JP2020169943A - Storage battery state evaluation system - Google Patents

Abstract

To precisely evaluate the state of a storage battery system.SOLUTION: The storage battery state evaluation system is for evaluating the state of a storage battery system made of a plurality of storage battery cells. The storage battery state evaluation system includes: a memory for holding the voltages of at least two storage battery cells located differently in the distribution of voltages of a plurality of storage battery cells of the voltage of the plurality of storage battery cells; and a degradation state calculation unit for calculating the inclination of the voltage to the time in a resting time after at least two of the storage battery cells are discharged.SELECTED DRAWING: Figure 1

Description

The following description relates to an apparatus and method for evaluating the state of a secondary battery.

Techniques for assessing the state of health (SOH) of secondary batteries are important for the optimal use of secondary batteries by power storage systems, electric vehicles and other systems.

Specific examples of the SOH evaluation method include a method using a predetermined SOH function and a terminal voltage of a battery system (Patent Document 1), and a method based on a change in internal resistance measurable from the current-voltage characteristics of the battery system (Patent Document 1). 2) can be mentioned.

Japanese Unexamined Patent Publication No. 2012-42312 Japanese Unexamined Patent Publication No. 2004-31120

The related techniques described in Patent Documents 1 and 2 have the following problems.

The evaluation using the predetermined SOH function is accurate with respect to the measurement of individual battery cells. However, it is not accurate for the measurement of battery packs in which the SOH of each of the constituent battery cells is different.

In a storage battery system, there are variations in the health status of battery cells due to manufacturing. This variation may be expanded by the temperature distribution in each module or submodule, which acts as an environment for locally accelerating deterioration.

The storage battery system usually includes a cell balance controller system so that the full capacity of the battery is effectively used. However, the system-wide SOH is still most affected by the battery cell with the lowest SOH. This cell balance controller system hides the true characteristics of a degraded battery cell during charging and discharging. This is because the SOH is calculated using the system-wide voltage read while the cell balance controller system is running. This also applies to Patent Document 1 and Patent Document 2, and the true SOH cannot be clarified. In order to clarify the true SOH of the storage battery system, it is necessary to detect the distribution of the state of the battery cells, especially the cell having the lowest SOH.

In order to solve at least one of the above problems, the present invention is a storage battery state evaluation system for evaluating the state of a storage battery system composed of a plurality of storage battery cells, and the plurality of voltages of the plurality of storage battery cells are evaluated. A memory that holds the voltage of at least two storage battery cells having different positions in the voltage distribution of the storage battery cells, and a deterioration state calculation unit that calculates the inclination of the voltage with respect to time in the rest period after discharge of the at least two storage battery cells. It is characterized by having.

According to one aspect of the present invention, SOH can be evaluated more accurately than in the conventional technique.

Issues, configurations and effects other than those mentioned above will be clarified by the description of the following examples.

It is explanatory drawing of the voltage in the rest period after discharge of the battery system of Example 1 of this invention. It is explanatory drawing of the structure of the battery system in Example 1 of this invention. It is a functional block diagram of BMU, PCS and PC used in Example 1 of this invention. It is a functional block diagram of the PC in Example 1 of this invention. It is explanatory drawing of the example of the detailed calculation of dVt / dt by the SOH calculation processing unit of Example 1 of this invention. It is explanatory drawing of the calculation of Vt and Rt after the elapse of a predetermined time by the SOH calculation processing part of Example 2 of this invention. It is explanatory drawing of the relationship between SOH and dVt / dt, Vt and R in Example 1 of this invention. It is a functional block diagram of the SOH calculation processing part of Example 2 of this invention. It is explanatory drawing of the pre-accelerated test in Example 3 of this invention. It is explanatory drawing of the system self-accelerated test (SSAT) in Example 3 of this invention. It is a functional block diagram of the SOH calculation processing part of Example 4 of this invention. It is a flowchart which shows the processing of the SOH calibration part in the SOH calculation processing part of Example 4 of this invention. It is explanatory drawing of the correction of the slope of the SOH curve using the current capacity'in Example 4 of this invention. It is explanatory drawing which shows the example of the different SOC pattern of the battery pack which supports different types of loads in Example 4 of this invention. It is explanatory drawing of the calculation of the capacitance based on the open circuit voltage characteristic in Example 4 of this invention. FIG. 5 is an explanatory diagram of CCV vs. SOC characteristics for different C rates in Example 4 of the present invention. It is explanatory drawing of the voltage vs. SOC / capacity characteristic of a new battery and an old battery in Example 4 of this invention. It is explanatory drawing of the GUI displayed in Example 1 of this invention.

Here, a battery SOH evaluation method according to a preferred embodiment of the present invention will be described with reference to the drawings.

In a storage battery system consisting of battery cells connected in series and in parallel, the SOH (State of Health) of the system is affected by the distribution of SOH in each battery cell. Performance is limited by the battery with the lowest SOH. In a storage battery system equipped with a cell balance controller, it was found that the difference in the state of the battery cells appears during the rest period after discharge.

FIG. 1 is an explanatory diagram of a voltage in a rest period after discharge of the battery system according to the first embodiment of the present invention.

As shown in FIG. 1, the difference in voltage becomes remarkable by giving a pause period after discharging the battery system.

Therefore, it is a feature of the present invention to measure the voltage (at least two of V_max, V_ave and V_min) during the rest period after discharge. Here, V_max, V_ave, and V_min are the maximum value, the average value, and the minimum value of the voltage during the rest period after discharge of each battery cell in the battery system, respectively.

In Example 1, the time derivative of the voltage, that is, at least two of dVt_max / dt, dVt_ave / dt, and dVt_min / dt, is calculated to evaluate the distribution of SOH in the battery cells embedded in the system. It will be described to utilize the voltage mismatch in the later pause period. The combination of dVt_max / dt and dVt_min / dt may be the best, but either combination is possible.

The following detailed description has been made for a comprehensive understanding of the methods, devices, and / or systems described herein. However, various modifications and changes in the system, equipment, or method will be apparent to those skilled in the art. Also, the operating steps and / or calculation process are not limited to those set here and can be modified as known in the art. The examples described herein are provided to ensure thorough and complete disclosure.

The description here is based on the assumption that the secondary battery is a lithium ion battery. However, the definition of a secondary battery broadly includes batteries that can be charged and discharged. That is, the secondary battery may be, for example, a lead battery, a nickel cadmium battery, or an electric double layer capacitor.

Further, in this embodiment, SOH is used as an index indicating the degree of deterioration (deterioration state) of the battery. This is the degree of deterioration of the capacity compared to the capacity of the initial battery (capacity retention rate) or the degree of deterioration of the internal resistance compared to the initial capacity (rate of increase in resistance), and is a commonly used index. is there. In the following description, SOH is used as the capacity retention rate. However, such an index is an example, and an index other than SOH indicating the degree of deterioration of the battery may be used. Both the SOH of the entire battery system and the SOH of the individual battery cells constituting the system can be evaluated, and as described above, the SOH of the entire system is affected by the SOH of the individual battery cells constituting the system. receive.

FIG. 2 is an explanatory diagram of the configuration of the battery system according to the first embodiment of the present invention.

In FIG. 2, a battery system 200 including a plurality of modules 201, BMU202, PCS203 and a PC (Personal Computer) 204, each containing a plurality of submodules, is used as an example of an implementation of the method.

The battery system includes a PCS (Power conditioning system) 203, a BMU (Battery management unit) 202, and a plurality of modules 201 connected in series and in parallel. The module 201 includes a plurality of submodules 205 connected in series. The submodule 205 includes a plurality of battery cells 206 connected in parallel. In submodule 205, sensing data of battery cell voltage and temperature can be obtained. The module has an active cell balance controller 207 for controlling the distribution of charge during charging and discharging.

As described above, the sub-module 205 actually includes a plurality of battery cells 206 connected in parallel, but these can be collectively regarded as one battery cell. In the following description, the voltage and temperature of the submodule 205 are treated as the voltage and temperature of the battery cell.

Module 201 is connected to BMU 202 in series and in parallel. The read values of the voltage and temperature of the battery cell are expressed as the voltage and temperature of the sub-module 205, and are sent from each module 201 to the BMU 202. The BMU 202 is equipped with a control circuit 208 for controlling the voltage balance between the modules 201. The system DC voltage V_sys, system DC current I_sys, submodule maximum voltage V_max, submodule minimum voltage V_min, submodule maximum temperature T_max, and submodule minimum temperature T_min are sent from the BMU 202 to the PCS 203. Then, the above data is periodically sent from PCS203 to PC204.

FIG. 3 is a functional block diagram of BMU202, PCS203 and PC204 used in the first embodiment of the present invention.

Information on V_max, V_min, T_max and T_min of the sub-module 205 is sent from the BMU 202 to the sampling processing unit 301 of the PCS 203. The DC voltage V_sys and DC current I_sys of the battery system are also sent to the sampling processing unit 301. V_max, V_min, T_max, and T_min are periodically sent from the signal conversion transmitter 302 of the PCS203 to the PC204 together with the DC voltage V_sys and the DC current I_sys of the battery system. Although the PC 204 is installed outside the PCS 203 in the present invention, the PC 204 may actually be installed inside the PCS 203.

FIG. 4 is a functional block diagram of the PC 204 according to the first embodiment of the present invention.

The PC 204 includes an input / output (I / O) 305, a charge / discharge control unit 306, a memory 307, a SOH calculation processing unit 308, a system self-acceleration test (SSAT) processing unit 309, and a GUI (Graphical User Interface) 310.

The charge / discharge control unit 306, the SOH calculation processing unit 308, and the system self-acceleration test processing unit 309 may be realized by a dedicated processor, respectively, or a general-purpose processor may execute a program stored in the memory 307. It may be realized. The GUI is a display device that displays, for example, characters and drawings.

Data at a predetermined time (for example, 1 second) interval from the signal conversion transmission device 302 of the PCS 203 is received by the I / O 305 of the PC 204 and stored in the memory 307. The charge / discharge control unit 306 gives discharge, pause, and charge control commands to the PCS 203 through the I / O 305. Information on control commands is also stored in memory 307.

The SOH calculation processing unit 308 determines whether the control command is paused after discharge (step 401). When the control command is pause after discharge, the processing of the SOH calculation processing unit 308 is started (step 402). The SOH calculation processing unit 308 uses the data from the memory 307 to calculate the voltage differentiation, calculate and plot the SOH distribution (step 403), and evaluate the SOH of the system based on them (step 404). .. The calculation result is written back to the memory 307. This completes the process (step 405).

<Evaluation of SOH using voltage differentiation>
FIG. 5 is an explanatory diagram of an example of detailed calculation of dVt / dt by the SOH calculation processing unit 308 of the first embodiment of the present invention.

The control state information is sent to the memory 307 and stored. When the control state is pause after discharge, that triggers the start of the SOH calculation processing unit 308. The conditions required for discharge in "pause after discharge" are discharge until a specific average SOC (SOC: charge rate) value is reached, discharge until a specific voltage value is reached, or until a specific discharge period is reached. Various settings are possible, such as the discharge of.

The rest period can be characterized by the conditions under which no current flows or a constant current flows. When the pause period begins, the timestamp is set to t = 0 seconds.

At the elapsed time t1, V_max (t1) and V_min (t1) are set to Vt_max and Vt_min. Here, the time stamp t1 may have any predetermined value. Vt_ave (t1) is calculated by dividing V_sys (t1) by the number of battery cells connected in series (depending on the system configuration).

Note that dVt / dt may be a strict time derivative of Vt, but may be the slope of the voltage between any two times. In this embodiment, the latter will be described as dVt / dt. For example, in order to calculate dVt / dt, it may be necessary to define dt as delta_t. For example, if delta_t is set, the voltage data read at t1 + delta_t / 2 and t1-delta_t / 2 will be required. dVt_max / dt, dVt_ave / dt, and dVt_min / dt can be calculated by the following equations (1) to (3).

FIG. 7 is an explanatory diagram of the relationship between SOH and dVt / dt, Vt and R in Example 1 of the present invention.

FIG. 7A shows the relationship between SOH and dVt / dt. The horizontal axis of FIG. 7A is SOH, and the vertical axis is 1 / V', that is, the reciprocal of dVt / dt. FIG. 7A shows that there is a relationship that dVt / dt increases as the SOH decreases (that is, as the battery deteriorates), and that the relationship becomes more pronounced as the SOC decreases. ..

That is, using the correlation between SOH and dVt / dt shown in FIG. 7 (a), the distribution of SOH in the battery cell including SOH_max, SOH_ave, and SOH_min can be obtained from dVt_min / dt, dVt_ave / dt, and dVt_max / dt. Each can be predicted. The distribution of SOH can be approximated, for example, by assuming that SOH_min, SOH_ave, and SOH_max follow a normal distribution, a lognormal distribution, or any other distribution function. For cells that are generally in the initial state, at least two of SOH_max, SOH_ave, and SOH_min are needed to plot the distribution, assuming the distribution follows a normal distribution function. Therefore, in the present invention, at least two of dVt_max / dt, dVt_ave / dt, and dVt_min / dt are required to evaluate the distribution of SOH.

As shown in FIG. 7A, the smaller the SOC, the more remarkable the increase in dVt / dt with respect to the decrease in SOH. From this, the system may estimate SOH based on dVt / dt when SOC is less than a predetermined value. This ensures the accuracy of the estimation.

FIG. 18 is an explanatory diagram of the GUI displayed in the first embodiment of the present invention.

The SOH prediction result of the system is displayed on the GUI shown in FIG. 18A. This is the statistical conditions from the calculation of the voltage derivative, the distribution of SOH, the current SOH evaluation, the future SOH evaluation curve, and the remaining charge / discharge cycles (ie, how many more charges / discharges are possible). Display at least one of the predictions.

Further, by acquiring the data of the temperature distribution inside the battery system, it is possible to detect which cell has the lowest SOH. This can be done by the log data of the temperature sensor 210 embedded in the submodule 205 or by monitoring the infrared image of the battery pack. The result is displayed on the GUI shown in FIG. 18 (b). This shows the maximum SOH, average SOH, minimum SOH of cells, coloring map of cell settings, list of cells with low SOH, their locations, and the recommended situation (maintenance or replacement) for them.

In the first embodiment, the time derivative of the maximum voltage, the minimum voltage, and the average voltage of the submodule is calculated, and the distribution of SOH is estimated based on the result. However, this is just an example, and the SOH distribution can be similarly estimated using at least two voltages with different positions in the voltage distribution of the plurality of submodules. For example, it may be a combination of a maximum voltage and a minimum voltage, a combination of a maximum voltage and an average voltage, or a combination of a minimum voltage and an average voltage. Alternatively, for example, it may be a combination of a voltage of + 1σ and a voltage of -1σ of the distribution. In either case, the distribution of SOH can be estimated by fitting the normal distribution.

Next, Example 2 of the present invention will be described. Except for the differences described below, each part of the battery system of Example 2 has the same function as each part of the same reference numeral of Example 1 shown in FIGS. 1 to 5, 7 and 18. Therefore, their description will be omitted.

In Example 2, the voltage mismatch during the rest period after discharge is used to read the voltage (at least two of Vt_max, Vt_ave, and Vt_min) and the internal resistance value (Rt_max, Rt_ave) at a given elapsed time t. , And at least two of Rt_min) are calculated to evaluate the distribution of SOH in the battery embedded in the system. Calculation using these two parameters can consider two deterioration factors, which is considered to improve accuracy.

FIG. 8 is a functional block diagram of the SOH calculation processing unit 308 according to the second embodiment of the present invention.

The processing executed by the SOH calculation processing unit 308 of the second embodiment is the same as the processing of the SOH calculation processing unit 308 of the first embodiment, except that steps 403 and 404 are replaced with steps 801 and 802, respectively. The SOH calculation processing unit 308 calculates and plots the SOH using the voltage Vt at the predetermined elapsed time t2 and the resistance Rt at the predetermined elapsed time t2 (step 801), and uses the result to calculate the SOH of the system. Is evaluated (step 802).

<Evaluation of SOH using voltage reading and resistance>
Here, it will be described that the voltage discrepancy in the rest period after discharge is used for the prediction of SOH using the voltage Vt at the predetermined elapsed time t2 and the resistance Rt at the predetermined elapsed time t2.

FIG. 6 is an explanatory diagram of calculation of Vt and Rt after a lapse of a predetermined time by the SOH calculation processing unit 308 of the second embodiment of the present invention.

Similar to the dV / dt method, Vt_max (t2) and Vt_min (t2) are set as Vt_max and Vt_min, respectively, at the elapsed time t2 of the rest period after discharge. Vt_ave is calculated from V_sys (t2) and depends on the battery configuration. From Vt_max, Vt_ave, and Vt_min, SOH_min1, SOH_ave1, and SOH_max1 are evaluated using the relationship between SOH and Vt during the post-discharge pause period shown in FIG. 7 (b).

Further, the internal resistance value Rt at the elapsed time t2 is calculated as follows. At the time stamp t = 0, the voltages Vt_max (0), Vt_ave (0), and Vt_min (0) are recorded. The average current of the system is also recorded as It (0). At the elapsed time t = t2, Vt_max (t2), Vt_ave (t2), Vt_min (t2) and It (t2) are recorded. Then, Rt_max, Rt_ave, and Rt_min are calculated by the following equations (4) to (6).

From Rt_max, Rt_ave, and Rt_min, SOH_min2, SOH_ave2, and SOH_max2 are evaluated using the relationship between SOH and Rt shown in FIG. 7 (c).

From the evaluation of SOH using Vt and Rt, the SOH of the entire system is predicted by, for example, averaging the values of SOH.

The SOH distribution of the system is evaluated using SOH_min, SOH_ave, and SOH_max. The distribution of SOH is used as a parameter to evaluate the SOH of the entire system. The calculation result is displayed in the GUI shown in FIG. 18 as in the first embodiment.

Next, Example 3 of the present invention will be described. Except for the differences described below, each part of the battery system of Example 3 is the same as the same coded parts of Example 1 and Example 2 shown in FIGS. 1-8 and 18. Since they have functions, their description will be omitted.

In Example 3, an accelerated test is required to obtain data on the relationship between SOH and dVt / dt and Vt and Rt.

In this example, at least one of a pre-accelerated test or a system self-accelerated test (SSAT) is required.

Pre-accelerated testing is a well-known way to assess the SOH or life cycle of a battery, which exposes the battery to stresses (temperature, voltage, pressure, etc.) that exceed normal operating conditions in a short period of time to reveal defects or failures. This is a test.

FIG. 9 is an explanatory diagram of a pre-accelerated test according to Example 3 of the present invention.

As shown in FIG. 9, at least two battery acceleration cycle tests, each under different stress levels, are required. In this example, temperature is used as an acceleration factor. An acceleration cycle test is performed in which the charge / discharge cycle is repeated under temperatures T1 and T2, and dVt / dt, Vt and Rt are observed throughout the cycle. SOH is also measured throughout the cycle. From the result, the activation energy Ea for each parameter (SOH, dVt / dt, Vt and Rt) is calculated.

Here, as an example, the acceleration factor (AF) is used to quantify the rate of performance degradation between the test under T1 and the test under T2.

The temperature activation energy Ea is evaluated using the Arrhenius equation (Equation (10)).

Where k is the Boltzmann constant.

This type of approximation is commonly used to describe the mechanism of temperature acceleration failure.

Here, by transforming the mathematical formula using Es as a constant, the AF of the operating temperature with respect to T1 or T2 can be evaluated.

Next, the system self-accelerated test (SSAT) will be described. Unlike the pre-accelerated test, SSAT uses the temperature difference in the system and the voltage difference during the rest period after discharge as parameters.

FIG. 10 is an explanatory diagram of the system self-accelerated test (SSAT) according to the third embodiment of the present invention.

During the operation of the battery system, the maximum cell temperature T_max and the minimum cell temperature T_min are observed and stored in memory.

In a battery system where the SOH of the initial cells is uniform, it is assumed that the cells of SOH_min deteriorate under T_max and the cells of SOH_max deteriorate under T_min. Since SOH correlates with dVt / dt, Vt and Rt during the rest period after discharge, observe (1) dVt / dt or (2) Vt and Rt throughout the cycle and test them for acceleration in the system. Can be regarded as. This idea is shown in FIG. An example of dVt / dt will be described. When two different levels of dVt / dt (dVt / dt (1) and dVt / dt (2)) intersect the data points of dVt_max / dt and dVt_min / dt, the AF calculation of equation (11) is started. be able to.

Here, _Δ Nmin is the number of cycles of dVt_min / dt from the point where dVt / dt (2) intersects to the point where dVt / dt (1) intersects. Then, _Δ N_max is the number of cycles of dVt_max / dt from the intersection of dVt / dt (2) to the intersection of dVt / dt (1).

The activation energy Ea2 is calculated from the following equations (12) and (13).

The Ea data is used as a parameter to analyze the SOH state of the battery system.

Either of these two accelerated tests can predict future reductions in SOH. For systems with varying SOH, it is also possible to predict how the distribution function will change (stretch).

Furthermore, by acquiring the temperature distribution of the battery system, it is possible to detect which cell has the lowest SOH. This can be done, for example, by logging the data of the temperature sensor 210 embedded in the submodule 205, or by monitoring the infrared image of the battery pack. For example, a battery cell having a high temperature may be estimated as a cell having a low SOH based on the measurement data of the temperature sensor 210 or an infrared image.

The calculation result is displayed in the GUI shown in FIG. 18 as in Examples 1 and 2. In the example of FIG. 18 (a), the future decrease in SOH predicted by the accelerated test is displayed as a dotted line portion of the SOH curve with respect to the number of cycles. In addition, the number of remaining cycles until the SOH of the system drops to 60%, which is estimated from this curve, is displayed. In the example of FIG. 18B, a battery cell having a high temperature (that is, a cell presumed to have a low SOH) is displayed as a region surrounded by a dotted line.

Next, Example 4 of the present invention will be described. Except for the differences described below, each part of the battery system of Example 4 is the same as each part of the same reference numerals of Examples 1 to 3 shown in FIGS. 1 to 10 and 18. Since they have functions, their description will be omitted.

In Example 4, the SOH calibration algorithm for verifying the prediction of SOH by the method of Example 1 or Example 2 when the decrease of SOH exceeds any of the limits will be described.

FIG. 11 is a functional block diagram of the SOH calculation processing unit 308 according to the fourth embodiment of the present invention.

The processing executed by the SOH calculation processing unit 308 of the fourth embodiment is the same as the processing of the SOH calculation processing unit 308 of the first embodiment except that steps 403 and 404 are replaced by steps 1101 to 1103. Of these, steps 1101 and 1103 correspond to steps 403 and 404 of Example 1, respectively, but in Example 4, a SOH calibration process (step 1102 is added, which is executed by the SOH calculation processing unit 308). It may be executed by the SOH calibration unit provided inside or outside the SOH calculation processing unit 308. Hereinafter, the SOH calibration unit in the SOH calculation processing unit 308 will be described as executing step 1102. ..

FIG. 12 is a flowchart showing the processing of the SOH calibration unit in the SOH calculation processing unit 308 of the fourth embodiment of the present invention.

When the SOH calculation processing unit 308 calculates the distribution of SOH and SOH_ave (steps 1202 and 1201 respectively), the calculation result is sent to the SOH calibration unit. If there is an abnormality or contradiction detected while evaluating the distribution of SOH and SOH_ave, the SOH calibration unit solves and corrects the problem. In this example, the SOH_ave calculated this time (eg, SOH_ave (n)) is more than 2% higher than the previously calculated SOH_ave (eg, SOH_ave (n-1)) (step 1203: Yes). Alternatively, a judgment condition is given so that when the SOH of the distribution is larger than the expected threshold value and SOH_ave'is 2% or more larger than the previously calculated SOH_ave (step 1204: Yes), it is judged as abnormal. ..

Note that 2% here is an example of the SOH standard, and other appropriate values may be used. The calculation method of SOH_ave'is shown in FIG. 13 (b). The large deviation of SOH_ave'from the previously calculated SOH_ave means that the shape of the estimated SOH distribution deviates significantly from the normal distribution, that is, the correlation between the set dVt / dt and SOH. Indicates that may no longer be appropriate.

If the above conditions are checked and the result is true (ie, at least one of steps 1203 or 1204 is determined to be Yes), then the SOH calibrator uses a calibration algorithm to accommodate that SOH. Calculate the capacity value (current capacity) (step 1205). The SOH calibrator also evaluates the capacitance (current capacitance') using the measurable physical variables voltage and current (step 1206). The SOH calibrator compares these two capacitances and, if there is a difference, calculates the percentage of the difference (the value of "Y" in FIG. 12) (step 1207).

Then, the SOH calibration unit determines whether the difference Y is larger than a specific predetermined threshold value δ (step 1208), and if it is large (step 1208: Yes), the slope of the SOH curve for the specific SOC. Is adjusted based on the SOH estimated from the value of the current capacity (step 1209), and the result is stored in the memory 307.

In the above example, the difference Y between the current capacity and the current capacity'is used as an index showing the magnitude of the dissociation between the two. For example, the ratio between the current capacity and the current capacity'. Other values, such as, may be used as an index indicating the magnitude of the dissociation between the two. If the divergence between the two is large, the correlation between the set dVt / dt and SOH may not be appropriate, and calibration is performed.

FIG. 13 is an explanatory diagram of correction of the slope of the SOH curve using the current capacity'in Example 4 of the present invention.

FIG. 13 (a) illustrates how the slope is changed under the condition of SOH_ave (n-1) -SOH_ave (n)> 2% (ie, step 1203: Yes). When the above conditions are satisfied, SOH_ave (n) calculated using the straight line of y = mx + a is sent to the SOH calibration unit, and the current capacitance is calculated. If it is compared to the current capacity'and the condition (| Y | <= δ) is met (step 1208: Yes), the SOH calculated from the current capacity'(which is dVt_ave / dt (n)). Is assumed to correspond to), but is used as a parameter to change the slope from m to m'. Therefore, the new formula for this straight line is y = m'x + a.

FIG. 13 (b) shows the case where the second condition, that is, {| Distribution |> Δ} && {SOH_ave'-dV_ave / dt (n-1)> 2%} is satisfied (step 1204: Yes). ), The same change of inclination will be described.

<Calculation of current capacity>
The SOH transmitted from the SOH prediction algorithm of Example 1 or 2 must be converted to the corresponding capacitance for calibration (Equation (14)). The rated capacity (specific capacity) of the battery pack is used herein as given in this formula for the calculation of "current capacity". Here, the rated capacity is the specified capacity of the used battery pack determined before assembling the battery, and SOH is the SOH value obtained from the SOH prediction algorithm.

Current capacity = rated capacity x SOH% ・ ・ ・ (14)

<Evaluation of current capacity>
Capacity assessment must be made in relation to the form of changes in battery SOC.

FIG. 14 is an explanatory diagram showing an example of different SOC patterns of a battery pack that supports different types of loads in the fourth embodiment of the present invention.

Here we show three different battery SOC profiles for three different types of loads. Section A (the part surrounded by the dotted line with the notation "A") shows an example of a load for which a rest period during the charge / discharge cycle is valid. That is, section A shows the time change of SOC when a pause period is set from the end of discharge to the start of charging.

Section B (the part surrounded by the dotted line with the notation "B") shows an example of a load with no pause. In this case, the load cycle is continuously switched between charging and discharging (ie, without a pause), but charging and discharging is repeated in the range of SOC% of 20 or more and 75 or less.

Section C (the part surrounded by the dotted line with the notation of "C") shows an example of a load having no rest period as in Section B. However, in section C, unlike section B, charging / discharging is repeated in various ranges in which the SOC% is 20 or more and 75 or less.

FIG. 15 is an explanatory diagram of the calculation of the capacitance based on the open circuit voltage characteristic in the fourth embodiment of the present invention.

If a pause during the cycle is in effect as shown in Section A of FIG. 14, the pause is for the algorithm to measure the OCV (open circuit voltage) and evaluate each SOC as shown in FIG. Used. The current capacity is calculated by the following equation (15). Here, the current capacity_A'is the capacity of the battery at the charging start point (SP) shown in FIG. 14, and the rated capacity is the capacity according to the specifications of the battery as described in the data sheet. is there. SOC_A'is extracted from the SOC vs. OCV curve shown in FIG.

Current capacity_A'= Rated capacity x SOC_A'% ・ ・ ・ (15)

If there is no pause as shown in Section B of FIG. 14, the SOC calibrator will continue to monitor the SOC value. When the SOC reaches a predetermined minimum point X% (X is less than 20%), the SOC calibration unit measures the battery terminal voltage, that is, the closed circuit voltage CCV.

FIG. 16 is an explanatory diagram of CCV vs. SOC characteristics for different C rates in Example 4 of the present invention.

The corresponding SOC_B'for the evaluation of the current capacity_B'is derived from the CCV vs. SOC relationship shown in FIG. This is the correct method only if the data to be compared are all at the same C rate. CCV vs. SOC characteristics for a few different C rates are obtained from accelerated aging data and stored in memory 307. For unstored C rates, the interpolated data is used if it is between two recorded characteristics. The current capacity_B'is evaluated using the following equation (16). The rated capacity is the specified capacity of the battery as described in the data sheet.

Current capacity_B'= Rated capacity x SOC_B'% ・ ・ ・ (16)

The current capacity calculation is more accurate when the SOC variation is between 20% and 75% (the flat middle region of the lithium-ion battery voltage curve), as shown in Section C of FIG. Must be done. In such a case, a more accurate method is used instead of the above capacity calculation method.

FIG. 17 is an explanatory diagram of the voltage vs. SOC / capacitance characteristics of the new battery and the old battery in the fourth embodiment of the present invention.

Here, as shown in FIG. 17, the battery pack is charged with the minimum allowable C rate in order to reduce the influence of the internal resistance on the voltage characteristics. The voltage characteristics obtained for SOC in voltage are compared to similar characteristics (or characteristics obtained from previous calibration) obtained when the battery was new.

Ideally, the voltage value V1 (used battery) will be greater than V2 (new battery). Therefore, when this relationship is used for CCV, it is possible to accurately indicate the difference in SOC and the difference in capacity value between a new and used battery pack when the created characteristics are due to the same C rate.

As shown in FIG. 17, for any CCV indicated by V, the SOC_C'' and SOC_C'of new and used battery packs can be derived from the CCV vs. SOC relationship of the respective profiles. The following equations (17) and (18) can be used to evaluate the SOC of both new and used batteries in CCV and calculate their respective capacities for that SOC. Here, the current capacity_C'' indicates the current capacity of the used battery. Current capacity_C'indicates the current capacity when the battery was new.

Current capacity _C'' = Rated capacity x SOC_C''% ・ ・ ・ (17)
Current capacity_C'= Rated capacity x SOC_C'% ・ ・ ・ (18)

From the current capacity _C'and the current capacity _C'', the capacity reduction rate for the current capacity _C'(new battery) can be calculated using the following equation (19).

Capacity reduction rate = (current capacity_C''-current capacity_C') / current capacity_C'x 100 (19)

From the capacity reduction rate, the current capacity_C'when the battery is charged to 100% SOC is calculated by the equation (20).

Current capacity_C'= Capacity reduction rate x Rated capacity ... (20)

In such cases, only the lowest acceptable C-rate CCV vs. SOC characteristics during charging should be recorded.

<Calibration / correction of capacity>
As shown in FIG. 13, the estimated current capacity'value is compared to the current capacity obtained from the prediction algorithm.

Y = (current capacity-current capacity') ... (21)

Here, it is assumed that the absolute value of the integer "Y" is δ or less.

If there is a difference between the two, as shown in FIG. 13, the slope of the SOH with respect to the specification SOC for the 1 / V'curve is corrected based on the SOH estimated using the current capacitance'. The curve. This modified SOH curve is used as a reference for the evaluation of SOH in future predictions according to Examples 1, 2 and 3.

A typical example of the embodiment of the present invention described above can be summarized as follows. That is, it is a storage battery state evaluation system that evaluates the state of a storage battery system composed of a plurality of storage battery cells (for example, battery cell 206 or submodule 205), and is a voltage of a plurality of storage battery cells among the voltages of the plurality of storage battery cells. A memory that holds the voltage of at least two battery cells with different positions in the distribution (for example, memory 307) and a gradient of the voltage with respect to time in the rest period after discharge of at least two battery cells (for example, dVt_max / dt, dVt_min / dt). And a deterioration state calculation unit (for example, SOH calculation processing unit 308) for calculating (at least two of dVt_ave / dt).

Here, the deterioration state calculation unit may calculate the deterioration state (for example, SOH) of at least two storage battery cells based on the slope of the voltage of at least two storage battery cells with respect to time.

Further, the deterioration state calculation unit determines the deterioration state of the plurality of storage battery cells based on the deterioration state of at least two storage battery cells and the positions of the voltages of at least two storage battery cells in the voltage distribution of the plurality of storage battery cells. The distribution (eg, the distribution of SOH) may be calculated.

This makes it possible to estimate the distribution of SOH, which could not be observed by a system equipped with a conventional balance controller, and it is possible to estimate the state of the storage battery with high accuracy.

In addition, the deterioration state calculation unit may predict future changes in the distribution of deterioration states of a plurality of storage battery cells by performing an acceleration test of the storage battery cells (see, for example, Example 3).

This makes it possible to accurately predict, for example, the number of remaining charge / discharge cycles of the storage battery system.

Further, at this time, the deterioration state calculation unit calculates the acceleration coefficient based on the slope of the voltage of the two storage battery cells having different temperatures in the rest period after the discharge of the plurality of charge / discharge cycles with respect to time (for example, Example). 3 System self-acceleration test), future changes in the distribution of the deterioration state of a plurality of storage battery cells may be predicted based on the acceleration coefficient.

This makes it possible to accurately predict, for example, the number of remaining charge / discharge cycles of the storage battery system without performing an accelerated test in advance.

Further, the memory shows correlation information (for example, FIG. 7A) showing the correlation between the charge rate of the storage battery cell, the inclination of the voltage with respect to the time in the rest period after the discharge of the storage battery cell, and the deterioration state of the storage battery cell. (Relationship between SOH and 1 / V'for each value of SOC) is maintained, and the deterioration state calculation unit determines the slope of the voltage with respect to the time of the rest period after discharge of at least two storage battery cells and the inclination of at least two storage battery cells with respect to time. The deterioration state of at least two storage battery cells may be calculated based on the charge rate in the rest period after discharge and the correlation information.

This makes it possible to accurately estimate the state of the storage battery.

Further, the deterioration state calculation unit calculates the capacity retention rate (for example, SOH) as the deterioration state of the storage battery cell, and the difference between the calculated deterioration state of the plurality of storage battery cells and the deterioration state of the plurality of storage battery cells calculated last time. Is larger than a predetermined reference (for example, step 1203 in FIG. 12: Yes), or when the deviation from the predetermined condition of the calculated deterioration state distribution of the plurality of storage battery cells is larger than the predetermined reference (for example, step 1204). : Yes), the first capacity of the plurality of storage battery cells (for example, the current capacity of step 1205) is calculated from the deterioration state calculated based on the inclination of the voltage of at least two storage battery cells with respect to time, and the plurality of storage batteries The second capacity of the plurality of storage battery cells (for example, the current capacity in step 1206) is calculated based on the voltage and current of the cells, and the deviation between the first capacity and the second capacity is larger than a predetermined reference. In some cases (eg, step 1208: Yes), the correlation information may be updated to match the second capacitance (eg, step 1209, FIG. 13).

As a result, when the correlation between the retained dVt / dt and SOH does not match the actual condition, calibration can be performed to maintain the accuracy of estimating the state of the storage battery.

Here, when the deterioration state calculation unit applies a charge / discharge cycle including the rest period after discharge to the plurality of storage battery cells (for example, when it corresponds to section A of FIG. 14), the deterioration state calculation unit of the plurality of storage battery cells. A second capacity may be calculated based on the charge rate corresponding to the open circuit voltage and the predetermined capacity (eg, the method shown in FIG. 15).

As a result, calibration can be performed with high accuracy.

Further, the deterioration state calculation unit calculates the slope of the voltage of at least two storage battery cells in the rest period after discharge when the charge rate (for example, SOC) of at least two storage battery cells is lower than a predetermined value. May be good.

As shown in FIG. 7A, the smaller the SOC, the more the difference in SOH appears as the difference in dVt / dt. Therefore, it is possible to accurately estimate the state of the storage battery by using the voltage value when the SOC is small.

Further, the voltage of at least two storage battery cells having different positions in the voltage distribution of the plurality of storage battery cells may be at least two of the maximum value, the minimum value, and the average value among the voltages of the plurality of storage battery cells.

Many general BMUs output the maximum and minimum values of the cell voltage. Moreover, the average value of the cell voltage can be calculated from the system voltage and the number of cells in the system. Therefore, this makes it possible to provide a storage battery state evaluation system that is generally easy to use.

Further, as another example of the present invention, the following system can be considered. That is, it is a storage battery state evaluation system that evaluates the state of a storage battery system composed of a plurality of storage battery cells, and among the voltages of the plurality of storage battery cells, at least two storage battery cells having different positions in the voltage distribution of the plurality of storage battery cells. The internal resistance of at least two battery cells based on the voltage, the memory holding the current of the entire battery system, the voltage during the rest period after discharge of at least two battery cells, and the current of the entire battery system. A deterioration state calculation unit that calculates the deterioration state of at least two storage battery cells based on the voltage during the rest period after discharge of at least two storage battery cells and the internal resistance of at least two storage battery cells. Has.

This corresponds to, for example, the system described in Example 2. This makes it possible to accurately estimate the state of the storage battery.

Further, as yet another example of the present invention, the following system can be considered. That is, it is a storage battery state evaluation system having a plurality of storage battery cells, a storage battery management unit (for example, BMU202) connected to the plurality of storage battery cells, and a computer (for example, PC204) connected to the storage battery management unit. The management unit outputs the voltages of at least two storage battery cells having different positions in the voltage distribution of the plurality of storage battery cells among the voltages of the plurality of storage battery cells, and the computer outputs the rest period after the discharge of at least two storage battery cells. Calculate the gradient of the voltage in time with respect to time.

This makes it possible to accurately estimate the state of the storage battery.

Here, the computer instructs the storage battery management unit to discharge the plurality of storage battery cells and then instructs the storage battery cells to suspend the plurality of storage battery cells, and the voltage time in the pause period after the discharge of at least two storage battery cells is triggered. The slope with respect to may be calculated.

For example, the charge / discharge control unit 306 of the PC 204 may give the above instruction, and the SOH calculation processing unit 308 may execute the process as a trigger. As a result, the PC 204 can start processing at an appropriate timing based on the signal generated by the PC 204, so that the state of the storage battery can be estimated accurately.

The present invention is not limited to the above-mentioned examples, and includes various modifications. For example, the above-described embodiment has been described in detail for a better understanding of the present invention, and is not necessarily limited to the one including all the configurations of the description. Further, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is possible to add the configuration of another embodiment to the configuration of one embodiment. Further, it is possible to add / delete / replace a part of the configuration of each embodiment with another configuration.

Further, each of the above configurations, functions, processing units, processing means and the like may be realized by hardware by designing a part or all of them by, for example, an integrated circuit. Further, each of the above configurations, functions, and the like may be realized by software by the processor interpreting and executing a program that realizes each function. Information such as programs, tables, and files that realize each function can be stored in non-volatile semiconductor memories, hard disk drives, storage devices such as SSDs (Solid State Drives), or computer-readable non-computers such as IC cards, SD cards, and DVDs. It can be stored in a temporary data storage medium.

In addition, the control lines and information lines are shown as necessary for explanation, and not all control lines and information lines are shown in the product. In practice, it can be considered that almost all configurations are interconnected.

201 Module 202 Battery management unit (BMU)
203 Power conditioning system (PCS)
204 PC
205 Submodule 206 Storage battery cell 207 Active cell balance controller 208 Control circuit 210 Temperature sensor

Claims (13)

It is a storage battery status evaluation system that evaluates the status of a storage battery system consisting of a plurality of storage battery cells.
A memory that holds the voltages of at least two storage battery cells having different positions in the voltage distribution of the plurality of storage battery cells among the voltages of the plurality of storage battery cells.
A storage battery state evaluation system comprising: a deterioration state calculation unit for calculating a slope of a voltage with respect to time in a rest period after discharge of at least two storage battery cells. The storage battery state evaluation system according to claim 1.
The deterioration state calculation unit is a storage battery state evaluation system, which calculates the deterioration state of at least two storage battery cells based on the inclination of the voltage of the at least two storage battery cells with respect to time. The storage battery state evaluation system according to claim 2.
The deterioration state calculation unit deteriorates the plurality of storage battery cells based on the deterioration state of the at least two storage battery cells and the positions of the voltages of the at least two storage battery cells in the voltage distribution of the plurality of storage battery cells. A storage battery state evaluation system characterized by calculating the state distribution. The storage battery state evaluation system according to claim 3.
The deterioration state calculation unit is a storage battery state evaluation system characterized in that a future change in the distribution of the deterioration state of the plurality of storage battery cells is predicted by performing an acceleration test of the storage battery cells. The storage battery state evaluation system according to claim 4.
The deterioration state calculation unit calculates an acceleration coefficient based on the inclination of the voltage of the two storage battery cells having different temperatures with respect to time in the rest period after the discharge of a plurality of charge / discharge cycles, and is based on the acceleration coefficient. A storage battery state evaluation system characterized by predicting future changes in the distribution of deterioration states of the plurality of storage battery cells. The storage battery state evaluation system according to claim 3.
The memory holds correlation information indicating the correlation between the charge rate of the storage battery cell, the slope of the voltage in the rest period after the discharge of the storage battery cell with respect to time, and the deterioration state of the storage battery cell.
The deterioration state calculation unit determines the inclination of the voltage with respect to the time in the rest period after discharging the at least two storage battery cells, the charge rate in the rest period after discharging the at least two storage battery cells, and the correlation information. A storage battery state evaluation system, which calculates the deterioration state of at least two storage battery cells based on the calculation. The storage battery state evaluation system according to claim 6.
The deterioration state calculation unit
The capacity retention rate is calculated as the deteriorated state of the storage battery cell, and
The difference between the calculated deterioration state of the plurality of storage battery cells and the previously calculated deterioration state of the plurality of storage battery cells is larger than a predetermined reference, or the calculated distribution of the deterioration state of the plurality of storage battery cells is predetermined. When the deviation from the condition of is larger than a predetermined reference, the first capacity of the plurality of storage battery cells is calculated from the deteriorated state calculated based on the inclination of the voltage of the at least two storage battery cells with respect to time.
The second capacity of the plurality of storage battery cells is calculated based on the voltage and current of the plurality of storage battery cells.
A storage battery state evaluation system characterized in that when the deviation between the first capacity and the second capacity is larger than a predetermined reference, the correlation information is updated so as to match the second capacity. The storage battery state evaluation system according to claim 6.
When the charge / discharge cycle including the rest period after the discharge is applied to the plurality of storage battery cells, the deterioration state calculation unit determines the charge rate corresponding to the open circuit voltage of the plurality of storage battery cells and a predetermined value. A storage battery state evaluation system characterized in that the second capacity is calculated based on the capacity. The storage battery state evaluation system according to claim 1.
The deterioration state calculation unit is characterized in that when the charge rate of at least two storage battery cells is lower than a predetermined value, the slope of the voltage with respect to time in the rest period after discharge of the at least two storage battery cells is calculated. Battery condition evaluation system. The storage battery state evaluation system according to claim 1.
The voltage of at least two storage battery cells having different positions in the voltage distribution of the plurality of storage battery cells is characterized by being at least two of the maximum value, the minimum value, and the average value among the voltages of the plurality of storage battery cells. Battery condition evaluation system. It is a storage battery status evaluation system that evaluates the status of a storage battery system consisting of a plurality of storage battery cells.
A memory that holds the voltages of at least two storage battery cells having different positions in the voltage distribution of the plurality of storage battery cells and the current of the entire storage battery system among the voltages of the plurality of storage battery cells.
The internal resistance of the at least two storage battery cells is calculated based on the voltage in the rest period after the discharge of the at least two storage battery cells and the current of the entire storage battery system, and after the discharge of the at least two storage battery cells. The storage battery state evaluation is characterized by having a deterioration state calculation unit that calculates the deterioration state of the at least two storage battery cells based on the voltage during the rest period and the internal resistance of the at least two storage battery cells. system. A storage battery state evaluation system including a plurality of storage battery cells, a storage battery management unit connected to the plurality of storage battery cells, and a computer connected to the storage battery management unit.
The storage battery management unit outputs the voltages of at least two storage battery cells having different positions in the voltage distribution of the plurality of storage battery cells among the voltages of the plurality of storage battery cells.
The computer is a storage battery state evaluation system characterized by calculating the slope of voltage with respect to time in a rest period after discharge of at least two storage battery cells. The storage battery state evaluation system according to claim 12.
When the computer instructs the storage battery management unit to discharge the plurality of storage battery cells and then instructs the storage battery management unit to suspend the plurality of storage battery cells, the voltage in the pause period after the discharge of the at least two storage battery cells is triggered. A storage battery condition evaluation system characterized by calculating the inclination of the battery with respect to time.