Method for estimating the capacity retention rate of a secondary battery and program for estimating the capacity retention rate of a secondary battery

Abstract

In this secondary battery capacity retention ratio estimating method for estimating a capacity retention ratio (SOH) of a secondary battery using Weibull's law: a total capacity retention ratio of the secondary battery, obtained from at least one of secondary battery data during operation and a cycle test, is divided into a float component capacity retention ratio attributable to deterioration due to a usage period, and a cycle component capacity retention ratio attributable to deterioration due to a number of charges / discharges; Weibull coefficients mf and ηf corresponding to the float component capacity retention ratio, and the float component capacity retention ratio in formula (1) are obtained; Weibull coefficients mc and ηc corresponding to the cycle component capacity retention ratio, and the cycle component capacity retention ratio in formula (2) are obtained; and the capacity retention ratio in a period t or at a cycle number N is estimated using formula (A).

Description

[Technical Field]

[0001] The present invention relates to a method for estimating the capacity retention rate of a secondary battery, a program for estimating the capacity retention rate of a secondary battery, and a device for estimating the capacity retention rate of a secondary battery in a battery storage system comprising a single rechargeable secondary battery cell or a plurality of rechargeable secondary battery cells connected in series or parallel, and a power adjustment device connected to a commercial power source or power generation device and capable of supplying power to a connected load. [Background technology]

[0002] To reduce the use of commercial power, a battery storage system has been proposed that stores electricity generated using natural energy sources such as solar power in a battery, and then supplies the stored electricity to loads that require power, instead of using commercial power.

[0003] For example, energy storage systems like the one described above are often used with one to two charge-discharge cycles per day, and it is known that the capacity retention rate of secondary batteries gradually decreases due to cycle degradation and aging. The capacity of secondary batteries after prolonged use cannot be determined without actual measurement, but since this would require shutting down the energy storage system in use, it is becoming necessary to predict the capacity retention rate of secondary batteries in order to understand the current state of the secondary batteries while they are in operation. Furthermore, in order to meet the demand for reducing environmental impact, there are requests for extending the lifespan of energy storage systems, and it is becoming necessary to predict the future lifespan of secondary batteries.

[0004] Conventional methods include preparing a large number of complex charge state maps to correct for capacity retention rates, and there are known formulas for predicting capacity retention rates. Known formulas for predicting capacity retention rates include those using the square root law and the power law. It is known that the capacity degradation rate of a secondary battery can be determined by the square root law, which states that it is proportional to the amount of current (integrated current) flowing through the secondary battery raised to the power of 1 / 2, or to the square root of the time the secondary battery has been left unused. The formula is as follows, and by finding the square root of the amount of current flowing through the secondary battery, which is the amount of current flowing through the secondary battery, the degradation state (or capacity degradation rate) of that secondary battery can be estimated.

[0005]

number

[0006] Furthermore, a technique has been disclosed that allows for the estimation of the full charge capacity or remaining capacity (remaining capacity) of a secondary battery by determining the accumulated charge amount based on the time course of the charge and discharge current, without interrupting the power supply from the secondary battery or discharging the secondary battery to its discharge termination state (see, for example, Patent Document 1). The formula is as follows (power law).

[0007]

number

[0008] However, the square root rule has the problem of large discrepancies with actual measurements. On the other hand, the power law shows good fitting but similarly experiences discrepancies with reality. Furthermore, since both the square root rule and the power law can mathematically allow for capacity retention rates below 0%, there is a problem that predicted values ​​in long-term forecasts tend to be lower than the actual values. Therefore, the inventors proposed a novel method for estimating capacity retention rate using Weibull's law (see Non-Patent Document 1). This method treats a battery as an assembly of partial batteries and can estimate its lifespan by predicting its failure rate, and is expressed by the following formula.

[0009]

number

[0010] [Patent Document 1] Japanese Patent Publication No. 2009-52974 [Non-patent literature]

[0011] [Non-Patent Document 1] Abstracts of the 59th Battery Symposium, p. 212, published November 26, 2018. [Overview of the Initiative] [Problems that the invention aims to solve]

[0012] The above method for estimating capacity retention using Weibull's law shows good agreement with measured values ​​compared to the square root law and power law, but the error becomes larger for long-term predictions. Therefore, more accurate life prediction is needed for practical application.

[0013] In view of these circumstances, the present invention aims to provide a method for estimating the state of health (SOH) of a secondary battery, a program for estimating the state of health (SOH) of a secondary battery, and a device for estimating the state of health (SOH) of a secondary battery, which can be estimated more accurately over a longer period of time. [Means for solving the problem]

[0014] A first aspect of the present invention that solves the above problems is: In a method for estimating the capacity retention rate (SOH) of a secondary battery using Weibull's law, The total capacity retention rate of a secondary battery obtained from at least one of the data from a secondary battery in operation and a cycle test is separated into the float component capacity retention rate due to degradation over the period of use and the cycle component capacity retention rate due to degradation over the number of charge-discharge cycles. The Weibull coefficient m corresponding to the float component volume retention rate f η f And determine the float component volume retention rate using the following formula (1), Weibull coefficient m corresponding to the cycle component capacity retention rate c η c And calculate the cycle component volume retention rate using the following formula (2): The capacity retention rate over period t or cycle number N is estimated using the following formula (A). The present invention relates to a method for estimating the capacity retention rate of a secondary battery, characterized by the following features:

[0015]

number

[0016] A second aspect of the present invention is: The float component capacity retention rate is determined from the measured values ​​of the float test, and the total capacity retention rate is determined from the measured total capacity retention rate obtained from the secondary battery data during operation or from the total cycle test capacity retention rate obtained from the measured values ​​of the cycle test, and the float component capacity retention rate and the cycle component capacity retention rate are separated. The present invention relates to a method for estimating the capacity retention rate of a secondary battery according to a first embodiment, characterized by the following:

[0017] A third aspect of the present invention is: By plotting the float component volume retention rate in relation to ln(period) and ln(ln(1 / volume retention rate)), a Weibull plot of the float component volume retention rate is created. A linear float degradation prediction line is estimated from the Weibull plot of the float component volume retention rate. From the slope and intercept of the float deterioration prediction line, m f and η f Seeking, m f and η f And the float component volume retention rate is determined from the above formula (1), The cycle component capacity retention rate is obtained by dividing the total capacity retention rate by the float component capacity retention rate. By performing a Weibull plot of the cycle component capacity retention rate in relation to ln(cycle number) and ln(ln(1 / capacity retention rate)), a Weibull plot of the cycle component capacity retention rate is created, An approximate straight-line cycle degradation prediction line is estimated from the Weibull plot of the cycle component capacity retention rate, m is obtained from the slope and intercept of the cycle degradation prediction line, c and η, c and the cycle component capacity retention rate is obtained from the above m, c and η, c and the formula (2). This is the capacity retention rate estimation method for a secondary battery according to the second aspect. This is the capacity retention rate estimation method for a secondary battery according to the second aspect, characterized by the above.

[0018] A fourth aspect of the present invention is obtaining the float component capacity retention rate from the measured values of the cycle test, separating the float component capacity retention rate and the cycle component capacity retention rate by using the actually measured total capacity retention rate obtained from the secondary battery data during operation or the total cycle test capacity retention rate obtained from the measured values of the cycle test as the total capacity retention rate. This is the capacity retention rate estimation method for a secondary battery according to the first aspect, characterized by the above.

[0019] A fifth aspect of the present invention is by performing a Weibull plot of the total capacity retention rate in relation to ln(period) and ln(ln(1 / capacity retention rate)), a Weibull plot of the total capacity retention rate is created, a polynomial representing a curve is obtained by performing polynomial fitting on the Weibull plot of the total capacity retention rate, a tangent line at an initial predetermined period of the polynomial is obtained, m is obtained from the slope and intercept of the tangent line, f and η, f and the float component capacity retention rate is obtained from the above m, f and η, f and the cycle component capacity retention rate is obtained by dividing the total capacity retention rate by the float component capacity retention rate. This is the capacity retention rate estimation method for a secondary battery according to the fifth aspect, characterized by the above. By plotting the aforementioned cycle component capacity retention rate in relation to ln(number of cycles) and ln(ln(1 / capacity retention rate)), a Weibull plot of the cycle component capacity retention rate is created. A linear cycle degradation prediction line is estimated from the Weibull plot of the cycle component capacity retention rate, and the slope and intercept of the cycle degradation prediction line are used to determine m c and η c Seeking, m c and η c The cycle component volume retention rate can be determined from equation (2) above. The fourth embodiment of the method for estimating the capacity retention rate of a secondary battery is characterized by the following:

[0020] A sixth aspect of the present invention is: By plotting the total capacity retention rate in relation to ln(period) and ln(ln(1 / capacity retention rate)), a Weibull plot of the total capacity retention rate is created. The Weibull plot of the total capacity retention rate is fitted with a polynomial to obtain a polynomial that represents the curve. The slope of the polynomial is determined from the two points of the Weibull plot during the initial predetermined period. Find the tangent line to the polynomial with the aforementioned slope, and from the slope and intercept of the tangent line, m f and η f Seeking, m f and η f And the float component volume retention rate is determined from the above formula (1), The cycle component capacity retention rate is obtained by dividing the total capacity retention rate by the float component capacity retention rate. By plotting the aforementioned cycle component capacity retention rate in relation to ln(number of cycles) and ln(ln(1 / capacity retention rate)), a Weibull plot of the cycle component capacity retention rate is created. A linear cycle degradation prediction line is estimated from the Weibull plot of the cycle component capacity retention rate. From the slope and intercept of the cycle degradation prediction line, m c and η c Seeking, mc and η c The cycle component volume retention rate can be determined from equation (2) above. The fourth embodiment of the method for estimating the capacity retention rate of a secondary battery is characterized by the following:

[0021] A seventh aspect of the present invention is: The float component capacity retention rate is determined by the measured total capacity retention rate obtained from the secondary battery data during operation, and the total capacity retention rate is determined by the measured total capacity retention rate obtained from the secondary battery data during operation or the total cycle test capacity retention rate obtained from the measured values ​​of the cycle test, and the float component capacity retention rate and the cycle component capacity retention rate are separated. The present invention relates to a method for estimating the capacity retention rate of a secondary battery according to a first embodiment, characterized by the following:

[0022] An eighth aspect of the present invention is: By plotting the measured total capacity retention rate in relation to ln(period) and ln(ln(1 / capacity retention rate)), a Weibull plot of the measured total capacity retention rate is created. The Weibull plot of the measured total capacity retention rate is fitted with a polynomial to obtain a polynomial that represents the curve. Find the tangent line to the aforementioned polynomial during the initial predetermined period, From the slope and intercept of the tangent line, m f and η f Seeking, m f and η f And the float component volume retention rate is determined from the above formula (1), The cycle component capacity retention rate is obtained by dividing the total capacity retention rate by the float component capacity retention rate. The aforementioned cycle component capacity retention rate is plotted in a Weibull plot in relation to ln(number of cycles) and ln(ln(1 / capacity retention rate)) to create a Weibull plot of the cycle component capacity retention rate. A linear cycle degradation prediction line is estimated from the Weibull plot of the cycle component capacity retention rate. From the slope and intercept of the cycle degradation prediction line, m c and η cSeeking, m c and η c The cycle component volume retention rate can be determined from equation (2) above. The seventh embodiment of the method for estimating the capacity retention rate of a secondary battery is characterized by the following:

[0023] A ninth aspect of the present invention is: By plotting the measured total capacity retention rate in relation to ln(period) and ln(ln(1 / capacity retention rate)), a Weibull plot of the measured total capacity retention rate is created. The Weibull plot of the measured total capacity retention rate is fitted with a polynomial to obtain a polynomial that represents the curve. The slope of the polynomial is determined from the two points of the Weibull plot during the initial predetermined period. Find the tangent line to the polynomial with the aforementioned slope, From the slope and intercept of the tangent, m f and η f Seeking, m f and η f And the float component volume retention rate is determined from the above formula (1), The cycle component capacity retention rate is obtained by dividing the total capacity retention rate by the float component capacity retention rate. By plotting the aforementioned cycle component capacity retention rate in relation to ln(number of cycles) and ln(ln(1 / capacity retention rate)), a Weibull plot of the cycle component capacity retention rate is created. A linear cycle degradation prediction line is estimated from the Weibull plot of the cycle component capacity retention rate. From the slope and intercept of the cycle degradation prediction line, m c and η c Seeking, m c and η c The cycle component volume retention rate can be determined from equation (2) above. The seventh embodiment of the method for estimating the capacity retention rate of a secondary battery is characterized by the following:

[0024] A tenth aspect of the present invention is: In a secondary battery capacity retention rate (SOH) estimation program that estimates the capacity retention rate of secondary batteries using Weibull's law, A procedure for separating the total capacity retention rate of a secondary battery obtained from at least one of operational secondary battery data, cycle tests, and float tests into a float component capacity retention rate due to degradation over the period of use and a cycle component capacity retention rate due to degradation over the number of charge-discharge cycles, The Weibull coefficient m corresponding to the float component volume retention rate f η f And the procedure for determining the float component volume retention rate in the following formula (1), Weibull coefficient m corresponding to the cycle component capacity retention rate c η c And the procedure for determining the cycle component volume retention rate of the following equation (2), The computer is made to perform a procedure to estimate the capacity retention rate over a period of time t or a number of cycles N using the following formula (A). The present invention relates to a program for estimating the capacity retention rate of secondary batteries.

[0025]

number

[0026] An eleventh aspect of the present invention is: The procedure involves determining the float component capacity retention rate from the measured values ​​of the float test, and separating it into the float component capacity retention rate and the cycle component capacity retention rate by taking the measured total capacity retention rate obtained from the secondary battery data during operation or the total cycle test capacity retention rate obtained from the measured values ​​of the cycle test as the total capacity retention rate. Make the computer function and execute it. The present invention relates to a program for estimating the capacity retention rate of a secondary battery according to a tenth embodiment, characterized by the following:

[0027] A twelfth aspect of the present invention is: The procedure for creating a Weibull plot of the float component's volume retention rate is as follows: A procedure for estimating a linear float degradation prediction line from the Weibull plot of the float component volume retention rate, The slope and intercept of the float deterioration prediction line are used to determine the Weibull coefficient m. f and η f The procedure for finding and The Weibull coefficient m f and η f The procedure for determining the float component volume retention rate from the above formula (1), The procedure for determining the cycle component volume retention rate is to divide the total volume retention rate by the float component volume retention rate, The procedure for creating a Weibull plot of the cycle component capacity retention rate is to plot the cycle component capacity retention rate in relation to ln(number of cycles) and ln(ln(1 / capacity retention rate)), and A procedure for estimating a linear cycle degradation prediction line from the Weibull plot of the aforementioned cycle component capacity retention rate, From the slope and intercept of the cycle degradation prediction line, the Weibull coefficient m c and η c The procedure for finding and The Weibull coefficient m c and η c The computer is made to perform the procedure for determining the cycle component volume retention rate from equation (2) above. The present invention relates to a program for estimating the capacity retention rate of a secondary battery according to an eleventh embodiment, characterized by the following:

[0028] A thirteenth aspect of the present invention is: The computer is instructed to perform a procedure to separate the float component capacity retention rate from the cycle component capacity retention rate by determining the float component capacity retention rate from the measured values ​​of the cycle test, and using the measured total capacity retention rate obtained from the secondary battery data during operation or the total cycle test capacity retention rate obtained from the measured values ​​of the cycle test as the total capacity retention rate. The present invention relates to a secondary battery capacity retention rate estimation program according to a tenth embodiment, characterized by the following:

[0029] A fourteenth aspect of the present invention is: The procedure for creating a Weibull plot of the total capacity retention rate is to plot the total capacity retention rate in relation to ln(period) and ln(ln(1 / capacity retention rate)), and The procedure involves fitting a polynomial to the Weibull plot of the total capacity retention rate to obtain a polynomial that represents the curve, A procedure for finding the tangent line to the aforementioned polynomial during an initial predetermined period, From the slope and intercept of the tangent line, the Weibull coefficient m f and η f The procedure for finding and m f and η f The procedure for determining the float component volume retention rate from the above formula (1), The procedure for determining the cycle component volume retention rate is to divide the total volume retention rate by the float component volume retention rate, The procedure for creating a Weibull plot of the cycle component capacity retention rate is to plot the cycle component capacity retention rate in relation to ln(number of cycles) and ln(ln(1 / capacity retention rate)), and From the Weibull plot of the cycle component capacity retention rate, a linear cycle degradation prediction line is estimated, and from the slope and intercept of the cycle degradation prediction line, the Weibull coefficient m is calculated. c and η c Determine the above m c and η c The procedure for determining the cycle component volume retention rate from equation (2) above. Make the computer function and execute it. The thirteenth embodiment of a secondary battery capacity retention rate estimation program is characterized by the following:

[0030] A fifteenth aspect of the present invention is: The procedure for creating a Weibull plot of the total capacity retention rate is to plot the total capacity retention rate in relation to ln(period) and ln(ln(1 / capacity retention rate)), and The procedure involves fitting a polynomial to the Weibull plot of the total capacity retention rate to obtain a polynomial that represents the curve, A procedure for determining the slope of the polynomial from two points on the Weibull plot during an initial predetermined period, Find the tangent line to the polynomial with the aforementioned slope, and from the slope and intercept of the tangent line, find the Weibull coefficient m f and η f The procedure for finding and m f and η f The procedure for determining the float component volume retention rate from the above formula (1), The procedure for determining the cycle component volume retention rate is to divide the total volume retention rate by the float component volume retention rate, The procedure for creating a Weibull plot of the cycle component capacity retention rate is to plot the cycle component capacity retention rate in relation to ln(number of cycles) and ln(ln(1 / capacity retention rate)), and A procedure for estimating a linear cycle degradation prediction line from the Weibull plot of the aforementioned cycle component capacity retention rate, From the slope and intercept of the cycle degradation prediction line, the Weibull coefficient m c and η c Determine the above m c and η c The procedure for determining the cycle component volume retention rate from equation (2) above. Make the computer function and execute it. The thirteenth embodiment of a secondary battery capacity retention rate estimation program is characterized by the following:

[0031] A sixteenth aspect of the present invention is: The computer is instructed to perform a procedure to separate the float component capacity retention rate from the cycle component capacity retention rate by determining the float component capacity retention rate from the measured total capacity retention rate obtained from the secondary battery data during operation, and using the measured total capacity retention rate obtained from the secondary battery data during operation or the total cycle test capacity retention rate obtained from the measured values ​​of the cycle test as the total capacity retention rate. The present invention relates to a secondary battery capacity retention rate estimation program according to a tenth embodiment, characterized by the following:

[0032] A 17th aspect of the present invention is: The procedure for creating a Weibull plot of the measured total capacity retention rate is as follows: The procedure involves fitting a polynomial to the Weibull plot of the measured total capacity retention rate to obtain a polynomial that represents the curve, and A procedure for finding the tangent line to the aforementioned polynomial during an initial predetermined period, From the slope and intercept of the tangent line, the Weibull coefficient m f and η f The procedure for finding and m f and η f The procedure for determining the float component volume retention rate from the above formula (1), The procedure for determining the cycle component volume retention rate is to divide the total volume retention rate by the float component volume retention rate, The procedure for creating a Weibull plot of the cycle component capacity retention rate is to plot the cycle component capacity retention rate in relation to ln(number of cycles) and ln(ln(1 / capacity retention rate)), and A procedure for estimating a linear cycle degradation prediction line from the Weibull plot of the aforementioned cycle component capacity retention rate, From the slope and intercept of the cycle degradation prediction line, the Weibull coefficient m c and η c Determine the above m c and η c The procedure for determining the cycle component volume retention rate from equation (2) above. Make the computer function and execute it. The 16th embodiment of a secondary battery capacity retention rate estimation program is characterized by the following:

[0033] An eighteenth aspect of the present invention is: The procedure for creating a Weibull plot of the measured total capacity retention rate is to plot the relationship between ln(period) and ln(ln(1 / capacity retention rate)) and The procedure involves fitting a polynomial to the Weibull plot of the measured total capacity retention rate to obtain a polynomial that represents the curve, and A procedure for determining the slope of the polynomial from two points on the Weibull plot during an initial predetermined period, Find the tangent line to the polynomial with the aforementioned slope, From the slope and intercept of the tangent line, the Weibull coefficient m f and η f The procedure for finding and The procedure for determining the float component volume retention rate, The procedure for determining the cycle component volume retention rate is to divide the total volume retention rate by the float component volume retention rate, The procedure for creating a Weibull plot of the cycle component capacity retention rate is to plot the cycle component capacity retention rate in relation to ln(number of cycles) and ln(ln(1 / capacity retention rate)), and A procedure for estimating a linear cycle degradation prediction line from the Weibull plot of the aforementioned cycle component capacity retention rate, From the slope and intercept of the cycle degradation prediction line, the Weibull coefficient m c and η c Determine the above m c and η c The procedure for determining the cycle component volume retention rate from equation (2) above. Make the computer function and execute it. The 16th embodiment of a secondary battery capacity retention rate estimation program is characterized by the following:

[0034] A 19th aspect of the present invention is: A secondary battery capacity retention rate estimation device that performs a method for estimating the capacity retention rate of a secondary battery, A storage means storing data from at least one of the cycle test and the float test, The system includes data acquisition means for obtaining operational secondary battery data, period t, and cycle count N from the secondary battery. A procedure for separating the total capacity retention rate of a secondary battery obtained from at least one of the secondary battery data during operation and the cycle test into a float component capacity retention rate due to deterioration over the usage period and a cycle component capacity retention rate due to deterioration over the number of charge and discharge cycles, and The Weibull coefficient m corresponding to the float component capacity retention rate f , η f and a procedure for obtaining the float component capacity retention rate of the following formula (1), and The Weibull coefficient m corresponding to the cycle component capacity retention rate c , η c and a procedure for obtaining the cycle component capacity retention rate of the following formula (2), and Implementing a procedure for estimating the capacity retention rate at the period t or the number of cycles N by the following formula (A) to estimate the capacity retention rate (SOH) of the secondary battery There is a capacity retention rate estimation device for a secondary battery, characterized in that.

[0035]

Number

Effect of the Invention

[0036] According to the present invention, by separating the capacity retention rate of a secondary battery into a float component due to deterioration over time and a cycle component due to deterioration over the number of charge and discharge cycles, it is possible to accurately estimate the capacity retention rate of the secondary battery over a long period, and to provide a capacity retention rate estimation method for a secondary battery, a capacity retention rate estimation program for a secondary battery, and a capacity retention rate estimation device for a secondary battery.

Brief Description of the Drawings

[0037] [Figure 1] It is a diagram showing a schematic configuration of a storage battery system which is an example of a secondary battery to which the method of the present invention is applied. [Figure 2] It is a functional block diagram showing an example of the schematic configuration of the control unit of FIG. 1. [Figure 3] It is a schematic flowchart of the method of the present invention. [Figure 4]This figure shows an example of a Weibull plot of float test results. [Figure 5] This diagram illustrates a method for determining the cycle component capacity retention rate through rebate. [Figure 6] This figure shows a Weibull plot of the total cycle capacity retention rate in relation to the period t. [Figure 7] This figure illustrates an example of finding the equation of a curve by polynomial fitting to Weibull plot points, and then finding the slope of the tangent line by differentiating the polynomial. [Figure 8] This figure illustrates an example of determining the Weibull coefficients mf and ηf from the slope and intercept of the prediction line for float degradation. [Figure 9] This figure illustrates an example of a Weibull plot showing the cycle component capacity retention rate in relation to the number of cycles N. [Figure 10] This figure illustrates an example of determining the Weibull coefficients mc and ηc from the slope and intercept of the predicted line for cycle degradation. [Figure 11] This figure shows the results of Example 1. [Figure 12] This figure shows the results of Example 2. [Figure 13] This figure shows the results of Example 3. [Figure 14] This figure shows a comparison of predicted and measured values ​​for the long-term cycle in Example 1. [Figure 15] This figure shows the results of comparing the predicted values ​​and actual measured values ​​for long-term forecasting in Example 2. [Figure 16] This figure shows the results of Example 4. [Figure 17] This figure shows the results of Example 5. [Modes for carrying out the invention]

[0038] The present invention will be described in detail below based on embodiments.

[0039] (Embodiment 1) Figure 1 is a diagram showing an example of a schematic configuration of a battery storage system to which the method of the present invention is to be implemented. As shown in Figure 1, the battery storage system 1 comprises a battery storage system 2, which is a secondary battery for storing electricity, and a power adjustment device 3. The power adjustment device 3 is connected to a commercial power source 4, a load 5, and further to a solar power generation device 6, which is a power generation device that generates electricity using natural energy, for example.

[0040] The storage battery 2 is configured to be able to charge and discharge power, and is composed of one or more rechargeable secondary battery cells 2a. Examples of secondary battery cells 2a that make up such a storage battery 2 include lithium-ion batteries, nickel-metal hydride batteries, nickel-cadmium batteries, lead-acid batteries, etc. In this embodiment, a lithium-ion battery was used as the storage battery 2. Furthermore, the multiple secondary battery cells 2a are connected based on the functions and capabilities required of the storage battery, and may be connected in series or in parallel.

[0041] The power adjustment device 3 is a so-called power conditioner and includes an inverter 30 that rectifies the AC power supplied as commercial power 4 and converts the DC power from the storage battery 2 and the solar power generation device 6 into AC power and outputs it to the load 5, as well as a plurality of switches (first switch 31 to fifth switch 35) and a control unit 40 that controls the power adjustment device 3 overall. In this embodiment, the inverter 30 is a bidirectional inverter that has the function of converting input DC power into AC power and outputting it, and the function of converting input AC power into DC power and outputting it.

[0042] The commercial power supply 4 is supplied with electricity from an electric utility company, and in this embodiment, AC power is supplied.

[0043] The power generation device is a power generation device that generates electricity using natural energy (renewable energy) such as sunlight, solar thermal energy, hydroelectric power, wind power, geothermal energy, wave power, temperature difference, and biomass. In this embodiment, a solar power generation device 6 was used as the power generation device.

[0044] In this battery storage system 1, the power adjustment device 3 is controlled by the control unit 40 to convert the DC power generated by the solar power generation device 6 into AC power via the battery 2 and inverter 30 and supply it to the load 5 at a desired timing and rate. The power adjustment device 3 is also controlled by the control unit 40 to convert the AC power supplied from the commercial power supply 4 into DC power via the load 5 and inverter 30 and supply it to the battery 2 at a desired timing.

[0045] Furthermore, the power adjustment device 3 is equipped with a plurality of switches (first switch 31 to fifth switch 35) which are switches that can be opened and closed by the control unit 40. Specifically, it comprises a first switch 31 located between the solar power generation device 6 and the inverter 30, a second switch 32 located between the inverter 30 and the storage battery 2, a third switch 33 located between the branching point 50 between the commercial power supply 4 and the load 5 and the inverter 30, a fourth switch 34 located between the branching point 50 and the commercial power supply 4, and a fifth switch 35 located between the branching point 50 and the load 5. The control unit 40 controls the opening and closing of the first switch 31 to the fifth switch 35 to perform the charging and discharging of the storage battery 2 and control the supply destination of the commercial power supply 4. In other words, the first switch 31 to the fifth switch 35 are controllable by the control unit 40. Note that the fifth switch 35 may be a circuit breaker and not controlled by the control unit 40.

[0046] Here, the control unit 40 of the power adjustment device 3 will be further explained with reference to Figure 2. Figure 2 is a functional block diagram showing the schematic configuration of the control unit 40.

[0047] As shown in Figure 2, the control unit 40 controls the entire power adjustment device 3 and comprises a power generation device monitoring means 41, a storage battery monitoring means 42, and a charge / discharge control means 43.

[0048] The power generation device monitoring means 41 detects the power generation status of the photovoltaic power generation device 6. That is, the power generation device monitoring means 41 detects whether the photovoltaic power generation device 6 is generating power or not due to sunlight. The power generation device monitoring means 41 may also detect the amount of power generated when the photovoltaic power generation device 6 is generating power.

[0049] The battery monitoring means 42 measures the charge / discharge current, voltage, ambient and battery temperature, operating time, cycle count, etc. of the battery 2 and estimates the State of Charge (SOC), State of Health (SOH), etc. In addition, the battery monitoring means 42 in this embodiment also functions as a monitoring device (CMU: Cell Monitor Unit) that monitors voltage, current, temperature, etc. for each secondary battery cell 2a or for each group of battery cells composed of multiple secondary battery cells 2a. The battery monitoring means 42 detects abnormalities in the voltage, current, temperature, etc. of the secondary battery cell 2a or the group of multiple secondary battery cells 2a and transmits the occurrence of the abnormality to the charge / discharge control means 43.

[0050] The charge / discharge control means 43 controls the inverter 30 and the first to fifth switches 31 to 5 35 based on various conditions to control the charging and discharging of the storage battery 2 and the power supply from the commercial power source 4.

[0051] The power generation device monitoring means 41, the battery monitoring means 42, and the charge / discharge control means 43, although not specifically shown in the figures, can be implemented by a central processing unit (CPU), a read-and-write memory (RAM), and a read-only memory (ROM) for storing various programs, which constitute the power adjustment device 3.

[0052] The method of the present invention is applied to such battery storage systems, but of course, it is not limited to these battery storage systems. The present invention provides a method for estimating the capacity retention rate of a secondary battery that is actually in use. Specifically, it obtains data such as temperature, current, voltage, operating time, and cycle count of an operating secondary battery, and estimates the state of health (SOH) based on this data.

[0053] While the battery monitoring means 42 may perform the method of the present invention, the battery monitoring means 42 may also transmit the data it collects to an external computing device, and the computing device that acquired the data may then perform the method of the present invention. A secondary battery capacity retention rate estimation device that implements the method of the present invention comprises, for example, a storage means for storing data from at least one of a cycle test and a float test, a data acquisition means for obtaining operational secondary battery data, period t, and number of cycles N from the secondary battery, and a calculation device for performing various calculations. The storage means, data acquisition means, and computing device are preferably provided by a server connected via a network such as the Internet, but they may also be provided by a computer connected to the network.

[0054] In this invention, the terms are defined and used as follows. The state of health (SOH) of a secondary battery is separated into a float component, which is due to degradation caused by the use of the secondary battery, and a cycle component, which is due to degradation caused by charging and discharging. The capacity retention rate due to degradation caused by the period of use is defined as the float component capacity retention rate, and the capacity retention rate due to degradation caused by the number of charge and discharge cycles is defined as the cycle component capacity retention rate. Furthermore, in addition to the capacity retention rate estimated by this invention, the capacity retention rate of secondary batteries may also be as follows. Actual total capacity retention rate: Determined from data of a secondary battery in operation. Total cycle test capacity retention rate: Determined from the measured values ​​of the cycle test.

[0055] The measured total capacity retention rate and total cycle test capacity retention rate, which are derived from measurements, include both the float component and the cycle component, and this is defined as the total capacity retention rate. Note that the measured value from the float test includes only the float component and is not included in the total capacity retention rate.

[0056] A schematic flowchart of the present invention's method is shown in Figure 3. In this invention, the measured capacity retention rate of a secondary battery, obtained from data of a secondary battery in operation, cycle tests, and float tests, is separated into a float component capacity retention rate due to degradation over the period of use and a cycle component capacity retention rate due to degradation over the number of charge-discharge cycles. As shown in Figure 3, the method of the present invention determines the measured capacity retention rate by comparing the total capacity retention rate, such as the measured total capacity retention rate or the total cycle test capacity retention rate, with the float test capacity retention rate obtained by a float test if necessary (step S1). After this, a float component separation step (step S10) and a cycle component separation step (step S20) are performed.

[0057] In the float component separation step S10, the steps include plotting the float component volume retention rate (step S11) and calculating the time from the SOH calculation base point and the SOH Weibull coefficient (float degradation) m f η f The process involves performing the steps of determining (step S12) and determining the float component volume retention rate (step S13).

[0058] On the other hand, in the cycle component separation step S20, there is a step (step S21) to plot the cycle component volume retention rate, and the time from the SOH calculation base point and the SOH Weibull coefficient (cycle degradation) m c η c The steps of determining (step S22) and determining the cycle component volume retention rate (step S23) are performed.

[0059] Note that the plot of the cycle component capacity retention rate in step S21 can be made, for example, by performing a step (step S30) of dividing back the total capacity retention rate by the float component capacity retention rate. The float component capacity retention rate is represented by the following formula (1), and the cycle component capacity retention rate is represented by the following formula (2). Then, in the present invention, the capacity retention rate (SOH(t)) of a target battery cell or the like is estimated (step S50) using the following estimation formula (A) for the capacity retention rate SOH (step S40).

[0060] In the power storage system described above, the power storage battery monitoring means 42 acquires temperature, current, voltage, operating period, etc. for each secondary battery cell 2a or for each battery cell group composed of a plurality of secondary battery cells 2a, and uses this to estimate the capacity retention rate of the target battery cell or the like by the following estimation formula (A) for the capacity retention rate SOH.

[0061] Here, when using the estimation formula (A) for the capacity retention rate, through an experiment using a test battery cell of the same type as the target battery cell, the Weibull coefficient m f , η f , m c and η c are preferably obtained in advance.

[0062] The Weibull coefficient m f , η f , m c and η c depend on the capacity, structure, material, etc. of the battery cell, and thus are different for each type of battery cell. Therefore, it is preferable to use the same type of battery test cell. If the same type of test battery cell is not used, the estimation result of the capacity retention rate will deviate from that of the power storage system. Even for the same type of test battery cell, it differs depending on the average charge rate (average SOC) of its usage situation. Therefore, it is preferable to obtain the Weibull coefficient m f , η f for each average SOC. Also, the Weibull coefficient m f , and η fSince this value also changes depending on the operating temperature, it is preferable to determine it for each temperature. Furthermore, as will be discussed later, the Weibull coefficient m is related to the cycle degradation. c and η c It is independent of temperature.

[0063] Furthermore, the Weibull coefficient m was obtained from the test battery. f η f , m c and η c This is determined by performing calculations using a formula that estimates the capacity retention rate from each test.

[0064] Then, the battery monitoring means 42 obtains the temperature, current, and voltage of the battery cells, etc., and calculates the average State of Charge (SOC) of the operating battery, and the Weibull coefficient m corresponding to the calculated average SOC and temperature. f η f , m c and η c Select the appropriate component and estimate the capacity retention rate (SOH) of the battery cell, etc., using the following estimation formula (A).

[0065]

number

[0066] The following describes in detail the method for estimating the capacity retention rate of a secondary battery using the capacity retention rate estimation formula (A) described above.

[0067] The present invention is based on a method for estimating the capacity retention rate of a secondary battery, in which the secondary battery is treated as an assembly of partial batteries, and the capacity retention rate of the secondary battery is predicted using Weibull's law based on the prediction of the failure rate of the partial batteries. However, a key feature of this method is that it separates the degradation of the secondary battery, which causes a decrease in the capacity retention rate, into float degradation and cycle degradation, and uses this separation as the estimation formula (A). By separating and processing the temperature-dependent float component capacity retention rate and the temperature-independent cycle component capacity retention rate, a more accurate capacity retention rate can be estimated, and as will be described in detail later, in particular, the capacity retention rate after long-term use can be estimated more accurately. Therefore, the present invention has a significant effect in determining the lifespan of a secondary battery.

[0068] Here, float component capacity retention rate refers to degradation that depends on the usage period of the secondary battery, while cycle component capacity retention rate refers to degradation that depends on the number of cycles, with one cycle being a charge-discharge cycle.

[0069] The procedure for determining the Weibull coefficient is described below. (Float test for coefficient determination) For a specified type of secondary battery, the battery is operated at a specified temperature and fixed at a specified state of charge (SOC), and the change in capacity over the operating time is measured. If necessary, the same test is performed under different operating temperatures and SOCs. For example, the capacity is checked by fixing the voltage at 50% SOC and leaving the battery at different temperatures such as 25°C, 45°C, and 60°C for extended periods. Alternatively, the capacity is checked at 25°C, 45°C, and 60°C while fixing the voltage at other SOC percentages.

[0070] (Cycle test for coefficient determination) For a specified type of secondary battery, one cycle is defined as the period during which the battery is charged from 0% to 100% SOC and then discharged from 100% SOC to 0%. The SOC is repeatedly increased or decreased while the cycle period is constant. For example, if charging and discharging are performed three times a day, three cycles can be completed in one day, resulting in 300 cycles in 100 days and 3000 cycles in 1000 days.

[0071] The capacity corresponding to the number of cycles is measured, and the total cycle test capacity retention rate is obtained to determine the Weibull coefficient.

[0072] The measured values ​​obtained are the capacity for each cycle count when the secondary battery is operated at a predetermined temperature. The number of cycles and the measured values ​​just need to correspond; the measurement can be performed after each cycle, at predetermined intervals, or irregularly. To make the SOH estimation more accurate, it is preferable to have as many measured values ​​as possible.

[0073] The capacity retention rate is calculated by dividing the degraded capacity by the capacity at the start of the test, and is the ratio of the degraded capacity to the initial capacity retention rate. In other words, the total cycle test capacity retention rate is the value obtained by dividing the measured value obtained from the cycle test by the initial full charge capacity.

[0074] (Measurement method for determining coefficients from operational secondary batteries) The measured values ​​for determining the coefficient may be directly obtained from the secondary battery, for example, the energy storage system described above, which is the target of the estimation of the capacity retention rate (SOH). The measured values ​​for determining the float coefficient can be obtained by measuring the capacity when a predetermined SOC is reached during a predetermined operating period from the start of operation, and the measured values ​​for determining the cycle coefficient can be obtained by measuring the capacity when a predetermined number of cycles have been completed from the start of operation. The method for counting the number of cycles when obtaining the measured values ​​for determining the cycle coefficient can be determined as appropriate. For example, one cycle may be counted as a set of charge and discharge where the capacity moved by 50% or more of the full charge capacity, or one cycle may be counted every two passes through a specific percentage of SOC, or one cycle may be counted when the accumulated actual charge and discharge capacity matches the capacity of one charge and discharge cycle of that battery. Since the battery temperature does not change significantly depending on the environment in which the energy storage system is placed, the battery temperature can be measured and the average temperature can be used.

[0075] The capacity retention rate is calculated by dividing the capacity after degradation by the capacity at the start of the test, and is the ratio of the capacity after degradation to the initial capacity retention rate. In other words, the capacity retention rate is the value obtained by dividing the measured value from the energy storage system by the initial full charge capacity.

[0076] The capacity retention rate of the energy storage system can be estimated by determining a predetermined Weibull coefficient using the following procedure. (Separation method 1 for float component capacity retention rate and cycle component capacity retention rate) A cycle test is performed using a specified lot of a specified type of secondary battery, and at the same time, a float test is performed using the same lot of secondary batteries.

[0077] The capacity retention rate is determined from the measured capacity in this way, and the Weibull coefficient is determined by plotting a Weibull plot (vertical axis ln(ln(1 / retention rate)), horizontal axis ln(period t)). Note that plotting with the vertical axis ln(ln(1 / retention rate)) and the horizontal axis ln(period t) can also be expressed as plotting the relationship between the natural logarithm ln(t) of the float period t and the natural logarithm ln(ln(1 / measured float value)) of the reciprocal of the measured float value.

[0078] First, a Weibull plot is created showing the relationship between the float test period t and the retention rate, resulting in a graph with the vertical axis ln(ln(1 / retention rate)) and the horizontal axis ln(period t)). A linear prediction line (float degradation prediction line) is then obtained from this graph using a fitting method such as regression analysis (e.g., least squares method), and the slope and intercept of this prediction line are used to determine m f and η f We will find the slope of the prediction line m. f and η f is exp[intercept / (-m f This is the result. Note that this type of fitting method can also be performed using simulation software or spreadsheet software.

[0079] In this way, from the results of the float test, the Weibull coefficient m corresponding to the float component volume retention rate can be obtained. f η f It is possible to find this.

[0080] Figure 4 shows an example of a Weibull plot of the results of this float test, plotting the measured values ​​at 25°C and 45°C with a SOC of 50%, and at 60°C with a SOC of 50%, and the Weibull coefficient m under each condition. f η f And this Weibull coefficient m can be calculated. f η f The float component volume retention rate can be determined from this.

[0081] It can be seen that the Weibull coefficient differs depending on the temperature under each condition. When determining the capacity retention rate of an operating battery, it is preferable to use the results of a float test under temperature conditions close to the operating temperature or average temperature.

[0082] On the other hand, the Weibull coefficient m of the cycle component capacity retention rate c η c This cannot be determined from the results of cycle tests. In reality, the degradation data obtained from cycle tests includes components that have degraded purely by the cycle and components that have degraded by the float.

[0083] In a cycle test, the capacity retention rate can be considered to be equal to the retention rate due to pure cycle degradation multiplied by the retention rate due to float degradation (according to Weibull's law, multiplying the summation values ​​results in the summation value). Therefore, it is preferable to use the formula: Capacity retention rate due to pure cycle degradation = Capacity retention rate obtained from the measured values ​​of the cycle test (measured value) ÷ Float component capacity retention rate (predicted value from Weibull's law for the float test mentioned above). In this case, this calculation is referred to as "dividing back".

[0084] Figure 5 shows an example of this recalculation. Dividing (a) "Total cycle capacity retention rate obtained from the measured values ​​of the cycle test (measured value)" by (b) "Float component capacity retention rate (predicted value from Weibull's law in the float test, plotted after converting the period t to the number of cycles N)" gives (c) "Cycle component capacity retention rate, which is the retention rate due to pure cycle degradation."

[0085] Figure 5(c) plots the measured data at 25°C, 45°C, and 60°C, along with the results obtained by dividing these values ​​by the volume retention rate determined from the float test. The vertical axis plots the volume retention rate (vertical axis) for each cycle number for cycle tests at 25°C, 45°C, and 60°C with a SOC of 50%.

[0086] To explain this recalculation in more detail, float degradation also occurs during the N cycles due to the float period t. For example, if a 1000-cycle test yields a capacity retention rate of 85%, the float retention rate for the period t required to complete 1000 cycles is calculated by analyzing the float test results using Weibull's law. If this result (for example, Figure 5(b)) is 90%, then the cycle retention rate due to pure cycle degradation over 1000 cycles is 85% ÷ 90% = 94.4%, which is the cycle component capacity retention rate (Figure 5(c)).

[0087] Thus, using the cycle component capacity retention rate of pure cycle degradation, a Weibull plot (vertical axis ln(ln(1 / retention rate)), horizontal axis ln(period t)) is created, and the Weibull coefficient is determined in the same way as in the float test. That is, from the Weibull plot, a prediction line is obtained using a fitting method such as the least squares method, similar to the float test, and the slope and intercept of this prediction line are used to determine m c η c We will find this Weibull coefficient m. c η c From this, the retention rate of the cycle component volume can be determined.

[0088] (Separation method 2 for float component capacity retention rate and cycle component capacity retention rate) A cycle test is performed using a specified lot of secondary batteries of a specified type. The total cycle capacity retention rate is determined from the measured capacity obtained from such tests, and this is plotted in relation to the period t using a Weibull plot (vertical axis ln(ln(1 / total capacity retention rate)), horizontal axis ln(period t)). An example of this result is shown in Figure 6.

[0089] Next, the equation of the curve is obtained by polynomial fitting of the plotted points, and the slope of the tangent line is found by differentiating the polynomial. When finding the slope of the tangent line, it is preferable to find the slope as early as possible in the Weibull plot. The section up to the 5th plot point is preferable because the effects of cycle degradation are minimal. The section up to the 3rd plot point is even preferable, and finding the tangent line at the 1st point is even preferable. This is because finding the tangent line at a shorter time period eliminates the effects of cycle degradation. An example of this result is shown in Figure 7.

[0090] Furthermore, in the early stages of the Weibull plot, the slope of the line between two points on the Weibull plot can be used as the slope of the tangent line to determine the slope. In this case as well, it is preferable to determine the tangent line at a shorter time period, as this eliminates the effect of cycle degradation. Also, it is preferable to use plots with consecutive cycle numbers for the two points on the Weibull plot used to determine the slope.

[0091] This slope is taken as the slope of the prediction line for the float component volume retention rate, and the equation of the straight line that is tangent to the first point of the curve is found. This equation of the straight line is taken as the prediction line for the float degradation. Then, the Weibull coefficient m is obtained from the slope and intercept of this prediction line. f η f We will find the value. Figure 8 shows an example of this result.

[0092] Next, the total capacity retention rate is divided back by the predicted line of the float component capacity retention rate to obtain the cycle component capacity retention rate, and a Weibull plot is created in relation to the number of cycles N. Figure 9 shows an example of this result. Next, from the Weibull plot of cycle degradation, a prediction line is obtained using a fitting method such as the least squares method, similar to the example described above, and the slope and intercept of this prediction line are used to determine m c η c We calculate this. Figure 10 shows an example of this result. In this way, the capacity retention rate can be determined in the same manner as in separation method 1 described above.

[0093] (Separation method 3 for float component volume retention rate and cycle component volume retention rate) The data from the battery that is actually in operation is retrieved from the data storage location. The measured total capacity retention rate is determined from the capacity obtained from the measured values ​​of the battery in operation, and this is plotted as a Weibull plot in relation to the period t (vertical axis ln(ln(1 / total capacity retention rate)), horizontal axis ln(period t)).

[0094] Next, the equation of the curve is obtained by polynomial fitting of the plotted points, and the slope of the tangent line is found by differentiating the polynomial. When finding the slope of the tangent line, it is preferable to find the slope as early as possible in the Weibull plot. The interval up to the 5th plot point is preferable because the effects of cycle degradation are minimal. The interval up to the 3rd plot point is even preferable, and finding the tangent line at the 1st point is even preferable. This is because finding the tangent line at a shorter time period eliminates the effects of cycle degradation.

[0095] Furthermore, in the early stages of the Weibull plot, the slope of the line between two points on the Weibull plot can be used as the slope of the tangent line to determine the slope. In this case as well, it is preferable to determine the tangent line at a shorter time period, as this eliminates the effects of cycle degradation. Also, it is preferable to use two points on the Weibull plot used to determine the slope that represent consecutive cycle numbers.

[0096] This slope is taken as the slope of the prediction line for the float component volume retention rate, and the equation of the straight line that is tangent to the first point of the curve is found, and this equation of the straight line is taken as the prediction line for the float degradation. Then, the Weibull coefficient m is obtained from the slope and intercept of this prediction line. f η f We seek.

[0097] Next, the total capacity retention rate is divided by the predicted line of the float component capacity retention rate to obtain the cycle component capacity retention rate, and a Weibull plot is created in relation to the number of cycles N. Then, from the Weibull plot of the cycle degradation, a prediction line is obtained using a fitting method such as the least squares method, similar to the example described above, and the slope and intercept of this prediction line are used to determine m c η cThis is how we determine the capacity retention rate. In this way, the capacity retention rate can be determined in the same manner as in separation methods 1 and 2 described above.

[0098] (Estimation of capacity retention rate) For secondary batteries of the same type as the one being estimated, the Weibull coefficient m corresponds to a predetermined temperature and predetermined SOC. f η f , m c and η c Select the appropriate value and introduce it into the prediction formula (A) described above to estimate the volume retention rate SOH for period t.

[0099] By more accurately estimating the future State of Health (SOH), it becomes possible to appropriately set the charge and discharge parameters for degraded secondary batteries that have been used for a long time, thereby preventing overcharging and over-discharging and enabling safer battery use. Furthermore, it becomes possible to more accurately determine the timing of remaining charge detection, maintenance, and battery replacement in the energy storage system. [Examples]

[0100] (Example 1) For lithium-ion secondary batteries, the Weibull coefficient was determined using the separation method for float degradation and cycle degradation described above. Secondary battery (PD50S03): The positive electrode is lithium iron phosphate, the negative electrode is graphite, and the electrolyte is ethylene carbonate (EC):dimethyl carbonate (DMC) = 3:7 with 1.2M lithium hexafluoride phosphate (LiPF6) as a supporting electrolyte. The positive and negative electrodes are stacked elements facing each other with a polyolefin separator in between. The capacity is 50Ah. The elements are housed in a stainless steel metal case. The cycle test consisted of 6 cycles per day. The float test was conducted at an average SOC of 75% and a temperature of 30°C.

[0101] When the Weibull coefficients were determined using the separation method 1 described above, the Weibull coefficients were as follows. m f (m of the volume retention rate of the float component) = 0.289298 η f (η of the volume retention rate of the float component) = 7.14 × 10 3 (The period is in years) m c (m of the cycle component volume retention rate) = 1.86356 η c (η of the cycle component volume retention rate) = 40751.6 Furthermore, the result was a degradation curve as shown in Figure 11.

[0102] (Example 2) Using the same secondary battery as in Example 1, the capacity retention rate was determined using the separation method 1 for float degradation and cycle degradation described above. Figure 12 shows the capacity retention rate at 60°C and for each state of temperature (SOC).

[0103] (Example 3) Using the same secondary battery as in Example 1, the capacity retention rate was determined using the separation method 1 for float degradation and cycle degradation described above. Figure 13 shows the volume retention rate at 25°C and each SOC.

[0104] (Examples 1-3) Figures 11 to 13, which show the results of Examples 1 to 3 obtained using separation method 1, show that in all cases the predicted values ​​and the measured values ​​were in close agreement.

[0105] Figure 14 also shows a comparison of predicted and measured values ​​for the long-term cycle of Example 1. The forecast was based on 6 cycles per day, an average SOC of 70%, and a temperature of 30°C. As a result, the predicted values ​​and the measured values ​​were in close agreement.

[0106] Furthermore, Figure 15 shows the results of comparing the predicted values ​​and measured values ​​for Example 2, based on long-term forecasts.

[0107] As a result, the predicted and actual values ​​matched even after nearly 15,000 cycles. For comparison, we plotted the results predicted using the Weibull rule without separating float degradation and cycle degradation (Comparative Example 1), and the results predicted using the conventional exponential rule (Comparative Example 2). It was found that the deviation from the measured values ​​becomes large after 11,000 cycles.

[0108] (Example 4) Using the same secondary battery as in Example 1, the capacity retention rate was determined using the separation method 2 for float degradation and cycle degradation described above. The results are shown in Figure 16. The float degradation prediction × cycle degradation prediction results for Example 4, and the predicted values ​​and measured values ​​were in close agreement. For comparison, the results for float degradation prediction only and cycle degradation prediction only are also shown, but these differed significantly from the measured values.

[0109] (Example 5) Using data obtained from a system (battery capacity 2.5kWh) consisting of 16 secondary batteries connected in series, the same as in Example 1, the capacity retention rate was determined using the float degradation and cycle degradation separation method 3 described above. The results are shown in Figure 17, and the predicted and measured values ​​were in close agreement. [Industrial applicability]

[0110] This invention can be effectively used in industrial fields that construct battery storage systems that utilize batteries as a power source, as well as in industrial fields that perform their maintenance and operation. [Explanation of Symbols]

[0111] 1…Battery storage system 2… Storage battery 2a…Secondary battery cell 3…Power adjustment device 4…Commercial power supply 5…Load 6…Solar power generation equipment (power generation equipment) 30…Inverter 31…First switch 32...Second switch 33... Third switch 34…Fourth switch 35…5th switch 40... Control Unit 41... Power generation equipment monitoring means 42...Battery monitoring means 43...Charge / Discharge Control Means

Claims

1. In a method for estimating the capacity retention rate (SOH) of a secondary battery using Weibull's law, When separating the total capacity retention rate of a secondary battery obtained from at least one of the operational secondary battery data and cycle test results into the float component capacity retention rate due to degradation over the period of use and the cycle component capacity retention rate due to degradation over the number of charge / discharge cycles, the following separation is performed: (a), (b), or (c) (a) The float component capacity retention rate is determined from the measured values ​​of the float test, and the measured total capacity retention rate obtained from the secondary battery data during operation or the total cycle test capacity retention rate obtained from the measured values ​​of the cycle test is taken as the total capacity retention rate, and the float component capacity retention rate and the cycle component capacity retention rate are separated. (b) The float component capacity retention rate is determined by the measured values ​​of the cycle test, and the measured total capacity retention rate obtained from the secondary battery data during operation or the total cycle test capacity retention rate obtained from the measured values ​​of the cycle test is taken as the total capacity retention rate, and the float component capacity retention rate and the cycle component capacity retention rate are separated. (c) The float component capacity retention rate is determined by the measured total capacity retention rate obtained from the secondary battery data during operation, and the measured total capacity retention rate obtained from the secondary battery data during operation or the total cycle test capacity retention rate obtained from the measured values ​​of the cycle test is taken as the total capacity retention rate, and the float component capacity retention rate and the cycle component capacity retention rate are separated; Next, The Weibull coefficient m corresponding to the float component volume retention rate ｆ η ｆ And determine the float component volume retention rate of the following formula (1), Weibull coefficient m corresponding to the cycle component capacity retention rate ｃ η ｃ And calculate the cycle component volume retention rate using the following formula (2): A method for estimating the capacity retention rate of a secondary battery, characterized by estimating the capacity retention rate over a period t or number of cycles N using the following formula (A). [Math 1]

2. When separating in (a), By plotting the float component volume retention rate in relation to ln (period) and ln (ln(1 / volume retention rate)), a Weibull plot of the float component volume retention rate is created. A linear float degradation prediction line is estimated from the Weibull plot of the float component volume retention rate. From the slope and intercept of the float deterioration prediction line, m ｆ and η ｆ Seeking, Said m ｆ and η ｆ And the float component volume retention rate is determined from the above formula (1), The cycle component capacity retention rate is obtained by dividing the total capacity retention rate by the float component capacity retention rate. By plotting the cycle component capacity retention rate in relation to ln(number of cycles) and ln(ln(1 / capacity retention rate)), a Weibull plot of the cycle component capacity retention rate is created. A linear cycle degradation prediction line is estimated from the Weibull plot of the cycle component capacity retention rate. From the slope and intercept of the cycle deterioration prediction line, m ｃ and η ｃ are obtained, Said m ｃ and η ｃ The cycle component volume retention rate is determined from the above equation (2). The method for estimating the capacity retention rate of a secondary battery according to feature 1.

3. When separating in (b), A Weibull plot of the total capacity retention rate is created by plotting the relationship between ln (period) and ln (ln(1 / capacity retention rate)). The Weibull plot of the total capacity retention rate is fitted with a polynomial to obtain a polynomial that represents the curve. Find the tangent line to the aforementioned polynomial during the initial predetermined period, From the slope and intercept of the aforementioned tangent, m ｆ and η ｆ Seeking, Said m ｆ and η ｆ And the float component volume retention rate is determined from the above formula (1), The cycle component capacity retention rate is obtained by dividing the total capacity retention rate by the float component capacity retention rate. The aforementioned cycle component capacity retention rate is plotted in relation to ln(number of cycles) and ln(ln(1 / capacity retention rate)) to create a Weibull plot of the cycle component capacity retention rate. A linear cycle degradation prediction line is estimated from the Weibull plot of the cycle component capacity retention rate, and the slope and intercept of the cycle degradation prediction line are used to determine m ｃ and η ｃ Seeking, Said m ｃ and η ｃ The cycle component volume retention rate is determined from the above equation (2). The method for estimating the capacity retention rate of a secondary battery according to feature 1.

4. When separating in (b), A Weibull plot of the total capacity retention rate is created by plotting the relationship between ln (period) and ln (ln(1 / capacity retention rate)). The Weibull plot of the total capacity retention rate is fitted with a polynomial to obtain a polynomial that represents the curve. The slope of the polynomial is determined from the two points of the Weibull plot during the initial predetermined period. Find the tangent line to the polynomial having the aforementioned slope, and from the slope and intercept of the tangent line, m ｆ and η ｆ Seeking, Said m ｆ and η ｆ And the float component volume retention rate is determined from the above formula (1), The cycle component capacity retention rate is obtained by dividing the total capacity retention rate by the float component capacity retention rate. The aforementioned cycle component capacity retention rate is plotted in relation to ln(number of cycles) and ln(ln(1 / capacity retention rate)) to create a Weibull plot of the cycle component capacity retention rate. A linear cycle degradation prediction line is estimated from the Weibull plot of the cycle component capacity retention rate. From the slope and intercept of the cycle degradation prediction line, m ｃ and η ｃ Seeking, Said m ｃ and η ｃ The cycle component volume retention rate is determined from the above equation (2). The method for estimating the capacity retention rate of a secondary battery according to feature 1.

5. When separating (c), By plotting the measured total capacity retention rate in relation to ln(period) and ln(ln(1 / capacity retention rate)), a Weibull plot of the measured total capacity retention rate is created. The Weibull plot of the measured total capacity retention rate is fitted with a polynomial to obtain a polynomial that represents the curve. Find the tangent line to the aforementioned polynomial during the initial predetermined period, From the slope and intercept of the aforementioned tangent, m ｆ and η ｆ Seeking, Said m ｆ and η ｆ And the float component volume retention rate is determined from the above formula (1), The cycle component capacity retention rate is obtained by dividing the total capacity retention rate by the float component capacity retention rate. By plotting the cycle component capacity retention rate in relation to ln(number of cycles) and ln(ln(1 / capacity retention rate)), a Weibull plot of the cycle component capacity retention rate is created. A linear cycle degradation prediction line is estimated from the Weibull plot of the cycle component capacity retention rate. From the slope and intercept of the cycle degradation prediction line, m ｃ and η ｃ Seeking, Said m ｃ and η ｃ The cycle component volume retention rate is determined from the above equation (2). The method for estimating the capacity retention rate of a secondary battery according to feature 1.

6. When separating in (c), By plotting the measured total capacity retention rate in relation to ln(period) and ln(ln(1 / capacity retention rate)), a Weibull plot of the measured total capacity retention rate is created. The Weibull plot of the measured total capacity retention rate is fitted with a polynomial to obtain a polynomial that represents the curve. The slope of the polynomial is determined from the two points of the Weibull plot during the initial predetermined period. Find the tangent line to the polynomial with the aforementioned slope, From the slope and intercept of the aforementioned tangent, m ｆ and η ｆ Seeking, Said m ｆ and η ｆ And the float component volume retention rate is determined from the above formula (1), The cycle component capacity retention rate is obtained by dividing the total capacity retention rate by the float component capacity retention rate. By plotting the cycle component capacity retention rate in relation to ln(number of cycles) and ln(ln(1 / capacity retention rate)), a Weibull plot of the cycle component capacity retention rate is created. A linear cycle degradation prediction line is estimated from the Weibull plot of the cycle component capacity retention rate. From the slope and intercept of the cycle degradation prediction line, m ｃ and η ｃ Seeking, Said m ｃ and η ｃ The cycle component volume retention rate is determined from the above equation (2). The method for estimating the capacity retention rate of a secondary battery according to feature 1.

7. In a secondary battery capacity retention rate (SOH) estimation program that estimates the capacity retention rate of secondary batteries using Weibull's law, When separating the total capacity retention rate of a secondary battery obtained from at least one of operational secondary battery data, cycle tests, and float tests into a float component capacity retention rate due to degradation over the period of use and a cycle component capacity retention rate due to degradation over the number of charge-discharge cycles, the following separation procedure is performed: (a) The float component capacity retention rate is determined from the measured values ​​of the float test, and the measured total capacity retention rate obtained from the secondary battery data during operation or the total cycle test capacity retention rate obtained from the measured values ​​of the cycle test is taken as the total capacity retention rate, and the float component capacity retention rate and the cycle component capacity retention rate are separated. (b) The float component capacity retention rate is determined by the measured values ​​of the cycle test, and the measured total capacity retention rate obtained from the secondary battery data during operation or the total cycle test capacity retention rate obtained from the measured values ​​of the cycle test is taken as the total capacity retention rate, and the float component capacity retention rate and the cycle component capacity retention rate are separated. (c) The float component capacity retention rate is determined by the measured total capacity retention rate obtained from the secondary battery data during operation, and the measured total capacity retention rate obtained from the secondary battery data during operation or the total cycle test capacity retention rate obtained from the measured values ​​of the cycle test is taken as the total capacity retention rate, and the float component capacity retention rate and the cycle component capacity retention rate are separated; The Weibull coefficient m corresponding to the float component volume retention rate ｆ η ｆ And the procedure for determining the float component volume retention rate in the following formula (1), Weibull coefficient m corresponding to the cycle component capacity retention rate ｃ η ｃ And the procedure for determining the cycle component volume retention rate in the following formula (2), The computer is made to perform the procedure for estimating the capacity retention rate over a period of t or a number of cycles N using the following formula (A). A program for estimating the capacity retention rate of a secondary battery, characterized by the above features. [Math 2]

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