Apparatus and method for diagnosing battery

Abstract

A method for diagnosing a battery according to one aspect of the present disclosure includes: a differential curve generation step of generating, for each predetermined diagnosis cycle, a differential curve representing a relationship between a voltage of the battery and a differential capacity obtained by differentiating a capacity of the battery with respect to the voltage; a target peak detection step in which a target peak is detected among peaks of the differential curve, and along with the increase of the service time of the battery, the differential capacity value of the target peak is decreased and then increased or the voltage value of the target peak is increased and then decreased; a peak information obtaining step of obtaining target peak information including a differential capacity value and a voltage value of the target peak from each of a plurality of differential curves generated while the diagnostic cycle is repeated a plurality of times; and a diagnosis step of diagnosing the state of the battery on the basis of target peak information obtained from the plurality of differential curves.

Description

Technical Field

[0001] This application is based on and claims priority to Korean Patent Application No. 10-2024-0015291, filed with the Korean Intellectual Property Office on January 31, 2024, the disclosure of which is incorporated herein by reference in its entirety.

[0002] This disclosure relates to an apparatus and method for diagnosing batteries, and more particularly to an apparatus and method for nondestructively diagnosing rechargeable and discharging batteries. Background Technology

[0003] Recently, demand for portable electronic products such as laptops, digital cameras, and mobile phones has increased dramatically, and electric vehicles, energy storage systems, robots, and satellites have seen significant development. Therefore, there is active research into high-performance batteries that allow for charging and discharging and possess high energy density.

[0004] Types of rechargeable batteries include lithium-ion batteries, such as lithium-ion or lithium-ion polymer batteries, as well as nickel-cadmium, nickel-metal hydride, and nickel-zinc batteries. Among these batteries, lithium-ion batteries have the following advantages: relatively long lifespan, very low self-discharge rate, and high energy density. Because they have almost no memory effect compared to nickel-based batteries, their applications are gradually expanding.

[0005] The positive and negative electrodes of these batteries gradually deteriorate with repeated charge and discharge cycles, and they no longer maintain the capacity they had at the time of manufacture, but instead deteriorate. Therefore, accurate diagnosis of battery condition is required in order to accurately predict battery life, remaining life, and replacement time.

[0006] However, since existing technologies simply diagnose batteries through the overall state of health (SOH), there are problems with the accuracy and reliability of the diagnostic results, and as a result, efficient management corresponding to the current state of the battery is difficult. Summary of the Invention

[0007] Technical issues

[0008] The technical challenge sought to be addressed in this disclosure is to provide an apparatus and method for diagnosing batteries, which enables real-time diagnosis of battery status while improving the accuracy and reliability of the diagnostic results.

[0009] Another technical challenge that this disclosure seeks to address is to provide an apparatus and method for diagnosing batteries that enables efficient battery management.

[0010] Technical solution

[0011] A method for diagnosing a battery according to one aspect of this disclosure includes: a differential curve generation step, which generates a differential curve representing the relationship between the battery's voltage and differential capacity for each predetermined diagnostic cycle, the differential capacity being obtained by differentiating the battery's capacity relative to the voltage; a target peak detection step, which detects a target peak among the peaks of the differential curve, wherein the differential capacity value of the target peak first decreases and then increases, or the voltage value of the target peak first increases and then decreases, as the battery's usage time increases; a peak information acquisition step, which obtains target peak information, including the differential capacity value and voltage value of the target peak, from each of a plurality of differential curves generated while the diagnostic cycle is repeated multiple times; and a diagnostic step, which detects a trend switching point based on the target peak information obtained from the plurality of differential curves, at which the trend of change of at least one of the differential capacity value and voltage value of the target peak changes from an increasing trend to a decreasing trend or from a decreasing trend to an increasing trend over time, and diagnoses the state of the battery by referring to the trend switching point.

[0012] In an embodiment, the target peak detection step may include: dividing the entire voltage segment of the differential curve into multiple sub-segments that are different from each other and identifying a target sub-segment among the multiple sub-segments; and detecting a peak in the differential curve that is located in the target sub-segment as the target peak.

[0013] In an embodiment, the target sub-segment may be a segment from 4.0 [V] to 4.2 [V].

[0014] In an embodiment, the diagnostic steps may include: detecting a first trend switching point, at which the trend of change of the differential capacity value changes from a decreasing trend to an increasing trend over time; and determining the state of the battery before the first trend switching point as a first deterioration state and the state of the battery after the first trend switching point as a second deterioration state.

[0015] In an embodiment, the diagnostic steps may further include determining that the battery needs to be replaced when the differential capacity value of the target peak exceeds a predetermined first threshold after the first trend switching point.

[0016] In an embodiment, the diagnostic steps may include: detecting a second trend switching point, at which the voltage value change trend changes from an increasing trend to a decreasing trend over time; and determining the battery state before the second trend switching point as a third degradation state and the battery state after the second trend switching point as a fourth degradation state.

[0017] In an embodiment, the diagnostic steps may further include determining that the battery needs to be replaced when the voltage value of the target peak decreases below a predetermined second threshold after the second trend switching point.

[0018] In an embodiment, the method for diagnosing a battery may further include a battery management step that lowers the upper voltage limit of the battery when a trend switching point is detected in the diagnostic step.

[0019] In an embodiment, the battery management steps may include: calculating the difference between a first voltage value and a second voltage value of a target peak, the first voltage value being obtained from the most recently generated differential curve among a plurality of differential curves, and the second voltage value being obtained from a differential curve generated immediately preceding the most recently generated differential curve; and reducing the upper limit of the battery voltage in response to the difference.

[0020] According to another aspect of this disclosure, an apparatus for diagnosing a battery includes: a differential curve generation unit configured to generate, for each predetermined diagnostic cycle, a differential curve representing the relationship between the battery's voltage and differential capacity, wherein the differential capacity is obtained by differentiating the battery's capacity relative to the voltage; a peak information acquisition unit configured to detect a target peak among the peaks of the differential curve, wherein the differential capacity value of the target peak first decreases and then increases, or the voltage value of the target peak first increases and then decreases, as the battery's usage time increases, and to obtain target peak information including the differential capacity value and voltage value of the target peak from each of a plurality of differential curves generated while the diagnostic cycle is repeated multiple times; and a diagnostic unit configured to detect a trend switching point based on the target peak information obtained from the plurality of differential curves, wherein at the trend switching point, the trend of change of at least one of the differential capacity value and voltage value of the target peak changes from an increasing trend to a decreasing trend or from a decreasing trend to an increasing trend over time, and to diagnose the state of the battery by referring to the trend switching point.

[0021] In an embodiment, the diagnostic step unit can be configured to detect a first trend switching point, at which the trend of change of the differential capacity value changes from a decreasing trend to an increasing trend over time, determine the state of the battery before the first trend switching point as a first deterioration state, and determine the state of the battery after the first trend switching point as a second deterioration state.

[0022] In an embodiment, the diagnostic unit may be configured to detect a second trend switching point, at which the voltage value change trend changes from an increasing trend to a decreasing trend over time, determine the battery state before the second trend switching point as a third deterioration state, and determine the battery state after the second trend switching point as a fourth deterioration state.

[0023] In an embodiment, the device for diagnosing the battery may further include a battery management unit configured to reduce the upper limit of the battery voltage when a trend switching point is detected.

[0024] According to another aspect of this disclosure, the battery pack includes the means for diagnosing the battery as described above.

[0025] According to another aspect of this disclosure, a vehicle includes the device for diagnosing the battery as described above.

[0026] Beneficial effects

[0027] According to embodiments of this disclosure, since the battery is diagnosed by generating a differential curve representing the relationship between the battery voltage and differential capacity at each predetermined diagnostic cycle, the differential curve is obtained by differentiating the battery capacity relative to the voltage, thus the battery status can be diagnosed in real time.

[0028] Furthermore, according to embodiments of this disclosure, by detecting a target peak that exhibits specific behavior over time among the peaks appearing in the differential curve and diagnosing the battery based on the changing trend of at least one of the differential capacity value and voltage value of the target peak, changes in the state of the battery can be accurately confirmed, and the accuracy and reliability of the diagnostic results can be improved.

[0029] Furthermore, according to embodiments of this disclosure, by reducing the upper voltage limit of the battery in response to the difference between a first voltage value of the target peak obtained from the latest latest differential curve among a plurality of differential curves generated for each main cycle and a second voltage value of the target peak obtained from the differential curve immediately preceding the latest differential curve, efficient management corresponding to the current state of the battery can be performed, and the battery life can be extended and safety can be improved.

[0030] Furthermore, those skilled in the art to which this disclosure pertains will be able to clearly understand from the following description that various technical problems not mentioned above can be solved according to the various embodiments of this disclosure. Attached Figure Description

[0031] Figure 1 This is a block diagram illustrating an apparatus for diagnosing a battery according to an embodiment of the present disclosure.

[0032] Figure 2 This is a graph showing an example of a capacity-voltage curve.

[0033] Figure 3 This is a diagram showing an example of a differential curve.

[0034] Figure 4 It is a graph showing the overall trend of the differential capacity value of the peak of the differential curve changing over time.

[0035] Figure 5 It is a graph showing the overall trend of the voltage value of the peak of the differential curve changing over time.

[0036] Figure 6 It is shown Figure 3 An enlarged view of region A1 of the differential curve shown.

[0037] Figure 7 This is a graph showing the location of the target peak at the start of battery life.

[0038] Figure 8 This is a graph showing the location of the target peak at the end of battery life.

[0039] Figure 9 It is a graph showing the trend of the differential capacity value of the target peak changing over time.

[0040] Figure 10 It is a graph showing the trend of the voltage value of the target peak changing over time.

[0041] Figure 11 This is a flowchart illustrating a method for diagnosing a battery according to an embodiment of the present disclosure.

[0042] Figure 12 This is a flowchart illustrating a battery management process for diagnosing a battery according to an embodiment of the present disclosure.

[0043] Figure 13 This is a diagram illustrating a battery pack according to an embodiment of the present disclosure.

[0044] Figure 14 This is a diagram illustrating a vehicle according to an embodiment of the present disclosure. Detailed Implementation

[0045] In the following description, to clarify the technical solutions corresponding to the technical challenges of this disclosure, embodiments according to this disclosure will be described in detail with reference to the accompanying drawings. However, when interpreting this disclosure, if the description of related prior art obscures the main points of this disclosure, its description may be omitted. Furthermore, the terminology used in this specification is defined in consideration of the functions in this disclosure, and these terms may vary according to the intentions or practices of the designer, manufacturer, etc. Therefore, the definitions of the terms described below should be based on the content throughout this specification.

[0046] Figure 1 This is a block diagram illustrating an apparatus 100 for diagnosing a battery according to an embodiment of the present disclosure.

[0047] like Figure 1 As illustrated in the figure, a battery diagnostic apparatus 100 according to an embodiment of the present disclosure includes a control unit 110. The control unit 110 controls the overall operation of the battery diagnostic apparatus 100 and is configured to non-destructively diagnose rechargeable and discharging batteries.

[0048] Control unit 110 may include one or more general-purpose processors or one or more ASICs (Application-Specific Integrated Circuits) for performing battery diagnostic logic, and according to one embodiment, may optionally include hardware such as registers and memory. Control unit 110 may be configured with a combination of hardware such as a processor and software such as a computer program. That is, the battery diagnostic logic of control unit 110 may be configured as a computer program and stored in the memory of control unit 110 or storage unit 140 described below, and the stored computer program may be configured to be executed by the hardware of control unit 110.

[0049] Meanwhile, the control unit 110 includes a differential curve generation unit 112, a peak information acquisition unit 114, and a diagnostic unit 116 as detailed components.

[0050] The differential curve generation unit 112 is configured to generate a differential curve for each predetermined diagnostic cycle representing the relationship between the voltage and differential capacity of the target battery for diagnosis, wherein the differential capacity is obtained by differentiating the battery capacity relative to the voltage.

[0051] For example, when a diagnostic cycle is reached, the differential curve generation unit 112 can measure the electrical values ​​of the battery while it is being charged or discharged, and generate a curve representing the relationship between the battery's voltage and capacity.

[0052] Next, the differential curve generation unit 112 can generate a differential curve by differentiating the curve relative to the battery voltage.

[0053] The peak information acquisition unit 114 is configured to detect a target peak among the peaks appearing in the differential curve. As the battery usage time increases, the differential capacity value of the target peak first decreases and then increases, or the voltage value of the target peak first increases and then decreases. The target peak information is obtained from each of the multiple differential curves generated while the diagnostic cycle is repeated multiple times.

[0054] The target peak information includes the differential capacity and voltage values ​​of the target peaks appearing in each differential curve.

[0055] In an embodiment, the peak information acquisition unit 114 can divide the entire voltage segment of each differential curve into multiple sub-segments that are different from each other, determine the target sub-segment among the multiple sub-segments, and detect the peak located in the target sub-segment among the peaks that appear in each differential curve as the target peak.

[0056] In this case, the target sub-segment can be identified as the segment from 4.0[V] to 4.2[V].

[0057] In this way, the peak information acquisition unit 114 can reduce the amount of computation required for target peak detection and shorten the target peak detection time by pre-determining the target sub-segment where the target peak is detected.

[0058] The diagnostic unit 116 confirms the trend of the differential capacity and voltage values ​​of the target peak over time based on the target peak information obtained from multiple differential curves, and diagnoses the battery based on the confirmed trend.

[0059] Specifically, the diagnostic unit 116 detects trend switching points based on target peak information. At the trend switching point, the trend of at least one of the differential capacity value and voltage value of the target peak changes from an increasing trend to a decreasing trend or from a decreasing trend to an increasing trend over time, and the state of the battery is diagnosed with reference to the trend switching point.

[0060] For example, if the trend of the differential capacity value changes from a first trend in which the differential capacity value gradually decreases over time to a second trend in which the differential capacity value gradually increases over time, then the diagnostic unit 116 can determine that a change in the state of the battery has occurred.

[0061] In other words, the diagnostic unit 116 can detect the first trend switching point where the trend of the differential capacity value changes from a decreasing trend to an increasing trend over time, determine the state of the battery before the first trend switching point as the first deterioration state, and determine the state of the battery after the first trend switching point as the second deterioration state, which is different from the first deterioration state.

[0062] For example, a first degradation state could be a state in which the charging / discharging conditions of the battery need to be controlled. Conversely, a second degradation state could be a state in which the upper limit of the battery voltage must be reduced.

[0063] In an embodiment, if the differential capacity value of the target peak exceeds a predetermined first threshold over time after the first trend switching point, the diagnostic unit 116 can determine that the battery needs to be replaced.

[0064] Furthermore, if the voltage value change trend changes from a third trend in which the voltage value gradually increases over time to a fourth trend in which the voltage value gradually decreases over time, then the diagnostic unit 116 can determine that a change in the state of the battery has occurred.

[0065] For example, the diagnostic unit 116 can detect a second trend switching point where the voltage value changes from an increasing trend to a decreasing trend over time, determine the battery state before the second trend switching point as a third deterioration state, and determine the battery state after the second trend switching point as a fourth deterioration state different from the third deterioration state.

[0066] For example, the third degradation state could be a state in which the charging / discharging conditions of the battery need to be controlled. Additionally, the fourth degradation state could be a state in which the upper limit of the battery voltage must be reduced.

[0067] In an embodiment, if the voltage value of the target peak decreases to below a predetermined second threshold over time after the second trend switching point, the diagnostic unit 116 can determine that the battery needs to be replaced.

[0068] In an embodiment, when the trend of the differential capacity value changes from a decreasing trend to an increasing trend and when the trend of the voltage value changes from an increasing trend to a decreasing trend, the diagnostic unit 116 can determine that a change in the state of the battery has occurred.

[0069] Furthermore, if the differential capacity value changes from a decreasing trend to an increasing trend and the voltage value changes from an increasing trend to a decreasing trend, and the differential capacity value of the target peak exceeds the first threshold or the voltage value of the target peak decreases to below the predetermined second threshold, then the diagnostic unit 116 can determine that the battery needs to be replaced.

[0070] In an embodiment, the control unit 110 may further include a diagnostic result notification unit 118a. The diagnostic result notification unit 118a may be configured to output a visual, auditory, or audiovisual notification signal corresponding to the diagnostic result of the battery using a predetermined output device.

[0071] In an embodiment, the control unit 110 may further include a battery management unit 118b. The battery management unit 118b may be configured to control the charging and / or discharging conditions of the battery based on the diagnostic results of the diagnostic unit 116.

[0072] For example, the battery management unit 118b can control the charging / discharging device 16, described later, to appropriately adjust the battery voltage range, the charging current and / or the current rate of the discharging current, etc. Furthermore, the battery management unit 118b can control the cooling device 18, described later, to reduce the battery temperature.

[0073] In an embodiment, when battery degradation is diagnosed, the battery management unit 118b can be configured to reduce the battery voltage at the end of charging in response to the difference between the current voltage value of the target peak and a predetermined reference voltage value. The reference voltage value may be the voltage value of the target peak measured at the start of battery life (BOL) or a voltage value determined during battery design.

[0074] In an embodiment, the battery management unit 118b can be configured to reduce the upper limit of the battery voltage when the first trend switching point or the second trend switching point is detected.

[0075] For example, the battery management unit 118b can calculate the difference between the current voltage value of the target peak obtained from the latest differential curve, which is the most recently generated differential curve among a plurality of differential curves generated for each diagnostic cycle, and the previous voltage value of the target peak obtained from the differential curve generated immediately before the latest differential curve.

[0076] In addition, the battery management unit 118b can reduce the upper limit of the battery voltage in response to the calculated difference.

[0077] The differential curve generation unit 112, peak information acquisition unit 114, diagnostic unit 116, diagnostic result notification unit 118a, and battery management unit 118b of the aforementioned control unit 110 can be implemented as a combination of a processor and a program executed by the processor. In this case, the control unit 110 can be implemented as a single processor, or it can be implemented as two or more interconnected processors.

[0078] In an embodiment, the device 100 for diagnosing the battery may further include a communication unit 120. The communication unit 120 may be configured to receive data transmitted from other servers or communication terminals via wired and / or wireless communication networks, and to transmit the data to the control unit 110, or to transmit control signals, diagnostic data, etc., processed by the control unit 110 to other servers or communication terminals. For this purpose, the communication unit 120 may include a communication modem performing wired and / or wireless communication.

[0079] In an embodiment, the device 100 for diagnosing the battery may further include an input unit 130. The input unit 130 may be configured to receive commands or data from a system operator or administrator. For this purpose, the input unit 130 may include input devices such as a keyboard, operation buttons, or a touchpad.

[0080] In an embodiment, the device 100 for diagnosing the battery may further include a storage unit 140. The storage unit 140 may be configured to store and manage data required for the operation of the device 100 for diagnosing the battery. For this purpose, the storage unit 140 may include one or more of ROM, RAM, EEPROM, registers, flash memory, CD-ROM, magnetic tape, hard disk, floppy disk, and optical data recording devices.

[0081] In an embodiment, the device 100 for diagnosing the battery may further include an output unit 150. The output unit 150 may be configured to output a notification signal from the diagnostic result notification unit 118a visually, audibly, or audiovisually. For this purpose, the output unit 150 may include a visual output device, such as a light-emitting diode, a monitor, a display panel, or a touchscreen. Furthermore, the output unit 150 may also include a sound generating device, such as a speaker.

[0082] In an embodiment, the device 100 for diagnosing the battery may be configured to interlock with a measuring device 12 for measuring the battery's voltage, charging current, and / or discharging current, a communication device 14 for communicating with another device, a charging / discharging device 16 for charging and discharging the battery, a cooling device 18 for cooling the battery, etc.

[0083] In another embodiment, the device 100 for diagnosing a battery according to the present disclosure may include one or more of the above-described measuring device 12, communication device 14, charging / discharging device 16, and cooling device 18.

[0084] Figure 2 This is a graph showing an example of the capacity-voltage curve BP.

[0085] like Figure 2 As shown in the diagram, when the diagnostic cycle is reached, the differential curve generation unit 112 can generate a curve BP representing the relationship between the battery's voltage and capacity by measuring the battery's electrical values ​​while the battery is being charged or discharged.

[0086] In this case, the differential curve generation unit 112 can find positive electrode curve PP and negative electrode curve NP that are similar to the battery curve BP by combining with each other, and provide the start point pi and end point pf of the positive electrode curve PP and the start point ni and end point nf of the negative electrode curve NP to the diagnostic unit 116. The diagnostic unit 116 can use the start point pi and end point pf of the positive electrode curve PP and the start point ni and end point nf of the negative electrode curve NP as diagnostic factors representing the state of the battery.

[0087] In addition, the differential curve generation unit 112 can generate a differential curve by differentiating the curve BP relative to the battery voltage.

[0088] Figure 3 This is a diagram showing an example of the differential curve DP.

[0089] like Figure 3 As shown in the figure, the differential curve generation unit 112 is configured to generate a differential curve DP1 for each predetermined diagnostic cycle, representing the relationship between the battery voltage and the differential capacity (dQ / dV), which is obtained by differentiating the battery capacity relative to the voltage.

[0090] Then, the peak information acquisition unit 114 is configured to acquire target peak information from each differential curve generated for each diagnostic cycle. Here, the target peak information may include the differential capacity value and voltage value of the target peak P5 detected among the multiple peaks P1 to P5 of the corresponding differential curve DP1.

[0091] The target peak P5 is a peak that exhibits unique behavior as the battery's usage time increases. In other words, the target peak P5 can be a peak whose differential capacity value first decreases and then increases, or whose voltage value first increases and then decreases, as the battery's usage time increases.

[0092] In other words, the entire voltage range of the differential curve DP1 can be divided into multiple sub-segments S1 to S5 based on the peaks P1 to P5 of the differential curve DP1.

[0093] Among these multiple sub-segments S1 to S5, a target sub-segment S5 that exhibits a peak that behaves differently from the other peaks over time can be predetermined. The target sub-segment S5 can be defined as the segment from 4.0 [V] to 4.2 [V].

[0094] For example, the peak information acquisition unit 114 can detect peak P5 located in the target sub-segment S5 as the target peak among the multiple peaks P1 to P5 of each differential curve.

[0095] Figure 4 It is a graph showing the overall trend of the differential capacity value of the peak of the differential curve changing over time.

[0096] Figure 5 It is a graph showing the overall trend of the voltage value of the peak of the differential curve changing over time.

[0097] like Figure 4 and Figure 5 As shown, among the multiple peaks P1 to P5 of the differential curve DP1, except for the target peak P5, the other peaks exhibit the following trend: as time passes or the number of charge / discharge cycles increases, the differential capacity value (i.e., intensity) decreases while the voltage value increases. This trend is analyzed as being attributed to the loss of positive electrode capacity and the increase in resistance of the battery.

[0098] On the other hand, the target peak P5 shows a similarity to... Figure 4 and Figure 5 The trends shown are different trends.

[0099] Figure 6 It is shown Figure 3 An enlarged view of region A1 of the differential curve shown.

[0100] like Figure 6 As shown, the target peak P5 of the differential curve DP1 generated at the BOL point of the battery can have a voltage value V1.

[0101] Figure 7 This is a graph showing the location of the target peak P5' at the beginning of battery life.

[0102] like Figure 7As shown, at the target peak P5' of the differential curve DP2 generated at the beginning of the battery's life, the differential capacity value can decrease, as in the general trend described above, and its voltage value can have a voltage value V2 that is greater than the previous voltage value V1.

[0103] Figure 8 This is a graph showing the location of the target peak P5'' at the end of battery life.

[0104] like Figure 8 As shown, at the target peak P5'' of the differential curve DP3 generated at the end of the battery's life, unlike the overall trend described above, the differential capacity value increases, and its voltage value V3 is less than the voltage value V1.

[0105] The specific behavior of these target peaks P5, P5', and P5'' is related to the loss of positive electrode capacity and the increase in battery internal resistance.

[0106] Therefore, the diagnostic unit 116 can confirm the trend of the differential capacity value and voltage value of the target peak over time based on the peak information obtained while the diagnostic cycle is repeated multiple times, and diagnose the battery based on the confirmed trend.

[0107] In addition, if battery degradation is diagnosed, the battery management unit 118b can reduce the upper limit of the battery voltage in response to the difference (ΔV) between the current voltage value V3 and the voltage value V1 of the target peak P5'', that is, the voltage value of the battery when charging is terminated, thereby extending the battery life and ensuring battery safety.

[0108] Figure 9 It is a graph showing the trend of the differential capacity value of the target peak changing over time.

[0109] like Figure 9 As shown, the trend of the differential capacity value of the target peak P5 can be a first trend TL1 that gradually decreases over time, and then changes to a second trend TL2 that gradually increases over time after the first trend switching point t1.

[0110] In this case, the diagnostic unit 116 can detect the first trend switching point t1 when the trend of the differential capacity value changes from a decreasing trend to an increasing trend over time, determine the state of the battery before the first trend switching point t1 as the first deterioration state, and determine the state of the battery after the first trend switching point t1 as the second deterioration state, which is different from the first deterioration state.

[0111] Figure 10 It is a graph showing the trend of the voltage value of the target peak changing over time.

[0112] like Figure 10As shown, the voltage value of the target peak P5 can be shown as a third trend TL3 that gradually increases over time, and then changes from the second trend switching point t3 to a fourth trend TL4 that gradually decreases over time.

[0113] In this case, the diagnostic unit 116 can detect the second trend switching point t3 where the voltage value changes from an increasing trend to a decreasing trend over time, determine the battery state before the second trend switching point t3 as the third deterioration state, and determine the battery state after the second trend switching point t3 as the fourth deterioration state, which is different from the third deterioration state.

[0114] Figure 11 This is a flowchart illustrating a method for diagnosing a battery according to an embodiment of the present disclosure.

[0115] like Figure 11 The method for diagnosing a battery, as illustrated in the figure, is a method for non-destructively diagnosing a battery capable of charging and discharging, and can be executed by a processor.

[0116] First, the processor generates a differential curve at each predetermined diagnostic cycle, representing the relationship between the voltage of the target battery and its differential capacity, which is obtained by differentiating the battery's capacity relative to the voltage (S10).

[0117] For example, when a diagnostic cycle arrives, the processor can measure the battery's electrical values ​​while the battery is being charged or discharged, and generate a curve representing the relationship between the battery's capacity and voltage.

[0118] The processor can then generate a differential curve by differentiating the curve relative to the battery voltage.

[0119] Next, the processor detects the target peak among the peaks appearing in the differential curve. As the battery usage time increases, the differential capacity value of the target peak first decreases and then increases, or the voltage value of the target peak first increases and then decreases. The processor obtains and stores the target peak information from each of the multiple differential curves generated while the diagnostic cycle is repeated multiple times (S20).

[0120] In this case, the target peak information includes the differential capacity value and voltage value of the target peak in each differential curve.

[0121] In an embodiment, the processor can divide the entire voltage segment of each differential curve into multiple sub-segments that are different from each other, determine the target sub-segment among the multiple sub-segments, and detect the peak located in the target sub-segment among the peaks that appear in each differential curve as the target peak.

[0122] In this case, the target sub-segment can be identified as the segment from 4.0[V] to 4.2[V].

[0123] In this way, the processor can reduce the amount of computation required for target peak detection and shorten the target peak detection time by pre-determining the target sub-segment that was detected.

[0124] Then, based on the target peak information obtained from multiple differential curves, the processor checks the trend of the differential capacity value and voltage value of the target peak over time, and diagnoses the battery based on the checked trend (S30).

[0125] Specifically, the processor detects trend switching points based on target peak information. At the trend switching point, the trend of at least one of the differential capacity value and voltage value of the target peak changes from an increasing trend to a decreasing trend or from a decreasing trend to an increasing trend over time. The state of the battery is diagnosed by referring to the trend switching point.

[0126] For example, if the trend of the differential capacity value changes from a first trend of the differential capacity value gradually decreasing over time to a second trend of the differential capacity value gradually increasing over time, the processor can determine that battery degradation or a change in degradation state has occurred (S40).

[0127] In other words, the processor can detect the first trend switching point where the trend of the differential capacity value changes from a decreasing trend to an increasing trend over time, determine the state of the battery before the first trend switching point as the first deterioration state, and determine the state of the battery after the first trend switching point as the second deterioration state, which is different from the first deterioration state.

[0128] For example, a first degradation state could be a state in which the charging / discharging conditions of the battery need to be controlled. Conversely, a second degradation state could be a state in which the upper limit of the battery voltage must be reduced.

[0129] In an embodiment, if the differential capacity value of the target peak exceeds a predetermined first threshold over time after the first trend switching point, the processor can determine that the battery needs to be replaced.

[0130] Furthermore, if the voltage value change trend changes from a third trend in which the voltage value gradually increases over time to a fourth trend in which the voltage value gradually decreases over time, the processor can determine that battery degradation or a change in degradation state has occurred.

[0131] For example, the processor can detect a second trend switching point where the voltage value changes from an increasing trend to a decreasing trend over time, determine the battery state before the second trend switching point as a third deterioration state, and determine the battery state after the second trend switching point as a fourth deterioration state, which is different from the third deterioration state.

[0132] For example, the third degradation state could be a state in which the charging / discharging conditions of the battery need to be controlled. Additionally, the fourth degradation state could be a state in which the upper limit of the battery voltage must be reduced.

[0133] In an embodiment, if the voltage value of the target peak decreases to below a predetermined second threshold over time after the second trend switching point, the processor can determine that the battery needs to be replaced.

[0134] In an embodiment, when the trend of the differential capacity value changes from a decreasing trend to an increasing trend and the trend of the voltage value changes from an increasing trend to a decreasing trend, the processor can determine that a change in the state of the battery has occurred.

[0135] In addition, after the trend of the differential capacity value changes from a decreasing trend to an increasing trend and the trend of the voltage value changes from an increasing trend to a decreasing trend, if the differential capacity value of the target peak exceeds the first threshold or the voltage value of the target peak decreases to below the predetermined second threshold, the processor can determine that the battery needs to be replaced.

[0136] Then, the processor adjusts the battery charging and / or discharging conditions based on the battery diagnostic results (S50).

[0137] For example, the processor can control the reference Figure 1 The described charging / discharging device 16 appropriately adjusts the battery voltage range, the battery charging current, and / or the current rate of the discharging current. Additionally, the battery management unit 118b can be referenced... Figure 1 Control the cooling device 18 to reduce the battery temperature.

[0138] In one embodiment, if battery degradation is diagnosed, the processor can be configured to reduce the battery voltage at the end of charging in response to the difference between the current voltage value of the target peak and a predetermined reference voltage value. The reference voltage value may be the voltage value of the target peak measured at the start of battery life (BOL) or a voltage value determined during battery design.

[0139] At the same time, the processor can use a predetermined output device to output visual, auditory, or audiovisual notification signals corresponding to the diagnostic results of the battery.

[0140] Next, the processor can repeat the above steps (S10 to S50) for each diagnostic cycle until the battery is no longer in use (S60).

[0141] Figure 12 This is a flowchart illustrating a battery management process for diagnosing a battery according to an embodiment of the present disclosure.

[0142] like Figure 12 As shown, the processor can determine the trend of the differential capacity value and / or voltage value of the target peak over time based on multiple sequentially generated differential curves (S51).

[0143] Furthermore, the processor can manage the battery in different ways depending on whether the trend of change of the differential capacity value of the detected target peak changes from a decreasing trend to an increasing trend over time, or whether the trend of change of the voltage value of the target peak changes from an increasing trend to a decreasing trend over time.

[0144] If neither the first trend switching point nor the second trend switching point is detected, the processor can typically control the charging and discharging conditions of the battery. For example, the processor can reduce the current rate of the battery's charging current and / or discharging current, or reduce the battery's temperature (S52, S53).

[0145] On the other hand, if at least one of the first trend switching point and the second trend switching point is detected, the processor can calculate the difference between the current voltage value of the target peak obtained from the latest recently generated differential curve among a plurality of differential curves and the previous voltage value of the target peak obtained from the differential curve generated immediately before the latest differential curve (S54).

[0146] Furthermore, the processor can reduce the upper limit of the battery voltage in response to the calculated difference (S55).

[0147] Figure 13 This is a diagram illustrating a battery pack 10 according to an embodiment of the present disclosure.

[0148] like Figure 13 As shown, the battery pack 10 includes a battery B that allows charging and discharging, and a device 100 for diagnosing the battery according to this disclosure. In embodiments, the battery pack 10 may optionally also include a measuring device 12, a communication device 14, a charging / discharging device 16, and a cooling device 18.

[0149] The measuring device 12 can be configured to measure the voltage and / or current of the battery B. For this purpose, the measuring device 12 may include a voltage sensor for sensing the voltage of the battery B and / or a current sensor 12b for sensing the current of the battery B.

[0150] The measuring device 12 can measure the voltage of battery B via the first sensing line SL1 and the second sensing line SL2. Additionally, the measuring device 12 can measure the current of battery B via the third sensing line SL3 connected to the current measuring circuit A. The current measuring circuit A may include a shunt resistor.

[0151] According to an embodiment of this disclosure, the apparatus 100 for diagnosing a battery can obtain the voltage value of battery B through measuring device 12. For reference, the capacity of battery B can be calculated by applying the current integration method.

[0152] The communication device 14 can be configured to perform communication with another remotely located device. For example, the communication device 14 can be configured to receive data sent from a remote server or communication terminal via a wired and / or wireless communication network, and send the data to the device 100 for diagnosing the battery, or send data generated in the device 100 for diagnosing the battery to another server or communication terminal. For this purpose, the communication device 14 may include a communication modem that performs wired and / or wireless communication.

[0153] The charging / discharging device 16 can be configured to charge and / or discharge the battery B. For this purpose, the charging / discharging device 16 may include a charger for charging the battery B, a discharger for discharging the battery B, at least one switch for electrically connecting the battery B to terminals T1 and T2 of the battery pack 10, etc.

[0154] According to embodiments of the present disclosure, the device 100 for diagnosing a battery can control the charging / discharging device 16 to perform or stop charging or discharging of the battery B, set charging / discharging conditions, or change the set charging / discharging conditions.

[0155] The cooling device 18 can be configured to cool the battery B. To this end, the cooling device 18 may include a heat sink that absorbs heat from the battery B and releases it to the outside.

[0156] Figure 14 This is a diagram illustrating a vehicle 2 according to an embodiment of the present disclosure.

[0157] like Figure 14 As shown, a vehicle 2 according to an embodiment of the present disclosure may include a battery pack 10 that provides electrical energy required for the operation of the vehicle and a device 100 for diagnosing the battery according to the present disclosure.

[0158] In this case, the device 100 for diagnosing the battery can be configured to interact with the ECU (electronic control unit) that controls the operation of the vehicle 2 or the BMS (battery management system) of the battery pack 10.

[0159] Additionally, the device 100 for diagnosing the battery can be configured to receive data sent from a remote server 4 via a wired and / or wireless communication network, or to send data generated by the device 100 for diagnosing the battery to the server 4.

[0160] For reference, the device 100 for diagnosing batteries according to this disclosure can be applied to various electrical devices or electrical systems other than vehicles, as well as ESS (energy storage systems).

[0161] Furthermore, embodiments of this disclosure can be implemented as a computer system and a computer program operating the computer system. When embodiments of this disclosure are implemented as a computer program, the components of this disclosure may include program segments that perform corresponding operations or tasks through a corresponding computer system. These computer programs or program segments may be stored in various computer-readable recording media. Computer-readable recording media may include all types of media that record data readable by a computer system. For example, computer-readable recording media may include ROM, RAM, EEPROM, registers, flash memory, CD-ROM, magnetic tape, hard disk, floppy disk, or optical data recording devices. Additionally, these recording media may be distributed across various network-connected computer systems to store or execute program code in a distributed manner.

[0162] As described above, according to embodiments of this disclosure, since the battery is diagnosed by generating a differential curve representing the relationship between the battery voltage and differential capacity at each predetermined diagnostic cycle, and this differential curve is obtained by differentiating the battery capacity relative to the voltage, the state of the battery can be diagnosed in real time.

[0163] Furthermore, according to embodiments of this disclosure, by detecting a target peak that exhibits specific behavior over time among the peaks appearing in the differential curve, and diagnosing the battery based on the changing trend of at least one of the differential capacity value and voltage value of the target peak, changes in the state of the battery can be accurately confirmed, and the accuracy and reliability of the diagnostic results can be improved.

[0164] Furthermore, according to embodiments of this disclosure, by reducing the upper voltage limit of the battery in response to the difference between a first voltage value of the target peak obtained from the latest latest differential curve among a plurality of differential curves generated for each main cycle and a second voltage value of the target peak obtained from the differential curve immediately preceding the latest differential curve, efficient management corresponding to the current state of the battery can be performed, and the battery life can be extended and safety can be improved.

[0165] Furthermore, embodiments of this disclosure can solve various technical problems in the corresponding and related technical fields, in addition to those mentioned in this specification.

[0166] This disclosure has been described with reference to specific embodiments. However, those skilled in the art will clearly understand that various modified embodiments can be implemented within the technical scope of this disclosure. Therefore, the embodiments disclosed above should be considered illustrative rather than restrictive. In other words, the true technical scope of this disclosure is indicated by the claims, and all differences within their equivalents should be interpreted as being included in this disclosure.

Claims

1. A method for diagnosing a battery, comprising: A differential curve generation step generates a differential curve representing the relationship between the battery's voltage and differential capacity for each predetermined diagnostic cycle, wherein the differential capacity is obtained by differentiating the battery's capacity relative to the voltage. The target peak detection step detects the target peak among the peaks of the differential curve. As the battery usage time increases, the differential capacity value of the target peak first decreases and then increases, or the voltage value of the target peak first increases and then decreases. The peak information acquisition step obtains target peak information, including the differential capacity value and the voltage value of the target peak, from each of a plurality of differential curves generated while the diagnostic cycle is repeated multiple times. as well as The diagnostic step detects a trend switching point based on the target peak information obtained from the plurality of differential curves, at which the trend of change of at least one of the differential capacity value and the voltage value of the target peak changes from an increasing trend to a decreasing trend or from a decreasing trend to an increasing trend over time, and the state of the battery is diagnosed by referring to the trend switching point.

2. The method for diagnosing a battery according to claim 1, in, The target peak detection step includes: The steps of dividing the entire voltage region of the differential curve into multiple distinct sub-regions and determining the target sub-region among these sub-regions; and The step of detecting the peaks of the differential curve that are located in the target sub-segment as the target peak.

3. The method for diagnosing a battery according to claim 2, in, The target sub-segment is the segment from 4.0[V] to 4.2[V].

4. The method for diagnosing a battery according to claim 1, in, The diagnostic steps include: The step of detecting the first trend switching point, at which point the trend of change of the differential capacity value changes from a decreasing trend to an increasing trend over time; and The steps of determining the state of the battery before the first trend switching point as a first deterioration state and the state of the battery after the first trend switching point as a second deterioration state.

5. The method for diagnosing a battery according to claim 4, in, The diagnostic steps also include determining that the battery needs to be replaced when the differential capacity value of the target peak exceeds a predetermined first threshold after the first trend switching point.

6. The method for diagnosing a battery according to claim 1, in, The diagnostic steps include: The step of detecting the second trend switching point, at which point the voltage value's change trend changes from an increasing trend to a decreasing trend over time; and The steps of determining the state of the battery as a third degradation state before the second trend switching point and the state of the battery as a fourth degradation state after the second trend switching point.

7. The method for diagnosing a battery according to claim 6, in, The diagnostic steps also include determining that the battery needs to be replaced when the voltage value of the target peak decreases below a predetermined second threshold after the second trend switching point.

8. The method for diagnosing a battery according to claim 1, further comprising: A battery management step that reduces the upper voltage limit of the battery when the trend switching point is detected in the diagnostic step.

9. The method for diagnosing a battery according to claim 8, in, The battery management steps include: The step of calculating the difference between a first voltage value and a second voltage value of the target peak, wherein the first voltage value is obtained from the most recently generated differential curve among the plurality of differential curves, and the second voltage value is obtained from a differential curve generated immediately preceding the most recently generated differential curve; and The step of reducing the upper voltage limit of the battery in response to the difference.

10. An apparatus for diagnosing a battery, comprising: A differential curve generation unit is configured to generate, for each predetermined diagnostic cycle, a differential curve representing the relationship between the battery's voltage and differential capacity, wherein the differential capacity is obtained by differentiating the battery's capacity relative to the voltage. A peak information acquisition unit is configured to detect a target peak among the peaks of the differential curve. As the battery usage time increases, the differential capacity value of the target peak first decreases and then increases, or the voltage value of the target peak first increases and then decreases. The unit obtains target peak information, including the differential capacity value and the voltage value of the target peak, from each of the multiple differential curves generated while the diagnostic cycle is repeated multiple times. as well as A diagnostic unit is configured to detect a trend switching point based on the target peak information obtained from the plurality of differential curves, at which the trend of change of at least one of the differential capacity value and the voltage value of the target peak changes from an increasing trend to a decreasing trend or from a decreasing trend to an increasing trend over time, and to diagnose the state of the battery by referring to the trend switching point.

11. The apparatus for diagnosing batteries according to claim 10, in, The diagnostic step unit is configured to detect a first trend switching point, at which the trend of change of the differential capacity value changes from a decreasing trend to an increasing trend over time. The state of the battery before the first trend switching point is determined as a first deterioration state, and the state of the battery after the first trend switching point is determined as a second deterioration state.

12. The apparatus for diagnosing batteries according to claim 10, in, The diagnostic unit is configured to detect a second trend switching point, at which the voltage value changes from an increasing trend to a decreasing trend over time. The state of the battery before the second trend switching point is determined to be a third deterioration state, and the state of the battery after the second trend switching point is determined to be a fourth deterioration state.

13. The apparatus for diagnosing a battery according to claim 10, further comprising: A battery management unit configured to reduce the upper voltage limit of the battery when the trend switching point is detected.

14. A battery pack comprising the means for diagnosing the battery according to any one of claims 10 to 13.

15. A vehicle comprising a device for diagnosing a battery according to any one of claims 10 to 13.

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