WO2024111395A1

WO2024111395A1 - Battery management system, battery management method, and battery management program

Info

Publication number: WO2024111395A1
Application number: PCT/JP2023/039933
Authority: WO
Inventors: 彰彦工藤; 幸嗣早田; 英治大水
Original assignee: エナジーウィズ株式会社
Priority date: 2022-11-25
Filing date: 2023-11-06
Publication date: 2024-05-30

Abstract

This battery management system comprises: an acquisition unit that acquires reference data indicating the state of a storage battery during a reference period and target data indicating the state of the storage battery in a target period after the reference period; a calculation unit that calculates the characteristic value regarding discharge of the storage battery during the reference period as a reference characteristic value, on the basis of the reference data and a minimum drive voltage of electric equipment that uses power supplied from the storage battery, and calculates the characteristic value related to the discharge of the storage battery during the target period as a target characteristic value on the basis of the target data and the minimum drive voltage; and an estimation unit that estimates a deterioration state of the storage battery on the basis of a relationship between the reference characteristic value and the target characteristic value.

Description

Battery management system, battery management method, and battery management program

One aspect of the present disclosure relates to a battery management system, a battery management method, and a battery management program.

Patent Document 1 describes an automatic battery life determination device for an electrically powered vehicle. This automatic battery life determination device has a voltage/current detection means for detecting the battery's terminal voltage and output current, a resistance detection means for calculating the battery's internal resistance from the detected changes in terminal current and output voltage, a limit drive power calculation means for calculating the battery output at the minimum drive voltage value of the motor based on the terminal voltage change data and output current change data, and an output means for comparing the calculated internal resistance with a reference value representing the maximum internal resistance capable of ensuring battery performance and for comparing the calculated output with a reference value representing the minimum output capable of ensuring the performance of the electrically powered vehicle, and for determining and notifying that the battery has reached the end of its life or is nearing the end of its life.

Japanese Patent Application Laid-Open No. 9-230010

There is a need for a method to accurately estimate the deterioration state of storage batteries.

A battery management system according to one aspect of the present disclosure includes an acquisition unit that acquires reference data indicating the state of a storage battery in a reference period and target data indicating the state of the storage battery in a target period following the reference period, a calculation unit that calculates a characteristic value related to the discharge of the storage battery in the reference period as a reference characteristic value based on the reference data and a minimum drive voltage of an electric device that uses power supplied from the storage battery, and calculates a characteristic value related to the discharge of the storage battery in the target period as a target characteristic value based on the target data and the minimum drive voltage, and an estimation unit that estimates a degradation state of the storage battery based on the relationship between the reference characteristic value and the target characteristic value.

A battery management method according to one aspect of the present disclosure is executed by a battery management system having at least one processor. This battery management method includes the steps of acquiring reference data indicating the state of the storage battery in a reference period and target data indicating the state of the storage battery in a target period after the reference period, calculating a characteristic value related to the discharge of the storage battery in the reference period as a reference characteristic value based on the reference data and a minimum drive voltage of an electric device that uses power supplied from the storage battery, and calculating a characteristic value related to the discharge of the storage battery in the target period as a target characteristic value based on the target data and the minimum drive voltage, and estimating a deterioration state of the storage battery based on the relationship between the reference characteristic value and the target characteristic value.

A battery management program according to one aspect of the present disclosure causes a computer to execute the steps of acquiring reference data indicating the state of a storage battery during a reference period and target data indicating the state of the storage battery during a target period following the reference period, calculating a characteristic value relating to the discharge of the storage battery during the reference period as a reference characteristic value based on the reference data and the minimum operating voltage of an electric device that uses power supplied from the storage battery, and calculating a characteristic value relating to the discharge of the storage battery during the target period as a target characteristic value based on the target data and the minimum operating voltage, and estimating a deterioration state of the storage battery based on the relationship between the reference characteristic value and the target characteristic value.

In this aspect, the degraded state of the storage battery is estimated from the relationship between a reference characteristic value calculated based on the reference data and the minimum driving voltage and a target characteristic value calculated based on the target data and the minimum driving voltage. By taking into account the minimum driving voltage, which is a parameter of the electrically-driven device to which power is supplied from the storage battery, it is possible to calculate a reference characteristic value and a target characteristic value that are in line with the actual use of the storage battery. Therefore, the degraded state of the storage battery can be accurately estimated based on the relationship between these two characteristic values.

According to one aspect of the present disclosure, the deterioration state of a storage battery can be accurately estimated.

FIG. 2 is a diagram illustrating an example of a functional configuration of a battery management system. FIG. 2 is a diagram illustrating an example of a hardware configuration of a computer that constitutes a battery management system. 4 is a flowchart showing an example of a process performed by the battery management system. FIG. 11 is a diagram illustrating an example of time-series data of SOC. FIG. 13 is a diagram showing another example of time-series data of SOC. FIG. 1 is a diagram showing an example of a graph relating to OCV-SOC characteristics. FIG. 13 is a diagram showing an example of a graph relating to DCR-SOC characteristics. FIG. 13 is a diagram showing an example of a graph relating to a reference characteristic value and a target characteristic value.

Below, an embodiment of the present disclosure will be described in detail with reference to the attached drawings. In the description of the drawings, identical or equivalent elements are given the same reference numerals, and duplicate descriptions will be omitted.

[System Configuration]
The battery management system 1 is a computer system that estimates the degradation state of a storage battery. The degradation state indicates the degree to which the performance of the storage battery has deteriorated from a new state at the time of manufacture. Examples of the types of storage battery include, but are not limited to, a lead-acid battery and a lithium-ion battery. The storage battery may be a battery pack composed of a plurality of single cells of the same type.

In one example, the battery management system 1 estimates the degradation state of a storage battery that supplies power to an electrically-driven device. In other words, it can be said that the battery management system 1 estimates the degradation state of a storage battery mounted on or connected to the electrically-driven device. An electrically-driven device is a device that operates using all or part of the electric energy stored in a storage battery as its motive power. The electrically-driven device may be, for example, an electric vehicle or a robot. The electrically-driven vehicle may be a vehicle for carrying people or a vehicle for moving luggage. The electrically-driven vehicle may be an aerial work vehicle having a function of moving people vertically, or a loading vehicle having a function of moving luggage vertically. The loading vehicle may be, for example, a forklift or an automated guided vehicle (AGV). In one example, the battery management system 1 may estimate the degradation state of a storage battery mounted on a forklift.

FIG. 1 is a diagram showing the functional configuration of a battery management system 1 according to an example. The battery management system 1 estimates the degradation state of a storage battery mounted on or connected to an electrically-driven device 2. In one example, the battery management system 1 includes a server 10. The server 10 can access a database 20 that stores storage battery data indicating the state of the storage battery mounted on or connected to the electrically-driven device 2 via a communication network. The database 20 stores storage battery data for each of at least one electrically-driven device 2. The database 20 may be a component of the battery management system 1, or may be provided in a computer system separate from the battery management system 1. The communication network used for the battery management system 1 is, for example, composed of at least one of the Internet and an intranet.

Each electric device 2 provides storage battery data to the database 20. In one example, the electric device 2 includes a battery management unit (BMU) 3 that monitors or controls the storage battery. The BMU 3 repeatedly measures the state of the storage battery at a given time interval and generates storage battery data indicating the state. The BMU 3 then transmits the storage battery data to the database 20 via a communication network at a given timing. The BMU 3 may be provided outside the electric device 2. The storage battery data is time-series data indicating the state of the storage battery. For example, each record of the storage battery data includes a measurement date and time and at least one physical quantity indicating the state of the storage battery. Examples of the physical quantity include, but are not limited to, a measured voltage, a measured current, and a measured temperature. For example, if each record of the storage battery includes a measured current, the measured current when the storage battery is charging is recorded as a positive value, and the measured current when the storage battery is discharging is recorded as a negative value. The storage battery data indicates a physical quantity measured, for example, every 100 milliseconds. In the database 20, the storage battery data is associated with at least one of a storage battery ID and an electric device ID. The storage battery ID is an identifier that uniquely identifies the storage battery. The electric device ID is an identifier that uniquely identifies the electric device 2.

The server 10 is a computer that estimates the deterioration state of the storage battery based on the storage battery data. The server 10 has the following functional modules: an acquisition unit 11, a calculation unit 12, an estimation unit 13, and an output unit 14. The acquisition unit 11 is a functional module that acquires storage battery data from the database 20. The calculation unit 12 is a functional module that calculates characteristic values related to the discharge of the storage battery using the acquired storage battery data. The estimation unit 13 is a functional module that estimates the deterioration state of the storage battery based on the calculated characteristic values. The output unit 14 is a functional module that outputs processing results including the estimated deterioration state.

FIG. 2 is a diagram showing an example of a general hardware configuration of a computer 100 constituting the server 10. For example, the computer 100 comprises a processor (e.g., a CPU) 101 that executes an operating system, application programs, etc., a main memory unit 102 consisting of ROM and RAM, an auxiliary memory unit 103 consisting of a storage device such as a hard disk or flash memory, a communication control unit 104 consisting of a network card or wireless communication module, input devices 105 such as a keyboard and mouse, and an output device 106 such as a monitor.

Each functional module of server 10 is realized by loading a predetermined program onto processor 101 or main memory unit 102 and having processor 101 execute the program. Processor 101 operates communication control unit 104, input device 105, or output device 106 in accordance with the program, and reads and writes data in main memory unit 102 or auxiliary memory unit 103. Data or databases required for processing are stored in main memory unit 102 or auxiliary memory unit 103.

The server 10 is composed of at least one computer. When multiple computers are used, a single server 10 is logically constructed by connecting these computers via a communication network such as the Internet or an intranet.

The battery management program for causing a computer or computer system to function as the battery management system 1 or server 10 includes program code for causing the computer or computer system to function as an acquisition unit 11, a calculation unit 12, an estimation unit 13, and an output unit 14. This battery management program may be provided after being non-temporarily recorded on a tangible recording medium such as a CD-ROM, a DVD-ROM, or a semiconductor memory. Alternatively, the battery management program may be provided via a communications network as a data signal superimposed on a carrier wave. The provided battery management program is stored in, for example, the auxiliary memory unit 103. The processor 101 reads out the battery management program from the auxiliary memory unit 103 and executes it to realize each of the above-mentioned functional modules.

Before describing the processing by the battery management system 1 (server 10), we will describe several parameters that the calculation unit 12 uses to calculate characteristic values. As described above, the calculation unit 12 calculates characteristic values related to the discharge of the storage battery. In one example, the calculation unit 12 calculates characteristic values for each of a reference period and a target period. In this disclosure, the characteristic values in the reference period are also referred to as "reference characteristic values," and the characteristic values in the target period are also referred to as "target characteristic values."

In one example, the calculation unit 12 calculates the discharge time required for the closed circuit voltage (CCV) to reach the minimum drive voltage V _min from the voltage at full charge as the characteristic value. Hereinafter, the "discharge time required for the closed circuit voltage (CCV) to reach the minimum drive voltage V _min from the voltage at full charge" is simply referred to as the "discharge time". The calculation unit 12 may calculate the discharge time when the electric device 2 performs constant power discharge with the maximum discharge power P _max as the characteristic value. The maximum discharge power P _max indicates the power required to operate the electric device 2 at the maximum output. The minimum drive voltage V _min indicates the minimum voltage required to output the maximum discharge power P _max . Therefore, when the CCV in the electric device 2 falls below the minimum drive voltage V _min , the electric device 2 cannot operate at the maximum discharge power P _max . The maximum discharge power P _max and the minimum drive voltage V _min are values set for each electric device 2, and are recorded in the database 20 in association with at least one of the storage battery ID and the electric device ID, for example. The fully charged state refers to the point in time when sufficient electricity is stored in the storage battery, for example, when the SOC (State Of Charge) indicating the charge state of the storage battery is 100% or more.

In one example, in order to calculate the discharge time, the calculation unit 12 uses an OCV-SOC characteristic indicating _the relationship between the SOC and an open circuit voltage (OCV) and a DCR-SOC characteristic indicating the relationship between the SOC and a direct current resistance (DCR), in addition to the maximum discharge power P max and the minimum drive voltage V _min .

In this example, the calculation unit 12 performs calculations based on an equivalent circuit of the storage battery. The equivalent circuit includes a power source whose voltage changes in proportion to the SOC, and an internal resistance whose resistance value changes in proportion to the SOC. The calculations based on the equivalent circuit include an equation showing the OCV-SOC characteristics and an equation showing the DCR-SOC characteristics.

The OCV-SOC characteristic may be expressed by a linear equation (1) or a quadratic equation (2).
OCV = a _OCV + b _OCV · SOC ... (1)
OCV = a _OCV + b _OCV · SOC + c _OCV · SOC ² ... (2)
It can be said that a _OCV and b _OCV in the formula (1) are first-order approximation constants, and a _OCV , b _OCV , and c _OCV in the formula (2) are second-order approximation constants.

The DCR-SOC characteristic may be expressed by the linear equation (3) or the quadratic equation (4).
DCR = a _DCR + b _DCR · SOC ... (3)
DCR = a _DCR + b _DCR · SOC + c _DCR · SOC ² ... (4)
It can be said that _aDCR and _bDCR in equation (3) are first-order approximation constants, and _aDCR , _bDCR , and _cDCR in equation (4) are second-order approximation constants.

[System Operation]
An example of processing by the battery management system 1 (server 10) will be described with reference to Figures 3 to 8, and a battery management method according to this embodiment will be described. Figure 3 is a flowchart showing an example of processing by the battery management system. Figures 4 and 5 are diagrams showing examples of time-series data of SOC. Figure 6 is a diagram showing an example of a graph relating to OCV-SOC characteristics. Figure 7 is a diagram showing an example of a graph relating to DCR-SOC characteristics. Figure 8 is a diagram showing an example of a graph relating to a reference characteristic value and a target characteristic value.

In step S1, the acquisition unit 11 acquires data identification information. The data identification information is information used to read out storage battery data from the database 20. In one example, the data identification information includes at least one of a storage battery ID and an electric device ID, a maximum discharge power _Pmax , a minimum driving voltage _Vmin , a reference period, and a target period. For example, the reference period may correspond to a time when the storage battery is new, and the target period may correspond to a past time including the current time. The reference period and the target period are set by a predetermined time width. The time width may be a period during which multiple charging and discharging are expected to be performed, and may be set over multiple days, such as three days. The acquisition unit 11 may accept data identification information input by a user of the battery management system 1, or may automatically set the data identification information based on a given rule.

In step S2, the acquisition unit 11 acquires storage battery data corresponding to the reference period as reference data. The acquisition unit 11 reads from the database 20 a group of records of storage batteries that correspond to at least one of the storage battery ID and the electric device ID and the reference period.

In step S3, the calculation unit 12 calculates a reference characteristic value based on the reference data acquired in step S2 and the minimum drive voltage _Vmin .

In one example, the calculation unit 12 calculates moving averages of the measured voltage and measured current for each of a number of intervals set along the time axis. For example, if the time interval between records is 100 milliseconds, the calculation unit 12 sets the interval to 10 seconds and calculates the average value of 100 physical quantities within that interval every 10 seconds.

Next, the calculation unit 12 calculates the SOC(k) for each interval k for which the moving average has been obtained, using equation (5).
SOC(k)=1−Σ{I(k)/α}/W _bat ... (5)
Here, W _bat indicates the rated capacity of the storage battery, and I(k) indicates the measured current in section k. α is a coefficient for converting current (A) to capacity (Ah). If the length of the section is 10 seconds, α=360. Σ{I(k)/α} indicates the consumed capacity of the storage battery up to section k. As described above, in the database 20, the measured current when the storage battery is in a charging state is recorded as a positive value, and the measured current when the storage battery is in a discharging state is recorded as a negative value. Therefore, Σ{I(k)/α} can also be said to be the integrated capacity value of the storage battery up to section k.

Furthermore, the calculation unit 12 calculates the elapsed time ET for each section k based on each calculated SOC(k). The elapsed time ET indicates the time elapsed since the most recent SOC was 100%.

As a result, the calculation unit 12 obtains the measured current I(k), measured voltage MV(k), SOC(k), and elapsed time ET(k) for each of the n intervals k (k=1 to n). That is, the calculation unit 12 obtains time series data for the moving average of the measured current, the moving average of the measured voltage, the corresponding SOC, and the corresponding elapsed time. In one example, each record of the time series data obtained by the calculation unit 12 includes the moving average of the measured current, the moving average of the measured voltage, the corresponding SOC, and the corresponding elapsed time ET.

Then, the calculation unit 12 selects, from the obtained time series data, the time series data of the valid section used to calculate the characteristic value as valid time series data. In one example, the calculation unit 12 excludes the time series data of the invalid section that may be a cause of error in estimating the degradation state as invalid time series data, and selects the remaining time series data of the valid section as valid time series data.

In one example, the invalid section may include a time period from when the storage battery is fully charged to when a predetermined time Ta has elapsed. Hereinafter, this time period is also referred to as a first invalid section. The predetermined time Ta may be, for example, one hour.

Alternatively, the invalid section may include a time section from the point at which charging of a storage battery whose charging time is less than the threshold Tb is completed until the time equivalent to the charging time has elapsed. Hereinafter, this time section is also referred to as a second invalid section. The threshold Tb may be, for example, one hour.

Alternatively, the invalid section may include a time period from the end of charging that starts when the SOC is equal to or greater than the threshold value Ca% and ends when the SOC is less than 100% until the next time the storage battery is fully charged. Hereinafter, this time period is also referred to as the third invalid section. The threshold value Ca may be, for example, 90%.

An example of the third invalid section will be described with reference to FIG. 4. The horizontal axis of the graph shown in FIG. 4 indicates time t, and the vertical axis indicates SOC (%). In the example shown in FIG. 4, the threshold value Ca is 90%. At time t1, charging begins with an SOC of 90% or more, and at time t2, charging ends with an SOC of less than 100%. Thereafter, at time t3, the storage battery is fully charged. In this example, the calculation unit 12 identifies the time period from time t2 to time t3 as the third invalid section.

As another example of the third invalid section, the invalid section may include a time period from the end of charging that starts when the SOC is equal to or greater than a threshold value Ca%, when the SOC has increased by equal to or greater than Ci%, and when the SOC is less than 100%, until the next time the storage battery is fully charged. The threshold value Ci may be, for example, 3%.

Alternatively, the invalid section may include a time period from when the cumulative decrease in SOC reaches 100% without the SOC exceeding the threshold Cb% since the previous full charge to when the storage battery is next fully charged. The cumulative decrease in SOC refers to the integrated value of the SOC consumed, regardless of whether the storage battery is charged during discharging. Hereinafter, this time period is also referred to as the fourth invalid section. The threshold Cb may be, for example, 90%.

An example of the fourth invalid section will be described with reference to FIG. 5. The horizontal axis of the graph shown in FIG. 5 indicates time t, and the vertical axis indicates SOC (%). In the example shown in FIG. 5, the threshold Cb is 90%. The previous full charge is completed at time t4, and the next full charge is completed at time t5. The storage battery is charged several times between time t4 and time t5, but the SOC does not exceed 90% during this time period. At time t6, the cumulative decrease in SOC of the storage battery that was fully charged at time t4 reaches 100%. In this example, the calculation unit 12 identifies the time period from time t6 to time t5 as the fourth invalid section.

In one example, the calculation unit 12 excludes the time series data in at least one of the first to fourth invalid intervals as invalid time series data, and selects the time series data in the remaining valid intervals as valid time series data.

Next, the calculation unit 12 calculates the OCR-SOC characteristic and the DCR-SOC characteristic based on the effective time series data by a statistical method. For example, the calculation unit 12 calculates the OCR-SOC characteristic shown in formula (1) and the DCR-SOC characteristic shown in formula (4). As an example, the calculation unit 12 may use the Marquardt method, which is a nonlinear least square method, as the statistical method. The calculation unit 12 calculates the OCV-SOC characteristic and the DCR-SOC characteristic by using the Marquardt method to calculate the first-order approximation constants a _OCV and b _OCV and the second-order approximation constants a _DCR , b _DCR , and c _DCR that minimize the mean square error between the measured voltage MV and the theoretical voltage CV. In one example, the theoretical voltage CV in the section k is obtained by formula (6). Formula (6) can be said to represent the IV characteristic of the storage battery based on the equivalent circuit of the storage battery, and can also be said to be a calculation formula for the theoretical voltage.
CV(k)=OCV(k)-I(k)·DCR(k)={ _aOCV + _bOCV ·SOC(k)}-I(k)·{ _aDCR + _bDCR ·SOC(k)+ _cDCR ·SOC(k) ² }...(6)

Alternatively, the calculation unit 12 may use multivariate analysis as a statistical method. In one example, the calculation unit 12 may calculate the first-order approximation constants _aOCV and _bOCV and the second-order approximation constants _aDCR , _bDCR , and _cDCR based on the formula (6).

That is, first, the calculation unit 12 calculates the IV characteristics so as to minimize the mean square error between the measured voltage MV and the theoretical voltage CV using a statistical method such as the Marquardt method, multivariate analysis, etc. Next, the calculation unit 12 calculates the first-order approximation constants _aOCV and _bOCV and the second-order approximation constants _aDCR , _bDCR , and _cDCR based on the IV characteristics, thereby calculating the OCV-SOC characteristics and the DCR-SOC characteristics.

Then, the calculation unit 12 calculates the OCV and DCR at each time point in the valid time series data based on the calculated OCV-SOC characteristic and DCR-SOC characteristic. In one example, the calculation unit 12 calculates the corresponding OCV and DCR by substituting the SOC at each time point into the OCV-SOC characteristic shown in formula (1) and the DCR-SOC characteristic shown in formula (4).

Next, the calculation unit 12 calculates the CCV at each time point in the valid time-series data by solving the equation (7) showing the relationship between the OCV and DCR, the maximum discharge power _Pmax , and the CCV. That is, the calculation unit 12 calculates the corresponding CCV based on the OCV and DCR at each time point and the maximum discharge power _Pmax using the equation (8).
CCV=OCV- _Pmax /CCV·DCR (7)
CCV = (OCV + sqrt (OCV ² - 4 · P _max · DCR) / 2 ... (8)

The calculation unit 12 adds the calculated OCV, DCR, and CCV at each time point to each record of the valid time series data. Thus, in one example, each record of the valid time series data includes a moving average of the measured current, a moving average of the measured voltage, a corresponding SOC, a corresponding elapsed time ET, and a corresponding OCV, DCR, and CCV.

Next, the calculation unit 12 calculates the discharge time in the reference period as a reference characteristic value based on the CCV at each time point calculated by formula (8) and the corresponding elapsed time ET. The calculation unit 12 may obtain the elapsed time ET at the time point when the CCV reaches the minimum drive voltage V _min as the discharge time. Hereinafter, the elapsed time is represented as ET _Vmin . As described above, since there is a possibility that charging and discharging are performed multiple times in the reference period, the phenomenon in which the CCV reaches the minimum drive voltage V _min may occur multiple times in the reference period. In this case, the calculation unit 12 may calculate the statistical value of multiple elapsed times ET _Vmin as the discharge time. The statistical value may be, for example, an average value or a median value. Alternatively, regardless of the number of times the phenomenon in which the CCV reaches the minimum drive voltage V _min occurs in the reference period, the calculation unit 12 may calculate a regression equation indicating the relationship between the CCV and the elapsed time ET based on the pair of the CCV and the elapsed time ET at each time point, and apply the minimum drive voltage V _min to the regression equation to calculate the discharge time. The CCV calculated by the formula (8) is based on the OCV-SOC characteristic and the DCR-SOC characteristic in the reference period. Therefore, it can be said that the calculation unit 12 calculates the reference characteristic value based on the OCV-SOC characteristic and the DCR-SOC characteristic in the reference period in addition to the minimum drive voltage _Vmin .

In step S4, the acquisition unit 11 acquires storage battery data corresponding to the target period as target data. The acquisition unit 11 reads out a group of records of storage battery data corresponding to at least one of the storage battery ID and the electric device ID and the target period from the database 20.

In step S5, the calculation unit 12 calculates the target characteristic value based on the target data acquired in step S4 and the minimum driving voltage _Vmin . In one example, the calculation unit 12 calculates the target characteristic value in the same manner as the reference characteristic value. That is, the calculation unit 12 calculates the moving average of the measured voltage and the measured current for each predetermined interval. Then, the calculation unit 12 calculates the SOC for each interval. Then, the calculation unit 12 obtains time series data for the moving average of the measured current, the moving average of the measured voltage, the corresponding SOC, and the corresponding elapsed time ET during the target period. Then, the calculation unit 12 selects valid time series data from the obtained time series data.

Next, the calculation unit 12 calculates the IV characteristic for the target period using a statistical method based on the valid time series data, and calculates the first-order approximation constants a _OCV and b _OCV and the second-order approximation constants a _DCR , b _DCR , and c _DCR based on the IV characteristic, thereby calculating the OCV-SOC characteristic and the DCR-SOC characteristic.

Next, the calculation unit 12 calculates the CCV at each time point in the valid time series data based on the OCV and DCR at each time point obtained by the OCV-SOC characteristic and the DCR-SOC characteristic, and the maximum discharge power P _max . Then, the calculation unit 12 calculates the discharge time in the target period as the target characteristic value based on the calculated CCV at each time point and the corresponding elapsed time ET. As in the process for the reference period, the calculation unit 12 may calculate the statistical value of a plurality of elapsed times ET _Vmin as the discharge time, or may calculate the discharge time by a regression equation. As in the calculation of the reference characteristic value, the calculation unit 12 may calculate the target characteristic value based on the OCV-SOC characteristic and the DCR-SOC characteristic in the target period in addition to the minimum drive voltage V _min .

In step S6, the calculation unit 12 calculates the relationship between the reference characteristic value and the target characteristic value. In one example, the ratio between the reference characteristic value and the target characteristic value is calculated as the relationship between the reference characteristic value and the target characteristic value. Alternatively, the difference between the reference characteristic value and the target characteristic value may be calculated as the relationship between the reference characteristic value and the target characteristic value. The relationship between the reference characteristic value and the target characteristic value indicates how the characteristics of the storage battery have changed over time from the reference period to the target period. Therefore, the relationship between the two can be said to represent the SOH (State of Health), which indicates the deterioration state of the storage battery.

The calculation unit 12 may calculate a ratio relating to the discharge time as the relationship between the reference period and the target characteristic value. In one example, the calculation unit 12 calculates a ratio indicating the relationship between the discharge time in the reference period and the discharge time in the target period as the relationship between the reference characteristic value and the target characteristic value. In the present disclosure, this relationship is also referred to as "SOH-P."

In step S7, the estimation unit 13 estimates the degraded state of the storage battery based on the relationship between the reference characteristic value and the target characteristic value. In one example, the estimation unit 13 estimates the degraded state of the storage battery based on the ratio between the discharge time in the reference period and the discharge time in the target period. Alternatively, the estimation unit 13 may estimate the degraded state of the storage battery based on the difference between the reference characteristic value and the target characteristic value.

In step S8, the output unit 14 outputs the processing result. In one example, the output unit 14 outputs the deterioration state of the storage battery estimated by the estimation unit 13 as the processing result. Alternatively, the output unit 14 outputs the relationship between the reference characteristic value and the target characteristic value calculated by the calculation unit 12 as the processing result in addition to the deterioration state. As described above, the relationship may be the ratio between the reference characteristic value and the target characteristic value, or the difference between the reference characteristic value and the target characteristic value. The output unit 14 may output the deterioration state of the storage battery to another functional module in the battery management system 1 for subsequent processing in the battery management system 1. Alternatively, the output unit 14 may store the deterioration state of the storage battery in a predetermined storage device such as a memory or a database. Alternatively, the output unit 14 may display the deterioration state of the storage battery on a display device. Alternatively, the output unit 14 may transmit the deterioration state of the storage battery to another computer system.

With reference to Figures 6 to 8, an example of the characteristics of a storage battery in each of a reference period and a target period will be described. In this example, the reference period corresponds to a period during which the storage battery is new, and the target period corresponds to a period during which the storage battery is degraded. The calculation unit 12 calculates the OCV-SOC characteristics as shown in Figure 6, and calculates the DCR-SOC characteristics as shown in Figure 7. In Figure 6, graph 201 shows the OCV-SOC characteristics in the reference period, and graph 202 shows the OCV-SOC characteristics in the target period. In Figure 7, graph 211 shows the DCR-SOC characteristics in the reference period, and graph 212 shows the DCR-SOC characteristics in the target period.

FIG. 8 corresponds to FIG. 6 and FIG. 7. The horizontal axis indicates time (h), and the vertical axis indicates CCV (V). In FIG. 8, graph 221 indicates the discharge time in the reference period, and graph 222 indicates the discharge time in the target period. As can be seen from

graphs

221 and 222, as the storage battery deteriorates, the time it takes for the CCV to reach the minimum driving voltage _Vmin becomes shorter. If the ratio of the target characteristic value to the reference characteristic value is represented as SOH-P, the SOH-P gradually decreases from 1.0 (or 100%) as the storage battery deteriorates. In one example, when the SOH-P is 0.5 (or 50%) or less, there is a high probability that the product life of the storage battery is at the end. In this way, the deterioration state of the storage battery can be estimated based on the value of SOH-P, i.e., the relationship between the reference characteristic value and the target characteristic value.

[Modification]
Various examples of the present disclosure have been described in detail above. However, the present disclosure is not limited to the above examples. Various modifications of the present disclosure are possible without departing from the spirit and scope of the present disclosure.

The battery management system 1 may repeatedly execute the processes of steps S4 to S6 for each of the multiple target periods while repeatedly using the reference characteristic value calculated once in steps S2 and S3. That is, the calculation unit 12 may calculate the target characteristic value for each of the multiple target periods and calculate the relationship between the reference characteristic value and the target characteristic value. In this case, the calculation unit 12 may weight the calculated relationship for each target period based on a weighting parameter, and then calculate an average value of the relationship for the multiple target periods. This average value can also be said to be a weighted average value. The weighting parameter includes at least one of an approximate constant in the OCV-SOC characteristic, an approximate constant in the DCR-SOC characteristic, a total discharge amount in the target period, a time interval with respect to the timing of refilling the storage battery, and a rate of change of the target characteristic value. The rate of change of the target characteristic value indicates the rate of change from the target characteristic value in the previous target period. In step S7, the battery management system 1 may estimate the deterioration state of the storage battery based on the weighted average value.

In one example, one target period is regarded as one cycle, and multiple target periods for obtaining one weighted average value are set as n cycles, where n>1. In this case, a weighted average value of the relationship between the reference characteristic value and the target characteristic value in n cycles is calculated. When (n+1) or more target periods are set along the time axis, the battery management system 1 may calculate a weighted average value of the relationship between the reference characteristic value and the target characteristic value for each combination while shifting combinations of n consecutive target periods along the time axis, and calculate time series data of a weighted moving average of the relationship. In step S7, the battery management system 1 may estimate the degradation state of the storage battery based on the time series data.

If at least one of the one or more approximation constants of the OCV-SOC characteristic and the one or more approximation constants of the DCR-SOC characteristic used in calculating the reference characteristic value or the target characteristic value is outside a predetermined range, the estimation unit 13 may determine that the relationship between the reference characteristic value calculated using those characteristics and the target characteristic value is invalid. If the relationship between the reference characteristic value and the target characteristic value is invalid, the estimation unit 13 may not need to estimate the degradation state of the storage battery based on that relationship.

Furthermore, if the relationship between the reference characteristic value and the target characteristic value is determined to be invalid a predetermined number of times in succession, the estimation unit 13 may estimate that a sudden change has occurred in the characteristics of the storage battery. In this case, the output unit 14 may output, as a processing result, information indicating that the product life of the storage battery is at the end, based on the estimation.

The calculation unit 12 may calculate the OCV-SOC characteristics and the DCR-SOC characteristics using a method other than a statistical method. For example, the calculation unit 12 may calculate the OCV-SOC characteristics and the DCR-SOC characteristics using a Kalman filter each time measurement data is obtained.

A computer or device other than the server 10 may calculate the relationship between the reference characteristic value and the target characteristic value. For example, each BMU 3 may calculate the relationship between the reference characteristic value and the target characteristic value for the corresponding storage battery. In other words, the battery management system may be implemented in the BMU 3.

The BMU 3 may calculate a moving average of the measured voltage and current, and transmit storage battery data indicating these moving averages to the database 20. In this case, the amount of communication between the BMU 3 and the database 20 can be reduced, and the processing load on the server 10 can be reduced.

The battery management method executed by at least one processor is not limited to the above examples. For example, some of the steps or processes described above may be omitted, or the steps may be executed in a different order. Also, any two or more of the steps described above may be combined, or some of the steps may be modified or deleted. Alternatively, other steps may be executed in addition to the steps described above.

In this disclosure, the expression "at least one processor executes a first process, executes a second process, ... executes an nth process" or a corresponding expression indicates a concept including a case where the processor executing the n processes from the first process to the nth process changes midway. In other words, this expression indicates a concept including both a case where all n processes are executed by the same processor and a case where the processor changes among the n processes according to an arbitrary policy.

In this disclosure, when comparing the magnitude relationship of two numerical values, either of the two criteria "greater than or equal to" and "greater than" may be used, or either of the two criteria "less than or equal to" and "less than" may be used.

[Additional Notes]
As can be seen from the various examples above, the present disclosure includes the following aspects.
<Item 1>
an acquisition unit that acquires reference data indicating a state of the storage battery in a reference period and target data indicating a state of the storage battery in a target period after the reference period;
a calculation unit that calculates a characteristic value related to the discharge of the storage battery during the reference period as a reference characteristic value based on the reference data and a minimum driving voltage of an electrically-driven device that uses power supplied from the storage battery, and calculates a characteristic value related to the discharge of the storage battery during the target period as a target characteristic value based on the target data and the minimum driving voltage;
an estimation unit that estimates a degradation state of the storage battery based on a relationship between the reference characteristic value and the target characteristic value;
A battery management system comprising:
<Item 2>
The calculation unit,
A discharge time during the reference period during which the closed circuit voltage of the storage battery decreases from a fully charged voltage to the minimum driving voltage is calculated as the reference characteristic value;
Calculating the discharge time during the target period as the target characteristic value;
2. The battery management system according to item 1.
<Item 3>
The calculation unit calculates a ratio between the reference characteristic value and the target characteristic value as the relationship.
3. The battery management system according to

claim

1 or 2.
<Item 4>
The calculation unit,
Calculating an OCV-SOC characteristic indicating a relationship between a state of charge of the storage battery and an open circuit voltage of the storage battery during the reference period, and a DCR-SOC characteristic indicating a relationship between the state of charge of the storage battery and a direct current resistance of the storage battery during the reference period, based on the reference data;
Calculating the reference characteristic value based on the OCV-SOC characteristic and the DCR-SOC characteristic during the reference period in addition to the minimum driving voltage;
Calculating the OCV-SOC characteristic and the DCR-SOC characteristic during the target period based on the target data;
Calculating the target characteristic value based on the OCV-SOC characteristic and the DCR-SOC characteristic during the target period in addition to the minimum driving voltage;
4. The battery management system according to claim 1,
<Item 5>
The state of the storage battery indicated by each of the reference data and the target data includes at least a measured voltage and a measured current of the storage battery;
The calculation unit,
Based on the reference data, an IV characteristic which is a relationship between the measured current, the measured voltage, and the state of charge during the reference period is calculated by a statistical method, and based on the IV characteristic, the OCV-SOC characteristic and the DCR-SOC characteristic during the reference period are obtained;
Based on the target data, an IV characteristic which is a relationship between the measured current, the measured voltage, and the state of charge during the target period is calculated by the statistical method, and the OCV-SOC characteristic and the DCR-SOC characteristic during the target period are obtained based on the IV characteristic.
5. The battery management system according to item 4.
<Item 6>
1. A battery management method executed by a battery management system having at least one processor, comprising:
obtaining reference data indicating a state of the storage battery in a reference period and target data indicating a state of the storage battery in a target period after the reference period;
calculating a characteristic value related to the discharge of the storage battery during the reference period as a reference characteristic value based on the reference data and a minimum driving voltage of an electrically-driven device that uses power supplied from the storage battery, and calculating a characteristic value related to the discharge of the storage battery during the target period as a target characteristic value based on the target data and the minimum driving voltage;
estimating a degradation state of the storage battery based on a relationship between the reference characteristic value and the target characteristic value;
A battery management method comprising:
<Item 7>
obtaining reference data indicating a state of the storage battery in a reference period and target data indicating a state of the storage battery in a target period after the reference period;
calculating a characteristic value related to the discharge of the storage battery during the reference period as a reference characteristic value based on the reference data and a minimum driving voltage of an electrically-driven device that uses power supplied from the storage battery, and calculating a characteristic value related to the discharge of the storage battery during the target period as a target characteristic value based on the target data and the minimum driving voltage;
estimating a degradation state of the storage battery based on a relationship between the reference characteristic value and the target characteristic value;
A battery management program that causes a computer to execute the following.

According to items 1, 6, and 7, the degraded state of the storage battery is estimated from the relationship between the reference characteristic value calculated based on the reference data and the minimum driving voltage and the target characteristic value calculated based on the target data and the minimum driving voltage. By taking into account the minimum driving voltage, which is a parameter of the electrically-driven device to which power is supplied from the storage battery, it is possible to calculate the reference characteristic value and the target characteristic value that are in line with the actual use of the storage battery. Therefore, the degraded state of the storage battery can be accurately estimated based on the relationship between these two characteristic values.

The discharge time it takes for the closed circuit voltage of a storage battery to drop from the fully charged voltage to the minimum operating voltage clearly indicates the deterioration state of the storage battery. Therefore, according to item 2, by using the discharge time as a characteristic value, the deterioration state of the storage battery can be estimated more accurately.

According to item 3, by using the ratio between the reference characteristic value and the target characteristic value as the relationship between the two characteristic values, the deterioration state of the storage battery can be estimated more clearly.

According to item 4, by using the OCV-SOC characteristics and DCR-SOC characteristics in the reference period and the target period to calculate the characteristic values, the reference characteristic value and the target characteristic value can be accurately calculated.

According to item 5, by using statistical methods to obtain the OCV-SOC characteristics and DCR-SOC characteristics, these characteristics can be obtained with high accuracy from the measured values of the storage battery. By using the accurately obtained OCV-SOC characteristics and DCR-SOC characteristics to calculate the characteristic values, it is expected that the accuracy of both the calculation of the characteristic values and the deterioration state of the storage battery during the reference period and the target period can be improved.

1: Battery management system, 2: Electric device, 11: Acquisition unit, 12: Calculation unit, 13: Estimation unit, 14: Output unit.

Claims

an acquisition unit that acquires reference data indicating a state of the storage battery in a reference period and target data indicating a state of the storage battery in a target period after the reference period;
a calculation unit that calculates a characteristic value related to the discharge of the storage battery during the reference period as a reference characteristic value based on the reference data and a minimum driving voltage of an electrically-driven device that uses power supplied from the storage battery, and calculates a characteristic value related to the discharge of the storage battery during the target period as a target characteristic value based on the target data and the minimum driving voltage;
an estimation unit that estimates a degradation state of the storage battery based on a relationship between the reference characteristic value and the target characteristic value;
A battery management system comprising:
The calculation unit,
A discharge time during the reference period during which the closed circuit voltage of the storage battery decreases from a fully charged voltage to the minimum driving voltage is calculated as the reference characteristic value;
Calculating the discharge time during the target period as the target characteristic value;
The battery management system of claim 1 .
The calculation unit calculates a ratio between the reference characteristic value and the target characteristic value as the relationship.
The battery management system according to claim 1 .
The calculation unit,
Calculating an OCV-SOC characteristic indicating a relationship between a state of charge of the storage battery and an open circuit voltage of the storage battery during the reference period, and a DCR-SOC characteristic indicating a relationship between the state of charge of the storage battery and a direct current resistance of the storage battery during the reference period, based on the reference data;
Calculating the reference characteristic value based on the OCV-SOC characteristic and the DCR-SOC characteristic during the reference period in addition to the minimum driving voltage;
Calculating the OCV-SOC characteristic and the DCR-SOC characteristic during the target period based on the target data;
Calculating the target characteristic value based on the OCV-SOC characteristic and the DCR-SOC characteristic during the target period in addition to the minimum driving voltage;
The battery management system according to claim 1 .
The state of the storage battery indicated by each of the reference data and the target data includes at least a measured voltage and a measured current of the storage battery;
The calculation unit,
Based on the reference data, an IV characteristic which is a relationship between the measured current, the measured voltage, and the state of charge during the reference period is calculated by a statistical method, and based on the IV characteristic, the OCV-SOC characteristic and the DCR-SOC characteristic during the reference period are obtained;
Based on the target data, an IV characteristic which is a relationship between the measured current, the measured voltage, and the state of charge during the target period is calculated by the statistical method, and the OCV-SOC characteristic and the DCR-SOC characteristic during the target period are obtained based on the IV characteristic.
The battery management system according to claim 4.
1. A battery management method executed by a battery management system having at least one processor, comprising:
obtaining reference data indicating a state of the storage battery in a reference period and target data indicating a state of the storage battery in a target period after the reference period;
calculating a characteristic value related to the discharge of the storage battery during the reference period as a reference characteristic value based on the reference data and a minimum driving voltage of an electrically-driven device that uses power supplied from the storage battery, and calculating a characteristic value related to the discharge of the storage battery during the target period as a target characteristic value based on the target data and the minimum driving voltage;
estimating a degradation state of the storage battery based on a relationship between the reference characteristic value and the target characteristic value;
A battery management method comprising:
obtaining reference data indicating a state of the storage battery in a reference period and target data indicating a state of the storage battery in a target period after the reference period;
calculating a characteristic value related to the discharge of the storage battery during the reference period as a reference characteristic value based on the reference data and a minimum driving voltage of an electrically-driven device that uses power supplied from the storage battery, and calculating a characteristic value related to the discharge of the storage battery during the target period as a target characteristic value based on the target data and the minimum driving voltage;
estimating a degradation state of the storage battery based on a relationship between the reference characteristic value and the target characteristic value;
A battery management program that causes a computer to execute the following: