Battery authenticity determination method, battery authenticity determination device, and program

Abstract

An acquisition unit (41) acquires, for a battery that is a judgment object, first data indicating a charge / discharge history in a first period and second data indicating a charge / discharge history in a second period that is earlier than the first period, a calculation unit (42) calculates, based on the first data, a first state quantity indicating a state quantity of the battery in the first period, and calculates, based on the second data, a second state quantity indicating an estimated value of the state quantity of the battery in the first period, a judgment unit (43) performs, based on the first state quantity and the second state quantity, a true / false judgment of whether the battery is a genuine product or a fake product in the first period, and an output unit (44) outputs a result of the true / false judgment.

Description

Technical Field

[0001] This disclosure relates to a method, device, and procedure for determining the authenticity of batteries. Background Technology

[0002] Patent document 1 disclosed a battery authentication system that determines the authenticity of a battery based on the battery pack ID assigned to the ECU of the battery pack.

[0003] According to the battery authentication system disclosed in the aforementioned Patent Document 1, the battery can be correctly identified as a counterfeit even if only the battery cells are replaced with counterfeit ones.

[0004] Prior art literature

[0005] Patent documents

[0006] Patent Document 1: Japanese Patent Application Publication No. 2012-222945 Summary of the Invention

[0007] The purpose of this disclosure is to provide a technology that can correctly identify a battery as a counterfeit even if only the battery cells are replaced with counterfeit ones.

[0008] The battery authenticity determination method disclosed herein involves, for the battery being determined, acquiring first data representing the charge-discharge history in a first period and second data representing the charge-discharge history in a second period earlier than the first period; calculating a first state quantity representing the state quantity of the battery in the first period based on the first data; calculating a second state quantity representing the inferred value of the state quantity of the battery in the first period based on the second data; and determining whether the battery is a genuine or counterfeit product in the first period based on the first and second state quantities, and outputting the result of the authenticity determination. Attached Figure Description

[0009] Figure 1 This is a simplified block diagram illustrating the structure of the battery management system according to embodiments of the present disclosure.

[0010] Figure 2 This is a flowchart representing the first instance of the authenticity judgment process performed by the server device.

[0011] Figure 3 This is a graph showing an example of the time series variation of the fully charged capacity of a battery pack.

[0012] Figure 4 This is a flowchart representing the second example of the authenticity judgment process performed by the server device.

[0013] Figure 5 This is a graph showing an example of the distribution of OCV values ​​corresponding to the SOC of the battery pack.

[0014] Figure 6 This is a flowchart representing the third example of the authenticity judgment process performed by the server device.

[0015] Figure 7 This is a graph showing the voltage drop that occurs as the battery pack discharges.

[0016] Figure 8 This is a graph showing an example of the distribution of voltage drops corresponding to the battery pack's SOC and discharge current rate.

[0017] Figure 9 This is the flowchart for the fourth example of the authenticity judgment process performed by the server device.

[0018] Figure 10 This is a diagram representing the first variation of the system structure.

[0019] Figure 11 This is a diagram representing the second variation of the system structure.

[0020] Figure 12 This is a diagram representing the third variation of the system structure. Detailed Implementation

[0021] (Based on the understanding that forms the basis of this disclosure)

[0022] Genuine battery packs used in electric motorcycles and similar products are expensive and can be resold, so counterfeit products are expected to circulate widely. To prevent accidents or vehicle malfunctions caused by the use of inferior counterfeit products, and to maintain a reasonable price for genuine products, it is necessary to curb the circulation of counterfeit products in the market.

[0023] Patent Document 1 disclosed a battery authentication system for batteries installed in electric vehicles. In this system, an anti-theft unit compares a first battery pack ID stored in the memory of the ECU of the battery pack with a second battery pack ID stored in the memory of the ECU of the vehicle. If the two match, the vehicle is allowed to start; if they do not match, the vehicle is prohibited from starting.

[0024] However, according to the battery authentication system disclosed in the aforementioned Patent Document 1, when a genuine ECU is used in the battery pack and only the battery cells are replaced with counterfeit ones, the anti-theft unit mistakenly identifies the battery pack as genuine because the ID of the first battery pack stored in the memory of the ECU remains unchanged.

[0025] In order to solve the aforementioned problems, the inventors have come to the understanding that recording the charging and discharging history of a battery and determining the authenticity of the battery based on the state variables of the battery that can be calculated from the charging and discharging history, thereby detecting the exchange of battery cells through sudden large changes in the state variables, and thus came to this disclosure.

[0026] The various methods disclosed herein will now be explained.

[0027] In one aspect of the battery authenticity determination method disclosed herein, a computer, for a battery having battery cells, acquires first data representing the charge-discharge history in a first period and second data representing the charge-discharge history in a second period earlier than the first period. Based on the first data, a first state quantity representing the state quantity of the battery in the first period is calculated. Based on the second data, a second state quantity representing the inferred value of the state quantity of the battery in the first period is calculated. Based on the first state quantity and the second state quantity, the authenticity determination of the battery, whether it is a genuine product or a counterfeit product, is performed in the first period, and the result of the authenticity determination is output.

[0028] According to this method, a first state quantity representing the state quantity of the battery during a first period is calculated based on first data, and a second state quantity representing the inferred value of the battery state quantity during the first period is calculated based on second data. When a genuine battery cell is replaced with a counterfeit, the first and second state quantities differ significantly before and after the replacement. Therefore, by determining the authenticity of the battery based on the first and second state quantities, the replacement of the battery cell can be detected. As a result, even if only the battery cell is replaced with a counterfeit, the battery can be correctly identified as a counterfeit.

[0029] In the above manner, the state quantity includes the fully charged capacity.

[0030] This method allows for the accurate calculation of a battery's full charge capacity based on its charge and discharge history. Therefore, determining the authenticity of a battery based on its full charge capacity can improve the accuracy of the determination.

[0031] In the above method, in the calculation of the first state quantity, based on the first data, the fully charged capacity is calculated whenever the battery is fully charged during the first period, thereby calculating multiple fully charged capacity values. In the calculation of the second state quantity, based on the second data, an inferred value of the fully charged capacity of the battery during the first period, an allowable upper limit value, and an allowable lower limit value interleaved with the inferred value are calculated. In the authenticity determination, the ratio of the number of fully charged capacity values ​​exceeding the allowable upper limit value or less than the allowable lower limit value during the first period to the total number of the multiple fully charged capacity values ​​is calculated as the probability that the battery is a counterfeit.

[0032] This method outputs the probability of a battery being counterfeit as the result of a authenticity judgment, rather than a binary choice between whether the battery is genuine or counterfeit.

[0033] In the above manner, the state quantity includes the open terminal voltage corresponding to the remaining capacity rate.

[0034] In this way, the open terminal voltage corresponding to the battery's remaining capacity rate can be accurately calculated based on the battery's charge and discharge history. Therefore, judging the authenticity of a battery by using the open terminal voltage corresponding to the battery's remaining capacity rate can improve the accuracy of the judgment.

[0035] In the above method, in the calculation of the first state quantity, based on the first data, the open terminal voltage is calculated whenever the battery is charged during the first period, thereby calculating multiple open terminal voltage values. In the calculation of the second state quantity, based on the second data, an inferred value of the open terminal voltage during the first period, an allowable upper limit value, and an allowable lower limit value are calculated. In the authenticity determination, the ratio of the number of open terminal voltage values ​​exceeding the allowable upper limit value or less than the allowable lower limit value during the first period to the total number of multiple open terminal voltage values ​​is calculated as the probability that the battery is a counterfeit.

[0036] This method outputs the probability that a battery is counterfeit as a result of authenticity judgment, rather than a binary choice of whether the battery is genuine or counterfeit.

[0037] In the above manner, the state quantity includes a decreasing voltage corresponding to the remaining capacity rate and the discharge current rate.

[0038] This method allows for the accurate calculation of the voltage drop corresponding to the battery's remaining capacity rate and discharge current rate based on the battery's charge and discharge history. Therefore, determining the authenticity of a battery based on the voltage drop corresponding to its remaining capacity rate and discharge current rate can improve the accuracy of the determination.

[0039] In the above method, in the calculation of the first state quantity, based on the first data, the voltage drop is calculated whenever the battery is discharged during the first period, thereby calculating multiple voltage drop values. In the calculation of the second state quantity, based on the second data, an inferred value of the voltage drop during the first period, an allowable upper limit value, and an allowable lower limit value interposed with the inferred value are calculated. In the authenticity determination, the ratio of the number of voltage drop values ​​exceeding the allowable upper limit value or less than the allowable lower limit value during the first period to the total number of the multiple voltage drop values ​​is calculated as the probability that the battery is a counterfeit.

[0040] This method outputs the probability that a battery is counterfeit as a result of authenticity judgment, rather than a binary choice of whether the battery is genuine or counterfeit.

[0041] The battery authenticity determination device disclosed herein comprises: an acquisition unit for acquiring, for a battery having battery cells, first data representing the charge-discharge history during a first period and second data representing the charge-discharge history during a second period earlier than the first period; a calculation unit for calculating, based on the first data, a first state quantity representing the state quantity of the battery during the first period, and based on the second data, a second state quantity representing an inferred value of the state quantity of the battery during the first period; a determination unit for determining whether the battery is a genuine product or a counterfeit product during the first period based on the first state quantity and the second state quantity; and an output unit for outputting the result of the authenticity determination.

[0042] In this method, the calculation unit calculates a first state quantity representing the state quantity of the battery during the first period based on the first data, and calculates a second state quantity representing the inferred value of the state quantity of the battery during the first period based on the second data. When a genuine battery cell is replaced with a counterfeit, the first and second state quantities differ significantly before and after the replacement. Therefore, by having the judgment unit determine the authenticity of the battery based on the first and second state quantities, it is possible to detect that the battery cell has been replaced. As a result, even if only the battery cell is replaced with a counterfeit, the battery can be correctly identified as a counterfeit.

[0043] One aspect of this disclosure relates to a program for enabling a computer to function as: an acquisition unit, for a battery having battery cells, acquiring first data representing the charge-discharge history during a first period and second data representing the charge-discharge history during a second period earlier than the first period; a calculation unit, based on the first data, calculating a first state quantity representing the state quantity of the battery during the first period, and based on the second data, calculating a second state quantity representing an inferred value of the state quantity of the battery during the first period; a judgment unit, based on the first state quantity and the second state quantity, judging whether the battery is genuine or counterfeit during the first period; and an output unit, outputting the result of the authenticity judgment.

[0044] In this method, the calculation unit calculates a first state quantity representing the state quantity of the battery during a first period based on the first data, and calculates a second state quantity representing the inferred value of the state quantity of the battery during the first period based on the second data. When a genuine battery cell is replaced with a counterfeit one, the first and second state quantities differ significantly before and after the replacement. Therefore, by having the judgment unit determine the authenticity of the battery based on the first and second state quantities, the battery cell replacement can be detected. As a result, even if only the battery cell is replaced with a counterfeit, the battery can be correctly identified as a counterfeit.

[0045] This disclosure can also be implemented as a computer program for causing a computer to execute the characteristic structures included in the methods described above, or as an apparatus or system operating based on the computer program. Furthermore, the computer program described above can be distributed as a computer-readable non-volatile recording medium such as a CD-ROM, or distributed via a communication network such as the Internet.

[0046] Furthermore, the embodiments described below are all specific examples of this disclosure. The numerical values, shapes, structural elements, steps, and order of steps shown in the following embodiments are examples and are not intended to limit the scope of this disclosure. In addition, structural elements in the following embodiments that represent the highest-level concept but are not described in the independent claims are described as arbitrary structural elements. Moreover, the contents of all embodiments can be combined.

[0047] (Implementation of this disclosure)

[0048] Hereinafter, embodiments of the present disclosure will be described in detail using the accompanying drawings. Furthermore, elements given the same reference numerals in different drawings represent the same or corresponding elements.

[0049] Figure 1This is a block diagram illustrating a simplified structure of the battery management system according to an embodiment of the present disclosure. In this embodiment, the battery management system manages multiple battery packs 2A and 2B installed in multiple vehicles 1A and 1B, such as electric motorcycles.

[0050] The battery management system includes a server device 5 connected to a communication network 4. The communication network 4 is, for example, a public wired network. The server device 5 is, for example, a cloud server, which functions as a authenticity verification device in the system architecture described in this embodiment.

[0051] Server device 5 includes a communication unit 31, a control unit 32, and a storage unit 33. The communication unit 31 is configured using a communication module for wireless communication via any communication method such as IP. The storage unit 33 is configured using a hard disk, SSD, or semiconductor memory, etc. The storage unit 33 stores a program 51 and historical data 52. The control unit 32 is configured using a data processing device such as a CPU. As the CPU executes the program 51 to perform its functions, the control unit 32 includes an acquisition unit 41, a calculation unit 42, a judgment unit 43, and an output unit 44.

[0052] Vehicle 1A includes battery pack 2A and vehicle control device 3A. Battery pack 2A supplies power to drive the drive motor and other components mounted on vehicle 1A. In addition, battery pack 2A can be charged via a plug-in method by receiving power from a commercial power source or the like connected to an external power source of vehicle 1A.

[0053] Battery pack 2A includes: a control unit 11A, a communication unit 12A, a current sensor 13A, a voltage sensor 14A, and a battery cell 15A. The control unit 11A is configured using a data processing device such as a CPU. The communication unit 12A is configured using a communication module for wireless communication via any communication method such as Bluetooth (registered trademark). The battery cell 15A is configured using a rechargeable secondary battery such as a lithium-ion battery. The current sensor 13A detects the charging and discharging current (charging current and discharging current) of the battery cell 15A and outputs current value data representing the detected current value. The voltage sensor 14A detects the voltage between the two terminals (positive and negative) of the battery cell 15A and outputs voltage value data representing the detected voltage value.

[0054] The vehicle control device 3A is configured to utilize a portion of the functions of the navigation device in the vehicle 1A. The vehicle control device 3A includes a control unit 21A and communication units 22A and 23A. The control unit 21A is configured using a data processing device such as a CPU. The communication unit 22A is configured using a communication module for wireless communication with the communication unit 12A of the battery pack 2A via any communication method such as Bluetooth (registered trademark). The communication unit 23A is configured using a communication module for wireless communication with the communication unit 31 of the server device 5 via any communication method such as IP.

[0055] The structure of vehicle 1B is the same as that of vehicle 1A. Vehicle 1B includes a battery pack 2B and a vehicle control device 3B. The battery pack 2B includes a control unit 11B, a communication unit 12B, a current sensor 13B, a voltage sensor 14B, and battery cells 15B. The vehicle control device 3B includes a control unit 21B and communication units 22B and 23B.

[0056] In the battery management system of this embodiment, the server device 5 manages the battery packs 2A and 2B mounted on vehicles 1A and 1B. Each battery pack 2A and 2B is assigned an identification information, namely a battery pack ID, for identifying multiple battery packs.

[0057] If the charging / discharging current flows to battery cell 15A, current value data is input from current sensor 13A to control unit 11A, and voltage value data is input from voltage sensor 14A to control unit 11A. Control unit 11A inputs the current value data and voltage value data to communication unit 12A. This current value data and voltage value data include the battery pack ID of battery pack 2A. Communication unit 12A sends the current value data and voltage value data to vehicle control device 3A. Communication unit 22A of vehicle control device 3A receives the current value data and voltage value data and inputs the received current value data and voltage value data to control unit 21A. Control unit 21A inputs the current value data and voltage value data to communication unit 23A. Communication unit 23A sends the current value data and voltage value data to server device 5. Communication unit 31 of server device 5 receives the current value data and voltage value data and inputs the received current value data and voltage value data to control unit 32. The control unit 32 associates the current and voltage data with the battery pack ID of the included battery pack 2A and stores them in the storage unit 33. Similarly, for vehicle 1B, the control unit 32 associates the current and voltage data with the battery pack ID of battery pack 2B and stores them in the storage unit 33. In this way, historical data 52, which associates the data with the battery pack IDs of each battery pack 2A and 2B and represents the charging and discharging history of each battery pack 2A and 2B, is stored in the storage unit 33.

[0058] Figure 2 This is a flowchart illustrating the first example of the authenticity judgment process performed by server device 5. The following explanation uses battery pack 2A as the judgment object, but the same applies when battery pack 2B is used as the judgment object.

[0059] If the execution command for determining the authenticity of battery pack 2A is input to the control unit 32, then firstly, in step SP101, the acquisition unit 41 acquires historical data 52 related to battery pack 2A by reading from the storage unit 33.

[0060] Next, in step SP102, the calculation unit 42 sets the period for determining the object. Hereinafter, an example of performing the battery authenticity determination process using one month as the unit period will be described. However, the unit period is not limited to one month; it can be any period such as several weeks or months.

[0061] Figure 3 This is a graph showing an example of the time-series variation of the fully charged capacity (FCC value) of a 2A battery pack. Figure 3 In the example shown, May of that year was the manufacturing month of battery pack 2A, and it was determined that battery pack 2A was a genuine product up to July of the same year. In this case, the calculation unit 42 sets the first month that was not yet determined, namely August of the same year, as the period to be determined (the month to be determined).

[0062] Next, in step SP103, the calculation unit 42 extracts all historical data (hereinafter referred to as "fully charged data") corresponding to the charging operations performed up to the fully charged state from the historical data 52 related to battery pack 2A in the month of judgment. The calculation unit 42 calculates the FCC value (first state quantity) for each of the extracted fully charged data. As an algorithm for calculating the FCC value based on the current value data and voltage value data contained in the fully charged data, any algorithm can be used. For example, correlation data that establishes a correlation between the internal resistance ratio of the battery in the initial state and the deterioration state and the fully charged capacity ratio in the initial state and the deterioration state can be pre-created and stored in the storage unit. The calculation unit 42 infers the internal resistance value of the battery based on the current value data, the voltage value data and known mapping information. The calculation unit 42 calculates the fully charged capacity ratio corresponding to the internal resistance ratio calculated based on the inferred internal resistance value by using the above-mentioned correlation data, thereby inferring the FCC value corresponding to each fully charged data.

[0063] Next, in step SP104, the calculation unit 42 calculates the inferred FCC value (second state quantity) of battery pack 2A in the target month based on historical data 52 related to battery pack 2A in the already determined month. The calculation unit 42 calculates the FCC value using the same algorithm as described above for all fully charged data from each of the already determined months, i.e., May to July, calculating the average of multiple FCC values ​​X5 to X7 for each month. The calculation unit 42 uses any inference algorithm, such as an approximation based on least squares or a prediction model based on machine learning, to derive, for example, an approximate straight line L based on the multiple averages X5 to X7. This approximate straight line L is applied to the target month, i.e., August, to calculate the inferred FCC value X8 for August.

[0064] Furthermore, the calculation unit 42 calculates the permissible value for the inferred FCC value in the target month based on historical data 52 from the most recent judged month. For example, the calculation unit 42 calculates the standard deviation σ by statistically processing multiple FCC values ​​in July, calculates the upper permissible value XU as the inferred value X8 plus 2×σ, and calculates the lower permissible value XL as the inferred value X8 minus 2×σ.

[0065] Next, in step SP105, the determination unit 43, based on the first state quantity and the second state quantity, determines whether the battery pack 2A is a genuine product or a counterfeit product within the month of determination. For example, the determination unit 43 determines whether the multiple FCC values, which are the first state quantity, fall within the allowable range including the inferred value X8, which is the second state quantity (i.e., a range below the upper allowable value XU and above the lower allowable value XL). Furthermore, the determination unit 43 calculates a probability probability K1 (=Y1 / Z1×100) indicating the probability that the battery pack 2A is a counterfeit product, as the ratio of the number of FCC values ​​(Y1) exceeding the upper allowable value XU or falling below the lower allowable value XL to the total number of multiple FCC values ​​(Z1), which are the first state quantity.

[0066] Next, in step SP106, the output unit 44 outputs data representing the likelihood rate K1 as the result of the truth or falsehood judgment based on the judgment unit 43. The battery management system administrator can access the server device 5 from the server device 5 via the communication network 4 to obtain the data representing the likelihood rate K1.

[0067] According to Example 1, the FCC value of battery pack 2A can be correctly calculated based on the historical charging and discharging data 52 of battery pack 2A. Therefore, the accuracy of the judgment can be improved by judging the authenticity of battery pack 2A based on the FCC value of battery pack 2A.

[0068] Furthermore, the probability K1, which represents the likelihood that battery pack 2A is a counterfeit, can be output as the result of the authenticity judgment, rather than a binary choice of whether battery pack 2A is a genuine product or a counterfeit.

[0069] Figure 4 This is a flowchart illustrating the second example of the authenticity judgment process performed by server device 5. The following explanation uses battery pack 2A as the judgment object, but the same applies when battery pack 2B is used as the judgment object.

[0070] If the execution command for determining the authenticity of battery pack 2A is input to the control unit 32, then firstly, in step SP201, the acquisition unit 41 acquires historical data 52 related to battery pack 2A in the same manner as in the first example described above.

[0071] Next, in step SP202, the calculation unit 42 sets the period for determining the object, just like in the first example above.

[0072] Next, in step SP203, the calculation unit 42 extracts all historical data (hereinafter referred to as "charging data") corresponding to the charging operation of battery pack 2A from the historical data 52 related to battery pack 2A in the judgment target month. For each extracted charging data, the calculation unit 42 calculates the open terminal voltage value (OCV value, first state quantity) corresponding to the remaining capacity rate (SOC) of battery pack 2A. The calculation unit 42 can calculate the SOC, for example, using the current integration method. Furthermore, the calculation unit 42 can approximate the voltage value data contained in the charging data as the OCV value. The calculation unit 42 divides the SOC distribution range (e.g., 40-100%) into multiple SOC regions by dividing it with a predetermined step width (e.g., 10%), and for each charging data, calculates the average of the multiple OCV values ​​contained in each SOC region as the OCV value corresponding to that SOC region.

[0073] Next, in step SP204, the calculation unit 42 calculates the inferred value (second state quantity) of the OCV value corresponding to the SOC of the battery pack 2A in the month of judgment based on the historical data 52 related to the battery pack 2A in the month of judgment.

[0074] Figure 5 This is a diagram showing an example of the distribution of OCV values ​​corresponding to the SOC of battery pack 2A. The calculation unit 42 calculates the OCV values ​​corresponding to the SOC using the same algorithm as described above, based on all charging data for each month from May to July, which are the months for which the SOC has been determined. The average of the multiple OCV values ​​for the months for which the SOC has been determined in each SOC region is calculated as the inferred OCV values ​​Y8A to Y8F corresponding to each SOC region.

[0075] Furthermore, the calculation unit 42 calculates the permissible value of the inferred value for the OCV value in the most recent judged month based on the historical data 52 of the judged month. For example, the calculation unit 42 calculates the standard deviation σ according to the SOC region by statistically processing multiple OCV values ​​in July. The permissible upper limit value YU is calculated by adding 2×σ to each inferred value Y8A to Y8F according to the SOC region, and the permissible lower limit value YL is calculated by subtracting 2×σ from each inferred value Y8A to Y8F according to the SOC region.

[0076] Next, in step SP205, the determination unit 43, based on the first state quantity and the second state quantity, determines whether the battery pack 2A is a genuine product or a counterfeit product within the month of determination. For example, the determination unit 43 determines whether the multiple OCV values, which are the first state quantity, fall within the allowable range of the inferred values ​​Y8A to Y8F, which are the second state quantity (i.e., the range below the upper allowable value YU and above the lower allowable value YL). Furthermore, the determination unit 43 calculates the probability that the battery pack 2A is a counterfeit product, K2 (=Y2 / Z2×100), as the ratio of the number of OCV values ​​(Y2) exceeding the upper allowable value YU or falling below the lower allowable value YL to the total number of multiple OCV values ​​(Z2) that are the first state quantity.

[0077] Next, in step SP206, the output unit 44 outputs data representing the result of the truth or falsehood judgment based on the judgment unit 43, i.e., the suspicion rate K2.

[0078] In the second example, based on the historical charging and discharging data 52 of battery pack 2A, the OCV value corresponding to the SOC of battery pack 2A can be correctly calculated. Therefore, by using the OCV value corresponding to the SOC of battery pack 2A to determine the authenticity of battery pack 2A, the accuracy of the determination can be improved.

[0079] Furthermore, the probability K2, which represents the likelihood that battery pack 2A is a counterfeit, can be output as the result of the authenticity judgment, rather than a binary choice of whether battery pack 2A is a genuine product or a counterfeit.

[0080] Figure 6 This is a flowchart illustrating the third example of the authenticity judgment process performed by server device 5. The following explanation uses battery pack 2A as the judgment object, but the same applies when battery pack 2B is used as the judgment object.

[0081] If the execution command for determining the authenticity of battery pack 2A is input to the control unit 32, then firstly, in step SP301, the acquisition unit 41 acquires historical data 52 related to battery pack 2A in the same manner as in the first example described above.

[0082] Next, in step SP302, the calculation unit 42 sets the period for determining the object, just like in the first example above.

[0083] Next, in step SP303, the calculation unit 42 extracts all historical data (hereinafter referred to as "discharge data") corresponding to the discharge operation of battery pack 2A from the historical data 52 related to battery pack 2A in the month of judgment. For each extracted discharge data, the calculation unit 42 calculates the voltage drop value (first state quantity) corresponding to the SOC of battery pack 2A and the discharge current rate (the ratio of the discharge current value to the maximum discharge current value).

[0084] Figure 7 This diagram illustrates the voltage drop that occurs during the discharge of battery pack 2A. At time T1, the discharge of battery pack 2A begins with the opening of the throttle valve of vehicle 1A. At time T2, the voltage drop ends when the rate of voltage drop falls below a predetermined value (e.g., 0.1V / sec). The difference between the terminal voltage V1 of battery cell 15A at time T1 and the terminal voltage V2 at time T2 (=V1-V2) is the voltage drop value.

[0085] The calculation unit 42 can calculate the State of Charge (SOC) for example using the current integration method. Furthermore, the calculation unit 42 can process the current value data included in the discharge data into a discharge current value. Additionally, the calculation unit 42 can process the voltage value data included in the discharge data into an inter-terminal voltage value. The calculation unit 42 divides the SOC distribution range (e.g., 50-100%) into multiple SOC regions by dividing it with a predetermined step width (e.g., 10%). Furthermore, the calculation unit 42 divides the discharge current rate distribution range (e.g., 50-100%) into multiple current rate regions by dividing it with a predetermined step width (e.g., 10%). If the calculation unit 42 detects a voltage drop in each discharge data, it calculates and records the voltage drop value by corresponding to the SOC region and current rate region of the battery pack 2A at that time and the discharge current rate.

[0086] Next, in step SP304, the calculation unit 42 calculates the inferred value (second state quantity) of the SOC and the corresponding drop voltage value of the discharge current rate of the battery pack 2A in the month of judgment based on the historical data 52 related to the battery pack 2A in the month of judgment.

[0087] Figure 8This is a diagram showing an example of the distribution of voltage drops corresponding to the State of Charge (SOC) and discharge current rate of battery pack 2A. The calculation unit 42 calculates the voltage drops corresponding to the SOC and discharge current rate using the same algorithm as described above, taking all discharge data from each month (May to July) as the months for which the current rate was determined. The average of the multiple voltage drops for each month in each SOC region and each current rate region is calculated as an estimated value of the voltage drops corresponding to each SOC region and each current rate region.

[0088] Furthermore, the calculation unit 42 calculates the permissible value for the inferred value of the voltage drop in the target month based on historical data 52 from the most recent judged month. The calculation unit 42 performs statistical processing on multiple voltage drop values ​​in, for example, July, to calculate the standard deviation σ according to the SOC region and the current rate region, calculates the upper limit permissible value according to the SOC region and the current rate region as the value of adding 2×σ to each inferred value, and calculates the lower limit permissible value according to the SOC region and the current rate region as the value of subtracting 2×σ from each inferred value.

[0089] Next, in step SP305, the determination unit 43, based on the first state quantity and the second state quantity, determines whether the battery pack 2A is a genuine product or a counterfeit product within the month of determination. For example, the determination unit 43 determines whether the multiple voltage drops, which are the first state quantity, fall within the allowable range (i.e., the range below the upper allowable value and above the lower allowable value) of each inferred value, which are the second state quantity. Furthermore, the determination unit 43 calculates a probability K3 (=Y3 / Z3×100) representing the probability that the battery pack 2A is a counterfeit product, which is the ratio of the number of voltage drops (Y3) exceeding the upper allowable value or falling below the lower allowable value to the total number of voltage drops (Z3) of the multiple voltage drops, which are the first state quantity.

[0090] Next, in step SP306, the output unit 44 outputs data representing the result of the truth or falsehood judgment based on the judgment unit 43, i.e., the suspicion rate K3.

[0091] According to Example 3, the voltage drop value corresponding to the SOC and discharge current rate of battery pack 2A can be accurately calculated based on the historical charging and discharging data 52 of battery pack 2A. Therefore, by determining the authenticity of battery pack 2A based on the voltage drop value corresponding to the SOC and discharge current rate of battery pack 2A, the accuracy of the determination can be improved. Furthermore, the voltage drop value may vary depending on the output of the vehicle equipped with the battery pack; therefore, the voltage drop value can also be calculated separately for each type of vehicle.

[0092] Furthermore, the probability K3, which represents the likelihood that battery pack 2A is a counterfeit, can be output as the result of the authenticity judgment, rather than a binary choice of whether battery pack 2A is a genuine product or a counterfeit.

[0093] Figure 9 This is a flowchart illustrating the fourth example of the truth-verification process performed by server device 5. This fourth example combines examples 1 through 3 described above. However, it is not necessary to combine all of examples 1 through 3 described above; in addition, examples other than those 1 through 3 can also be combined.

[0094] If the execution command for the authenticity judgment process of all battery packs managed in the server device 5 is input to the control unit 32, then firstly, in step SP401, the acquisition unit 41 sets the battery pack ID of the battery pack 2A that was initially judged by updating the battery pack ID.

[0095] Next, in step SP402, the acquisition unit 41 acquires historical data 52 related to the battery pack 2A in the same manner as in the first example described above.

[0096] Next, in step SP403, the calculation unit 42 sets the period for determining the object, just like in the first example above.

[0097] Next, in step SP404, the calculation unit 42 and the judgment unit 43 calculate the suspected rate K1 in the same way as in steps SP103 to SP105.

[0098] Next, in step SP405, the calculation unit 42 and the judgment unit 43 calculate the suspected rate K2 in the same manner as in steps SP203 to SP205 above.

[0099] Next, in step SP406, the calculation unit 42 and the judgment unit 43 calculate the suspected rate K3 in the same manner as in steps SP303 to SP305.

[0100] Next, in step SP407, the judgment unit 43 calculates the suspected rate K4 by weighting the suspected rates K1 to K3 with coefficients W1 to W3 of "0" or higher as shown in the following formula (1).

[0101] K4=(W1×K1+W2×K2+W3×K3) / (W1+W2+W3): (1)

[0102] Next, in step SP408, the output unit 44 outputs data representing the result of the authenticity judgment based on the judgment unit 43, i.e., the suspicion rate K4, which indicates that the battery pack 2A is the object of judgment.

[0103] Next, in step SP409, the acquisition unit 41 determines whether the authenticity judgment process, which takes all battery packs managed in the server device 5 as the judgment object, has ended.

[0104] If there is an unchecked battery pack (step SP409: No), then in step SP401, the acquisition unit 41 sets the battery pack ID of the battery pack 2B to be checked next by updating the battery pack ID. The processing after step SP402 is then performed.

[0105] When the verification process for all battery packs has been completed (step SP409: Yes), the control unit 32 ends the process.

[0106] (Summarize)

[0107] According to the battery management system of this embodiment, the calculation unit 42 calculates the FCC value (first state quantity) representing the state quantity of the battery pack 2A (battery) during the first period based on historical data 52 (first data) in the judgment period (first period). Furthermore, the calculation unit 42 calculates the FCC value (second state quantity) representing the inferred value of the battery's state quantity during the first period based on historical data 52 (second data) in a judgment period earlier than the first period (second period). When a genuine battery cell 15A is replaced with a counterfeit, the first state quantity and the second state quantity differ significantly before and after the replacement. Therefore, by having the judgment unit 43 determine the authenticity of the battery based on the first and second state quantities, it is possible to detect that the battery cell 15A has been replaced. As a result, even if only the battery cell 15A is replaced with a counterfeit, the battery can be correctly identified as a counterfeit.

[0108] (First variation)

[0109] Figure 10 This diagram illustrates a first modified example of the system structure. In this modified example, battery packs 2A and 2B include storage units 16A and 16B. Storage units 16A and 16B are configured using semiconductor memories or the like.

[0110] Battery packs 2A and 2B, as well as server device 5, all function as nodes in the blockchain, sharing the same historical data 52 in the storage units 16A, 16B, and 33 of each node. When the charge / discharge history of any battery pack 2A or 2B is updated, the update information indicating the update is sent to other battery packs 2B and 2A, as well as server device 5, via communication network 4. The historical data 52 is updated shared across all nodes.

[0111] According to this variation, it is difficult to tamper with the historical data 52 based on a third party, thus improving the security of the system.

[0112] (Second variation)

[0113] Figure 11This is a diagram illustrating the second variation of the system structure. In this variation, instead of a server device 5 such as a cloud server acting as the authenticity verification device, a local PC or a dedicated counterfeit detector acts as the authenticity verification device 6.

[0114] The battery pack 2 includes: a control unit 11, a communication unit 12, a current sensor 13, a voltage sensor 14, battery cells 15, and a storage unit 16. The storage unit 16 is constructed using a semiconductor memory or the like. The communication unit 12 can communicate with the communication unit 31 of the authenticity verification device 6 via wired or wireless means.

[0115] As the vehicle operates, charging and discharging current flows through the battery cell 15, current value data is input from the current sensor 13 to the control unit 11, and voltage value data is input from the voltage sensor 14 to the control unit 11. The control unit 11 inputs historical data 52, which includes current value data and voltage value data, to the storage unit 16, and the storage unit 16 stores the historical data 52.

[0116] If battery pack 2 is removed from the vehicle and connected to the authenticity verification device 6, the control unit 11 reads historical data 52 from the storage unit 16 and inputs the historical data 52 to the communication unit 12. The communication unit 12 sends the historical data 52 to the authenticity verification device 6. The communication unit 31 of the authenticity verification device 6 receives the historical data 52 and inputs the received historical data 52 to the control unit 32. The control unit 32 stores the historical data 52 in the storage unit 33. Furthermore, based on the historical data 52 read from the storage unit 33, the control unit 32 performs authenticity verification processing on battery pack 2 using the same method as in the above embodiment.

[0117] Through this modified example, by using a simple structure such as a local PC as the authenticity determination device 6, it is possible to realize the authenticity determination process for the battery pack 2.

[0118] (3rd variation)

[0119] Figure 12 This is a diagram illustrating a third variation of the system structure. In this variation, the charger 7, used to charge the battery pack 2, is connected to the server device 5 via the communication network 4.

[0120] As the vehicle operates, charging and discharging current flows through the battery cell 15, current value data is input from the current sensor 13 to the control unit 11, and voltage value data is input from the voltage sensor 14 to the control unit 11. The control unit 11 inputs historical data 52, which includes current value data and voltage value data, to the storage unit 16, and the storage unit 16 stores the historical data 52.

[0121] If battery pack 2 is removed from the vehicle and connected to charger 7, control unit 11 reads historical data 52 from storage unit 16 and inputs the historical data 52 to communication unit 12. Communication unit 12 sends historical data 52 to charger 7. Communication unit 22 of charger 7 receives historical data 52 and inputs the received historical data 52 to control unit 21. Control unit 21 inputs historical data 52 to communication unit 23. Communication unit 23 sends historical data 52 to server device 5. Communication unit 31 of server device 5 receives historical data 52 and inputs the received historical data 52 to control unit 32. Control unit 32 stores historical data 52 in storage unit 33. Furthermore, based on historical data 52 read from storage unit 33, control unit 32 performs authenticity determination processing for battery pack 2 using the same method as in the above embodiment.

[0122] This modified example enables the verification of the authenticity of battery pack 2 installed in vehicles with plug types that do not correspond to the plug type.

[0123] Industrial availability

[0124] This disclosure is particularly useful for applications of battery management systems that manage the state of multiple battery packs mounted on multiple electric motorcycles, etc.

Claims

1. A method for determining the authenticity of a battery. The computer performs the following processing: For a battery with battery cells, first data representing the charge-discharge history during a first period and second data representing the charge-discharge history during a second period earlier than the first period are obtained. Based on the first data, a first state quantity representing the state quantity of the battery during the first period is calculated. Based on the second data, a second state quantity is calculated, representing an inferred value of the state quantity of the battery during the first period. Based on the first state quantity and the second state quantity, during the first period, a determination is made as to whether the battery is a genuine product or a counterfeit. Output the result of the truth or falsehood judgment.

2. The method for determining the authenticity of a battery according to claim 1, wherein, The state quantity includes the fully charged capacity.

3. The method for determining the authenticity of a battery according to claim 2, wherein, In the calculation of the first state quantity, based on the first data, the fully charged capacity is calculated each time the battery is fully charged during the first period, thereby calculating multiple fully charged capacity values. In the calculation of the second state quantity, based on the second data, an estimated value of the battery's full charge capacity during the first period, and an upper and lower allowable limit value interposed with this estimated value are calculated. In the authenticity determination, the ratio of the number of fully charged capacity values ​​exceeding the upper limit or falling below the lower limit during the first period to the total number of the plurality of fully charged capacity values ​​is calculated as the probability that the battery is a counterfeit.

4. The method for determining the authenticity of a battery according to any one of claims 1 to 3, wherein, The state quantity includes the open terminal voltage corresponding to the remaining capacity rate.

5. The method for determining the authenticity of a battery according to claim 4, wherein, In the calculation of the first state quantity, based on the first data, the open terminal voltage is calculated each time the battery is charged during the first period, thereby calculating multiple open terminal voltage values. In the calculation of the second state quantity, based on the second data, the inferred value of the voltage between the open terminals during the first period, and the upper and lower allowable limits interposed with the inferred value are calculated. In the authenticity determination, the ratio of the number of open terminal voltage values ​​exceeding the upper limit or falling below the lower limit during the first period to the total number of open terminal voltage values ​​is calculated as the probability that the battery is a counterfeit.

6. The method for determining the authenticity of a battery according to any one of claims 1 to 5, wherein, The state quantity includes the voltage drop corresponding to the remaining capacity rate and discharge current rate.

7. The method for determining the authenticity of a battery according to claim 6, wherein, In the calculation of the first state quantity, based on the first data, the voltage drop is calculated each time the battery is discharged during the first period, thereby calculating multiple voltage drop values. In the calculation of the second state quantity, based on the second data, the inferred value of the voltage drop during the first period, and the upper and lower allowable limits interposed with the inferred value are calculated. In the authenticity determination, the ratio of the number of voltage drops exceeding the upper limit or falling below the lower limit during the first period to the total number of the plurality of voltage drops is calculated as the probability that the battery is a counterfeit.

8. A device for determining the authenticity of a battery, comprising: The acquisition unit acquires, for a battery having battery cells, first data representing the charge-discharge history during a first period and second data representing the charge-discharge history during a second period earlier than the first period; The calculation unit calculates a first state quantity representing the state quantity of the battery during the first period based on the first data, and calculates a second state quantity representing an inferred value of the state quantity of the battery during the first period based on the second data. and The judgment unit, based on the first state quantity and the second state quantity, determines whether the battery is a genuine product or a counterfeit product during the first period; and The output section outputs the result of the truth or falsehood judgment.

9. A program for enabling a computer to function as: The acquisition unit acquires, for a battery having battery cells, first data representing the charge-discharge history in a first period and second data representing the charge-discharge history in a second period earlier than the first period. The calculation unit calculates a first state quantity representing the state quantity of the battery during the first period based on the first data, and calculates a second state quantity representing an inferred value of the state quantity of the battery during the first period based on the second data. The judgment unit, based on the first state quantity and the second state quantity, makes a judgment on whether the battery is a genuine product or a counterfeit product during the first period; and The output unit outputs the result of the truth or falsehood judgment.

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