Battery capacity estimation method and device based on charging terminal current reduction data

Abstract

The present invention provides a battery capacity estimation method and device based on charging terminal current reduction data. The method performs cyclic decay on each type of battery pack to obtain multiple sets of battery pack experimental data. Each set of battery pack experimental data is processed to obtain multiple charging data sets. The average slope of each charging data set is obtained based on all charging data sets. The relationship between the average slope of each charging data set and the corresponding intermediate capacity is determined. The method obtains battery pack data corresponding to a set number of cyclic decay cycles of the battery pack under test, processes the battery pack data corresponding to the set number of cyclic decay cycles to obtain the average slope of the corresponding charging data set, and estimates the capacity of the battery under test based on the average slope of the charging data set corresponding to the set number of cyclic decay cycles and the relationship between the average slope of the charging data set and the corresponding intermediate capacity. The present invention can automatically and efficiently estimate battery capacity.

Description

Technical Field

[0001] The present invention relates to the field of battery technology, and in particular to a battery capacity estimation method and device based on charging terminal current reduction data. Background Art

[0002] Lithium batteries, due to their high energy density and long lifespan, have become the primary power source for electric vehicles, mobile phones, and other fields. In the process of battery state estimation, battery capacity estimation plays a vital role.

[0003] There are two main types of battery capacity estimation methods: model method and data-driven method.

[0004] The model method is divided into empirical model and mechanism model. The empirical model is prone to parameter mismatch during use. The main challenge of the mechanism model is the lack of a unique theoretical circuit model for lithium batteries, and the numerical estimation of virtual circuit components requires large and expensive equipment such as EIS equipment.

[0005] The advantage of data-driven methods is that they don't require knowledge of the battery's internal electrochemical properties. They can extract certain characteristics of the battery's degradation process to achieve online estimation of battery capacity, making them practical. Therefore, data-driven methods have gradually become the mainstream method for battery state estimation. However, most data-driven methods have complex feature extraction processes and a large number of feature variables. In some cases, they also need to be combined with machine learning algorithms, which brings a certain degree of complexity.

[0006] Generally, the minimum capacity of a single cell in a battery pack determines the service life and efficiency of the battery pack. Offline calibration of the battery pack capacity requires disassembling the battery pack and fully charging and discharging it, which is time-consuming and labor-intensive. Summary of the Invention

[0007] In view of the above-mentioned shortcomings of the prior art, an object of the present invention is to provide a battery capacity estimation method and device based on charging terminal current reduction data, so as to solve the problem of low efficiency in the prior art.

[0008] To achieve the above and other related objectives, the present invention provides a method for estimating battery capacity based on charging terminal current reduction data, the method comprising at least the following steps:

[0009] Perform cycle decay on each type of battery pack to obtain multiple sets of battery pack experimental data;

[0010] Processing the experimental data of each battery pack to obtain multiple charging data sets;

[0011] Obtain the average slope of each charging data set based on all charging data sets;

[0012] The relationship between the average slope of the charging data set and the corresponding intermediate capacity is obtained according to the average slope of each charging data set and the intermediate capacity of the corresponding cycle decay;

[0013] Obtain battery pack data corresponding to the set number of times the battery pack to be tested is cycle-attenuated for a set number of times, process the battery pack data corresponding to the set number of times to obtain the average slope of the corresponding charging data set, and estimate the capacity of the battery to be tested based on the average slope of the charging data set corresponding to the set number of cycle-attenuation and the relationship between the average slope of the charging data set and the corresponding intermediate capacity.

[0014] Preferably, the process of performing cycle decay on the battery pack to obtain multiple sets of battery pack experimental data includes at least:

[0015] Based on the initial capacity of the battery pack, the battery pack is fully discharged and fully charged in sequence to reduce the capacity of the battery pack to an intermediate capacity;

[0016] A set of battery pack experimental data is obtained according to a full charging process; the battery pack experimental data is the voltage, current, temperature and battery pack capacity of each single cell at each moment during the full charging process;

[0017] Cycle multiple full discharge and full charge processes until the battery pack capacity decays to the battery pack discharge cut-off capacity;

[0018] After cycle decay, multiple groups of battery pack experimental data are obtained; each group of battery pack experimental data includes a single cell experimental data set of each single cell at each time.

[0019] Preferably, each full charging process includes:

[0020] In the first charging stage, constant current charging is performed with a first set current;

[0021] In the second charging stage, constant current charging is performed at the first set current until the maximum voltage of the single battery in the battery pack reaches the first set voltage, and constant current charging is performed at the second set current;

[0022] In the third charging stage, constant current charging is performed at the second set current until the maximum voltage of the single battery in the battery pack reaches the second set voltage, constant current charging is performed at the third set current, and charging is stopped when the maximum voltage of the single battery in the battery pack reaches the third set voltage;

[0023] The first set current>the second set current>the third set current; the first set voltage<the second set voltage<the third set voltage.

[0024] Preferably, processing the experimental data of each group of battery packs to obtain multiple charging data sets includes:

[0025] Preprocessing all battery pack experimental data to obtain multiple groups of battery pack data;

[0026] The multiple sets of battery pack data are screened to obtain multiple charging data sets.

[0027] Preferably, all battery pack experimental data are preprocessed to obtain multiple battery pack data sets as follows:

[0028] Each single cell test data set in each set of battery pack test data is judged according to the abnormal judgment condition to obtain an abnormal judgment result, and multiple sets of battery pack data are obtained according to the abnormal judgment result; the abnormal judgment result includes normal battery pack test data and abnormal battery pack test data.

[0029] Preferably, the abnormality judgment condition is: the difference between the current value of a single battery at a certain moment in a certain group of battery pack experimental data and the constant current value of the corresponding charging stage is greater than a set current threshold.

[0030] Preferably, obtaining multiple sets of battery data according to the abnormality judgment result includes:

[0031] When the abnormality judgment result is that a certain set of battery pack test data is normal battery pack test data, the normal battery pack test data is maintained;

[0032] When the abnormality judgment result is that a certain group of battery pack test data is abnormal battery pack test data, the abnormal battery pack test data is processed to obtain updated battery pack test data;

[0033] The normal battery pack test data and the updated battery pack test data are formed into multiple groups of battery pack data according to a time sequence relationship.

[0034] Preferably, when the abnormality judgment result is that certain battery pack test data is abnormal battery pack data, processing the abnormal battery pack test data to obtain updated battery pack test data includes:

[0035] Counting the abnormal data in each single cell experimental data set in the abnormal battery pack experimental data to obtain the number of abnormalities in the corresponding single cell experimental data set;

[0036] Determining an abnormality handling method for the abnormal battery pack test data according to the number of abnormalities in each single battery test data set in the abnormal battery pack test data;

[0037] The abnormal battery pack test data is processed according to the abnormal processing method of the abnormal battery pack test data to obtain updated battery pack test data.

[0038] Preferably, obtaining the average slope of each charging data set according to all charging data sets includes:

[0039] Determine the charging end current drop phase for each charging data set;

[0040] Calculate the cell slope of each cell in the current reduction phase at the end of charging for each charging data set;

[0041] Determine an outlier single cell according to the single cell slopes of all single cells in the current reduction phase of all charging terminals, and obtain each charging terminal current reduction data set based on the outlier single cell;

[0042] The average slope of the corresponding charging data set is obtained according to the single cell slopes of all single cells in the charging terminal current reduction data set.

[0043] To achieve the above-mentioned purpose and other related purposes, the present invention also provides a battery capacity estimation device based on charging terminal current reduction data, the device including a processor and a memory, the memory storing a computer program that can be run on the processor, and the computer program, when executed by the processor, implements the steps of the above-mentioned battery capacity estimation method based on charging terminal current reduction data.

[0044] As described above, the battery capacity estimation method and device based on charging terminal current reduction data of the present invention have the following beneficial effects:

[0045] The present invention provides a battery capacity estimation method and device based on terminal charging current reduction data. By calculating the average slope of all single cells in each charging data set in the terminal charging current reduction stage, the relationship between the average slope and capacity of all single cells in the battery pack is established, thereby estimating the capacity of the same type of battery pack at different stages, saving a lot of manpower and material resources and having high accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 Shown is a flow chart of a battery capacity estimation method based on charging terminal current reduction data according to the present invention.

[0047] Figure 2 Shown is a schematic diagram of each full charging process and its charging end current reduction stage in an embodiment of the present invention.

[0048] Figure 3 Shown is a schematic diagram of the single cell slope distribution of all single cells at all charging terminals in an embodiment of the present invention.

[0049] Figure 4 Shown is a structural schematic diagram of a battery capacity estimation device based on charging terminal current reduction data according to the present invention. DETAILED DESCRIPTION

[0050] The following describes the embodiments of the present invention through specific examples. Those skilled in the art will readily understand the other advantages and benefits of the present invention from the disclosure herein. The present invention may also be implemented or applied through various other specific embodiments, and the details in this specification may be modified or altered based on different viewpoints and applications without departing from the spirit of the present invention.

[0051] See also Figure 1-4 It should be noted that the diagrams provided in this embodiment are merely schematic illustrations of the basic concept of the present invention. Therefore, the diagrams only show components related to the present invention and are not drawn according to the number, shape, and size of components in actual implementation. In actual implementation, the type, quantity, and proportion of each component may be changed arbitrarily, and the component layout may also be more complex.

[0052] Method Example:

[0053] The flow chart of the battery capacity estimation method based on charging terminal current reduction data is as follows: Figure 1 As shown, the following combination Figure 1 The steps of the battery capacity estimation method based on charging terminal current reduction data of the present invention are described in detail. The estimation method includes:

[0054] S1, cycle decay of each type of battery pack to obtain multiple sets of battery pack experimental data;

[0055] In the present invention, the battery packs may be of different types, and there may be one or more battery packs of each type. In the embodiment of the present invention, description is made by taking one battery pack of each type as an example.

[0056] The process of performing cycle decay on a battery pack to obtain multiple sets of battery pack experimental data includes at least:

[0057] Based on the initial capacity of the battery pack, the battery pack is sequentially fully discharged and fully charged to decay the battery pack capacity to an intermediate capacity; wherein the intermediate capacity is the maximum capacity of the battery pack after being fully discharged and then fully charged in the current cycle during each cycle decay process;

[0058] A set of battery pack experimental data is obtained based on a full charge process;

[0059] Cycle multiple full discharge and full charge processes until the battery pack capacity decays to the battery pack discharge cut-off capacity;

[0060] After the cycle decay, multiple sets of battery pack experimental data are obtained. Each set of battery pack experimental data includes a single cell experimental data set of each single cell at each time.

[0061] The battery pack discharge cut-off capacity is a set ratio of the initial capacity, and the value of the set ratio is based on the end point of the battery's service life.

[0062] Each full charge process includes:

[0063] In the first charging stage, constant current charging is performed with a first set current;

[0064] In the second charging stage, constant current charging is performed at the first set current until the maximum voltage of the single battery in the battery pack reaches the first set voltage, and constant current charging is performed at the second set current;

[0065] In the third charging stage, constant current charging is performed at the second set current until the maximum voltage of the single battery in the battery pack reaches the second set voltage, constant current charging is performed at the third set current, and charging is stopped when the maximum voltage of the single battery in the battery pack reaches the third set voltage;

[0066] The first set current>the second set current>the third set current; the first set voltage<the second set voltage<the third set voltage.

[0067] The voltage, current, temperature, and battery pack capacity of each single cell at each moment during each full-charge process are obtained. Therefore, the battery pack test data of the present invention is the battery-related data corresponding to the full-charge process. Therefore, the battery pack test data is the voltage, current, temperature, and battery pack capacity of each single cell at each moment during the full-charge process. In this embodiment of the present invention, M sets of battery pack test data are obtained; each set of battery pack test data is a single cell test data set for each single cell in the battery pack at each moment.

[0068] In an embodiment of the present invention, a 280Ah iron phosphate battery pack is subjected to a cycle aging test. The battery pack has 36 single cells connected in series. At a standard ambient temperature of 25° C., the cycle decays to 80% of the initial capacity.

[0069] Specifically, the initial capacity C0 of the iron phosphate battery pack is 280Ah. After the first full discharge treatment, the capacity of the battery pack decays to the first intermediate capacity C1. Then, after the battery pack with the first intermediate capacity C1 is fully charged for the first time, the capacity of the battery pack decays to the second intermediate capacity C2 after the second full discharge treatment. And so on. After 1001 cycles of attenuation, the battery pack capacity decays to the battery pack discharge cut-off capacity, and the battery pack that has been fully discharged for the 1001th time is fully charged, so that it has the 1001th full charge treatment, so as to obtain 1001 sets of battery pack experimental data.

[0070] The full charge process of the iron phosphate battery pack in each cycle is as follows:

[0071] The first charging stage is a constant current charging with a current of 280A;

[0072] The second charging stage is when the charging current of the first stage is constant current charged until the maximum voltage of the single battery in the battery pack reaches 3.51V, and then constant current charging is performed at a current of 92.4A;

[0073] The third charging stage is when the charging current of the second stage is used for constant current charging until the maximum voltage of the single cell in the battery pack reaches 3.6V, and then constant current charging is performed at a current of 28A until the maximum voltage of the single cell reaches 3.65V and then charging is stopped.

[0074] S2, processing the experimental data of each group of battery packs to obtain multiple charging data sets;

[0075] The present invention processes each set of battery pack experimental data obtained after conducting an experiment on the battery pack to obtain an effective charging data set for estimating the capacity of the battery pack.

[0076] S21, preprocessing all battery pack experimental data to obtain multiple groups of battery pack data;

[0077] This step aims to eliminate and correct abnormal data caused by power outages, equipment maintenance, data collection, etc. in the three stages of full charging processing.

[0078] Each single cell test data set in each set of battery pack test data is judged according to the abnormal judgment condition to obtain an abnormal judgment result, and multiple sets of battery pack data are obtained according to the abnormal judgment result; the abnormal judgment result includes normal battery pack test data and abnormal battery pack test data.

[0079] The abnormality judgment condition is: the difference between the current value of a single battery at a certain moment in the experimental data of a certain battery pack and the constant current value of the corresponding charging stage is greater than the set current threshold.

[0080] The abnormal judgment results obtained by judging each single cell experimental data set in each group of battery pack experimental data according to the abnormal judgment conditions include:

[0081] If the difference between the current value of a single cell at a certain moment in a certain single cell test data set in a certain group of battery pack test data and the constant current value of the corresponding charging stage is greater than the set current threshold, then the battery pack test data of this group is judged to be abnormal battery pack test data;

[0082] Otherwise, the group of battery pack test data is judged to be normal battery pack test data, that is, if the difference between the current value of all single cells in all single cell test data sets at all times in a group of battery pack test data and the constant current value of the corresponding charging stage is less than the set current threshold, then the group of battery pack test data is judged to be normal battery pack test data.

[0083] In an embodiment of the present invention, if the difference between the current value of a single cell in a group of battery pack experimental data at a certain moment and the constant current value of the corresponding charging stage is greater than 5A, it means that the single cell experimental data of the single cell at that moment is abnormal, that is, at least one single cell experimental data set in the group of battery pack experimental data has abnormal data, and the group of battery pack experimental data corresponding to the single cell at that moment is judged to be abnormal battery pack experimental data.

[0084] Based on the abnormality judgment results, multiple sets of battery data are obtained, including:

[0085] When the abnormality judgment result is that a certain set of battery pack test data is normal battery pack test data, the normal battery pack test data is maintained;

[0086] When the abnormality judgment result is that a certain group of battery pack test data is abnormal battery pack test data, the abnormal battery pack test data is processed to obtain updated battery pack test data;

[0087] The normal battery pack test data and the updated battery pack test data are formed into multiple groups of battery pack data according to a time sequence relationship.

[0088] The present invention processes multiple groups of battery pack experimental data differently according to the abnormality judgment results, and forms multiple new groups of battery pack data according to the time sequence relationship. This can effectively avoid the interference of abnormal data on the battery pack experimental data, thereby improving the accuracy of subsequent battery capacity estimation.

[0089] In the present invention, when the abnormality judgment result is that certain battery pack test data is abnormal battery pack data, processing the abnormal battery pack test data to obtain updated battery pack test data includes:

[0090] Counting the abnormal data in each single cell experimental data set in the abnormal battery pack experimental data to obtain the number of abnormalities in the corresponding single cell experimental data set;

[0091] In an embodiment of the present invention, if the i-th group of battery pack test data is abnormal battery pack test data, and the j-th single cell test data in the abnormal battery pack test data has 15 moments of single cell test data judged as abnormal data, then the number of abnormalities in the abnormal battery pack test data is 15.

[0092] If the i+1th battery pack test data is abnormal battery pack test data, and the j+1th single cell in the abnormal battery pack test data has 8 moments of single cell test data judged as abnormal data, then the number of abnormalities in the abnormal battery pack test data is 8.

[0093] Determining an abnormality handling method for the abnormal battery pack test data according to the number of abnormalities in each single battery test data set in the abnormal battery pack test data;

[0094] The abnormality handling method of the present invention includes replacing and discarding abnormal data in the abnormal battery pack test data by interpolation, so that the number of battery pack data obtained is less than or equal to the number of battery pack test data.

[0095] When the number of abnormalities in a single battery test data set in the abnormal battery pack test data is greater than a set value, the abnormal processing method of the abnormal battery pack test data is to discard the abnormal battery pack test data;

[0096] When the number of abnormalities in any single cell test data set in the abnormal battery pack test data is less than a set value, the abnormality processing method of the abnormal battery pack test data is to replace the abnormal data in the abnormal battery pack test data by interpolation.

[0097] The abnormal battery pack test data is processed according to the abnormal processing method of the abnormal battery pack test data to obtain updated battery pack test data.

[0098] Specifically, for each abnormal data in the abnormal battery pack experimental data, fitting is performed by using a certain number of single cell experimental data on both sides of the abnormal data in the single cell data set where the abnormal data is located. The fitting value at the corresponding moment of the abnormal data point is obtained according to the fitting result, and the fitting value is used to replace the abnormal value, thereby realizing the replacement of the abnormal data in the abnormal battery experimental data.

[0099] Since each group of battery pack laboratory data is a single cell experimental data set of each single cell in the battery pack at each moment, the battery pack data obtained by preprocessing each group of battery pack experimental data is normal battery pack experimental data and abnormal battery pack experimental data, that is, the single cell data set of each single cell at each moment.

[0100] In an embodiment of the present invention, a cycle aging test is performed on a 280Ah iron phosphate battery pack. The battery pack has 36 single cells connected in series. At a standard ambient temperature of 25°C, 1001 sets of battery pack experimental data are obtained during the process of cycle decay to 80% of the initial capacity. There are a total of 5 sets of abnormal battery pack experimental data, among which 4 sets of abnormal battery pack experimental data use interpolation to replace the abnormal data in the abnormal battery pack experimental data, and 1 set of abnormal battery pack experimental data is discarded, that is, a set of battery pack experimental data corresponding to one cycle should be discarded among the 5 sets of abnormal battery pack experimental data. Therefore, this embodiment preprocesses the 1001 sets of battery pack experimental data to obtain 1000 sets of battery pack data.

[0101] S22, screening the multiple groups of battery pack data to obtain multiple charging data sets.

[0102] In order to improve the processing efficiency of battery pack data, a part of the battery pack data is screened out from multiple groups of battery pack data as a charging data set. The selected group of battery pack data is a charging data set; however, if the selection is inappropriate, it will also cause errors in cycle and battery capacity estimation. Therefore, it is necessary to ensure that the number of charging data sets is sufficient to construct the relationship between the average slope corresponding to the number of subsequent battery pack cycles and the intermediate capacity corresponding to the number of cycles.

[0103] The screening principle of the present invention is to select a group of battery pack data every set cycle, thereby obtaining multiple charging data sets; each charging data set includes a single battery data set of each single battery at each moment.

[0104] In an embodiment of the present invention, the set cycle can be 50 or 100; specifically, the battery pack data corresponding to the same order in the set cycle can be used as a charging data set. For example, when a group of battery pack data is selected every 50 cycles, 20 charging data sets are obtained, and specifically the 1st group of battery pack data, the 51st group of battery pack data, ..., the 951st group of battery pack data are respectively used as a charging data set; when a group of battery pack data is selected every 100 cycles, 10 charging data sets are obtained, and specifically the 100th group of battery pack data, the 200th group of battery pack data, ..., the 1000th group of battery pack data are respectively used as a charging data set.

[0105] S3, processing all charging data sets to obtain the average slope of each charging data set;

[0106] This step aims to process all charging data sets to obtain the average slope of each charging data set, that is, the average slope of all single cells in each charging data set.

[0107] S31, determining the charging end current reduction stage of each charging data set;

[0108] The present invention determines the charging terminal current reduction stage of the charging data set according to the single cell voltage in the charging data set.

[0109] The current reduction stage at the end of charging is from the start time to the end time; among them, the start time is the time when the maximum voltage of the single cell in the battery pack reaches the first set voltage by constant current charging with the first set current; when the voltage difference of any single cell at adjacent moments in the third charging stage is the smallest, any moment in the adjacent moments is the end time.

[0110] It should be noted that for the same charging data set, the current reduction phase at the end of charging for all single cells is the same.

[0111] In the embodiment of the present invention, Figure 2 As shown, point 1 represents the starting time and point 2 represents the ending time.

[0112] S32, calculating the cell slope of each cell in the current reduction phase at the end of charging in each charging data set;

[0113]

[0114] Among them, K ij is the cell slope of the jth cell in the i-th charging data set; V2 is the voltage of the jth cell in the i-th charging data set at the termination time; V1 is the voltage of the jth cell in the i-th charging data set at the starting time; T2 is the termination time, and T1 is the starting time.

[0115] In the embodiment of the present invention, each charging data set includes 36 single-cell batteries. Therefore, each of the 20 charging data sets includes 36 single-cell slopes.

[0116] S33, determining an outlier single cell according to the single cell slopes of all single cells in the current reduction phase of all charging terminals, and obtaining each charging terminal current reduction data set based on the outlier single cell;

[0117] Based on the single cell slopes of all single cells in the current reduction stage of all charging terminals, an overall distribution diagram of the single cell slopes of each identical single cell in all charging terminals is obtained; theoretically, on the overall distribution diagram, the single cell slope change trend of all single cells should be the same, but when it is found from the overall distribution diagram that the single cell slope change trend of one or a few certain single cells is different from the overall single cell slope change, these one or a few certain single cells are defined as discrete single cells, and the single cells and their single cell slopes after the discrete single cells are deleted are used as the current reduction data sets of each charging terminal. The number of charging terminal current reduction data sets is the same as the number of charging data sets, but the number of single cells in the charging terminal current reduction data set is less than or equal to the number of single cells in the charging data set.

[0118] In the embodiment of the present invention, Figure 3 As shown, there are 3 outlier cells, and there are 33 remaining cells in each charging end current drop data set. Therefore, there are cell slopes corresponding to 33 cells in each charging end current drop data set.

[0119] S34 , obtaining an average slope of the corresponding charging data set according to the single cell slopes of all single cells in each charging terminal current reduction data set.

[0120] the average slope of each charging data set;

[0121]

[0122] in, is the average slope of the i-th charging terminal current reduction data set; h is the number of outlier cells; Nh is the number of cells in the charging terminal current reduction data set; the i-th charging terminal current reduction data set corresponds to the i-th charging data set.

[0123] In the embodiment of the present invention, there are 20 charging data sets, so this step obtains 20 average slopes.

[0124] S4, obtaining a mathematical model between the average slope of the charging data set and the corresponding intermediate capacity according to the average slope of each charging data set and the intermediate capacity of the corresponding cycle decay;

[0125] Specifically, the relationship between the average slope of the charging data set corresponding to the number of battery pack cycles and the intermediate capacity corresponding to the number of cycles is obtained according to the average slope of each charging data set and the intermediate capacity corresponding to the cycle decay;

[0126] In an embodiment of the present invention, if the first charging data set is generated after the battery decays to the first intermediate capacity for the first time, the second charging data set is generated after the battery decays to the 51st intermediate capacity for the 51st time, and so on, then a relationship between the average slope of the battery data set and the corresponding intermediate capacity is established based on the average slope of the first charging data set and the first intermediate capacity, the average slope of the second charging data set and the 51st intermediate capacity, and so on. Then, fitting and interpolation are performed based on all battery data sets and the corresponding intermediate capacities to obtain the relationship between the average slope of the battery data set and the corresponding intermediate capacity. In the present invention, the relationship between the average slope of the battery data set and the corresponding intermediate capacity is specifically a linear relationship.

[0127] Through the above steps of the present invention, the relationship between the average slope of the battery data set and the corresponding intermediate capacity of various types of battery packs can be established.

[0128] S5, obtaining battery pack data corresponding to the set number of times the battery pack to be tested is cycle-attenuated, processing the battery pack data corresponding to the set number of times to obtain the average slope of the corresponding charging data set, and estimating the capacity of the battery to be tested based on the average slope of the charging data set corresponding to the set number of cycles and the relationship between the average slope of the charging data set and the corresponding intermediate capacity.

[0129] Specifically, multiple sets of battery pack data are obtained after the battery pack under test has decayed at a set number of cycles. The battery pack data under test is analyzed using steps S1 to S3 to obtain the average slope of the charging data set corresponding to the set number of cycle decays. The capacity of the battery pack under test is estimated based on the average slope of the charging data set corresponding to the set number of cycle decays and the relationship between the average slope of the charging data set and the corresponding intermediate capacity. In this way, the battery pack data of the battery under test using the method of S1 to S3 is effectively improved in terms of the accuracy of the battery data and the accuracy of the battery capacity estimation.

[0130] More specifically, when the average slope Kr of a set of charging data sets corresponding to a certain cycle decay is obtained, the corresponding intermediate capacity is obtained as Cr based on the relationship between the average slope of the battery data set and the corresponding intermediate capacity. If the intermediate capacity corresponding to this cycle decay is a set ratio of the initial capacity of the battery pack as S%, then the initial capacity of the battery pack to be tested can be obtained as Cr / S%. Therefore, the present invention can not only estimate the initial capacity of the battery to be tested, but also estimate the intermediate capacity after each cycle of full discharge, that is, the battery capacity after the current full discharge.

[0131] Device Example:

[0132] The present invention also provides a battery capacity estimation device based on charging terminal current reduction data. Figure 4 As shown, the device includes a processor and a memory, wherein the memory stores a computer program that can be run on the processor, and when the computer program is executed by the processor, the steps of the above-mentioned method for predicting branch current balancing in the battery system are implemented.

[0133] Since the principles and steps of the method for predicting branch current balancing in a battery system have been described in detail in the method embodiment, they will not be repeated in this embodiment.

[0134] In summary, the present invention calculates the average slope of all cells in each charging data set during the terminal current reduction phase, establishing a relationship between the average slope and capacity of all cells in the battery pack. This allows for estimation of the capacity of the same type of battery pack at different stages, saving significant manpower and resources while achieving high accuracy. Therefore, the present invention effectively overcomes the shortcomings of existing technologies and possesses high industrial value.

[0135] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the present invention. Anyone skilled in the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by one of ordinary skill in the art without departing from the spirit and technical principles disclosed herein are intended to be covered by the claims of the present invention.

Claims

1. A battery capacity estimation method based on charging terminal current reduction data, characterized in that: The method comprises at least the following steps: Perform cycle decay on each type of battery pack to obtain multiple sets of battery pack experimental data; Processing the experimental data of each battery pack to obtain multiple charging data sets; All charging data sets are processed to obtain the average slope of each charging data set; The relationship between the average slope of the charging data set and the corresponding intermediate capacity is obtained according to the average slope of each charging data set and the intermediate capacity of the corresponding cycle decay; Obtaining battery pack data corresponding to a set number of cycles of decay after the battery pack under test has decayed for a set number of times, processing the battery pack data corresponding to the set number of times to obtain an average slope of a corresponding charging data set, and estimating the capacity of the battery under test based on the average slope of the charging data set corresponding to the set number of cycles of decay and the relationship between the average slope of the charging data set and the corresponding intermediate capacity; The process of performing cycle decay on a battery pack to obtain multiple sets of battery pack experimental data includes at least: Based on the initial capacity of the battery pack, the battery pack is fully discharged and fully charged in sequence to reduce the capacity of the battery pack to an intermediate capacity; A set of battery pack experimental data is obtained based on a full charge process; Repeating multiple cycles of full discharge and full charge until the battery pack capacity decays to a battery pack discharge cut-off capacity; the battery pack discharge cut-off capacity is a set ratio of the initial capacity of the battery pack, and the value of the set ratio is based on the end point of the battery life; After cycle decay, multiple groups of battery pack experimental data are obtained; each group of battery pack experimental data includes a single cell experimental data set of each single cell at each time.

2. The battery capacity estimation method based on charging terminal current reduction data according to claim 1 is characterized in that: The battery pack experimental data are the voltage, current, temperature and battery pack capacity of each single cell at each moment during the full charging process.

3. The battery capacity estimation method based on charging terminal current reduction data according to claim 2 is characterized in that: Each full charge process includes: In the first charging stage, constant current charging is performed with a first set current; In the second charging stage, constant current charging is performed at the first set current until the maximum voltage of the single battery in the battery pack reaches the first set voltage, and constant current charging is performed at the second set current; In the third charging stage, constant current charging is performed at the second set current until the maximum voltage of the single battery in the battery pack reaches the second set voltage, constant current charging is performed at the third set current, and charging is stopped when the maximum voltage of the single battery in the battery pack reaches the third set voltage; The first set current>the second set current>the third set current; the first set voltage<the second set voltage<the third set voltage.

4. The battery capacity estimation method based on charging terminal current reduction data according to claim 1, characterized in that: The experimental data of each battery pack is processed to obtain multiple charging data sets including: Preprocessing all battery pack experimental data to obtain multiple groups of battery pack data; The multiple sets of battery pack data are screened to obtain multiple charging data sets.

5. The battery capacity estimation method based on charging terminal current reduction data according to claim 4 is characterized in that: Preprocessing of all battery pack experimental data to obtain multiple groups of battery pack data is as follows: Each single cell test data set in each set of battery pack test data is judged according to the abnormal judgment condition to obtain an abnormal judgment result, and multiple sets of battery pack data are obtained according to the abnormal judgment result; the abnormal judgment result includes normal battery pack test data and abnormal battery pack test data.

6. The battery capacity estimation method based on charging terminal current reduction data according to claim 5 is characterized in that: The abnormality judgment condition is: the difference between the current value of a single battery at a certain moment in the experimental data of a certain battery pack and the constant current value of the corresponding charging stage is greater than the set current threshold.

7. The battery capacity estimation method based on charging terminal current reduction data according to claim 5, characterized in that: Based on the abnormality judgment results, multiple sets of battery data are obtained, including: When the abnormality judgment result is that a certain set of battery pack test data is normal battery pack test data, the normal battery pack test data is maintained; When the abnormality judgment result is that a certain group of battery pack test data is abnormal battery pack test data, the abnormal battery pack test data is processed to obtain updated battery pack test data; The normal battery pack test data and the updated battery pack test data are formed into multiple groups of battery pack data according to a time sequence relationship.

8. The battery capacity estimation method based on charging terminal current reduction data according to claim 7, characterized in that: When the abnormality judgment result is that certain battery pack test data is abnormal battery pack data, processing the abnormal battery pack test data to obtain updated battery pack test data includes: Counting the abnormal data in each single cell experimental data set in the abnormal battery pack experimental data to obtain the number of abnormalities in the corresponding single cell experimental data set; Determining an abnormality handling method for the abnormal battery pack test data according to the number of abnormalities in each single battery test data set in the abnormal battery pack test data; The abnormal battery pack test data is processed according to the abnormal processing method of the abnormal battery pack test data to obtain updated battery pack test data.

9. The battery capacity estimation method based on charging terminal current reduction data according to claim 8, characterized in that: The average slope of each charging data set obtained based on all charging data sets includes: Determine the charging end current drop phase for each charging data set; Calculate the cell slope of each cell in the current reduction phase at the end of charging for each charging data set; Determine an outlier single cell according to the single cell slopes of all single cells in the current reduction phase of all charging terminals, and obtain each charging terminal current reduction data set based on the outlier single cell; The average slope of the corresponding charging data set is obtained according to the single cell slopes of all single cells in each charging terminal current reduction data set.

10. A battery capacity estimation device based on charging terminal current reduction data, characterized in that: The device includes a processor and a memory, wherein the memory stores a computer program that can be run on the processor, and when the computer program is executed by the processor, the steps of the battery capacity estimation method based on charging terminal current reduction data according to any one of claims 1 to 9 are implemented.

Images