JP2021058017A - Estimation device, estimation method, and computer program - Google Patents

Abstract

To provide an estimation device, an estimation method, and a computer program capable of accurately estimating the deterioration of a power storage element.SOLUTION: An estimation device 4 includes a first acquisition unit 41 that acquires SOC time-series data in a power storage element, a second acquisition unit 41 that acquires the shape change of the power storage element, a specific unit 41 that specifies a representative value of SOC in a predetermined period of the time-series data, and a SOC fluctuation amount per unit time, and an estimation unit 41 that estimates deterioration of the power storage element on the basis of the specified representative value, the SOC fluctuation amount, and the acquired shape change.SELECTED DRAWING: Figure 8

Description

The present invention relates to an estimation device, an estimation method, and a computer program for estimating deterioration of a power storage element.

A power storage element that can store electrical energy and supply energy as a power source when needed is used. The power storage element is applied to portable equipment, power supply equipment, transportation equipment including automobiles and railways, industrial equipment including aerospace and construction equipment, and the like.
A power storage element (hereinafter referred to as a battery) such as a lithium ion secondary battery gradually deteriorates due to repeated charging and discharging. One of the deteriorations is an increase in the thickness of the case containing the element due to an increase in the internal pressure due to the generation of gas inside the battery, a change in the volume of the active material, a change in the shape of the separator, and the like.

Easily and accurately estimating the SOH (State of Health: capacity retention rate, resistance value, etc.) of a battery is an important issue in determining whether or not a battery can be used and how to use it.
Many techniques for estimating the SOH of a battery have been developed. Based on the past usage history data, a method having high accuracy but requiring a long time for estimation, a high cost method, a simple method having low estimation accuracy, and the like are used, which has a problem.

In the deterioration diagnosis method of Patent Document 1, the thickness W at the time of charging and discharging of the secondary battery is measured, and the thickness characteristic expressed as the relationship between the thickness W and the voltage V (or the amount of charge Q) is acquired, and the thickness W is obtained. _{The voltage V W} (or Q _W ), which is the voltage (or the amount of charge) that starts to increase, is calculated as the feature amount. Then, the capacity deterioration of the secondary battery is diagnosed by comparing with the deterioration characteristics of the voltage V _W (or Q _W).

Japanese Unexamined Patent Publication No. 2015-60761

In the deterioration diagnosis method of Patent Document 1, the use of the battery is stopped and the thickness W of the battery is obtained, and there is a problem that the deterioration cannot be estimated at all times during the use of the battery. Further, it is desired to improve the accuracy of estimation of deterioration including the case where the fluctuation pattern of SOC (State Of Charge) is complicated.

An object of the present invention is to provide an estimation device, an estimation method, and a computer program capable of accurately estimating deterioration of a power storage element.

The estimation device according to one aspect of the present invention includes a first acquisition unit that acquires SOC time-series data in the power storage element, a second acquisition unit that acquires the shape change of the power storage element, and the time-series data in a predetermined period. A specific unit that specifies a representative value of SOC and an amount of SOC fluctuation, and an estimation unit that estimates deterioration of the power storage element based on the specified representative value, the amount of SOC fluctuation, and the acquired shape change. To be equipped.

In the estimation method according to one aspect of the present invention, the SOC time series data of the power storage element is acquired, the shape change of the power storage element is acquired, the representative value of the SOC in the predetermined period of the time series data, and the SOC fluctuation amount. Is specified, and the deterioration of the power storage element is estimated based on the specified representative value, the SOC fluctuation amount, and the acquired shape change.

A computer program according to one aspect of the present invention acquires SOC time-series data in a power storage element, acquires a shape change of the power storage element, and includes a representative value of SOC in a predetermined period of the time-series data and an SOC fluctuation amount. Is specified, and the computer is made to execute a process of estimating the deterioration of the power storage element based on the specified representative value, the SOC fluctuation amount, and the acquired shape change.

In the present invention, the deterioration of the power storage element can be estimated with high accuracy.

It is a graph which shows the relationship between the thickness increase amount and the capacity decrease rate at the time of leaving a battery by changing the average SOC and the temperature of a battery. It is a graph which shows the relationship between the thickness increase amount and the capacity decrease rate at the time of performing the charge / discharge cycle test by changing the average SOC and the temperature. It is a graph which shows the relationship between the thickness increase amount and the capacity decrease rate at the time of performing the charge / discharge cycle test by changing the SOC fluctuation amount per unit time. It is a block diagram which shows the structure of the charge / discharge system and the server which concerns on Embodiment 1. FIG. It is a perspective view of a battery module. It is a block diagram which shows the structure of BMU. It is a graph which shows the relationship between the thickness increase amount and the measured capacity decrease rate. It is a graph which shows the result of having obtained the relationship between the SOC fluctuation amount and the coefficient k for each temperature, and for each average SOC. It is a flowchart which shows the procedure of the calculation process of the capacity reduction rate by a control unit. It is a graph which shows the relationship between time and SOC of a predetermined period, and the relationship between time and temperature. It is a frequency map of SOC. It is a graph which shows the relationship between the elapsed time and the capacity decrease rate.

(Outline of Embodiment)
The estimation device according to the embodiment includes a first acquisition unit that acquires SOC time-series data in the power storage element, a second acquisition unit that acquires the shape change of the power storage element, and a representative of SOC in a predetermined period of the time-series data. It includes a specific unit that specifies a value and an SOC fluctuation amount, and an estimation unit that estimates deterioration of the power storage element based on the specified representative value, the SOC fluctuation amount, and the acquired shape change.

Here, the representative value of SOC means an average value, a center value, a mode value, a minimum value, a maximum value, or the like of SOC in a predetermined period of time series data.
Here, the shape change is the amount of displacement such as swelling of the electrode body or element, the amount of displacement of the case (either closed type or open type) accommodating the electrode body or element, and the force spreading outward (reaction force). Or a change in the pressure applied to at least one surface of the power storage element, or a combination thereof.
Examples of the case for accommodating include a square case, a cylindrical case, a pouch laminated film, and the like.
Deterioration of the power storage element can be estimated by acquiring the shape change regardless of whether the power storage element is completely restrained, free, or in the intermediate state.
The SOC fluctuation amount means the integrated value (total SOC) of the SOC fluctuation amount, and corresponds to the number of cycles.

The change in the shape of the power storage element has a strong correlation with the change in the capacity of the power storage element. The present inventors have found that when the use of the power storage element is stopped, the amount of change in SOH with respect to the amount of thickness increase differs depending on the representative SOC. It was also found that when the amount of change in SOC is the same when the power storage element is used, the amount of change in SOH differs depending on the representative SOC. It was found that when the representative SOCs are the same, the amount of change in SOH differs depending on the amount of SOC fluctuation. That is, it has been found that when estimating the deterioration of the power storage element, it is necessary to consider the representative value of SOC and the amount of SOC fluctuation, which are the characteristic values of the SOC time series data.

According to the above configuration, deterioration of the power storage element is estimated based on the representative value and the SOC fluctuation amount, which are characteristic values of the SOC time series data, and the acquired shape change of the power storage element. Deterioration at any time point can be easily and accurately estimated during use of the power storage element, including when the SOC fluctuation pattern is complicated.

The information required for estimation is the feature value and the shape change of the power storage element, and it is not necessary to use a large measuring device such as a charging / discharging device, and the labor and cost can be suppressed. When the load pattern of the power storage element is roughly determined in advance, the estimated central SOC, SOC fluctuation amount, and average temperature are known in advance, so that the SOH can be estimated only from the information on the shape change during operation. .. The SOH can be estimated from the information on the central SOC, the amount of SOC fluctuation, the average temperature, and the information on the shape change in the most frequently used load pattern.
Since deterioration can be estimated by changing the shape of the power storage element, deterioration of the power storage element can be constantly monitored simply by installing a sensor that detects the thickness or internal pressure, and the calculation of estimation can be simplified. BMU (Battery Management) Unit) can be simplified.

In the above-mentioned estimation device, the estimation unit refers to the relationship between the representative value, the SOC fluctuation amount, and the coefficient, specifies the coefficient based on the specified representative value, and the SOC fluctuation amount, and sets the specified coefficient. , The deterioration is estimated based on the acquired shape change.

According to the above configuration, the deterioration is estimated by referring to the relationship between the representative value, the SOC fluctuation amount, and the coefficient, and specifying the coefficient based on the specified representative value and the representative value, so that the estimation accuracy is good.

In the above-mentioned estimation device, a third acquisition unit for acquiring the temperature of the power storage element in the SOC region is provided, the specific unit specifies a temperature representative value based on the acquired temperature, and the estimation unit specifies. Deterioration of the power storage element is estimated based on the temperature representative value.

Examples of the temperature representative value include the average value, the mode value, the median value, etc. of the fluctuation range interval.
When the representative SOC and the SOC fluctuation amount are the same, the SOH change amount differs depending on the temperature.
According to the above configuration, when the temperature representative value such as the average temperature of the power storage element is not constant, the average temperature is specified based on the acquired temperature, and the deterioration of the power storage element is estimated accurately based on the average temperature. it can.

In the estimation method according to the embodiment, the SOC time series data of the power storage element is acquired, the shape change of the power storage element is acquired, and the representative value of the SOC in the predetermined period of the time series data and the SOC fluctuation amount are specified. , The deterioration of the power storage element is estimated based on the specified representative value, the SOC fluctuation amount, and the acquired shape change.

According to the above configuration, the deterioration of the power storage element is estimated based on the representative value and the SOC fluctuation amount which are the feature values of the SOC time series data, and the acquired shape change of the power storage element. Deterioration at any time point can be easily and accurately estimated during use of the power storage element, including when the SOC fluctuation pattern is complicated.

The computer program according to the embodiment acquires SOC time-series data in the power storage element, acquires a shape change of the power storage element, and specifies a representative value of SOC in a predetermined period of the time-series data and an SOC fluctuation amount. , The computer is made to execute a process of estimating the deterioration of the power storage element based on the specified representative value, the SOC fluctuation amount, and the acquired shape change.

According to the above configuration, the deterioration of the power storage element is estimated based on the representative value and the SOC fluctuation amount which are the feature values of the SOC time series data, and the acquired shape change of the power storage element. Deterioration at any time point can be easily and accurately estimated during use of the power storage element, including when the SOC fluctuation pattern is complicated.

Hereinafter, a method for estimating deterioration of the power storage element will be specifically described.
FIG. 1 is a graph showing the relationship between the amount of increase in thickness and the rate of decrease in capacity when the battery is left unattended with the average SOC and the temperature of the battery (battery module) changed. The horizontal axis is the thickness increase amount (%), and the vertical axis is the capacity decrease rate (%). When the average SOC is 25%, 50%, and 100%, respectively, the results of actual measurement of the relationship between the thickness increase and the capacity decrease rate when the battery temperature is 25 ° C, 35 ° C, and 45 ° C are obtained. Shown. When the average SOC was 100%, the relationship between the thickness increase amount and the capacity decrease rate when the temperatures were 5 ° C. and 15 ° C. was also determined.

From FIG. 1, it can be seen that the slope of the approximate curve of each measured point differs depending on the average SOC, and the slope of the approximate curve differs depending on the temperature even in the same average SOC.

FIG. 2 is a graph showing the relationship between the amount of increase in thickness and the rate of decrease in capacity when a charge / discharge cycle test is performed at different average SOCs and temperatures. The horizontal axis is the thickness increase amount (%), and the vertical axis is the capacity decrease rate (%). The results of the cycle test in the range of 0-25%, 50-75%, and 75-100% SOC with the battery temperature of 45 ° C. are shown. That is, the amount of SOC fluctuation per unit time is the same. The results of a cycle test with an SOC in the range of 75-100% at a temperature of 20 ° C. are also shown.

From FIG. 2, it can be seen that when the SOC fluctuation amount is the same, the slope of the approximate curve differs depending on the average SOC. When the average SOC and the amount of SOC fluctuation are the same, the slope of the approximate curve is larger when the environmental temperature is 20 ° C than when the environmental temperature is 45 ° C.

FIG. 3 is a graph showing the relationship between the thickness increase amount and the capacity decrease rate when the charge / discharge cycle test is performed by changing the SOC fluctuation amount. The horizontal axis is the thickness increase amount (%), and the vertical axis is the capacity decrease rate (%). The result of the cycle test in the range of SOC of 55-65% and 20-100% with the battery temperature of 45 ° C. is shown.
From FIG. 3, it can be seen that when the average SOC is the same, the slope of the approximate curve differs depending on the amount of SOC fluctuation. In the case of FIG. 3, the smaller the SOC fluctuation amount, the larger the slope of the approximate curve.

As described above, when the capacitance change is plotted against the thickness increase amount, the slope changes depending on the representative SOC such as the average SOC, the SOC fluctuation amount, and the temperature. The present inventors have found that by acquiring the representative SOC, SOC fluctuation amount, and temperature, specifying the inclination, and acquiring the shape change of the power storage element, the SOH can be easily estimated satisfactorily by the function of the shape change. , The present invention has been completed.

The estimation method according to the present embodiment acquires SOC time-series data in the power storage element and acquires a shape change of the power storage element. The representative value of SOC in a predetermined period of time series data and the amount of SOC fluctuation per unit time are specified, and the deterioration of the power storage element is determined based on the specified representative value and the amount of SOC fluctuation and the acquired shape change. presume.

(Embodiment 1)
Hereinafter, a case where the power storage element is a lithium ion secondary battery will be described.
FIG. 4 is a block diagram showing the configurations of the charge / discharge system 1 and the server 9 according to the first embodiment.
The charge / discharge system 1 includes a battery module 3, a BMU 4, a voltage sensor 5, a current sensor 6, a control device 7, a temperature sensor 8, a thickness sensor 11, and a pressure sensor 15. The charge / discharge system 1 may include either the thickness sensor 11 or the pressure sensor 15.

In the battery module 3, lithium ion secondary batteries (hereinafter referred to as cells) 2 as a plurality of power storage elements are connected in series. The control device 7 controls the entire charging / discharging system 1.
The server 9 includes a control unit 91 and a communication unit 92.
The control device 7 includes a control unit 71, a display unit 72, and a communication unit 73.
The control unit 71 of the control device 7 is connected to the control unit 91 via the communication unit 73, the network 10, and the communication unit 92.
The load 14 is connected to the battery module 3 via the terminals 12 and 13. When charging, a charger is connected to the battery module 3.

The control units 71 and 91 are composed of, for example, a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), and the like, and control the operations of the control device 7 and the server 9, respectively.
The communication units 73 and 92 have a function of communicating with other devices via the network 10, and can transmit and receive required information.
The display unit 72 of the control device 7 can be composed of a liquid crystal panel, an organic EL (Electro Luminescence) display panel, or the like. The control unit 71 controls the display unit 72 to display the required information.

In the present embodiment, any one of the BMU 4, the control device 7, and the server 9 functions as the estimation device of the present invention. If the server 9 does not function as an estimation device, the charge / discharge system 1 may not be connected to the server 9.
Although FIG. 4 shows a case where one set of battery modules 3 is provided, a plurality of sets of battery modules 3 may be connected in series.
The BMU 4 may be a battery ECU.

The voltage sensor 5 is connected in parallel to the battery module 3 and outputs a detection result according to the overall voltage of the battery module 3. The voltage sensor 5 is connected to the positive electrode terminal 23 and the negative electrode terminal 26 described later in each cell 2, _{measures the voltage V 1} between the terminals 23 and 26 of each cell 2, and V ₁ of each cell 2. The voltage V between the negative electrode lead 33 and the positive electrode lead 34, which will be described later, is detected in the battery module 3, which is the total value.
The current sensor 6 is connected in series with the battery module 3 and outputs a detection result according to the current of the battery module 3.
The temperature sensor 8 is provided in the vicinity of the battery module 3 and outputs a detection result according to the temperature of the battery module 3.

The thickness sensor 11 includes an X-ray CT device, a laser displacement sensor, a strain sensor (strain gauge), and the like. The thickness sensor 11 measures the thickness of the cell 2 of the battery module 3 in the parallel direction.
The pressure sensor 15 measures the pressing force of a pair of end plates (not shown) sandwiching the battery modules 3 in a parallel direction. When the internal pressure of the cell 2 increases due to deterioration, the compression force between the end plates increases. The pressure sensor 15 may measure a force (reaction force) spreading to the outside of the battery module 3 or a pressure applied to at least one surface of the battery module 3.

FIG. 5 is a perspective view of the battery module 3.
The battery module 3 includes a rectangular parallelepiped case 31 and a plurality of the cells 2 housed in the case 31.

The cell 2 includes a rectangular parallelepiped case body 21, a lid plate 22, terminals 23 and 26 provided on the lid plate 22, a burst valve 24, and an electrode body 25. The electrode body 25 is formed by laminating a positive electrode plate, a separator, and a negative electrode plate, and is housed in a case body 21.
The electrode body 25 may be obtained by winding a positive electrode plate and a negative electrode plate in a flat shape via a separator.

The positive electrode plate is a plate-shaped (sheet-shaped) or long strip-shaped metal foil made of aluminum, an aluminum alloy, or the like, in which an active material layer is formed on a positive electrode base material foil. The negative electrode plate is a plate-like (sheet-like) or long strip-shaped metal foil made of copper, a copper alloy, or the like, in which an active material layer is formed on a negative electrode base material foil. The separator is a microporous sheet made of synthetic resin.

Positive electrode active material used in the active material layer of the positive electrode, for example, _{Li x (Ni a Mn b Co} c M d) O 2 (M is Li, Ni, Mn, metal elements other than Co, 0 ≦ a <1,0 It is a layered oxide represented by ≦ b <1, 0 ≦ c <1, a + b + c + d = 1, 0 <x ≦ 1.1, and a and c are not 0 at the same time). The positive electrode active material has a layered rock salt type crystal structure. The a may satisfy 0.5 ≦ a ≦ 1. In this case, the transition metal site contains a large amount of Ni.
The positive electrode active material, a d = 0, is preferably a NCM represented by _{Li x (Ni a Co c Mn} b) O 2 (a + b + c = 1). The NCM may be NCM111 (a: b: c = 1: 1: 1), NCM523 (a: b: c = 5: 2: 3) having a high Ni content, or the like.
The positive electrode active material, M is Al, a b = 0, may be the NCA represented by _{Li x (Ni a Co c Al} d) O 2 (a + c + d = 1).
In NCM or NCA, the metal other than Li and Ni is not limited to the case where each metal is composed of two kinds of metals, and the metal may be composed of three or more kinds of metals. For example, a small amount of Ti, Nb, B, W, Zr, Ti, Mg and the like may be contained.

As the positive electrode active material, for example LiMeO ₂ -Li ₂ MnO ₃ solid solution, Li ₂ O-LiMeO ₂ solid solution, Li ₃ NbO ₄ -LiMeO ₂ solid solution, Li ₄ WO ₅ -LiMeO ₂ solid solution, Li ₄ TeO ₅ -LiMeO ₂ solid solution , Li ₃ SbO _4- LiFeO ₂ solid solution, Li ₂ RuO _3- LiMeO ₂ solid solution, Li ₂ RuO _{3- Li 2} MeO ₃ solid solution and the like.
The positive electrode active material is not limited to the above cases.

Examples of the negative electrode active material used for the negative electrode active material layer include metals or alloys such as hard carbon, Si, Sn, Cd, Zn, Al, Bi, Pb, Ge, and Ag, chalcogenides containing these, and the like. As an example of chalcogenide, SiO can be mentioned.

A plurality of cells 2 are connected in series by electrically connecting the adjacent terminals 23 and 26 of the adjacent cells 2 of the battery module 3 by the bus bar 32.
The terminals 23 and 26 of the cells 2 at both ends of the battery module 3 are provided with leads 34 and 33 for taking out electric power.

FIG. 6 is a block diagram showing the configuration of BMU4. The BMU 4 includes a control unit 41, a storage unit 42, a timekeeping unit 47, an input unit 48, and a communication unit 49. Each of these parts is communicatively connected to each other via a bus.

The control unit 41 has the same configuration as the control unit 71.
The control unit 41 functions as a processing unit that executes the SOH calculation process by reading and executing the SOH estimation program 43 described later.
The timekeeping unit 47 counts the elapsed time.
The input unit 48 receives inputs of detection results from the voltage sensor 5, the current sensor 6, the temperature sensor 8, and the thickness sensor 11.
The communication unit 49 has a function of communicating with other devices via the network 10, and can transmit and receive required information.

The storage unit 42 is composed of, for example, a hard disk drive (HDD) or the like, and stores various programs and data. The SOH estimation program 43 is stored in the storage unit 42. The SOH estimation program 43 is provided in a state of being stored in a computer-readable recording medium 50 such as a CD-ROM, a DVD-ROM, or a USB memory, and is stored in the storage unit 42 by being installed in the BMU 4. Further, the SOH estimation program 43 may be acquired from an external computer (not shown) connected to the communication network and stored in the storage unit 42.

The storage unit 42 also stores charge / discharge history data 44 and temperature data 45. The charge / discharge history is an operation history of the battery module 3, information indicating a period (use period) in which the battery module 3 is charged or discharged, information on charge or discharge performed by the battery module 3 in the use period, and the like. Information including. The information indicating the usage period of the battery module 3 is information including information indicating the start and end points of charging or discharging, the cumulative usage period in which the battery module 3 has been used, and the like. The information regarding charging or discharging performed by the battery module 3 is information indicating the voltage, rate, etc. at the time of charging or discharging performed by the battery module 3.
The temperature data 45 stores the transition of the temperature of the battery module 3.

The coefficient table 46 is also stored in the storage unit 42.
As shown in FIG. 7, the first relationship between the thickness increase amount and the SOH is experimentally obtained in advance for each of the average temperatures of the plurality of representative SOCs and the battery module 3. Here, it is assumed that the representative SOC is the average value of SOC (average SOC) and the SOH is the volume reduction rate. The horizontal axis of FIG. 7 is the thickness increase amount (%), and the vertical axis is the capacity decrease rate (%). The control unit 41 calculates the coefficient of the approximate curve of the first relationship as the coefficient k.

As shown in FIG. 8, the second relationship between the SOC fluctuation amount and the coefficient k is experimentally obtained for each average SOC for each temperature, and the control unit 41 stores the second relationship in the coefficient table 46. The horizontal axis of FIG. 8 is SOC (% / day), and the vertical axis is k. FIG. 8 shows a case where the average temperature is 45 ° C. The control unit 41 specifies the average SOC, the amount of SOC fluctuation, and the average temperature, and specifies the coefficient k with reference to the second relationship stored in the coefficient table 46.
The coefficient table 46 may store the coefficient k as a function of average SOC, SOC variation, and average temperature.
The coefficient k can be interpolated by interpolation calculation.
When the representative SOC is the center value of the SOC or the mode of the SOC, the control unit 41 sets the second relationship between the SOC fluctuation amount and the coefficient k as a coefficient for each temperature and for each of the center value or the mode of the SOC. Store in table 46.

Instead of storing the coefficient k in the coefficient table 46 for each temperature, the temperature is fixed at a predetermined temperature to obtain the coefficient k, which is stored in the coefficient table 46 and stored in the coefficient table 46, and the coefficient k is based on the average SOC and the amount of SOC fluctuation. After specifying, the temperature-corrected coefficient k (T) may be obtained by the Arenius plot.

When the thickness sensor 11 detects the compression force of the battery module 3 (internal pressure of the battery module 3), the control unit 41 converts the amount of increase in the compression force into the amount of increase in thickness and is based on the second relationship stored in the coefficient table 46. To specify the coefficient k.
Alternatively, the third relationship between the amount of increase in compression force and the rate of decrease in capacity is experimentally obtained for each of a plurality of average SOCs and temperatures. The control unit 41 calculates the coefficient of the approximate curve of the third relationship as the coefficient k. The fourth relationship between the SOC fluctuation amount and the coefficient k is experimentally obtained for each temperature and for each average SOC, and the control unit 41 stores the fourth relationship in the coefficient table 46.
Instead of storing the coefficient k in the coefficient table 46 for each temperature, the temperature is fixed at a predetermined temperature to obtain the coefficient k, which is stored in the coefficient table 46, and the coefficient k is specified based on the average SOC and the amount of SOC fluctuation. After that, the temperature-corrected coefficient k (T) may be obtained by the Arenius plot.

FIG. 9 is a flowchart showing a procedure for calculating the capacity reduction rate by the control unit 41.
The control unit 41 acquires the SOC time series data and the temperature (S1). As shown in FIG. 10, the control unit 41 acquires the relationship between the time and the SOC of a predetermined period and the relationship between the time and the temperature. In FIG. 10, the horizontal axis is time, the vertical axis on the left side is SOC (%), and the vertical axis on the right side is temperature (° C.).

The control unit 41 specifies the average SOC (%) as the representative SOC and the SOC fluctuation amount (% / day) (S2). The control unit 41 may calculate the standard deviation and the average value of the SOC based on the time series data, and specify the calculated average value as the representative SOC. The mean value is approximately equal to the central value of SOC.
The control unit 41 may acquire the charging start point and the discharging start point from the time series data, and specify the SOC in the middle between the charging start point and the discharge start point as the center value of the SOC.
The control unit 41 may generate the SOC frequency map shown in FIG. 11 and specify the Mode of the SOC as the representative SOC. In FIG. 11, the horizontal axis is SOC (%) and the vertical axis is frequency.

The control unit 41 specifies the average temperature based on the time series data (S3).
The control unit 41 acquires the thickness increase amount based on the thickness detected by the thickness sensor 11 (S4).

The control unit 41 reads out the coefficient table 46 and specifies the coefficient k based on the specified representative SOC and the amount of SOC fluctuation (S5). When the control unit 41 specifies that the average temperature is 45 ° C., the average SOC is 25%, and the SOC fluctuation amount is 500 (% / day), for example, in the graph of FIG. 8 where the average SOC is 25%, the SOC fluctuation amount is Read the coefficient k when it is 500 (% / day).

The control unit 41 calculates the capacity reduction rate (S6), and ends the process. As shown in FIG. 7, the volume decrease rate is represented by a function of the thickness increase amount with the coefficient k as a factor. The control unit 41 substitutes the thickness increase amount acquired at the time of estimation into the variable of the function, and calculates the capacity reduction rate.
When the pressing force of the battery module 3 is detected by the pressure sensor, the capacity reduction rate is calculated in the same manner as described above.

FIG. 12 is a graph showing the relationship between the elapsed time and the capacity decrease rate calculated based on the thickness increase amount acquired corresponding to the elapsed time, representing the estimated time point for acquiring the thickness increase amount by the elapsed time. The horizontal axis is time (day), and the vertical axis is the capacity reduction rate (%). In FIG. 12, the actually measured values of the capacity reduction rates at a plurality of elapsed times are also shown.
From FIG. 12, it can be seen that the accuracy of estimating the capacity reduction rate by the estimation method of the present embodiment is good.

In the present embodiment, the representative SOC and the SOC fluctuation amount, which are the feature values of the SOC time series data, and the average temperature are specified, and the specified representative SOC, the SOC fluctuation amount, and the average temperature, and the acquired battery module 3 Deterioration of the battery module 3 is estimated based on the amount of increase in thickness. Deterioration at any time point can be easily and accurately estimated during use of the battery module 3, including cases where the SOC fluctuation pattern is complicated.
Based on the estimated SOH, the future usage of the battery module 3 can be determined.

The information required for the estimation is the feature value and the shape change of the battery module 3, and it is not necessary to use a large measuring device such as a charging / discharging device, and the labor and cost can be suppressed.
Since deterioration can be estimated only by changing the shape of the battery module 3, deterioration of the battery module 3 can be constantly monitored simply by installing a sensor that detects the thickness, internal pressure, or the like. The calculation of estimation can be simplified, and BMU4 can be simplified.

The embodiment is not restrictive. The scope of the present invention is intended to include all modifications within the meaning and scope equivalent to the claims.
The capacity reduction rate is not limited to the case of estimating the capacity reduction rate based on the shape change of the battery module 3, and the capacity reduction rate may be estimated based on the shape change of the cell 2.
It is not limited to the case where the change in the pressing force is estimated as the shape change in the state where the battery module 3 is completely restrained. Cell 2 may be in a free state or in an intermediate state. The change in the force (reaction force) spreading to the outside of the cell 2 and the change in the pressure applied to at least one surface of the cell 2 may be used as the shape change.
The SOC representative value is not limited to the central SOC, and the temperature representative value is not limited to the average temperature.
The SOH is not limited to the case of estimating the capacity reduction rate, and the capacity retention rate, resistance value, etc. may be estimated. In this case, the relationship between the thickness increase amount and the capacity retention rate or the resistance value is obtained experimentally, and the coefficient of the approximate curve of the relationship is calculated as the coefficient k.

The estimation method according to the present invention can also be applied to a charge / discharge system such as a mobile body, a mobile device, a power generation facility, a power demand facility, and a regenerative power storage device for railways.
The power storage element is not limited to the lithium ion secondary battery. The power storage element may be another secondary battery, a primary battery, or an electrochemical cell such as a capacitor.

1 Charging / discharging system 2 Battery (power storage element)
3 Battery module (power storage element)
4 BMU
41 Control unit (1st acquisition unit, 2nd acquisition unit, 3rd acquisition unit, specific unit, estimation unit)
42 Storage unit 43 SOH estimation program 44 History data 45 Temperature data 46 Coefficient table 47 Timekeeping unit 48 Input unit 49, 92 Communication unit 5 Voltage sensor 6 Current sensor 7 Control device 8 Temperature sensor 9 Server 91 Control unit 10 Network 11 Thickness sensor 15 Pressure sensor

Claims (5)

The first acquisition unit that acquires SOC time series data in the power storage element,
The second acquisition unit that acquires the shape change of the power storage element,
A specific part that specifies the representative value of SOC in a predetermined period of the time series data and the amount of SOC fluctuation, and
An estimation device including an estimation unit that estimates deterioration of the power storage element based on the specified representative value, the SOC fluctuation amount, and the acquired shape change. The estimation unit
With reference to the relationship between the representative value, the SOC fluctuation amount, and the coefficient, the coefficient is specified based on the specified representative value and the SOC fluctuation amount.
The estimation device according to claim 1, wherein the deterioration is estimated based on the specified coefficient and the acquired shape change. A third acquisition unit for acquiring the temperature of the power storage element during the period for acquiring the time series data is provided.
The specific part specifies a temperature representative value based on the acquired temperature, and determines the temperature representative value.
The estimation device according to claim 1 or 2, wherein the estimation unit estimates the deterioration based on the specified temperature representative value. Acquires the SOC time series data of the power storage element and obtains it.
Acquires the shape change of the power storage element,
The representative value of SOC in the predetermined period of the time series data and the amount of SOC fluctuation are specified.
An estimation method for estimating deterioration of the power storage element based on the specified representative value, the SOC fluctuation amount, and the acquired shape change. Acquires the SOC time series data of the power storage element and obtains it.
Acquires the shape change of the power storage element,
The representative value of SOC in the predetermined period of the time series data and the amount of SOC fluctuation are specified.
A computer program that causes a computer to execute a process of estimating deterioration of the power storage element based on the specified representative value, the SOC fluctuation amount, and the acquired shape change.

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