A battery type determination system and method based on weightlessness curve modeling

Abstract

This application discloses a battery type determination system and method based on weight loss curve modeling, relating to the field of battery type determination technology. The system includes a first acquisition module for acquiring real-time weight values ​​of the battery under test at fixed intervals 'a'; a curve fitting module for constructing a weight loss fitting curve for the battery under test using a fitting method; a second acquisition module for determining the liquid substance determination value of the battery under test based on weight loss characteristic values; a judgment module for determining whether to compensate the liquid substance determination value based on test confidence level; a compensation module for determining the compensation coefficient of the liquid substance determination value and obtaining the compensated liquid substance determination value; and a battery type determination module for determining the battery type of the battery under test. This application effectively overcomes the drawbacks of existing methods that rely on simplified processing based on the difference between initial and final mass.

Description

Technical Field

[0001] This application relates to the field of battery type determination technology, and in particular to a battery type determination system and method based on weight loss curve modeling. Background Technology

[0002] The widely used weight loss method has significant limitations. This method calculates the weight loss rate simply by measuring the difference between the initial and final mass, completely ignoring the rich information contained in the dynamic weight loss curve recorded during the test. This simplistic approach, relying solely on the difference between the initial and final mass, results in overly coarse test results that fail to accurately reflect the dynamic changes in the electrolyte release process, let alone reveal the kinetic mechanisms and intrinsic laws governing electrolyte release. Due to the lack of in-depth analysis and utilization of the weight loss curve, existing methods cannot capture the detailed characteristics of the electrolyte release rate changing over time, resulting in a superficial understanding of electrolyte release behavior and severely hindering a deeper understanding and precise control of the electrolyte release process.

[0003] Therefore, it is necessary to design a battery type determination system and method based on weightlessness curve modeling to solve the problems existing in the current technology. Summary of the Invention

[0004] The purpose of this application is to provide a battery type determination system and method based on weight loss curve modeling, which can solve the problem that existing methods cannot capture the detailed characteristics of electrolyte release rate changes over time, resulting in the understanding of electrolyte release behavior remaining at a superficial level, which seriously restricts the in-depth understanding and precise control of the electrolyte release process.

[0005] To achieve the above objectives, this application provides the following solution:

[0006] In a first aspect, this application provides a battery type determination system based on weightlessness curve modeling, comprising:

[0007] The first acquisition module is used to identify the battery to be tested, perform a weight loss rate test on the battery to be tested, and acquire the real-time weight value of the battery to be tested at fixed intervals a.

[0008] The curve fitting module is used to construct the weight loss fitting curve of the battery under test based on the fixed interval a and the real-time weight value, and by using a fitting method.

[0009] The second acquisition module is used to extract features from the weight loss fitting curve, obtain the weight loss feature value of the battery under test, and determine the liquid substance determination value of the battery under test based on the weight loss feature value.

[0010] The judgment module is used to collect the historical liquid substance judgment value corresponding to each historical test battery, determine the test confidence level of the historical test battery based on the historical liquid substance judgment value, and determine whether to compensate the liquid substance judgment value based on the test confidence level.

[0011] The compensation module is used to collect the initial weight loss characteristic parameters of the battery under test when it is determined that the liquid substance determination value should be compensated, and to determine the compensation coefficient of the liquid substance determination value based on the test confidence level and the initial weight loss characteristic parameters, and to obtain the compensated liquid substance determination value.

[0012] The battery type determination module is used to determine the battery type of the battery to be tested based on the compensation liquid substance determination value.

[0013] Optionally, when constructing the weight loss fitting curve of the battery under test based on the fixed interval 'a' and the real-time weight value using a fitting method, the specific steps include:

[0014] The real-time weight value is preprocessed, including data alignment and noise filtering at the fixed interval a, to obtain the preprocessed weight value.

[0015] The preprocessed weight value and the corresponding fixed interval 'a' are used as inputs, and the initial weightlessness fitting curve is constructed using the fitting method described above; wherein, the fitting method includes exponential decay fitting or piecewise linear regression.

[0016] Obtain the initial weight loss value of the battery under test, and determine the preliminary estimation parameters of the initial weight loss fitting curve;

[0017] The initial weightlessness fitting curve is optimized and fitted based on the initial weightlessness value and preliminary estimated parameters to obtain the weightlessness fitting curve.

[0018] Optionally, determining the liquid substance determination value of the battery under test based on the weight loss characteristic value specifically includes:

[0019] The weightlessness characteristic values ​​are analyzed to obtain the weightlessness rate and plateau weight of the weightlessness fitting curve;

[0020] The basic liquid substance determination value of the battery under test is determined based on the initial weight loss value and the plateau weight.

[0021] The optimization coefficient for the determination value of the basic liquid substance is determined based on the weight loss rate;

[0022] The basic liquid substance determination value is optimized based on the optimization coefficient to obtain the liquid substance determination value.

[0023] Optionally, determining the optimization coefficient for the basic liquid substance determination value based on the weight loss rate specifically includes:

[0024] The weight loss rate is compared with the first weight loss rate and the second weight loss rate, and the optimization coefficient of the basic liquid substance determination value is determined based on the comparison result; wherein, the first weight loss rate is less than the second weight loss rate;

[0025] When the weightlessness rate is less than or equal to the first weightlessness rate, the optimization coefficient is determined to be the first optimization coefficient;

[0026] When the weightlessness rate is greater than the first weightlessness rate and less than or equal to the second weightlessness rate, the optimization coefficient is determined to be the second optimization coefficient.

[0027] When the weightlessness rate is greater than the second weightlessness rate, the optimization coefficient is determined to be the third optimization coefficient.

[0028] Optionally, when determining the test confidence level of the historical test battery based on the historical liquid substance determination value, the specific steps include:

[0029] Obtain the actual liquid substance value corresponding to each of the historical test batteries;

[0030] Obtain the deviation index between the historical liquid substance determination value and the actual liquid substance value;

[0031] The deviation index is compared with a preset test confidence mapping table, and the test confidence level corresponding to each historical test battery is determined based on the comparison result.

[0032] Optionally, determining whether to compensate the liquid substance determination value based on the test confidence level specifically includes:

[0033] Statistical analysis was performed on all the test confidence scores to calculate the average test confidence score;

[0034] Set a confidence threshold;

[0035] The average test confidence level is compared with the confidence threshold, and the comparison result is used to determine whether to compensate the liquid substance judgment value.

[0036] If the average test confidence level is greater than or equal to the confidence level threshold, it is determined that no compensation will be made for the liquid substance determination value.

[0037] Otherwise, the determination value of the liquid substance is to be compensated.

[0038] Optionally, a compensation coefficient for the liquid substance determination value is determined based on the test confidence level and the initial weightlessness characteristic parameters, and a compensated liquid substance determination value is obtained, specifically including:

[0039] The initial weight loss characteristic parameters are analyzed to obtain the initial weight loss percentage of the battery under test;

[0040] The difference between the average test confidence level and the confidence level threshold is obtained and denoted as the confidence level difference.

[0041] A compensation vector set is constructed based on the initial percentage of weightlessness and the confidence difference;

[0042] The compensation vector group is compared with the historical compensation group, and the compensation coefficient of the liquid substance determination value is determined based on the comparison result.

[0043] When there is a historical compensation vector group in the historical compensation group that is the same as the compensation vector group, the historical compensation coefficient corresponding to the historical compensation vector group is used as the compensation coefficient.

[0044] When there is no historical compensation vector group in the historical compensation group that is the same as the compensation vector group, the compensation coefficient is determined according to the compensation vector group.

[0045] The liquid substance determination value is compensated according to the compensation coefficient, and the compensated liquid substance determination value is obtained.

[0046] Optionally, determining the compensation coefficients based on the compensation vector set specifically includes:

[0047] The matching degree between each compensation vector group and each historical compensation vector group is obtained one by one;

[0048] Get the maximum matching degree;

[0049] If the historical compensation vector group corresponding to the maximum matching degree is unique, then the historical compensation coefficient corresponding to the historical compensation vector group shall be used as the compensation coefficient.

[0050] If the historical compensation vector group corresponding to the maximum matching degree is not unique, then the historical compensation coefficient corresponding to each maximum matching degree is obtained, and the average value of all the historical compensation coefficients is calculated and denoted as the historical average compensation coefficient. The historical average compensation coefficient is then used as the compensation coefficient.

[0051] Optionally, determining the battery type of the battery under test based on the compensated liquid substance determination value specifically includes:

[0052] The determination value of the compensating liquid substance is compared with the first determination value of the compensating liquid substance and the second determination value of the compensating liquid substance, and the battery type of the battery to be tested is determined according to the comparison result; wherein, the first determination value of the compensating liquid substance is less than the second determination value of the compensating liquid substance.

[0053] When the determination value of the compensation liquid substance is less than or equal to the determination value of the first compensation liquid substance, the battery type of the battery to be tested is determined to be a solid-state battery.

[0054] When the determination value of the compensation liquid substance is greater than the first determination value of the compensation liquid substance and less than or equal to the second determination value of the compensation liquid substance, the battery type of the battery to be tested is determined to be a hybrid solid-liquid battery.

[0055] When the compensation liquid substance determination value is greater than the second compensation liquid substance determination value, the battery type of the battery to be tested is determined to be a liquid battery.

[0056] Secondly, this application provides a battery type determination method based on weightlessness curve modeling, specifically including the following steps:

[0057] Identify the battery to be tested, perform a weight loss rate test on the battery to be tested, and collect the real-time weight value of the battery to be tested at fixed intervals a;

[0058] Based on the fixed interval 'a' and the real-time weight value, a weight loss fitting curve for the battery under test is constructed using a fitting method.

[0059] Feature extraction is performed on the weight loss fitting curve to obtain the weight loss feature value of the battery under test, and the liquid substance determination value of the battery under test is determined based on the weight loss feature value.

[0060] Collect the historical liquid substance determination value corresponding to each historical test battery, determine the test confidence level of the historical test battery based on the historical liquid substance determination value, and determine whether to compensate the liquid substance determination value based on the test confidence level.

[0061] When it is determined that the liquid substance determination value needs to be compensated, the initial weight loss characteristic parameters of the battery under test are collected, and the compensation coefficient of the liquid substance determination value is determined based on the test confidence level and the initial weight loss characteristic parameters, and the compensated liquid substance determination value is obtained.

[0062] The battery type of the battery to be tested is determined based on the compensation liquid substance determination value.

[0063] According to the specific embodiments provided in this application, this application has the following technical effects:

[0064] This application provides a battery type determination system and method based on weight loss curve modeling, which effectively overcomes the shortcomings of existing simplified methods that rely on the difference between initial and final mass. The system, through in-depth analysis of the weight loss curve, can accurately capture the detailed characteristics of electrolyte release rate changes over time, providing a deeper understanding of electrolyte release behavior. This helps to reveal the kinetic mechanism and intrinsic laws of electrolyte release, thereby achieving precise control of the electrolyte release process. In practical applications, the system and method involved in this application can improve the accuracy and reliability of battery type determination. For different types of batteries, it can more accurately determine the content and state of liquid substances, providing strong support for battery research and development, production, and quality control. During the battery research and development stage, by determining the content and state of liquid substances in the battery, the design and manufacturing process can be optimized, improving battery performance and safety. During the production process, abnormalities in the battery's liquid substances can be detected in a timely manner, ensuring the stability of product quality. Attached Figure Description

[0065] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0066] Figure 1 A schematic diagram of the functional modules of a battery type determination system based on weightlessness curve modeling provided in an embodiment of this application;

[0067] Figure 2 This is a flowchart illustrating a battery type determination method based on weightlessness curve modeling, provided as an embodiment of this application. Detailed Implementation

[0068] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0069] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0070] In one exemplary embodiment, such as Figure 1As shown, a battery type determination system based on weightlessness curve modeling is provided. The battery type determination system based on weightlessness curve modeling includes: a first acquisition module, a curve fitting module, a second acquisition module, a judgment module, a compensation module, and a battery type determination module.

[0071] The first acquisition module is used to identify the battery to be tested, perform a weight loss rate test on the battery to be tested, and acquire the real-time weight value of the battery to be tested at fixed intervals a.

[0072] The curve fitting module is used to construct the weight loss fitting curve of the battery under test based on the fixed interval a and the real-time weight value, using a fitting method.

[0073] Specifically, when constructing the weight loss fitting curve of the battery under test based on the fixed interval 'a' and the real-time weight value using a fitting method, the process includes:

[0074] The real-time weight value is preprocessed, including data alignment and noise filtering at the fixed interval a, to obtain the preprocessed weight value.

[0075] The preprocessed weight value and the corresponding fixed interval 'a' are used as inputs, and the initial weightlessness fitting curve is constructed using the fitting method described above; wherein, the fitting method includes exponential decay fitting or piecewise linear regression.

[0076] Obtain the initial weight loss value of the battery under test, and determine the preliminary estimation parameters of the initial weight loss fitting curve;

[0077] In this embodiment, the initial weight loss value refers to the initial weight value of the battery under test at the start of the weight loss rate test (i.e., when time t=0). This initial weight loss value serves as the benchmark reference data for subsequently constructing the weight loss fitting curve. By comparing and analyzing it with the real-time weight values ​​collected at each fixed interval 'a', it can accurately reflect the weight change trend of the battery under test throughout the entire test process, laying the foundation for the accuracy of subsequent curve fitting.

[0078] The initial weightlessness fitting curve is optimized and fitted based on the initial weightlessness value and preliminary estimated parameters to obtain the weightlessness fitting curve.

[0079] In this embodiment, the preliminary estimation parameters include a preliminary estimate of the plateau weight. This preliminary estimate of the plateau weight is a preliminary inference of the plateau weight based on limited early real-time weight data or empirical values ​​when constructing the initial weight loss fitting curve.

[0080] Specifically, in this embodiment, the initial weight of the battery under test is set to 50.00g. During the process of collecting real-time weight values ​​at fixed intervals 'a' (1 minute), the weight data for the first 10 minutes are: 49.80g, 49.65g, 49.55g, 49.48g, 49.44g, 49.42g, 49.41g, 49.40g, 49.40g, and 49.40g. After noise filtering and time alignment, these data points are input into the exponential decay function model:

[0081] ;

[0082] Where W(t) represents the weight of the battery at time t. This is the initial weight of the battery. To provide a preliminary estimate of the weight during the plateau period, k is the decay constant.

[0083] In this embodiment, =50.00g, preliminary estimate of plateau phase weight =49.40g, attenuation constant k=0.35. Based on the preliminary parameter estimates, least squares optimization was performed to obtain the weightlessness fitting curve:

[0084] ;

[0085] Where t represents time, this weight loss fitting curve more accurately reflects the weight change of the battery under test during the weight loss process.

[0086] The second acquisition module is used to extract features from the weight loss fitting curve, obtain the weight loss feature value of the battery under test, and determine the liquid substance determination value of the battery under test based on the weight loss feature value.

[0087] In this embodiment, the liquid substance determination value refers to the content of liquid substance inside the battery obtained from the battery weight loss rate test.

[0088] In this embodiment, determining the liquid substance determination value of the battery under test based on the weight loss characteristic value specifically includes:

[0089] The weightlessness characteristic values ​​are analyzed to obtain the weightlessness rate and plateau weight of the weightlessness fitting curve;

[0090] In this embodiment, the weightlessness characteristic value also includes the duration of the plateau period.

[0091] The basic liquid content determination value of the battery under test is determined based on the initial weight loss value and the plateau weight; the basic liquid content determination value is the difference between the initial weight loss value and the plateau weight.

[0092] The optimization coefficient for the determination value of the basic liquid substance is determined based on the weight loss rate;

[0093] The basic liquid substance determination value is optimized based on the optimization coefficient to obtain the liquid substance determination value.

[0094] Understandably, by deeply analyzing and calculating characteristic values ​​such as weight loss rate and plateau weight, a more accurate liquid substance determination value can be obtained. This determination value can more accurately reflect the actual situation of liquid substances in the battery under test, providing a reliable basis for subsequent battery type determination and related processing. The process of optimizing the basic liquid substance determination value based on optimization coefficients to obtain a final liquid substance determination value involves multiplying the optimization coefficients by the basic liquid substance determination value.

[0095] Specifically, the optimization coefficient for determining the basic liquid substance determination value based on the weight loss rate includes:

[0096] The weight loss rate is compared with the first weight loss rate and the second weight loss rate, and the optimization coefficient of the basic liquid substance determination value is determined based on the comparison result; wherein, the first weight loss rate is less than the second weight loss rate;

[0097] When the weightlessness rate is less than or equal to the first weightlessness rate, the optimization coefficient is determined to be the first optimization coefficient;

[0098] When the weightlessness rate is greater than the first weightlessness rate and less than or equal to the second weightlessness rate, the optimization coefficient is determined to be the second optimization coefficient.

[0099] When the weightlessness rate is greater than the second weightlessness rate, the optimization coefficient is determined to be the third optimization coefficient.

[0100] Understandably, the optimization coefficients are arranged in the order of first optimization coefficient < second optimization coefficient < third optimization coefficient. This setting of optimization coefficients is based on the relationship between the rate of weight loss and the content of liquid substances in the battery. When the rate of weight loss is low, it means that the release of liquid substances in the battery is relatively slow, possibly indicating low activity of the internal liquid substances or the presence of factors hindering release. In this case, a smaller optimization coefficient is applied to conservatively adjust the basic liquid substance determination value. When the rate of weight loss is in a moderate range, the release of liquid substances in the battery is in a relatively normal state, and the corresponding optimization coefficient is moderate, reasonably optimizing the basic liquid substance determination value. When the rate of weight loss is high, it indicates that the release of liquid substances in the battery is rapid, possibly indicating a higher content of liquid substances inside the battery or a more active release mechanism. Therefore, a larger optimization coefficient is applied, allowing the liquid substance determination value to more accurately reflect the actual situation of the battery. By dynamically adjusting the optimization coefficients based on the rate of weight loss, the accuracy and reliability of the liquid substance determination value are further improved, enabling the entire battery type determination system based on weight loss curve modeling to function better in practical applications.

[0101] The judgment module is used to collect the historical liquid substance judgment value corresponding to each historical test battery, determine the test confidence level of the historical test battery based on the historical liquid substance judgment value, and determine whether to compensate the liquid substance judgment value based on the test confidence level.

[0102] Specifically, determining the test confidence level of the historical test battery based on the historical liquid substance determination value includes:

[0103] Obtain the actual liquid substance value corresponding to each of the historical test batteries;

[0104] Obtain the deviation index between the historical liquid substance determination value and the actual liquid substance value;

[0105] The deviation index is compared with a preset test confidence mapping table, and the test confidence level corresponding to each historical test battery is determined based on the comparison result.

[0106] It is understandable that the actual liquid substance value refers to the accurate content of liquid substance injected into the battery during filling; it is a known and definite value. By calculating the deviation index between historical liquid substance judgment values ​​and actual liquid substance values, the degree of difference between the judgment value and the true value can be intuitively understood. The preset test confidence level mapping table is established based on a large amount of experimental data and experience, and it maps the deviation index to the test confidence level. When the deviation index is small, it indicates that the historical liquid substance judgment value is close to the actual liquid substance value, and the corresponding test confidence level is high, meaning that the judgment result of the historical test battery is relatively reliable. Conversely, when the deviation index is large, it indicates that there is a large deviation between the judgment value and the actual value, the test confidence level is low, and the judgment result of the historical test battery is less reliable.

[0107] Specifically, determining whether to compensate for the liquid substance determination value based on the test confidence level includes:

[0108] Statistical analysis was performed on all the test confidence scores to calculate the average test confidence score;

[0109] Set a confidence threshold;

[0110] The average test confidence level is compared with the confidence threshold, and the comparison result is used to determine whether to compensate the liquid substance judgment value.

[0111] If the average test confidence level is greater than or equal to the confidence level threshold, it is determined that no compensation will be made for the liquid substance determination value.

[0112] Otherwise, the determination value of the liquid substance is to be compensated.

[0113] Understandably, setting a confidence threshold is to measure the overall reliability of historical test battery judgment results. When the average test confidence is greater than or equal to the confidence threshold, it indicates that the judgment results of historical test batteries are generally reliable, and the liquid substance judgment value obtained based on this also has high credibility, requiring no compensation. However, when the average test confidence is less than the confidence threshold, it indicates that the judgment results of historical test batteries have a large deviation, and the overall reliability is low. In this case, it is necessary to compensate for the liquid substance judgment value of the current test battery to improve the accuracy of the judgment result.

[0114] The compensation module is used to collect the initial weight loss characteristic parameters of the battery under test when it is determined that the liquid substance determination value should be compensated, and to determine the compensation coefficient of the liquid substance determination value based on the test confidence level and the initial weight loss characteristic parameters, and to obtain the compensated liquid substance determination value.

[0115] Specifically, determining the compensation coefficient for the liquid substance determination value based on the test confidence level and initial weightlessness characteristic parameters, and obtaining the compensated liquid substance determination value, includes:

[0116] The initial weight loss characteristic parameters are analyzed to obtain the initial weight loss percentage of the battery under test;

[0117] The difference between the average test confidence level and the confidence level threshold is obtained and denoted as the confidence level difference.

[0118] A compensation vector set is constructed based on the initial percentage of weightlessness and the confidence difference;

[0119] The compensation vector group is compared with the historical compensation group, and the compensation coefficient of the liquid substance determination value is determined based on the comparison result.

[0120] When there is a historical compensation vector group in the historical compensation group that is the same as the compensation vector group, the historical compensation coefficient corresponding to the historical compensation vector group is used as the compensation coefficient.

[0121] When there is no historical compensation vector group in the historical compensation group that is the same as the compensation vector group, the compensation coefficient is determined according to the compensation vector group.

[0122] The liquid substance determination value is compensated according to the compensation coefficient, and the compensated liquid substance determination value is obtained.

[0123] In this embodiment, the initial weight loss percentage refers to the percentage of weight lost by the battery under test in the initial stage of weight loss (i.e., the period after weight loss begins) relative to its initial weight. It reflects the release of liquid substances from the battery in the initial stage. For example, if the test duration is 5 hours and the fixed interval 'a' is 2 minutes, the initial weight loss percentage is calculated by the proportion of weight lost in the first 30 minutes (i.e., the first 15 sampling points) relative to the initial weight.

[0124] Understandably, by obtaining the difference between the average test confidence level and the confidence threshold, the gap between the reliability of historical test battery judgment results and the expected reliability can be quantified. The compensation vector set combines two key factors: the initial weight loss percentage and the confidence level difference, thus more comprehensively considering the characteristics of the battery under test and the reliability of historical tests. Comparing the compensation vector set with historical compensation sets is based on the accumulation of experience from historical data. The historical compensation set records the compensation coefficients used in similar situations in the past. When the same historical compensation vector set exists, the corresponding historical compensation coefficient is directly adopted, which can make full use of historical experience and improve the accuracy and efficiency of compensation. When the same historical compensation vector set does not exist, the compensation coefficient is determined based on the compensation vector set.

[0125] It is understandable that multiplying the compensation coefficient by the liquid substance determination value yields the compensated liquid substance determination value.

[0126] Specifically, determining the compensation coefficients based on the compensation vector set includes:

[0127] The matching degree between each compensation vector group and each historical compensation vector group is obtained one by one;

[0128] Get the maximum matching degree;

[0129] If the historical compensation vector group corresponding to the maximum matching degree is unique, then the historical compensation coefficient corresponding to the historical compensation vector group shall be used as the compensation coefficient.

[0130] If the historical compensation vector group corresponding to the maximum matching degree is not unique, then the historical compensation coefficient corresponding to each maximum matching degree is obtained, and the average value of all the historical compensation coefficients is calculated and denoted as the historical average compensation coefficient. The historical average compensation coefficient is then used as the compensation coefficient.

[0131] In this embodiment, the matching degree is calculated using the cosine similarity algorithm. Cosine similarity assesses the similarity between two vectors by calculating the cosine of the angle between them; the closer the cosine is to 1, the more similar the two vectors are. Specifically, for the compensation vector group and the historical compensation vector group, they are treated as vectors in a vector space, and the matching degree between them is calculated using the cosine similarity formula. This method of calculating the matching degree has many advantages. On the one hand, it is not affected by the vector length, focusing only on the direction of the vectors, which allows for effective matching degree calculation between compensation vector groups and historical compensation vector groups of different sizes. On the other hand, cosine similarity calculation is simple and efficient, quickly calculating the matching degree between each historical compensation vector group and the current compensation vector group, thereby improving the overall efficiency of the judgment system.

[0132] Understandably, determining the compensation coefficient in this way fully leverages the experience gained from historical data, maximizing the accuracy of compensation. Even if no historical compensation vector group is identical to the current one, the most similar historical case can be found by calculating the matching degree, and the compensation coefficient can be determined based on this. This allows the compensation liquid substance determination value to more closely approximate the actual liquid substance content in the battery under test, further improving the accuracy and reliability of the entire battery type determination system based on weight loss curve modeling. In the actual production and R&D of batteries, more accurate liquid substance determination values ​​can provide stronger support for battery quality control and performance optimization, contributing to the production of battery products with superior performance and higher safety.

[0133] The battery type determination module is used to determine the battery type of the battery to be tested based on the compensation liquid substance determination value.

[0134] Specifically, determining the battery type of the battery under test based on the compensated liquid substance determination value includes:

[0135] The determination value of the compensating liquid substance is compared with the first determination value of the compensating liquid substance and the second determination value of the compensating liquid substance, and the battery type of the battery to be tested is determined according to the comparison result; wherein, the first determination value of the compensating liquid substance is less than the second determination value of the compensating liquid substance.

[0136] When the determination value of the compensation liquid substance is less than or equal to the determination value of the first compensation liquid substance, the battery type of the battery to be tested is determined to be a solid-state battery.

[0137] When the determination value of the compensation liquid substance is greater than the first determination value of the compensation liquid substance and less than or equal to the second determination value of the compensation liquid substance, the battery type of the battery to be tested is determined to be a hybrid solid-liquid battery.

[0138] When the compensation liquid substance determination value is greater than the second compensation liquid substance determination value, the battery type of the battery to be tested is determined to be a liquid battery.

[0139] It is understandable that determining the type of battery under test based on the compensation liquid substance determination value is a scientifically effective classification method. Different types of batteries have significantly different liquid substance contents. By comparing the compensation liquid substance determination value with two preset thresholds, the battery type can be classified. When the compensation liquid substance determination value is less than or equal to the first compensation liquid substance determination value, it is determined to be a solid-state battery, which has high safety and stability and is advantageous in scenarios with high safety requirements. If it is between the first and second compensation liquid substance determination values, it is determined to be a hybrid solid-liquid battery, combining some advantages of solid-state and liquid batteries. If it is greater than the second compensation liquid substance determination value, it is determined to be a liquid battery, which has high energy density and good charge-discharge performance, but has safety hazards such as leakage. This determination method can provide a basis for the subsequent processing and application of batteries. In recycling, it can improve efficiency and resource utilization; in use, it can help formulate better usage and maintenance strategies, extend lifespan, and improve efficiency; it can also promote the development of battery technology and provide direction for the research and development of new batteries, such as optimizing solid-state battery design to improve safety and performance.

[0140] Based on the same inventive concept, this application also provides a method for determining battery type based on weightlessness curve modeling to implement the aforementioned battery type determination system based on weightlessness curve modeling. The solution provided by this method is similar to the implementation described in the above system. Therefore, the specific limitations in one or more embodiments of the battery type determination method based on weightlessness curve modeling provided below can be found in the limitations of the battery type determination system based on weightlessness curve modeling described above, and will not be repeated here.

[0141] In one exemplary embodiment, such as Figure 2 As shown, a method for determining battery type based on weightlessness curve modeling is provided, including the following steps:

[0142] Step 1: Determine the battery to be tested, perform a weight loss rate test on the battery to be tested, and collect the real-time weight value of the battery to be tested at fixed intervals a.

[0143] Step 2: Based on the fixed interval 'a' and the real-time weight value, construct the weight loss fitting curve of the battery under test using a fitting method;

[0144] Step 3: Extract features from the weight loss fitting curve to obtain the weight loss feature value of the battery under test, and determine the liquid substance determination value of the battery under test based on the weight loss feature value;

[0145] Step 4: Collect the historical liquid substance determination value corresponding to each historical test battery, determine the test confidence level of the historical test battery based on the historical liquid substance determination value, and determine whether to compensate the liquid substance determination value based on the test confidence level.

[0146] Step 5: When it is determined that the liquid substance determination value needs to be compensated, the initial weight loss characteristic parameters of the battery under test are collected. Based on the test confidence level and the initial weight loss characteristic parameters, the compensation coefficient of the liquid substance determination value is determined, and the compensated liquid substance determination value is obtained.

[0147] Step 6: Determine the battery type of the battery to be tested based on the compensation liquid substance determination value.

[0148] The battery type determination system and method based on weight loss curve modeling provided in this embodiment effectively overcomes the drawbacks of existing simplified methods that rely on the difference between initial and final mass. By deeply analyzing the weight loss curve, it accurately captures the detailed characteristics of the electrolyte release rate changing over time, helping to reveal the kinetic mechanism and intrinsic laws of electrolyte release, thereby achieving precise control over the electrolyte release process. In practical applications, the system and method involved in this embodiment can improve the accuracy and reliability of battery type determination. For different types of batteries, the system and method involved in this embodiment can more accurately determine the content and state of their liquid substances, providing strong support for battery research and development, production, and quality control. During the battery research and development stage, accurate determination of battery type can optimize battery design and manufacturing processes, improving battery performance and safety. During the production process, it can promptly detect abnormalities in the battery's liquid substances, ensuring the stability of product quality.

[0149] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0150] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0151] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A battery type determination system based on weightlessness curve modeling, characterized in that, The battery type determination system based on weightlessness curve modeling includes: The first acquisition module is used to identify the battery to be tested, perform a weight loss rate test on the battery to be tested, and acquire the real-time weight value of the battery to be tested at fixed intervals a. The curve fitting module is used to construct the weight loss fitting curve of the battery under test based on the fixed interval a and the real-time weight value, and by using a fitting method. The second acquisition module is used to extract features from the weight loss fitting curve, obtain the weight loss feature value of the battery under test, and determine the liquid substance determination value of the battery under test based on the weight loss feature value. The judgment module is used to collect the historical liquid substance judgment value corresponding to each historical test battery, determine the test confidence level of the historical test battery based on the historical liquid substance judgment value, and determine whether to compensate the liquid substance judgment value based on the test confidence level. The compensation module is used to collect the initial weight loss characteristic parameters of the battery under test when it is determined that the liquid substance determination value should be compensated, and to determine the compensation coefficient of the liquid substance determination value based on the test confidence level and the initial weight loss characteristic parameters, and to obtain the compensated liquid substance determination value. The battery type determination module is used to determine the battery type of the battery to be tested based on the compensation liquid substance determination value.

2. The battery type determination system based on weightlessness curve modeling according to claim 1, characterized in that, Based on the fixed interval 'a' and the real-time weight value, a weight loss fitting curve for the battery under test is constructed using a fitting method, specifically including: The real-time weight value is preprocessed, including data alignment and noise filtering at the fixed interval a, to obtain the preprocessed weight value. The preprocessed weight value and the corresponding fixed interval 'a' are used as inputs, and the initial weightlessness fitting curve is constructed using the fitting method described above; wherein, the fitting method includes exponential decay fitting or piecewise linear regression. Obtain the initial weight loss value of the battery under test, and determine the preliminary estimation parameters of the initial weight loss fitting curve; The initial weightlessness fitting curve is optimized and fitted based on the initial weightlessness value and preliminary estimated parameters to obtain the weightlessness fitting curve.

3. The battery type determination system based on weightlessness curve modeling according to claim 2, characterized in that, The determination of the liquid substance status of the battery under test based on the weight loss characteristic value specifically includes: The weightlessness characteristic values ​​are analyzed to obtain the weightlessness rate and plateau weight of the weightlessness fitting curve; The basic liquid substance determination value of the battery under test is determined based on the initial weight loss value and the plateau weight. The optimization coefficient for the determination value of the basic liquid substance is determined based on the weight loss rate; The basic liquid substance determination value is optimized based on the optimization coefficient to obtain the liquid substance determination value.

4. The battery type determination system based on weightlessness curve modeling according to claim 3, characterized in that, The optimization coefficient for determining the basic liquid substance determination value is based on the weight loss rate, specifically including: The weight loss rate is compared with the first weight loss rate and the second weight loss rate, and the optimization coefficient of the basic liquid substance determination value is determined based on the comparison result; wherein, the first weight loss rate is less than the second weight loss rate; When the weightlessness rate is less than or equal to the first weightlessness rate, the optimization coefficient is determined to be the first optimization coefficient; When the weightlessness rate is greater than the first weightlessness rate and less than or equal to the second weightlessness rate, the optimization coefficient is determined to be the second optimization coefficient. When the weightlessness rate is greater than the second weightlessness rate, the optimization coefficient is determined to be the third optimization coefficient.

5. The battery type determination system based on weightlessness curve modeling according to claim 4, characterized in that, The test confidence level of the historical test battery is determined based on the historical liquid substance determination value, specifically including: Obtain the actual liquid substance value corresponding to each of the historical test batteries; Obtain the deviation index between the historical liquid substance determination value and the actual liquid substance value; The deviation index is compared with a preset test confidence mapping table, and the test confidence level corresponding to each historical test battery is determined based on the comparison result.

6. The battery type determination system based on weightlessness curve modeling according to claim 5, characterized in that, Determining whether to compensate for the liquid substance determination value based on the test confidence level specifically includes: Statistical analysis was performed on all the test confidence scores to calculate the average test confidence score; Set a confidence threshold; The average test confidence level is compared with the confidence threshold, and the comparison result is used to determine whether to compensate the liquid substance judgment value. If the average test confidence level is greater than or equal to the confidence level threshold, it is determined that no compensation will be made for the liquid substance determination value. Otherwise, the determination value of the liquid substance is to be compensated.

7. The battery type determination system based on weightlessness curve modeling according to claim 6, characterized in that, Based on the test confidence level and initial weightlessness characteristic parameters, a compensation coefficient for the liquid substance determination value is determined, and a compensated liquid substance determination value is obtained, specifically including: The initial weight loss characteristic parameters are analyzed to obtain the initial weight loss percentage of the battery under test; The difference between the average test confidence level and the confidence level threshold is obtained and denoted as the confidence level difference. A compensation vector set is constructed based on the initial percentage of weightlessness and the confidence difference; The compensation vector group is compared with the historical compensation group, and the compensation coefficient of the liquid substance determination value is determined based on the comparison result. When there is a historical compensation vector group in the historical compensation group that is the same as the compensation vector group, the historical compensation coefficient corresponding to the historical compensation vector group is used as the compensation coefficient. When there is no historical compensation vector group in the historical compensation group that is the same as the compensation vector group, the compensation coefficient is determined according to the compensation vector group. The liquid substance determination value is compensated according to the compensation coefficient, and the compensated liquid substance determination value is obtained.

8. The battery type determination system based on weightlessness curve modeling according to claim 7, characterized in that, Determining the compensation coefficients based on the compensation vector set specifically includes: The matching degree between each compensation vector group and each historical compensation vector group is obtained one by one; Get the maximum matching degree; If the historical compensation vector group corresponding to the maximum matching degree is unique, then the historical compensation coefficient corresponding to the historical compensation vector group shall be used as the compensation coefficient. If the historical compensation vector group corresponding to the maximum matching degree is not unique, then the historical compensation coefficient corresponding to each maximum matching degree is obtained, and the average value of all the historical compensation coefficients is calculated and denoted as the historical average compensation coefficient. The historical average compensation coefficient is then used as the compensation coefficient.

9. The battery type determination system based on weightlessness curve modeling according to claim 8, characterized in that, The battery type of the battery under test is determined based on the compensated liquid substance determination value, specifically including: The determination value of the compensating liquid substance is compared with the first determination value of the compensating liquid substance and the second determination value of the compensating liquid substance, and the battery type of the battery to be tested is determined according to the comparison result; wherein, the first determination value of the compensating liquid substance is less than the second determination value of the compensating liquid substance. When the determination value of the compensation liquid substance is less than or equal to the determination value of the first compensation liquid substance, the battery type of the battery to be tested is determined to be a solid-state battery. When the determination value of the compensation liquid substance is greater than the first determination value of the compensation liquid substance and less than or equal to the second determination value of the compensation liquid substance, the battery type of the battery to be tested is determined to be a hybrid solid-liquid battery. When the compensation liquid substance determination value is greater than the second compensation liquid substance determination value, the battery type of the battery to be tested is determined to be a liquid battery.

10. A method for determining battery type based on weightlessness curve modeling, characterized in that, The battery type determination method based on weightlessness curve modeling, when applied to the battery type determination system based on weightlessness curve modeling as described in any one of claims 1-9, specifically includes the following steps: Identify the battery to be tested, perform a weight loss rate test on the battery to be tested, and collect the real-time weight value of the battery to be tested at fixed intervals a; Based on the fixed interval 'a' and the real-time weight value, a weight loss fitting curve for the battery under test is constructed using a fitting method. Feature extraction is performed on the weight loss fitting curve to obtain the weight loss feature value of the battery under test, and the liquid substance determination value of the battery under test is determined based on the weight loss feature value. Collect the historical liquid substance determination value corresponding to each historical test battery, determine the test confidence level of the historical test battery based on the historical liquid substance determination value, and determine whether to compensate the liquid substance determination value based on the test confidence level. When it is determined that the liquid substance determination value should be compensated, the initial weight loss characteristic parameters of the battery under test are collected, and the compensation coefficient of the liquid substance determination value is determined based on the test confidence level and the initial weight loss characteristic parameters, and the compensated liquid substance determination value is obtained. The battery type of the battery to be tested is determined based on the compensation liquid substance determination value.

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