Information processing device, information processing method, computer program, and information processing system

Abstract

[Problem] To provide an information processing device, an information processing method, a computer program, and an information processing system that make it possible to estimate the timing at which a target event will occur at a target storage battery that includes a plurality of cells. [Solution] This information processing device comprises a processing part that calculates target trend data that represents the trend in the value of an index for the state of a target storage battery on the basis of measurement data for the target storage battery and estimates the timing at which a target event will occur at the target storage battery on the basis of the target trend data and at least one piece of standard trend data that represents a standard trend in the value of the index for the state of a storage battery during a period from a first time to a second time at which the target event occurs at the storage battery.

Description

Information processing device, information processing method, computer program, and information processing system

[0001] FIELD Embodiments of the present invention relate to an information processing device, an information processing method, a computer program, and an information processing system.

[0002] Battery systems for power grids and those used as infrastructure for public transportation, etc., must maintain their performance and functionality over the long term.Battery systems are typically constructed by connecting battery cells (also called battery packs), the smallest units, in series and parallel to form battery modules, connecting battery modules in series according to the required voltage to form battery units, and connecting battery units in parallel until the required storage capacity is achieved.

[0003] It is important to estimate in advance when a battery unit will stop functioning due to partial degradation of the battery system (e.g., battery unit degradation) so that the battery unit can be replaced at the appropriate time and the battery system can be maintained efficiently. To achieve this, it is necessary to estimate when the battery unit will stop functioning (the lifespan of some battery cells within the battery unit). Deductive electrochemical methods (such as simulations using physical models and the Arrhenius law) are known for estimating the deterioration progression of individual battery cells and for estimating the lifespan of secondary batteries. However, estimating the lifespan of all cells using measured voltages for each cell is not practical for large-scale battery systems due to the high data collection costs.

[0004] In a battery unit, battery cells do not all deteriorate at the same time, but rather some battery cells deteriorate at a faster rate. In light of this, a technology has been proposed that detects the deterioration of some battery cells in a battery unit using an index called the SoH (State of Health) ratio. Calculating the SoH ratio does not require measurements of all battery cells in the battery unit; instead, it uses only statistical data such as maximum, minimum, and average voltages, which reduces the cost of data collection.

[0005] It is possible to estimate the timing (period) of a battery unit's shutdown by estimating the transition of the SoH ratio. However, since the SoH ratio does not necessarily reflect the deterioration of each individual battery cell included in the battery unit, it is difficult to estimate the transition of the SoH ratio.

[0006] Patent No. 6134438 Patent No. 7193678 International Publication No. 2023 / 026743 International Publication No. 2022 / 249916

[0007] The present embodiment provides an information processing device, an information processing method, a computer program, and an information processing system that are capable of estimating the timing at which a target event will occur in a target storage battery.

[0008] The information processing device of this embodiment includes a processing unit that calculates target trend data representing the trend in the value of an index related to the state of a target storage battery based on measurement data related to the target storage battery, and estimates the timing at which the target event will occur in the target storage battery based on the target trend data and at least one reference trend data representing the reference trend in the value of the index related to the state of the storage battery during the period from a first time to a second time at which a target event will occur in the storage battery.

[0009] 5 is a block diagram showing an example of an information processing device according to an embodiment of the present invention. A diagram showing an example of the configuration of a storage battery system. A diagram showing an example of the configuration of a battery module. A diagram showing an example of a deterioration model generated by a model generation unit. A diagram showing an example of estimating the stop time of a target battery unit using a deterioration model ... different from that of FIG. 5. A diagram showing an example of creating a maintenance plan using the estimated stop time of each battery unit. A flowchart of an example of the operation of an information processing device. A diagram showing the hardware configuration of an information processing device.

[0010] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. Fig. 1 is a block diagram showing an example of an information processing system 1 according to an embodiment of the present invention. The information processing system 1 includes a storage battery system 2 and an information processing device 100 according to this embodiment. The information processing device 100 includes a processing unit 10 and a storage unit 11. The processing unit 10 includes a data acquisition unit 12, a calculation unit 13, a model generation unit 14, a deterioration transition estimation unit 15, and an input / output unit 16. The calculation unit 13 includes a State of Health (SoH) calculation unit 131, a maximum / minimum voltage SoH calculation unit 132, and an SoH ratio calculation unit 133.

[0011] The information processing device 100 is connected to the storage battery system 2 via a communication network. The communication network may be a wireless or wired network, or a cable such as a serial bus cable. The input / output unit 16 has a function of outputting data or information to a user and receiving various information or instructions from the user. As an example, the input / output unit 16 includes an output device such as a display device or a communication device, and an input device such as a keyboard, a mouse, or a voice input device. The input / output unit 16 may also be a touch panel that also has input / output functions.

[0012] The storage battery system 2 includes a plurality of battery units, and the information processing device 100 is an estimation device that estimates the timing at which a target event will occur for each of these battery units.

[0013] In this embodiment, the target event is the suspension of operation of the battery unit. Suspension of operation includes various cases, such as when operation is suspended due to a malfunction, or when a user monitors the measurement data of the battery unit and determines that suspension is necessary and then suspends the battery unit. Other target events include when a degradation test reveals that the degree of degradation exceeds a threshold, or when a user determines that degradation is progressing and makes the battery unit a special monitoring target.

[0014] Here, estimation includes both estimation for a future time point and estimation for a past time point, but the following description will focus on estimation for a future time point. Estimation for a future time point is also specifically referred to as prediction. The power storage system 2 or the battery unit may also be referred to as a storage battery.

[0015] 2 shows an example configuration of a storage battery system 2. The storage battery system 2 has a configuration in which a plurality of battery units 23 are connected in parallel. Each battery unit 23 has a configuration in which a plurality of battery modules 22 are connected in series. Each battery unit 23 can be individually removed and replaced with a new battery unit.

[0016] 3 shows an example of the configuration of a battery module 22. In the battery module 22, a plurality of unit batteries (cells) 21 are connected in series, and a plurality of the series-connected cells 21 are further connected in parallel. As another example of the configuration of the battery module 22, a configuration in which only one series-connected cell 21 exists is also possible.

[0017] The configuration of the battery unit 23 in Fig. 2 is an example, and the battery unit may have a configuration other than that shown in Fig. 2. For example, the battery unit may not include a battery module, but may include a series connection of multiple cells, or multiple such series connections connected in parallel.

[0018] In this embodiment, the battery unit 23 is the storage battery to be evaluated (target storage battery), but the target storage battery may also be the battery module 22. It is also possible to define the power storage system 2 as the target storage battery. The target storage battery may be defined arbitrarily as long as it includes multiple cells. The battery unit 23 and the battery module 22 are examples of storage batteries capable of storing (charging) and discharging electrical energy, and the target storage battery may have other configurations as long as it includes multiple cells.

[0019] Parameters such as the voltage, current, and temperature of each battery unit 23 can be measured using measuring equipment and transmitted as measurement data to the information processing device 100. For example, a battery management unit (BMU) or cell monitoring unit (CMU) included in a battery energy storage system (BESS) may record the parameters of each battery unit 23, or a separate device capable of recording the parameters of the battery unit 23 may be installed within the storage battery system 2. The measurement data may be transmitted directly to the information processing device 100 by the storage battery system 2 or the battery unit 23, or may be transmitted via a device that collects information about the storage battery system 2 or the battery unit 23. By acquiring the measurement data of each battery unit 23 in the operating storage battery system 2 in this manner, the timing (e.g., stop time) at which an event occurs in the battery unit 23 can be estimated even when the storage battery system 2 is operating (e.g., even when short-cycle charging and discharging is performed 24 hours a day, 365 days a year). This does not require the storage battery system 2 or the battery unit 23 to be shut down. The stop time of a battery unit 23 that has already stopped operating may be estimated (in this case, estimation for a past time point) by using the battery unit 23 that has already stopped operating as the target of estimation.

[0020] The measurement data for each battery unit includes at least data necessary to calculate the SoH of the battery unit 2 (storage battery). The SoH is an index indicating the degradation state, which is an example of the state of the battery unit 2 (storage battery). The degradation state of the battery unit 23 may be expressed in any manner. For example, it may be defined using the full charge capacity that decreases due to degradation, the internal resistance that increases due to degradation, or the like.

[0021] In this description, the SoH is defined as the ratio of the full charge capacity at the time of evaluation to the full charge capacity specified for the battery unit (full charge capacity at the time of evaluation / full charge capacity specified). The evaluation time may be any time. For example, if measurement data is saved daily as a file containing one day's worth of measurement results, the amount of power consumed on that day can be calculated from this one day's worth of measurement data. Therefore, the time when the measurement data is saved may be the evaluation time. Furthermore, based on the measurement results, an SoH transition run chart may be generated, for example, with the horizontal axis representing the amount of power and the vertical axis representing the SoH. In this case, the SoH for the cumulative number of equivalent cycles up to the desired evaluation time may be calculated.

[0022] Any method may be used to calculate the SoH of a battery unit. For example, the measurement data may include the voltage of each battery unit (e.g., the average voltage per fixed time period), and the standard deviation or variance of the voltage distribution may be calculated based on the time-series voltage data. Reference data showing a general relationship between the SoH and the standard deviation or variance of the voltage distribution is then created in advance from battery units (storage batteries) that have been degraded in various ways, and the SoH is then calculated from the calculated standard deviation or variance based on the reference data. The SoH may be calculated using such a method. The reference data is stored in advance in the storage unit 11.

[0023] Furthermore, in order to calculate the maximum and minimum voltage SoH described below, the measurement data includes data indicating whether the battery unit 23 is charging or discharging. For example, if the direction of current charging or discharging the battery unit 23 (storage battery) is represented by the positive or negative sign of the current, the measurement data includes the current charging or discharging the storage battery. Furthermore, the measurement data includes the maximum and minimum voltage values ​​of each cell in the battery unit. The measurement data may include the maximum and minimum voltage values ​​of the battery modules included in the battery unit, or may include the maximum and minimum voltage values ​​of the multiple cells in each battery module for each battery module.

[0024] Note that the measurement data may include values ​​of parameters that are not used in calculating the SoH.

[0025] The storage unit 11 stores data used in processing by the information processing device 100. This data includes, for example, measurement data (operation data) acquired from the storage battery system 2, reference data for calculating the SoH, SoH ratio transition data for each battery unit 23, SoH ratio transition data for battery units that have already stopped operating (past SoH ratio transition data), a degradation model, and output data to be presented to the user. Details of these data will be described later. Note that the data stored in the storage unit 11 is not limited to this, and for example, processing results of each component of the information processing device 100 may also be stored.

[0026] The data acquisition unit 12 acquires measurement data from the storage battery 2 or each battery unit 23 and stores the data in the memory unit 11. The stored measurement data is used as a history. For example, time-series data such as the transition of the voltage of each battery unit can be confirmed from the stored measurement data.

[0027] Based on the accumulated measurement data, the calculation unit 13 calculates an SoH ratio as an index for detecting deterioration (detecting accelerated deterioration) of any part of the cells in each battery unit 23, with each battery unit 23 being the battery unit 23 to be evaluated. The calculation unit 13 includes an SoH calculation unit 131, a maximum / minimum voltage SoH calculation unit 132, and an SoH ratio calculation unit 133. In this embodiment, the SoH ratio is used as the index, but any other index may be used as long as it is an index that can evaluate the state of a battery unit including multiple cells.

[0028] The SoH calculation unit 131 calculates the SoH of the battery unit 23 based on the accumulated measurement data. For example, as described above, the SoH calculation unit 131 calculates the standard deviation or variance of the distribution of voltage values ​​of the battery unit 23 per unit period, such as one day. Then, based on the reference data, the SoH of the battery unit 23 is calculated from the calculated standard deviation or variance.

[0029] Based on the accumulated measurement data, the maximum and minimum voltage SoH calculation unit 132 calculates the maximum and minimum voltage SoH for the battery unit 23. The maximum and minimum voltage SoH is an SoH based on the maximum and minimum voltages of the battery cells in the battery unit 23.

[0030] The cells included in the battery unit 23 vary in internal resistance due to deterioration. Consequently, the voltages of the individual cells also vary. The maximum / minimum voltage SoH calculation unit 132 regards the maximum voltage among the cell voltages as the voltage of the battery unit 23 during charging, and regards the minimum voltage among the cell voltages as the voltage of the battery unit 23 during discharging. Then, similar to the SoH calculation unit 131, it calculates the SoH of the battery unit 23. In other words, the maximum / minimum voltage SoH calculation unit 132 obtains maximum / minimum voltage data using the maximum voltage of the internal cells instead of the voltage of the battery unit 23 during charging, and the minimum voltage of the internal cells instead of the voltage of the battery unit 23 during discharging. The SoH of the battery unit 23 is then calculated from the maximum / minimum voltage data, and the calculated SoH is set as the maximum / minimum voltage SoH.

[0031] The cell with the maximum voltage when the battery unit 23 is charged and the cell with the minimum voltage when the battery unit 23 is discharged do not necessarily coincide, and the maximum / minimum voltage SoH provisionally indicates the most deteriorated state of the cells in the battery unit. In other words, the maximum / minimum voltage SoH indicates the possibility of the most deteriorated state in the battery unit 23, and therefore has a smaller value than the SoH.

[0032] For example, the voltage standard deviation method is known, which can evaluate the SoH of a storage battery without stopping the charging or discharging operation. The voltage standard deviation method uses a plot locus diagram in which the State of Charge (SoC) of a cell during charging or discharging is the X-coordinate and the terminal voltage of the cell is the Y-coordinate. It is known that, even if the charging or discharging power is the same, the distribution along the Y-axis, in other words, the terminal voltage variation, of the plot widens as the SoH decreases. The voltage standard deviation method estimates the SoH based on this distribution. When calculating the maximum and minimum voltage SoH using this voltage standard deviation method, the locus diagram shows a plot of the maximum voltage on the Y-coordinate and a plot of the minimum voltage on the Y-coordinate. Therefore, the distribution along the Y-axis becomes very large. This also shows that the maximum and minimum voltage SoH is a smaller value than the SoH.

[0033] The SoH ratio calculation unit 133 calculates an SoH ratio for each battery unit 23. The SoH ratio represents the ratio of the maximum and minimum voltages SoH of the battery unit 23 to the SoH of the battery unit 23 (maximum and minimum voltages SoH / SoH). As described above, the maximum and minimum voltages SoH depend on the most deteriorated state of the battery unit. On the other hand, the SoH depends on all the cells in the battery unit 23. Therefore, if the most deteriorated state is approximately the same as the other cells, the SoH ratio will be a value close to 1. If the most deteriorated state is more deteriorated than the other cells, the SoH ratio will be a value less than 1. In other words, the SoH ratio represents how deteriorated the most deteriorated state of the battery unit is compared to the other cells. By using the SoH ratio as an index, even if the battery unit 23 appears to be in good health overall, it is possible to recognize that some of the internal cells are more deteriorated than the others.

[0034] Each time the SoH ratio calculation unit 133 calculates an SoH ratio, the SoH ratio is stored in the storage unit 11 in association with the identification information of the battery unit 23 for which the SoH ratio was calculated. A time series (collection) of SoH ratios calculated for the same battery unit 23 is referred to as SoH ratio trend data. The SoH ratio trend data includes a time series of SoH ratios for multiple times (third times) and represents the SoH ratio trend. If the calculation unit 13 calculates an SoH ratio once a day, the SoH ratio trend data is updated by adding an SoH ratio once a day. If the battery system 2 has X battery units 23, X pieces of SoH ratio trend data are stored corresponding to these X battery units 23 and updated daily. Note that the time in this embodiment may be in seconds, minutes, hours, days, or other units. The following description assumes a daily unit.

[0035] The storage unit 11 also stores SoH ratio transition data (hereinafter referred to as past SoH ratio transition data) for multiple battery units that have already been shut down in the past (for example, reached the end of their life or been replaced) (see FIG. 1 ). The SoH ratio transition data may be generated by the calculation unit 13 or may be provided in advance from an external source. These multiple battery units are different from the multiple battery units 23 in the operating storage battery system 2 and have already been shut down. These battery units that have been shut down in the past are also referred to as "past battery units."

[0036] The last data in the past SoH ratio transition data corresponds to the time when operation stopped (stop time).

[0037] The model generation unit 14 extracts data from multiple past battery unit SoH ratio transition data that spans a certain period of time or longer, going back from the last data point in time. The certain period of time to go back may be one year or longer, such as one year, one year and a half, or two years, or it may be shorter than one year. The extracted SoH ratio transition data is recorded as extracted SoH ratio transition data.

[0038] The model generation unit 14 expands these multiple extracted SoH ratio transition data into a space with the horizontal axis representing time and the vertical axis representing the SoH ratio, aligns the last data point of each data point to the same time position in the space, and clusters these extracted SoH ratio transition data. Any method can be used for clustering, such as hierarchical clustering or non-hierarchical clustering. This generates one or more clusters. Although the following assumes the case where there are multiple clusters, the number of clusters may be one.

[0039] For each cluster, the model generation unit 14 averages the extracted SoH ratio transition data belonging to the cluster at corresponding times (the same times when aligned as above) and obtains the string of averaged values ​​as reference SoH ratio transition data (reference time-series data). The set of reference SoH ratio transition data obtained for each cluster is called a deterioration model (or transition model). Here, only one deterioration model is generated, but multiple deterioration models may be generated by changing the fixed retroactive period. The deterioration models generated by the model generation unit 14 are stored in the memory unit 11 (see FIG. 1).

[0040] FIG. 4 shows an example of a degradation model generated by the model generation unit 14. Two pieces of reference SoH ratio transition data G1 and G2 are shown as graphs. The two pieces of reference SoH ratio transition data G1 and G2 are also referred to as reference graphs G1 and G2. The two dashed lines sandwiching the reference SoH ratio transition data G1 represent the standard deviation line. Similarly, the two dashed lines sandwiching the reference SoH ratio transition data G2 represent the standard deviation. The ends of the reference SoH ratio transition data G1 and G2 are aligned, and the sizes of the reference SoH ratio transition data G1 and G2 correspond to the length of the aforementioned retroactive period. Note that the actual end times (actual stop times) of the reference SoH ratio transition data G1 and G2 may be different, but here, for alignment purposes, the positions of the end data of both pieces are aligned to the same position in space. The time indicated by the actual last data of each of the reference SoH ratio transition data G1 and G2 corresponds to the second time, and the time preceding the last time by the above-mentioned period corresponds to the first time. The first time and second time may be different for each of the reference SoH ratio transition data G1 and G2.

[0041] The deterioration transition estimation unit 15 sets each battery unit 23 as a target battery unit (target storage battery), reads the SoH ratio transition data of the target battery unit from the storage unit 11, and estimates the timing when a target event will occur in the target battery unit using the read SoH ratio transition data and the above-mentioned deterioration model. Specifically, in this example, it estimates the timing (e.g., time) when the target battery unit will stop. The estimated time here is a time after the most recent time when the SoH ratio of the target battery unit was calculated.

[0042] FIG. 5 shows an example of estimating the stop time of a target battery unit using a degradation model. The solid line indicates the graph of SoH ratio transition data D for the target battery unit. The SoH ratio transition data D is also referred to as target graph D. Also shown are reference SoH ratio transition data G1 and G2 (reference graphs G1 and G2) for the degradation model. The reference SoH ratio transition data G1 and G2 are similar to those in FIG. 4, but are displayed more simply than in FIG. 5. The SoH ratio transition data D and the reference SoH ratio transition data G1 and G2 are expanded in a space with the horizontal axis representing time and the vertical axis representing an index (the SoH ratio in this example).

[0043] The deterioration transition estimation unit 15 calculates a matching degree (also referred to as a similarity degree) based on the distance between the reference graphs G1 and G2 while moving at least one of the SoH ratio transition data D (object graph D) and the reference graphs G1 and G2 horizontally (in the time direction). A higher matching degree (similarity degree) indicates a closer distance. When calculating the matching degree, the tail positions of the reference graphs G1 and G2 do not need to match each other; instead, the relative positions of the reference graphs G1 and G2 in the time direction are independently adjusted relative to the object graph D. Based on the matching degree, the unit searches for the reference graph (reference SoH ratio transition data) that best matches the object graph D and the position that matches the object graph D. In the example of FIG. 5 , the object graph D and the reference graph G2 are most closely matched at the positions shown in the figure. The estimated time EP until the target battery unit stops is calculated as the time corresponding to the distance in the time direction from the time indicated by the tail data of the object graph D (SoH ratio transition data D) at the best matched position (referred to as the current time T1) to the tail position of the reference graph G2. In addition, the estimated time EP is added to the current time T1 to obtain the time when the target battery unit is estimated to stop (estimated stop time T2). The estimated stop time T2 is an example of the timing when the target event is estimated to occur in the target battery unit.

[0044] Here, the degree of matching is calculated, for example, by calculating the distance between two pieces of data (here, the distance between the target graph D and the reference graph G1 or G2) at corresponding times (the same time) in space for multiple corresponding times (for example, all times), and then dividing the sum of the calculated distances by the number of those multiple times. The distance may be, for example, Euclidean distance, but is not limited to this. By dividing the sum of the distances by the number of times, appropriate evaluation is possible even if the number of corresponding times (number of samples) differs for each reference graph (reference SoH transition data) for which the degree of matching is calculated.

[0045] Figure 6 shows an example of estimating the stop time of a target battery unit using a degradation model different from that shown in Figure 5. Here, reference SoH ratio transition data G11, G12 (reference graphs G11, G12) different from those shown in Figure 5 are shown. The SoH ratio transition data D (target graph D) is assumed to be the same as that shown in Figure 5.

[0046] This shows a case where the degree of matching for the object graph D with both the reference graphs G11 and G12 is equal to or greater than the threshold value. The reference graphs G11 and G12 have the highest degree of matching with the object graph D at the positions shown in the figure, and both degrees of matching are greater than the threshold value.

[0047] In this case, for example, the estimated stop time T5 is determined by dividing the interval between the stop time T3 of the target battery unit estimated from the reference graph G11 and the stop time T4 of the target battery unit estimated from the reference graph G12, based on the distance from the reference graph G11 (degree of matching) and the distance from the reference graph G12 (degree of matching). That is, the estimated stop time T5 can be obtained by calculating the ratio of the degrees of matching between the reference graph G11 and the reference graph G12, calculating a weighted sum of the time until the stop time T3 and the time until the stop time T4 based on the ratio, and adding the value (time) of the weighted sum to the end time of the target graph D. In the example of FIG. 6 , two reference graphs with a high degree of matching are used, but an estimated stop time can also be obtained by performing a similar weight calculation using three or more reference graphs with a high degree of matching.

[0048] As another method, the reference graph with the shortest time from the end of the target graph D to the end of the reference graph may be selected from among the reference graphs with a matching degree equal to or greater than a threshold. The time corresponding to the distance in the time direction from the data at the end of the target graph D to the end of the selected reference graph is calculated as the estimated time until the target battery unit stops. The time at which the target battery unit is estimated to stop (estimated stop time) is calculated by adding this estimated time to the time indicated by the data at the end of the target graph D (current time).

[0049] In the example of FIG. 5 described above, one of the reference graphs (reference SoH ratio transition data) is selected based on the degree of matching with each reference graph. However, other methods may be used to select a reference graph. For example, the calculation unit 13 calculates, as attribute information, the time change or integrated value of at least one of the temperature, current value, voltage value, power value, and SoC until the storage battery unit shut down in the past, in association with the past SoH ratio transition data. When the model generation unit 14 generates the reference SoH ratio transition data from the past SoH ratio transition data belonging to the cluster, it obtains attribute information for the reference SoH ratio transition data by averaging this attribute information. Attribute information including the same items is also generated for the target battery unit. The degradation transition estimation unit 15 compares the attribute information including the same items for the target battery unit with the attribute information of each of the multiple reference SoH ratio transition data and selects the reference SoH ratio transition data with the closest value. The selected reference SoH ratio transition data is used to estimate the shutdown time. This method may be applied to the example of FIG. 6 to select two or more reference SoH ratio transition data having the closest values ​​to estimate the stop time.

[0050] If there is no reference graph with a matching degree equal to or greater than the threshold, the estimated stop time of the target battery unit is not calculated, and the estimated stop times calculated for the other battery units 23 in the storage battery system 2 (excluding the other battery units for which the estimated stop time has not been calculated) are obtained. The latest of the obtained estimated stop times is set as Tmax. It may be determined that the target battery unit will not be stopped until time Tmax. Alternatively, the time from the current time to Tmax may be calculated, and it may be determined that the target battery unit will not be stopped during the calculated time. If the estimated stop times are not calculated for all battery units 23 in the storage battery system 2, it may be determined that the target battery unit will not be stopped during the time from the current time to a predetermined time T0. The length of time until time T0 may be, for example, the data length extracted from the past SoH ratio transition data used to generate the deterioration model (see FIG. 4 ). In other words, it may be the length of the period going back from the time indicated by the last data in the past SoH ratio transition data.

[0051] The input / output unit 16 generates output data including information about the stop time estimated by the deterioration progression estimation unit 15 in association with identification information of the battery unit 23 that was the subject of the estimation, and outputs the generated output data visibly to a user. When performing estimation for all battery units 23 in the storage battery system 2, the input / output unit 16 may perform estimation for all battery units 23 and then output output data including information about the stop time at which all battery units 23 were stopped. The user can view the output data displayed on the input / output unit 16 (display device) to determine whether there is a battery unit 23 whose life (stop time) is approaching the end of its life, and decide to perform maintenance work (replacement) on the battery units 23 that have a short time until their stop time.

[0052] [Regeneration of Deterioration Model] In the example of FIG. 5 , there may be cases where the target battery unit shuts down earlier than the estimated time calculated for the target battery unit (i.e., the battery unit shuts down earlier than estimated). In this case, the processing unit 10 receives information indicating that the target battery unit shut down earlier than the estimated time via the input / output unit 16 and stores the SoH ratio transition data of the target battery unit up to the shutdown as new past SoH ratio transition data in the storage unit 11. Note that cases where the target battery unit shuts down include various cases, such as when operation stops due to a malfunction or when a user monitors the measurement data of the target battery unit and determines that shutdown is necessary and shuts it down. The model generation unit 14 then regenerates the deterioration model using this new past SoH ratio transition data. This improves the accuracy of the deterioration model.

[0053] Furthermore, even if the target battery unit is left as is without being replaced after the estimated shutdown time has passed, the battery unit may continue to operate, and the time until it actually shuts down may be longer than the estimated time. In this case, after the target battery unit actually shuts down, the SoH ratio transition data up to the shutdown of the target battery unit may be used as new past SoH ratio transition data, and the degradation model may be regenerated in the same way as in the case where the battery unit shuts down earlier than estimated.

[0054] [Creating a Maintenance Plan] The input / output unit 16 may create a maintenance plan as output data based on information relating to the stop time estimated by the deterioration transition estimation unit 15, and output information about the maintenance plan to the user.

[0055] FIG. 7 shows an example of creating a maintenance plan using the estimated shutdown time of each battery unit 23. There are n battery units whose shutdown times are estimated, and the information on the battery units is arranged vertically from top to bottom in order of the shortest time until shutdown. Battery unit x represents the battery unit with the xth shortest time until shutdown. The right direction represents the direction of time. For ease of understanding, the horizontal direction is divided into periods of regular time intervals. Circles in the figure schematically indicate periods that include the estimated shutdown time of a battery unit. Periods A, B, and C are candidate periods for maintenance work (replacement, etc.).

[0056] To prevent an operating unit from stopping while the battery unit is in operation, it is necessary to replace the battery unit before the estimated stop time. Therefore, for battery units 1 to 3, if they are not replaced at the next time A, they will not be able to be replaced before the estimated stop time, so they must be replaced at time A. In this case, for battery units 4 to n, whether they are replaced at time A or not depends on whether the next replacement time is time B, time C, or a time further in the future.

[0057] If the next-next maintenance work can be performed at time B, then only battery units 1, 2, and 3 need to be replaced at time A. On the other hand, if the next-next maintenance work is at time C, then battery unit 4 must also be replaced during the maintenance work at time A. If the next-next maintenance work is later than time C, then all battery units 1 to n must be replaced at time A.

[0058] Therefore, when the timing of maintenance work is determined, the battery units to be replaced can be determined using the estimated stop time. Also, when the number of battery units to be replaced is determined, the timing of maintenance work can be determined using the estimated stop time. Such determinations can be made by the processing unit 10 or the input / output unit 16, and the determination results can be output to the user from the input / output unit 16 as maintenance plan-related data.

[0059] 8 is a flowchart showing an example of the operation of the information processing device 100. Here, the operation of the deterioration progression estimation unit 15 will be described assuming that the method described above with reference to FIG.

[0060] The data acquisition unit 12 acquires measurement data (operation data) of each battery unit 23 from the storage battery system 2 and stores it in the storage unit 11 (S11). The calculation unit 13 calculates an SoH ratio using the acquired measurement data and stores it in the storage unit 11 (S12). That is, the SoH ratio transition data for each battery unit 23 is updated by adding the currently calculated SoH ratio to the SoH ratio transition data. The model generation unit 14 generates a degradation model (transition model) based on the past SoH ratio transition data (S13). However, if a degradation model has already been generated and stored in the storage unit 11 and the degradation model generation conditions are not met, the degradation model may not be generated. For example, the generation conditions may be met when new past SoH ratio transition data is added after the previous degradation model was generated. Alternatively, the generation conditions may be determined to be met when a user explicitly instructs the degradation model to be generated.

[0061] The deterioration transition estimation unit 15 calculates the degree of matching between the SoH transition data of the battery unit 23 and each reference SoH transition data included in the deterioration model, and detects the matching reference SoH transition data and the matching position (S14). For example, it detects the reference SoH transition data with the highest degree of matching that is equal to or greater than a threshold, and the position that best matches the reference SoH transition data (highest degree of matching or closest distance), that is, the relative position between the best-matching reference SoH transition data and the SoH transition data. When matching reference SoH transition data is detected (YES in S14), the deterioration transition estimation unit 15 calculates the time corresponding to the distance in the time direction from the end of the SoH transition data to the end of the matching reference SoH transition data at the matching position as the estimated time until operation shutdown. The time indicated by the last data point in the SoH transition data (current time) plus the estimated time is calculated as the estimated stop time (e.g., estimated stop date) of the battery unit (S15). After this, it is determined whether all battery units have been evaluated (S16). Even if no matching reference SoH transition data is found in the above-mentioned step S14 (NO in S14), it is also determined whether all battery units have been evaluated (same S16).

[0062] If there is a battery unit that has not yet been evaluated (NO in S16), the process returns to step S 14. If all battery units have been evaluated (YES in S16), the process ends.

[0063] As described above, according to this embodiment, it is possible to estimate the number of days until a battery unit will shut down even without operation data (measurement data) for all cells in a storage battery (battery unit), and to determine the appropriate timing for maintenance work.

[0064] 9 shows the hardware configuration of the information processing device 100. The information processing device 100 is configured by a computer device 600. The computer device 600 includes a CPU 601, an input interface 602, a display device 603, a communication device 604, a main storage device 605, and an external storage device 606, which are interconnected by a bus 607.

[0065] The CPU (Central Processing Unit) 601 executes an information processing program, which is a computer program, on the main storage device 605. The information processing program is a program that realizes each of the above-mentioned functional components of the information processing device 100. The information processing program may be realized not by a single program, but by a combination of multiple programs and scripts. Each functional component is realized by the CPU 601 executing the information processing program.

[0066] The input interface 602 is a circuit for inputting operation signals from input devices such as a keyboard, a mouse, and a touch panel to the information processing device 100. The input interface 602 corresponds to the input / output unit 16.

[0067] The display device 603 displays data output from the information processing device 100. The display device 603 is, for example, but not limited to, an LCD (liquid crystal display), an organic electroluminescence display, a CRT (cathode ray tube), or a PDP (plasma display). Data output from the computer device 600 can be displayed on the display device 603. The display device 603 corresponds to the input / output unit 16.

[0068] The communication device 604 is a circuit that enables the information processing device 100 to communicate with an external device wirelessly or via a wire. Data can be input from the external device via the communication device 604. The data input from the external device can be stored in the main memory device 605 or the external memory device 606. The communication device 604 corresponds to the input / output unit 16.

[0069] The main memory device 605 stores an information processing program, data required for executing the information processing program, data generated by executing the information processing program, etc. The information processing program is deployed and executed on the main memory device 605. The main memory device 605 is, for example, a RAM, a DRAM, or an SRAM, but is not limited to these. Each storage unit or database of the information processing device 100 may be constructed on the main memory device 605.

[0070] The external storage device 606 stores information processing programs, data required for executing the information processing programs, data generated by executing the information processing programs, etc. These information processing programs and data are read into the main storage device 605 when the information processing programs are executed. The external storage device 606 is, for example, a hard disk, an optical disk, a flash memory, or a magnetic tape, but is not limited to these. Each storage unit or database of the information processing device 100 may be constructed on the external storage device 606.

[0071] The information processing program may be pre-installed in computer device 600, or may be stored in a storage medium such as a CD-ROM. The information processing program may also be uploaded to the Internet.

[0072] Furthermore, the information processing device 100 may be configured as a single computer device 600, or may be configured as a system made up of a plurality of computer devices 600 connected to each other.

[0073] The present invention is not limited to the above-described embodiments, and the components can be modified and embodied in practice without departing from the spirit of the invention. Furthermore, various inventions can be created by appropriately combining multiple components disclosed in the above-described embodiments. For example, configurations in which some components are omitted from all the components shown in each embodiment may also be considered. Furthermore, components described in different embodiments may be appropriately combined.

[0074] This embodiment can also be configured as follows: [Item 1] An information processing device comprising: a processing unit that calculates target transition data representing a transition of a value of an index related to a state of a target storage battery based on measurement data related to the target storage battery, and estimates a timing when the target event will occur in the target storage battery based on the target transition data and at least one reference transition data representing a reference transition of the value of the index related to the state of the storage battery during a period from a first time to a second time when a target event will occur in the storage battery. [Item 2] The target storage battery has a plurality of cells, and the processing unit calculates the value of the index based on a minimum voltage and a maximum voltage among voltages of a plurality of cells in the target storage battery for each of a plurality of third times, and calculates data including the values ​​of the index at the plurality of third times as the target transition data. [Item 3] The information processing device according to item 1 or 2, wherein the processing unit calculates transition data representing transitions in values ​​of the indexes related to states of the plurality of storage batteries until the target event occurs in the plurality of storage batteries based on measurement data related to the plurality of storage batteries in which the target event has occurred; generates at least one cluster each including one or more of the transition data by clustering the plurality of transition data calculated for the plurality of storage batteries; and generates the reference transition data for each cluster based on the one or more of the transition data included in the cluster. [Item 4] The information processing device according to any one of items 1 to 3, wherein the processing unit expands the target transition data and the plurality of reference transition data in a space whose axes are time and the index, moves at least one of the target transition data and the plurality of reference transition data in the time direction, selects one of the reference transition data based on a distance between the target transition data and the plurality of reference transition data, and aligns the one reference transition data with the target transition data, calculates a distance in the time direction from an end of the target transition data to an end of one of the reference transition data, and estimates a timing at which the target event will occur by adding a time corresponding to the calculated distance in the time direction to a time indicated by data at the end of the target transition data.[Item 5] The information processing device according to any one of items 1 to 4, wherein the processing unit expands the target transition data and the plurality of reference transition data in a space whose axes are time and the index, moves at least one of the target transition data and the plurality of reference transition data in the time direction, selects two or more of the reference transition data for the target transition data based on distances between the target transition data and the plurality of reference transition data, and aligns the selected two or more reference transition data with the target transition data, calculates a plurality of distances in the time direction from an end of the target transition data to ends of the two or more plurality of reference transition data, and estimates a timing at which the target event will occur based on times corresponding to the calculated distances in the time direction, a ratio between the distances to each of the two or more reference transition data, and a time indicated by data at the end of the target transition data. [Item 6] The information processing device according to any one of items 1 to 5, wherein attribute information indicating a change over time or an integrated value of at least one of temperature, current value, voltage value, power value, and SoC is associated with each of the plurality of reference trend data, and the processing unit calculates the attribute information indicating the change over time or an integrated value of at least one of temperature, current value, voltage value, power value, and SoC based on the measurement data for the target storage battery, selects at least one of the reference trend data based on the calculated attribute information and a plurality of pieces of attribute information corresponding to the plurality of reference trend data, and estimates the timing of the target event to occur based on the target trend data using the selected reference trend data. [Item 7] The information processing device according to any one of items 1 to 6, wherein the processing unit acquires information indicating a timing of the target event to occur in the target storage battery, and, if a difference between the timing indicated by the acquired information and the estimated timing of the target event to occur satisfies a condition, generates the reference trend data based on trend data of the value of the index of the target storage battery up to the occurrence of the target event. [Item 8] The information processing device according to any one of items 1 to 7, wherein the target event is a stop of operation, and the timing at which the target event occurs in the target storage battery is a time at which the operation of the target storage battery stops.[Item 9] The information processing device according to item 8, wherein the time when operation of the target storage battery will stop is a date when operation of the target storage battery will stop. [Item 10] The information processing device according to any one of items 1 to 9, wherein the target storage battery has a plurality of cells, and the processing unit calculates a first SoH based on the measurement data of the target storage battery, calculates a second SoH based on a minimum voltage and a maximum voltage among voltages of the plurality of cells in the target storage battery, and calculates the value of the index from a ratio of the second SoH to the first SoH. [Item 11] The information processing device according to item 4, wherein the processing unit selects the reference trend data having the largest similarity according to the distance that is equal to or greater than a threshold, and when there is no reference trend data having a similarity that is equal to or greater than the threshold, estimates that the timing when the target event will occur will be after the time indicated by the last data of the target trend data plus the length of the period from the first time to the second time. [Item 12] The information processing device according to Item 4, wherein the processing unit selects the reference trend data whose similarity according to the distance is equal to or greater than a threshold and is the largest, the processing unit estimates a timing at which the target event will occur for the plurality of target storage batteries, and when there is a target storage battery for which there is no reference trend data whose similarity is equal to or greater than the threshold, the processing unit sets the timing at which the target event will occur to a time obtained by adding the latest of the estimated timings for one or more target storage batteries for which there is reference trend data whose similarity is equal to or greater than the threshold to the time indicated by the last data of the target trend data for the target storage battery for which there is no reference trend data whose similarity is equal to or greater than the threshold. [Item 13] The information processing device according to Item 4, wherein the processing unit calculates a similarity based on a distance between the target trend data and the plurality of reference trend data, selects the reference trend data whose similarity is largest, and aligns the reference trend data with the target trend data at a position where the similarity is largest.[Item 14] The information processing device according to item 5, wherein the processing unit calculates a similarity based on a distance between the target transition data and a plurality of the reference transition data, selects two or more of the reference transition data with the greatest similarity, and aligns the two or more reference transition data with the target transition data at positions where the similarity is greatest. [Item 15] The information processing device according to any one of items 1 to 14, wherein the processing unit expands the target transition data and the reference transition data in a space whose axes are time and the index, moves at least one of the target transition data and the reference transition data in the time direction to align the reference transition data with the target transition data at a position where the similarity according to the distance between the target transition data and the reference transition data is highest or equal to or greater than a threshold, calculates a distance in the time direction from an end of the target transition data to an end of one of the reference transition data, and estimates a timing when the target event will occur by adding a time corresponding to the calculated distance in the time direction to a time indicated by the last data of the target transition data. [Item 16] An information processing method comprising: calculating, based on measurement data for a target storage battery, target transition data representing a transition in the value of an index related to the state of the target storage battery; and estimating a timing at which the target event will occur in the target storage battery based on the target transition data and at least one reference transition data representing a reference transition in the value of the index related to the state of the storage battery during a period from a first time to a second time at which the target event will occur in the storage battery. [Item 17] A computer program for causing a computer to execute the steps of: calculating, based on measurement data for a target storage battery, target transition data representing a transition in the value of an index related to the state of the target storage battery; and estimating a timing at which the target event will occur in the target storage battery based on the target transition data and at least one reference transition data representing a reference transition in the value of the index related to the state of the storage battery during a period from the first time to a second time at which the target event will occur in the storage battery.[Item 18] An information processing system comprising: a target storage battery; and a processing unit that calculates target transition data representing a transition in the value of an index related to the state of the target storage battery based on measurement data related to the target storage battery; and estimates the timing at which the target event will occur in the target storage battery based on the target transition data and at least one reference transition data representing a reference transition in the value of the index related to the state of the storage battery during a period from a first time to a second time at which a target event will occur in the storage battery.

[0075] REFERENCE SIGNS LIST 11 Storage unit 12 Data acquisition unit 13 Calculation unit 14 Model generation unit 15 Deterioration progression estimation unit 16 Input / output unit 21 Unit battery (cell) 22 Battery module 23 Battery unit 23 Total battery unit 100 Information processing device 131 SoH calculation unit 132 Maximum / minimum voltage SoH calculation unit 133 SoH ratio calculation unit 600 Computer device 602 Input interface 603 Display device 604 Communication device 605 Main memory device 606 External memory device 607 Bus

Claims

1. An information processing device comprising: a processing unit that calculates target trend data representing the trend of an index value relating to the state of a target storage battery based on measurement data relating to the target storage battery; and estimates the timing at which the target event will occur in the target storage battery based on the target trend data and at least one reference trend data representing a reference trend of the value of the index relating to the state of the storage battery during the period from a first time to a second time at which a target event will occur in the storage battery.

2. The information processing device of claim 1, wherein the target storage battery has a plurality of cells, and the processing unit calculates the value of the index based on the minimum and maximum voltages of the voltages of the plurality of cells in the target storage battery for each of a plurality of third times, and calculates data including the values ​​of the index for the plurality of third times as the target trend data.

3. The information processing device described in claim 1, wherein the processing unit calculates transition data representing the transition of the values ​​of the indicators related to the state of the plurality of storage batteries until the target event occurs in the plurality of storage batteries based on measurement data related to the plurality of storage batteries in which the target event occurred, clusters the plurality of transition data calculated for the plurality of storage batteries to generate at least one cluster each including one or more of the transition data, and generates the reference transition data for each cluster based on the one or more of the transition data included in the cluster.

4. The information processing device of claim 1, wherein the processing unit expands the target transition data and the plurality of reference transition data in a space with time and the index as axes, moves at least one of the target transition data and the plurality of reference transition data in the time direction, selects one of the reference transition data based on the distance between the target transition data and the plurality of reference transition data, aligns one of the reference transition data with the target transition data, calculates the distance in the time direction from the end of the target transition data to the end of one of the reference transition data, and estimates the timing at which the target event will occur by adding the time corresponding to the calculated distance in the time direction to the time indicated by the data at the end of the target transition data.

5. The information processing device of claim 1, wherein the processing unit expands the target transition data and the plurality of reference transition data in a space with time and the index as axes, moves at least one of the target transition data and the plurality of reference transition data in the time direction, selects two or more of the reference transition data for the target transition data based on the distance between the target transition data and the plurality of reference transition data, aligns the selected two or more reference transition data with the target transition data, calculates multiple time-direction distances from the end of the target transition data to the ends of two or more of the plurality of reference transition data, and estimates the timing at which the target event will occur based on the times corresponding to the calculated multiple time-direction distances, the ratio between the distances to each of the two or more reference transition data, and the time indicated by the last data of the target transition data.

6. The information processing device of claim 1, wherein each of the plurality of reference trend data corresponds to attribute information indicating a time change or an integrated value of at least one of temperature, current value, voltage value, power value, and SoC, and the processing unit calculates attribute information indicating a time change or an integrated value of at least one of temperature, current value, voltage value, power value, and SoC based on the measurement data related to the target storage battery, selects at least one of the reference trend data based on the calculated attribute information and a plurality of attribute information corresponding to the plurality of reference trend data, and uses the selected reference trend data to estimate the timing when the target event will occur based on the target trend data.

7. The information processing device described in claim 1, wherein the processing unit acquires information indicating the timing at which the target event occurred in the target storage battery, and if the difference between the timing indicated by the acquired information and the estimated timing at which the target event occurred satisfies a condition, generates the reference trend data based on trend data of the value of the index of the target storage battery up until the target event occurred.

8. The information processing device according to claim 1, wherein the target event is a stoppage of operation, and the timing at which the target event occurs in the target storage battery is the time at which the operation of the target storage battery stops.

9. The information processing device according to claim 8, wherein the time when the operation of the target storage battery will stop is a date when the operation of the target storage battery will stop.

10. The information processing device of claim 1, wherein the target storage battery has a plurality of cells, and the processing unit calculates a first SoH based on the measurement data of the target storage battery, calculates a second SoH based on the minimum and maximum voltages of the voltages of the plurality of cells in the target storage battery, and calculates the value of the index based on the ratio of the second SoH to the first SoH.

11. The information processing device of claim 4, wherein the processing unit selects the reference trend data whose similarity according to the distance is greater than or equal to a threshold and whose similarity is the greatest, and when there is no reference trend data whose similarity is greater than or equal to the threshold, estimates that the timing of the occurrence of the target event will be after the time indicated by the last data of the target trend data plus the length of the period from the first time to the second time.

12. The information processing device of claim 4, wherein the processing unit selects the reference trend data whose similarity according to the distance is equal to or greater than a threshold and is the largest, the processing unit estimates the timing at which the target event will occur for multiple target batteries, and when there is a target battery for which there is no reference trend data with a similarity equal to or greater than the threshold, the processing unit determines the timing at which the target event will occur to be the time obtained by adding the time until the latest timing among the timings estimated for one or more target batteries for which there is reference trend data with a similarity equal to or greater than the threshold to the time indicated by the last data of the target trend data for the target battery for which there is no reference trend data with a similarity equal to or greater than the threshold.

13. The information processing device of claim 1, wherein the processing unit calculates similarity based on the distance between the target trend data and a plurality of reference trend data, selects the reference trend data with the greatest similarity, and aligns the reference trend data with the target trend data at the position where the similarity is greatest.

14. The information processing device of claim 5, wherein the processing unit calculates similarity based on the distance between the target trend data and multiple reference trend data, selects two or more reference trend data with the greatest similarity, and aligns the two or more reference trend data with the target trend data at positions where the similarity is greatest.

15. The information processing device of claim 1, wherein the processing unit expands the target transition data and the reference transition data in a space with time and the index as axes, moves at least one of the target transition data and the reference transition data in the time direction to align the reference transition data with the target transition data at a position where the similarity according to the distance between the target transition data and the reference transition data is highest or equal to or greater than a threshold, calculates the distance in the time direction from the end of the target transition data to the end of one of the reference transition data, and estimates the timing when the target event will occur by adding the time corresponding to the calculated distance in the time direction to the time indicated by the data at the end of the target transition data.

16. An information processing method comprising: calculating target transition data representing a transition in the value of an index relating to the state of a target storage battery based on measurement data relating to the target storage battery; and estimating the timing at which the target event will occur in the target storage battery based on the target transition data and at least one reference transition data representing a reference transition in the value of the index relating to the state of the storage battery during a period from a first time to a second time at which a target event will occur in the storage battery.

17. A computer program for causing a computer to execute the steps of: calculating target trend data representing the trend in the value of an index relating to the state of a target storage battery based on measurement data relating to the target storage battery; and estimating the timing at which the target event will occur in the target storage battery based on the target trend data and at least one reference trend data representing the reference trend in the value of the index relating to the state of the storage battery during the period from a first time to a second time at which a target event will occur in the storage battery.

18. An information processing system comprising: a target storage battery; and a processing unit that calculates target trend data representing the trend of an index value related to the state of the target storage battery based on measurement data related to the target storage battery; and estimates the timing at which the target event will occur in the target storage battery based on the target trend data and at least one reference trend data representing a reference trend of the index value related to the state of the storage battery during a period from a first time to a second time at which a target event will occur in the storage battery.