Battery measurement abnormity judgment module and battery measurement abnormity judgment method thereof

Abstract

The invention provides a battery measurement abnormity judgment module and a battery measurement abnormity judgment method thereof. The module comprises a database, a battery parameter acquisition unit and a battery measurement abnormity judgment unit. The database stores a reference battery parameter data set of the battery module. The battery measurement abnormity judgment unit is used for obtaining a correlation value of the reference battery parameter data set and the current battery parameter data set; obtaining a reference slope of the reference battery parameter data set and a current slope of the current battery parameter data set based on the correlation value being equal to or less than a first preset value; obtaining a slope difference between the reference slope and the current slope; if the slope difference is equal to or smaller than a second preset value, judging whether the current battery parameter data set is abnormal or not; and on the basis that the slope difference is greater than a second preset value, judging that the current battery parameter data set belongs to battery module abnormality.

Description

[0001] Cross - reference to related applications

[0002] This application claims the priority of Taiwan, China Patent Application No. 112148449 filed on December 13, 2023, which is incorporated herein by reference for all purposes as if fully set forth herein. Technical field

[0003] The present invention relates to a battery measurement anomaly determination module and a battery measurement anomaly determination method. Background art

[0004] An electric vehicle is a vehicle that uses electric power to drive a motor to drive the vehicle body forward, and it includes at least a battery module and its measurement module. The measurement module can measure the electrical signal of the battery for the backend to monitor the current status of the battery. However, the anomaly of the electrical signal may indicate an anomaly of the battery module or the measurement module. If the system cannot confirm, it may cause misoperation and pose a risk of overcharging or over - discharging the battery. Therefore, one of the goals of those skilled in the art is to propose a method to determine which type of anomaly the electrical signal anomaly belongs to. Summary of the invention

[0005] An embodiment of the present invention proposes a battery measurement anomaly determination module. The battery measurement anomaly determination module includes a database and a battery measurement anomaly determination unit. The database stores a reference battery parameter data set of the battery module. The battery measurement anomaly determination unit is used to: obtain the correlation value between the reference battery parameter data set and the current battery parameter data set; based on the correlation value being equal to or less than a first preset value, obtain the reference slope of the reference battery parameter data set and the current slope of the current battery parameter data set; obtain the slope difference between the reference slope and the current slope; based on the slope difference being equal to or less than a second preset value, determine whether the current battery parameter data set is a measurement anomaly or no anomaly; and, based on the slope difference being greater than the second preset value, determine that the current battery parameter data set is a battery module anomaly.

[0006] Another embodiment of the present invention proposes a battery measurement anomaly determination method. The battery measurement anomaly determination method includes the following steps: the battery measurement anomaly determination unit obtains the correlation value between the reference battery parameter data set and the current battery parameter data set; based on the correlation value being equal to or less than a first preset value, the battery measurement anomaly determination unit obtains the reference slope of the reference battery parameter data set and the current slope of the current battery parameter data set; the battery measurement anomaly determination unit obtains the slope difference between the reference slope and the current slope; based on the slope difference being equal to or less than a second preset value, the battery measurement anomaly determination unit determines whether the current battery parameter data set is a measurement anomaly or no anomaly; and, based on the slope difference being greater than the second preset value, the battery measurement anomaly determination unit determines that the current battery parameter data set is a battery module anomaly.

[0007] To have a better understanding of the above and other aspects of the present invention, specific embodiments are hereinafter given and described in detail in conjunction with the accompanying drawings as follows. Description of the Drawings

[0008] Figure 1 A functional block diagram of a battery system according to an embodiment of the present invention is shown;

[0009] Figure 2A Shown is Figure 1 A schematic diagram of a reference curve C11 of a certain battery cell in the battery system in the charging mode and abnormal curves (C12 and C13) under "measurement anomaly";

[0010] Figure 2B Shown is Figure 1 A schematic diagram of a reference curve C21 of a certain battery cell in the battery system in the discharging mode and abnormal curves (C22 and C23) under "measurement anomaly";

[0011] Figure 3 Shown is Figure 1 A schematic diagram of a partial reference curve C31 of a certain battery cell in the battery system in the discharging mode and partial abnormal curves (C32 and C33) under "battery module anomaly";

[0012] Figure 4A Shown is Figure 2A A schematic diagram of a reference curve C11 and a currently measured curve C42 (charging mode);

[0013] Figure 4B Shown is Figure 2B A schematic diagram of a reference curve C21 and a currently measured curve C52 (discharging mode);

[0014] Figure 5A Shown is in the charging mode Figure 2A A schematic diagram of the change of charge with voltage of a reference curve C11 and the change of charge with voltage of a currently measured curve C42;

[0015] Figure 5B Shown is in the discharging mode Figure 2B A schematic diagram of the change of charge with voltage of a reference curve C21 and the change of charge with voltage of a currently measured curve C52;

[0016] Figure 6 Shown is Figure 1 A flowchart of a battery measurement anomaly determination method of a battery measurement anomaly determination module;

[0017] Figure 7 Shown is Figure 1 Of the battery measurement anomaly determination module according to Figure 6Flowchart of the first method for the disclosed judgment method to further determine whether the current battery parameter data set D2 belongs to "measurement anomaly" or "no anomaly".

[0018] Figure 8 Illustrate Figure 1 The battery measurement anomaly judgment module according to Figure 6 Flowchart of the second method for the disclosed judgment method to further determine whether the current battery parameter data set D2 belongs to "measurement anomaly" or "no anomaly".

[0019] Among them, reference numerals:[[]]END]]

[0020] 10: Battery system

[0021] 100: Battery measurement anomaly judgment module

[0022] 110: Database

[0023] 120: Battery parameter acquisition unit

[0024] 130: Battery measurement anomaly judgment unit

[0025] 140: Battery charge conversion unit

[0026] 200: Battery module

[0027] 300: Measurement module

[0028] C11, C21, C31: Reference curves

[0029] C12, C13, C22, C23, C32, C33: Anomaly curves

[0030] C42, C52: Currently measured curves

[0031] c1: First preset value

[0032] c2: Second preset value

[0033] c3: Third preset value

[0034] D1: Reference battery parameter data set

[0035] D2: Current battery parameter data set

[0036] k1: Reference maximum curvature

[0037] k2: Current maximum curvature

[0038] Q1: Reference charge value

[0039] Q2: Current charge value

[0040] Q1’ C11 , Q1’C21 : Reference peak

[0041] Q2’ C42 , Q2’ C52 : Current peak

[0042] R1: Related value

[0043] S1: Reference slope

[0044] S2: Current slope

[0045] ΔS: Slope difference

[0046] V1, V κ1 , V C11 , V C21 : Reference voltage value

[0047] V2, V κ2 , V C42 , V C52 : Current voltage value

[0048] V κ1 , V C42 : Reference voltage value

[0049] γ1 S : Reference Spearman correlation coefficient

[0050] γ2 S : Current Spearman correlation coefficient

[0051] ΔV1, ΔV2: Voltage difference. Detailed implementation manners

[0052] Please refer to Figures 1 to 3 , Figure 1 , which shows a functional block diagram of the battery system 10 according to an embodiment of the present invention (taking a single battery cell as an example), Figure 2A shows Figure 1 a schematic diagram of the reference curve C11 of a certain battery cell in the battery system 10 in the charging mode and the abnormal curves (C12 and C13) under "measurement anomaly", Figure 2B shows Figure 1 a schematic diagram of the reference curve C21 of a certain battery cell in the battery system 10 in the discharging mode and the abnormal curves (C22 and C23) under "measurement anomaly", and Figure 3 shows Figure 1 a schematic diagram of the local reference curve C31 of a certain battery cell in the battery system 10 in the discharging mode and the local abnormal curves (C32 and C33) under "battery module anomaly".

[0053] The battery system 10 can be applied to an electric vehicle, but the implementation of this application is not limited thereto. In another embodiment, the battery system 10 can be applied to the battery management system of an energy storage system.

[0054] As Figure 1 shown, the battery system 10 includes a battery measurement abnormality determination module 100, a battery module 200, and a measurement module 300. The battery module 200 includes at least one battery cell (not shown) and can supply current to an external device. The measurement module 300 includes at least one sensor or measurement circuit, which can measure the electrical signals (e.g., voltage and / or current) of each battery cell in the battery module 200. The battery measurement abnormality determination module 100 can obtain the electrical signals (e.g., voltage and / or current) of the battery module 200 and determine whether an abnormality has occurred in the battery system 10 based on the electrical signals, and further determine whether the abnormality is an abnormality of the battery module 200 itself (hereinafter referred to as "battery module abnormality") or a hardware abnormality of the measurement module 300 (hereinafter referred to as "measurement abnormality"). The "battery module abnormality" is, for example, an abnormality of the battery cell itself.

[0055] Generally, a battery management system (BMS) does not have an abnormality detection function. In this embodiment, the battery measurement abnormality determination module 100 can be applied to the battery management system, so that the battery management system using the battery measurement abnormality determination module 100 has an abnormality detection function; alternatively, the battery measurement abnormality determination module 100 and the measurement module 300 can be applied to the battery management system; or, the battery measurement abnormality determination module 100 can be separately configured from the battery management system but electrically connected to each other.

[0056] As Figure 1 shown, the battery measurement abnormality determination module 100 includes a database 110, a battery parameter acquisition unit 120, a battery measurement abnormality determination unit 130, and a power conversion unit 140. The database 110 can be stored in a storage device (e.g., a memory or a storage disk). At least two of the battery parameter acquisition unit 120, the battery measurement abnormality determination unit 130, and the power conversion unit 140 can be integrated into a single unit. In one embodiment, at least one of the battery parameter acquisition unit 120, the battery measurement abnormality determination unit 130, and the power conversion unit 140 can be integrated into a controller or a processor. In addition, at least one of the battery parameter acquisition unit 120, the battery measurement abnormality determination unit 130, and the power conversion unit 140 can adopt a physical circuit formed by at least a semiconductor process, such as a semiconductor chip or a semiconductor package.

[0057] In another embodiment, the battery measurement anomaly determination module 100 may omit the battery parameter acquisition unit 120. The battery parameter acquisition unit 120 and the battery measurement anomaly determination module 100 may be components of the same level in the battery system 10, and the battery parameter acquisition unit 120 is electrically connected to the measurement module 300 and the battery measurement anomaly determination module 100.

[0058] As Figure 1 shown, the database 110 stores a reference battery parameter data group D1 of the battery module 200. The battery parameter acquisition unit 120 is used to acquire a current battery parameter data group D2 of the battery module 200. The battery measurement anomaly determination unit 130 is used to: obtain a correlation value R1 between the reference battery parameter data group D1 and the current battery parameter data group D2; based on the correlation value R1 being equal to or less than a first preset value c1, obtain a reference slope S1 of the reference battery parameter data group D1 and a current slope S2 of the current battery parameter data group D2 in the same power range; obtain a slope difference ΔS between the reference slope S1 and the current slope S2; based on the slope difference ΔS being equal to or less than a second preset value, determine whether the current battery parameter data group D2 belongs to "measurement anomaly" or "no anomaly"; and, based on the slope difference ΔS being greater than a second preset value c2, determine that the current battery parameter data group D2 belongs to "battery module anomaly". In this way, the battery measurement anomaly determination module 100 of the embodiment of the present application can determine whether the current battery parameter data group D2 belongs to "measurement anomaly" or "battery module anomaly".

[0059] The reference battery parameter data group D1 may include two types of data. One is charging mode data, which can be represented as Figure 2A a reference curve C11, and the other is discharging mode data, which can be represented as Figure 2B a reference curve C21. The battery measurement anomaly determination module 100 can detect the mode (charging mode or discharging mode) of the battery module 200 and select corresponding data (charging mode data or discharging mode data) according to the detected mode.

[0060] As Figure 2A shown, the reference curve C11 represents the correspondence between the power value (for example, the capacitance of a certain battery cell in the battery module 200) and the voltage value in the charging mode data of the reference battery parameter data group D1. The abnormal curves C12 and C13 represent the correspondence between the power value and the voltage value of the battery system under "measurement anomaly". The unit of the power value is, for example, ampere-hour (Ah), and the unit of the voltage value is, for example, volt (Volt, V). Comparing these curves, it can be seen that in "measurement anomaly", as shown in area A1 (meaning the same power range), the slopes of the reference curve C11 and the abnormal curves (C12 and C13) are almost the same, and the difference between the two is only the deviation of the voltage value. Similarly, as Figure 2BAs shown, the reference curve C21 represents the correspondence between the power values (e.g., the capacitance of a certain battery cell in the battery module 200) and the voltage values of the discharge mode data in the reference battery parameter data set D1, and the abnormal curves C22 and C23 represent the correspondence between the power values and the voltage values of the battery system under "measurement anomaly". By comparing these curves, it can be seen that in "measurement anomaly", the slopes of the reference curve C21 and the abnormal curves (C22 and C23) are almost the same, and the only difference between the two is the difference in the voltage values at the same power. As Figure 3 shown, the reference curve C31 represents the correspondence between the power values (e.g., the capacitance of a certain battery cell in the battery module 200) and the voltage values of the discharge mode data in the reference battery parameter data set D1, and the abnormal curves C32 and C33 represent the correspondence between the power values and the voltage values of the battery system under "battery module anomaly". By comparing these curves, it can be seen that in "battery module anomaly", there is no linear relationship between the reference curve C31 and the abnormal curves (C32 and C33).

[0061] As Figure 1 shown, the reference battery parameter data set D1 is, for example, the electrical signal of a normal battery module. The reference battery parameter data set D1 includes several corresponding reference voltage values V1 and several reference power values Q1. The reference battery parameter data set D1 can be obtained in advance through methods such as battery original factory information or real battery model simulation, and stored in the database 110.

[0062] Please refer to Figure 4A , which shows Figure 2A a schematic diagram (charging mode) of the reference curve C11 and the currently measured curve C42 (currently measured). Figure 4A For the reference curve C11, the power value on the horizontal axis coordinate (e.g., the capacitance of a certain battery cell in the battery module 200) and the voltage value on the vertical axis coordinate are respectively the reference power value Q1 and the reference voltage value V1, while Figure 4A for the currently measured curve C42, the power value on the horizontal axis coordinate and the voltage value on the vertical axis coordinate are respectively the current power value Q2 and the current voltage value V2. The currently measured curve C42 is generated based on the current battery parameter data set D2.

[0063] The current battery parameter data set D2 is, for example, obtained by the measurement module 300 from the battery module 200, and the battery parameter acquisition unit 120 then obtains the current battery parameter data set D2 through the measurement module 300. In addition, the current battery parameter data set D2 includes several current voltage values V2 and several current current values I2. The power conversion unit 140 can convert each current current value I2 into the corresponding current power value Q2 (i.e., Figure 4A(horizontal axis coordinate). For example, the power conversion unit 140 may integrate the current current value I2 with respect to time to obtain the current power value Q2. The foregoing current slope S2 is obtained based on the current voltage value V2 and the current power value Q2 (to be described later).

[0064] In one embodiment, the function and / or circuit of the power conversion unit 140 may be integrated into the battery measurement anomaly determination unit 130. Thus, the battery measurement anomaly determination unit 130 may integrate the current current value I2 with respect to time to obtain the current power value Q2. In another embodiment, the function and / or circuit of the power conversion unit 140 may be integrated into the battery parameter acquisition unit 120. Thus, the battery parameter acquisition unit 120 may integrate the current current value I2 with respect to time to obtain the current power value Q2.

[0065] In the charging mode, the battery measurement anomaly determination unit 130 is further configured to: obtain the reference Spearman correlation coefficient γ1 of these reference voltage values V1 and these reference power values Q1 S ; obtain the current Spearman correlation coefficient γ2 of these current voltage values V2 and these current power values Q2 S ; obtain the reference Spearman correlation coefficient γ1 S and the current Spearman correlation coefficient γ2 S ; and use the difference as the foregoing correlation value R1.

[0066] Further, for example, in the charging mode, the battery measurement anomaly determination unit 130 is further configured to: obtain the reference Spearman correlation coefficient γ1 according to the following formula (1a) S =ρ R (Q1)R(V1); obtain the current Spearman correlation coefficient γ2 according to the following formula (1b) S =ρ R (Q2)R(V2); and obtain the correlation value R1 according to the following formula (1c), where the correlation value R1 is, for example, the difference or the absolute value of the difference between the reference Spearman correlation coefficient γ1 S and the obtained current Spearman correlation coefficient γ2 S . σ R (Q1) and σ R (V1) are the standard deviations of the ranked variables, and cov(R(Q1),R(V1)) is the covariance of the ranked variables. Similarly, σ R (Q2) and σ R (V2) are the standard deviations of the ranked variables; cov(R(Q2),R(V2)) is the covariance of the ranked variables.

[0067]

[0068]

[0069] R1 = |γ1 S - γ2 S |…(1c)

[0070] In the charging mode, the Spearman correlation coefficient ranges from -1 to 1. For the reference voltage value V1 and the reference power value Q1, when the reference Spearman correlation coefficient γ1 S is greater than 0, it indicates that the reference voltage value V1 and the reference power value Q1 are positively correlated; when the reference Spearman correlation coefficient γ1 S is less than 0, it indicates that the reference voltage value V1 and the reference power value Q1 are negatively correlated; when the reference Spearman correlation coefficient γ1 S is equal to 0, it indicates that there is no correlation between the reference voltage value V1 and the reference power value Q1. The current Spearman correlation coefficient γ2 S has the same or similar characteristics as the reference Spearman correlation coefficient γ1 S and will not be elaborated here. When the correlation value R1 is equal to or less than the first preset value c1, the battery measurement abnormality determination unit 130 proceeds with the abnormality type determination. When the correlation value R1 is greater than the first preset value c1, it indicates that the current battery parameter data set D2 is a non-normal charge and discharge curve situation, which does not belong to the abnormality of this application, and the battery measurement abnormality determination unit 130 does not perform the abnormality type determination. In one embodiment, the first preset value c1 can be set according to requirements. The smaller the number, the stricter the correlation coefficient setting. For example, according to the "three-sigma rule", the first preset value c1 can be less than 0.003.

[0071] In the charging mode, the battery measurement abnormality determination unit 130 is further configured to: obtain a reference slope S1 according to the following formula (2a); obtain a current slope S2 according to the following formula (2b); and obtain a slope difference ΔS according to the following formula (2c). Wherein, ΔQ represents a power range, the reference slope S1 and the current slope S2 are obtained based on the same power range, ΔV1 represents the difference between two adjacent reference voltage values V1, and ΔV2 represents the difference between two adjacent current voltage values V2.

[0072]

[0073]

[0074]

[0075] In the charging mode, when the slope difference ΔS is greater than the second preset value c2, it indicates that the current battery parameter data set D2 belongs to "battery module anomaly". The second preset value c2 can be set according to requirements. The smaller the number, the stricter the correlation coefficient setting. For example, according to the "three-sigma rule", the second preset value c2 can be less than 0.003. When the slope difference ΔS is equal to or less than the second preset value c2, it indicates that the current battery parameter data set D2 may belong to "measurement anomaly" or "no anomaly". In other words, just by the judgment method that the slope difference ΔS is equal to or less than the second preset value c2, it is still impossible to completely determine that the current battery parameter data set D2 belongs to "measurement anomaly". However, through the method described below, it is possible to further determine whether the current battery parameter data set D2 belongs to "measurement anomaly" or "no anomaly".

[0076] In the charging mode, the battery measurement anomaly determination unit 130 is further configured to: obtain the reference voltage value V corresponding to the reference maximum curvature k1 of the charging mode data in the reference battery parameter data set D1 κ1 ; obtain the current voltage value V corresponding to the current maximum curvature k2 of the current battery parameter data set D2 κ2 ; obtain the reference voltage value V κ1 and the current voltage value V κ2 of the voltage difference ΔV1; and, based on the voltage difference ΔV1 being equal to or greater than the third preset value c3, determine that the current battery parameter data set D2 belongs to "measurement anomaly". In addition, based on the voltage difference ΔV1 being less than the third preset value c3, it indicates that the current battery parameter data set D2 has little difference from the reference battery parameter data set D1, and the current battery parameter data set D2 can be determined to belong to "no anomaly". In one embodiment, the third preset value c3 is greater than 0, for example, it is 0.2, or even larger or smaller.

[0077] In the charging mode, the reference maximum curvature k1, the current maximum curvature k2, and the voltage difference ΔV1 are respectively obtained by the following formulas (3a) to (3c). In the formulas, Q1′(t) is the first derivative of the reference power value Q1 with respect to time, Q1”(t) is the second derivative of the reference power value Q1 with respect to time, V1′(t) is the first derivative of the reference voltage value V1 with respect to time, and V1”(t) is the second derivative of the reference voltage value V1 with respect to time, Q2′(t) is the first derivative of the current power value Q2 with respect to time, Q2”(t) is the second derivative of the current power value Q2 with respect to time, V2′(t) is the first derivative of the current voltage value V2 with respect to time, and V2”(t) is the second derivative of the current voltage value V2 with respect to time.

[0078]

[0079]

[0080] ΔV1 = |V κ1-V κ2 |…(3c)

[0081] As Figure 4A shown, in the charging mode, the reference maximum curvature k1 occurs at the first characteristic point A C11 or the second characteristic point B C11 of the reference curve C11, while the current maximum curvature k2 occurs at the first characteristic point A C42 or the second characteristic point B C42 of the currently measured curve C42. The "characteristic point" here is, for example, the maximum curvature point of the curve. Taking the reference maximum curvature k1 occurring at the first characteristic point A C11 of the reference curve C11 and the current maximum curvature k2 occurring at the first characteristic point A C42 of the currently measured curve C42 as an example, the reference voltage value V κ1 is the voltage value corresponding to the vertical axis at the first characteristic point A C11 , and the current voltage value V κ2 is the voltage value corresponding to the vertical axis at the first characteristic point A C42 .

[0082] In addition, in the charging mode, based on the slope difference ΔS being equal to or less than the second preset value c2, the current battery parameter data set D2 may belong to "measurement anomaly" or "no anomaly", that is, when the slope difference ΔS is equal to or less than the second preset value c2, it cannot be completely determined that the current battery parameter data set D2 belongs to "measurement anomaly". However, based on "the slope difference ΔS is equal to or less than the second preset value c2" and "the voltage difference ΔV1 is equal to or greater than the third preset value c3", the credibility that the current battery parameter data set D2 belongs to "measurement anomaly" is increased. In other words, on the premise of "the slope difference ΔS is equal to or less than the second preset value c2", combined with the judgment method of "the voltage difference ΔV1 is equal to or greater than the third preset value c3", the judgment result that "the current battery parameter data set D2 belongs to measurement anomaly" can be confirmed to be true.

[0083] Please refer to Figure 4B , which shows Figure 2B a schematic diagram (discharge mode) of the reference curve C21 and the currently (currently measured) measured curve C52. Figure 4B For the reference curve C21, the power value (e.g., the capacitance of a certain battery cell in the battery module 200) of the horizontal axis coordinate and the voltage value of the vertical axis coordinate are respectively the reference power value Q1 and the reference voltage value V1, while Figure 4B for the currently measured curve C52, the power value of the horizontal axis coordinate and the voltage value of the vertical axis coordinate are respectively the current power value Q2 and the current voltage value V2. Figure 4B The judgment method in the shown discharge mode is similar to or the same as the judgment method in the aforementioned Figure 4A shown charging mode.

[0084] For example, in the discharge mode, the battery measurement anomaly determination unit 130 may obtain the reference Spearman correlation coefficient γ1 in the same manner (e.g., the above formulas (1a) to (1c)). S , the current Spearman correlation coefficient γ2 S and the difference Δγ. The battery measurement anomaly determination unit 130 also obtains the reference slope S1, the current slope S2, and the slope difference ΔS in the same manner (e.g., the above formulas (2a) to (2c)). When the slope difference ΔS is greater than the second preset value c2, it indicates that the current battery parameter data set D2 belongs to "battery module anomaly". When the slope difference ΔS is equal to or less than the second preset value c2, it indicates that the probability that the current battery parameter data set D2 belongs to "measurement anomaly" is high, but it may also belong to "no anomaly". In other words, through the determination method where the slope difference ΔS is equal to or less than the second preset value c2, it is not possible to completely determine that the current battery parameter data set D2 belongs to "measurement anomaly". Through the method described below, it is possible to further determine whether the current battery parameter data set D2 belongs to "measurement anomaly" or "no anomaly".

[0085] As Figure 4B shown, the battery measurement anomaly determination unit 130 is further configured to: obtain the reference voltage value V corresponding to the reference maximum curvature k1 of the discharge mode data in the reference battery parameter data set D1 κ1 ; obtain the current voltage value V corresponding to the current maximum curvature k2 of the current battery parameter data set D2 κ2 ; obtain the reference voltage value V κ1 and the current voltage value V κ2 of the voltage difference ΔV1; and, based on the voltage difference ΔV1 being equal to or greater than the third preset value c3, determine that the current battery parameter data set D2 belongs to "measurement anomaly". In addition, based on the voltage difference ΔV1 being less than the third preset value c3, it indicates that the difference between the current battery parameter data set D2 and the reference battery parameter data set D1 is small, and the current battery parameter data set D2 can be determined to belong to "no anomaly". In addition, in the discharge mode, the reference maximum curvature k1, the current maximum curvature k2, and the voltage difference ΔV1 are obtained by the above formulas (3a) to (3c) respectively.

[0086] As Figure 4B shown, in the discharge mode, the reference maximum curvature k1 occurs at the first characteristic point A C21 or the second characteristic point B C21 of the reference curve C21, and the current maximum curvature k2 occurs at the first characteristic point A C52 or the second characteristic point B C52 of the currently measured curve C52. The "characteristic point" here is, for example, the maximum curvature point of the curve. Taking the reference maximum curvature k1 occurring at the first characteristic point A of the reference curve C21 C21And the current maximum curvature k2 occurs at the first feature point A of the currently measured curve C52 C52 For example, the reference voltage value V κ1 is the voltage value corresponding to the first feature point A C21 on the vertical axis, and the current voltage value V κ2 is the voltage value corresponding to the first feature point A C52 on the vertical axis.

[0087] In addition, in the discharge mode, based on the slope difference ΔS being equal to or less than the second preset value c2, the current battery parameter data set D2 belongs to "measurement anomaly" or "no anomaly". That is, when the slope difference ΔS is equal to or less than the second preset value c2, it cannot be fully determined that the current battery parameter data set D2 belongs to "measurement anomaly". However, based on "the slope difference ΔS is equal to or less than the second preset value c2" and "the voltage difference ΔV1 is equal to or greater than the third preset value c3", the credibility that the current battery parameter data set D2 belongs to "measurement anomaly" is increased. In other words, on the premise of "the slope difference ΔS is equal to or less than the second preset value c2", combined with the judgment method of "the voltage difference ΔV1 is equal to or greater than the third preset value c3", it can be confirmed that the judgment result of "the current battery parameter data set D2 belongs to measurement anomaly" is true.

[0088] The following introduces another judgment method for determining whether the current battery parameter data set D2 belongs to "measurement anomaly" or "no anomaly".

[0089] Please refer to Figure 5A , which shows the schematic diagram of the change of the reference curve C11's charge with respect to voltage and the change of the currently measured curve C42's charge with respect to voltage in the charging mode Figure 4A . Figure 5A The horizontal axis coordinate of

[0090] is the voltage value (for example, the voltage value of a certain battery cell in the battery module 200), and the vertical axis coordinate is the change of the charge value with respect to the voltage value, such as the charge differential with respect to voltage. C11 ; Obtain the reference peak Q1' of the reference charge with respect to voltage change C42 ; Obtain the current peak Q2' of the current charge with respect to voltage change C11 ; Obtain the reference voltage value V C11 corresponding to the reference peak Q1' C42 and the current voltage value V C42The voltage difference ΔV2; and, based on the voltage difference ΔV2 being equal to or greater than a third preset value c3, it is determined that the current battery parameter data set D2 belongs to "measurement anomaly". The aforementioned reference power with respect to voltage change is, for example, the first derivative of the reference power value Q1 with respect to the voltage value (i.e., ΔQ1 / ΔV1), and the current power with respect to voltage change is, for example, the first derivative of the current power value Q2 with respect to the voltage value (i.e., ΔQ2 / ΔV2).

[0091] In addition, the battery measurement anomaly determination unit 130 can obtain the reference peak Q1' using the following formulas (4a) to (4c) C11 and the current peak Q2' C42 and the voltage difference ΔV2.

[0092]

[0093]

[0094] ΔV2 = |V C11 - V C42 |...(4c)

[0095] In addition, in the charging mode, based on the slope difference ΔS being equal to or less than a second preset value c2, the current battery parameter data set D2 may belong to "measurement anomaly" or "no anomaly", that is, when the slope difference ΔS is equal to or less than the second preset value c2, it cannot be completely determined that the current battery parameter data set D2 belongs to "measurement anomaly". However, based on "the slope difference ΔS is equal to or less than the second preset value c2" and "the voltage difference ΔV2 is equal to or greater than the third preset value c3", the credibility that the current battery parameter data set D2 belongs to "measurement anomaly" is increased. In other words, on the premise of "the slope difference ΔS is equal to or less than the second preset value c2", combined with the judgment method of "the voltage difference ΔV2 is equal to or greater than the third preset value c3", it can be confirmed that the judgment result of "the current battery parameter data set D2 belongs to measurement anomaly" is true.

[0096] Please refer to Figure 5B , which shows the schematic diagram of the power with respect to voltage change of the reference curve C21 and the power with respect to voltage change of the currently measured curve C52 in the discharge mode Figure 4B . Figure 5B The horizontal axis coordinate of is the voltage value (for example, the voltage value of a certain battery cell in the battery module 200), and the vertical axis coordinate is the change of the power value with respect to the voltage value. Figure 5B The judgment method of the shown discharge mode is similar to or the same as the aforementioned Figure 5A shown judgment method of the charging mode.

[0097] For example, in the discharge mode, the battery measurement anomaly determination unit 130 is also used to: obtain the reference peak Q1' of the reference power with respect to voltage change C21; Obtain the current peak value Q2' of the voltage change corresponding to the current battery charge C52 ; Obtain the reference peak value Q1' C21 The corresponding reference voltage value V C21 And the current peak value Q2' C52 The corresponding current voltage value V C52 The voltage difference ΔV2; and, based on the voltage difference ΔV2 being equal to or greater than the third preset value c3, determine that the current battery parameter data set D2 belongs to "measurement anomaly". In addition, the battery measurement anomaly determination unit 130 can obtain the reference peak value Q1' according to the above formulas (4a) to (4c) C21 The reference peak value Q1' C52 The current peak value Q2' C21 And the voltage difference ΔV2 (i.e., ΔV2 = |V C52 |).

[0098] In addition, in the discharge mode, based on the slope difference ΔS being equal to or less than the second preset value c2, the current battery parameter data set D2 may belong to "measurement anomaly" or "no anomaly", that is, when the slope difference ΔS is equal to or less than the second preset value c2, it cannot be completely determined that the current battery parameter data set D2 belongs to "measurement anomaly". However, based on "the slope difference ΔS is equal to or less than the second preset value c2" and "the voltage difference ΔV2 is equal to or greater than the third preset value c3", the credibility that the current battery parameter data set D2 belongs to "measurement anomaly" is increased. In other words, on the premise of "the slope difference ΔS is equal to or less than the second preset value c2", combined with the determination method of "the voltage difference ΔV2 is equal to or greater than the third preset value c3", it can be confirmed that the determination result of "the current battery parameter data set D2 belongs to measurement anomaly" is true.

[0099] Please refer to Figure 6 Which shows Figure 1 The flowchart of the battery measurement anomaly determination method of the battery measurement anomaly determination module 100.

[0100] In step S110, the battery parameter acquisition unit 120 acquires the current battery parameter data set D2 of the battery module 200. In one embodiment, the current battery parameter data set D2 includes, for example, several current voltage values V2 and several current current values I2.

[0101] In step S120, the charge conversion unit 140 can convert each current current value I2 into the corresponding current charge value Q2 (i.e., Figure 4A The abscissa of). For example, the charge conversion unit 140 can integrate the current current value I2 with respect to time to obtain the current charge value Q2.

[0102] In step S130, the battery measurement anomaly determination unit 130 obtains a correlation value R1 between the reference battery parameter data set D1 and the current battery parameter data set D2. For example, the battery measurement anomaly determination unit 130 can use the previous formulas (1a) to (1c) to obtain the reference Spearman correlation coefficient γ1 of these reference voltage values V1 and these reference power values Q1 S and the current Spearman correlation coefficient γ2 of these current voltage values V2 and these current power values Q2 S and obtain the reference Spearman correlation coefficient γ1 S and the difference between the current Spearman correlation coefficient γ2 S and use the difference as the correlation value R1.

[0103] In step S140, the battery measurement anomaly determination unit 130 determines whether the correlation value R1 is equal to or less than a first preset value c1. If so, the process proceeds to step S150; if not, the current battery parameter data set D2 may be a case of an abnormal charge and discharge curve, which is not an anomaly in this application. The battery measurement anomaly determination unit 130 does not perform an anomaly type determination, so the process returns to step S110 to continue monitoring the current battery parameter data set D2 at the next time point.

[0104] In step S150, the battery measurement anomaly determination unit 130 obtains the reference slope S1 of the reference battery parameter data set D1 and the current slope S2 of the current battery parameter data set D2. For example, the battery measurement anomaly determination unit 130 can use the previous formulas (2a) to (2b) to obtain the reference slope S1 and the current slope S2.

[0105] In step S160, the battery measurement anomaly determination unit 130 obtains the slope difference ΔS between the reference slope S1 and the current slope S2. For example, the battery measurement anomaly determination unit 130 can use the previous formula (2c) to obtain the slope difference ΔS.

[0106] In step S170, the battery measurement anomaly determination unit 130 determines whether the slope difference ΔS is equal to or less than a second preset value c2. If so, the process proceeds to step S180; if not, the process proceeds to step S190.

[0107] In step S180, the battery measurement anomaly determination unit 130 determines whether the current battery parameter data set D2 belongs to "measurement anomaly" or "no anomaly".

[0108] In step S190, the battery measurement anomaly determination unit 130 determines that the current battery parameter data set D2 belongs to "battery module anomaly", and can optionally output a warning signal indicating "battery module anomaly", such as an optical signal, an acoustic signal, an image signal, and / or a vibration signal, etc.

[0109] The judgment result of step S180 can only indicate that the current battery parameter data set D2 may belong to "measurement anomaly" or may also belong to "no anomaly". The following further introduces several methods for determining whether the current battery parameter data set D2 belongs to "measurement anomaly" or "no anomaly".

[0110] Please refer to Figure 7 , which shows Figure 1 of the battery measurement anomaly judgment module 100 according to Figure 6 the disclosed judgment method to further judge the flowchart of the first method for determining whether the current battery parameter data set D2 belongs to "measurement anomaly" or "no anomaly". The same process can be used to judge whether the current battery parameter data set D2 belongs to "measurement anomaly" or "no anomaly" in both the charging mode and the discharging mode.

[0111] Continuing from step S180, in step S210, the battery measurement anomaly judgment unit 130 can use the aforementioned method to obtain the reference voltage value V corresponding to the reference maximum curvature k1 of the reference battery parameter data set D1 κ1 .

[0112] In step S220, the battery measurement anomaly judgment unit 130 can use the aforementioned method to obtain the current voltage value V corresponding to the current maximum curvature k2 of the current battery parameter data set D2 κ2 .

[0113] In step S230, the battery measurement anomaly judgment unit 130 can use the aforementioned method to obtain the voltage difference ΔV1 between the reference voltage value V κ1 and the current voltage value V κ2 .

[0114] In step S240, the battery measurement anomaly judgment unit 130 judges whether the voltage difference ΔV1 is equal to or greater than the third preset value c3. If so, the process proceeds to step S250; if not, the process proceeds to step S260.

[0115] In step S250, the battery measurement anomaly judgment unit 130 judges that the current battery parameter data set D2 belongs to "measurement anomaly", and can selectively output a warning signal indicating "measurement anomaly", such as a light signal, a sound signal, a video signal, and / or a vibration signal, etc.

[0116] In step S260, the battery measurement anomaly judgment unit 130 judges that the current battery parameter data set D2 belongs to "no anomaly".

[0117] Please refer to Figure 8 , which shows Figure 1 of the battery measurement anomaly judgment module 100 according to Figure 6Flowchart of the second method for further determining whether the current battery parameter data set D2 belongs to "measurement anomaly" or "no anomaly" in the disclosed determination method. The following takes the charging mode as an example for illustration. The same process can be adopted for the discharging mode, which will not be elaborated here.

[0118] Continuing from step S180, in step S310, the battery measurement anomaly determination unit 130 can use the aforementioned method to obtain the reference peak value Q1' of the reference battery power with respect to the voltage change of these reference battery powers Q1. C11 。

[0119] In step S320, the battery measurement anomaly determination unit 130 can use the aforementioned method to obtain the current peak value Q2' of the current battery power with respect to the voltage change of these current battery powers Q2. C42 。

[0120] In step S330, the battery measurement anomaly determination unit 130 can use the aforementioned method to obtain the reference voltage value V corresponding to the reference peak value Q1'. C11 corresponding to the reference voltage value V C11 and the current peak value Q2' C42 corresponding to the current voltage value V C42 of the voltage difference ΔV2.

[0121] In step S340, the battery measurement anomaly determination unit 130 determines whether the voltage difference ΔV2 is equal to or greater than the third preset value c3. If so, the process proceeds to step S350; if not, the process proceeds to step S360.

[0122] In step S350, the battery measurement anomaly determination unit 130 determines that the current battery parameter data set D2 belongs to "measurement anomaly", and can selectively output a warning signal indicating "measurement anomaly", such as a light signal, a sound signal, a video signal, and / or a vibration signal, etc.

[0123] In step S360, the battery measurement anomaly determination unit 130 determines that the current battery parameter data set D2 belongs to "no anomaly".

[0124] In summary, the embodiment of the present application proposes a battery measurement anomaly determination module and a battery measurement anomaly determination method thereof, which compare the correlation between the current battery parameter data set and the reference battery parameter data set. When the correlation is equal to or less than the first preset value, the battery measurement anomaly determination module determines whether the current battery parameter data set belongs to "measurement anomaly", "no anomaly", or "battery module anomaly" based on the slopes of the current battery parameter data set and the reference battery parameter data set. When the current battery parameter data set is determined to possibly belong to "measurement anomaly" or "no anomaly", the battery measurement anomaly determination module further determines whether the determination result that the current battery parameter data set belongs to "measurement anomaly" is true based on the characteristic points of the current battery parameter data set (for example, the maximum curvature point or the peak value of the change in battery power with respect to voltage) and the characteristic points of the reference battery parameter data set (for example, the maximum curvature point or the peak value of the change in battery power with respect to voltage).

[0125] In summary, although the present application has been disclosed above in embodiments, it is not intended to limit the present application. Those of ordinary skill in the technical field to which the present application pertains can make various modifications and refinements without departing from the spirit and scope of the present application. Therefore, the protection scope of the present application shall be defined by the scope of the patent application.

Claims

1. A battery measurement anomaly judgment module, characterized in that, it includes: a database storing a reference battery parameter data group of the battery module; and a battery measurement anomaly judgment unit for: obtaining the correlation values of the reference battery parameter data group and the current battery parameter data group; based on the correlation value being equal to or less than a first preset value, obtaining the reference slope of the reference battery parameter data group and the current slope of the current battery parameter data group; obtaining the slope difference between the reference slope and the current slope; based on the slope difference being equal to or less than a second preset value, judging whether the current battery parameter data group is abnormally measured or not; and based on the slope difference being greater than the second preset value, judging that the current battery parameter data group is an anomaly of the battery module.

2. The battery measurement anomaly judgment module according to claim 1, characterized in that, it further in cludes: a battery parameter acquisition unit for acquiring the current battery parameter data group of the battery module.

3. The battery measurement anomaly judgment module according to claim 1, characterized in that, the current battery parameter data group includes a current voltage value and a current current value; the battery measurement anomaly judgment module further includes: a power conversion unit for converting the current current value into a corresponding current power value; wherein, the battery measurement anomaly judgment unit is further used for: based on the correlation value being less than the first preset value, obtaining the current slope of the current voltage value and the current power value.

4. The battery measurement anomaly judgment module according to claim 3, characterized in that, the reference battery parameter data group includes a reference voltage value and a reference power value; the battery measurement anomaly judgment unit is further used for: obtaining the reference Spearman correlation coefficient of the reference voltage value and the reference power value; obtaining the current Spearman correlation coefficient of the current voltage value and the current power value; obtaining the difference between the reference Spearman correlation coefficient and the current Spearman correlation coefficient; and using the difference as the correlation value.

5. The battery measurement anomaly judgment module according to claim 4, characterized in that, the battery measurement anomaly judgment unit is further used for: Obtain the reference Spearman correlation coefficient γ1 according to the following formula (1a). S ; Obtain the current Spearman correlation coefficient γ2 according to the following formula (1b) S ; and obtaining the correlation value R1 according to the following formula (1c); R1 = |γ1 S - γ2 S |…(1).

6. The battery measurement anomaly judgment module according to claim 3, characterized in that, the reference battery parameter data group includes a reference voltage value V1 and a reference power value Q1, and the battery measurement anomaly judgment unit is further used for: obtaining the reference slope S1 according to the following formula (2a); obtaining the current slope S2 according to the following formula (2b); and obtaining the slope difference ΔS according to the following formula (2c); wherein, V2 represents the current voltage value, Q2 represents the current power value, ΔQ represents the power interval, ΔV1 represents the difference between two adjacent reference voltage values V1, and ΔV2 represents the difference between two adjacent current voltage values V2.

7. The battery measurement anomaly judgment module according to claim 1, characterized in that, the reference battery parameter data group includes a reference voltage value and a reference power value, and the current battery parameter data group includes a current voltage value and a current power value; the battery measurement anomaly judgment unit is further used for: obtaining the reference voltage value corresponding to the reference maximum curvature of the reference battery parameter data group; Obtain the current voltage value corresponding to the current maximum curvature of the current battery parameter data set; Obtain the voltage difference between the reference voltage value and the current voltage value; And Based on the voltage difference being equal to or greater than a third preset value, determine that the current battery parameter data set belongs to the measurement anomaly.

8. The battery measurement anomaly determination module according to claim 1, Characterized in that The reference battery parameter data set includes a reference power value, and the current battery parameter data set includes a current power value; the battery measurement anomaly determination unit is further configured to: Obtain the reference peak value of the reference power value with respect to voltage change; Obtain the current peak value of the current power value with respect to voltage change; Obtain the voltage difference between the reference voltage value corresponding to the reference peak value and the current voltage value corresponding to the current peak value; And Based on the voltage difference being equal to or greater than a third preset value, determine that the current battery parameter data set belongs to the measurement anomaly.

9. A battery measurement anomaly determination method, Characterized in that Includes: The battery measurement anomaly determination unit obtains the correlation value between the reference battery parameter data set and the current battery parameter data set; Based on the correlation value being less than a first preset value, the battery measurement anomaly determination unit obtains the reference slope of the reference battery parameter data set and the current slope of the current battery parameter data set; The battery measurement anomaly determination unit obtains the slope difference between the reference slope and the current slope; Based on the slope difference being equal to or less than a second preset value, the battery measurement anomaly determination unit determines whether the current battery parameter data set is a measurement anomaly or not; And Based on the slope difference being greater than the second preset value, the battery measurement anomaly determination unit determines that the current battery parameter data set is a battery module anomaly.

10. The battery measurement anomaly determination method according to claim 9, Characterized in that Further includes: The battery parameter acquisition unit acquires the current battery parameter data set of the battery module.

11. The battery measurement anomaly determination method according to claim 9, Characterized in that The current battery parameter data set includes a current voltage value and a current current value; The battery measurement anomaly determination method further includes: The power conversion unit converts the current current value into a corresponding current power value; Based on the correlation value being less than the first preset value, the battery measurement anomaly determination unit obtains the current slope of the current voltage value and the current power value.

12. The battery measurement anomaly determination method according to claim 11, Characterized in that The reference battery parameter data set includes a reference voltage value and a reference power value; the battery measurement anomaly determination method further includes: Obtain the reference Spearman correlation coefficient of the reference voltage value and the reference power value; Obtain the current Spearman correlation coefficient of the current voltage value and the current power value; Obtain the difference between the reference Spearman correlation coefficient and the current Spearman correlation coefficient; and use the difference as the correlation value.

13. The battery measurement anomaly determination method according to claim 11, Characterized in that Further includes: The battery measurement abnormality determination unit obtains the reference Spearman correlation coefficient γ1 according to the following formula (1a). S ; The battery measurement abnormality determination unit obtains the current Spearman correlation coefficient γ2 according to the following formula (1b). S ; and The battery measurement anomaly determination unit obtains the correlation value R1 according to the following formula (1c); Wherein, R1 = |γ1 S - γ2 S |…(1).

14. The battery measurement anomaly determination method according to claim 11, Characterized in that The reference battery parameter data set includes a reference voltage value V1 and a reference charge value Q1, and the battery measurement anomaly determination method further includes: The battery measurement anomaly determination unit obtains the reference slope S1 according to the following formula (2a); The battery measurement anomaly determination unit obtains the current slope S2 according to the following formula (2b); and The battery measurement anomaly determination unit obtains the slope difference ΔS according to the following formula (2c); wherein, wherein, V2 represents the current voltage value, Q2 represents the current charge value, ΔQ represents the charge interval, ΔV1 represents the difference between two adjacent reference voltage values V1, and ΔV2 represents the difference between two adjacent current voltage values V2.

15. The battery measurement anomaly determination method according to claim 9, characterized in that the reference battery parameter data set includes a reference voltage value and a reference charge value, and the current battery parameter data set includes a current voltage value and a current charge value; the battery measurement anomaly determination method further includes: The battery measurement anomaly determination unit obtains the reference voltage value corresponding to the reference maximum curvature of the reference battery parameter data set; The battery measurement anomaly determination unit obtains the current voltage value corresponding to the current maximum curvature of the current battery parameter data set; The battery measurement anomaly determination unit obtains the voltage difference between the reference voltage value and the current voltage value; and The battery measurement anomaly determination unit determines that the current battery parameter data set belongs to the measurement anomaly based on the voltage difference being equal to or greater than a third preset value.

16. The battery measurement anomaly determination method according to claim 9, characterized in that the reference battery parameter data set includes a reference charge value, and the current battery parameter data set includes a current charge value; the battery measurement anomaly determination method further includes: The battery measurement anomaly determination unit obtains the reference peak value of the reference charge value with respect to voltage change; The battery measurement anomaly determination unit obtains the current peak value of the current charge value with respect to voltage change; The battery measurement anomaly determination unit obtains the voltage difference between the reference voltage value corresponding to the reference peak value and the current voltage value corresponding to the current peak value; and The battery measurement anomaly determination unit determines that the current battery parameter data set belongs to the measurement anomaly based on the voltage difference being equal to or greater than a third preset value.

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