Estimation method, estimation device, and computer program

Abstract

Provided is an estimation method wherein a computer carries out a process for estimating capacities of a power storage element in accordance with a plurality of full discharge characteristics that are based on a partial charge / discharge profile of the power storage element, estimating the capacity range of the power storage element on the basis of each estimated capacity, and outputting the estimated capacity range.

Description

Estimation method, estimation device, and computer program

[0001] The present invention relates to an estimation method, an estimation device, and a computer program.

[0002] The use of energy storage devices is expanding to stabilize and effectively utilize the electricity generated by power generation facilities such as solar power generation facilities and wind power generation facilities. It is known that energy storage devices deteriorate with repeated charging and discharging, and their capacity gradually decreases.

[0003] Patent document 1 discloses a technology that can estimate the overall discharge characteristics of a storage element at a predetermined point after the start of operation without stopping the operation of the system in which the storage element is installed, and diagnose the full charge capacity of the storage element based on the overall discharge characteristics.

[0004] Japanese Patent Application Laid-Open No. 2023-010325

[0005] The technology of Patent Document 1 does not estimate the capacity range of the storage element.

[0006] The present disclosure aims to provide a technique capable of estimating the capacity range of a storage element.

[0007] An estimation method according to one aspect of the present disclosure includes a computer executing a process to estimate the capacity of a storage element according to a plurality of overall discharge characteristics based on a partial charge / discharge profile of the storage element, estimate a capacity range of the storage element based on each estimated capacity, and output the estimated capacity range.

[0008] According to the present disclosure, the capacity range of a storage element can be estimated.

[0009] 1 is a diagram illustrating an overview of a remote monitoring system. FIG. 1 is a diagram illustrating an example of the configuration of a container of a power storage system. FIG. 2 is a diagram illustrating an example of an electrical connection configuration of a power storage system. FIG. 3 is a block diagram illustrating an example of the configuration of a remote monitoring system. FIG. 4 is a schematic diagram illustrating an example of a partial charge / discharge profile and an overall discharge characteristic. FIG. 5 is a diagram illustrating an example of a reliability distribution map. FIG. 6 is a diagram illustrating two partial charge / discharge profiles with different widths of the electricity quantity-voltage region and an example of a candidate overall discharge characteristic based on each partial charge / discharge profile. FIG. 7 is a diagram illustrating a change in capacity range due to a change in the partial charge / discharge profile. FIG. 8 is a flowchart illustrating an example of a processing procedure executed by an estimation device. FIG. 9 is a flowchart illustrating an example of a processing procedure executed by an estimation device. FIG. 10 is a schematic diagram illustrating an example of a result screen showing an estimation result. FIG. 11 is a schematic diagram illustrating an example of a display of detailed information. FIG. 12 is a flowchart illustrating an example of a processing procedure executed by an estimation device of a second embodiment.

[0010] (1) In an estimation method according to one aspect of the present disclosure, a computer executes a process of estimating the capacity of a storage element according to a plurality of overall discharge characteristics based on a partial charge / discharge profile of the storage element, estimating a capacity range of the storage element based on each estimated capacity, and outputting the estimated capacity range.

[0011] In this specification, the term "energy storage element" refers to any element that stores electricity. The smallest unit of a energy storage element is called a storage cell. A "partial charge / discharge profile" refers to, for example, a portion of a charge / discharge profile between an upper limit voltage and a lower limit voltage set for a energy storage element, or a portion of a charge / discharge profile between an upper limit SOC (State of Charge) and a lower limit SOC set for a energy storage element. The term "partial" is used to distinguish the partial charge / discharge profile from the overall discharge characteristic. An "overall discharge characteristic" refers to, for example, a characteristic represented by a continuous discharge curve between an upper limit voltage and a lower limit voltage set for a energy storage element, or a characteristic represented by a continuous discharge curve between an upper limit SOC and a lower limit SOC set for a energy storage element. The "capacity of the energy storage element" refers to the full charge capacity of the energy storage element, which is the total amount of electricity generated when the energy storage element is discharged from a fully charged state (SOC 100%) to an SOC of 0% at a constant current value. The capacity of the storage element can be calculated by subtracting the capacity (electrical quantity) corresponding to the upper limit voltage from the capacity (electrical quantity) corresponding to the lower limit voltage of the overall discharge characteristic.

[0012] The present applicant has proposed a technology for estimating the overall discharge characteristics of a storage element based on operational data of a storage system in which the storage element is installed, and diagnosing the full charge capacity based on the estimated overall discharge characteristics (Japanese Patent Application No. 2021-114387, etc.). In this technology, a partial charge / discharge profile of the storage element is generated based on the operational data, and one overall discharge characteristic is estimated based on the generated partial charge / discharge profile. One full charge capacity is calculated from the estimated one overall discharge characteristic.

[0013] Operational data collected from an energy storage system may not be suitable for capacity estimation depending on the quality of the data and the analysis method used for capacity estimation. For example, operational data in cases where a storage element has not been charged or discharged for a long period of time, or where there is a bias in the voltage range or state of charge (SOC) range during charging or discharging, is likely to be unsuitable for capacity estimation. If operational data unsuitable for capacity estimation is used, the accuracy of the estimation result will be lower than if operational data suitable for capacity estimation is used.

[0014] In the estimation of the overall discharge characteristic in the above technology, at least one of the positive and negative single-electrode characteristics of the energy storage element is adjusted so that the difference between the positive and negative single-electrode characteristics approaches (approximates) the partial charge / discharge profile. The optimal (likely) overall discharge characteristic is estimated from the difference between the positive and negative single-electrode characteristics after adjustment to achieve the closest approximation. That is, one overall discharge characteristic is ultimately determined from among many candidate overall discharge characteristics obtained by adjusting the positive and negative single-electrode characteristics. The operational data and the state of the partial charge / discharge profile based on the operational data affect the number of candidate overall discharge characteristics. The greater the number of candidate overall discharge characteristics, the more difficult it is to uniquely determine a solution, and the lower the accuracy of the estimation. If only a capacity value is presented as the estimation result, the user cannot grasp the accuracy of the presented capacity value.

[0015] According to the estimation method (1) above, it is possible to provide an estimated result of the capacity range of the storage element, which leads to an understanding of the accuracy of the output of the estimated result and improves the reliability of the output result. The capacity range depends on the number of candidates for the overall discharge characteristic based on the charge / discharge profile. The more candidate overall discharge characteristics there are, the greater the capacity calculated from the overall discharge characteristic and the wider the capacity range. As mentioned above, the greater the number of candidate overall discharge characteristics, the lower the accuracy of the estimation. The accuracy of the output of the estimated result can be recognized from the capacity range.

[0016] Since the reliability of the capacity estimation can be recognized, the user can decide whether to adopt the estimation result of this method depending on the reliability, improving convenience. For example, when the capacity range is wide, other measurement results or capacities obtained by other calculation methods can be used instead, and when the capacity range is narrow, the result of this method is emphasized. This makes it easier to link with other capacity information.

[0017] (2) In the estimation method of (1) above, reliability information indicating the reliability of the estimation of each capacity may be derived, and the derived reliability information may be output.

[0018] According to the estimation method (2) above, the reliability of the capacity estimation can be quantified, so that the certainty of the output of the estimation result can be provided more clearly.

[0019] (3) In the estimation method of (2), the reliability may be derived based on a difference between the charge / discharge profile and the overall discharge characteristic fitted to the charge / discharge profile.

[0020] According to the estimation method (3) above, the reliability can be calculated efficiently and accurately based on the shape error between the charge / discharge profile and the overall discharge characteristics.

[0021] (4) In the estimation method of (2) above, the reliability may be derived based on the occurrence probability of internal parameters of a mathematical model that calculates the overall discharge characteristics in the charge / discharge profile based on measured values ​​including the current and voltage of the storage element.

[0022] According to the estimation method (4) above, the reliability can be calculated with high accuracy using the occurrence probability of the internal parameters of the mathematical model by a technique such as the MCMC (Markov Chain Monte Carlo) method.

[0023] (5) In the estimation method according to any one of (2) to (4) above, the reliability information may include a graph showing a distribution of the reliability or a relationship between the capacity and the reliability.

[0024] According to the estimation method (5) above, the distribution of reliability and reliability for each capacity can be visually and clearly recognized, thereby improving user convenience.

[0025] (6) In any one of the estimation methods (2) to (5) above, a capacity range in which the reliability satisfies a predetermined requirement may be estimated from the capacity ranges corresponding to each capacity estimated from the plurality of overall discharge characteristics based on the charge / discharge profile.

[0026] According to the estimation method (6), the amount of data output can be reduced, making it easier to understand the estimation results. By taking the reliability state into consideration, a more likely capacity range can be appropriately estimated.

[0027] (7) In any one of the estimation methods (1) to (6) above, an optimal capacity corresponding to the optimal overall discharge characteristic among the plurality of overall discharge characteristics may be obtained, and the obtained optimal capacity may be output in correspondence with the capacity range.

[0028] According to the estimation method (7) above, the optimum capacity and capacity range based on the charge / discharge profile can be provided in an integrated manner, so that the capacity of the storage element can be recognized more accurately.

[0029] (8) In any one of the estimation methods (1) to (7) above, a screen may be output that displays the capacity range using a rod-shaped object whose length changes depending on the width of the capacity range.

[0030] According to the estimation method (8) above, the estimated capacity range can be easily understood at a glance, improving user convenience.

[0031] (9) In the estimation method of (8) above, an optimal capacity corresponding to the optimal overall discharge characteristic among the plurality of overall discharge characteristics may be obtained, and an object indicating the optimal capacity may be superimposed and displayed on the rod-shaped object.

[0032] According to the estimation method (9) above, the optimum capacity and capacity range based on the charge / discharge profile can be visually presented together, improving the visibility of the estimation result.

[0033] (10) In the estimation method of (8) or (9) above, a screen may be output that displays a plurality of the rod-shaped objects corresponding to the capacity ranges based on the charge / discharge profile for a plurality of periods.

[0034] According to the estimation method (10) above, the time series change in the capacity range can be recognized at a glance, and the capacity range for each period can be easily compared.

[0035] (11) In any one of the estimation methods (1) to (10) above, if the optimal capacity corresponding to the optimal overall discharge characteristic among the plurality of overall discharge characteristics is less than a predetermined value and the width of the capacity range is less than a predetermined value, warning information may be output.

[0036] According to the estimation method of (11) above, when an estimation result indicating a capacity decrease of the storage element is obtained and the estimation result is somewhat reliable, warning information can be output. Since the warning information can be output taking into account the reliability of the estimation result, the reliability of the warning information can be improved.

[0037] (12) An estimation device according to one aspect of the present disclosure includes a processing unit that executes a process of estimating the capacity of a storage element according to a plurality of overall discharge characteristics based on a partial charge / discharge profile of the storage element, estimating a capacity range of the storage element based on each estimated capacity, and outputting the estimated capacity range.

[0038] (13) A computer program according to one aspect of the present disclosure causes a computer to execute a process of estimating the capacity of a storage element according to a plurality of overall discharge characteristics based on a partial charge / discharge profile of the storage element, estimating a capacity range of the storage element based on each estimated capacity, and outputting the estimated capacity range.

[0039] The present disclosure will be specifically described with reference to the drawings showing embodiments thereof.

[0040] (First embodiment) Fig. 1 is a diagram showing an overview of a remote monitoring system 100. The remote monitoring system 100 enables remote access to information related to a power storage element 51 included in a power storage system 5. The remote monitoring system 100 includes an estimation device 1 and a user device 3. The estimation device 1 and the user device 3 are communicably connected via a network N. The number of power storage systems 5 may be one or three or more. The estimation device 1 may be provided in any of the power storage systems 5.

[0041] The estimation device 1 is an information processing device capable of various information processing and information transmission and reception, such as a server computer, a personal computer, a quantum computer, etc. The estimation device 1 acquires measurement data related to the energy storage elements 51 transmitted from each energy storage system 5 that is the target of remote monitoring. The estimation device 1 performs various analysis processes, including estimation of the energy storage capacity of the energy storage elements 51, based on the measurement data, and provides the analysis results to the user via the user device 3.

[0042] The user device 3 is an information processing terminal device capable of performing various information processes and transmitting and receiving information, such as a personal computer, a smartphone, or a tablet terminal. The user device 3 is used by an operator, such as a manager or maintenance technician, of the energy storage system 5, who is an example of a user. The user device 3 can display the analysis results provided by the estimation device 1.

[0043] The power storage system 5 is, for example, an ESS (Energy Storage System) and is used in power generation systems such as solar power generation systems, wind power generation systems, hydroelectric power generation systems, biomass power generation systems, geothermal power generation systems, and thermal power generation systems. The power storage system 5 may include a power supply-related device 52 such as a power conditioner in addition to a large number of power storage elements 51. The power storage system 5 stores power supplied from the power generation system and supplies the stored power to other power consumption equipment (loads) or a power grid.

[0044] The power storage system 5 may be used for other purposes, for example, by being connected to a power grid (grid interconnection) and used to suppress voltage fluctuations and frequency fluctuations in the power grid, or by being installed on the premises of a power consumer such as a factory and used for energy management such as a business continuity plan (BCP) measure or peak shifting, or for power trading in the power market. The power storage system 5 may be used together with a power converter such as a converter or inverter in a backup power system (emergency power system). The power storage system 5 is not limited to industrial applications and may also be for home use.

[0045] Each of the power storage systems 5 is equipped with a communication device 6 for transmitting measurement data related to the power storage elements 51 to the estimation device 1, or is connected to the communication device 6. The communication device 6 transmits data to the estimation device 1 via the network N.

[0046] The network N is a wired or wireless network including, for example, the Internet, a carrier network that realizes wireless communication according to a predetermined mobile communication standard, a general optical fiber line, etc. The network N may also include a local network for the manufacturer or maintenance company of the energy storage element 51.

[0047] FIG. 2 shows an example of the configuration of a container C of the power storage system 5. The container C of the power storage system 5 houses multiple (e.g., nine) power storage panels. Although not shown, the power storage system 5 may be configured by omitting the container C and installing multiple power storage panels outdoors. Each power storage panel may include, for example, three banks. Each bank is configured by electrically connecting multiple power storage modules in series. A power storage module has multiple power storage cells connected in series. The three banks are connected in parallel to each other. A configuration in which multiple banks are connected in parallel is also called a domain. When the required output voltage is low (when the number of power storage modules connected in series can be reduced), the power storage panel may include, for example, six banks. The number of banks included in the power storage panel and the number of power storage modules included in each bank are selected arbitrarily. The power storage panel in FIG. 2 includes one domain, but may also include multiple domains.

[0048] The energy storage module is configured by connecting multiple energy storage cells in series. In one example, the energy storage cells are lithium-ion secondary battery cells. Alternatively, the energy storage cells may be battery cells such as all-solid-state batteries, lead batteries, redox flow batteries, zinc-air batteries, alkaline manganese batteries, lithium-sulfur batteries, sodium-sulfur batteries, silver-zinc oxide batteries, nickel-metal hydride batteries, and molten salt thermal batteries, or may be capacitors. The number of energy storage cells constituting the energy storage module can be selected arbitrarily.

[0049] Fig. 3 shows an example of an electrical connection configuration of the power storage system 5. Fig. 3 shows the electrical connection configuration of one power storage board included in the power storage system 5. The power storage system 5 includes a plurality of banks, a domain management device M, and a communication device 6. The domain management device M and the communication device 6 may be housed in a control board separate from the power storage board, which is built into the container C. In the example of Fig. 3 , the power storage board includes three banks: bank #1, bank #2, and bank #3.

[0050] Each of the banks #1, #2, and #3 includes a bank management device 53, a control board 54 provided in each power storage module, and the like.

[0051] Each bank is connected to the outside (such as a power supply source or a power supply destination) via a power circuit. For example, the power supply source to the bank is a power generation facility, and the power supply destination of the bank is a load. A power converter (not shown) may be provided between the bank and the power supply source or the power supply destination. The bank stores (charges) power supplied from the power supply source and supplies (discharges) the stored power to the external power supply destination.

[0052] The control board 54 acquires measurement data related to each storage cell of the energy storage module through various sensors (not shown). The sensors provided in the bank include, for example, a current sensor that measures the current flowing through the storage cell, a voltage sensor that measures the voltage of the storage cell, and a temperature sensor that measures the temperature of the storage cell. The measurement data can be acquired repeatedly at appropriate intervals, such as every 0.1 second, 0.5 seconds, or 1 second. The control board 54 has a communication function that complies with a predetermined communication protocol, and outputs the acquired measurement data, including the current, voltage, and temperature of the storage cell, to the bank management device 53.

[0053] The bank management device 53 is a device for monitoring the state of the bank. The bank management device 53 acquires measurement data including the current, voltage, and temperature of the storage cells, and calculates the SOC of the bank based on the acquired measurement data, thereby monitoring the state of the bank at each time.

[0054] The domain management device M is a device for monitoring the status of a domain (an entire bank). The domain management device M is communicably connected to the bank management device 53 of each bank. The domain management device M aggregates measurement data from the bank management device 53 of each bank belonging to the domain. An existing communication standard such as CAN (Controller Area Network) is used for communication between the domain management device M and each bank management device 53. Alternatively, communication standards such as LIN (Local Interconnect Network), ECHONET (registered trademark), and ECHONET Light (registered trademark) may be used.

[0055] The communication device 6 securely transmits data to the estimation device 1 wirelessly or via a wired connection. The communication device 6 may be, for example, a network interface card. The domain management device M transmits measurement data of the energy storage elements 51 acquired from each bank management device 53 to the estimation device 1 via the communication device 6. The domain management device M or the communication device 6 may hold measurement data for a predetermined period of time and transmit the measurement data to the estimation device 1 at predetermined time intervals.

[0056] The estimation device 1 collects and stores the measurement data received from each power storage system 5. The measurement data transmitted to the estimation device 1 may be associated with identification information of the power storage elements 51, connection configuration data, and the like. The estimation device 1 can identify which power storage system 5 the data transmitted from the communication device 6 is related to, and store the data in association with related information.

[0057] 4 is a block diagram showing an example configuration of the remote monitoring system 100. The estimation device 1 includes a processing unit 11, a storage unit 12, and a communication unit 13. The estimation device 1 may be a single computer, or may be a computer system configured with multiple computers and peripheral devices. The estimation device 1 may be a virtual machine whose entity is virtualized, or may be a cloud.

[0058] The processing unit 11 includes one or more processors such as a central processing unit (CPU), a microprocessing unit (MPU), or a graphics processing unit (GPU). The processing unit 11 includes a memory serving as a temporary storage medium, such as a static random access memory (SRAM) or a dynamic random access memory (DRAM). The processing unit 11 may include functions such as a timer that measures the elapsed time from when a measurement start instruction is given to when a measurement end instruction is given, a counter that counts numbers, and a clock that outputs date and time information. The CPU and other components included in the processing unit 11 read and execute various computer programs stored in the storage unit 12 to control each hardware component and cause the entire device to function as the estimation device of the present disclosure. The processing unit 11 may be implemented as software, or part or all of it may be implemented as hardware, such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

[0059] The storage unit 12 includes a non-volatile storage device such as a hard disk or a flash memory. The storage unit 12 may be separate from the estimation device 1 and may be one or more external storage devices connected externally. The storage unit 12 stores various computer programs and data referenced by the processing unit 11. The storage unit 12 of this embodiment stores a program 121 for causing a computer to execute processing related to estimating the capacity range of the storage element 51, and a storage element database (DB) 122 for storing various information related to the storage element 51. The program 121 may include a program for realizing a web server function. The program 121 enables the processing unit 11 to present various information to the user device 3 via a web page and to perform a web server function of receiving information from the user.

[0060] A computer program (program product) including the program 121 may be provided by a non-transitory recording medium 1A on which the computer program is readably recorded. The recording medium 1A is a portable memory such as a CD-ROM, a USB memory, or an SD (Secure Digital) card. The processing unit 11 reads the desired computer program from the recording medium 1A using a reading device (not shown) and stores the read computer program in the storage unit 12. Alternatively, the computer program may be provided via communication. The program 121 may be a single computer program or may be composed of multiple computer programs. The program 121 may also be executed on a single computer or may be executed cooperatively by multiple computers.

[0061] The energy storage element DB 122 stores various information related to the capacity estimation process. The energy storage element DB 122 stores, for example, measurement data received from the energy storage system 5, formulas used in the capacity estimation process, table data, estimation results, etc. Each time the processing unit 11 receives measurement data including identification information, current, voltage, temperature, etc. of the energy storage element 51 transmitted from the energy storage system 5, the processing unit 11 stores the received measurement data in chronological order in the energy storage element DB 122. Each time the processing unit 11 executes the capacity estimation process, the processing unit 11 stores the obtained estimation result in the energy storage element DB 122.

[0062] The communication unit 13 includes a communication device that realizes communication via the network N. The processing unit 11 transmits and receives data to and from the user device 3 through the communication unit 13.

[0063] The configuration of the estimation device 1 is not limited to the above example, and may include, for example, a display unit that displays an image, an operation unit that accepts user operations, and the like.

[0064] The user device 3 includes a processing unit 31 , a storage unit 32 , a communication unit 33 , a display unit 34 , and an operation unit 35 .

[0065] The processing unit 31 includes one or more processors such as a CPU or a GPU. The storage unit 32 includes a non-volatile storage device such as a hard disk or a flash memory. The storage unit 32 stores various computer programs and data referenced by the processing unit 31. The computer programs stored in the storage unit 32 include a program 321. The program 321 may include a web browser function. By executing the program 321, the processing unit 31 accesses the estimation device 1 via the web browser and executes processing related to the output of various information including the capacity estimation results of the storage element 51.

[0066] The communication unit 33 includes a communication device that realizes communication via the network N. The processing unit 31 transmits and receives data to and from the estimation device 1 via the communication unit 33.

[0067] The display unit 34 includes a display device such as a liquid crystal display, an organic EL (Electro Luminescence) display, etc. The display unit 34 displays various information including the estimation result of the capacity range according to instructions from the processing unit 31.

[0068] The operation unit 35 is an interface that accepts user operations. The operation unit 35 includes, for example, a keyboard, a mouse, a touch panel device with a built-in display, a speaker, a microphone, etc. The operation unit 35 accepts operation input from the user and sends a control signal corresponding to the operation content to the processing unit 31.

[0069] The method of estimating the capacity range of the storage element 51 executed by the estimation device 1 will be described below.

[0070] The estimation device 1 generates a partial charge / discharge profile based on time-series data of measurement data including the current and voltage of the storage element 51, and estimates an optimal (likely) overall discharge characteristic of the storage element 51 (hereinafter also referred to as the optimal overall discharge characteristic) corresponding to the generated partial charge / discharge profile. By calculating the capacity corresponding to the optimal overall discharge characteristic, an optimal (likely) capacity (hereinafter also referred to as the optimal capacity) for the storage element 51 can be obtained. The generation of the partial charge / discharge profile and the estimation of the overall discharge characteristic can be performed using known techniques (for example, the technique described in Japanese Patent Application No. 2021-114387).

[0071] FIG. 5 is a schematic diagram showing an example of a partial charge / discharge profile and an overall discharge characteristic. In FIG. 5, the horizontal axis represents the quantity of electricity (Ah), and the vertical axis represents the voltage or potential (V). In FIG. 5, S represents the partial charge / discharge profile (quantity of electricity-voltage plot), and curve Qa represents the overall discharge characteristic (quantity of electricity (capacity)-voltage characteristic). Alternatively, the partial charge / discharge profile may be an SOC-voltage plot, and the overall discharge characteristic may be an SOC-voltage characteristic. FIG. 5 also shows a curve Px representing the positive electrode single-electrode characteristic and a curve Nx representing the negative electrode single-electrode characteristic used to estimate the overall discharge characteristic.

[0072] Although detailed description is omitted, the overall discharge characteristic is obtained by calculating the difference between the potential of the positive single-electrode characteristic of the energy storage element 51 and the potential of the negative single-electrode characteristic. The positive single-electrode characteristic and the negative single-electrode characteristic depend on internal state parameters such as the positive electrode effectiveness (utilization rate), charge reserve amount, discharge reserve amount, and discharge start position of the positive electrode. By optimizing the internal state parameters so that the overall discharge characteristic approaches the partial charge / discharge profile, an optimal overall discharge characteristic corresponding to the optimized internal state parameters can be obtained.

[0073] In optimizing the internal state parameter, the internal state parameter is adjusted so as to minimize a difference between the charge / discharge profile and the overall discharge characteristic fitted to the charge / discharge profile (hereinafter also referred to as a fitting error). The fitting error may be expressed as, for example, the sum of squares or a linear sum of the voltage difference between the voltage of a partial charge / discharge profile corresponding to a specific amount of electricity and the voltage of the overall discharge characteristic.

[0074] The estimation device 1 of this embodiment stores the entire history of the iterative calculations performed in optimizing the internal state quantity parameters in the energy storage element DB 122. The information stored in the energy storage element DB 122 includes, for example, all candidate overall discharge characteristics estimated by the iterative calculations and fitting errors corresponding to each candidate overall discharge characteristic. The candidate overall discharge characteristics (hereinafter also referred to as candidate overall discharge characteristics) refer to overall discharge characteristics that can be the optimal overall discharge characteristics based on the partial charge / discharge profile.

[0075] The estimation device 1 derives the capacity (Ah) corresponding to each of the multiple candidate overall discharge characteristics and the reliability of the estimation based on the multiple stored candidate overall discharge characteristics and the fitting error corresponding to each candidate overall discharge characteristic.

[0076] The reliability of the estimation is information indicating the accuracy of the capacity estimation. The accuracy of the capacity estimation is synonymous with the accuracy of the estimation of the candidate overall discharge characteristics that are the subject of the capacity calculation. The reliability of the estimation is calculated, for example, based on the fitting error. The smaller the fitting error, the larger the calculated value of the reliability of the estimation. The reliability of the estimation may be calculated, for example, using the following formula:

[0077]

[0078] where l is the confidence of the estimate and d is the fitting error.

[0079] As a method for calculating the reliability, a likelihood function L may be defined as shown in the following equation, and a probability distribution of the full charge / discharge capacity (FCC) of the energy storage element may be calculated using Bayes' theorem and the Markov Chain Monte Carlo (MCMC) method. In this method, the error between the partial charge / discharge profile (OCV, Ah) obtained from the observation results and the estimated partial charge / discharge profile is converted into a reliability, which is the likelihood function L or probability distribution p(FCC|Ah, OCV) expressed by the following equation, and the reliability can be calculated together with the estimated FCC result. Note that the estimated charge / discharge profile here refers to a charge / discharge profile extracted from the overall discharge characteristics and falling within the same capacity range as the partial charge / discharge profile obtained from the observation results, for comparison with the observation results. L(θ|Ah, OCV) ∝ p(OCV|Ah, θ) p(θ|Ah, OCV) ∝ L(θ|Ah, OCV) p(θ) = p(OCV|Ah, θ) p(θ) FCC = f(θ) In the formula, L is a likelihood function, Ah is the capacity of the storage element, FCC is the full charge / discharge capacity of the storage element, OCV is the open circuit voltage of the storage element, and θ is the internal state quantity of the storage element.

[0080] Based on the capacity corresponding to each candidate overall discharge characteristic and the reliability of the estimation, the estimation device 1 generates a reliability distribution map showing the distribution of the reliability of the estimation for the energy storage elements 51. The reliability distribution map is an example of reliability information showing the reliability of the estimation.

[0081] Fig. 6 shows an example of a reliability distribution diagram. The reliability distribution diagram can be generated by plotting the capacity and the estimated reliability corresponding to each candidate overall discharge characteristic on a two-dimensional coordinate system with the horizontal axis representing capacity (Ah) and the vertical axis representing the estimated reliability. In Fig. 6, the plot of the reliability is represented by a cross (x).

[0082] The estimation device 1 may derive a reliability curve (approximation line) indicating the relationship between capacity and reliability or a reliability function (approximation formula) indicating the reliability curve based on the generated reliability distribution map. In Fig. 6, a curve M represents the reliability curve and the reliability function. The reliability curve and the reliability function are other examples of reliability information indicating the reliability of the estimation.

[0083] For example, the estimation device 1 divides the generated reliability distribution map into divided regions obtained by dividing the capacity by a predetermined capacity width, and identifies the maximum reliability value within each divided region. The estimation device 1 derives an approximation line for the plot of the maximum reliability value for each divided region identified, and an approximation function that indicates the approximation line. The approximation method is not particularly limited, and an appropriate function may be used for approximation. The reliability curve and reliability function represent the likelihood of occurrence of the estimated capacity. The capacity at which the reliability function shows a peak value corresponds to the optimal capacity.

[0084] Based on the capacities corresponding to the respective candidate overall discharge characteristics, the estimation device 1 derives an estimated capacity range for the energy storage element 51. The capacity range can be a capacity band whose upper limit is the maximum value of the capacities corresponding to the respective candidate overall discharge characteristics and whose lower limit is the minimum value of the capacities.

[0085] The capacity range estimated for the storage element 51 may be a portion of the entire capacity range defined by the maximum and minimum estimated capacities, and may correspond to a section that satisfies a predetermined reliability requirement. For example, within the region enclosed by the reliability curve and the x-axis (capacity axis) shown in FIG. 6 , an X% confidence interval is defined as a capacity range in which the ratio of the area of ​​a specific capacity range to the area of ​​the entire capacity range (area of ​​the specific capacity range / area of ​​the entire capacity range) exceeds X%. In FIG. 6 , the hatched area represents the area corresponding to the specific capacity range. The estimation device 1 can derive an X% confidence interval from the entire capacity range as a final estimation result. The confidence interval to be extracted can be set in advance depending on the purpose of the estimation. The estimation device 1 may be configured to accept a user's setting or change of the confidence interval when performing the estimation process.

[0086] The estimation device 1 executes the above-described estimation process for each storage element 51 and stores the obtained estimation results in the storage element DB 122. The storage element DB 122 stores information such as identification information of the storage element 51, an estimation target period, a generated partial charge / discharge profile, an optimal overall discharge characteristic, an optimal capacity, a capacity range, a capacity corresponding to each candidate overall discharge characteristic, a reliability corresponding to each candidate overall discharge characteristic, a reliability distribution map, a reliability curve, and a reliability function, in association with each other, using an estimation ID as a key, for example.

[0087] The estimation device 1 outputs, as an estimation result, a capacity range along with the optimum capacity of the storage element 51. The output estimation result may include reliability information, a partial charge / discharge profile, an optimum overall discharge characteristic, reliability, and the like.

[0088] It is expected that the capacity range of the storage element 51 and the reliability of the estimation will change depending on the state of the partial charge / discharge profile. A specific example will be described below.

[0089] 7 shows an example of two partial charge-discharge profiles with different widths of the electrical quantity-voltage region and candidate overall discharge characteristics based on each partial charge-discharge profile. In FIG. 7, the horizontal axis represents capacity (Ah) and the vertical axis represents voltage (V).

[0090] The upper diagram in Fig. 7 shows a partial charge / discharge profile composed of the electric quantity-voltage plots for only region 1 of the electric quantity-voltage regions of the storage element divided into regions 1 to 4, and a candidate overall discharge characteristic based on the partial charge / discharge profile. The lower diagram in Fig. 7 shows a partial charge / discharge profile composed of the electric quantity-voltage plots across regions 1 to 4, and a candidate overall discharge characteristic based on the partial charge / discharge profile. Regions 1 to 4 are divided into approximately the same electric quantity width, and the electric quantity value increases from region 1 to region 4.

[0091] As conceptually shown in FIG. 7 , when the width of the electrical quantity-voltage region of the partial charge / discharge profile is short and information on the partial charge / discharge profile is insufficient, as in the partial charge / discharge profile corresponding to region 1, there are a relatively large number of candidate overall discharge characteristics that can be estimated from the partial charge / discharge profile. It is difficult to uniquely determine the optimal overall discharge characteristic from among the many candidates, and the estimation accuracy decreases. When the width of the electrical quantity-voltage region of the partial charge / discharge profile is long and information on the partial charge / discharge profile is sufficient, as in the partial charge / discharge profiles corresponding to regions 1 to 4, the number of candidate overall discharge characteristics that can be estimated from the partial charge / discharge profile is relatively small. Therefore, it becomes easier to identify the optimal overall discharge characteristic, and the estimation accuracy improves.

[0092] Figure 8 is a diagram illustrating the change in capacity range due to changes in the partial charge / discharge profile. The reliability curves obtained when estimating each candidate overall discharge characteristic based on the partial charge / discharge profile for the different partial charge / discharge profiles in the electrical quantity-voltage region shown in the upper part of Figure 8 are shown in the center and bottom of Figure 8. In the center and bottom of Figure 8, the horizontal axis represents capacity (Ah), and the vertical axis represents the reliability of the estimation.

[0093] The central diagram in Fig. 8 shows reliability curves for partial charge / discharge profiles composed of the electric quantity-voltage plots for each of Region 1, Regions 1-2, Regions 1-3, and Regions 1-4 shown in the upper part of Fig. 8. The shorter the width of the electric quantity-voltage region of the partial charge / discharge profile, the more types of overall discharge characteristics can be estimated from the partial charge / discharge profile, and the wider the capacity range derived from these overall discharge characteristics.

[0094] The lower diagram in Figure 8 shows the reliability curves for the partial charge / discharge profiles composed of the electric quantity-voltage plots for Region 1 and Region 4. Even if the width of the electric quantity-voltage region of the partial charge / discharge profile is the same, the candidate overall discharge characteristics based on the partial charge / discharge profile change depending on the electric quantity-voltage zone and the gradient of the profile. Therefore, the distribution of the reliability of the estimation of each candidate overall discharge characteristic changes, and the width of the capacity range becomes wider and narrower.

[0095] As described above, the more candidate overall discharge characteristics based on the partial charge / discharge profile and the lower the accuracy of the estimation of the optimal overall discharge characteristic, the wider the capacity range. The fewer candidate overall discharge characteristics based on the partial charge / discharge profile and the higher the accuracy of the estimation of the optimal overall discharge characteristic, the narrower the capacity range. In other words, the capacity range is an indicator of the accuracy of the estimation of the optimal overall discharge characteristic. In this embodiment, by providing the capacity range as the capacity estimation result, it is possible to grasp the accuracy of the capacity estimation result.

[0096] 9 and 10 are flowcharts showing an example of a processing procedure executed by the estimation device 1. The processing unit 11 of the estimation device 1 executes the following processing in accordance with the program 121 stored in the storage unit 12. The processing unit 11 executes the following processing repeatedly, for example, at predetermined or appropriate time intervals. The processing unit 11 may start the following processing when an instruction to execute estimation is received.

[0097] The processing unit 11 of the estimation device 1 acquires time-series data of the current and voltage of the storage element 51 during the estimation target period (step S11). The processing unit 11 generates a partial charge / discharge profile based on the acquired time-series data of the current and voltage (step S12).

[0098] The processing unit 11 sets the internal state quantity parameters (step S13). The processing unit 11 may first set a capacitance value, and then set the value of the internal state quantity parameter corresponding to the set capacitance value based on the correspondence between the capacitance value and the internal state quantity parameter stored in advance.

[0099] The processing unit 11 estimates a candidate overall discharge characteristic based on the positive single-electrode characteristic and the negative single-electrode characteristic corresponding to the set internal state quantity parameter (step S14). The processing unit 11 calculates a fitting error between the estimated candidate overall discharge characteristic and the charge / discharge profile (step S15). The processing unit 11 stores the estimated candidate overall discharge characteristic and the calculated fitting error in the energy storage element DB 122 in association with each other (step S16).

[0100] The processing unit 11 determines whether the optimal discharge characteristics have been estimated (step S17). When it is determined that the optimal discharge characteristics have not been estimated because, for example, the estimated fitting error is not the smallest or is equal to or greater than a preset error threshold (S17: NO), the processing unit 11 returns the process to step S13. The processing unit 11 repeatedly performs the processes from step S13 onward to adjust the internal state parameters according to a predetermined rule, estimate a new candidate overall discharge characteristic from the adjusted internal state parameters, and calculate a fitting error. Each time the processing unit 11 performs an iterative calculation, it stores the newly estimated candidate overall discharge characteristic and the fitting error in the energy storage element DB 122.

[0101] For example, if it is determined that the optimal discharge characteristics have been estimated because the estimated fitting error is minimum or less than an error threshold (YES in S17), the processing unit 11 calculates the capacity corresponding to each candidate overall discharge characteristic (step S18). By the processing in step S18, the optimal candidate overall discharge characteristic selected from the candidate overall discharge characteristics, i.e., the optimal capacity corresponding to the optimal discharge characteristic, is also calculated.

[0102] The processing unit 11 calculates the reliability of the estimation corresponding to each calculated capacity based on the fitting error of each candidate overall discharge characteristic stored in the energy storage element DB 122 (step S19).

[0103] The processing unit 11 generates a reliability distribution diagram showing the distribution of the estimation reliability based on the capacity and the estimation reliability corresponding to each of the calculated candidate overall discharge characteristics (step S20).The processing unit 11 derives a reliability curve and a reliability function showing the relationship between the capacity and the reliability based on the generated reliability distribution diagram (step S21).

[0104] The processing unit 11 derives a capacity range defined by the maximum and minimum values ​​of each capacity based on each capacity corresponding to each candidate overall discharge characteristic (step S22). From the entire derived capacity range, the processing unit 11 derives a capacity range corresponding to a predetermined confidence interval (e.g., an 85% confidence interval) that satisfies a preset ratio (step S23). Step S23 may be omitted.

[0105] The processing unit 11 generates an estimation result screen including the optimum capacity, the capacity range, the reliability curve, the partial charge / discharge profile, the optimum overall discharge characteristic, the reliability, etc. (Step S24). The processing unit 11 outputs the generated estimation result screen to the user device 3 (Step S25), and the series of processes ends.

[0106] 11 is a schematic diagram showing an example of a result screen 340 showing the estimation result. The processing unit 31 of the user device 3 causes the display unit 34 to display the result screen 340 (Web screen) including the estimation result of the energy storage element 51 of the energy storage system 5 to be displayed, based on the screen information transmitted from the estimation device 1.

[0107] The result screen 340 includes a capacity range graph 341 that shows the transition of the capacity range of the storage element 51. The horizontal axis of the capacity range graph 341 indicates the number of years of operation (years), and the vertical axis indicates the capacity (Ah) of the storage element 51. The number of years of operation indicates the time elapsed since the start of operation in years. In the capacity range graph 341, the capacity range is represented by a bar-shaped arrow object 342 whose length changes depending on the width of the capacity range. The capacity value and capacity range of the storage element 51 can be recognized from the position and length of the bar-shaped arrow object 342 in the y-axis (capacity axis) direction. A round object 343 (circle) representing the optimal capacity value is superimposed on the bar-shaped arrow object 342 that represents the capacity range.

[0108] The estimation device 1 references the energy storage element DB 122 and reads out the capacity range and optimal capacity value corresponding to the identification information of the energy storage element 51 to be displayed for a predetermined operating period. The estimation device 1 generates, for each operating period, an arrow object 342 whose length is varied to correspond to the width of the capacity range defined by the difference between the maximum and minimum values ​​of the read capacity range. The estimation device 1 places the generated arrow object 342 on the capacity range graph 341 at a position corresponding to the capacity value of the capacity range and the operating period to be estimated. The estimation device 1 displays a round object 343 superimposed on the arrow object 342 at a position corresponding to the optimal capacity value for each operating period.

[0109] 11 shows an example in which the capacity range of the storage element 51 is represented by a stick-shaped arrow object 342. Alternatively, the capacity range of the storage element 51 may be represented in an appropriate display mode that allows the capacity range to be recognized. The capacity range of the storage element 51 may be represented, for example, by a numerical value or a reliability curve.

[0110] At least one of the arrow object 342 and the round object 343 included in the result screen 340 may have a function as a reception unit for receiving a request to display detailed information. The user can select a round object 343 corresponding to one of the operation periods on the result screen 340 using the operation unit 35, thereby displaying the optimal overall discharge characteristic corresponding to the optimal capacity indicated by the selected round object 343.

[0111] FIG. 12 is a schematic diagram showing an example of display of detailed information. FIG. 12 is an example of a result screen 340 displayed when an arrow object 342 corresponding to one of the operation periods in FIG. 11 is selected. When the estimation device 1 receives the selection of one of the round objects 343 through the user device 3, it reads out from the energy storage element DB 122 a reliability distribution diagram and a reliability curve or reliability function corresponding to the operation period of the selected arrow object 342. The estimation device 1 generates a result screen 340 including a reliability graph 344 showing the read reliability distribution diagram and the reliability curve or reliability function, and provides the result screen 340 to the user device 3. As shown in FIG. 12, the result screen 340 may display an arrow object 342 indicating a capacity range (reliability interval) and a round object 343 indicating an optimal capacity together with the reliability graph 344.

[0112] The detailed information may be, for example, information such as an optimal overall discharge characteristic, a partial charge / discharge profile, and the reliability of the estimation of the optimal overall discharge characteristic. For example, when the estimation device 1 receives the selection of any of the round objects 343 in Fig. 11 through the user device 3, the estimation device 1 may generate a result screen 340 including a discharge characteristic graph showing the optimal overall discharge characteristic and the partial charge / discharge profile corresponding to the operation period of the selected round object 343.

[0113] The detailed information may be displayed as a separate screen from the result screen 340 in Fig. 11 , or may be displayed as a pop-up on the result screen 340 in Fig. 11 . The configuration of the result screen 340 showing the estimation results is not limited to the examples shown in Fig. 11 and 12 . The detailed information may be displayed in response to a display request received using an object other than the arrow object 342 and the circle object 343, or may be initially displayed without receiving a display request.

[0114] The estimation device 1 may output the result screen 340 at any timing, for example, in response to receiving a request to output the result screen 340 via the user device 3. The estimation device 1 may switch between outputting and not outputting the result screen depending on whether the width of the estimated capacity range is equal to or greater than a predetermined value. For example, the estimation device 1 may be configured, as an initial setting, not to output the result screen when the width of the estimated capacity range is equal to or greater than a predetermined value because it is highly likely that the estimation accuracy has decreased, and to output the result screen only when the width of the estimated capacity range is less than the predetermined value.

[0115] Second Embodiment In a second embodiment, warning information indicating that the capacity is deteriorating is output according to the result of estimating the capacity range. The following mainly describes the differences from the first embodiment, and the same reference numerals are used to designate the same components as the first embodiment, and detailed descriptions thereof will be omitted.

[0116] 13 is a flowchart showing an example of a processing procedure executed by the estimation device 1 of the second embodiment. The estimation device 1 may start the following processing successively after the processing of FIGS. 9 and 10 ends, for example.

[0117] The processing unit 11 of the estimation device 1 determines whether the optimal capacity for the current estimation period calculated in step S18 is less than a preset optimal capacity threshold (step S31). If it is determined that the current optimal capacity is equal to or greater than the optimal capacity threshold (S31: NO), the processing unit 11 ends the process.

[0118] If it is determined that the current optimal capacity is less than the optimal capacity threshold (S31: YES), the processing unit 11 determines whether the width of the current capacity range derived in step S22 or step S23 is less than a predetermined capacity range threshold (step S32).

[0119] If it is determined that the width of the current capacity range is equal to or greater than the capacity range threshold (S32: NO), the processing unit 11 determines whether the estimation result for the previous estimation target period satisfies a specific requirement based on the information stored in the energy storage element DB 122 (step S33). The specific requirement is that the optimal capacity is less than the optimal capacity threshold and the width of the capacity range is equal to or greater than the capacity threshold. The previous estimation target period is the estimation target period immediately preceding the current estimation target period.

[0120] If the processing unit 11 determines that the optimal capacity in the previous estimation period is less than the optimal capacity threshold and the width of the capacity range is not equal to or greater than the capacity threshold and therefore the specific requirement is not met (S33: NO), the processing unit 11 ends the processing.If the processing unit 11 determines that the optimal capacity in the previous estimation period is less than the optimal capacity threshold and the width of the capacity range is equal to or greater than the capacity threshold and therefore the specific requirement is met (S33: YES), the processing unit 11 proceeds to step S34.

[0121] If it is determined that the width of the current capacity range is less than the capacity threshold value (S32: YES), the processing unit 11 advances the process to step S34.

[0122] If it is determined that the previous estimation result satisfies the specific requirement and that the width of the current capacity range is equal to or greater than the capacity threshold, the processing unit 11 generates warning information indicating that the capacity of the storage element 51 is degraded (step S34). The processing unit 11 outputs the generated warning information to the user device 3 (step S35). The processing unit 11 then ends the series of processes.

[0123] The output of the warning information may be performed, for example, by displaying text or an illustration indicating that the capacity has deteriorated, or by outputting a predetermined alert sound, turning on a lamp, etc. The estimation device 1 may display the warning information using the estimation result screen.

[0124] In the above example, the warning information is output when the optimal capacity is less than the optimal capacity threshold and the width of the capacity range is equal to or greater than the capacity threshold for two consecutive periods. Alternatively, the estimation device 1 may not output the warning information when the optimal capacity is less than the optimal capacity threshold and the width of the capacity range is equal to or greater than the capacity threshold. Instead of determining whether the optimal capacity is less than the optimal capacity threshold, the estimation device 1 may determine whether the decrease in the optimal capacity from the previous time is equal to or greater than a threshold.

[0125] The embodiments disclosed herein are illustrative in all respects and should not be considered limiting. The technical features described in each embodiment can be combined with each other, and the scope of the present invention is intended to include all modifications within the scope of the claims and equivalents thereto. The sequences shown in each embodiment are not limited, and within the scope of no contradiction, each processing step may be executed in a different order, or multiple processes may be executed in parallel. The entity that performs each process is not limited, and within the scope of no contradiction, the process of each device may be executed by another device.

[0126] The matters described in each embodiment can be combined with each other. Furthermore, the independent claims and dependent claims described in the claims can be combined with each other in any and all combinations, regardless of the reference format. Furthermore, the claims use a format in which a claim references two or more other claims (multiple claim format), but this is not limited to this. A multiple claim (multi-multi claim) that references at least one other multiple claim may also be used.

[0127] REFERENCE SIGNS LIST 100 Remote monitoring system 1 Estimation device 11 Processing unit 12 Storage unit 13 Communication unit 121 Program 122 Energy storage element DB 1A Recording medium 3 User device 31 Processing unit 32 Storage unit 33 Communication unit 34 Display unit 35 Operation unit 321 Program 3A Recording medium 5 Energy storage system 5 Energy storage element

Claims

1. An estimation method in which a computer executes a process of estimating the capacity of a storage element according to a plurality of overall discharge characteristics based on partial charge / discharge profiles of the storage element, estimating a capacity range of the storage element based on each estimated capacity, and outputting the estimated capacity range.

2. The estimation method according to claim 1, further comprising: deriving reliability information indicating the reliability of the estimation of each capacity; and outputting the derived reliability information.

3. The estimation method according to claim 2, wherein the reliability is derived based on a difference between the charge / discharge profile and the overall discharge characteristic fitted to the charge / discharge profile.

4. The estimation method according to claim 2, wherein the reliability is derived based on the occurrence probability of an internal parameter of a mathematical model that calculates the overall discharge characteristics in the charge / discharge profile based on measured values ​​including the current and voltage of the storage element.

5. The estimation method according to claim 2 or 3, wherein the reliability information includes a graph showing a distribution of the reliability or a relationship between the capacity and the reliability.

6. An estimation method as described in claim 2 or claim 3, which estimates the capacity range corresponding to each capacity estimated from the multiple overall discharge characteristics based on the charge / discharge profile, in which the reliability satisfies a specified requirement.

7. The estimation method according to claim 1 or 2, further comprising: obtaining an optimum capacity according to an optimum overall discharge characteristic among the plurality of overall discharge characteristics; and outputting the obtained optimum capacity in association with the capacity range.

8. The estimation method according to claim 1 or 2, wherein a screen displaying the capacity range is output using a rod-shaped object whose length changes according to the width of the capacity range.

9. The estimation method according to claim 8, wherein an optimal capacity corresponding to an optimal overall discharge characteristic among the plurality of overall discharge characteristics is obtained, and an object indicating the optimal capacity is displayed superimposed on the rod-shaped object.

10. The estimation method according to claim 8, wherein a screen is output that displays a plurality of the rod-shaped objects corresponding to the capacity ranges based on the charge / discharge profile for a plurality of periods.

11. An estimation method as described in claim 1 or claim 2, which outputs warning information when the optimal capacity corresponding to the optimal overall discharge characteristic among the plurality of overall discharge characteristics is less than a predetermined value and the width of the capacity range is less than a predetermined value.

12. An estimation device comprising a processing unit that executes a process of estimating the capacity of a storage element according to a plurality of overall discharge characteristics based on partial charge / discharge profiles of the storage element, estimating a capacity range of the storage element based on each estimated capacity, and outputting the estimated capacity range.

13. A computer program that causes a computer to execute a process of estimating the capacity of a storage element according to a plurality of overall discharge characteristics based on partial charge / discharge profiles of the storage element, estimating a capacity range of the storage element based on each estimated capacity, and outputting the estimated capacity range.

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