Overheating diagnostic method, overheating diagnostic device providing the 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-reference to 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 the contents disclosed in the literature of the Korean patent application are included as part of this specification.

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

Background Art

[0003] Recently, the demand for portable electronic products such as notebook computers, video cameras, mobile phones, etc. has increased rapidly. As the development of electric vehicles, energy storage batteries, robots, satellites, etc. becomes full-scale, research on high-performance batteries capable of repeated charging and discharging has been actively carried out.

[0004] Current commercialized batteries include nickel-cadmium batteries, nickel-metal hydride batteries, nickel-zinc batteries, lithium batteries, etc. Among these, lithium batteries have attracted attention for their advantages of almost no memory effect, free charging and discharging, very low self-discharge rate, and high energy density compared to nickel-based batteries.

[0005] On the other hand, the temperature of the battery is an element that has an important influence on the performance of the battery. Generally, when the temperature of the battery is distributed at an appropriate temperature, it can operate efficiently. For example, when the temperature of the battery is excessively high, the performance of the battery may decrease due to a decrease in the safety of the negative electrode crystal lattice of the battery, or it may lead to accidents such as explosions. Therefore, it is necessary to accurately monitor the temperature of the battery.

[0006] Conventionally, battery overheating was diagnosed by comparing the measured battery temperature with a preset reference value. However, this conventional method has a problem in that the time interval between the diagnosis of an overheating event and the actual occurrence of battery explosion or other problems is excessively short, making it difficult to take appropriate measures. Furthermore, this conventional method has the problem of misdiagnosing a temperature rise due to battery aging as an overheating event. [Overview of the project] [Problems that the invention aims to solve]

[0007] The present invention relates to an overheating diagnostic method that can accurately and quickly diagnose abnormal heat generation behavior (hereinafter referred to as overheating) in an object, an overheating diagnostic device that provides this method, and a battery system. [Means for solving the problem]

[0008] An overheating diagnostic device according to one feature of the present invention includes a measuring unit that measures the temperature of an object at each diagnostic point in time for diagnosing overheating of the object, a storage unit that stores the temperature values ​​measured by the measuring unit, and a control unit that, for each diagnostic point in time, extracts a plurality of previous diagnostic points corresponding to a predetermined number of samples based on the diagnostic point in time, calculates a moving average value which is the average of a plurality of temperature values ​​corresponding to each of the plurality of diagnostic points, and diagnoses overheating of the object by comparing the temperature values ​​measured at each diagnostic point in time with a reference value which is a predetermined value greater than the moving average value.

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

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

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

[0012] A battery system according to other features of the present invention includes a battery comprising a plurality of battery cells, a measuring unit that measures the temperature of the battery at each diagnostic time point for diagnosing overheating of the battery, a storage unit that stores the temperature values ​​measured by the measuring unit, and a control unit that, for each diagnostic time point, 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 the average of a plurality of temperature values ​​corresponding to each of the plurality of diagnostic time points, and diagnoses overheating of the battery by comparing the temperature values ​​measured at each diagnostic time point with a reference value which is a predetermined value greater than the moving average value.

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

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

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

[0016] A method for diagnosing overheating according to another feature of the present invention includes a temperature data collection step of collecting temperature values, which are temperature measurements of the battery, at a predetermined diagnostic point for diagnosing overheating of a battery including multiple battery cells; a sample group determination step of extracting multiple previous diagnostic points corresponding to the number of samples based on the diagnostic point; a reference value determination step of calculating a moving average value, which is the average of multiple temperature values ​​corresponding to each of the multiple diagnostic points, and a reference value that is a predetermined value greater than the moving average value; and an overheating diagnosis step of diagnosing overheating of the battery by comparing the temperature values ​​with the reference value.

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

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

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

[0020] Unlike conventional methods that use fixed reference values ​​for diagnosis, this invention calculates a reference value that reflects the temperature trend of the object at each point in time of overheat diagnosis, and performs overheat diagnosis by comparing the calculated reference value with the measured temperature, thereby enabling rapid determination of the occurrence of an overheat event.

[0021] This invention prevents the misdiagnosis of an overheating event as an overheating event by calculating a reference value that reflects the temperature trend of an object at each point in time of overheating diagnosis and comparing the calculated reference value with the measured temperature. [Brief explanation of the drawing]

[0022] [Figure 1] This is a block diagram illustrating an overheating diagnostic device according to one embodiment. [Figure 2] This is a block diagram illustrating a battery system according to another embodiment. [Figure 3] This is a flowchart illustrating the overheating diagnosis method according to the embodiment. [Figure 4] This is a flowchart that explains in detail the reference value determination stage (S300) in Figure 3. [Figure 5] This is an illustrative diagram showing the temperature change of a defect-free battery in charging mode. [Figure 6] This is an example diagram showing an overheating diagnosis performed on a defective battery in charging mode. [Modes for carrying out the invention]

[0023] The embodiments disclosed herein will be described in detail below with reference to the attached drawings, but 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 “part” used for components in the following description are added or mixed for the sole purpose of ease of specification preparation and do not have any distinguishing meaning or role in themselves. Furthermore, in describing the embodiments disclosed herein, if it is determined that a specific description of the relevant prior art may obscure the gist of the embodiments disclosed herein, such detailed description will be omitted. In addition, the attached drawings are merely for the purpose of making the embodiments disclosed herein easy to understand, and it is understood that the technical ideas disclosed herein are not limited by the attached drawings and include all modifications, equivalents or substitutes that fall within the idea and technical scope of the present invention.

[0024] Terms including ordinal numbers, such as "first," "second," etc., can be used to describe a variety of components, but the components are not limited by such terms. These terms are used solely for the purpose of distinguishing one component from another.

[0025] When it is mentioned that one component is “linked” or “connected” to another component, it is understood that it may be directly linked or connected to the other component, but there may also be other components in between. Conversely, when it is mentioned that one component is “directly linked” or “directly connected” to another component, it is understood that there are no other components in between.

[0026] In this application, terms such as “includes” or “having” are intended to specify the presence of features, figures, stages, operations, components, parts, or combinations thereof as described in the specification, and are understood not to pre-exist to exclude the presence or possibility of adding one or more other features, figures, stages, operations, components, parts, or combinations thereof.

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

[0028] Referring to Figure 1, the overheating diagnostic device 1 includes a measurement unit 11, a storage unit 13, and a control unit 15.

[0029] The measurement unit 11 measures the temperature of an object at each diagnostic point (hereinafter referred to as a diagnostic point) where overheating of the object is diagnosed, and can transmit the measurement results to the control unit 15. For example, the measurement unit 11 may include a temperature sensor for measuring the temperature of an object. In this case, the object may include, but is not limited to, a battery, and may include a variety of devices that need to be predicted in advance before an overheating event occurs.

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

[0031] 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 when a diagnostic time point based on pre-set conditions arrives. For example, if the object is a battery, the diagnostic time point may be when the battery charging begins or when the battery discharging ends. However, it is not limited to these, and the diagnostic time point can be set in a variety of ways.

[0032] First, when the control unit 15 counts diagnostic time points in the direction of previous diagnostic time points, based on the current diagnostic time point (N), it can extract multiple diagnostic time points included in a preset number of samples (SN) to determine a sample population. At this time, the number of samples (SN) is the number of multiple diagnostic time points included in the sample population, and can be determined to an optimal number based on experiments or other factors.

[0033] The sample population may be a subgroup of the population at multiple past diagnostic points, and may be a group used to calculate the moving mean (MA) and standard deviation mean (σ_ave), as described below.

[0034] [Table 1]

[0035] Table 1 above is an example of a lock-up table for the temperature (T), moving average (MA), standard deviation (SD), average standard deviation (SD_ave), and reference value (Th) of an object corresponding to multiple diagnostic time points. Below, the reference value (Th) required for overheating diagnosis at the Nth diagnostic time point is shown. N The method for calculating () will be explained in detail. The sample size (SN) will be assumed to be 5.

[0036] For reference, in Table 1, at the initial diagnosis time (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), mean standard deviation (SD_ave), and baseline (Th) (therefore, the corresponding values ​​in Table 1 are shown as blank). Furthermore, at predetermined diagnosis time points adjacent to the initial diagnosis time point (1) (e.g., 2, 3, 4, 5), there are insufficient numbers of previous diagnosis time points that constitute the sample population, making it difficult to calculate the moving average (MA), standard deviation (SD), mean standard deviation (SD_ave), and baseline (Th). In this case, the designer can provide values ​​that are calculated on average by the experiment as the moving average (MA), standard deviation (SD), mean standard deviation (SD_ave), and baseline (Th) for the initial diagnosis time point and adjacent diagnosis time points (e.g., 1, 2, 3, 4, 5).

[0037] When the control unit 15 counts the diagnostic time points in the direction of previous diagnostic time points based on the current diagnostic time point (N), it can extract the N-1st, N-2nd, N-3rd, N-4th, and N-5th diagnostic time points corresponding to the sample size (SN) of 5, and determine the sample population.

[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 population, 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 belonging to the sample population.

[0039] If so, for example, when the object is a battery, if the battery is used for a considerable period of time, the internal resistance value increases due to aging, and it is possible to prevent the problem of misdiagnosing the temperature rise due to the increase in the internal resistance value as the occurrence of a thermal event. In addition, it is possible to solve the problem of misdiagnosing a temporary temperature rise as the occurrence of a thermal event.

[0040] Next, the control unit 15 determines a reference value (Th N ) corresponding to the N-th diagnosis time point based on the temperature values measured at each of a plurality of diagnosis time points (N-1, N-2, N-3, N-4, N-5) belonging to the sample population.

[0041] According to one embodiment, the control unit 15 diagnoses whether the object is overheated by comparing the temperature value (T N ) measured at the N-th diagnosis time point with the reference value (Th N ). For example, referring to Table 1, the moving average value (MA N ), and the standard deviation average (SD N _ave) are values necessary for calculating the reference value (Th N ). However, the standard deviation (SD N ) is not a value necessary for diagnosing the overheated state at the N-th diagnosis time point, but is necessary for diagnosing the overheated state at subsequent diagnosis time points (N+1, N+2,...), so it can be calculated at the N-th diagnosis time point and stored in the storage unit 13.

[0042] Hereinafter, referring to Table 1, the moving average value (MA N ), the standard deviation (SD N ), the standard deviation average (SD N _ave), and the reference value (Th N ) calculated by the control unit 15 at the N-th diagnosis time point will be described.

[0043] The control unit 15 averages a plurality of temperature values (29.4°C, 29.3°C, 29.4°C, 29.3°C, 29.5°C) 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 (29.4°C + 29.3°C + 29.4°C + 29.3°C + 29.5°C / 5 = 29.38°C) to obtain the moving average value (MA NThe moving average (MA) can be calculated at the Nth diagnosis point, assuming a sample size (SN) of 5. N ) can be calculated by 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 value (T) corresponding to each of the multiple diagnostic 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 Based on this, the standard deviation (SD) corresponding to the Nth diagnostic time point is determined. N It is possible to calculate ).

[0046] [Table 2]

[0047] As explained earlier, the standard deviation (SD) corresponding to the Nth diagnostic time point N The standard deviation (SD) corresponding to the Nth diagnostic time point is not a value required when diagnosing the overheating state, but it is required when diagnosing the presence or absence of overheating of the object at subsequent diagnostic time points (N+1, N+2, ...). Therefore, the standard deviation (SD) corresponding to the Nth diagnostic time point is not required. N This value is calculated at the Nth diagnostic stage and can be stored in the storage unit 13.

[0048] [Table 3]

[0049] The control unit 15, referring to Table 3 above, determines multiple standard deviations (SD) corresponding to multiple diagnostic time points (N-5, N-4, N-3, N-2, N-1) belonging to the sample population. N-5 SD N-4 SD N-3 SD N-2 SDN-1 Based on this, the mean standard deviation (SD) corresponding to the Nth diagnostic time point is used. N _ave (0.0742) can be calculated.

[0050] The control unit 15 calculates the moving average value (MA). N A reference value (Th) that is a predetermined value greater than ) can be calculated. In this embodiment, the control unit 15 can calculate an error value (ER) by multiplying the standard deviation mean (SD_ave) by a preset multiple (Q), and then calculate the reference value (Th) by adding the error value (ER) to the moving average (MA). At this time, the multiple (Q) is a value used to set a standard for whether or not an overheating event occurs, and can be determined to a variety of values ​​by experiment. In the following, we assume that the multiple (Q) is a natural number 3.

[0051] Temperature deviations of approximately ±0.5°C can occur depending on the type of temperature sensor used to measure the temperature of an object in overheating diagnostic devices, 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 deviations that may occur due to the temperature sensor.

[0052] In one embodiment, the standard deviation mean (SD_ave) is set to a predetermined deviation reference value (Th_ DV If the value is greater than or equal to ), the control unit 15 can calculate the error value (ER) by multiplying the mean standard deviation (SD_ave) by a predetermined multiple. At this time, the deviation reference value (Th_ DV ) may be a reference value to reflect errors that may occur during the temperature measurement process. For example, the deviation reference value (Th_ DV While it can be set to 0.5℃, it is not limited to this value and can be determined to various values ​​through experiments, etc.

[0053] The standard deviation mean (SD_ave) is equal to a predetermined deviation threshold (Th_ DV If the value is greater than or equal to the specified value, the control unit 15 can calculate the error value (ER) using the following formula (2).

[0054] ER = SD_ave × Q … Equation (2)

[0055] In other embodiments, the standard deviation mean (SD_ave) is set to a predetermined deviation reference value (Th_ DV If the value is less than 0.5°C, the control unit 15 can determine a predetermined correction value (CB) as the error value (ER). In this case, the correction value (CB) may be a value used to correct errors that may occur during the temperature measurement process. For example, the correction value (CB) can be set to 0.5°C, but is not limited to this value and can be determined to various values ​​through experiments, etc.

[0056] ER = CB … Equation (3)

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

[0058] The control unit 15 can calculate a reference value (Th) by adding an error value (ER) to the moving average value (MA). For example, if the standard deviation mean (SD_ave) is equal to a predetermined deviation reference value (Th_ DV If the value is greater than or equal to ), the control unit 15 can calculate the error value (ER) by multiplying the standard deviation mean (SD_ave) by a predetermined multiple, and then calculate the reference value (Th) by adding the error value (ER) to the moving average (MA). As another example, if the standard deviation mean (SD_ave) is greater than or equal to a predetermined deviation reference value (Th_ DVIf the value is less than ), the control unit 15 can determine the correction value (CB) as the error value (ER) and calculate 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 above, the mean standard deviation (SD) corresponding to the Nth diagnostic time point is... N _ave, 0.0742) is the standard deviation value (Th_ DV Since it is less than 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℃) to the moving average value (MA, 29.38). That is, the reference value (Th) may be 29.88℃ (29.38℃ + 0.5℃).

[0061] The control unit 15 determines the temperature (T) measured at the Nth diagnostic time. N ) value and reference value (Th) calculated at the Nth diagnostic time. N By comparing these values, it is possible to diagnose whether or not an overheating event has occurred in the object.

[0062] For example, referring to Table 1, the temperature measured at the Nth diagnostic point (T N Let's assume the value is 30°C. The temperature (T) corresponding to the Nth diagnostic time point. N , 30℃) value corresponds to the reference value (Th) at the Nth diagnostic time point. N Since the temperature exceeds 29.88℃, the control unit 35 can diagnose that an overheating event has occurred.

[0063] [Table 4]

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

[0065] Referring to Table 4, the control unit 15 can determine the sample population by counting the diagnostic time points in the direction of previous diagnostic time points, starting from the current diagnostic time point (N+1), and extracting the Nth, N-1st, N-2nd, N-3rd, and N-4th diagnostic time points, which correspond to the sample size (SN) of 5.

[0066] The control unit 15 can extract multiple diagnostic 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 diagnostic time points belonging to the sample population.

[0067] The control unit 15 uses Tables 1 to 3 and Equations (1) to (4) described above to calculate the moving average (MA) corresponding to the N+1 diagnostic time point. N+1 ), standard deviation (SD N+1 ), standard deviation mean (SD N+1 _ave), and reference value (Th N+1 It is possible to calculate ).

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

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

[0070] Battery 10 may include multiple battery cells connected in series and / or parallel. While Figure 2 shows three battery cells connected in parallel, battery 10 may include any number of battery cells connected in series and / or parallel, and is not limited to this arrangement. In one embodiment, the battery cells may be rechargeable secondary batteries.

[0071] Furthermore, for example, the battery 10 can supply desired power to an external device by connecting a predetermined number of battery cells in parallel to form a battery bank, and by connecting a predetermined number of battery banks in series to form a battery pack. As another example, the battery 10 can supply desired power to an external device by connecting a predetermined number of battery cells in parallel to form a battery bank, and by connecting a predetermined number of battery banks in parallel to form a battery pack. However, it is not limited to such connections, and the battery 10 includes multiple battery banks, each containing multiple battery cells connected in series and / or parallel, and multiple battery banks can also be connected in series and / or parallel.

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

[0073] Relay 20 controls the electrical connection between the battery system 2 and the external device. When relay 20 is turned on, the battery system 2 and the external device are electrically connected for charging or discharging, and when relay 20 is turned off, the battery system 2 and the external device are electrically disconnected. At this time, the external device may be a charger in a charging cycle where power is supplied to charge the battery 10, or a load in a discharging cycle where the battery 10 discharges power to the external device.

[0074] The BMS30 includes a measurement unit 31, a storage unit 33, and a control unit 35. The overheating diagnostic device 1 shown in Figure 1 can correspond to the BMS30 shown in Figure 2. Specifically, the functions performed by the measurement unit 11, storage unit 13, and control unit 15 of the overheating diagnostic device 1 correspond to the functions performed by the measurement unit 31, storage unit 33, and control unit 35 of the BMS30. For example, the overheating diagnostic device 1 can be configured separately from the battery system 2. As another example, as shown in Figure 2, the BMS30 can perform the functions of the overheating diagnostic device 1 within the battery system 2.

[0075] The following explanations of the functions of the measurement unit 31, storage unit 33, and control unit 35 of the BMS30 will be replaced by the explanations of the functions of the measurement unit 11, storage unit 13, and control unit 15 of the overheat diagnostic device 1.

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

[0077] The overheating diagnostic method, the overheating diagnostic device 1 providing this method, and the battery system 2 will be described below with reference to Figures 1 to 4. While the measurement unit 31, storage unit 33, and control unit 35 of the BMS 30 will be described below, the same principles apply to the measurement unit 11, storage unit 13, and control unit 15 of the overheating diagnostic device 1. Furthermore, while the battery 10 will be described, the method is not limited to this and can be applied equally to a variety of objects requiring temperature measurement.

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

[0079] When a diagnostic time point determined by 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 diagnostic 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 a predetermined diagnostic time point, and transmit it to the control unit 35.

[0080] Next, the control unit 35 extracts multiple previous diagnostic time points corresponding to the sample size (SN) based on the current diagnostic time point (N) to determine the sample population (S200).

[0081] Referring to Table 1, the control unit 35 can determine the sample population by counting the diagnostic time points in the direction of previous diagnostic time points, based on the current diagnostic time point (N), and extracting the N-1st, N-2nd, N-3rd, N-4th, and N-5th diagnostic time points, which correspond to the sample size (SN) of 5.

[0082] The control unit 35 extracts multiple diagnostic time points (N-1, N-2, N-3, N-4, N-5) to determine a sample population, and determines a reference value (Th) used for defect diagnosis based on the temperature values ​​measured at each of the multiple diagnostic time points belonging to the sample population. N The reference value (Th) can be determined using the method described below. N By configuring this setting, you can prevent the problem of misdiagnosing temperature increases due to battery aging as overheating events. It also solves the problem of misdiagnosing temporary temperature increases as overheating events.

[0083] Next, the control unit 35 determines 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 decided (S300).

[0084] At step S300, referring to Figure 4, the control unit 35 averages multiple temperature values ​​corresponding to each of the multiple diagnostic time points belonging to the sample population and calculates the moving average value (MA) corresponding to the Nth diagnostic time point. N Calculate (S310).

[0085] Specifically, as shown in Table 1, the control unit 35 averages multiple temperature values ​​(29.4°C, 29.3°C, 29.4°C, 29.3°C, 29.5°C) corresponding to 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) and calculates a moving average value (MA) corresponding to the Nth diagnostic time point. N The moving average (MA) can be calculated at the Nth diagnosis point, assuming a sample size (SN) of 5. N ) can be calculated by the above formula (1).

[0086] At stage S300, the control unit 35 averages the multiple standard deviations corresponding to each of the multiple diagnostic time points belonging to the sample population to obtain the mean standard deviation (SD). N Calculate the average standard deviation (SD) N The error value is calculated based on _ave) (S320).

[0087] Specifically, referring to Table 3, the control unit 35 calculates multiple standard deviations (SD) corresponding to multiple diagnostic time points (N-5, N-4, N-3, N-2, N-1) belonging to the sample population. N-5 SD N-4 SD N-3 SD N-2 SD N-1 Based on this, the mean standard deviation (SD) corresponding to the Nth diagnostic time point is used. N _ave (0.0742) can be calculated.

[0088] Temperature deviations of approximately ±0.5°C can occur depending on the type of temperature sensor used to measure the temperature of an object in overheating diagnostic devices, 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 deviations that may occur due to the temperature sensor.

[0089] In one embodiment, the standard deviation mean (SD_ave) is set to a predetermined deviation reference value (Th_ DV If the value is greater than or equal to ), the control unit 35 can calculate the error value (ER) by multiplying the mean standard deviation (SD_ave) by a predetermined multiple (Q). At this time, the deviation reference value (Th_ DV ) may be a reference value to reflect 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 to this value and can be determined as a variety of values ​​through experiments, etc. Specifically, the control unit 35 can calculate the error value (ER) using the above formula (2).

[0090] In other embodiments, the standard deviation mean (SD_ave) is set to a predetermined deviation reference value (Th_ DV If the value is less than 0.5°C, the control unit 35 can determine a predetermined correction value (CB) as the error value (ER). In this case, the correction value (CB) may be a value used to correct errors that may occur during the temperature measurement process. For example, the correction value (CB) can be set to 0.5°C, but is not limited to this and can be determined to various values ​​through experiments, etc. Specifically, the control unit 35 can calculate the error value (ER) using the above formula (3).

[0091] For example, referring to Table 3, the control unit 35 sets the mean standard deviation (SD) corresponding to the Nth diagnostic time point. N The average standard deviation (SD) corresponding to the Nth diagnostic time point can be calculated as 0.0742. N_ave, 0.0742) is the predetermined deviation standard value (Th_ DV Since it is less than 0.5, the control unit 35 can determine a predetermined correction value (CB, 0.5) as the error value (ER, 0.5).

[0092] At 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, the standard deviation mean (SD_ave) is set to a predetermined deviation threshold (Th_ DV If the standard deviation is greater than or equal to a predetermined deviation reference value (Th), the control unit 35 can calculate the error value (ER) by multiplying the standard deviation mean (SD_ave) by a predetermined multiple, and then calculate the reference value (Th) by adding the error value (ER) to the moving average (MA). As another example, if the standard deviation mean (SD_ave) is greater than or equal to a predetermined deviation reference value (Th_ DV If the value is less than ), 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) using the above formula (4).

[0094] For example, referring to Table 3, the mean standard deviation (SD) corresponding to the Nth diagnostic time point is shown. N _ave, 0.0742) is the standard deviation value (Th_ DV Since it is less than 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℃) to the moving average value (MA, 29.38). That is, the reference value (Th) may be 29.88℃ + 29.38℃ + 0.5℃.

[0095] Next, the control unit 35 checks the temperature (T) measured at the Nth diagnostic time. N ) value and reference value (Th) calculated at the Nth diagnostic time. N By comparing these values, the presence or absence of an overheating event for battery 10 is diagnosed (S400).

[0096] At stage S400, referring to Figure 3, the control unit 35 determines the temperature (T) corresponding to the Nth diagnostic time point. N ) Value is the reference value (Th N Determine if it exceeds (S410).

[0097] If the result exceeds the threshold (S410, Yes), 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 measured at the Nth diagnostic point (T N Let's assume the value is 30°C. The temperature (T) corresponding to the Nth diagnostic time point. N , 30℃) value corresponds to the reference value (Th) at the Nth diagnostic time point. N Since the temperature exceeds 29.88℃, the control unit 35 can diagnose that an overheating event has occurred.

[0099] If the judgment result is not exceeded (S410, No), the control unit 35 diagnoses the temperature of the battery 10 as normal (S430).

[0100] Figure 5 is an example diagram showing the temperature change of a battery without defects in charging mode, and Figure 6 is an example diagram showing an overheat diagnosis performed on a defective battery in charging mode.

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

[0102] Figure 5 is an illustrative diagram showing the temperature change over time when a defect-free battery is charged at various external temperatures.

[0103] For example, when the ambient temperature is 25°C, in a charging mode where the battery 10 is charged by the power of an external device, the temperature change of the battery 10 over time is shown in Graph T1. A This can be handled. As another example, when the ambient temperature is 30°C and the battery 10 is being charged, the temperature change of the battery 10 over time is shown in Graph T2. BIt can handle this. Similarly, the temperature change of battery 10 at ambient temperatures of 35°C and 40°C is shown in graph 3T. C and the fourth graph T D It can handle this.

[0104] In other words, 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 as shown in Figure 5, the temperature change over time (i.e., the slope) may remain constant.

[0105] Referring to Figure 6, this is an illustrative graph showing the temperature change over time when a defective battery is charged at a predetermined external temperature, and it is a graph derived from experiments.

[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, is the reference line. The reference line can be constructed by connecting the reference values ​​calculated for each diagnostic point according to the embodiment. Referring to Figures 5 and 6, the temperature change of a battery without defects forms a linear graph as shown in Figure 5, while the temperature change of a defective battery can form a curved graph as shown in Figure 6.

[0107] Conventionally, if the temperature of the battery 10 exceeded a fixed reference value (for example, 60°C), an overheating event was diagnosed at that point in time. Referring to Figure 6, conventionally, overheating of the battery 10 could be diagnosed for the first time at the second time point AD2.

[0108] However, according to one embodiment of the overheating diagnosis method, 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 (for example, 60°C). In the experimental results, overheating of the battery 10 was first diagnosed at the first time point AD1. Specifically, in the diagnostic results, overheating events were continuously diagnosed at each diagnostic time point from the first time point AD1, when the solid line FL crossed the dotted line DL, to the second time point AD2.

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

[0110] Although embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto. Various modifications and improvements made by persons with ordinary skill in the art to which the present invention belongs also fall within the scope of the present invention.

Claims

1. A measuring unit for measuring the temperature of an object, The measurement unit has a storage unit that stores the temperature value measured by the measurement unit, The control unit includes, for each diagnostic time point in which overheating of the object is diagnosed, extracts a predetermined number of previous diagnostic time points corresponding to the current diagnostic time point, calculates a moving average value which is the average of a plurality of temperature values ​​corresponding to each of the plurality of diagnostic time points, and diagnoses overheating of the object by comparing the temperature value measured at each diagnostic time point with a reference value which is a predetermined value greater than the moving average value, The control unit calculates a mean standard deviation, which is the average of multiple standard deviations corresponding to each of the multiple diagnostic time points. If the mean standard deviation is smaller than a predetermined deviation reference value, it determines a predetermined correction value as the first error value and calculates the reference value by adding the first error value to the moving average value.

2. The overheating diagnostic device according to claim 1, wherein the control unit calculates a second error value by multiplying the standard deviation mean by a predetermined multiple if the standard deviation mean is greater than or equal to a predetermined deviation reference value, and calculates the reference value by adding the second error value to the moving average value.

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

4. A battery containing multiple battery cells, A measuring unit for measuring the temperature of the battery, The measurement unit has a storage unit that stores the temperature value measured by the measurement unit, The control unit includes, for each diagnostic time point in which overheating of the battery is diagnosed, extracts a predetermined number of previous diagnostic time points corresponding to the current diagnostic time point, calculates a moving average value which is the average of a plurality of temperature values ​​corresponding to each of the plurality of diagnostic time points, and diagnoses overheating of the battery by comparing the temperature value measured at each diagnostic time point with a reference value which is a predetermined value greater than the moving average value, The control unit calculates a standard deviation mean, which is the average of multiple standard deviations corresponding to each of the multiple diagnostic time points. If the standard deviation mean is smaller than a predetermined deviation reference value, it determines a predetermined correction value as the first error value and calculates the reference value by adding the first error value to the moving average value.

5. The battery system according to claim 4, wherein the control unit calculates a second error value by multiplying the average standard deviation by a predetermined multiple if the average standard deviation is equal to or greater than a predetermined deviation reference value, and calculates the reference value by adding the second error value to the moving average.

6. The battery system according to 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. At a predetermined diagnostic point in which overheating of a battery containing multiple battery cells is diagnosed, a temperature data acquisition step is performed to collect temperature values, which are temperature measurements of the battery. A sample group determination step in which multiple prior diagnostic time points corresponding to the sample size are extracted based on the aforementioned diagnostic time point, A reference value determination step, which involves calculating a moving average value which is the average of multiple temperature values ​​corresponding to each of the multiple diagnostic time points, and a reference value which is a predetermined value greater than the moving average value, The process includes an overheating diagnosis step in which the temperature value is compared with the reference value to diagnose overheating of the battery, The above-mentioned reference value determination step involves calculating a standard deviation mean, which is the average of the standard deviations corresponding to each of the multiple diagnostic time points; if the standard deviation mean is smaller than a predetermined deviation reference value, a predetermined correction value is determined as the first error value; and the reference value is calculated by adding the first error value to the moving average value.

8. The overheating diagnosis method according to claim 7, wherein the reference value determination step involves, if the average standard deviation is equal to or greater than a predetermined deviation reference value, multiplying the average standard deviation by a predetermined multiple to calculate a second error value, and adding the second error value to the moving average to calculate the reference value.

9. The overheating diagnostic method according to claim 7 or 8, wherein the overheating diagnostic step diagnoses that an overheating event has occurred in the battery if the temperature measurement value exceeds the reference value.

Images