to charge it, or a load in a discharging cycle that 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 diagnostic 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, storage unit 13, and control unit 15 of the overheat diagnostic device 1 can correspond to the functions performed by the measurement unit 31, storage unit 33, and control unit 35 of the BMS 30, respectively. For example, the overheat diagnostic device 1 can be configured separately from the battery system 2. As another example, the BMS 30 can perform the function of the overheat diagnostic 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 overheat diagnostic device 1.

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

[0077] 1 to 4, an overheat diagnostic method, an overheat diagnostic device 1 that provides the method, and a battery system 2 will be described below. While the following description will be made of the measurement unit 31, storage unit 33, and control unit 35 of the BMS 30, the same can be applied to the measurement unit 11, storage unit 13, and control unit 15 of the overheat diagnostic device 1. Also, while the description will be made of a battery 10, the present invention is not limited to this and can be applied to various objects that require 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 time point when 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 temperature values measured by the temperature sensor at predetermined time intervals or in real time, extract temperature data corresponding to the predetermined diagnosis time point, and transmit the extracted temperature data to the control unit 35.

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

[0081] Referring to Table 1, when counting the diagnosis time points from the current diagnosis time point (N) toward the previous diagnosis time point, the control unit 35 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 five sample numbers (SN), to determine the sample group.

[0082] The control unit 35 extracts a plurality of diagnostic time points (N-1, N-2, N-3, N-4, 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 diagnostic 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 group. 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 diagnostic time points belonging to the sample group to obtain a moving average value (MA) corresponding to the Nth diagnostic time point. N ) is calculated (S310).

[0085] Specifically, referring to Table 1, the control unit 35 calculates the moving average (MA) corresponding to the Nth diagnostic time point by averaging the multiple temperature values (29.4°C, 29.3°C, 29.4°C, 29.3°C, 29.5°C) corresponding to the multiple diagnostic time points (N-5, N-4, N-3, N-2, N-1) belonging to the sample population (29.4°C + 29.3°C + 29.4°C + 29.3°C + 29.5°C / 5 = 29.38°C). N , 29.38℃). That is, 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 diagnostic time points belonging to the sample population to obtain a mean standard deviation (SD N _ave) and calculate the standard deviation mean (SD N An error value is calculated based on the average value (_ave) (S320).

[0087] Specifically, referring to Table 3, the control unit 35 calculates a plurality of standard deviations (SD) corresponding to a plurality of diagnostic time points (N-5, N-4, N-3, N-2, N-1) belonging to the sample population. 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) corresponding to the Nth diagnosis time point N _ave, 0.0742) can be calculated.

[0088] Temperature deviations of about ±0.5°C can occur depending on the type of temperature sensor installed in overheating diagnostic devices to measure the temperature of an object, and the type of ADC (Analog-Digital Converter) that converts the measured analog temperature value into 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] In 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 ) can be set to 0.5, but is not limited thereto and can be determined as various values through experiments, etc. Specifically, the control unit 35 can calculate the error value (ER) using the above equation (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). In this case, 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 equation (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 predetermined 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 the specified deviation reference value (Th_ DV ), the control unit 35 calculates the error value (ER) by multiplying the standard deviation average value (SD_ave) by a predetermined multiple, and calculates 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) corresponding to the Nth diagnosis point N _ave, 0.0742) is the deviation standard value (Th_ DV Since the moving average value (MA, 29.38) is smaller than the moving average value (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 value (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 ) (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 was the reference value (Th N , 29.88°C), the control unit 35 can diagnose that an overheating event has occurred.

[0099] If the result of the determination 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 overheat 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, in a charging mode in which the battery 10 is charged by power from an external device when the ambient temperature is 25° C., the temperature change of the battery 10 over 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 when the ambient temperature is 35°C and when the ambient temperature is 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 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, this is an example graph derived from an experiment showing temperature change over time when a defective battery is charged at a predetermined external temperature.

[0106] In this case, the solid line FL represents the actually measured battery temperature, and the dotted line DL shown adjacent to the solid line FL represents the reference line. The reference line may be constructed by connecting reference values calculated at each diagnosis point according to an embodiment. Referring to Figures 5 and 6, the temperature change of a battery without a defect forms a straight line graph as in Figure 5, while the temperature change of a defective battery may form a curved line graph as in Figure 6.

[0107] In the past, if the temperature of the battery 10 exceeded a fixed reference value (e.g., 60°C), an overheating event was diagnosed at that time. Referring to Figure 6, in the past, overheating of the battery 10 was 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 from the first point in time AD1, when the solid line FL crosses the dotted line DL, to the second point in time AD2.

[0109] 6, the experimental results show that there is a time difference of about 1000 seconds (about 16 minutes) between the first point AD1 and the second point AD2. The overheating diagnosis method according to one embodiment has the advantage of being able to recognize the occurrence of an overheating event in the battery 10 in advance and to prepare countermeasures against the event.

[0110] Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited to these, and various modifications and improvements made by those skilled in the art to which the present invention pertains also fall within the scope of the present invention.

Claims

1. a measuring unit that measures the temperature of an object; a storage unit for storing the temperature value measured by the measurement unit; and a control unit that, for each diagnostic time point at which overheating of the object is diagnosed, extracts a plurality of previous diagnostic time points corresponding to a predetermined number of samples based on the diagnostic time point, calculates a moving average value which is an average of a plurality of temperature values corresponding to each of the plurality of diagnostic time points, and compares the temperature value measured at each diagnostic time point with a reference value which is a predetermined value greater than the moving average value to diagnose overheating of the object.

2. The overheating diagnostic device of claim 1, wherein the control unit calculates a standard deviation average value, which is an average of multiple standard deviations corresponding to each of the multiple diagnostic 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.

3. 3. The overheating diagnostic device of claim 2, wherein if the average standard deviation 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.

4. The overheat diagnostic device according to claim 1 , wherein the control unit diagnoses that an overheat event has occurred in the object if the measured temperature value exceeds the reference value.

5. a battery including a plurality of battery cells; a measurement unit for measuring the temperature of the battery; a storage unit for storing the temperature value measured by the measurement unit; a control unit that, for each diagnosis time point at which overheating of the battery is diagnosed, extracts 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 which 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 which is a predetermined value greater than the moving average value to diagnose overheating of the battery.

6. 6. The battery system of claim 5, wherein the control unit calculates an average standard deviation, which is an average of multiple standard deviations corresponding to each of the multiple diagnostic time points, calculates a first error value by multiplying the average standard deviation by a predetermined multiple, and calculates the reference value by adding the first error value to the moving average value.

7. 7. The battery system of claim 6, wherein the control unit determines a predetermined correction value as a second error value if the average standard deviation is smaller than a predetermined deviation reference value, and calculates the reference value by adding the second error value to the moving average value.

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

9. a temperature data collection step of collecting temperature values that 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 the number of samples based on the diagnosis time point; a reference value determination step of calculating a moving average value, which is an average of a plurality of temperature values corresponding to each of the plurality of diagnostic time points, and a reference value that is greater than the moving average value by a predetermined value; an overheat diagnosis step of comparing the temperature value with the reference value to diagnose overheating of the battery.

10. 10. The overheating diagnosis method according to claim 9, wherein the reference value determination step calculates an average standard deviation, which is an average of standard deviations corresponding to each of the plurality of diagnosis time points, calculates a first error value by multiplying the average standard deviation by a predetermined multiple, and calculates the reference value by adding the first error value to the moving average value.

11. 11. The overheating diagnosis method according to claim 10, wherein the reference value determination step determines a predetermined correction value as a second error value if the average standard deviation is smaller than a predetermined deviation reference value, and calculates the reference value by adding the second error value to the moving average value.

12. The overheat diagnostic method of claim 9 , wherein the overheat diagnostic step diagnoses that an overheat event has occurred in the battery if the measured temperature value exceeds the reference value.

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