Method for estimating internal degradation state of degraded battery and measurement system for executing the method

Abstract

The present invention provides a method for estimating the internal degradation state of a degraded battery and a measuring system for executing the method. In the measuring system (100), in the method for estimating the internal degradation state of a degraded battery, a target capacity characteristic curve (12) is calculated by differentiating the current carrying capacity with respect to a target charging curve (10) of an object battery (OB) using voltage. Furthermore, in the method for estimating the internal degradation state, changes in multiple parameters are obtained by fitting the target capacity characteristic curve (12) with a reference capacity characteristic curve calculated based on reference data (20). In the fitting operation, after fitting the reference capacity characteristic curve (30) and the target capacity characteristic curve (12) with a stronger correlation in the low current carrying capacity region and the high current carrying capacity region first, the weaker correlation is fitted. Thus, the reproducibility, reliability, and comprehensibility of the battery capacity degradation can be further improved.

Description

Technical Field

[0001] The present invention relates to an internal degradation state estimating method for estimating the internal degradation state of a degraded secondary battery and a measuring system for executing the method. Background Art

[0002] Japanese Patent Application Publication No. 2015-87344 discloses a half-cell fitting method for estimating the capacity degradation of a secondary battery based on the electromotive force curves of its positive and negative electrodes. This method estimates the internal degradation state by fitting one of the electromotive force curves of a new battery and the electromotive force curve of a degraded battery to the other. Capacity degradation is estimated based on changes in fitting parameters as the electromotive force curve is altered. Summary of the Invention

[0003] However, in existing methods for estimating the internal degradation state of a degraded battery, when fitting the post-degradation electromotive force curve to the pre-degradation electromotive force curve, changing one fitting parameter also affects the other fitting parameter. Adjusting one fitting parameter and then fitting the other fitting parameter makes it impossible to determine whether the primary cause of degradation lies in one fitting parameter or the other.

[0004] In view of the above-mentioned actual situation, the purpose of the present invention is to provide a method for estimating the internal degradation state of a deteriorated battery and a measurement system for executing the method, which can further improve the reproducibility, reliability and comprehensibility of the estimation of the state of battery capacity degradation by performing a fitting operation that takes into account the electrochemical characteristics of the battery.

[0005] To achieve the above-mentioned object, a first aspect of the present invention is a method for estimating the internal degradation state of a deteriorated battery. In this method, a target charge curve represented by ampacity and voltage is obtained for a target battery for which capacity degradation is estimated. The target charge curve is differentiated by the ampacity with respect to the voltage to obtain a differential value, and a target capacity characteristic curve represented by the ampacity and the differential value is calculated. For another battery of the same type as the target battery, a reference capacity characteristic curve represented by the ampacity and the differential value is calculated based on reference data including the ampacity and voltage. Changes in multiple parameters are obtained by fitting the reference capacity characteristic curve to the target capacity characteristic curve, thereby performing actual estimation processing for estimating capacity degradation of the target battery. In the fitting operation, the reference capacity characteristic curve and the target capacity characteristic curve are divided into a low ampacity region and a high ampacity region. The low ampacity region and the high ampacity region with a stronger correlation are fitted first, followed by fitting the low ampacity region and the high ampacity region with a weaker correlation.

[0006] Furthermore, in order to achieve the above-mentioned object, a second aspect of the present invention is a measurement system for executing a method for estimating the internal degradation state of a deteriorated battery, the system comprising: a charger for charging a target battery whose capacity is estimated to be deteriorated; and an estimating device connected to the charger, the estimating device being configured to: obtain a target charging curve represented by current carrying capacity and voltage based on the charging current and charging voltage supplied to the target battery, differentiate the current carrying capacity with respect to the target charging curve by the voltage to obtain a differential value, calculate a target capacity characteristic curve represented by the current carrying capacity and the differential value, and estimate the target capacity characteristic curve for another battery of the same type as the target battery. A battery is configured to calculate a reference capacity characteristic curve represented by the current carrying capacity and the differential value based on reference data including the current carrying capacity and the voltage, and to perform actual estimation processing for estimating capacity degradation of the target battery by obtaining changes in multiple parameters through a fitting operation of fitting the reference capacity characteristic curve to the target capacity characteristic curve. In the fitting operation, the reference capacity characteristic curve and the target capacity characteristic curve are divided into a low current carrying capacity region and a high current carrying capacity region, and after fitting the low current carrying capacity region and the high current carrying capacity region with a stronger correlation first, the low current carrying capacity region and the high current carrying capacity region with a weaker correlation are fitted.

[0007] The above-described method for estimating the internal degradation state of a deteriorated battery and the measurement system for executing the method can further improve the reproducibility, reliability, and comprehensibility of estimating the capacity degradation state of the battery by performing a fitting operation that takes the electrochemical characteristics of the battery into consideration.

[0008] The above-mentioned objects, features and advantages will be easily understood from the following description of the embodiments with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 This is an explanatory diagram showing a measurement system that executes a method for estimating the internal degradation state of a degraded battery according to one embodiment of the present invention.

[0010] Figure 2 This is a graph showing the target charge curve and reference data of a degraded target battery using current carrying capacity and voltage.

[0011] Figure 3 This is a graph explaining the main causes of battery capacity degradation.

[0012] Figure 4 The left side graph is a graph showing the charging curve. Figure 4 The right-hand graph of FIG. 1 is a graph showing a characteristic curve of the current-carrying capacity and the differential value obtained by differentiating the current-carrying capacity with respect to the charging curve using the voltage.

[0013] Figure 5 The left side graph is a graph showing the charging curve. Figure 5 The right-hand graph of FIG. 1 is a graph showing a characteristic curve of a differential value obtained by differentiating the current carrying capacity with respect to a charging curve and voltage.

[0014] Figure 6 This is a flowchart showing the processing flow of a method for estimating the internal degradation state of a degraded battery.

[0015] Figure 7 This is a flowchart showing the actual estimation process of the method for estimating the internal degradation state of a deteriorated battery.

[0016] Figure 8A This is a first charging curve graph for explaining changes in charging curves based on the fitting operation. Figure 8B This is a first characteristic curve diagram for explaining the fitting operation between characteristic curves by the fitting operation.

[0017] Figure 9A This is a second charging curve graph for explaining changes in charging curves based on the fitting operation. Figure 9B This is a second characteristic curve diagram for explaining the fitting operation between characteristic curves based on the fitting operation.

[0018] Figure 10A This is a third charging curve graph for explaining changes in charging curves based on the fitting operation. Figure 10BThis is a third characteristic curve diagram for explaining the fitting operation between characteristic curves based on the fitting operation.

[0019] Figure 11A This is a fourth charging curve graph for explaining changes in charging curves based on the fitting operation. Figure 11B This is a fourth characteristic curve diagram for explaining the fitting operation between characteristic curves based on the fitting operation. DETAILED DESCRIPTION

[0020] Hereinafter, the present invention will be described in detail with reference to the accompanying drawings by way of examples of preferred embodiments.

[0021] like Figure 1 As shown, a method for estimating the internal degradation state of a degraded battery according to one embodiment of the present invention uses a measurement system 100 to estimate the capacity degradation of a battery to be measured (hereinafter referred to as target battery OB). The measurement system 100 includes a placement unit 110, a charger 120, and an estimation device 140. The target battery OB is placed in the placement unit 110. The charger 120 charges the target battery OB placed in the placement unit 110. The estimation device 140 is communicatively connected to the charger 120 to actually estimate the capacity degradation of the target battery OB.

[0022] The target battery OB is a secondary battery having a positive electrode and a negative electrode capable of outputting power (current, voltage) and capable of being charged via the positive and negative electrodes. The type of secondary battery is not particularly limited, and examples thereof include lithium-ion secondary batteries, lithium-ion polymer secondary batteries, lead-acid batteries, and nickel-based batteries. In this embodiment, a lithium-ion secondary battery is used as the target battery OB. The number of target batteries OB measured by the measurement system 100 is not limited to one, and may be multiple.

[0023] The charger 120 includes a housing 122 and a pair of terminals 124 (a positive terminal 124a and a negative terminal 124b) mounted on the housing 122. The pair of terminals 124 are electrically connected to the target battery OB, which is placed in the placement section 110, via wiring 126. Disposed within the housing 122 are a power supply unit 128 capable of supplying power to the pair of terminals 124; an ammeter 130 for detecting the charging current supplied to the target battery OB from the power supply unit 128; and a voltmeter 132 for detecting the charging voltage supplied to the target battery OB from the power supply unit 128.

[0024] The power supply unit 128 outputs DC power (DC current, DC voltage) according to the state of the target battery OB. A storage-type DC power supply capable of supplying DC power is suitable for the power supply unit 128. The power supply unit 128 may also be configured to convert AC power supplied from the charger 120 to DC power. An ammeter 130 is connected in series with the power supply unit 128. The ammeter 130 detects the charging current output from the power supply unit 128. A voltmeter 132 is connected in parallel with the power supply unit 128 and ammeter 130. The voltmeter 132 detects the charging voltage (terminal voltage) of the target battery OB.

[0025] The estimation device 140 includes a data logger 142 (storage device) connected to the charger 120 and an information processing device 144 connected to the data logger 142. The data logger 142 is communicatively connected to the ammeter 130 and voltmeter 132 of the charger 120. The data logger 142 is a storage device that acquires and stores the charging current detected by the ammeter 130 and the charging voltage detected by the voltmeter 132. The data logger 142 can be a conventional hard disk drive (HDD), solid-state drive (SSD), or offline storage device. Although not shown, the data logger 142 includes an input / output interface, a processor, a timer, and the like (not shown). The input / output interface is communicatively connected to the ammeter 130, voltmeter 132, and information processing device 144 via a communication line 134. The processor controls the writing, reading, and erasing of the charging current and charging voltage. Alternatively, the data logger 142 may be provided in the charger 120. The data logger 142 may also receive the charging current and charging voltage from the charger 120 via wireless communication.

[0026] The data logger 142 measures time using a timer. It periodically and continuously acquires the charging current and voltage from the charger 120 and stores the data in association with time. This data is used to calculate the charging curve (charging characteristics, QV curve) of the target battery OB, expressed in terms of current carrying capacity (mAh) and charging voltage (V).

[0027] The information processing device 144 has one or more processors, memories, input / output interfaces, and electronic circuits. The memories can be applied to various drives (HDD, SSD, etc.), or can include memories attached to processors, integrated circuits, etc. By executing unillustrated programs stored in the memories by one or more processors, a plurality of functional modules for performing information processing are formed in the information processing device 144. In addition, at least a portion of each functional module may also have an integrated circuit such as an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or an electronic circuit including discrete devices.

[0028] Specifically, information processing device 144 includes a charging curve acquisition unit 146, a storage unit 148, and a fitting unit 150 as functional modules. Charging curve acquisition unit 146 acquires the charging current, charging voltage, time, and other information stored in data logger 142 to calculate the charging curve for target battery OB. Hereinafter, the charging curve for target battery OB will be referred to as target charging curve 10. Target charging curve 10 is a curve that plots the change in voltage relative to the current carrying capacity during charging of target battery OB. Figure 2 represents the object charging curve 10. Figure 2 In FIG. 1 , the target charging curve 10 is represented by a graph with the horizontal axis representing the current carrying capacity and the vertical axis representing the voltage.

[0029] like Figure 1 and Figure 2 As shown, the target charging curve 10 can be calculated using a known method. For example, the charging curve acquisition unit 146 calculates the cumulative charging current based on the charging current and time when charging the target battery OB from 0% SOC (State of Charge) to 100% (fully charged). This cumulative charging current corresponds to the current carrying capacity. The charging curve acquisition unit 146 can obtain the target charging curve 10 by plotting the charging voltage corresponding to the increase in the cumulative charging current. The charging curve acquisition unit 146 stores the obtained target charging curve 10 in the storage unit 148. The charging curve acquisition unit 146 may also store multiple data points that correspond to the current carrying capacity and charging voltage that constitute the target charging curve 10 in the storage unit 148 instead of the target charging curve 10. Alternatively, the measurement system 100 may calculate the target charging curve 10 using the data logger 142 and transmit the target charging curve 10 to the information processing device 144.

[0030] In addition to storing the target charge curve 10 acquired by the charge curve acquisition unit 146, the storage unit 148 also pre-stores reference data 20 for executing the method for estimating the internal degradation state of the degraded battery. In the present embodiment, the reference data 20 is obtained by performing a destructive inspection on another battery of the same type as the target battery OB (a battery manufactured using the same manufacturing method) and before degradation (unused, new).

[0031] The fitting unit 150 estimates the capacity degradation of the target battery OB by fitting the target charging curve 10 stored in the storage unit 148 with the reference data 20. The main causes of battery capacity degradation and the details of the fitting operation will be described below.

[0032] Secondary batteries (lithium-ion secondary batteries) such as Figure 3 As shown in the left-hand graph, the positive electrode PE and negative electrode NE each have a QV curve (hereinafter referred to as the positive electrode QV curve 22 and the negative electrode QV curve 24). The positive electrode QV curve 22 and the negative electrode QV curve 24 can be obtained by performing a destructive test. For example, a secondary battery is split (destroyed) into a positive electrode PE and a negative electrode NE to form a half-cell. After the split positive electrode PE and negative electrode NE are attached to the opposite electrode side with a separator, Li foil (lithium foil) is attached to the opposite electrode side and charging is performed. The positive electrode QV curve 22 and the negative electrode QV curve 24 are obtained by monitoring the charging current and charging voltage at this time.

[0033] The positive electrode QV curve 22 is represented by a graph with the horizontal axis being the current carrying capacity (Q) and the vertical axis being the voltage (V). In the positive electrode QV curve 22, the voltage increases as the current carrying capacity increases. Specifically, in the positive electrode QV curve 22, after the voltage rises sharply at low current carrying capacity, the voltage remains roughly constant even if the current carrying capacity increases, and as it approaches a higher current carrying capacity, the voltage rises. On the other hand, in the negative electrode QV curve 24, as the current carrying capacity increases, the voltage drops. Specifically, in the negative electrode QV curve 24, after the voltage drops sharply at low current carrying capacity, the voltage remains roughly constant even if the current carrying capacity increases, and as it approaches a higher current carrying capacity, the voltage gradually drops. And, as Figure 3 As shown in the right graph of the figure, the difference between the positive electrode QV curve 22 and the negative electrode QV curve 24 becomes the charging curve between the opposite poles of the secondary battery. Figure 3 The charging curve between opposite poles of the secondary battery shown in the right curve is called the full battery QV curve 26. That is, in the sense of the curve formed by combining the positive electrode PE and the negative electrode NE as half cells, the full battery QV curve is represented by Figure 3 The charging curve between opposite poles of the secondary battery shown in the right curve graph is the full battery QV curve 26.

[0034] Here, the capacity degradation of the secondary battery can be attributed to the following four main factors, each of which appears in the positive electrode QV curve 22, the negative electrode QV curve 24, and the full battery QV curve 26. Figure 3 In the figure, changes in the positive electrode QV curve 22 , the negative electrode QV curve 24 , and the full battery QV curve 26 in the secondary battery after deterioration are exemplified by two-dot chain lines.

[0035] (1) The capacity of the positive electrode PE decreases → the positive electrode QV curve 22 in the high current carrying capacity region moves toward the low current carrying capacity direction

[0036] (2) Capacity reduction of negative electrode NE → shift of negative electrode QV curve 24 in the high current carrying capacity region toward low current carrying capacity

[0037] (3) Reduction of lithium ions → Deviation in current carrying capacity due to the shift of the positive electrode QV curve 22 in the low current carrying capacity region toward the low current carrying capacity direction and the shift of the negative electrode QV curve 24 in the low current carrying capacity region toward the high current carrying capacity direction

[0038] (4) Resistance increase → Increase in the voltage difference between the positive electrode QV curve 22 and the negative electrode QV curve 24, or increase in the voltage deviation in the full cell QV curve 26

[0039] In other words, the main causes of secondary battery capacity degradation are four parameters: decreased positive electrode PE capacity, decreased negative electrode NE capacity, decreased lithium ions, and increased resistance. During the fitting process, the positive electrode QV curve 22, negative electrode QV curve 24, and full-cell QV curve 26, obtained through a destruction test of a reference battery, are used as reference data 20. This data 20 is then aligned with the target charge curve 10. The information processing device 144 analyzes the capacity degradation of the target battery OB based on the changes in each parameter during the fitting process.

[0040] However, the relationships between the four parameters, including the positive electrode QV curve 22, negative electrode QV curve 24, and full-cell QV curve 26, indicate that the parameters are interlinked in the charging curve. In conventional fitting operations, adjusting one parameter also changes the other. Therefore, even by simply fitting the target charging curve 10 to the reference data 20, it is impossible to determine which of the two parameters is the correct one.

[0041] Therefore, in the method for estimating the internal degradation state of a degraded battery according to this embodiment, the fitting unit 150 differentiates the current carrying capacity with respect to the target charging curve 10 by voltage to obtain a differential value, thereby extracting the characteristic points of the shape of the target charging curve 10. That is, Figure 4The target charge curve 10 represented by the current carrying capacity and voltage as shown is converted into a characteristic curve represented by the current carrying capacity and the differential value (dQ / dV). Hereinafter, this characteristic curve is referred to as the target capacity characteristic curve 12. Figure 4 The graph on the right shows the target capacitance characteristic curve 12, with the horizontal axis representing the current carrying capacity and the vertical axis representing the differential value. In the internal degradation state estimation method, a fitting operation is first performed on the converted target capacitance characteristic curve 12. This allows the resistance rise (voltage deviation) parameter to be temporarily ignored.

[0042] exist Figure 4 In the right-hand graph, the differential value of the target capacity characteristic curve 12 has two peaks in the low current carrying capacity (low SOC) region. Beyond these two peaks, the differential value of the target capacity characteristic curve 12 gradually decreases as the current carrying capacity increases. Here, the correlation between the shape of the target capacity characteristic curve 12 and the shape of the characteristics of the positive electrode PE and negative electrode NE of the battery is examined.

[0043] Regarding the positive electrode QV curve 22, the characteristic curve of the current carrying capacity and the differential value obtained by differentiating the current carrying capacity by voltage becomes Figure 4 The shape is indicated by a single dotted line in the right graph. This characteristic curve is hereinafter referred to as the positive electrode characteristic curve 32. In addition, regarding the negative electrode QV curve 24, the characteristic curve of the current carrying capacity and the differential value obtained by differentiating the current carrying capacity by voltage becomes Figure 4 The shape indicated by the double-dashed line in the right graph of FIG. This characteristic curve is hereinafter referred to as the negative electrode characteristic curve 34.

[0044] Comparing the target capacity characteristic curve 12, the positive electrode characteristic curve 32, and the negative electrode characteristic curve 34, in the low current carrying capacity region, the shape of the target capacity characteristic curve 12 is similar to that of the negative electrode characteristic curve 34. In other words, in the low current carrying capacity region, the target capacity characteristic curve 12 shows a strong correlation with the negative electrode characteristic curve 34. In contrast, in the high current carrying capacity (high SOC) region, the shape of the target capacity characteristic curve 12 is similar to that of the positive electrode characteristic curve 32. In other words, in the high current carrying capacity region, the target capacity characteristic curve 12 shows a strong correlation with the positive electrode characteristic curve 32.

[0045] Here, in lithium-ion secondary batteries, the correlation between the target capacity characteristic curve 12 and the negative electrode characteristic curve 34 in the low current carrying capacity region is stronger than the correlation between the target capacity characteristic curve 12 and the positive electrode characteristic curve 32 in the high current carrying capacity region. The target capacity characteristic curve 12 and the negative electrode characteristic curve 34 in the low current carrying capacity region have two peaks. It can be said that the parameter affecting the capacity drop of the positive electrode PE has little influence on the region between these two peaks. In other words, in the low current carrying capacity region, the parameter affecting the capacity drop of the negative electrode NE is highly independent of other parameters. On the other hand, the target capacity characteristic curve 12 and the positive electrode characteristic curve 32 in the high current carrying capacity region have no clear peaks and are therefore influenced by the parameter affecting the capacity drop of the negative electrode NE.

[0046] Thus, the fitting unit 150 sequentially fits the regions with strong correlation (independence) when fitting the target capacity characteristic curve 12 of the target battery OB with the positive electrode characteristic curve 32 and the negative electrode characteristic curve 34 included in the reference capacity characteristic curve 30. Specifically, the fitting unit 150 first performs a low-current-carrying capacity fitting operation in the low-current-carrying capacity region, fitting the target capacity characteristic curve 12 with the negative electrode characteristic curve 34 (reference data 20). During the low-current-carrying capacity fitting operation, one of the target capacity characteristic curve 12 and the negative electrode characteristic curve 34 is shifted in the voltage direction to eliminate any deviation in the voltage direction. This substantially adjusts the parameter for the capacity drop of the negative electrode NE.

[0047] Next, the fitting unit 150 performs a high-capacity fitting operation in the high-capacity region, fitting the target capacity characteristic curve 12 to the positive electrode characteristic curve 32 (reference data 20). During the high-capacity fitting operation, the target capacity characteristic curve 12 or the reference data 20 that shifted during the low-capacity fitting operation is shifted in the voltage direction to eliminate any deviation in that direction. This roughly adjusts the parameter for the decrease in the positive electrode PE capacity. Furthermore, during the high-capacity fitting operation, the target capacity characteristic curve 12 or the reference data 20 that shifted during the low-capacity fitting operation is shifted in the current-carrying capacity direction to eliminate any deviation in that direction. This roughly adjusts the parameter for the decrease in lithium ions.

[0048] Specifically, in the internal degradation state estimation method according to this embodiment, a low ampacity fitting operation is performed before a high ampacity fitting operation, thereby pre-setting the capacity reduction parameters of the negative electrode NE. Then, during the high ampacity fitting operation, with the capacity reduction parameters of the negative electrode NE pre-set, both the capacity reduction parameters of the positive electrode PE and the lithium ion reduction parameters can be stably adjusted.

[0049] Furthermore, the fitting unit 150 performs a voltage fitting operation to adjust the parameter of the resistance rise (voltage deviation) which is neglected in the above-mentioned low current carrying capacity fitting operation and high current carrying capacity fitting operation. Figure 5 As shown, the fitting unit 150 converts the target charge curve 10 of the target battery OB into a characteristic curve represented by the differential value of the current carrying capacity differentiated by the voltage and the voltage (hereinafter referred to as the target voltage characteristic curve 14). Correspondingly, the fitting unit 150 converts the full-battery QV curve 26 into a characteristic curve represented by the voltage and the differential value (hereinafter referred to as the full-battery characteristic curve 42) by differentiating the current carrying capacity by the voltage. In other words, the full-battery characteristic curve 42 corresponds to the reference voltage characteristic curve 40 calculated based on the reference data 20 obtained by the destructive inspection.

[0050] In other words, the fitting unit 150 extracts the characteristic points of the shape by differentiating the parameter of the resistance rise that changes in the Y-axis direction (voltage direction) in the target voltage characteristic curve 14 and the full battery characteristic curve 42. Figure 5 The correlation between the target voltage characteristic curve 14 and the full-cell characteristic curve 42 is weaker than the correlation between the target capacity characteristic curve 12 and the negative electrode characteristic curve 34, and the correlation between the target capacity characteristic curve 12 and the positive electrode characteristic curve 32. This is because, as described above, the full-cell QV curve 26 is calculated based on the difference between the positive electrode QV curve 22 and the negative electrode QV curve 24 and is easily affected by parameters such as the capacity drop of the positive electrode PE, the capacity drop of the negative electrode NE, and the reduction of lithium ions.

[0051] Therefore, the fitting unit 150 performs a voltage fitting operation. Specifically, the voltage characteristic curve 14 and the full-cell characteristic curve 42 (reference data 20) that shifted during the high current-carrying capacity fitting operation are shifted in the voltage direction (X-axis direction) to eliminate the deviation in the voltage direction. This allows the parameters that cause resistance increase to be roughly adjusted. Specifically, in the internal degradation state estimation method, the parameters of negative electrode NE capacity decrease, positive electrode PE capacity decrease, and lithium ion reduction are first changed and pre-fixed, and then the parameters that cause resistance increase are adjusted. Therefore, the fitting unit 150 can set the changes in all parameters that are the main causes of capacity degradation.

[0052] After the voltage fitting operation, fitting unit 150 performs a fine-tuning fitting operation, specifically, fine-tuning the deviation between target charge curve 10 of target battery OB and reference data 20 (negative electrode QV curve 24, positive electrode QV curve 22, and full battery QV curve 26). As described above, even when characteristic curves obtained by differentiating ampacity with respect to voltage are fitted to each other, slight deviations may occur in the charge curves represented by ampacity and voltage (target charge curve 10 and reference data 20 (negative electrode QV curve 24, positive electrode QV curve 22, and full battery QV curve 26)). Therefore, fitting unit 150 performs a final fine-tuning fitting operation on the charge curves to eliminate these slight deviations.

[0053] During this fine-tuning fitting operation, the fitting unit 150 simultaneously adjusts the parameters for the decrease in positive electrode PE capacity, the decrease in negative electrode NE capacity, the reduction in lithium ions, and the increase in resistance. Since these parameters are essentially adjusted through the low-current-carrying capacity fitting operation, the high-current-carrying capacity fitting operation, and the voltage fitting operation described above, the changes in these parameters due to the fine-tuning fitting operation are minimal.

[0054] Furthermore, during the fine-tuning fitting operation, the fitting unit 150 may also set upper and lower limits for each capacity degradation parameter. Furthermore, the charging curve region used in the fine-tuning fitting operation may include the entire ampacity range (0-100%), or may be divided into a low ampacity region used in the low ampacity fitting operation and a high ampacity region used in the high ampacity fitting operation.

[0055] The fitting unit 150 completes all fitting operations by completing the fine-tuning fitting operation. Upon completion, the fitting unit 150 stores the various capacity degradation parameters (capacity reduction of the positive electrode PE, capacity reduction of the negative electrode NE, reduction of lithium ions, and increase in resistance) that have changed through each fitting operation in the storage unit 148. Furthermore, the information processing device 144 notifies the user of the analyzed capacity degradation parameters via a notification mechanism (not shown) (e.g., a monitor). This allows the user to identify the capacity degradation status of the target battery OB.

[0056] Furthermore, in the internal degradation state estimation method, not only can the measurement system 100 measure the capacity degradation of the target battery OB after degradation (after use) but also perform initial processing to extract various parameters related to capacity degradation on the target battery OB before degradation (before use, new) using the above-described method. Thus, when using the internal degradation state estimation method, the various parameters related to capacity degradation of the target battery OB before degradation relative to the reference data 20 can be obtained in advance. The information processing device 144 can store the various parameters of the target battery OB before degradation in the storage unit 148 for use in estimating the capacity degradation of the target battery OB after degradation. Specifically, by adding or subtracting the differences between the various parameters of the target battery OB before degradation and the reference data 20 from the various parameters of the target battery OB after degradation, the degree of capacity degradation in the target battery OB after degradation can be detected with higher accuracy.

[0057] The measurement system 100 according to this embodiment is basically configured as described above. Figure 6 and Figure 7 The flow of a method for estimating the internal degradation state of a deteriorated battery will be described.

[0058] In the internal degradation state estimation method, to estimate the capacity degradation of the target battery OB, the user measures reference data 20 using a battery of the same type and stores the data in advance in the storage unit 148 of the information processing device 144 (step S10). As described above, the positive electrode QV curve 22 and the negative electrode QV curve 24 of the reference data 20 can be obtained by performing a destructive inspection on the battery of the same type. The full battery QV curve 26 can be obtained from the positive electrode QV curve 22 and the negative electrode QV curve 24.

[0059] In the internal degradation state estimation method, initial processing is then performed on the target battery OB before degradation to confirm the initial capacity level (step S20). During the initial processing, the measurement system 100 charges the target battery OB before degradation using the charger 120. The charging current and charging voltage during charging are stored in the data logger 142 to obtain an initial charging curve (not shown). The aforementioned fitting operation is performed based on the initial charging curve and the reference data 20. The processing flow of the fitting operation is the same as that for estimating the capacity degradation of the target battery OB after degradation and will be described in detail in the processing flow of the actual estimation process below.

[0060] This initial processing allows the measurement system 100 and the user to identify the initial state of the target battery OB, for which capacity degradation is actually estimated. The measurement system 100 stores the parameters obtained through the initial processing, indicating the capacity decrease of the positive electrode PE, the capacity decrease of the negative electrode NE, the decrease in lithium ions, and the increase in resistance, in the target battery OB before degradation, in the storage unit 148. However, since the degradation state can be identified using only the capacity degradation parameters obtained in the actual estimation process, this initial processing does not necessarily need to be performed.

[0061] Then, the internal degradation state estimation method performs actual estimation processing for estimating capacity degradation on the degraded target battery OB (step S30). Figure 7 As shown, during the actual estimation process, the measurement system 100 charges the degraded target battery OB using the charger 120 and stores the charging current and charging voltage in the data logger 142 (step S31). Next, the charging curve acquisition unit 146 of the information processing device 144 acquires the target charging curve 10 based on the stored charging current and charging voltage (step S32). Thereafter, the fitting unit 150 of the information processing device 144 fits the target charging curve 10 to the reference data 20.

[0062] like Figure 8A and Figure 8B As shown, in the fitting operation, the fitting unit 150 differentiates the current carrying capacity of the target charging curve 10 with the voltage to obtain a differential value, and converts the target charging curve 10 into the target capacity characteristic curve 12. Similarly, the positive electrode QV curve 22 of the reference data 20 is converted into the positive electrode characteristic curve 32. Similarly, the negative electrode QV curve 24 of the reference data 20 is converted into the negative electrode characteristic curve 34 (step S33). In addition, Figure 8A (and later Figure 9A 、 Figure 10A 、 Figure 11A ), in order to facilitate comparison of the target charge curve 10 and the reference data 20, the full battery QV curve 26 is represented by the difference between the positive electrode QV curve 22 and the negative electrode QV curve 24. Figure 8A As illustrated, before the fitting operation, the target charging curve 10 deviates from the full-battery QV curve 26 .

[0063] The fitting unit 150 sequentially extracts regions with strong correlation (independence) from the target capacity characteristic curve 12, the positive electrode characteristic curve 32, and the negative electrode characteristic curve 34, and performs fitting operations in descending order of correlation. Specifically, the fitting unit 150 first performs a low current carrying capacity fitting operation (step S34) to fit the target capacity characteristic curve 12 in the low current carrying capacity region (current carrying capacity range of approximately 0% to 30%) with the negative electrode characteristic curve 34. Figure 9BAs shown, one of the target capacity characteristic curve 12 and the negative electrode characteristic curve 34 (at Figure 9B In the case of the negative electrode characteristic curve 34), the deviation in the direction of the differential value is adjusted. Thus, the parameter of the capacity drop of the negative electrode NE changes through the low current carrying capacity fitting operation. Figure 9A In the illustrated graph, the subject charge curve 10 and the full-cell QV curve 26 are slightly closer to each other in the low-ampacity region due to the low-ampacity fitting operation.

[0064] Next, the fitting unit 150 performs a high current carrying capacity fitting operation to fit the target capacity characteristic curve 12 in the high current carrying capacity region (current carrying capacity range of about 80% to 100%) with the positive electrode characteristic curve 32 (step S35). Figure 10B As shown, one of the target capacity characteristic curve 12 and the positive electrode characteristic curve 32 (at Figure 10B In the process, the positive electrode characteristic curve 32) moves in the direction of the differential value and the current carrying capacity, and the deviation in the direction of the differential value and the current carrying capacity is adjusted. Thus, through the high current carrying capacity fitting operation, the parameters of the capacity drop of the positive electrode PE and the reduction of lithium ions are changed respectively. Figure 10A In the illustrated graph, the high-current-carrying-capacity fitting operation brings the target charge curve 10 and the full-cell QV curve 26 closer together in the high-current-carrying-capacity region, and the current-carrying capacity of the full-cell QV curve 26 decreases significantly. In other words, it can be said that the capacity degradation of the illustrated target battery OB is significantly affected by the reduction in lithium ions.

[0065] Next, the fitting unit 150 converts the target charging curve 10 into the target voltage characteristic curve 14. Similarly, the fitting unit 150 converts the full-battery QV curve 26 of the reference data 20 into the full-battery characteristic curve 42 (step S36). Furthermore, the fitting unit 150 performs a voltage fitting operation to fit the target voltage characteristic curve 14 to the full-battery characteristic curve 42 (step S37). Figure 11B As shown, one of the target voltage characteristic curve 14 and the full battery characteristic curve 42 (at Figure 11B In the case of the full battery characteristic curve 42), the full battery characteristic curve 42 moves in the voltage direction to compensate for the deviation in the voltage direction. Thus, the resistance rise parameter changes through the voltage fitting operation. Figure 11A In the illustrated graph, the target charge curve 10 and the full-battery QV curve 26 are substantially consistent with each other due to the voltage fitting operation.

[0066] At the end of the fitting process, fitting unit 150 performs a fine-tuning fitting process (step S38). This process eliminates minor deviations between target charge curve 10 and reference data 20 (positive electrode QV curve 22, negative electrode QV curve 24, and full-cell QV curve 26), thereby fitting target charge curve 10 to reference data 20.

[0067] When the above actual presumption process is completed, Figure 6 As shown, the information processing device 144 compares the various capacity degradation parameters obtained by the initial processing and the actual estimation processing to estimate the degradation state of the target battery OB and notifies the user of this degradation state through an appropriate notification mechanism (step S40). For example, the information processing device 144 performs addition or subtraction between the various capacity degradation parameters obtained by the initial processing and the various capacity degradation parameters obtained by the actual estimation processing. As a result, the user, viewing the estimation results notified by the information processing device 144, can accurately identify the degradation state of the target battery OB after degradation.

[0068] The present invention is not limited to the above-described embodiment and can be modified in various ways according to the main purpose of the invention. For example, in the method for estimating the internal degradation state of a deteriorated battery involved in this embodiment, a fitting operation is first performed on the low current-carrying capacity region with a strong correlation on the characteristic curve. However, in a case where the correlation of the high current-carrying capacity region on the characteristic curve is stronger than the correlation of the low current-carrying capacity region, the fitting operation of the high current-carrying capacity region can be performed first in the internal degradation state estimation method. Regarding the correlation between the object capacity characteristic curve 12 and the positive electrode characteristic curve 32 and the negative electrode characteristic curve 34, the fitting unit 150 can also calculate the correlation coefficient by a known calculation mechanism and determine the order of the fitting operation based on the correlation coefficient.

[0069] Furthermore, the low current-carrying capacity fitting operation (fitting the target capacity characteristic curve 12 with the negative electrode characteristic curve 34) and the high current-carrying capacity fitting operation (fitting the target capacity characteristic curve 12 with the positive electrode characteristic curve 32) are not limited to being performed once each. For example, the high current-carrying capacity fitting operation may be performed after the low current-carrying capacity fitting operation, and then the low current-carrying capacity fitting operation may be performed again. Alternatively, the low current-carrying capacity fitting operation may be performed after the high current-carrying capacity fitting operation, and then the high current-carrying capacity fitting operation may be performed again. In this way, by alternately performing the low current-carrying capacity fitting operation and the high current-carrying capacity fitting operation multiple times, the fitting accuracy can be improved.

[0070] The technical ideas and effects that can be grasped from the above-described embodiments are described below.

[0071] A first embodiment of the present invention is a method for estimating the internal degradation state of a deteriorated battery. For a target battery OB for which capacity degradation is estimated, a target charge curve 10, represented by ampacity and voltage, is obtained. The target charge curve 10 is differentiated by voltage to obtain a differential value, and a target capacity characteristic curve 12, represented by the ampacity and differential value, is calculated. A reference capacity characteristic curve 30, represented by the ampacity and differential value, is calculated based on reference data 20 of another battery of the same type as the target battery OB. A fitting operation of fitting the reference capacity characteristic curve 30 to the target capacity characteristic curve 12 is performed to obtain changes in multiple parameters, thereby performing actual estimation processing for the capacity degradation of the target battery OB. In the fitting operation, the reference capacity characteristic curve 30 and the target capacity characteristic curve 12 are divided into a low ampacity region and a high ampacity region. The low and high ampacity regions with a stronger correlation are fitted first, followed by the low and high ampacity regions with a weaker correlation.

[0072] As described above, the internal degradation state estimation method for a deteriorated battery enables a fitting operation that takes into account the electrochemical characteristics of the battery. Specifically, the internal degradation state estimation method calculates the target capacity characteristic curve 12 based on the charging curve, thereby limiting the various parameters used to estimate capacity degradation. Furthermore, during the fitting operation, the reference capacity characteristic curve 30 and the target capacity characteristic curve 12, whichever has a stronger correlation in the low and high current-carrying capacity regions, are fitted first. This allows the internal degradation state estimation method to set parameters for the stronger correlation first. This further improves the reproducibility, reliability, and comprehensibility of the battery capacity degradation state estimation method.

[0073] Furthermore, in the fitting operation, a low-capacity fitting operation is first performed, fitting the reference capacity characteristic curve 30 in the low-capacity region, which has a stronger correlation, to the target capacity characteristic curve 12. Next, a high-capacity fitting operation is performed, fitting the reference capacity characteristic curve 30 in the high-capacity region, which has a weaker correlation, to the target capacity characteristic curve 12. In this way, in the internal degradation state estimation method, by performing the fitting operations in the low-capacity region and then the high-capacity region in this order, it is possible to extract changes in each of the multiple parameters, including the capacity drop of the negative electrode NE, the capacity drop of the positive electrode PE, and the reduction in lithium ions.

[0074] Furthermore, the current carrying capacity is differentiated with respect to the target charge curve 10 to obtain a differential value, and a target voltage characteristic curve 14 represented by the voltage and the differential value is calculated. In the fitting operation, after fitting the reference capacity characteristic curve 30 to the target capacity characteristic curve 12, a voltage fitting operation is performed to fit the reference voltage characteristic curve 40 obtained by differentiating the current carrying capacity with respect to the reference data 20 to the target voltage characteristic curve 14. This allows the internal degradation state estimation method to stably extract parameters based on voltage deviations caused by resistance increase.

[0075] Furthermore, during the fitting operation, a fine-tuning fitting operation is performed after the voltage fitting operation to fine-tune the target charge curve 10 to the reference data 20 (full-cell QV curve 26). This allows the internal degradation state estimation method to eliminate even slight deviations caused by the characteristic curve fitting operation. Consequently, the internal degradation state estimation method enables the capacity degradation of the target battery OB to be estimated with higher accuracy.

[0076] Furthermore, an initial process is performed. During this initial process, a target charge curve 10 of the target battery OB before degradation is acquired. Changes in various parameters of the target battery OB before degradation are then acquired based on the target charge curve 10. During the actual estimation process, capacity degradation of the target battery OB is estimated based on the various parameters acquired in this actual estimation process and the various parameters acquired in the initial process. In this way, by using the various parameters acquired in the initial process and the various parameters acquired in the actual estimation process, the internal degradation state estimation method can better capture changes in various parameters that indicate capacity degradation.

[0077] Furthermore, the reference data 20 is obtained by destroying a battery of the same type as the target battery OB and separating it into its positive electrode PE and negative electrode NE. The reference data 20 includes a positive electrode QV curve 22, which represents the current carrying capacity and voltage of the positive electrode PE during charging, and a negative electrode QV curve 24, which represents the current carrying capacity and voltage of the negative electrode NE during charging. By applying the positive electrode QV curve 22 and the negative electrode QV curve 24 obtained by destroying the battery to the reference data 20, the internal degradation state estimation method can accurately obtain the reference data 20 used to estimate the capacity degradation of the target battery OB.

[0078] Furthermore, during the fitting operation, the positive electrode characteristic curve 32 and the negative electrode characteristic curve 34 are each fitted to the target capacity characteristic curve 12. The positive electrode characteristic curve 32 is obtained by differentiating the current carrying capacity with respect to the positive electrode QV curve 22, while the negative electrode characteristic curve 34 is obtained by differentiating the current carrying capacity with respect to the negative electrode QV curve 24. In this manner, by fitting the target capacity characteristic curve 12 with the negative electrode characteristic curve 34, the internal degradation state estimation method can accurately obtain parameters indicating capacity degradation of the negative electrode NE. Furthermore, by fitting the target capacity characteristic curve 12 with the positive electrode characteristic curve 32, the internal degradation state estimation method can accurately obtain parameters indicating capacity degradation of the positive electrode PE.

[0079] Furthermore, a second embodiment of the present invention is a measurement system 100 for executing a method for estimating the internal degradation state of a deteriorated battery, the measurement system 100 comprising: a charger 120 for charging a target battery OB whose capacity is estimated to be deteriorated; and an estimation device 140 connected to the charger 120. The estimation device 140 obtains a target charge curve 10 represented by current carrying capacity and voltage based on the charging current and charging voltage supplied to the target battery OB, differentiates the current carrying capacity with respect to the target charge curve 10 by voltage to obtain a differential value, calculates a target capacity characteristic curve 12 represented by the current carrying capacity and the differential value, and estimates the target capacity characteristic curve 12 for the same target battery OB as the target battery OB. For another type of battery, a reference capacity characteristic curve 30 represented by current carrying capacity and differential values ​​is calculated based on reference data 20 including current carrying capacity and voltage. A fitting operation is performed to fit the reference capacity characteristic curve 30 to the target capacity characteristic curve 12, thereby obtaining changes in various parameters and performing actual estimation processing for estimating capacity degradation of the target battery OB. In the fitting operation, the reference capacity characteristic curve 30 and the target capacity characteristic curve 12 are divided into a low current carrying capacity region and a high current carrying capacity region. The low current carrying capacity region and the high current carrying capacity region with a stronger correlation are fitted first, followed by the weaker correlation. Thus, by performing a fitting operation that takes into account the electrochemical characteristics of the battery, the measurement system 100 can further improve the reproducibility, reliability, and comprehensibility of battery capacity degradation.

Claims

1. A method for estimating the internal degradation state of a degraded battery, characterized in that: For an object battery (OB) estimated to have deteriorated capacity, a target charging curve (10) represented by current carrying capacity and voltage is obtained; Differentiating the current carrying capacity by the voltage in the target charging curve to obtain a differential value, and calculating a target capacity characteristic curve (12) represented by the current carrying capacity and the differential value; For another battery of the same type as the target battery, a reference capacity characteristic curve (30) represented by the current carrying capacity and the differential value is calculated based on reference data (20) including the current carrying capacity and the voltage, and a fitting operation is performed to fit the reference capacity characteristic curve to the target capacity characteristic curve to obtain changes in multiple parameters, thereby performing actual estimation processing for estimating capacity degradation of the target battery. In the fitting operation, the reference capacity characteristic curve and the target capacity characteristic curve are divided into a low current carrying capacity region and a high current carrying capacity region. A low current carrying capacity fitting operation is first performed to fit the reference capacity characteristic curve in the low current carrying capacity region, which has a stronger correlation with the high current carrying capacity region, with the target capacity characteristic curve. Next, a high current-carrying capacity fitting operation is performed to fit the reference capacity characteristic curve in the high current-carrying capacity region, which has a weaker correlation, with the target capacity characteristic curve.

2. The method for estimating the internal degradation state of a deteriorated battery according to claim 1, wherein: Differentiating the current carrying capacity with respect to the target charging curve by the voltage to obtain a differential value, and calculating a target voltage characteristic curve (14) represented by the voltage and the differential value, In the fitting operation, after fitting the reference capacity characteristic curve with the target capacity characteristic curve, the current carrying capacity is differentiated by the voltage according to the reference data to obtain a differential value, a reference voltage characteristic curve (40) represented by the voltage and the differential value is calculated, and a voltage fitting operation is performed to fit the reference voltage characteristic curve with the target voltage characteristic curve.

3. The method for estimating the internal degradation state of a deteriorated battery according to claim 2, wherein: In the fitting operation, after the voltage fitting operation, a fine-tuning fitting operation is performed to fit the object charging curve to the reference data through fine-tuning.

4. The method for estimating the internal degradation state of a deteriorated battery according to claim 1 or 3, wherein: performing an initial process in which the target charging curve of the target battery before degradation is acquired, and changes in the plurality of parameters of the target battery before degradation are acquired based on the target charging curve; In the actual estimation process, capacity degradation of the target battery is estimated based on the plurality of parameters acquired in the actual estimation process and the plurality of parameters acquired in the initial process.

5. The method for estimating the internal degradation state of a deteriorated battery according to claim 1 or 3, wherein: The reference data is obtained by breaking another battery of the same type as the target battery and separating it into a positive electrode and a negative electrode, The reference data includes: a positive electrode QV curve (22), which is represented by the current carrying capacity and voltage of the positive electrode when charged; and a negative electrode QV curve (24), which is represented by the current carrying capacity and voltage of the negative electrode when charged.

6. The method for estimating the internal degradation state of a deteriorated battery according to claim 5, wherein: In the fitting operation, a positive electrode characteristic curve (32) and a negative electrode characteristic curve (34) are respectively fitted to the target capacity characteristic curve, wherein the positive electrode characteristic curve is a curve obtained by differentiating the current carrying capacity with respect to the positive electrode QV curve using the voltage, and the negative electrode characteristic curve is a curve obtained by differentiating the current carrying capacity with respect to the negative electrode QV curve using the voltage.

7. A measuring system (100) for executing a method for estimating an internal degradation state of a degraded battery, characterized in that: The invention comprises: a charger (120) for charging a target battery whose capacity is estimated to be deteriorated; and an estimation device (140) connected to the charger. The estimating device is composed of: obtaining a target charging curve represented by current carrying capacity and voltage according to the charging current and charging voltage supplied to the target battery; Differentiating the current carrying capacity by the voltage with respect to the target charging curve to obtain a differential value, and calculating a target capacity characteristic curve represented by the current carrying capacity and the differential value, For another battery of the same type as the target battery, a reference capacity characteristic curve represented by the current carrying capacity and the differential value is calculated based on reference data including the current carrying capacity and the voltage, and a fitting operation is performed to fit the reference capacity characteristic curve to the target capacity characteristic curve to obtain changes in multiple parameters, thereby performing actual estimation processing for estimating capacity degradation of the target battery. In the fitting operation, the reference capacity characteristic curve and the target capacity characteristic curve are divided into a low current carrying capacity region and a high current carrying capacity region. A low current carrying capacity fitting operation is first performed to fit the reference capacity characteristic curve in the low current carrying capacity region, which has a stronger correlation with the high current carrying capacity region, with the target capacity characteristic curve. Next, a high current-carrying capacity fitting operation is performed to fit the reference capacity characteristic curve in the high current-carrying capacity region, which has a weaker correlation, with the target capacity characteristic curve.

Images