Active material thickness estimation value correction method, active material thickness estimation value correction program, and utilization method of battery

Abstract

To solve the problem in which a conventional active material thickness estimation value correction method cannot reduce a calculation load on estimation calculation of parameters.SOLUTION: An active material thickness estimation value correction method performs through automatic processing by a computer: ion concentration change calculation processing S41, S43 for calculating an ion concentration change amount indicating a change amount of a diffusion state of a carrier ion in a battery cell; active material thickness correction processing S45 for correcting, by using an output voltage, an active material thickness estimation value indicating a thickness of an active material layer coated on a pole plate stored in the battery cell; and execution determination processing S42, S44 for selectively executing the active material thickness correction processing on condition that the ion concentration change amount is equal to or less than a threshold value set in advance.SELECTED DRAWING: Figure 6

Description

[Technical field]

[0001] The present invention relates to an active material thickness estimated value correction method, an active material thickness estimated value correction program, and a battery usage method, for example, for correcting an active material thickness estimated value used for controlling a battery in accordance with the actual state of a battery cell. [Background technology]

[0002] In recent years, secondary batteries that have been used for a specific purpose have come to be recycled for other purposes. However, when using secondary batteries, if the battery parameters for grasping the state of the secondary battery cannot be grasped, a problem occurs in which the battery control becomes unstable due to overcharging, overdischarging, etc. of the secondary battery. In particular, in controlling secondary batteries, battery parameters including an active material thickness estimate value indicating the thickness of the active material layer applied to the electrode foil are used. Thus, a method for estimating the active material thickness of a secondary battery is disclosed in Patent Documents 1 and 2.

[0003] Patent Documents 1 and 2 disclose techniques for calculating a single-electrode capacity maintenance rate or an estimated active material thickness (or electrode plate thickness). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2010-060384 A [Patent Document 2] JP 2014-126411 A Summary of the Invention [Problem to be solved by the invention]

[0005] When recycling secondary batteries, the usage history of the secondary battery to be recycled may be unknown, or the secondary battery may have unknown information such as the materials used in the secondary battery and the manufacturing process. When using such secondary batteries with unknown origins, the specific structure of the battery cell is not known, and there is a problem that it is not possible to calculate the active material thickness estimate by applying the techniques described in Patent Documents 1 and 2, which require an initial value for the specific structure of the battery cell for calculation. In addition, Patent Documents 1 and 2 require calculations to be performed periodically during operation of the battery cell, and there is a problem that the calculation load required to improve the accuracy of the active material thickness estimate is large.

[0006] The present invention has been made in consideration of the above circumstances, and aims to reduce the calculation load while improving the accuracy of the active material thickness estimation value, which is one of the battery parameters of a secondary battery of unknown nature, during operation. [Means for solving the problem]

[0007] One aspect of the active material thickness estimate correction method of the present invention automatically performs the following processes by a computer: a current / voltage measurement process for acquiring a current value indicating the magnitude of a charge / discharge current to a battery cell and an output voltage of the battery cell, which are acquired during a charge / discharge operation performed on the battery cell; an ion concentration change calculation process for calculating an ion concentration change amount indicating a change in the diffusion state of carrier ions within the battery cell; an active material thickness correction process for correcting an active material thickness estimated value indicating the thickness of an active material layer applied to a plate contained in the battery cell using the output voltage; and an execution determination process for selectively executing the active material thickness correction process on the condition that the ion concentration change amount is equal to or less than a predetermined threshold value.

[0008] One aspect of the active material thickness estimate value correction program of the present invention causes a computer to execute a current / voltage measurement process that acquires a current value indicating the magnitude of a charge / discharge current to a battery cell obtained during a charge / discharge operation performed on the battery cell and an output voltage of the battery cell; an ion concentration change calculation process that calculates an ion concentration change amount indicating a change in the diffusion state of carrier ions within the battery cell; an active material thickness correction process that corrects an active material thickness estimated value indicating the thickness of an active material layer applied to a plate contained in the battery cell using the output voltage; and an execution determination process that selectively executes the active material thickness correction process on the condition that the ion concentration change amount is below a predetermined threshold value.

[0009] One aspect of the battery utilization method according to the present invention includes a first determination process for receiving an input of product information including at least information on the battery type of a battery cell, determining a first provisional battery parameter set in advance based on the product information, and determining whether or not the battery type is a target battery type; a battery characteristic estimation process for measuring the dimensions of the battery cell determined to be the target battery type and then assembling the battery cell into a state in which the battery cell can be charged and discharged, estimating a degree of deterioration of the battery cell and a current electrode capacity that is a current electrode capacity of the battery cell based on charge and discharge current values ​​and an output voltage value of the battery cell obtained by charging and discharging the assembled battery cell, and estimating a thickness of an active material layer of the battery cell based on the measurement results of the dimensions of the battery cell; and a characteristic degradation state estimation process for estimating a parameter that is an index of a degree of characteristic degradation of the battery cell based on an amount of change in battery resistance of the battery cell calculated from current and voltage values ​​obtained when the assembled battery cell is repeatedly charged and discharged multiple times. a second determination process for determining whether the battery cell can be used for the intended use based on the values ​​estimated by the battery characteristic estimation process and the characteristic deterioration state estimation process; a battery parameter adaptation process for setting, for the battery cell determined to be usable for the intended use, the parameters estimated by the battery characteristic estimation process and the characteristic deterioration state estimation process as battery parameters to be used for controlling the battery cell; a battery usage process for updating a power limit of the battery cell according to the deterioration degree while performing a charging rate and deterioration degree estimation process using the battery parameters set in the battery parameter adaptation process, and continuing to use the battery cell until it is determined that the battery life of the battery cell has expired; and an automatic parameter correction process for performing a correction process on the battery parameters related to deterioration of the battery cell using at least a current value indicating the magnitude of a charge / discharge current to the battery cell obtained in a charge / discharge operation performed on the battery cell during the battery usage process, and an output voltage of the battery cell. Effect of the Invention

[0010] According to the active material thickness estimate correction method, active material thickness estimate correction program, and battery utilization method of the present invention, it is possible to reduce the calculation load while improving the accuracy of the active material thickness estimate, which is one of the battery parameters of a secondary battery of unknown origin, during operation. [Brief description of the drawings]

[0011] [Figure 1] 10 is a flowchart illustrating the flow of a method of using a battery when the battery specifications are known. [Diagram 2] 4 is a flowchart illustrating a method of using a battery according to the first embodiment. [Diagram 3] 4 is a flowchart illustrating a flow of a battery characteristics estimation process according to the first embodiment. [Figure 4] 4 is a flowchart illustrating a flow of a characteristic degradation state estimation process according to the first embodiment. [Diagram 5] FIG. 2 is a diagram for explaining an outline of an active material thickness estimated value correction method according to the first embodiment. [Figure 6] 10 is a flowchart illustrating a flow of an active material thickness estimated value correction process according to the first embodiment. [Figure 7] FIG. 4 is a diagram for explaining a calculation method for the active material thickness correction process according to the first embodiment. [Figure 8] 11 is a flowchart illustrating a flow of an active material thickness estimated value correction process according to the second embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] In order to clarify the description, the following description and drawings are omitted and simplified as appropriate. In addition, each element shown in the drawings as a functional block performing various processes can be configured in hardware with a CPU (Central Processing Unit), memory, and other circuits, and in software, can be realized by a program loaded into memory. Therefore, it is understood by those skilled in the art that these functional blocks can be realized in various forms by hardware alone, software alone, or a combination thereof, and are not limited to any one of them. In addition, the same elements are given the same symbols in each drawing, and duplicated explanations are omitted as necessary.

[0013] Moreover, the above-mentioned program includes a set of instructions (or software code) for making the computer perform one or more functions described in the embodiment when the program is read into the computer. The program may be stored in a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, the computer-readable medium or the tangible storage medium includes random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technology, CD-ROM, digital versatile disc (DVD), Blu-ray (registered trademark) disk or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device. The program may be transmitted on a transitory computer-readable medium or a communication medium. By way of example and not limitation, the transitory computer-readable medium or the communication medium includes electrical, optical, acoustic, or other forms of propagating signals.

[0014] In addition, the battery utilization method according to the first embodiment described below is performed by an automatic process in which multiple programs executed on separate computers are prepared for each process in the flow of battery utilization in cooperation with each other.

[0015] First embodiment In the following description, a method of using a battery that reuses a secondary battery will be described. Therefore, in the following description, the secondary battery will simply be referred to as a battery. Furthermore, in the method of using a battery according to the first embodiment, regardless of whether the battery is used as a battery pack made up of a combination of multiple batteries, the battery parameters and performance will be evaluated for each individual battery cell, so in the description, the term battery cell will be used.

[0016] First, before explaining the battery utilization method according to the first embodiment, a battery utilization method in which the non-destructive battery degradation state estimation method implemented in the battery utilization method according to the first embodiment is not used will be explained as a comparative example.

[0017] Fig. 1 shows a flowchart explaining the flow of a method of using a battery when the battery specifications are known (a method of using a battery according to a comparative example). As shown in Fig. 1, in the method of using a battery according to the comparative example, detailed product information of the battery is input when starting to use the battery cell (step S101). Specifically, in step S101, the detailed product information includes the capacity of the new battery cell when it starts to be used, design information such as the thickness of the active material layers that make up the electrode plates, characteristic variations of the battery cell caused by manufacturing variations, and life characteristics of the battery cell.

[0018] Next, in the battery usage method according to the comparative example, the product information acquired in step S101 is used to acquire the characteristics of the battery cell and diagnose the battery cell (step S102). In this step S102, the battery cell is repeatedly charged and discharged to acquire information such as the full charge capacity of the battery cell, the terminal resistance value of the battery cell (hereinafter referred to as battery resistance), the input / output characteristics of the battery cell, and the degree of capacity deterioration compared to a new battery cell. When a battery cell is reused, its usage history up to that point is unknown, and by performing the process of step S102, information necessary for appropriately controlling the battery cell is obtained. The process of step S102 usually takes several months to about half a year.

[0019] Next, based on the information acquired in steps S101 and S102, it is determined whether the battery cell has the performance required for the intended use (step S103). If it is determined in step S103 that the battery cell does not have the performance required for the intended use, the battery cell is considered for recycling for another use.

[0020] On the other hand, if it is determined in step S103 that the battery cell has the performance required for the intended use, a battery parameter adaptation process is performed in which the information (e.g., battery parameters) acquired in steps S101 and S102 is set in the system that uses the battery cell as battery parameters to be used in controlling the battery cell (step S104). Also, a power limit according to the performance of the battery cell is set in the system that uses the battery cell (step S105).

[0021] Thereafter, in the battery cell utilization method according to the comparative example, the charging rate (SOC: State Of Charge) and deterioration degree (SOH: State Of Health) of the battery cell are estimated (step S106) and the lifespan of the battery cell is predicted (step S107), and the battery cell is utilized until it is determined that the predicted lifespan has expired (YES branch of step S108).

[0022] As described above, in the battery usage method according to the comparative example, in order to use a battery cell, it is necessary to obtain information that can only be known by the battery manufacturer, such as the capacity of the battery cell when it is new, design information, characteristic variations, and life characteristics, and there is a problem that battery cells with unknown origins cannot be used. In addition, in the battery usage method according to the comparative example, it takes several months to understand the changes in battery characteristics caused by the use of the battery cell, so there is a problem that the period during which the battery cell cannot be used is extended. Furthermore, in the battery usage method according to the comparative example, in step S102, charging and discharging are repeated to obtain and diagnose the characteristics of the battery cell, so there is a problem that power not used for a specific purpose is required.

[0023] However, the battery usage method according to the first embodiment makes it possible to recycle even battery cells whose origins are unknown and whose information on the design and manufacture of the battery cell is difficult to obtain. Also, the battery usage method according to the first embodiment improves the accuracy of information for understanding the current characteristics of the battery cell while using the battery for a specific purpose, thereby shortening the unused period of the battery cell. The battery usage method according to the first embodiment will be specifically described below.

[0024] Fig. 2 shows a flowchart for explaining the battery usage method according to the first embodiment. In the battery usage method according to the first embodiment, first, product information including at least information on the battery type of the battery cell is input, and a first determination process is performed to determine first provisional battery parameters set in advance based on the product information and determine whether the battery type is a target one. In the example shown in Fig. 2, the first determination process is divided into steps S1 to S3.

[0025] In step S1, regardless of whether the identity of the battery cell is known or not, product information of the battery cell is input at the start of use (step S1). Specifically, in the battery usage method according to the first embodiment, information including at least the battery type of the battery cell to be used is input to the computer as product information in step S1. Here, secondary batteries are classified into lead-acid batteries, nickel-metal hydride batteries, lithium-ion batteries, etc., depending on the type of active material used. Therefore, in the battery usage method according to the first embodiment, information on the material from which the battery cell to be used is manufactured, such as a lead-acid battery, nickel-metal hydride battery, or lithium-ion battery, is provided to the computer as the battery type.

[0026] Next, in step S2, first provisional battery parameters (e.g., standard parameters) preset for each battery type of the battery cell to be used are provisionally determined as battery parameters (step S2). Here, the standard parameters in the battery utilization method according to the first embodiment are publicly available information, and are, for example, values ​​determined in advance by a business entity that reuses battery cells based on information published on a website or the like by a material manufacturer that is a supplier of the material for the battery cells. For example, the standard parameters include the thickness of the electrode foil, the thickness of the separator, the density of the active material layer coated on the electrode foil, the specific capacity of the active material layer, and the electrode capacity of the active material layer.

[0027] Next, in step S3, it is determined whether the battery cell to be used is a battery cell that is suitable for the intended use. Specifically, in step S3, for example, in a battery pack that uses a combination of multiple battery cells, it is necessary to combine battery cells of the same type, and it is determined whether the battery type is a target battery pack to be assembled. Also, in step S3, it may be determined to exclude battery cells that are obviously old, or battery cells whose shape is obviously unsuitable for the intended use.

[0028] Then, if it is determined in step S3 that the battery cell matches the intended use, a battery characteristic estimation process (step S6), a characteristic deterioration state estimation process (step S7), and a second judgment process (step S8) are performed on the target battery cell.

[0029] In the battery characteristic estimation process S6, the dimensions of the battery cell determined to be the target battery type are measured, and then the battery cell is assembled in a state in which it can be charged and discharged, and the deterioration level of the battery cell and the current electrode capacity of the battery cell are estimated based on the charge / discharge current value and the output voltage value of the battery cell obtained by charging and discharging the assembled battery cell, and the thickness of the active material layer of the battery cell is estimated based on the measurement results of the battery cell dimensions. Note that the example of Fig. 2 shows step S4 of measuring the dimensions of the battery cell as a process prior to the battery parameter estimation process, and step S5 of assembling the target battery cell so that it can be charged and discharged.

[0030] Here, the battery characteristic estimation process S6 will be described in more detail. In the battery characteristic estimation process S6, design parameters indicating the characteristics (e.g., capacity, etc.) of the battery cell in a new state and the structure of the battery cell are estimated using the provisional values ​​acquired in S2 and the measured values ​​acquired in step S4. In other words, in the battery characteristic estimation process, design parameters indicating the characteristics (e.g., capacity, etc.) of the battery cell in a new state and the structure of the battery cell are acquired without destroying the battery cell. Here, FIG. 3 shows a flowchart explaining the flow of the battery characteristic estimation process according to the first embodiment. As shown in FIG. 3, in the battery characteristic estimation process, provisional parameter setting process S21, current state measurement process S22, coating portion structure calculation process S23, and active material thickness calculation process S24 are performed.

[0031] In the provisional parameter setting process S21, provisional values ​​for each parameter, for example, aluminum foil thickness, copper foil thickness, separator thickness, positive electrode density, positive electrode specific capacity, negative electrode density, negative electrode specific capacity, initial positive electrode capacity, and initial negative electrode capacity, are set by referring to the standard parameters input in step S2.

[0032] In the current state measurement process S22, the battery cell is charged and discharged while controlling the battery cell using the provisional values ​​set by the provisional parameter setting process, and the degree of deterioration of the battery cell and the current electrode capacities of the battery cell, i.e., the current positive electrode capacity and the current negative electrode capacity, are estimated.

[0033] In the coating structure calculation process S23, the cross-sectional area of ​​the electrode body contained in the battery cell as viewed from a side perpendicular to the electrode stacking direction and the width of the coating portion of the electrode body are calculated based on dimensions that can be measured without destroying the battery cell (for example, the width, height, and thickness of the case that contains the electrode body in the battery cell obtained in step S4).

[0034] In the active material thickness calculation process S24, the thickness of the positive electrode active material layer and the thickness of the negative electrode active material layer are calculated using the aluminum foil thickness, copper foil thickness, separator thickness, positive electrode density, positive electrode specific capacity, negative electrode density, and negative electrode specific capacity whose provisional values ​​were set in step S21, the current positive electrode capacity and current negative electrode capacity whose estimated values ​​were calculated in step S22, and the cross-sectional area of ​​the electrode body and the coated portion width of the electrode body calculated in step S23.

[0035] The values ​​acquired and calculated in steps S21 to S24 are used in the characteristic degradation state estimation process that is performed after the battery characteristic estimation process and subsequent processes.

[0036] Next, the characteristic degradation state estimation process S7 will be described. In the characteristic degradation state estimation process S7, the amount of change in the battery resistance of the battery cell is calculated from the current and voltage values ​​obtained when the battery cell assembled in step S5 is repeatedly charged and discharged multiple times, and a parameter serving as an index of the degree of characteristic degradation of the battery cell is estimated based on the amount of change in the battery resistance of the battery cell.

[0037] FIG. 4 shows a flow chart for explaining the flow of the characteristic degradation state estimation process S7 according to the first embodiment. As shown in FIG. 4, the characteristic degradation state estimation process according to the first embodiment includes a current resistance value measurement process S31, a characteristic degradation factor analysis process S32, and a salt concentration unevenness mitigation process S33. In the current resistance value measurement process S31, charging and discharging are performed on the battery cell, and the current battery resistance of the battery cell is measured based on the charge and discharge current and the output voltage of the battery cell. In the characteristic degradation factor analysis process S32, a current value is estimated for each degradation factor parameter that is a characteristic degradation factor of the battery cell based on the difference between the battery resistance of the battery cell in a new state estimated in advance and the current battery resistance measured in the current resistance value measurement process S31. In the salt concentration unevenness mitigation process S33, the degradation factor parameter at that time point is set as a determined value in response to the fact that the current battery resistance measured after a certain period of charge and discharge processing in which the charge and discharge current is limited to a predetermined charge and discharge rate changes from a decrease to an increase, and the amount of change between the current battery resistance at the previous measurement and the current battery resistance at the current measurement falls within a certain range set in advance. In the characteristic degradation state estimation process S7, if the current battery resistance measured in the salt concentration unevenness mitigation process S33 is lower than the current battery resistance measured previously, the characteristic degradation cause analysis process S32 is executed based on the newly measured current battery resistance. By performing this characteristic degradation state estimation process S7, it becomes possible to optimize the control of the battery cell according to the degradation state of the battery, and to use the battery cell safely and with higher performance.

[0038] Next, in the second determination process in step S8, it is determined whether the battery cell can be used for the intended use based on the estimated values ​​in the battery characteristic estimation process S6 and the characteristic degradation state estimation process S7. If the battery cell is suitable for the intended use in this second determination process S8, the battery parameter adaptation process S9 and the battery use processes S10 to S14 are performed.

[0039] In the battery parameter adaptation process S9, the parameters estimated in the battery characteristic estimation process S6 and the characteristic degradation state estimation process S7 are set as battery parameters to be used for controlling the battery cell.

[0040] In the battery utilization process of steps S10 to S14, the battery control parameters set in the battery parameter adaptation process are used to estimate the charging rate (SOC: State Of Charge) and deterioration level (SOH: State Of Health) (step S10), while updating the power limit of the battery cell according to the deterioration level (step S12), and continuing to utilize the battery cell until it is determined that the battery life of the battery cell has expired (step S14).

[0041] Here, in the processing of steps S10 to S14, an automatic parameter correction process S11 is performed between the estimation process of the charging rate and the deterioration degree (step S10) and the update process of the power limit (step S12). In this automatic parameter correction process S11, a correction process is performed on battery parameters related to deterioration of the battery cell using at least a current value indicating the magnitude of a charge / discharge current to the battery cell acquired in a charge / discharge operation performed on the battery cell during the battery use process, and an output voltage of the battery cell. In the automatic parameter correction process S11, a correction process is performed to reflect changes in values ​​due to the progress of use of the battery cell, such as a capacity deviation, capacity deterioration, active material thickness, plate area, battery resistance increase judgment, and ion diffusion coefficient estimated value. In the automatic parameter process S11 according to the first embodiment, a correction method for the active material thickness is particularly characterized. Note that in the battery use method according to the first embodiment, the value calculated in the active material thickness calculation process S24 is an active material thickness estimated value, which is an estimated value of the thickness of the active material layer. Therefore, the accuracy of the active material thickness estimated value is improved by correcting the active material thickness estimated value to match the actual state of the battery cell in the active material thickness estimated value correction process performed in the parameter automatic process S11. The active material thickness estimated value correction method according to the first embodiment will be described in detail below.

[0042] First, FIG. 5 shows an outline of the active material thickness estimate correction method according to the first embodiment. In a secondary battery, the calculation of the active material thickness estimate uses the voltage error of the output voltage of the battery cell as a calculation element. The voltage error is greatly related to the amount of change in the ion diffusion concentration. Here, the voltage error elements caused by the error in the active material thickness estimate include five elements, namely, the positive electrode OCP, the negative electrode OCP, the liquid phase potential difference, the reaction overvoltage, and the DC resistance voltage. The voltage error elements related to the change in the ion diffusion concentration include three elements, namely, the positive electrode OCP, the negative electrode OCP, and the liquid phase potential difference. Therefore, in the active material thickness estimate correction method according to the first embodiment, the active material thickness estimate correction process is performed excluding the period in which the ion diffusion concentration change is large. The example shown in FIG. 5 shows an example of the time transition of the output voltage. The ion diffusion concentration change is the period in which the output voltage fluctuation is large, and the example shown in FIG. 5 shows the period TMA in which the ion diffusion concentration change exceeds a threshold value. In the active material thickness estimate correction method according to the first embodiment, the active material thickness estimate correction process is performed in the period excluding the period TMA.

[0043] In the active material thickness estimate correction method according to the first embodiment, the calculation load can be reduced by selectively performing the active material thickness estimation correction process according to the magnitude of the ion diffusion concentration change. In addition, in the active material thickness estimate correction method according to the first embodiment, the calculation load can be reduced by reducing the number of variables to be considered in the calculation of the active material thickness estimate by performing the correction process by selecting a period in which the ion diffusion concentration change is small, thereby improving the accuracy of the active material thickness estimate while reducing the calculation load. Therefore, a specific example of the active material thickness estimate correction process according to the first embodiment will be described below.

[0044] FIG. 6 shows a flow chart for explaining the flow of the active material thickness estimated value correction process according to the first embodiment. In the active material thickness estimated value correction process, a current / voltage measurement process, an ion concentration change calculation process, an active material thickness correction process, and an execution determination process are performed. In the current / voltage measurement process, a current value indicating the magnitude of the charge / discharge current to the battery cell and an output voltage of the battery cell are obtained in a charge / discharge operation performed on the battery cell. The current / voltage measurement process is a process for obtaining a charge / discharge current value of the battery cell and an output voltage of the battery cell in a battery system in which the battery cell is incorporated while the battery cell is in operation. In other words, the current / voltage measurement process is a process for obtaining a current value indicating the magnitude of the charge / discharge current to the battery cell and an output voltage of the battery cell, which are obtained in a charge / discharge operation performed on the battery cell. Thus, the current / voltage measurement process is an operation performed as a normal process during the operation of the battery cell, and is therefore omitted from FIG. 6.

[0045] In the ion concentration change calculation process, an ion concentration change amount indicating the amount of change in the diffusion state of carrier ions in a battery cell is calculated. In the flowchart shown in Fig. 6, in order to determine the change in solid-phase ion concentration and the change in liquid-phase ion concentration separately, a solid-phase ion concentration change calculation process S41 and a liquid-phase ion concentration change calculation process S43 are shown as the ion concentration change amount calculation process. In the solid-phase ion concentration change calculation process S41, a solid-phase ion concentration change amount which is the amount of change in the ion concentration of carrier ions in the solid phase is calculated. In the liquid-phase ion concentration change calculation process S43, a liquid-phase ion concentration change amount which is the amount of change in the ion concentration of carrier ions in the liquid phase is calculated.

[0046] In the solid-phase ion concentration change calculation process S41 and the liquid-phase ion concentration change calculation process S43, the amount of change in the diffusion state of the carrier ions in the battery cell is calculated. The amount of change is calculated by applying a current value and a numerical value including at least an estimated diffusion coefficient that can be obtained by the computer at the start of the process to a Newman model to calculate the carrier ion concentration. Then, in the ion diffusion saturation calculation process, the amount of change is calculated by applying the carrier ion concentration to an equation derived from Fick's second law.

[0047] Here, Fick's second law is expressed by equation (1) where D is the diffusion coefficient, x is an arbitrary position, and c is the carrier ion concentration.

number

[0048] In the execution determination process, the active material thickness correction process is selectively executed under the condition that the amount of change in ion concentration is equal to or less than a preset threshold value. In the flowchart shown in FIG. 6, a first execution determination process S42 and a second execution determination process S44 are shown as execution determination processes in order to individually determine the change in solid-phase ion concentration and the change in liquid-phase ion concentration. In the first execution determination process S42, when the amount of change in solid-phase ion concentration calculated in the solid-phase ion concentration change calculation process S41 is equal to or less than a preset first threshold value, the liquid-phase ion concentration change calculation process S43 is executed. In the second execution determination process S44, when the amount of change in liquid-phase ion concentration calculated in the liquid-phase ion concentration change calculation process S43 is equal to or less than a preset second threshold value, the active material thickness correction process S45 is executed.

[0049] In the active material thickness correction process S45, an active material thickness estimate value indicating the thickness of the active material layer applied to the electrode plate housed in the battery cell is corrected using the output voltage. More specifically, in the active material thickness correction process S45, for example, a voltage error y(k) included in the voltage value acquired in the current / voltage measurement process and an active material thickness estimate value x(k-1) calculated in the previous processing cycle are applied to a Kalman filter to obtain the active material thickness estimate value. Here, k is an integer indicating the processing cycle number.

[0050] Here, the Kalman filter will be explained. FIG. 7 shows a diagram for explaining a calculation method of the active material thickness correction process according to the first embodiment. FIG. 7 is a block diagram showing the process related to the Kalman filter. As shown in FIG. 7, in the calculation of the Kalman filter used in the active material thickness correction process S45, the active material thickness estimated value x(k-1) is multiplied by the system matrix A to calculate Ax(k-1). The system matrix A is a matrix including any fixed value set for each battery cell. Furthermore, Ax(k-1) is multiplied by (Ig(k)c T ) to get Ax(k-1)(Ig(k)c T ) where I is the identity matrix, g(k) is the noise model matrix, and c T is an observation coefficient vector, which is an eigenvalue set for each battery system including a battery cell. In addition, in the calculation of the Kalman filter in the active material thickness correction process S45, the voltage error y(k) is multiplied by the noise model matrix g(k) to obtain g(k)y(k). Then, Ax(k-1)(Ig(k)c T ) is added with g(k)y(k) to calculate a new active material thickness estimate x(k).

[0051] As described above, in the battery usage method according to the first embodiment, even if the battery cell has an unknown origin, it is possible to update the active material thickness estimated value to a highly accurate value that reflects the actual state of the battery cell while the battery cell is in operation. In other words, in the battery usage method according to the first embodiment, by executing the automatic parameter correction process S11, the battery parameters can be corrected to values ​​that match the actual state of the battery cell as the battery cell deteriorates due to use of the battery cell. By correcting the battery parameters during operation of the battery cell in this manner, it is possible to fully utilize the performance of the battery cell. In the battery usage method according to the first embodiment, it is possible to particularly improve the accuracy of the active material thickness estimated value.

[0052] Also, as explained above, in the battery usage method according to the first embodiment, in the active material thickness estimated value correction process in the parameter automatic correction process S11, a period in which the ion concentration change is small is selected and the active material thickness correction process S45 is executed. In this way, by limiting the period in which a process with a high calculation load is performed to only a period that satisfies certain conditions, the battery usage method according to the first embodiment can reduce the calculation load.

[0053] Furthermore, in the battery usage method according to the first embodiment, the execution period of the active material thickness correction process S45 is limited to a period in which the change in ion concentration is small, thereby reducing the number of variables to be considered in updating the active material thickness estimate value. This also makes it possible to reduce the calculation load required for the active material thickness correction process S45 in the battery usage method according to the first embodiment.

[0054] Embodiment 2 In the embodiment 2, a description will be given of another embodiment of the active material thickness estimated value correction process according to the embodiment 1. In the description of the embodiment 2, the contents described in the embodiment 1 will be denoted by the same reference numerals as in the embodiment 1, and the description thereof will be omitted.

[0055] As shown in Fig. 5, the period in which the ion concentration change is large is generally close to the period in which the output voltage is large. Therefore, in the active material thickness estimate correction process according to the second embodiment, before calculating the amount of change in the ion concentration, a voltage determination process is executed to selectively execute the ion concentration change calculation process when the rate of change in the output voltage is equal to or less than a preset voltage change threshold. Therefore, Fig. 8 shows a flowchart illustrating the flow of the active material thickness estimate correction process according to the second embodiment.

[0056] 8, in the active material thickness estimated value correction process according to the second embodiment, a voltage determination process S51 is executed before the solid phase ion concentration change calculation process S41 to determine whether the rate of change of the output voltage is equal to or less than a preset voltage change threshold. If the voltage determination process S51 determines that the rate of change of the output voltage is equal to or less than the preset voltage change threshold, the solid phase ion concentration change calculation process S41 is executed. On the other hand, if the voltage determination process S51 determines that the rate of change of the output voltage is greater than the voltage change threshold, the process is terminated without executing the processes from the solid phase ion concentration change calculation process S41 to the active material thickness correction process S45.

[0057] In addition, it is preferable that the voltage judgment threshold is set to be within a range narrower than the output voltage change range in which ion concentration changes occur, in which judgment processes related to ion concentration changes (e.g., the first execution judgment process S42 and the second execution judgment process S44) are performed.

[0058] As described above, in the active material thickness estimated value correction process according to the second embodiment, the frequency of execution of the ion concentration change calculation process is reduced by a determination based on the magnitude of the rate of change in the output voltage, which requires less calculation than the ion concentration change calculation process (solid phase ion concentration change calculation process S41 and liquid phase ion concentration change calculation process S43) which requires a large amount of calculation. As a result, the active material thickness estimated value correction process according to the second embodiment can reduce the calculation load more than the active material thickness estimated value correction process according to the first embodiment.

[0059] The present invention is not limited to the above-described embodiment, and can be modified as appropriate without departing from the spirit and scope of the present invention.

Claims

1. A current / voltage measurement process for acquiring a current value indicating a magnitude of a charge / discharge current to the battery cell and an output voltage of the battery cell, the current value being acquired in a charge / discharge operation performed on the battery cell; an ion concentration change calculation process for calculating an ion concentration change amount indicating an amount of change in a diffusion state of carrier ions in the battery cell; an active material thickness correction process for correcting an active material thickness estimated value indicating a thickness of an active material layer applied to an electrode plate contained in the battery cell using the output voltage; an execution determination process for selectively executing an active material thickness correction process on the condition that the amount of change in ion concentration is equal to or less than a preset threshold value; The method for correcting the estimated active material thickness is carried out by automatic processing using a computer.

2. the ion concentration change calculation process includes a solid-phase ion concentration change calculation process for calculating a solid-phase ion concentration change amount, which is the amount of change in the ion concentration of the carrier ions in a solid phase, and a liquid-phase ion concentration change calculation process for calculating a liquid-phase ion concentration change amount, which is the amount of change in the ion concentration of the carrier ions in a liquid phase; 2. The active material thickness estimation value correction method according to claim 1, wherein the execution determination process includes a first execution determination process for executing the liquid phase ion concentration change calculation process when the amount of change in solid phase ion concentration is equal to or less than a predetermined first threshold, and a second execution determination process for executing the active material thickness correction process when the amount of change in liquid phase ion concentration is equal to or less than a predetermined second threshold.

3. The active material thickness estimate correction method according to claim 1 , further comprising a voltage determination process for selectively executing the ion concentration change calculation process when a rate of change of the output voltage of the battery cell is equal to or lower than a preset voltage change threshold value.

4. A current / voltage measurement process for acquiring a current value indicating a magnitude of a charge / discharge current to the battery cell and an output voltage of the battery cell, the current value being acquired in a charge / discharge operation performed on the battery cell; an ion concentration change calculation process for calculating an ion concentration change amount indicating an amount of change in a diffusion state of carrier ions in the battery cell; an active material thickness correction process for correcting an active material thickness estimated value indicating a thickness of an active material layer applied to an electrode plate contained in the battery cell using the output voltage; an execution determination process for selectively executing an active material thickness correction process on the condition that the amount of change in ion concentration is equal to or less than a preset threshold value; The active material thickness estimated value correction program causes a computer to execute the above.

5. a first determination process for receiving product information including at least information on the battery type of the battery cell, determining first provisional battery parameters that are set in advance based on the product information, and determining whether the battery type is a target battery type; a battery characteristic estimation process for measuring the dimensions of the battery cell determined to be a target battery type, and then assembling the battery cell into a state in which the battery cell can be charged and discharged, estimating a degree of deterioration of the battery cell and a current electrode capacity that is a current electrode capacity of the battery cell based on a charge / discharge current value and an output voltage value of the battery cell obtained by charging and discharging the assembled battery cell, and estimating a thickness of an active material layer of the battery cell based on the measurement results of the dimensions of the battery cell; a characteristic degradation state estimation process for estimating a parameter that is an index of a characteristic degradation degree of the battery cell based on an amount of change in battery resistance of the battery cell calculated from current and voltage values ​​obtained when the assembled battery cell is repeatedly charged and discharged a plurality of times; a second determination process for determining whether the battery cell can be used for a desired purpose based on values ​​estimated by the battery characteristic estimation process and the characteristic degradation state estimation process; a battery parameter adaptation process for setting, for the battery cell determined to be usable for the intended use, parameters estimated by the battery characteristic estimation process and the characteristic degradation state estimation process as battery parameters to be used for controlling the battery cell; a battery usage process for updating a power limit of the battery cell according to the degree of deterioration while performing a process of estimating a charging rate and a degree of deterioration using the battery parameters set in the battery parameter adaptation process, and continuing to use the battery cell until it is determined that the battery life of the battery cell has expired; a parameter automatic correction process that performs a correction process on the battery parameters related to deterioration of the battery cell by using at least a current value indicating a magnitude of a charge / discharge current to the battery cell, the current value being acquired in a charge / discharge operation performed on the battery cell during the battery usage process, and an output voltage of the battery cell; A method of using a battery in which the above is carried out by automatic processing using a computer.

6. In the automatic parameter correction process, at least an active material thickness estimated value correction process is performed to correct an active material thickness estimated value indicating a thickness of an active material layer applied to an electrode plate contained in the battery cell, In the active material thickness estimated value correction process, a current / voltage measurement process for acquiring a current value indicating a magnitude of a charge / discharge current to the battery cell and an output voltage of the battery cell, the current value being acquired in a charge / discharge operation performed on the battery cell; an ion concentration change calculation process for calculating an ion concentration change amount indicating an amount of change in a diffusion state of carrier ions in the battery cell; an active material thickness correction process for correcting an active material thickness estimated value indicating a thickness of an active material layer applied to an electrode plate contained in the battery cell using the output voltage; an execution determination process for selectively executing an active material thickness correction process on the condition that the amount of change in ion concentration is equal to or less than a preset threshold value; 6. The method for using a battery according to claim 5, wherein said step is carried out by automatic processing using a computer.

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