Battery life determination method, apparatus, electronic device, and storage medium
By employing multiple linear judgment processes and combining the linear relationship between the differential capacity curve and the capacity decay value, the lifespan of lithium-ion batteries can be accurately determined, solving the problem of low accuracy in existing technologies and improving the accuracy of lithium-ion battery lifespan determination.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BATTERO TECH CORP LTD
- Filing Date
- 2022-10-31
- Publication Date
- 2026-06-12
Smart Images
Figure CN122193979A_ABST
Abstract
Description
[0001] This invention is a divisional application of the invention patent application filed on October 31, 2022, with application number 202211346381.X and application title "Battery Life Determination Method, Apparatus, Electronic Device and Storage Medium". Technical Field
[0002] This invention relates to the field of battery technology, and in particular to a method, apparatus, electronic device, and storage medium for determining battery life. Background Technology
[0003] To improve the safety of lithium-ion batteries, it is necessary to determine their cycle life to prevent damage caused by exceeding their cycle life. Currently, the cycle life of lithium-ion batteries can be determined based on the linear relationship between capacity retention and the number of battery cycles. However, due to abnormal conditions such as lithium plating that may occur during use, the linear relationship between capacity retention and cycle life may not be maintained. Therefore, directly determining the cycle life based on this linear relationship has low accuracy. Summary of the Invention
[0004] This invention provides a method, apparatus, electronic device, and storage medium for determining battery life, thereby improving the accuracy of battery life determination.
[0005] According to one aspect of the present invention, a method for determining battery life is provided, the method comprising at least one linear judgment process and a life determination process;
[0006] A linear decision process includes:
[0007] Perform charge-discharge cycles on the battery under test;
[0008] Determine the differential capacity curve and capacity decay value of the battery under test at different preset cycle numbers;
[0009] If the peak value of the differential capacity curve and the preset number of cycles satisfy a first linear relationship, and the capacity decay value and the preset number of cycles do not satisfy a second linear relationship, then the next linear judgment process is executed.
[0010] If the differential capacity peak value and the preset number of cycles satisfy the first linear relationship, and the capacity decay value and the preset number of cycles satisfy the second linear relationship, then the lifetime determination process is executed;
[0011] The lifespan determination process includes: determining the number of cycles corresponding to when the capacity decay value of the battery under test reaches the capacity decay threshold based on the second linear relationship, so as to determine the lifespan of the battery under test.
[0012] Optionally, determining the differential capacity curve and capacity decay value of the battery under test at different preset cycle numbers includes:
[0013] Starting from the current cycle number when the cycle is completed, and moving backward at preset intervals, obtain the discharge data of the battery under test at different preset cycle numbers; wherein, the discharge data includes at least the capacity and discharge voltage of the battery under test;
[0014] Based on the discharge data, the differential capacity curve and capacity decay value of the battery under test at different preset cycle numbers are determined.
[0015] Optionally, the method further includes:
[0016] If the differential capacity peak value and the preset number of cycles do not satisfy the first linear relationship, then the battery under test is determined to be abnormal.
[0017] Optionally, the peak differential capacity and the preset number of cycles satisfy a first linear relationship, including:
[0018] Based on the first linear relationship, a first function is obtained by linearly fitting each differential capacity peak value and its corresponding preset number of cycles.
[0019] If the first fitting variance of the first function is within a first preset range, then the peak differential capacity of the battery under test and the corresponding preset number of cycles satisfy the first linear relationship.
[0020] Optionally, the capacity decay value and the preset number of cycles satisfy a second linear relationship, including:
[0021] Based on the second linear relationship, a second function is obtained by linearly fitting each capacity decay value and the corresponding preset number of cycles.
[0022] If the second fitting variance of the second function is within the first preset range, then the capacity decay value and its corresponding preset number of cycles satisfy the second linear relationship.
[0023] Optionally, before determining the differential capacity curve and capacity decay value of the battery under test at different preset cycle numbers, the method further includes:
[0024] Obtain the initial capacity of the battery under test after at least two initial cycles;
[0025] The average of at least two initial capacities is used as the standard capacity of the battery under test.
[0026] Optionally, determining the capacity decay value of the battery under test at different preset number of cycles includes:
[0027] Obtain the current capacity of the battery under test at different preset number of cycles;
[0028] The capacity decay value is determined based on the difference between the current capacity and the standard capacity.
[0029] According to another aspect of the present invention, a battery life determination apparatus is provided, the battery life determination apparatus comprising:
[0030] The charge / discharge module is used to perform charge / discharge cycles on the battery under test.
[0031] The differential capacity curve and capacity decay value determination module is used to determine the differential capacity curve and capacity decay value of the battery under test at different preset cycle numbers;
[0032] A linearity judgment module is used to determine whether the peak value of the differential capacity curve and the preset number of cycles satisfy a first linear relationship, and whether the capacity decay value and the preset number of cycles satisfy a second linear relationship;
[0033] The lifespan determination module is used to determine the number of cycles corresponding to when the capacity decay value of the battery under test reaches the capacity decay threshold, based on the second linear relationship, if the differential capacity peak value and the preset number of cycles satisfy a first linear relationship and the capacity decay value and the preset number of cycles satisfy a second linear relationship, so as to determine the lifespan of the battery under test.
[0034] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:
[0035] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the battery life determination method according to any embodiment of the present invention.
[0036] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the battery life determination method according to any embodiment of the present invention.
[0037] The technical solution of this invention, through at least one linear judgment process, determines that if the differential capacity peak value of the differential capacity curve and the preset number of cycles satisfy a first linear relationship, but the capacity decay value and the preset number of cycles do not satisfy a second linear relationship, then it indicates that the battery under test may have an abnormal lithium plating phenomenon during the first charge-discharge cycle, and it is necessary to continue charging-discharge cycling on the battery under test and execute the next linear judgment process. By determining the differential capacity curve and capacity decay value at different preset number of cycles in the second cycle, linear judgment is continued. If, after the second cycle, the capacity decay value and the preset number of cycles still satisfy the second linear relationship, the linear judgment process continues, and the battery under test continues to be charged and discharged. If, after the second cycle, the differential capacity peak value of the differential capacity curve and the preset number of cycles satisfy the first linear relationship, and the capacity decay value and the preset number of cycles satisfy the second linear relationship, then, based on the second linear relationship, the capacity decay value and the preset number of cycles corresponding to different preset number of cycles in the second cycle are fitted to determine the function of capacity decay value and preset number of cycles. The capacity decay threshold is then substituted into the function of capacity decay value and preset number of cycles, and the resulting number of cycles is the lifespan of the battery under test. By performing linear judgment on the parameters of the battery under test, the function of capacity decay value and preset number of cycles can be accurately determined after lithium plating abnormalities occur in the battery under test. Compared with directly substituting the parameters of the battery under test into the linear relationship to determine the battery lifespan, this method can more accurately determine the lifespan of the battery under test. The technical solution of this invention solves the problem of low accuracy in battery lifespan obtained by directly substituting battery parameters into the linear relationship, and improves the accuracy of battery lifespan determination.
[0038] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description
[0039] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0040] Figure 1 This is a flowchart of a battery life determination method provided in an embodiment of the present invention;
[0041] Figure 2 This is a flowchart of another method for determining battery life provided by an embodiment of the present invention;
[0042] Figure 3This is the first curve showing the change of the peak value of the differential capacity with respect to the number of cycles;
[0043] Figure 4 It is the first curve showing the change of the logarithm of the capacity decay value with respect to the logarithm of the number of cycles;
[0044] Figure 5 This is the second curve showing the peak value of the differential capacity as a function of the number of cycles;
[0045] Figure 6 It is the second curve showing the change of the logarithm of the capacity decay value with respect to the logarithm of the number of cycles;
[0046] Figure 7 This is a flowchart of another method for determining battery life provided by an embodiment of the present invention;
[0047] Figure 8 This is a schematic diagram of a battery life determination device provided in an embodiment of the present invention;
[0048] Figure 9 This is a schematic diagram of the structure of an electronic device that implements the battery life determination method of the present invention. Detailed Implementation
[0049] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.
[0050] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0051] Figure 1 This is a flowchart of a battery life determination method provided in an embodiment of the present invention, such as... Figure 1 As shown, the battery life determination method includes:
[0052] S110, Perform charge-discharge cycles on the battery under test.
[0053] Specifically, the battery under test is, for example, a lithium-ion battery whose lifespan needs to be determined. The lifespan of the battery under test is, for example, its cycle life, which is the number of charge-discharge cycles the battery can undergo. One cycle includes one complete charge and discharge process. During the charge-discharge cycle of the battery under test, the number of cycles and the discharge data of the battery under test can be recorded in real time, providing a basis for subsequently determining the lifespan of the battery under test.
[0054] S120. Determine the differential capacity curve and capacity decay value of the battery under test at different preset cycle numbers.
[0055] Specifically, the differential capacity curve is, for example, the curve showing the change of the differential capacity of the battery under test with respect to its discharge voltage. The differential capacity of the battery under test is the derivative of its capacity with respect to the discharge voltage. Based on the capacity and discharge voltage of the battery under test during the discharge process at a preset number of cycles, the differential capacity of the battery under test can be determined, thereby determining the differential capacity curve at the preset number of cycles. The capacity decay value is, for example, the decrease in the capacity of the battery under test relative to its standard capacity. Based on the capacity of the battery under test during the discharge process at the preset number of cycles and the standard capacity of the battery under test, the capacity decay value of the battery under test at the preset number of cycles is determined.
[0056] S130. Determine whether the peak value of the differential capacity curve and the preset number of cycles satisfy the first linear relationship. If yes, proceed to step S140; otherwise, end.
[0057] Specifically, the differential capacity curve contains at least one characteristic peak, which indicates a phase transition in the battery material under test. The peak value of the differential capacity curve is, for example, the peak value corresponding to the first characteristic peak, which is the characteristic peak corresponding to the minimum discharge voltage among all characteristic peaks. The first linear relationship is, for example, y1 = a1x + b1, where y1 is the differential capacity peak value, x is the number of cycles, a1 is the first proportionality coefficient, and b1 is the first constant coefficient. If the differential capacity peak value and the corresponding preset number of cycles satisfy the first linear relationship, it indicates that the capacity change of the battery under test is normal, the battery state is normal, and the test can continue. If the differential capacity peak value and the corresponding preset number of cycles do not satisfy the first linear relationship, it indicates that the capacity change of the battery under test is abnormal, and the charging / discharging and lifespan determination of the battery under test is terminated.
[0058] S140. Determine whether the capacity decay value and the preset number of cycles satisfy the second linear relationship. If yes, proceed to step S150; otherwise, return to continue to step S110.
[0059] Specifically, the second linear relationship is, for example, Lny2 = a2Lnx + b2, where y2 is the capacity decay value, x is the number of cycles, a2 is the second proportional coefficient, and b2 is the second constant coefficient. If the capacity decay value and the preset number of cycles satisfy the second linear relationship, it indicates that the capacity decay of the battery under test is within the normal range. Since the capacity decay value and the preset number of cycles satisfy the second linear relationship, the lifespan of the battery under test can be determined based on the second linear relationship and the capacity decay threshold. If the capacity decay value and the preset number of cycles do not satisfy the second linear relationship, it indicates that the battery under test may experience lithium plating abnormalities during the first charge-discharge cycle. It is necessary to continue charging-discharge cycling the battery under test and determine the differential capacity curve and capacity decay value at different preset number of cycles in the second cycle. If, after the second cycle, the capacity decay value and the preset number of cycles still satisfy the second linear relationship, then the battery under test continues charging-discharge cycling; if, after the second cycle, the differential capacity peak value of the differential capacity curve and the preset number of cycles satisfy the first linear relationship, and the capacity decay value and the preset number of cycles satisfy the second linear relationship. Based on the second linear relationship, the capacity decay value corresponding to different preset cycle numbers in the second cycle is fitted to the preset cycle number to determine the function of capacity decay value and preset cycle number, which makes it easier to determine the life of the battery under test based on the function of capacity decay value and preset cycle number.
[0060] For example, the first cycle may consist of 200 cycles. If the capacity decay value and the preset number of cycles do not satisfy the second linear relationship, it indicates that the battery under test may have experienced lithium plating abnormalities during the first charge-discharge cycle. Therefore, the charge-discharge cycle continues, for example, up to 1000 cycles. The preset number of cycles in the second cycle may be 1000, 800, 600, and 400 cycles. If the differential capacity peak value of the differential capacity curve at 1000, 800, 600, and 400 cycles satisfies the first linear relationship with the preset number of cycles, and the capacity decay value and the preset number of cycles satisfy the second linear relationship, then based on the second linear relationship, the capacity decay value at 1000, 800, 600, and 400 cycles is fitted to the preset number of cycles to determine the function of capacity decay value and preset number of cycles. This facilitates determining the lifespan of the battery under test based on the function of capacity decay value and preset number of cycles.
[0061] By linearly judging the parameters of the battery under test, the function of capacity decay value and preset cycle number can be accurately determined after lithium plating abnormality occurs in the battery under test. Compared with directly substituting the parameters of the battery under test into the linear relationship to determine the battery life, the life of the battery under test can be determined more accurately.
[0062] S150. Based on the second linear relationship, determine the number of cycles corresponding to when the capacity decay value of the battery under test reaches the capacity decay threshold, so as to determine the life of the battery under test.
[0063] Specifically, the capacity decay threshold can be, for example, the capacity decay value corresponding to 80% of the standard capacity, or the capacity decay value corresponding to 70% of the standard capacity. Different application scenarios have different requirements for batteries, and the capacity decay threshold may also be different. Based on the second linear relationship, the capacity decay value corresponding to different preset cycle numbers and the preset cycle number are fitted to determine the function of capacity decay value and preset cycle number. Substituting the capacity decay threshold into the function of capacity decay value and preset cycle number, the resulting cycle number is the lifespan of the battery under test.
[0064] It should be noted that steps S110-S140 are linear judgment processes, and step S150 is a lifespan determination process. When the differential capacity peak value of the differential capacity curve and the preset number of cycles satisfy the first linear relationship, but the capacity decay value and the preset number of cycles do not satisfy the second linear relationship, the next linear judgment process is executed until the differential capacity peak value of the differential capacity curve and the preset number of cycles satisfy the first linear relationship, and the capacity decay value and the preset number of cycles satisfy the second linear relationship. Then, the lifespan determination process is executed to determine the lifespan of the battery under test.
[0065] The technical solution of this embodiment, by setting at least one linear judgment process, determines that if the differential capacity peak value of the differential capacity curve and the preset number of cycles satisfy a first linear relationship, but the capacity decay value and the preset number of cycles do not satisfy a second linear relationship, it indicates that the battery under test may have an abnormal lithium plating phenomenon in the first charge-discharge cycle, and it is necessary to continue charging-discharge cycling on the battery under test and execute the next linear judgment process. By determining the differential capacity curve and capacity decay value at different preset number of cycles in the second cycle, the linear judgment continues. If, after the second cycle, the capacity decay value and the preset number of cycles still satisfy the second linear relationship, the linear judgment process continues, and the battery under test continues to be charged and discharged. If, after the second cycle, the differential capacity peak value of the differential capacity curve and the preset number of cycles satisfy the first linear relationship, and the capacity decay value and the preset number of cycles satisfy the second linear relationship, then, based on the second linear relationship, the capacity decay value and the preset number of cycles corresponding to different preset number of cycles in the second cycle are fitted to determine the function of capacity decay value and preset number of cycles. The capacity decay threshold is then substituted into the function of capacity decay value and preset number of cycles, and the resulting number of cycles is the lifespan of the battery under test. By performing linear judgment on the parameters of the battery under test, the function of capacity decay value and preset number of cycles can be accurately determined after abnormal conditions occur in the battery under test (such as lithium plating abnormality). Compared with directly substituting the parameters of the battery under test into the linear relationship to determine the battery lifespan, the lifespan of the battery under test can be determined more accurately. The technical solution of this embodiment solves the problem of low accuracy in battery lifespan obtained by directly substituting battery parameters into the linear relationship, and improves the accuracy of battery lifespan determination.
[0066] Furthermore, the technical solution of this embodiment does not require setting up a small current calibration test outside of charge and discharge cycles, which reduces the time required to determine battery life.
[0067] Figure 2 This is a flowchart of another battery life determination method provided in an embodiment of the present invention. Optionally, refer to... Figure 2 The method for determining battery life includes:
[0068] S210, Perform charge-discharge cycles on the battery under test.
[0069] S220. Starting from the current cycle number when the cycle is completed, proceed backwards at preset intervals to obtain the discharge data of the battery under test at different preset cycle numbers; wherein, the discharge data includes at least the capacity and discharge voltage of the battery under test.
[0070] Specifically, after the cycle ends, multiple preset cycle counts are obtained by counting backwards from the current cycle count at the end of the cycle, at preset intervals. For example, the number of charge-discharge cycles of the battery under test is N, where N is a positive integer greater than 0. Multiple preset cycle counts are selected backwards from the cycle count at the end of the cycle, for example, N, Nm, N-2m…N-km; where k≥2, m≥10, and N-km>0. For example, when N=200, m=50, and k=2, the preset cycle counts are 200, 150, and 100. The capacity and discharge voltage of the battery under test during the discharge process are then obtained at 200, 150, and 100 cycles. If the capacity decay value and the preset cycle count do not satisfy the second linear relationship, it indicates that the battery under test may experience lithium plating abnormalities during the first charge-discharge cycle. Therefore, the charge-discharge cycle continues, for example, up to 1000 cycles. The preset cycle counts in the second cycle are, for example, 1000, 800, 600, and 400 cycles. After each round of iterations, starting from the current iteration count when the previous iteration was completed, and moving backwards at preset intervals, multiple preset iteration counts are obtained for each round.
[0071] S230. Determine the differential capacity curve and capacity decay value of the battery under test at different preset cycle numbers based on the discharge data.
[0072] Specifically, based on the capacity and discharge voltage of the battery under test during discharge, the differential capacity of the battery under test can be determined, thereby determining the differential capacity curve at a preset number of cycles. Based on the capacity of the battery under test during discharge and its standard capacity at the preset number of cycles, the capacity decay value of the battery under test at the preset number of cycles is determined.
[0073] For example, when the number of cycles is 200, the differential capacity curve and capacity decay value of the battery under test are determined by acquiring the capacity and discharge voltage during the discharge process at 200, 150 and 100 cycles.
[0074] S240. Determine whether the peak value of the differential capacity curve and the preset number of cycles satisfy the first linear relationship. If not, proceed to step S250; if yes, proceed to step S260.
[0075] S250, The battery under test is found to be abnormal.
[0076] Specifically, if the peak differential capacity and the preset number of cycles do not satisfy the first linear relationship, the differential capacity may suddenly change during a certain discharge, that is, the differential capacity of the battery under test may suddenly change, the capacity of the battery under test may change significantly, and the material of the battery under test may undergo a large phase transition, thus determining that the battery under test is abnormal, and no further charge-discharge cycles and life determination will be performed on the battery under test.
[0077] S260. Determine whether the capacity decay value and the preset number of cycles satisfy the second linear relationship. If yes, proceed to step S270; otherwise, return to continue to step S210.
[0078] S270. Based on the second linear relationship, determine the number of cycles corresponding to when the capacity decay value of the battery under test reaches the capacity decay threshold, so as to determine the life of the battery under test.
[0079] Based on the above implementation schemes, optionally, the peak differential capacity and the preset number of cycles satisfy a first linear relationship, including:
[0080] Step c1: Based on the first linear relationship, perform linear fitting on each differential capacity peak and its corresponding preset number of cycles to obtain the first function.
[0081] Specifically, the first function is a function of the differential capacity peak value with respect to the number of iterations. Based on the first linear relationship y1 = a1x + b1, a linear fit is performed on the differential capacity peak value and its corresponding preset number of iterations to obtain the first function, which facilitates determining whether the differential capacity peak value and the preset number of iterations satisfy the first linear relationship.
[0082] Step c2: If the first fitting variance of the first function is within the first preset range, then the peak value of the differential capacity of the battery under test and the corresponding preset number of cycles satisfy the first linear relationship.
[0083] Specifically, if the first fitting variance of the first function is within a first preset range, for example, the first fitting variance R1 2 If the value is greater than 0.95, it indicates that there is no overfitting or underfitting, thus confirming that the peak differential capacity of the battery under test and the corresponding preset number of cycles satisfy the first linear relationship.
[0084] For example, Table 1 is a first schematic table showing the differential capacity peak value and discharge voltage corresponding to a preset number of cycles. Figure 3 This is the first curve showing the change of the differential capacity peak value with respect to the number of cycles. Based on the first linear relationship, the differential capacity peak values in Table 1 and the corresponding preset number of cycles are fitted to obtain the following: Figure 3 The curve showing the first variation of the peak value of the differential capacity with respect to the number of cycles is shown.
[0085] Table 1. First schematic table of differential capacity peak value and discharge voltage corresponding to preset cycle number.
[0086]
[0087] like Figure 3 As shown, almost all data points fall on the curve, and the first fit variance R1 2=0.9957, which is greater than 0.95, thus determining that the peak value of the differential capacity and the corresponding preset number of cycles satisfy the first linear relationship.
[0088] Based on the above implementation schemes, optionally, the capacity decay value and the preset number of cycles satisfy a second linear relationship, including:
[0089] Step d1: Based on the second linear relationship, perform linear fitting on each capacity decay value and the corresponding preset number of cycles to obtain the second function.
[0090] Specifically, the second function is a function of the logarithm of the capacity decay value with respect to the logarithm of the number of cycles. Based on the second linear relationship Lny2=a2Lnx+b2, the logarithm of the capacity decay threshold and the corresponding logarithm of the preset number of cycles are linearly fitted to obtain the second function, which facilitates determining whether the capacity decay threshold and the preset number of cycles satisfy the second linear relationship.
[0091] Step d2: If the second fitting variance of the second function is within the first preset range, then the capacity decay value and its corresponding preset number of cycles satisfy the second linear relationship.
[0092] Specifically, if the second fitting variance of the second function is within a first preset range, for example, the second fitting variance R² 2 A value greater than 0.95 indicates that there is no overfitting or underfitting, thus confirming that the capacity threshold of the battery under test and the corresponding preset number of cycles satisfy the second linear relationship.
[0093] For example, Figure 4 This is the first curve showing the change of the logarithm of the capacity decay value with respect to the logarithm of the number of cycles. Based on the second linear relationship, the capacity decay value and the corresponding preset number of cycles are fitted to obtain the following... Figure 4 The curve shown illustrates the first change in the logarithm of the capacity decay value with respect to the logarithm of the number of cycles. (See also...) Figure 4 As shown, almost all points lie on the curve, and the second fit variance R² is... 2 =0.9973, which is greater than 0.95, thus determining that the capacity decay value and the corresponding preset number of cycles satisfy the second linear relationship.
[0094] In addition, according to Figure 3 The first curve showing the variation of the peak differential capacity with respect to the number of cycles and Figure 4The capacity retention rate at 500, 1000, and 1200 cycles was calculated using the first curve showing the change of the logarithm of the capacity decay value with respect to the logarithm of the number of cycles. This was compared with measured data. Table 2 shows a first schematic table of the calculated and measured capacity retention rates corresponding to the number of cycles. As shown in Table 2, the deviation between the calculated and measured capacity retention rates is small, indicating that the calculated and measured values are very close. Figure 3 The curve showing the first variation of the peak differential capacity with respect to the number of cycles and Figure 4 The first curve showing the logarithm of the capacity decay value versus the logarithm of the number of cycles is highly accurate.
[0095] Table 2. First schematic table of calculated and measured capacity retention rates corresponding to the number of cycles.
[0096]
[0097] In another implementation, if the battery under test exhibits an anomaly, such as lithium plating, the capacity threshold and the corresponding preset cycle number may not satisfy the second linear relationship. During the charge / discharge cycle of the battery under test, a larger preload is introduced at the 700th cycle to induce lithium plating, thus obtaining the differential capacity peak and discharge voltage corresponding to the preset cycle number. Table 3 is a second schematic table showing the differential capacity peak and discharge voltage corresponding to the preset cycle number. Figure 5 This is the second curve showing the peak value of the differential capacity as a function of the number of cycles. Figure 6 This is the second curve showing the change of the logarithm of the capacity decay value with respect to the logarithm of the number of cycles. Based on the first linear relationship, the differential capacity peak value in Table 3 is fitted to the corresponding preset number of cycles, resulting in the following... Figure 5 The second curve showing the peak differential capacity versus the number of cycles is shown, and the capacity decay value corresponding to the preset number of cycles in Table 3 is used to obtain the following... Figure 6 The second curve shows the logarithm of the capacity decay value versus the logarithm of the number of cycles.
[0098] Table 3. Second schematic table of differential capacity peak value and discharge voltage corresponding to preset cycle number.
[0099]
[0100] like Figure 5 As shown, in the first round of iterations (the first 700 iterations), almost all data points fall on the first curve segment, and the first fit variance R0 11 2=0.9931, which is greater than 0.95, thus confirming that in the first cycle, the peak value of the differential capacity and the corresponding preset number of cycles satisfy the first linear relationship. In the second cycle (cycles 700 to 900), almost all data points fall on the second curve segment, and the first fitting variance R0 is within the range of 0.9931. 12 2 =0.9981, which is greater than 0.95, thus determining that in the second round of the loop, the peak value of the differential capacity and the corresponding preset number of loops satisfy the first linear relationship. For example... Figure 6 As shown, in the first round of iterations (the first 700 iterations), almost all data points fall on the first segment of the curve, and the second fit variance R0 21 2 =0.9978, which is greater than 0.95, thus confirming that in the first cycle, the capacity decay value and the corresponding preset number of cycles satisfy the second linear relationship. In the second cycle (cycles 700 to 900), almost all data points fall on the second curve segment, and the second fitting variance R0 is within the second linear range. 21 2 =0.9926, which is greater than 0.95, thus determining that in the second cycle, the capacity decay value and the corresponding preset number of cycles satisfy the second linear relationship. Therefore, based on the function of the capacity decay value and the number of cycles determined in the second cycle, the lifespan of the battery under test can be determined.
[0101] In addition, according to Figure 5 The second curve showing the peak differential capacity with respect to the number of cycles and Figure 6 The second segment of the second curve representing the logarithm of the capacity decay value with respect to the logarithm of the number of cycles is used to calculate the segmented capacity retention rate for 1000, 1100, and 1200 cycles. The differential capacity peak value and the preset number of cycles in Table 3 are fitted into a segmented curve. The capacity decay value corresponding to the preset number of cycles in Table 3 is fitted into a segmented curve. Based on the segmented curve, the single-mode capacity retention rate is calculated and compared with the measured data. Table 4 is a second schematic table showing the calculated capacity retention rate and the measured capacity retention rate corresponding to the number of cycles.
[0102] Table 4. Second Schematic Table of Calculated and Measured Capacity Retention Rates Corresponding to Number of Cycles
[0103]
[0104] As shown in Table 4, the segmented deviation between the calculated and measured values of capacity retention rate using the segmented method is small, while the single deviation between the calculated and measured values of capacity retention rate using the single method is large, indicating that... Figure 5 The second curve showing the peak value of the differential capacity with respect to the number of cycles and Figure 6The second curve showing the logarithm of the capacity decay value with respect to the logarithm of the number of cycles has higher accuracy, meaning that the lifespan of the battery under test calculated by the piecewise curve is more accurate.
[0105] Figure 7 This is a flowchart of another battery life determination method provided in an embodiment of the present invention. Optionally, refer to... Figure 7 The method for determining battery life includes:
[0106] S310. Obtain the initial capacity of the battery under test after at least two initial cycles.
[0107] Specifically, "at least two initial cycles" refers to at least two charge-discharge cycles starting from the beginning of the battery under test. For example, obtaining the initial capacity of the battery under test at the initial three cycles means obtaining the initial capacity of the battery under test at the first discharge, the initial capacity at the second discharge, and the initial capacity at the third discharge. Because the material properties of the battery under test are relatively good at the beginning of charge-discharge, the capacity decay of the battery under test is negligible. Therefore, obtaining the initial capacity of the battery under test at the initial at least two cycles facilitates the accurate determination of the standard capacity of the battery under test.
[0108] S320, Use the average of at least two initial capacities as the standard capacity of the battery under test.
[0109] For example, when obtaining the initial capacity of the battery under test in the first three cycles, the average of the initial capacity of the battery under test in the first discharge, the initial capacity in the second discharge, and the initial capacity in the third discharge is taken as the standard capacity of the battery under test.
[0110] S330, perform charge-discharge cycles on the battery under test.
[0111] S340. Starting from the current cycle number when the cycle is completed, proceed backwards at preset intervals to obtain the discharge data of the battery under test at different preset cycle numbers; wherein, the discharge data includes at least the capacity and discharge voltage of the battery under test.
[0112] S350. Determine the differential capacity curve and capacity decay value of the battery under test at different preset cycle numbers based on the discharge data.
[0113] S360. Determine whether the peak value of the differential capacity curve and the preset number of cycles satisfy the first linear relationship. If not, proceed to step S370; if yes, proceed to step S380.
[0114] S370, The battery under test is confirmed to be faulty.
[0115] S380. Determine whether the capacity decay value and the preset number of cycles satisfy the second linear relationship. If yes, proceed to step S390; otherwise, return to continue to step S310.
[0116] S390. Based on the second linear relationship, determine the number of cycles corresponding to when the capacity decay value of the battery under test reaches the capacity decay threshold, so as to determine the life of the battery under test.
[0117] Based on the above technical solution, optionally, the capacity decay value of the battery under test at different preset cycle numbers is determined, including:
[0118] Step e1: Obtain the current capacity of the battery under test at different preset number of cycles.
[0119] Specifically, the current capacity of the battery under test after discharge is obtained after a preset number of cycles. For example, when the number of cycles is 200, the current capacity of the battery under test after discharge after 200, 150, and 100 cycles can be obtained.
[0120] Step e2: Determine the capacity decay value based on the difference between the current capacity and the standard capacity.
[0121] Specifically, by subtracting the current capacity at the preset number of cycles from the standard capacity, the capacity decay value corresponding to the preset number of cycles can be obtained. For example, by subtracting the current capacity of the battery under test after 200 cycles from the standard capacity, the capacity decay value of the battery under test after 200 cycles can be determined.
[0122] Figure 8 This is a schematic diagram of a battery life determination device provided in an embodiment of the present invention, as shown below. Figure 8 As shown, the battery life determination device includes: a charge / discharge module 410, a differential capacity curve and capacity decay value determination module 420, a linearity judgment module 430, and a life determination module 440. The charge / discharge module 410 is used to perform charge / discharge cycles on the battery under test. The differential capacity curve and capacity decay value determination module 420 is used to determine the differential capacity curve and capacity decay value of the battery under test at different preset cycle numbers. The linearity judgment module 430 is used to determine whether the differential capacity peak value of the differential capacity curve and the preset cycle number satisfy a first linear relationship, and whether the capacity decay value and the preset cycle number satisfy a second linear relationship. The life determination module 440 is used to determine the number of cycles corresponding to when the capacity decay value of the battery under test reaches the capacity decay threshold, based on the second linear relationship, if the differential capacity peak value and the preset cycle number satisfy the first linear relationship, and the capacity decay value and the preset cycle number satisfy the second linear relationship, so as to determine the life of the battery under test.
[0123] Optionally, the differential capacity curve and capacity decay value determination module 420 is specifically used to obtain the discharge data of the battery under test at different preset cycle numbers, starting from the current cycle number when the cycle is completed and proceeding forward at preset intervals; wherein, the discharge data includes at least the capacity and discharge voltage of the battery under test; and to determine the differential capacity curve and capacity decay value of the battery under test at different preset cycle numbers based on the discharge data.
[0124] Optionally, the battery life determination device further includes an anomaly determination module, which determines that the battery under test is abnormal if the differential capacity peak value and the preset number of cycles do not satisfy a first linear relationship.
[0125] Optionally, the battery life determination device further includes a standard capacity determination module, which is used to obtain the initial capacity of the battery under test at least twice in the initial cycle; and to take the average of the at least two initial capacities as the standard capacity of the battery under test.
[0126] The battery life determination device provided in this embodiment of the invention can execute the battery life determination method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the method.
[0127] Figure 9 A schematic diagram of an electronic device 10, which can be used to implement embodiments of the present invention, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein. Figure 9 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.
[0128] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.
[0129] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as battery life determination methods.
[0130] In some embodiments, the battery life determination method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the battery life determination method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the battery life determination method by any other suitable means (e.g., by means of firmware).
[0131] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.
[0132] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.
[0133] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.
[0134] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).
[0135] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.
[0136] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.
[0137] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.
[0138] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.
Claims
1. A method for determining battery life, characterized in that, This includes the first linear judgment process and the lifetime determination process; The first linear judgment process includes: Perform the first round of charge-discharge cycles on the battery under test; Determine the differential capacity curve and capacity decay value of the battery under test under different preset cycle numbers; if the differential capacity peak value of the differential capacity curve and the corresponding preset cycle number satisfy a first linear relationship, and the capacity decay value and the corresponding preset cycle number satisfy a second linear relationship, execute the lifetime determination process; The lifespan determination process includes: determining the number of cycles corresponding to the capacity decay threshold of the battery under test based on the second linear relationship, which is taken as the lifespan of the battery under test.
2. The method according to claim 1, characterized in that, The method also includes, If the differential capacity peak value and the corresponding preset number of cycles satisfy the first linear relationship, and the capacity decay value and the corresponding preset number of cycles do not satisfy the second linear relationship, the battery under test is charged and discharged continuously to perform the second linear judgment process.
3. The method according to claim 1, characterized in that, The differential capacity curve contains at least one characteristic peak, which indicates that the material of the battery under test has undergone a phase transition. The differential capacity peak value of the differential capacity curve is the peak value corresponding to the first characteristic peak, which is the characteristic peak corresponding to the minimum discharge voltage among the at least one characteristic peak.
4. The method according to claim 1, characterized in that, Determining whether the peak value of the differential capacity and the corresponding preset number of cycles satisfy a first linear relationship includes: Based on the first linear relationship, a first function is obtained by linearly fitting each differential capacity peak value and the corresponding preset number of cycles. When the first fitting variance of the first function is within a first preset range, it is determined that the peak value of each differential capacity and the corresponding preset number of cycles satisfy the first linear relationship.
5. The method according to claim 4, characterized in that, The first linear relationship is y1=a1x+b1, where y1 is the peak value of the differential capacity, x is the number of the first cycle or the number of the second cycle, a1 is the first proportional coefficient, and b1 is the first constant coefficient.
6. The method according to claim 1, characterized in that, Determining whether the capacity decay value and the corresponding preset number of cycles satisfy a second linear relationship includes: Based on the second linear relationship, a second function is obtained by linearly fitting each capacity decay value and the corresponding preset number of cycles. When the second fitting variance of the second function is within a first preset range, it is determined that each capacity decay value and the corresponding preset number of cycles satisfy the second linear relationship.
7. The method according to claim 6, characterized in that, The second linear relationship is Lny2=a2Lnx+b2, where y2 is the capacity decay value, x is the number of the first cycle or the number of the second cycle, a2 is the second proportional coefficient, and b2 is the second constant coefficient.
8. The method according to claim 1, characterized in that, Determining the capacity decay value of the battery under test when the number of cycles reaches different preset cycles includes: Obtain the current capacity of the battery under test at different preset cycle counts; The capacity decay value corresponding to each preset number of cycles is determined based on the difference between each current capacity and the standard capacity.
9. The method according to claim 8, characterized in that, The method further includes: Obtain the initial capacity of the battery under test after at least two initial cycles; The average of at least two initial capacities is used as the standard capacity of the battery under test.
10. The method according to claim 1, characterized in that, Determining the differential capacity curve and capacity decay value of the battery under test under different preset cycle numbers includes: Starting from the first cycle count, and moving backward at preset intervals, discharge data of the battery under test is obtained for different preset cycle counts; wherein, the discharge data includes the capacity and discharge voltage of the battery under test; Based on the discharge data, determine the differential capacity curve and capacity decay value of the battery under test when the number of cycles reaches different preset number of cycles.
11. The method according to claim 1, characterized in that, The method further includes: If the differential capacity peak value and the corresponding preset number of cycles do not satisfy the first linear relationship, the battery under test is determined to be abnormal.
12. An electronic device, characterized in that, include: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the battery life determination method according to any one of claims 1-11.
13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the battery life determination method according to any one of claims 1-11.