JP7392364B2 - Estimation device, estimation method and computer program - Google Patents

Description

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

Electric storage elements are used that can store electrical energy and supply energy as a power source when needed. Energy storage elements are applied to mobile devices, power supplies, transportation equipment including automobiles and railways, and industrial equipment including aviation, space, and construction equipment.
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 these deteriorations is an increase in the thickness of the case housing the element due to an increase in internal pressure due to gas generation inside the battery, expansion of the electrode group, and the like.

Multiple batteries are connected in series to form a battery module, which is often installed in equipment. Designing an optimal battery module while taking into account the amount of increase in case thickness is important from the viewpoint of cost and battery performance, and is also an important issue in the design of equipment equipped with battery modules. In other words, in order to design battery modules to maximize battery performance and to apply model-based development to devices equipped with battery modules, it is necessary to accurately predict changes in battery shape. be.

In Patent Document 1, the state of the secondary battery is stored as a history, a coefficient correlated to the amount of gas generated within the battery case is acquired based on the stored history, and the state of the secondary battery is determined from the acquired coefficient and the history. An invention of a control device for a secondary battery that calculates the amount of deterioration is disclosed.

JP2016-93066A

Conventional methods such as those disclosed in Patent Document 1 have insufficient accuracy in estimating the amount of increase in battery thickness. It is desired to improve the accuracy of estimation, including when the variation pattern of SOC (State of Charge) is complex.

An object of the present invention is to provide an estimation device, an estimation method, and a computer program that can accurately estimate a change in shape of a power storage element.

An estimation device according to one aspect of the present invention includes an acquisition unit that acquires time-series data of SOC in a power storage element, a fluctuation range of the SOC in the time-series data, and an SOC representative value representing an SOC region in the fluctuation range. and an estimation section that estimates a change in shape of the power storage element based on the specified variation range and the SOC representative value.

An estimation method according to one aspect of the present invention includes acquiring time-series data of SOC in a power storage element, and calculating a fluctuation range of the SOC in the time-series data and a representative value of the SOC representing an SOC region in the fluctuation range. A change in shape of the power storage element is estimated based on the specified variation range and the representative value.

A computer program according to one aspect of the present invention acquires time-series data of SOC in a power storage element, and calculates a fluctuation range of the SOC in the time-series data and a representative value of the SOC representing an SOC region in the fluctuation range. A computer is caused to perform a process of estimating a change in shape of the power storage element based on the specified fluctuation range and the representative value.

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

It is a graph showing a change in the amount of increase in thickness over time. ΔSOC is 25%, the charge/discharge current is the same, and the center SOC is changed to 37.5%, 62.5%, and 87.5%, and this is a graph showing the relationship between time and the amount of increase in thickness. 3 is a graph showing the relationship between time and the amount of increase in thickness when the amount of increase in thickness over time is subtracted from the total amount of increase in thickness shown in FIG. 2. FIG. This is a graph showing the relationship between the total SOC and the amount of increase in thickness when the center SOC is 60%, the charging/discharging current is the same, and ΔSOC is changed to 10% and 80%. 5 is a graph showing the relationship between the total SOC and the amount of increase in thickness when the amount of increase in thickness over time is subtracted from the total amount of increase in thickness shown in FIG. 4. FIG. This is a graph showing the relationship between the total SOC and the amount of increase in thickness when the center SOC and ΔSOC are the same and the temperature is 25°C and 45°C. 1 is a block diagram showing the configuration of a charging/discharging system and a server according to Embodiment 1. FIG. It is a perspective view of a battery module. FIG. 2 is a block diagram showing the configuration of a BMU. 7 is a flowchart illustrating a procedure for calculating a thickness increase amount by a control unit. It is a graph showing fluctuation data of SOC. It is a figure which shows an example of a 1st expansion coefficient table. FIG. 6 is an explanatory diagram of a method of specifying ΔSOC and center SOC from the start point of charging and discharging of SOC fluctuation data. FIG. 4 is an explanatory diagram of a method of counting each time the SOC reaches a threshold value from a starting point and specifying ΔSOC and the center SOC based on SOC fluctuation data. It is a graph showing fluctuation data of SOC. FIG. 2 is an explanatory diagram of a method for calculating the standard deviation and average value of SOC. It is a graph showing the relationship between standard deviation, average SOC, and first expansion coefficient stored in a first expansion coefficient table. FIG. 6 is an explanatory diagram of a method of calculating the amount of increase in thickness based on the specified first expansion coefficient and time. It is a graph showing the relationship between time and SOC when SOC is varied by Δ0.5%, Δ1.5%, Δ5%, Δ20%, and Δ30%. 20 is a graph obtained by Fourier transforming the waveform of FIG. 19 and decomposing it into waveform components in a plurality of frequency regions. It is a graph which shows the relationship between an amplitude spectrum, a frequency, and a 1st expansion coefficient. It is a graph showing the relationship between time and the amount of increase in thickness. It is a graph showing the results of determining the relationship between the total SOC and the amount of increase in thickness when the ΔSOC is the same and the center SOC is different. It is a graph showing the results of determining the relationship between the total SOC and the amount of increase in thickness when the center SOC is the same and the ΔSOC is different. It is a graph showing the result of calculating the relationship between time and thickness increase amount when charging and discharging are repeated in a short time and ΔSOC and center SOC have different complicated fluctuation patterns. It is a graph which shows the result of having calculated|required the relationship between time and the amount of thickness increase in the case of having a complicated fluctuation pattern. It is a flowchart which shows the processing procedure when predicting the remaining life of a battery module by a control part. FIG. 3 is a perspective view of a battery module according to Embodiment 3. It is a flowchart which shows the procedure of the calculation process of the amount of increase in compression force by a control part. FIG. 3 is a block diagram illustrating an example of the configuration of an information processing system according to a fourth embodiment. 3 is a flowchart illustrating a process of calculating a thickness increase amount by the control unit and a process of designing a battery module by the control unit. FIG. 3 is a block diagram illustrating an example of the configuration of an information processing system according to a fifth embodiment. 3 is a flowchart illustrating the steps of a thickness increase calculation process and a design process of the battery module by the control unit.

(Summary of embodiment)
An estimation device according to an embodiment includes an acquisition unit that acquires time-series data of SOC in a power storage element, a fluctuation range of the SOC in the time-series data, and a representative SOC value representing an SOC region in the fluctuation range. and an estimation section that estimates a shape change of the power storage element based on the specified variation range and the SOC representative value.

As will be described later, the inventors have found that even if the SOC fluctuation range is the same, when the SOC representative value representing the SOC area in this fluctuation range, for example, the central SOC, differs, the amount of increase in the thickness of the power storage element changes. found that there was a big difference. It has been found that even if the SOC representative value is the same, if the SOC fluctuation range is different, the amount of increase in the thickness of the power storage element is significantly different. Furthermore, it has been found that even if the fluctuation value and representative value of the SOC are the same, the amount of increase in the thickness of the power storage element differs when the temperature of the power storage element differs. That is, it has been found that when estimating a change in the shape of a power storage element, it is necessary to consider the path information of the SOC in which the power storage element is used (SOC usage range) and the representative temperature value during the period of this path. In addition to the center value of the SOC during the route period, representative SOC values include the average SOC, the mode, the minimum value, and the maximum value. Examples of the temperature representative value include the average value, mode value, median value, etc. of the range of fluctuation.
Note that if the representative temperature value of the electrical storage element is estimated to be constant from the load pattern (usage pattern) of the electrical storage element, etc., the temperature can be used as the representative temperature value.

Here, shape change refers to the amount of displacement such as swelling of the electrode body or element, the amount of displacement of the case (either closed or open type) that houses the electrode body or element, and the force (reaction force) that spreads outward. or a change in the pressure applied to at least one surface of the electricity storage element, or a combination thereof.
Examples of the housing case include a square case, a cylindrical case, and a pouch laminate film.
A shape change can be estimated whether the power storage element is in a completely restrained state, a free state, or an intermediate state.

According to the above configuration, the shape change of the power storage element is estimated based on the specified fluctuation width and the SOC representative value, that is, the estimation is performed taking into account the SOC usage range, so that it is possible to estimate the shape change in the case where the SOC fluctuation pattern is complex. The accuracy of estimation is good.
Since changes in battery shape can be estimated with high accuracy, an appropriate battery module can be designed.

The following four examples are given as methods for specifying the SOC representative value and the like. In order to improve the accuracy of identification, different indicators (settings of intervals, thresholds, etc. for estimating shape changes) are used, and different identification methods can be used depending on the indicators.
In the above estimation device, as a first identification method, the identification unit obtains a charging start point and a discharging start point based on the time series data, and based on the obtained charging start point and discharging start point. , the fluctuation range and the SOC representative value may be specified.

In the first identification method, there is no need to set an interval or a threshold value.
According to the above configuration, the fluctuation range and representative value of the SOC can be easily identified at the timing when charging is started and discharging is started. Even when charging and discharging are irregular and the SOC fluctuates in a complicated manner, the fluctuation range and representative value can be specified satisfactorily.

In the above-mentioned estimation device, as a second identification method, the identification unit calculates a fluctuation width and a representative SOC value from the starting point each time the SOC reaches a threshold value based on the time series data, and calculates the fluctuation range and the SOC representative value from the starting point to the point of calculation. The fluctuation range and SOC representative value calculated up to the point may be specified.

The second identification method requires setting a threshold value.
According to the above configuration, each time the SOC reaches the threshold value from the starting point, the fluctuation range of the SOC can be easily identified by summing the SOC, and the SOC representative value in the identified fluctuation range is identified. Even when charging and discharging are irregular and the SOC fluctuates in a complicated manner, the range of fluctuation and the representative SOC value can be specified satisfactorily.

In the above estimation device, as a third identification method, the identification unit calculates the standard deviation and average value of the SOC based on the time series data, and uses the calculated standard deviation and average value as the fluctuation range and the SOC. It may be specified as a representative value.

The third identification method requires setting a section.
According to the above configuration, the fluctuation range and the representative value can be easily specified by statistical processing. Even when charging and discharging are irregular and the SOC fluctuates in a complicated manner, the range of fluctuation and the representative SOC value can be specified satisfactorily.

In the above estimation device, as a fourth identification method, the identification unit converts the waveform of the SOC fluctuation in the time series data into a frequency component, and sets the amplitude of the transformed frequency component to the fluctuation width and the frequency to the SOC. It may also be specified as a variation amount.

The fourth identification method requires setting an interval. Here, the SOC variation amount is the integrated SOC variation amount, and corresponds to the number of cycles.
According to the above configuration, since the waveform of the SOC fluctuation is converted into a frequency component, it is possible to detect a waveform with a large fluctuation but a long period (fluctuation time) and a waveform with a small fluctuation but a short period. A waveform with large fluctuations but a long period has a large intensity (spectral intensity, amplitude spectrum in the case of Fourier transform) and is a waveform component with a low frequency. A waveform with small fluctuations but a short period has a low intensity and a high frequency waveform component. Even if the fluctuation is large, if the period is very long, the change in the shape of the power storage element is small. Even if the fluctuation is small, if the period is very short, the shape change is large. Although the waveform of the SOC fluctuation differs depending on the characteristics of the power storage element and the user's usage, the above configuration can detect any waveform and accurately estimate the shape change of the power storage element.

In the above-mentioned estimating device, the estimating unit refers to the relationship between the variation range, the SOC representative value, and the expansion coefficient, specifies the expansion coefficient based on the specified variation range and the SOC representative value, and calculates the specified expansion coefficient. The shape change may be estimated based on the coefficient and the amount of variation in SOC or time.

According to the above configuration, the relationship between the fluctuation range, the SOC representative value, and the expansion coefficient obtained in advance through experiments is referenced, and the expansion coefficient is specified based on the specified fluctuation range and the SOC representative value, and the shape change is performed. Since it is estimated, the estimation accuracy is good.

In the estimation device described above, the estimating unit calculates a shape change of the power storage element when energized based on the variation range and the SOC representative value, and adds a shape change over time to the calculated shape change. The shape change may be estimated by taking the change into account.

According to the above configuration, it is possible to accurately estimate a change in shape of the power storage element by taking into consideration a change in shape over time during non-energization. As an example, a change in shape over time is added to a change in shape during energization. Alternatively, when energizing, only the change in shape during energization may be estimated, and when not, only the change in shape over time may be estimated.

The estimation device described above may further include a prediction unit that predicts the remaining life of the electricity storage element based on the shape change estimated by the estimation unit.

According to the above configuration, in the shape change graph, the time when the shape change exceeds the threshold value is defined as the life span, and the remaining life can be predicted.

In the estimation device described above, the shape change may include information regarding pressure applied to at least one surface of the electricity storage element.

According to the above configuration, it is possible to estimate a change in shape of the power storage element based on a change in pressure. For example, by estimating the compressive force of end plates that connect and sandwich a plurality of power storage elements in series, a battery module can be designed well. When the electricity storage element is not restrained, a change in reaction force or a change in pressure applied to one surface can be considered as a change in shape.

In the above estimation device, the acquisition unit acquires the temperature of the electricity storage element in the section corresponding to the SOC region, the identification unit identifies a temperature representative value representing the temperature of the interval, and the estimation unit may estimate the shape change based on the temperature representative value.

As described above, even if the SOC variation value and the SOC representative value are the same, if the temperature of the power storage element is different, the amount of increase in the thickness of the power storage element will be different.
According to the above configuration, the change in shape of the power storage element can be estimated satisfactorily by taking into consideration the temperature representative value of the power storage element.

The estimation method according to the embodiment acquires time-series data of SOC in a power storage element, identifies a fluctuation range of the SOC in the time-series data, and a representative value of the SOC that represents the SOC region in the fluctuation range, A shape change of the power storage element is estimated based on the specified variation range and the representative value.

According to the above configuration, since the estimation is performed taking into account the SOC usage range of the power storage element, the estimation accuracy is good even when the SOC fluctuation pattern is complicated.

A computer program according to an embodiment acquires time-series data of SOC in a power storage element, identifies a fluctuation range of the SOC in the time-series data, and a representative value of the SOC representing an SOC region in the fluctuation range, A computer is caused to perform a process of estimating a change in shape of the power storage element based on the specified fluctuation range and the representative value.

According to the above configuration, since the SOC of the power storage element is estimated in consideration of the usage range, the estimation accuracy is good even when the SOC variation pattern is complicated.

A computer program according to an embodiment estimates time-series data of SOC in a power storage element, and specifies a fluctuation range of the SOC in the estimated time-series data and a representative value of SOC representing an SOC region in the fluctuation range. , causing a computer to execute a process of estimating a change in shape of the power storage element based on the specified fluctuation range and the representative value.

According to the above configuration, by specifying the SOC fluctuation range and the SOC representative value based on time-series data based on the usage method of the power storage element, it is possible to predict the shape change of the power storage element after a predetermined period of time has elapsed.

In the above-mentioned computer program, the computer may execute a process of designing the electricity storage element based on the estimated shape change.

According to the above configuration, the shape change of the power storage element after a predetermined period of time is predicted, and the shape and arrangement interval of the spacer placed between the plurality of power storage elements, the compressive force of the end plate that sandwiches the plurality of power storage elements, etc. are designed. can be performed well. Therefore, the performance of the power storage element can be maximized, excessive enlargement of the battery module can be avoided, and costs can be reduced.

Hereinafter, a method for estimating a change in shape of a power storage element will be specifically described.
FIG. 1 is a graph showing changes in thickness increase over time. The horizontal axis is time (days), and the vertical axis is thickness increase (%). The amount of increase in thickness is calculated by the sum of the amount of increase in thickness due to energization and the amount of increase in thickness over time when not energized. The amount of increase in thickness over time is expressed as a function of time with a predetermined coefficient as a factor, and the amount of increase in thickness due to energization is expressed as a function of time or total SOC (total variation in SOC) with a predetermined coefficient as a factor. Ru.

In Figure 2, the ΔSOC (SOC fluctuation range) is 25%, the charge/discharge current is the same, and the center SOC is changed to 37.5% (○), 62.5% (△), and 87.5% (□). It is a graph showing the relationship between time and the amount of increase in thickness when the thickness is increased. The horizontal axis is time (days), and the vertical axis is thickness increase (%). The amount of increase in thickness is the sum of the amount of increase in thickness due to energization and the amount of increase in thickness over time when not energized.

FIG. 3 is a graph showing the relationship between time and the amount of increase in thickness when the amount of increase in thickness over time is subtracted from the total amount of increase in thickness shown in FIG. The horizontal axis is time (days), and the vertical axis is thickness increase (%).
From FIGS. 2 and 3, even if ΔSOC is the same, when the center SOC is different, the amount of increase in thickness due to energization changes. The amount of increase in thickness due to energization increases depending on the size of the center SOC.

Figure 4 is a graph showing the relationship between the total SOC and the amount of thickness increase when the center SOC is 60%, the charge/discharge current is the same, and ΔSOC is changed to 10% (○) and 80% (△). be. The horizontal axis is the total SOC (%), and the vertical axis is the thickness increase (%). The amount of increase in thickness is the sum of the amount of increase in thickness due to energization and the amount of increase in thickness over time when not energized.

FIG. 5 is a graph showing the relationship between time and the amount of increase in thickness when the amount of increase in thickness over time is subtracted from the total amount of increase in thickness shown in FIG. The horizontal axis is the total SOC (%), and the vertical axis is the thickness increase (%).
From FIGS. 4 and 5, it can be seen that even if the center SOC is the same, when the SOC fluctuation range (ΔSOC) is different, the amount of increase in thickness due to energization changes. The amount of increase in thickness due to energization increases depending on the magnitude of the fluctuation in ΔSOC.

FIG. 6 is a graph showing the relationship between the total SOC and the amount of increase in thickness when the center SOC and ΔSOC are the same and the temperature of the power storage element is 25° C. (○) and 45° C. (Δ). The horizontal axis is the total SOC (%), and the vertical axis is the thickness increase (%). The amount of increase in thickness indicates the amount of increase in thickness due to energization, which is obtained by subtracting the amount of increase in thickness over time from the total amount of increase in thickness.
From FIG. 6, it can be seen that even if the center SOC and ΔSOC are the same, when the temperature is different, the amount of increase in thickness due to energization changes. The amount of increase in thickness due to energization increases as the temperature increases.

From the above, it can be seen that the amount of increase in thickness needs to be estimated in consideration of not only the total SOC or time, but also ΔSOC, center SOC, and temperature. It has been experimentally confirmed that when a cycle test is performed in the same SOC variation range by changing the charging/discharging current, there is a difference in the rate of increase in thickness depending on the applied current. That is, depending on the applied current, it is necessary to correct the coefficient for determining the amount of increase in thickness.

The inventor of the present application has developed an estimation device that estimates a change in shape of a power storage element based on ΔSOC, a representative SOC of an SOC region in a fluctuation range, and a representative temperature value. Examples of changes in the shape of the power storage element include the amount of increase in thickness, the pressure applied to at least one surface of the power storage element, and the like. The amount of increase in thickness refers to the amount of increase in the thickness of the central portion of the long side of the power storage element or the thickness of both sides. Examples of the representative SOC include the center SOC, average SOC, minimum SOC, and maximum SOC of the SOC area. Hereinafter, the amount of increase in thickness will be explained as the thickness at the center of the long side of the power storage element.

The estimation method according to the present embodiment acquires time-series data of SOC in a power storage element, and specifies ΔSOC in the time-series data, a representative SOC value such as a center SOC representing the SOC region in ΔSOC, and a representative temperature value. . Based on the specified ΔSOC, SOC representative value, and temperature representative value, a change in shape such as an increase in thickness of the electricity storage element is estimated.

(Embodiment 1)
Hereinafter, a case where the electricity storage element is a lithium ion secondary battery will be described.
FIG. 7 is a block diagram showing the configuration of the charging/discharging system 1 and the server 9 according to the first embodiment.
The charging/discharging system 1 includes a battery module 3, a BMU (Battery Management Unit) 4, a voltage sensor 5, a current sensor 6, a control device 7, and a temperature sensor 8.

In the battery module 3, a plurality of lithium ion secondary batteries (hereinafter referred to as cells) 2 as power storage elements are connected in series. The control device 7 controls the entire charging/discharging system 1 .
The server 9 includes a control section 91 and a communication section 92.
The control device 7 includes a control section 71, a display section 72, and a communication section 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 13 is connected to the battery module 3 via terminals 11 and 12. When charging, a charger is connected to the battery module 3.

The control units 71 and 91 are comprised of, for example, a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), etc., 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 send and receive required information.
The display unit 72 of the control device 7 can be configured with a liquid crystal panel, an organic EL (Electro Luminescence) display panel, or the like. The control unit 71 performs control to display required information on the display unit 72.

In this embodiment, either the BMU 4, the control device 7, or the server 9 functions as the estimation device of the present invention. In addition, when the server 9 does not function as an estimation device, the charging/discharging system 1 does not need to be connected to the server 9.
Although FIG. 7 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.
BMU4 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 a positive terminal 23 and a negative terminal 26 of each cell 2, which will be described later, and measures the voltage V ₁ between the terminals 23 and 26 of each cell 2, and calculates the voltage V ₁ of each cell 2. A voltage V between a negative lead 33 and a positive lead 34 of the battery module 3, which will be described later, is detected as a total value.
The current sensor 6 is connected in series to the battery module 3 and outputs a detection result according to the current of the battery module 3.
Temperature sensor 8 is provided near battery module 3 and outputs a detection result according to the temperature of battery module 3.

FIG. 8 is a perspective view of the battery module 3.
The battery module 3 includes a rectangular parallelepiped-shaped case 31 and a plurality of cells 2 housed in the case 31.

The cell 2 includes a rectangular parallelepiped case body 21, a cover plate 22, terminals 23 and 26 provided on the cover plate 22, a rupture 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 the case body 21.
The electrode body 25 may be obtained by winding a positive electrode plate and a negative electrode plate into a flat shape with a separator in between.

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

The positive electrode active material used in the positive electrode active material layer is, for example, Li _x ( _Nia Mn _b Co _c M _d ) O ₂ (M is a metal element other than Li, Ni, Mn, Co, 0≦a<1, 0 ≦b<1, 0≦c<1, a+b+c+d=1, 0<x≦1.1, a and c are not 0 at the same time). The positive electrode active material has a layered rock salt crystal structure. The above a may satisfy 0.5≦a≦1. In this case, transition metal sites contain a large amount of Ni.
The positive electrode active material is preferably NCM, where d=0 and represented by Li _x ( _Nia Co _c Mn _b ) O ₂ (a+b+c=1). The NCM may be NCM111 (a:b:c=1:1:1) or NCM523 (a:b:c=5:2:3) with a high Ni content.
The positive electrode active material may be NCA, where M is Al, b=0, and is represented by Li _x ( _Nia Co _c Al _d ) O ₂ (a+c+d=1).
Note that in NCM or NCA, the metals other than Li and Ni are not limited to two kinds of metals, and may be made of three or more kinds of metals. For example, small amounts of Ti, Nb, B, W, Zr, Ti, Mg, etc. may be included.

Examples of the positive electrode active material include 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 other Li-excess type active materials may be used.
The positive electrode active material is not limited to the above case.

Examples of the negative electrode active material used in the negative electrode active material layer include hard carbon, metals or alloys such as Si, Sn, Cd, Zn, Al, Bi, Pb, Ge, and Ag, and chalcogenides containing these. An example of a chalcogenide is SiO.

Adjacent terminals 23 and 26 of adjacent cells 2 of battery module 3 are electrically connected by bus bar 32, so that a plurality of cells 2 are connected in series.
Terminals 23 and 26 of the cells 2 at both ends of the battery module 3 are provided with leads 34 and 33 for extracting power.

FIG. 9 is a block diagram showing the configuration of the BMU 4. The BMU 4 includes a control section 41 , a storage section 42 , a clock section 47 , an input section 48 , and a communication section 49 . These units are communicably connected to each other via a bus.

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

The storage unit 42 is constituted by, for example, a hard disk drive (HDD), and stores various programs and data. The storage unit 42 stores a thickness increase calculation program 43. The thickness increase amount calculation program 43 is provided in a state stored in a computer-readable recording medium 50 such as a CD-ROM, DVD-ROM, or USB memory, and is stored in the storage unit 42 by installing it in the BMU 4. . Alternatively, the thickness increase calculation program 43 may be acquired from an external computer (not shown) connected to a communication network and stored in the storage unit 42.

The storage unit 42 also stores charging/discharging history data 44 . The charging/discharging history is the operation history of the battery module 3, and includes information indicating the period during which the battery module 3 was charged or discharged (period of use), information regarding charging or discharging performed by the battery module 3 during the period of use, etc. This is information that includes. The information indicating the period of use of the battery module 3 is information including information indicating the start and end points of charging or discharging, the cumulative period of use during which the battery module 3 was 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 storage unit 42 also stores a first expansion coefficient table 45 and a second expansion coefficient table 46.
As shown in FIG. 5, the relationship between the total SOC and the amount of increase in thickness is determined in advance by experiment for each temperature of the battery module 3, for each of a plurality of ΔSOCs and the center SOC, and the control unit 41 approximates the relationship. The coefficient of the curve is calculated as the first expansion coefficient. The first expansion coefficient table 45 stores a plurality of ΔSOCs, center SOCs, and corresponding first expansion coefficients for each temperature. In this case, a temperature table corresponding to the specified temperature representative value is selected, and the first expansion coefficient is specified based on the ΔSOC and the center SOC specified based on the SOC time series data. If there is no table for the corresponding temperature, interpolation calculations are performed between the tables.
When the first expansion coefficient can be represented by an Arrhenius plot, the first expansion coefficient table and the Arrhenius plot at a predetermined temperature are stored in the first expansion coefficient table 45. A first expansion coefficient is specified based on the specified ΔSOC and center SOC, and a temperature-corrected first expansion coefficient (T) is determined using an Arrhenius plot.
In addition, when it is estimated that the temperature representative value of the battery module 3 is constant from the load pattern (usage pattern) of the battery module 3, etc., the first expansion coefficient table corresponding to the temperature representative value may be stored.

The first expansion coefficient table 45 may store the first expansion coefficient as a function of ΔSOC and center SOC.
As shown in FIG. 3, the relationship between time and thickness increase is determined in advance for each of a plurality of ΔSOCs and the center SOC by experiment, and the coefficient of the approximation curve of this relationship is determined as the first expansion coefficient. It may also be stored in the coefficient table 45.
The first expansion coefficient can be interpolated by interpolation calculation.

The relationship between time and thickness increase amount is determined in advance through experiments at a plurality of temperatures and for each SOC during storage, and the control unit 41 calculates the coefficient of the approximate curve of the relationship as the second expansion coefficient. The second expansion coefficient table 46 stores SOCs at a plurality of temperatures and when left unused, and corresponding second expansion coefficients.

FIG. 10 is a flowchart illustrating a procedure for calculating the amount of increase in thickness by the control unit 41. As shown in FIG.
The control unit 41 acquires the SOC time series data and the temperature of the battery module 3 for a predetermined period (S1). The temperature may be acquired as time series data.
The control unit 41 specifies ΔSOC, the center SOC as the representative SOC, and the average temperature as the temperature representative value (S2). A specific method for determining ΔSOC and center SOC will be described later.

The control unit 41 reads the first expansion coefficient table 45 corresponding to the average temperature, and specifies the first expansion coefficient based on the specified ΔSOC and the center SOC (S3). If an Arrhenius plot is stored instead of storing the first expansion coefficient table for each average temperature, the control unit 41 calculates the first expansion corrected to the temperature at the time of calculation using the Arrhenius plot for the specified first expansion coefficient. Find the coefficient (T).

An example of specifying the first expansion coefficient is shown. FIG. 11 is a graph showing SOC fluctuation data. The horizontal axis is time (seconds), and the vertical axis is SOC (%). From FIG. 11, the center SOC is 40% and ΔSOC is 25%. FIG. 12 shows an example of the first expansion coefficient table 45. When the center SOC is 40% and ΔSOC is 25%, the first expansion coefficient k7d is specified from the first expansion coefficient table 45. Here, ΔSOC refers to the amount of variation during charging or discharging.

The control unit 41 calculates the first thickness increase amount based on the specified first expansion coefficient and the total SOC (S4).
The first thickness increase is expressed as a function of the total SOC, with the first expansion coefficient as a factor. If the coefficient of the approximate curve of the relationship between time and thickness increase amount determined for each temperature and each of the plurality of ΔSOCs and the center SOC is determined as the first expansion coefficient and stored in the first expansion coefficient table 45, the first The amount of increase in thickness is expressed as a function of time using the first expansion coefficient as a factor.

The control unit 41 reads the second expansion coefficient table 46 and specifies the second expansion coefficient based on the average temperature and the SOC when left unused (S5).
The control unit 41 calculates the second thickness increase amount based on the specified second expansion coefficient and time (S6). The second thickness increase amount is expressed as a function of time (or √ time) with the second expansion coefficient as a factor.
The control unit 41 adds the second thickness increase amount to the first thickness increase amount to calculate the total thickness increase amount (S7), and ends the process.

The method for identifying ΔSOC and center SOC will be specifically described below.
FIG. 13 is an explanatory diagram showing a method of specifying ΔSOC and center SOC from the charging/discharging starting point of SOC fluctuation data. The horizontal axis is time and the vertical axis is SOC (%).
The control unit 41 acquires the charging start point and the discharging start point from the SOC fluctuation data.
The control unit 41 specifies the difference in SOC between the charging start point and the discharging start point as ΔSOC.
The control unit 41 specifies the average SOC between the charge start point and the discharge start point as the center SOC, and specifies the average temperature as the representative temperature value.

FIG. 14 is an explanatory diagram showing a method of specifying ΔSOC and the center SOC by counting each time the SOC reaches a threshold value from the starting point, based on the SOC fluctuation data. The horizontal axis is time and the vertical axis is SOC (%).
The control unit 41 calculates ΔSOC and center SOC every time the amount of change in SOC increases or decreases by 2%.
The control unit 41 specifies the amount of change in SOC from the starting point to the count point as ΔSOC.
The control unit 41 specifies the average SOC from the starting point to the count point as the center SOC, and specifies the average temperature as the temperature representative value.

Next, a case will be described in which the standard deviation and average value of SOC are calculated based on time-series data, and the calculated standard deviation and average value are specified as ΔSOC and center SOC.
FIG. 15 is a graph showing SOC fluctuation data, where the horizontal axis is time (days) and the vertical axis is SOC (%).
The control unit 41 extracts data for a period for calculating the amount of increase in thickness from the SOC variation data.

FIG. 16 is an explanatory diagram for explaining a method of calculating the standard deviation and average value of SOC.
The control unit 41 calculates the standard deviation and average value of the SOC.

The control unit 41 reads the first expansion coefficient table 45 and specifies the first expansion coefficient.
FIG. 17 is a graph showing the relationship among the standard deviation, average SOC, and first expansion coefficient stored in the first expansion coefficient table 45 for each temperature. The horizontal axis is the standard deviation (%), and the vertical axis is the first expansion coefficient (%/√SOC). The standard deviation and the first expansion coefficient for each case of a, b, c, d, and e where the average SOC is 12.5%, 37.5%, 62.5%, 87.5%, and 100%. I am looking for the relationship between The control unit 41 refers to the first expansion coefficient table 45 corresponding to the average temperature and specifies the first expansion coefficient based on the standard deviation and average SOC specified as shown in FIG. 16. The control unit 41 may perform temperature correction on the first expansion coefficient using an Arrhenius plot.

FIG. 18 is an explanatory diagram of a method of calculating the amount of increase in thickness based on the specified first expansion coefficient and time. The horizontal axis is time (days), and the vertical axis is thickness increase (%).
The calculated value of the amount of increase in thickness is shown in a graph. Actual measured values are also shown. It can be seen from FIG. 18 that the calculated values match the actually measured values.

Next, a case will be described in which the waveform of the SOC fluctuation in time series data is converted into a frequency component, and the amplitude of the converted frequency component is specified as the fluctuation width, and the frequency is specified as the total SOC.
FIG. 19 is a graph showing the relationship between time and SOC when the SOC is varied by Δ0.5%, Δ1.5%, Δ5%, Δ20%, and Δ30% at a predetermined temperature. The horizontal axis is time [seconds], and the vertical axis is SOC [%]. In FIG. 19, graphs when the SOC is varied by Δ0.5%, Δ1.5%, Δ5%, Δ20%, and Δ30% are indicated by a, b, c, d, and e. FIG. 19 also shows fluctuations in SOC (example) when the power storage element is actually used.

FIG. 20 is a graph obtained by Fourier transforming the waveform in FIG. 19 and converting it into waveform components in a plurality of frequency regions. The horizontal axis is frequency [Hz], and the vertical axis is amplitude spectrum [%].
Waveform components corresponding to waveforms b, c, d, and e in FIG. 19 are shown, and waveform components obtained by converting the waveforms of the example are also shown. Among the waveform components corresponding to the waveform a in FIG. 19, the peak component has a frequency of approximately 0.013 and an amplitude of approximately 0.133, and is not shown in FIG.

The first expansion coefficient table 45 stores, for each temperature, the amplitude spectrum of the main peak of the frequency component and the relationship between the frequency and the first expansion coefficient. First, the first relationship between time (days) and the amount of increase in thickness when the SOC changes in patterns a, b, c, d, and e in FIG. 19 is determined.
FIG. 21 is a graph showing the second relationship between the amplitude spectrum, frequency, and first expansion coefficient. In FIG. 21, the x-axis is the amplitude spectrum [%], the y-axis is the frequency [Hz], and the z-axis is the first expansion coefficient. The second relationship shows the correspondence between the peak top frequency and amplitude spectrum of each waveform a, b, c, d, and e in FIG. 20 and the first expansion coefficient obtained from the approximate curve of the first relationship. There is. In FIG. 21, when the amplitude spectrum is approximately 10.2% and the amplitude is approximately 2×10 ⁻⁴ , the first expansion coefficient is approximately 0.94. The graph in FIG. 21 shows the case where interpolation is performed by interpolation calculation. In the case of FIG. 21, the first expansion coefficient can be determined by reading the values on the z-axis corresponding to the amplitude spectrum and frequency of the waveforms other than the waveforms a, b, c, d, and e in FIG. You can ask for it. In the case of the example shown in FIG. 20, the main peak has an amplitude spectrum of 8.02% and an amplitude of approximately 8.4×10 ⁻⁵ , and by reading the z coordinate of point ○, the first expansion coefficient can be determined to be approximately 0. 19. When determining the first expansion coefficient, weighting may be performed on a waveform component having a large intensity compared to a waveform component having a small intensity.

FIG. 22 is a graph showing the relationship between time and thickness increase amount at the predetermined temperature. In FIG. 22, the horizontal axis is time (days) and the vertical axis is the amount of increase in thickness (%). The calculated value shows the relationship between time and thickness increase amount when the first expansion coefficient is 0.19.
The experimental values are obtained by plotting the amount of increase in thickness at each time point at a plurality of measurement time points. From FIG. 22, it was confirmed that the estimation method of this embodiment can perform estimation well.
As described above, it was confirmed that the waveform of the SOC fluctuation can be converted into waveform components in multiple frequency regions, and the amount of increase in the thickness of the power storage element can be estimated with high accuracy based on each waveform component and the first expansion coefficient.

The results of determining the change in thickness increase due to energization are shown below.
FIG. 23 is a graph showing the results of determining the relationship between the total SOC and the amount of increase in thickness when the ΔSOC is the same and the center SOC is different. The amount of increase in thickness was calculated by the method of this embodiment for each case where the SOC fluctuated between 25-50%, between 50-75%, and between 75-100% (Example a, Example b, Example c). For each of the above cases, the amount of increase in thickness was calculated using the conventional method disclosed in Patent Document 1 (Comparative Example d, Comparative Example e, and Comparative Example f). In FIG. 23, the actual measured values are plotted as the amount of increase in thickness at a plurality of measurement points.
From FIG. 23, in the case of Comparative Examples d, e, and f, the thickness increase amount is calculated as approximately the same value even if the center SOC is different, whereas in the case of Examples a, b, and c, the thickness increase amount is calculated as approximately the same value even if the center SOC is different. Correspondingly, a thickness increase amount that approximates the actual measured value is calculated, indicating that the calculation accuracy is high.

FIG. 24 is a graph showing the results of determining the relationship between the total SOC and the amount of increase in thickness when the center SOC is the same and the ΔSOC is different. The amount of increase in thickness was calculated according to the present embodiment when the SOC varied between 55% and 65%, and when the SOC varied between 20% and 100% (Example g, Example h). For each of the above cases, the amount of increase in thickness was calculated by the method described in Patent Document 1 (Comparative Example i, Comparative Example J). In FIG. 24, the actual measurement values are plotted as the amount of increase in thickness at a plurality of measurement points.
From FIG. 24, in the case of Comparative Examples i and j, the thickness increase amount is calculated as approximately the same value even if the ΔSOC is different, whereas in the case of Examples g and h, it corresponds to each ΔSOC, and the thickness increase amount is calculated as the same value. It can be seen that an approximate thickness increase amount is calculated, and the calculation accuracy is high.

FIG. 25 is a graph showing the results of calculating the relationship between time and thickness increase amount when charging and discharging are repeated in a short period of time and the ΔSOC and center SOC have different and complex fluctuation patterns. The horizontal axis is time (days), and the vertical axis is thickness increase (%). The environmental temperature is 20°C. In FIG. 25, the actual measured values are plotted as the amount of increase in thickness at a plurality of measurement points.
From FIG. 25, it can be seen that the method of this embodiment allows the thickness increase amount to be calculated with high accuracy.

FIG. 26 is a graph showing the results of determining the relationship between time and the amount of increase in thickness in the case of having a complicated variation pattern as described above. The horizontal axis is time (days), and the vertical axis is thickness increase (%). The environmental temperature is 25°C. In FIG. 26, the actual measured values are plotted as the amount of increase in thickness at a plurality of measurement points.
From FIG. 26, it can be seen that the method of this embodiment allows the thickness increase amount to be calculated with high accuracy.

As described above, according to the present embodiment, the amount of increase in the thickness of the battery module 3 is estimated based on the specified ΔSOC and the center SOC, that is, the amount of increase in the thickness of the battery module 3 is estimated by taking into account the usage range of the SOC in which the battery module 3 is used. Therefore, the estimation accuracy is good even when the SOC variation pattern is complex.
Since changes in the shape of the battery module 3 can be estimated with high accuracy, it is also possible to design the battery module 3 to maximize the performance of the cell 2 and apply model-based development to devices equipped with the battery module 3. It is.

(Embodiment 2)
In the second embodiment, the control unit 41 estimates the remaining life of the battery module 3 based on the estimated thickness increase amount.
FIG. 27 is a flowchart showing a processing procedure when the control unit 41 predicts the remaining life of the battery module 3.

The control unit 41 calculates the thickness increase amount as described above (S11). The control unit 41 generates a graph of the amount of thickness increase as a function of time, with the first expansion coefficient as a factor, as shown in FIG. 26, for example, based on ΔSOC, center SOC, and time.
The control unit 41 calculates the remaining life of the battery module 3 (S12). For example, in the curve of FIG. 26, the control unit 41 reads the time when the amount of increase in thickness exceeds the threshold value, and subtracts the time from the read time to the present time to obtain the remaining life.

In the present embodiment, the future thickness increase can be predicted based on the thickness increase estimation graph, the remaining life can be predicted, and replacement of the battery module 3 can be managed.

(Embodiment 3)
In the third embodiment, the amount of increase in the pressing force that presses the power storage element is estimated as the change in the shape of the power storage element.
FIG. 28 is a perspective view of the battery module 3 according to the third embodiment.
End plates 15, 15 are arranged at both ends of the battery module 3 according to the third embodiment in the direction in which the cells 2 are arranged side by side. A spacer 19 made of synthetic resin is arranged between the cells 2, 2 and between the cell 2 and the end plate 15. The spacer 19 may have a corrugated plate shape. The end plates 15, 15 are for sandwiching the plurality of cells 2 and spacers 19 from the direction in which they are arranged side by side. From the viewpoint of strength, the end plate 15 is preferably made of metal such as stainless steel. In the case of a low compression type, the end plate 15 may be made of synthetic resin.

The connecting members 16, 16 are metal members that connect the end plates 15 to each other and restrain the plurality of cells 2 and the plurality of spacers 19 in a compressed state. The connecting member 16 has a rectangular frame shape that is long in the juxtaposition direction. The connecting member 16 is constructed by fastening the plurality of cells 2 and spacers 19 to the end plates 15 with bolts 17 on both sides in the juxtaposition direction, with the cells 2 and spacers 19 being compressed by the end plates 15, 15 in the juxtaposition direction. 2 is restrained in a compressed state.
When the internal pressure of the cell 2 increases due to deterioration, the spacer 19 deforms and the compressive force between the end plates 15 increases.

In the third embodiment, the storage unit 42 of the BMU 4 stores a first compression force coefficient table instead of the first expansion coefficient table 45. The relationship between the total SOC and the amount of increase in compression force is determined by experiment for each of the plurality of ΔSOCs and the center SOC, and the control unit 41 calculates the coefficient of the approximate curve as the first compression force coefficient. The first compression force coefficient table stores a plurality of ΔSOCs and center SOCs, and corresponding first compression force coefficients. In this case, the first compression force coefficient is determined by referring to the first compression force coefficient table based on the ΔSOC and the center SOC specified based on the SOC time series data, and then the first compression force is temperature-corrected using an Arrhenius plot. Find the coefficient (T). The first compression force coefficient table may store the first compression force coefficient in association with a plurality of ΔSOCs, center SOC, and temperature. In addition, the relationship between time and the amount of increase in compression force is determined in advance for each of a plurality of ΔSOCs and the center SOC by experiment, and the coefficient of the approximate curve of the relationship is determined as the first compression force coefficient. It may be stored in a table.
The first compression force coefficient can be interpolated by interpolation calculation.

The relationship between time and the amount of increase in compression force is determined in advance through experiments for each of a plurality of temperatures and each SOC during storage, and the control unit 41 calculates the coefficient of the approximate curve of the relationship as the second compression force coefficient. The second compression force coefficient table stores a plurality of temperatures and SOCs when left unused, and corresponding second compression force coefficients.

FIG. 29 is a flowchart showing the procedure of the calculation process of the amount of increase in compression force by the control unit 41.
The control unit 41 acquires SOC fluctuation data and the temperature of the battery module 3 for a predetermined period (S21).
The control unit 41 specifies ΔSOC, the center SOC as a representative SOC of the SOC, and the average temperature as a representative temperature value (S22).
The control unit 41 reads the first compression force coefficient table corresponding to the average temperature, and specifies the first compression force coefficient based on the specified ΔSOC, center SOC, and average temperature (S23). The control unit 41 may calculate the first compression force coefficient (T) corrected to the temperature at the time of calculation using an Arrhenius plot for the identified first compression force coefficient.

The control unit 41 calculates the first compression force increase amount based on the specified first compression force coefficient and the total SOC variation amount (S24). The first compression force increase amount is expressed as a function of the total SOC, with the first compression force coefficient as a factor. If the coefficient of the approximate curve of the relationship between time and compression force, determined for each of multiple ΔSOCs and center SOC, is determined as the first compression force coefficient and stored in the first compression force coefficient table, the first compression force increases. The amount is expressed as a function of time, factored by the first compression force coefficient.
The control unit 41 reads the second compression force coefficient table and specifies the second compression force coefficient based on the average temperature and the SOC when left unused (S25).
The control unit 41 calculates the second compression force increase amount based on the specified second compression force coefficient and time (S26).
The control unit 41 calculates a total compression force increase amount by adding the second compression force increase amount to the first compression force increase amount (S27), and ends the process.

According to this embodiment, a change in the shape of the battery module 3 can be estimated based on a change in compression force. By estimating the compressive force of the end plate 15 of the battery module 3, the battery module 3 can be designed well.

(Embodiment 4)
FIG. 30 is a block diagram illustrating an example of the configuration of an information processing system 81 according to the fourth embodiment. In the information processing system 81, terminals 61 and 62 of users such as a server 9 of an information management company, designers of the cells 2 and battery modules 3, etc., and designers of equipment in which the battery modules 3 are installed in vehicles etc. are connected to the Internet, etc. are connected via a network 10. The number of terminals is not limited to two. The terminals 61 and 62 can be configured with, for example, a desktop computer, a notebook personal computer, a tablet, a smartphone, or the like.

The server 9 includes a control section 91 , a storage section 93 , a clock section 97 , an input section 98 , and a communication section 92 . These units are communicably connected to each other via a bus.
The control unit 91 functions as a processing unit that executes the process of calculating the thickness increase amount by reading and executing the thickness increase amount calculation program 94.
The clock section 97 measures time.
The input unit 98 receives input of load pattern information from the terminals 61 and 62.
The communication unit 92 has a function of communicating with the terminals 61 and 62 via the network 10, and can send and receive required information.

The storage unit 93, the first expansion coefficient table 95, and the second expansion coefficient table 96 have the same configuration as the storage unit 42, the first expansion coefficient table 45, and the second expansion coefficient table 46. The thickness increase amount calculation program 94 is provided in a state stored in a computer-readable recording medium 51 such as a CD-ROM, DVD-ROM, or USB memory, and is stored in the storage unit 93 by installing it on the server 9. Ru. Alternatively, the thickness increase calculation program 94 may be acquired from an external computer (not shown) connected to a communication network and stored in the storage section 93.

Similarly, the terminals 61 and 62 include control units 61a and 62a, storage units 61b and 62b, timekeeping units 61c and 62c, input units 61d and 62d, and communication units 61e and 62e.

FIG. 31 is a flowchart illustrating a procedure for calculating the amount of increase in thickness by the control section 91 and a procedure for designing the battery module 3 by the control section 61a.
The control unit 61a of the terminal 61 transmits the load pattern of the battery module 3 to the server 9 (S41). Examples of the load pattern include temperature, time, voltage, current, etc. when the usage method of the battery module 3 is estimated.
The control unit 91 of the server 9 receives the load pattern of the battery module 3 from the terminal 61 (S31).

Based on the load pattern, the control unit 91 identifies ΔSOC, the center SOC as a representative SOC of the SOC, and the average temperature as a representative temperature value (S32).
The control unit 91 reads the first expansion coefficient table 95 corresponding to the average temperature, and specifies the first expansion coefficient based on the specified ΔSOC and center SOC (S33). The control unit 91 may calculate the first compression force coefficient (T) corrected to the assumed temperature using an Arrhenius plot for the identified first compression force coefficient. If the first expansion coefficient table 95 stores the first expansion coefficient corresponding to the assumed temperature, temperature correction is not necessary.

The control unit 91 calculates the first thickness increase amount based on the specified first expansion coefficient and the total SOC (S34).
The control unit 91 reads the second expansion coefficient table 96 and specifies the second expansion coefficient based on the assumed temperature and the SOC when left unused (S35).
The control unit 91 calculates the second thickness increase amount based on the specified second expansion coefficient and time (S36).
The control unit 91 adds the second thickness increase amount to the first thickness increase amount to calculate the total thickness increase amount (S37).
The control unit 91 transmits data on the total thickness increase amount to the terminal 61 (S38).

The control unit 61a receives data on the total thickness increase amount from the server 9 (S42).
The control unit 61a designs the battery module 3 (S43), and ends the process. The control unit 61a can appropriately design the shape and arrangement interval of the spacer 19 disposed between the plurality of cells 2, the compressive force of the end plate 15 that sandwiches the plurality of cells 2, and the like. Therefore, the performance of the cell 2 can be maximized, excessive enlargement of the battery module 3 can be avoided, and costs can be reduced.

When the terminal 61 is a terminal of a designer of equipment such as a vehicle in which the battery module 3 is mounted, the control unit 61a acquires data on the total thickness increase and designs the storage space etc. for the battery module 3 in the equipment. be able to. Equipment can also be designed based on the performance and lifespan of the battery module 3.
The terminal 62 also performs the same process as described above.

(Embodiment 5)
FIG. 32 is a block diagram showing an example of the configuration of the information processing system 82 according to the fifth embodiment. In the figure, the same parts as in FIG. 30 are given the same reference numerals, and detailed explanations are omitted.
In the information processing system 82 of the fifth embodiment, from the server 9 to the storage units 61b and 62b of the terminals 61 and 62, the thickness increase calculation programs 61f and 62f, the first expansion coefficient tables 61g and 62g, and the second expansion coefficient Tables 61h and 62h are installed. The thickness increase calculation programs 61f, 62f, etc. may be installed in the storage units 61b, 62b via a recording medium.

In the fifth embodiment, the control unit 61a or 62a estimates the amount of increase in the thickness of the battery module 3, and designs the battery module 3 based on the estimated amount of increase in the thickness. The thickness increase calculation programs 61f and 62f of the fifth embodiment include a process of acquiring a load pattern and a process of designing the battery module 3, but do not include a process of receiving a load pattern and a process of transmitting a total thickness increase. This differs from the thickness increase calculation program 94 in this point.

FIG. 33 is a flowchart showing the steps of the thickness increase calculation process and design process of the battery module 3 by the control unit 61a. The control unit 61a reads the thickness increase amount calculation program 61f and executes the thickness increase amount calculation process and the design process of the battery module 3.
The control unit 61a of the terminal 61 acquires the load pattern of the battery module 3 (S51). Examples of the load pattern include temperature, time, voltage, current, etc. when the usage method of the battery module 3 is estimated.

Based on the load pattern, the control unit 61a identifies ΔSOC, the center SOC as a representative SOC of the SOC, and the average temperature as a representative temperature value (S52).
The control unit 61a reads the first expansion coefficient table 61g corresponding to the average temperature, and specifies the first expansion coefficient based on the specified ΔSOC and center SOC (S53). The control unit 61a may calculate the first compression force coefficient (T) corrected to the temperature at the time of calculation using an Arrhenius plot for the identified first compression force coefficient. If the first expansion coefficient table 61g stores the first expansion coefficient corresponding to the assumed temperature, temperature correction is not necessary.

The control unit 61a calculates the first thickness increase amount based on the specified first expansion coefficient and the total SOC (S54).
The control unit 61a reads the second expansion coefficient table 61h, and specifies the second expansion coefficient based on the assumed temperature and the SOC when left unused (S55).
The control unit 61a calculates the second thickness increase amount based on the specified second expansion coefficient and time (S56).
The control unit 61a calculates the total thickness increase amount by adding the second thickness increase amount to the first thickness increase amount (S57).

The control unit 61a designs the battery module 3 (S58), and ends the process. The control unit 61a can appropriately design the shape and arrangement interval of the spacer 19 disposed between the plurality of cells 2, the compressive force of the end plate 15 that sandwiches the plurality of cells 2, and the like. Therefore, the performance of the cell 2 can be maximized, excessive enlargement of the battery module 3 can be avoided, and costs can be reduced.

When the terminal 61 is a terminal of a designer of a device in which the battery module 3 is installed, the control unit 61a can design the storage space for the battery module 3 in the device based on the data on the total thickness increase. . Equipment can also be designed based on the performance and lifespan of the battery module 3. Since changes in the shape of the battery module 3 can be predicted with high accuracy, model-based development can be applied to devices equipped with the battery module 3.
The terminal 62 also performs the same process as described above.

The embodiments described above are not limiting. The scope of the present invention is intended to include all changes within the meaning and scope equivalent to the claims.
The present invention is not limited to estimating changes in the shape of the battery module 3, but may also estimate changes in the shape of the cells 2.
The present invention is not limited to estimating a change in compressive force as a change in shape when the battery module 3 is completely restrained. Cell 2 may be in a free state or in an intermediate state. A change in the force (reaction force) spreading outside the cell 2 or a change in the pressure applied to at least one surface of the cell 2 may be considered a shape change.
The SOC representative value is not limited to the center SOC, and the temperature representative value is not limited to the average temperature.

The estimation method according to the present invention can also be applied to charging and discharging systems for moving objects, mobile devices, power generation equipment, power demand equipment, regenerative power storage devices for railways, and the like.
The power storage element is not limited to a 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 (storage element)
3 Battery module (storage element)
4 BMU
41 Control unit (identification unit, estimation unit, prediction unit)
42, 93 Storage section 43, 94 Thickness increase calculation program 44 History data 45, 95 First expansion coefficient table 46, 96 Second expansion coefficient table 47, 97 Timing section 48, 98 Input section 49, 92 Communication section 5 Voltage sensor 6 current sensor 7 control device 8 temperature sensor 9 server 91 control unit 10 network 61, 62 terminal

Claims (14)

an acquisition unit that acquires time-series data of SOC in the electricity storage element;
a specifying unit that specifies a fluctuation range of the SOC in the time-series data and an SOC representative value representing an SOC region in the fluctuation range;
An estimating device comprising: an estimating unit that estimates a change in shape of the power storage element based on the specified variation range and the SOC representative value. The specific part is
Obtaining a charging start point and a discharging start point based on the time series data,
The estimation device according to claim 1, wherein the fluctuation range and the SOC representative value are specified based on the acquired charging start point and discharge start point. The specific part is
Based on the time series data, each time the SOC reaches the threshold from the starting point, calculate the fluctuation range and the SOC representative value,
The estimating device according to claim 1, wherein the fluctuation range and SOC representative value calculated from the starting point to the point of calculation are specified. The specific part is
The estimating device according to claim 1, wherein a standard deviation and an average value of SOC are calculated based on the time series data, and the calculated standard deviation and average value are specified as the fluctuation range and the SOC representative value. The specific part is
Converting the waveform of the SOC fluctuation in the time series data into frequency components,
The estimation device according to claim 1, wherein the amplitude of the converted frequency component is specified as the variation width, and the frequency is specified as the variation amount of the SOC. The estimation unit is
Referring to the relationship between the variation range, the SOC representative value, and the expansion coefficient, specifying the expansion coefficient based on the specified variation range and the SOC representative value,
The estimating device according to any one of claims 1 to 5, wherein the shape change is estimated based on the specified expansion coefficient and the amount of variation in SOC or time. The estimation unit is
Calculating a change in shape of the electricity storage element when energized based on the fluctuation range and the SOC representative value,
The estimating device according to any one of claims 1 to 6, wherein the estimation device estimates a shape change by adding a shape change over time of the electricity storage element to the calculated shape change. The estimation device according to any one of claims 1 to 7, further comprising a prediction unit that predicts the remaining life of the electricity storage element based on the shape change estimated by the estimation unit. The estimating device according to any one of claims 1 to 8, wherein the shape change includes information regarding pressure applied to at least one surface of the electricity storage element. The acquisition unit acquires the temperature of the power storage element in a section corresponding to the SOC region,
The identification unit identifies a temperature representative value that represents the temperature in the section,
The estimation unit estimates the shape change based on the temperature representative value.
The estimation device according to any one of claims 1 to 9. The computer is
Obtain time series data of SOC in the energy storage element,
identifying a fluctuation range of the SOC in the time series data and a representative value of the SOC that represents the SOC region in the fluctuation range;
An estimation method for estimating a shape change of the electricity storage element based on the specified variation range and the representative value. Obtain time series data of SOC in the energy storage element,
identifying a fluctuation range of the SOC in the time series data and a representative value of the SOC that represents the SOC region in the fluctuation range;
A computer program that causes a computer to execute a process of estimating a change in shape of the electricity storage element based on the specified fluctuation range and the representative value. Estimating time series data of SOC in the energy storage element,
Identifying a fluctuation range of the SOC in the estimated time series data and a representative value of the SOC representing the SOC region in the fluctuation range,
A computer program that causes a computer to execute a process of estimating a change in shape of the electricity storage element based on the specified fluctuation range and the representative value. The computer program according to claim 13, which causes a computer to execute a process of designing the electricity storage element based on the estimated shape change.

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