JP2017075921A - Storage battery deterioration estimation system, storage battery deterioration estimation method, and storage battery deterioration estimation program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To allow the deterioration state of a storage battery to be appropriately estimated even when the storage battery discharges at an actual load for a prescribed time.SOLUTION: A storage battery management device 3 measures discharge data including discharge current and voltage at the time of discharge end when battery packs 20 discharge to a load facility 102 for a prescribed time and transmits the data to a monitoring device 5. The monitoring device 5 comprises: a discharge database 52 for storing the discharge data; an analysis task 55 for performing quantile point regression analysis at a prescribed quantile point of a discharge rate indicative of the ratio of the discharge current to the capacity of the battery pack 20 and the voltage at the time of discharge end on the basis of the discharge data of each battery pack 20; and an extraction task 56 for extracting a battery pack 20 belonging to the prescribed quantile point or below on the basis of a result of the analysis.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a storage battery deterioration estimation system that estimates a deterioration state of a storage battery, a storage battery deterioration estimation method, and a storage battery deterioration estimation program.

  Rechargeable batteries and secondary batteries such as sealed lead-acid batteries and lithium-ion secondary batteries are replaced with new ones when their capacity drops below the specified capacity as the years of use decrease. There is a need to. In addition, the expected life of the storage battery is presented by the manufacturer of the storage battery, but the actual life of the storage battery is affected by the use environment, use conditions, and the like. For this reason, in actual operation, it is necessary to know how much the storage battery capacity is at the present time, and to predict the period and remaining life until the end of the life, and to formulate a plan for replacing the storage battery, etc. .

  On the other hand, in order to know the storage battery capacity at the present time accurately, it is necessary to perform a discharge test. However, it takes a long time to discharge the storage battery to the discharge end voltage (the voltage at which discharge should be terminated in the specification). During this time, the storage battery cannot be used. That is, in the case of a storage battery used as a backup power source such as UPS (Uninterruptable Power Supply), the function as the backup power source is lost during the discharge test. For this reason, a method is known in which the storage battery is discharged for a short time without discharging the storage battery to the end-of-discharge voltage, the terminal voltage of the storage battery is measured, and the storage battery capacity from the change of the measured voltage to the end-of-discharge voltage is estimated. (For example, refer to Patent Document 1).

  In addition, a storage battery connected in parallel to a rectifier that supplies DC power to a load facility (operation target facility) and used as a backup power source for the load facility can be realized by reducing the output voltage of the rectifier. The deterioration is determined by discharging with a load (discharge current to be supplied to the load equipment). At this time, because the actual load (discharge current) of each storage battery is different, it is necessary to prepare for backup in the event of a power failure, and furthermore, it is necessary to operate and manage a huge amount of storage battery, etc. A determination method of determining “abnormal” when a predetermined voltage has been reached is adopted. Here, the predetermined time and the predetermined voltage are set based on the capacity and actual load of the storage battery.

JP-A-10-040967

  By the way, in the conventional determination method, it is determined as “abnormal” only when the predetermined voltage is reached by a predetermined time, and “normal” is determined when the predetermined voltage is not reached by the predetermined time. However, even when the predetermined voltage is not reached by the predetermined time, the storage battery may be deteriorated (capacity reduction). That is, when it is determined as “normal”, it cannot be estimated whether or not the storage battery is close to abnormality / deterioration. For this reason, it may be determined as “abnormal” at the next discharge, and a situation in which the storage battery must be replaced urgently may occur.

  Accordingly, an object of the present invention is to provide a storage battery deterioration estimation system, a storage battery deterioration estimation method, and a storage battery deterioration estimation program capable of appropriately estimating the deterioration state of the storage battery even when the storage battery is discharged for a predetermined time with an actual load. And

  In order to achieve the above object, according to the first aspect of the present invention, a monitoring device for monitoring a plurality of storage batteries and a storage battery management device arranged in each storage battery are connected to be able to communicate, and each storage battery management device is connected. Measures the discharge data including the discharge current and the voltage at the end of discharge when the storage battery is discharged to the load facility for a predetermined time and transmits it to the monitoring device, and the monitoring device stores the discharge data Based on the discharge data of each storage battery stored in the storage means and the storage means, the discharge rate indicating the ratio of the discharge current to the capacity of the storage battery and the voltage at the end of discharge are divided at a predetermined quantile point. A storage battery deterioration estimation system comprising: analysis means for performing regression analysis of points; and extraction means for extracting storage batteries belonging to the predetermined quantile or lower based on an analysis result by the analysis means. A.

  According to this invention, when each storage battery is discharged to the load facility for a predetermined time, the corresponding storage battery management device measures discharge data including the discharge current and the discharge end voltage and transmits it to the monitoring device. The storage unit stores and accumulates discharge data. Based on the stored discharge data, the monitoring device performs the quantile regression analysis on the discharge rate and the discharge end voltage at a predetermined quantile by the analyzing unit, and on the basis of the analysis result, the extracting unit performs a predetermined regression analysis. The storage batteries belonging to the quantile below are extracted.

  According to a second aspect of the present invention, in the storage battery deterioration estimation system according to the first aspect, the predetermined time includes a first predetermined time which is a discharge time when discharging only a predetermined discharge amount, and a discharge amount. A second predetermined time that is a non-related fixed time, and the analysis means includes a first group that is a group of storage batteries discharged for the first predetermined time, and a storage battery that is discharged for the second predetermined time. The analysis is performed on each of the second group which is a group.

  The invention according to claim 3 is characterized in that, in the storage battery deterioration estimation system according to claim 1 or 2, the predetermined quantile can be changed to an arbitrary value.

  The invention according to claim 4 stores discharge data including a discharge current and a voltage at the end of discharge when a plurality of storage batteries are discharged to each load facility for a predetermined time, and discharges the stored storage batteries. Based on the data, the discharge rate indicating the ratio of the discharge current to the capacity of the storage battery and the voltage at the end of discharge are quantized at a predetermined quantile, and based on the analysis result, the predetermined A storage battery inferior estimation method for extracting storage batteries belonging to a quantile or lower.

  According to a fifth aspect of the present invention, in the storage battery deterioration estimation method according to the fourth aspect of the present invention, the predetermined time includes a first predetermined time that is a discharge time when discharging only a predetermined discharge amount, and a discharge amount. And a second group of storage batteries discharged only for the second predetermined time, and a second group of storage batteries discharged for the first predetermined time. The above analysis is performed on each of the groups.

  According to a sixth aspect of the present invention, there is provided a storage means for storing discharge data including a discharge current and a discharge end voltage when a plurality of storage batteries are discharged to each load facility for a predetermined time. Based on the discharge data of each storage battery stored in the means, an analysis for performing a quantile regression analysis on a discharge rate indicating a ratio of the discharge current to the capacity of the storage battery and a voltage at the end of discharge at a predetermined quantile point And a storage battery deterioration estimation program for functioning as an extraction means for extracting a storage battery belonging to the predetermined quantile or lower based on an analysis result by the analysis means.

  According to a seventh aspect of the present invention, in the storage battery deterioration estimation program according to the sixth aspect, the predetermined time includes a first predetermined time that is a discharge time when discharging only a predetermined discharge amount, and a discharge amount. A second predetermined time that is a non-related fixed time, and the analysis means includes a first group that is a group of storage batteries discharged for the first predetermined time, and a storage battery that is discharged for the second predetermined time. The analysis is performed on each of the second group which is a group.

  According to the first, fourth, and sixth aspects of the present invention, the discharge rate and the discharge end voltage when a plurality of storage batteries are discharged for a predetermined time (with an actual load) to each load facility are divided. Since the rank regression analysis is performed and the storage batteries belonging to a predetermined quantile or less are extracted, it is possible to appropriately estimate the deterioration state of the storage battery. That is, when the predetermined quantile is, for example, 1%, storage batteries belonging to 1% or less of the whole, that is, storage batteries that are more specific and more likely to be deteriorated (decrease in capacity) than many other storage batteries. Can be extracted. For this reason, even if it determines with such a storage battery being "normal" by the conventional determination method, it becomes possible to estimate that it is a thing close | similar to abnormality and deterioration.

  At this time, although the actual load and discharge current at the time of discharge differ in each storage battery, the discharge rate indicating the ratio of the discharge current to the capacity of the storage battery and the voltage at the end of discharge are analyzed by quantile regression, so even if the discharge current is different It becomes possible to estimate the deterioration state of each storage battery appropriately. And since the deterioration state of a storage battery can be estimated appropriately in this way, it becomes possible to perform maintenance, replacement, etc. of the storage battery appropriately, early and systematically.

  According to the invention of claim 2, claim 5 and claim 7, the quantile regression is performed for the storage battery group discharged for the first predetermined time and the storage battery group discharged for the second predetermined time, respectively. Since a storage battery is extracted by analysis, it is possible to extract a storage battery that is highly likely to be deteriorated from a group of storage batteries that have been discharged for the same time even when the discharge times are different.

  According to the invention described in claim 3, since the predetermined quantile can be changed to an arbitrary value, the predetermined quantile is desired in accordance with the deterioration criterion, the age of the storage battery, the characteristics of the storage battery, and the like. By setting to this value, it becomes possible to more appropriately extract a storage battery having a high possibility of deterioration.

It is a schematic block diagram which shows the storage battery deterioration estimation system which concerns on embodiment of this invention. It is a figure which shows the voltage change in the deterioration estimation test in the storage battery deterioration estimation system of FIG. It is a schematic block diagram of the monitoring apparatus of the storage battery deterioration estimation system of FIG. It is a figure which shows the analysis result with respect to the 3-hour discharge group by the analysis task of the monitoring apparatus of FIG. It is a figure which shows the analysis result with respect to the 30% discharge group by the analysis task of the monitoring apparatus of FIG. It is a flowchart which shows the storage battery deterioration estimation method by the storage battery deterioration estimation system of FIG.

  The present invention will be described below based on the illustrated embodiments.

  FIG. 1 is a schematic configuration diagram showing a storage battery deterioration estimation system 1 according to an embodiment of the present invention. This storage battery deterioration estimation system 1 is a system that estimates the deterioration state (capacity reduction state) of a storage battery. In this embodiment, a plurality of cells (for example, 23 cells) 2 (for example, 23 cells) are connected in series. Assume that the connected assembled battery 20 as a whole is a storage battery to be estimated, and the assembled battery 20 is disposed at each of a plurality of sites R. Further, it is assumed that the nominal voltages of the assembled batteries 20 are the same.

  Each site R is located at a remote location from the monitoring center C. In the monitoring center C, a monitoring device 5 for monitoring each assembled battery 20 is installed, and in each assembled battery 20, a storage battery management device 3 is arranged. The monitoring device 5 and each storage battery management device 3 are communicably connected via a communication network NW. Here, the site R and the assembled battery 20 have an enormous number (for example, several thousand to several tens of thousands), and are numbers that can appropriately perform the quantile regression analysis described later. The case where the some assembled battery 20 and the storage battery management apparatus 3 are arrange | positioned is included.

  Furthermore, in this embodiment, the case where a sealed lead-acid battery that functions as a backup power source for the load facility 102 such as a communication device is the target storage battery will be mainly described below. Each assembled battery 20 is connected to the rectifier 4, and the electric power from the commercial power supply 101 is converted into direct current by the rectifier 4 and supplied to the assembled battery 20, so that the assembled battery 20 is charged. Further, the load facility 102 is connected to the rectifier 4, and DC power is supplied to the load facility 102 in the same manner. When the commercial power source 101 is powered off, DC power is supplied from the assembled battery 20 to the load facility 102. ing. Here, the load facility 102 is a facility that operates by supplying power from the rectifier 4 or the assembled battery 20, and excludes facilities for performing capacity tests on the storage battery.

  The rectifier 4 at each site R has a function of measuring a charging current value and a discharging current value with respect to the assembled battery 20, and is connected to the monitoring device 5 via a communication network NW so as to be communicable. Moreover, the rectifier 4 memorize | stores the date (discharge schedule) which discharges the assembled battery 20 experimentally, and will reduce an output voltage, if this date is reached. Thereby, the assembled battery 20 connected in parallel is discharged with respect to the load equipment 102, a deterioration estimation test is performed, and the rectifier 4 transmits the discharge current value to the monitoring device 5.

  The storage battery management device 3 is a device that constantly measures the voltage of each cell 2 in the assembled battery 20 and has the same configuration as a known and existing storage battery management device. That is, the voltage of each cell 2 and the total voltage of the assembled battery 20 are constantly measured, and when the measured voltage value is outside a predetermined appropriate voltage range, the abnormality detection result is transmitted / notified to the monitoring device 5. Moreover, the temperature (ambient temperature) of the assembled battery 20 is always measured, and the function which transmits measured temperature to the monitoring apparatus 5 regularly is provided. Furthermore, when the deterioration estimation test is performed, a function of transmitting to the monitoring device 5 the voltage value of each cell 2 at the end of the test (discharge end voltage) and the total voltage value of the assembled battery 20 (discharge end voltage). It has.

  Thus, in this embodiment, the rectifier 4 transmits the discharge current (current value) at the time of the deterioration estimation test to the monitoring device 5, and the storage battery management device 3 has the voltage at the end of discharge (voltage value) at the time of the deterioration estimation test. Is transmitted to the monitoring device 5. That is, the rectifier 4 functions as a part of the storage battery management device 3, and the rectifier 4 and the storage battery management device 3 measure discharge data including the discharge current and the voltage at the end of discharge and transmit it to the monitoring device 5. In contrast, the total discharge data may be measured only by the storage battery management device 3 and transmitted to the monitoring device 5. Further, as will be described later, the discharge data includes a determination result measured / determined by the storage battery management device 3 or the rectifier 4, a discharge start voltage, a discharge start date and time, and the like.

  Here, in the degradation estimation test, the assembled battery 20 is discharged for a predetermined time with an actual load (current value corresponding to the actual load) to the load facility 102 and reaches a predetermined voltage by a predetermined time (test time). Is determined as “abnormal”. The predetermined time and the predetermined voltage are set based on the capacity of the assembled battery 20 (cell 2), the actual load, and the like, and the predetermined time is a discharge time when discharging by a predetermined discharge amount. And a second predetermined time which is a fixed time regardless of the discharge amount.

  Specifically, the first predetermined time is calculated and set to a time (30% discharge time) when 30% of the capacity (rated capacity, normal capacity) of the assembled battery 20 is discharged, and the second predetermined time is set. The time is set / selected to 3 hours or 1 hour depending on the actual load / discharge current (discharge rate). A short time out of the first predetermined time or the second predetermined time is defined as a predetermined time (test time). Here, the discharge when the test time is the first predetermined time is “30% discharge”, the discharge when the second predetermined time is 3 hours is “3 hour discharge”, and the second predetermined time is 1 hour. The discharge in this case is referred to as “1 hour discharge”.

  In this deterioration estimation test, as shown in FIG. 2, before the test, the output voltage of the rectifier 4 and the total voltage / terminal voltage of the assembled battery 20 are the same float charging voltage Vf. When Vr decreases, the assembled battery 20 starts discharging. When the total voltage V1 of the assembled battery 20 does not reach the predetermined voltage (test stop voltage) Vs by the predetermined time (test time), it is determined as “normal” in this test, and the total voltage when the test time is reached. The value of V1 becomes the voltage at the end of discharge (test end voltage), and the test time becomes the discharge time. On the other hand, when the total voltage V2 of the assembled battery 20 reaches the predetermined voltage Vs by a predetermined time, it is determined as “abnormal” in this test, and the value of the predetermined voltage Vs becomes the voltage at the end of discharge, and becomes the predetermined voltage Vs. The time to reach is the discharge time.

  After the test, the output voltage of the rectifier 4 is restored to the float charging voltage Vf, and the assembled battery 20 is charged. Here, the reference symbol Vt in FIG. 2 is the lowest usable voltage at which the assembled battery 20 can be discharged.

  When such a deterioration estimation test is completed, as described above, the identification information, determination result, discharge current, discharge start voltage, discharge end voltage, ambient temperature, discharge start date and time and discharge end date and time of the assembled battery 20 are included. Discharge data is transmitted from the rectifier 4 and the storage battery management device 3 to the monitoring device 5.

  The monitoring device 5 is a device that monitors the state of each assembled battery 20. In addition to the monitoring function, the monitoring device 5 mainly includes a battery database (battery information storage means) 51 and a discharge database (storage means) as shown in FIG. 52, a discharge rate task (discharge rate calculation means) 53, a classification task (classification means) 54, an analysis task (analysis means) 55, an extraction task (extraction means) 56, and a central processing unit that controls these 57.

  The battery database 51 is a database that stores information (storage battery data) related to each assembled battery 20 (cell 2). For each piece of identification information of the assembled battery 20, the rated capacity of the assembled battery 20, the number of cells 2, the age ( Manufacturing date), information of the installed site R, and the like are stored. The discharge database 52 is a database that stores discharge data, and stores and accumulates discharge data received from the rectifier 4 and the storage battery management device 3 at each site R.

  The tasks (storage battery deterioration estimation programs) 53 to 56 are task programs that are arbitrarily or periodically started in order to estimate the deterioration state of the assembled battery 20.

  The discharge rate task 53 is a program for calculating the discharge rate in each deterioration estimation test. The discharge rate indicating the ratio of the discharge current to the capacity (rated capacity, normal capacity) of the assembled battery 20 is expressed as “discharge current ÷ rated capacity”. Calculate according to the following formula. Specifically, the discharge data of the assembled battery 20 is acquired from the discharge database 52, the storage battery data of the assembled battery 20 is acquired from the battery database 51, and the discharge rate is calculated by dividing the discharge current by the rated capacity. . Furthermore, the discharge rate is converted to a standard temperature (for example, 25 ° C.) based on the temperature (ambient temperature) during the deterioration estimation test. Such calculation is performed for all discharge data / deterioration estimation tests stored in the discharge database 52.

  The classification task 54 includes a first group that is a storage battery group (discharge group) discharged for a first predetermined time and a storage battery group (discharge group) that is discharged for a second predetermined time. This is a program for classifying into two groups. That is, according to the discharge rate calculated in the discharge rate task 53, the discharge (test time) of each deterioration estimation test is 30% discharge (30% discharge time), 3 hour discharge, or 1 hour discharge.

  For example, the first predetermined time at 30% discharge (30% discharge time) is calculated according to the discharge rate, and the second predetermined time is determined to be 3 hours or 1 hour according to the discharge rate. Alternatively, a short time of the second predetermined time is set as the test time. Alternatively, according to the discharge time depending on the difference between the discharge start date and time and the discharge end date and time, it is classified as 30% discharge or 3 hour discharge. Such classification is performed for all deterioration estimation tests. Here, the storage battery group of 30% discharge is referred to as “30% discharge group” (first group), the storage battery group of 3 hour discharge is referred to as “3 hour discharge group” (second group), and the storage battery group of 1 hour discharge is referred to as Let it be a “1-hour discharge group” (second group).

  Based on the discharge data of each assembled battery 20 stored in the discharge database 52, the analysis task 55 calculates a discharge rate indicating the ratio of the discharge current to the capacity (rated capacity, normal capacity) of the assembled battery 20 and the voltage at the end of discharge. , A quantile regression analysis at a predetermined quantile. In other words, the discharge rate calculated in the discharge rate task 53 and the voltage at the end of discharge in the discharge data are analyzed for quantile regression at a predetermined quantile for all the degradation estimation tests, and the regression at the predetermined quantile is performed. Calculate a straight line. Here, the predetermined quantile can be changed / set to an arbitrary value, and a plurality of values can be set.

Specifically, quantile regression analysis is performed with the discharge rate as x and the voltage at the end of discharge as y. At this time, the formulation of quantile regression analysis is as follows.

  Then, a predetermined quantile τ is set, thereby obtaining a regression line / regression function. For example, as shown in FIGS. 4 and 5, if the quantile τ is 0.01, the 1% regression lines L1 and L11 are calculated, and if the quantile τ is 0.05, the 5% regression lines L2 and L12 are calculated. When the quantile τ is 0.5, 50% regression lines L3 and L13 are calculated. In this embodiment, it is assumed that two quantile points of 0.01 and 0.05 are set.

  Such an analysis task 55 performs an analysis on a first group that is a storage battery group that has been discharged for a first predetermined time and a second group that is a storage battery group that has been discharged for a second predetermined time. . That is, in this embodiment, a regression line is calculated by performing quantile regression analysis with three quantiles for each of the 30% discharge group, the 3-hour discharge group, and the 1-hour discharge group. Here, FIG. 4 shows the analysis result of the 3-hour discharge group, and FIG. 5 shows the analysis result of the 30% discharge group.

  The extraction task 56 is a program that extracts the assembled batteries 20 belonging to a predetermined quantile or lower based on the analysis result by the analysis task 55. That is, in this embodiment, the predetermined quantiles are 0.01 and 0.05, the quantiles below 0.01 (the lower 1% or less of the whole) are warning areas, and the quantiles are 0.05. The attention area is below the point (less than 5% of the total). For example, in the 3-hour discharge group of FIG. 4, the assembled battery 20 belonging to 1% regression line L1 or less (the voltage at the end of discharge is L1 or less) is extracted and used as a warning target battery, and 5% regression line L2 or less (discharge) The assembled battery 20 belonging to the end-time voltage of L2 or less) is extracted and set as a caution target battery.

  Furthermore, the storage battery data of the assembled battery 20 of the warning target battery is acquired from the battery database 51, and the storage battery data is output as a warning target to a display or other equipment. Similarly, the storage battery data of the assembled battery 20 of the caution target battery is acquired from the battery database 51, and the storage battery data is output as a caution target to a display or other equipment. Such an extraction task 56 performs extraction for the first group and the second group, that is, in the 30% discharge group, the 3-hour discharge group, and the 1-hour discharge group, respectively.

  Next, an operation of the storage battery deterioration estimation system 1 having such a configuration, a storage battery deterioration estimation method by the storage battery deterioration estimation system 1, and the like will be described.

  First, each time a deterioration estimation test is performed on the assembled battery 20, the discharge current from the rectifier 4, the voltage at the end of discharge from the storage battery management device 3, and the like are sequentially transmitted to the monitoring device 5 as discharge data. Stored and accumulated (storage step).

  Next, when the monitoring device 5 is instructed and input to execute the deterioration estimation of the battery pack 20 (storage battery deterioration estimation program), as shown in FIG. 6, first, discharge data is obtained from the discharge database 52 (step S1). ), The discharge rate in each deterioration estimation test is calculated by the discharge rate task 53 (step S2). Subsequently, the classification task 54 classifies each deterioration estimation test into a 30% discharge group, a 3-hour discharge group, or a 1-hour discharge group (step S3).

  Next, for each of the 30% discharge group, the 3-hour discharge group, and the 1-hour discharge group, the analysis task 55 performs a quantile regression analysis at a predetermined quantile with respect to the discharge rate and the discharge end voltage. A regression line at the quantile is calculated (step S4, analysis step). Subsequently, the battery pack 20 belonging to a predetermined quantile or lower is extracted by the extraction task 56 (step S5, extraction step). Then, the storage battery data of the assembled battery 20 to be warned and cautioned is output to a display or other equipment.

  As described above, according to the storage battery deterioration determination system 1 and the storage battery deterioration determination method, the discharge rate and the discharge end when the plurality of assembled batteries 20 are discharged for a predetermined time (with an actual load) to each load facility 102. Since the assembled battery 20 belonging to the predetermined quantile or lower is extracted by performing the quantile regression analysis on the hourly voltage, the deterioration state of the assembled battery 20 can be appropriately estimated. That is, when the predetermined quantile is 1%, for example, the assembled battery 20 belonging to 1% or less of the whole, that is, there is a possibility that it is peculiar and deteriorated (capacity reduction) compared to many other assembled batteries 20. Can be extracted. For this reason, even if such an assembled battery 20 is determined as “normal” by the conventional determination method, it is possible to estimate that the assembled battery 20 is close to abnormality / deterioration.

  At this time, the actual load / discharge current at the time of discharge is different in each assembled battery 20, but the discharge rate indicating the ratio of the discharge current to the rated capacity of the assembled battery 20 and the voltage at the end of discharge are subjected to quantile regression analysis. Even if the currents are different, the deterioration state of each assembled battery 20 can be estimated appropriately. And since the deterioration state of a storage battery can be estimated appropriately in this way, it becomes possible to perform maintenance, replacement, etc. of the storage battery appropriately, early and systematically.

  Also, for the first group discharged for the first predetermined time and the second group discharged for the second predetermined time, that is, for the 30% discharge group, the 3 hour discharge group and the 1 hour discharge group. The assembled battery 20 is extracted by the quantile regression analysis. For this reason, even when the discharge times are different, it is possible to extract the assembled battery 20 that is highly likely to be deteriorated from the group of assembled batteries 20 that have been discharged for the same time.

  In addition, the first predetermined time is set to a discharge time when discharging by a predetermined discharge amount, the second predetermined time is set to a fixed time regardless of the discharge amount, and the shorter of the two times is the test time. It has become. For this reason, when the test time is the first predetermined time, it is possible to perform a more accurate estimation by discharging only a uniform discharge amount. When the test time is the second predetermined time, an excessive amount is obtained. It becomes possible to cope with actual discharge and backup in the event of a power failure by preventing discharge.

  In addition, since the predetermined quantile can be changed to an arbitrary value, the predetermined quantile is set to a desired value according to the deterioration criterion, the age of the assembled battery 20, the characteristics of the assembled battery 20, and the like. Thus, it becomes possible to more appropriately extract the assembled battery 20 having a high possibility of deterioration. Moreover, since the predetermined quantile can be set to a plurality of values, the assembled battery 20 belonging to a plurality of areas, for example, the assembled battery 20 belonging to the warning area and the assembled battery 20 belonging to the attention area as described above can be simultaneously used. It can be extracted and is very convenient.

  Although the embodiment of the present invention has been described above, the specific configuration is not limited to the above embodiment, and even if there is a design change or the like without departing from the gist of the present invention, Included in the invention. For example, in the above embodiment, the entire assembled battery 20 is the storage battery to be estimated, but the unit battery (each cell 2 or the like) may be the storage battery to be estimated. Of course, the present invention can be applied not only to sealed lead-acid batteries but also to other storage batteries such as lithium ion secondary batteries.

  In addition, the deterioration estimation is performed by performing quantile regression analysis on the entire deterioration estimation test / all batteries 20 stored in the discharge database 52, but only for a predetermined / desired deterioration estimation test or the like. For example, the deterioration estimation may be performed only for the deterioration estimation test performed in a predetermined period or the assembled battery 20 having a predetermined age. Furthermore, the assembled battery 20 determined as “abnormal” in the deterioration estimation test may be excluded from the deterioration estimation targets.

On the other hand, instead of providing the monitoring device 5 with the analysis task 55, the extraction task 56, etc., the following storage battery deterioration estimation program may be installed in a general-purpose computer.
Computer
Storage means (discharge database 52) for storing discharge data including a discharge current and a voltage at the end of discharge when a plurality of storage batteries are discharged to each load facility 102 for a predetermined time;
Based on the discharge data of each storage battery stored in the storage means, an analysis means (analysis) that performs a regression analysis of the discharge rate indicating the ratio of the discharge current to the capacity of the storage battery and the voltage at the end of discharge at a predetermined quantile. Task 55),
Extraction means (extraction task 56) for extracting storage batteries belonging to a predetermined quantile or lower based on the analysis result by the analysis means;
Storage battery deterioration estimation program to function as.

  Further, in the storage battery deterioration estimation program analysis means and extraction means, analysis and extraction are performed for the first group and the second group, that is, in the 30% discharge group, the 3-hour discharge group, and the 1-hour discharge group, respectively. May be performed.

1 Storage battery deterioration judgment system 2 cells (storage battery)
20 battery pack 3 storage battery management device 4 rectifier (storage battery management device)
5 Monitoring device 51 Battery database (battery information storage means)
52 Discharge database (storage means)
53 Discharge rate task (discharge rate calculation means)
54 Classification tasks (classification means)
55 Analysis Task (Analysis Means)
56 Extraction task (extraction means)
101 Commercial power supply 102 Load facility NW communication network C Monitoring center R Site

Claims (7)

A monitoring device that monitors a plurality of storage batteries and a storage battery management device disposed in each storage battery are connected to be freely communicable,
Each of the storage battery management devices measures discharge data including a discharge current and a voltage at the end of discharge when the storage battery is discharged to a load facility for a predetermined time, and transmits to the monitoring device,
The monitoring device
Storage means for storing the discharge data;
Based on the discharge data of each storage battery stored in the storage means, the discharge rate indicating the ratio of the discharge current to the capacity of the storage battery and the voltage at the end of discharge are quantized at a predetermined quantile. Analysis means to
An extraction means for extracting a storage battery belonging to the predetermined quantile or lower based on an analysis result by the analysis means,
A storage battery deterioration estimation system characterized by that. The predetermined time includes a first predetermined time that is a discharge time when discharging only a predetermined discharge amount, and a second predetermined time that is a fixed time regardless of the discharge amount,
The analysis means performs the analysis on a first group that is a storage battery group that has been discharged for the first predetermined time and a second group that is a storage battery group that has been discharged for the second predetermined time. ,
The storage battery deterioration estimation system according to claim 1. The predetermined quantile can be changed to an arbitrary value.
The storage battery deterioration estimation system according to any one of claims 1 and 2. When a plurality of storage batteries are discharged to each load facility for a predetermined time, discharge data including a discharge current and a discharge end voltage is stored,
Based on the stored discharge data of each storage battery, a discharge rate indicating the ratio of the discharge current to the capacity of the storage battery and the voltage at the end of the discharge are quantized at a predetermined quantile,
Based on the analysis result, a storage battery belonging to the predetermined quantile or lower is extracted.
The storage battery deterioration estimation method characterized by the above-mentioned. The predetermined time includes a first predetermined time that is a discharge time when discharging only a predetermined discharge amount, and a second predetermined time that is a fixed time regardless of the discharge amount,
The analysis is performed for each of a first group that is a storage battery group discharged for the first predetermined time and a second group that is a storage battery group that is discharged for the second predetermined time.
The storage battery deterioration estimation method according to claim 4. Computer
Storage means for storing discharge data including a discharge current and a discharge end voltage when a plurality of storage batteries are discharged to each load facility for a predetermined time;
Based on the discharge data of each storage battery stored in the storage means, the discharge rate indicating the ratio of the discharge current to the capacity of the storage battery and the voltage at the end of discharge are quantized at a predetermined quantile. Analysis means to
Extraction means for extracting a storage battery belonging to the predetermined quantile or lower based on an analysis result by the analysis means;
Storage battery deterioration estimation program to function as. The predetermined time includes a first predetermined time that is a discharge time when discharging only a predetermined discharge amount, and a second predetermined time that is a fixed time regardless of the discharge amount,
The analysis means performs the analysis on a first group that is a storage battery group that has been discharged for the first predetermined time and a second group that is a storage battery group that has been discharged for the second predetermined time. ,
The storage battery deterioration estimation program according to claim 6.

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