Battery life quick prediction method, apparatus, device, and medium

Abstract

The application provides a battery life quick prediction method, device, equipment and medium. The method comprises the following steps: obtaining a battery cycle stage according to the number of to-be-tested cycle factors and a battery cycle factor; testing the battery according to the battery cycle stage, obtaining a battery SOH attenuation value corresponding to each test sub-stage, and obtaining an equivalent cycle number corresponding to each test sub-stage according to the charging and discharging energy of the battery in each test sub-stage; obtaining an attenuation rate of the battery corresponding to each test sub-stage according to the battery SOH attenuation value and the equivalent cycle number corresponding to each test sub-stage; obtaining the value of each to-be-tested cycle factor according to the attenuation rate corresponding to each test sub-stage; and predicting the cycle life of the battery when the battery attenuates to a target battery SOH value according to the value of each to-be-tested cycle factor and the target battery SOH value. The method provided by the application can conveniently and quickly predict the battery life.

Description

Technical Field

[0001] The present application relates to the field of battery technology, and in particular to a method, device, equipment and medium for quickly predicting battery life. Background Art

[0002] Batteries are an important component in electrical terminalization and energy industry optimization. Among them, lithium-ion batteries have the characteristics of high energy density and long cycle life. As a clean energy, they have been widely used in the fields of electricity and electrochemistry.

[0003] To continuously develop electrical terminals and optimize the energy industry, predicting and evaluating battery cycle life is a crucial component of the battery industry. Evaluating battery cycle life is equivalent to evaluating the battery's recyclability; based on this performance evaluation, subsequent battery development and upgrades can be accelerated. However, existing methods for predicting battery cycle life require offline processing, involving obtaining impedance spectrum data for different batteries at the same number of cycles and for the same battery at different numbers of cycles, and then determining the battery cycle life based on this impedance spectrum data. This method requires a long time and, due to the limitations of offline data, cannot easily and quickly predict the battery's cycle life.

[0004] Therefore, there is an urgent need for a processing method that can conveniently and quickly predict cycle life. Summary of the Invention

[0005] The present application provides a method, apparatus, device and medium for quickly predicting battery life, which is used to solve the problem that the prediction method in the prior art requires offline testing and is not convenient and fast enough.

[0006] In a first aspect, the present application provides a method for quickly predicting battery life, comprising:

[0007] Obtaining a battery cycle stage according to the number of cycle factors to be measured and a battery cycle factor; wherein the battery cycle factor includes multiple test factors, the number of test sub-stages in the battery cycle stage is the same as the number of cycle factors to be measured, and the factor conditions of the test sub-stage include one or more of the test factors;

[0008] Testing the battery according to the battery cycle stage, obtaining the battery SOH decay value corresponding to each test sub-stage, and obtaining the equivalent number of cycles corresponding to each test sub-stage based on the charge and discharge energy of the battery in each test sub-stage;

[0009] Obtaining the battery decay rate corresponding to each test sub-stage according to the battery SOH decay value and the equivalent cycle number corresponding to each test sub-stage;

[0010] According to the attenuation rate corresponding to each test sub-stage, a value of each to-be-tested cycle factor is obtained;

[0011] According to the value of each to-be-tested cycle factor and a target battery SOH value, a cycle life of the battery when the battery attenuates to the target battery SOH value is predicted.

[0012] In a possible implementation, the obtaining, according to the battery SOH attenuation value corresponding to each test sub-stage and the equivalent cycle number, of an attenuation rate of the battery corresponding to each test sub-stage includes:

[0013] The battery cycle stage is executed at least once, and a total attenuation value is obtained according to the battery SOH attenuation values corresponding to different execution times of the same test sub-stage; the battery SOH attenuation value is a difference between battery SOH values before and after execution of the test sub-stage;

[0014] A total equivalent cycle number is obtained according to the equivalent cycle numbers corresponding to different execution times of the same test sub-stage;

[0015] The attenuation rate of the battery corresponding to each test sub-stage is obtained according to the total attenuation value and the total equivalent cycle number.

[0016] In a possible implementation, the obtaining, according to the charging and discharging energy of the battery in each test sub-stage, of the equivalent cycle number corresponding to each test sub-stage includes:

[0017] The charging and discharging energy of the battery in each test sub-stage is obtained according to a preset cycle number of the battery in each test sub-stage and a single-cycle charging and discharging energy of the battery;

[0018] The equivalent cycle number corresponding to each test sub-stage is obtained according to the charging and discharging energy and a rated energy of the battery.

[0019] In a possible implementation, the obtaining, according to the attenuation rate corresponding to each test sub-stage, of a value of each to-be-tested cycle factor includes:

[0020] A corresponding relationship between the attenuation rate of the battery in each test sub-stage and the to-be-tested cycle factor and the factor condition is obtained based on an Arrhenius empirical formula; the to-be-tested cycle factor includes a pre-factor, an average activation energy, and a characteristic parameter;

[0021] The value of each to-be-tested cycle factor is obtained according to the attenuation rate of the battery in each test sub-stage and the factor condition.

[0022] In a possible implementation, obtaining the correspondence between the decay rate of the battery in each test sub-stage and the cycle factor to be measured and the factor condition includes:

[0023] Obtaining pre-parameters according to the discharge rate / power of the battery in each test sub-stage and the pre-factor;

[0024] Obtaining a first post-parameter according to the average activation energy, the characteristic parameter, the charge rate / power of the battery in each test sub-stage, and the material system of the battery;

[0025] Obtaining a second post-parameter based on the free gas constant and the temperature of the incubator where the battery is located;

[0026] Acquire a total post-parameter according to the first post-parameter and the second post-parameter;

[0027] According to the pre-parameter and the total post-parameter, the corresponding relationship between the attenuation rate of the battery in each test sub-stage and the cycle factor to be measured and the factor condition is obtained.

[0028] In one possible implementation, predicting the cycle life of the battery when it decays to the target battery SOH value based on the value of each cycle factor to be measured and the target battery SOH value includes:

[0029] Substituting each cycle factor to be measured as a known number into the corresponding relationship between the decay rate of the battery and the cycle factor to be measured and the factor condition in each test sub-stage;

[0030] Determining the predicted degradation rate of the battery under any one or more of the preset test factors according to the preset test factors; wherein the factor conditions include the temperature of the incubator where the battery is located, the battery cycle rate, and the battery cycle power;

[0031] According to the predicted decay rate and the target battery SOH value, the cycle life of the battery when it decays to the target battery SOH value is obtained.

[0032] In a possible implementation, obtaining, according to the predicted decay rate and the target battery SOH value, the cycle life of the battery when it decays to the target battery SOH value includes:

[0033] Obtaining a target battery SOH attenuation value according to the current battery SOH value and the target battery SOH value;

[0034] Obtaining a total decay rate of the battery according to the predicted decay rate and an exponential factor of the predicted decay rate;

[0035] The cycle life of the battery when it decays to the target battery SOH value is obtained according to the target battery SOH decay value and the total decay rate.

[0036] In a second aspect, the present application provides a device for quickly predicting battery life, comprising:

[0037] A first acquisition module is configured to acquire a battery cycle stage according to a cycle factor to be measured and a battery cycle factor; wherein the battery cycle stage includes the number of test sub-stages and factor conditions of each test sub-stage, and the number of test sub-stages is consistent with the number of cycle factors to be measured;

[0038] A second acquisition module is used to obtain the battery SOH attenuation value corresponding to each test sub-stage, and obtain the equivalent cycle number corresponding to each test sub-stage according to the charge and discharge energy of the battery in each test sub-stage;

[0039] A first processing module is configured to obtain a decay rate of the battery according to the battery SOH decay value and the equivalent cycle number;

[0040] A second processing module is used to obtain the value of the cycle factor to be measured according to the decay rate;

[0041] The prediction module is used to predict the cycle life of the battery when it decays to the target battery SOH value based on the value of the cycle factor to be measured and the target battery SOH value.

[0042] In a third aspect, the present application provides a device for quickly predicting battery life, comprising: at least one processor and a memory;

[0043] The memory stores computer-executable instructions;

[0044] The at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor performs the battery life rapid prediction method as described above.

[0045] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for rapid prediction of battery life as described above.

[0046] The present application provides a method, apparatus, device and medium for quickly predicting battery life, which obtains a battery cycle stage according to the number of cycle factors to be measured and a battery cycle factor; wherein the battery cycle factor includes multiple test factors, the number of test sub-stages in the battery cycle stage is the same as the number of the cycle factors to be measured, and the factor conditions of the test sub-stage include one or more of the test factors; the battery is tested according to the battery cycle stage to obtain the battery SOH decay value corresponding to each test sub-stage, and the equivalent number of cycles corresponding to each test sub-stage is obtained according to the charge and discharge energy of the battery in each test sub-stage; the decay rate of the battery corresponding to each test sub-stage is obtained according to the battery SOH decay value and the equivalent number of cycles corresponding to each test sub-stage; the value of each cycle factor to be measured is obtained according to the decay rate corresponding to each test sub-stage; and the cycle life of the battery when it decays to the target battery SOH value is predicted according to the value of each cycle factor to be measured and the target battery SOH value.

[0047] In the above method, the number of test sub-stages in the battery cycle stage is confirmed by the number of cycle factors to be measured that need to be obtained to ensure that the numerical value of each cycle factor to be measured is solved subsequently; the factor conditions of the test sub-stages in the battery cycle stage are obtained through different test factors in the battery cycle factors, so that the battery data under different factor conditions can be tested in the battery cycle stage later, including the battery SOH decay value and equivalent cycle number of each test sub-stage; the battery decay rate of each test sub-stage can be obtained according to the battery SOH decay value and equivalent cycle number of each test sub-stage, and the cycle factor to be measured of each test sub-stage can be confirmed according to the decay rate. At this time, the cycle factor to be measured is a known number and can be used for subsequent battery life prediction; the cycle life of the battery can be predicted according to the cycle factor to be measured and the target battery SOH value of each test sub-stage; this process rationally utilizes various data parameters, so that the battery can predict its service life to reach the target battery SOH value through the cycle in the experiment, thereby realizing convenient and fast battery life prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0049] Figure 1 A schematic diagram of a test for rapid prediction of battery life provided in an embodiment of the present application;

[0050] Figure 2A process for quickly predicting battery life provided by an embodiment of the present application Figure 1 ;

[0051] Figure 3 A process for quickly predicting battery life provided in an embodiment of the present application Figure 2 ;

[0052] Figure 4 A decay rate fitting diagram of a method for rapid battery life prediction provided in an embodiment of the present application;

[0053] Figure 5 A process for quickly predicting battery life provided in an embodiment of the present application Figure 3 ;

[0054] Figure 6 A process for quickly predicting battery life provided in an embodiment of the present application Figure 4 ;

[0055] Figure 7 A diagram of a device for quickly predicting battery life provided by an embodiment of the present invention;

[0056] Figure 8 A hardware schematic diagram of a device for rapid battery life prediction provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0057] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0058] In real production and life, various energy consumption is rampant. In order to optimize the energy industry and achieve carbon neutrality, people have begun to study the comprehensive distribution of energy and the use of clean energy. Among them, batteries, as a type of clean energy, it is also very important to effectively improve their utilization efficiency.

[0059] The production process of the battery includes performance evaluation, wherein the estimation of the cycle life of the battery is also indispensable; the cycle life of the battery also represents the length of time that the battery can be recycled, and if the use time is too short, it means that the performance of the battery is poor. The existing battery life prediction methods mainly use the impedance spectrum data of the battery to continuously cycle experiments, or collect offline data through cycle experiments, and build a decay model for prediction. The prediction cycle of these prediction methods is very long, and can only be performed offline, which is very inconvenient to operate, so a more convenient, fast and effective battery cycle life detection method needs to be proposed.

[0060] The implementation process of the battery life prediction method proposed in the present application is described below through the drawings and specific examples.

[0061] Figure 1 A battery life prediction test schematic diagram is provided for the embodiments of the present application. As shown in the figure, the test includes a battery cycle stage, wherein the battery cycle stage includes a plurality of test sub-stages; Figure 1

[0062] The number of test sub-stages can be determined according to the number of cycle factors to be tested. The number of unknowns is equal to the number of cycle factors to be tested, and the same group of data is required to solve the number of unknowns. Each test sub-stage can measure a group of data, so the number of test sub-stages is the same as the number of cycle factors to be tested. For example, when there are 3 cycle factors to be tested, a complete battery cycle stage can be set up with 3 test sub-stages;

[0063] Each test sub-stage corresponds to different factor conditions, and the battery needs to be tested under the factor conditions corresponding to the test sub-stage. The factor conditions are composed of test factors in the battery cycle factors. For example, if the test factor is temperature, the three test sub-stages can be set to 10 degrees Celsius, 25 degrees Celsius and 45 degrees Celsius for cycling. The number of cycles of each test sub-stage can be the same or different, for example, the number of cycles of each test sub-stage is set to be greater than or equal to 50 cycles for cycle testing. Compared with the cycle prediction of several thousand cycles in the prior art, the scheme of the present embodiment is more time-saving in testing;

[0064] ​As shown in the figure, a battery cycle stage can be tested at four nodes. A battery SOH value is tested before the start of test sub-stage 1, and a battery SOH value is tested after the end of test sub-stage 1. The difference between the battery SOH values ​​before and after test sub-stage 1 can be used to obtain the first battery SOH attenuation value. Similarly, the battery SOH attenuation values ​​of test sub-stage 2 and test sub-stage 3 are obtained in turn; the charge and discharge energy of the battery in each test sub-stage is measured to obtain the equivalent number of cycles corresponding to the three test sub-stages; the battery SOH attenuation value of each test sub-stage is divided by the equivalent number of cycles to obtain the attenuation rate of the battery under different conditions;

[0065] The three decay rates are used as known data in the three data groups to solve the values ​​of the three cycle factors to be tested; the solved three cycle factors to be tested will be used as known numbers to predict the battery life in the future, and combined with the battery's target battery SOH value, the number of times the battery can be cycled from the current state to the target battery SOH value is predicted. The number of cycles is the cycle life of the battery to the target battery SOH value; when the cycling stage is over, the cycle factors to be tested can be directly used as known numbers for prediction, without the need for cycling experiments for each prediction, which is faster and more convenient than existing technologies.

[0066] Below through Figure 2 The specific embodiments further illustrate the implementation process of the battery life rapid prediction method proposed in this application.

[0067] Figure 2 A process for quickly predicting battery life provided in an embodiment of the present application Figure 1 .like Figure 2 As shown, the method includes:

[0068] S201. Obtain a battery cycle stage based on the number of cycle factors to be measured and a battery cycle factor; wherein the battery cycle factor includes multiple test factors, the number of test sub-stages in the battery cycle stage is the same as the number of cycle factors to be measured, and the factor conditions of the test sub-stage include one or more of the test factors.

[0069] The cycle factor to be measured is a necessary parameter for confirming and predicting the battery life. The cycle factor to be measured can be obtained based on experiments on the battery and can be regarded as a parameter characterizing the battery performance. After the specific value of the cycle factor to be measured is obtained through experiments, it can be used to predict the battery life. The number of cycle factors to be measured corresponds to the number of sets of formulas required to solve the specific values ​​of the cycle factors to be measured, which corresponds to the number of test sub-stages in the battery cycling stage that can be set. A set of solution formulas can be listed for each test sub-stage, so the number of test sub-stages in the battery cycling stage is the same as the number of cycle factors to be measured.

[0070] The battery cycle factors include multiple test factors. During the cycle experiment, the battery needs to set certain test conditions, such as temperature conditions, cycle rate, etc.; the factor conditions of each test sub-stage in the battery cycle stage can be composed of one or more test factors; for example, the factor condition of test sub-stage 1 is a temperature condition of 10 degrees Celsius, the factor condition of test sub-stage 2 is a temperature condition of 25 degrees Celsius, and the factor condition of test sub-stage 3 is a temperature condition of 45 degrees Celsius; or the factor condition of test sub-stage 1 is a temperature condition of 10 degrees Celsius and a cycle rate of 0.5C, the factor condition of test sub-stage 2 is a temperature condition of 10 degrees Celsius and a cycle rate of 1C, and the factor condition of test sub-stage 3 is a temperature condition of 25 degrees Celsius and a cycle rate of 0.25C.

[0071] S202. Test the battery according to the battery cycle stage, obtain the battery SOH decay value corresponding to each test sub-stage, and obtain the equivalent cycle number corresponding to each test sub-stage based on the charge and discharge energy of the battery in each test sub-stage.

[0072] A complete battery cycle stage includes at least one test sub-stage. In each test sub-stage, the battery can be cycled according to a set number of cycles (greater than or equal to 50 cycles), and the battery SOH value of the battery before and after the cycle of each test sub-stage is tested before and after the end of each test sub-stage. The battery SOH attenuation value is obtained based on the difference between the battery SOH values ​​before and after the cycle of the test sub-stage, so as to test the SOH attenuation of the battery after the cycle under the conditions of this test sub-stage. For example, the battery SOH value tested before test sub-stage 1 is 100%, and the battery SOH value tested after test sub-stage 1 may be 90% (current batteries generally do not decay so much after 50 cycles. This is an exaggerated data for the sake of example);

[0073] In addition to testing the battery SOH value before and after each test sub-stage, the charge and discharge energy of a single cycle of each test sub-stage can also be obtained. Based on the charge and discharge energy of the single cycle and the number of cycles of each test sub-stage, the equivalent number of cycles corresponding to each test sub-stage can be obtained.

[0074] S203: Obtain the battery decay rate corresponding to each test sub-stage according to the battery SOH decay value and the equivalent cycle number corresponding to each test sub-stage.

[0075] The battery SOH attenuation value corresponding to each test sub-stage is divided by the equivalent number of cycles corresponding to each test sub-stage to obtain the battery SOH attenuation corresponding to the unit equivalent number of cycles, that is, the battery attenuation rate.

[0076] S204. Obtain the value of each cycle factor to be tested according to the decay rate corresponding to each test sub-stage.

[0077] There is a corresponding relationship between the cycle factor to be measured and the attenuation rate of the battery. This corresponding relationship constitutes a relational expression, which includes all the cycle factors to be measured. The decay rate of each test sub-stage is solved accordingly, and then it can be substituted into the relational expression to obtain the same number of relational expression groups as the number of cycle factors to be measured. According to each relational expression, the value of each cycle factor to be measured can be obtained.

[0078] S205 , predicting the cycle life of the battery when it decays to the target battery SOH value based on the value of each cycle factor to be measured and the target battery SOH value.

[0079] The numerical value of the cycle factor to be measured solved above is substituted into the relationship as a known number. At this time, the decay rate in the relationship is an unknown number. According to the predicted conditions of the battery, the decay rate is substituted into the relationship to predict the decay rate, where the prediction conditions include one or more test factors; based on the predicted decay rate and the target battery SOH value, it can be predicted how many times the battery can cycle to the target battery SOH value under the test conditions, and the number of cycles is the battery cycle life.

[0080] The embodiments of the present application include confirming the number of test sub-stages in the battery cycle stage by the number of test cycle factors to be obtained to ensure that the numerical value of each test cycle factor to be measured is solved subsequently; obtaining the factor conditions of the test sub-stages in the battery cycle stage through different test factors in the battery cycle factors, so that the battery data under different factor conditions can be tested in the battery cycle stage later, including the battery SOH decay value and the equivalent cycle number of each test sub-stage; the battery decay rate of each test sub-stage can be obtained according to the battery SOH decay value and the equivalent cycle number of each test sub-stage, and the test cycle factor of each test sub-stage can be confirmed according to the decay rate. At this time, the test cycle factor is a known number and can be used for subsequent battery life prediction; the cycle life of the battery can be predicted according to the test cycle factor and the target battery SOH value of each test sub-stage; this process rationally utilizes various data parameters, so that the battery can predict its service life to reach the target battery SOH value through the cycle in the experiment, thereby realizing convenient and fast battery life prediction.

[0081] Below through Figure 3 、 Figure 4 The specific embodiments further illustrate the process of obtaining the attenuation rate in the method for rapid prediction of battery life proposed in this application.

[0082] Figure 3 A process for quickly predicting battery life provided in an embodiment of the present application Figure 2 . Figure 4 This is a decay rate fitting diagram of a battery life rapid prediction method provided in an embodiment of the present application. Figure 3 and Figure 4 As shown, the method includes:

[0083] S301. Execute the battery cycle phase at least once, and obtain a total attenuation value based on the battery SOH attenuation values ​​corresponding to different execution times of the same test sub-phase; wherein the battery SOH attenuation value is the difference between the battery SOH values ​​before and after the execution of the test sub-phase.

[0084] When executing one battery cycle stage, one battery SOH attenuation value and one equivalent cycle number can be obtained for each test sub-stage. When the battery cycle stages are repeated multiple times, multiple battery SOH attenuation values ​​and equivalent cycle numbers can be obtained for each test sub-stage. There is no need to calculate the average value for executing one battery cycle stage, but the average value can be calculated for executing multiple battery cycle stages. This embodiment is mainly explained by taking the execution of multiple battery cycle stages as an example. By summing the battery SOH attenuation values ​​of the same test sub-stage, the total value of the battery SOH attenuation value, i.e., the total attenuation value, can be obtained. For example, the battery SOH values ​​before and after the first cycle test sub-stage 1 are 100% and 95% respectively (the battery SOH values ​​before and after the first cycle test sub-stage 2 are 95% and 93% respectively, and the battery SOH values ​​before and after the first cycle test sub-stage 3 are 93% and 91% respectively), and the attenuation value is 5%. The battery SOH values ​​before and after the second cycle test sub-stage 1 are 91% and 88% respectively, and the attenuation value is 3%, so the total attenuation value is 8%.

[0085] S302. Obtain a total equivalent number of cycles according to the equivalent number of cycles corresponding to different execution times of the same test sub-phase.

[0086] When executing one battery cycling stage, one battery SOH decay value and one equivalent cycle number can be obtained for each test sub-stage. When the battery cycling stage is repeated multiple times, multiple battery SOH decay values ​​and equivalent cycle numbers can be obtained for each test sub-stage. The total equivalent cycle number of the battery in the same test sub-stage is summed up to obtain the total equivalent cycle number.

[0087] In the actual calculation process, for a certain test sub-stage, the calculation process of the equivalent number of cycles is as follows:

[0088] Obtaining the charge and discharge energy of the battery in each test sub-stage according to a preset number of cycles of the battery in each test sub-stage and the single-cycle charge and discharge energy of the battery;

[0089] According to the charge and discharge energy and the rated energy of the battery, the equivalent number of cycles corresponding to each test sub-stage is obtained.

[0090] Each test sub-stage is cycled for a preset number of cycles, and the charge and discharge energy of the battery in a single test sub-stage is related to the charge and discharge energy of a single cycle and the number of cycles. The charge and discharge energy of each single cycle is added to obtain the charge and discharge energy of the battery in the test sub-stage, and the equivalent cycle numbers of the same test sub-stage in multiple cycles are added to obtain the total equivalent cycle number.

[0091] For example, the calculation formula of the equivalent cycle number EFC is as follows:

[0092]

[0093] where cycle_num is the set number of cycles, E cha is the charge energy of a single cycle of the battery, E dis is the discharge energy of a single cycle of the battery, and E nom is the rated energy of the battery.

[0094] If the equivalent cycle number of the test sub-stage 1 in the first cycle is EFC1, and the equivalent cycle number of the test sub-stage 1 in the second cycle is EFC2, then the total equivalent cycle number of the test sub-stage 1 is EFC1+EFC2.

[0095] S303, according to the total attenuation value and the total equivalent cycle number, obtaining the attenuation rate of the battery in each test sub-stage.

[0096] The total attenuation value of the same test sub-stage is divided by the total equivalent cycle number of the same test sub-stage to obtain the average attenuation rate of the test sub-stage, Figure 4 The slope k of the function is the attenuation rate of a single test sub-stage. For example, SOH1 corresponds to 100%, SOH2 corresponds to 95%, and SOH3 corresponds to 92%. SOH1 to SOH2 corresponds to a 5% attenuation of the test sub-stage 1 in the first cycle, and SOH2 to SOH3 corresponds to a 3% attenuation of the test sub-stage 1 in the second cycle. The attenuation rate of the test sub-stage 1 is k1=(5%+3%) / (EFC1+EFC2).

[0097] In the embodiments of the present application, multiple battery SOH attenuation values and equivalent cycle numbers are obtained by multiple cycles of the battery, and the average attenuation rate is obtained according to the battery SOH attenuation value and the equivalent cycle number in the same test sub-stage, so as to increase the reliability of the test data.

[0098] The following will be further described by Figure 5 and specific embodiments to obtain the test cycle factor in the battery life prediction method proposed in the present application.

[0099] Figure 5A process for quickly predicting battery life provided in an embodiment of the present application Figure 3 .like Figure 5 As shown, the method includes:

[0100] S501 : Based on the Arrhenius empirical formula, obtain pre-parameters according to the discharge rate / power and pre-factor of the battery in each test sub-phase.

[0101] Based on the Arrhenius empirical formula, a relationship between the decay rate, the test factor and the cycle factor to be tested is constructed, and the relationship between the decay rate and the pre-parameters is included in the relationship;

[0102] The pre-parameter is composed of the discharge rate / power and pre-factor of the battery in each test sub-stage. For example, the discharge rate / power of the battery in each test sub-stage is multiplied by a constant and then added to the pre-factor to obtain the pre-parameter; among which the pre-factor is the cycle factor to be tested and the discharge rate / power is the test factor.

[0103] S502 : Obtain a first post-parameter according to the average activation energy, characteristic parameters, the charge rate / power of the battery in each test sub-phase, and the material system of the battery.

[0104] The relationship includes the relationship between the attenuation rate and the first post-parameter. The first post-parameter is composed of the average activation energy, the characteristic parameter, the charging rate / power of the battery in each test sub-stage, and the material system of the battery. For example, the characteristic parameter is multiplied by the charging rate / power of the battery in each test sub-stage and the material system of the battery, and then added to the average activation energy to obtain the first post-parameter; among which, the average activation energy and the characteristic parameter are the cycle factors to be measured, and the charging rate / power is the test factor.

[0105] S503 : Acquire a second post-parameter according to the free gas constant and the temperature of the incubator where the battery is located.

[0106] The relationship includes the relationship between the decay rate and the second post-parameter, which is composed of the free gas constant and the temperature of the incubator where the battery is located. For example, the second post-parameter is obtained by multiplying the free gas constant and the temperature of the incubator where the battery is located. Among them, the temperature of the incubator where the battery is located is a test factor, which has been listed in the above embodiment.

[0107] S504: Acquire a total post-parameter according to the first post-parameter and the second post-parameter.

[0108] The total post-parameter can be obtained by dividing the first post-parameter and the second post-parameter.

[0109] S505. Obtain, based on the pre-parameters and the total post-parameters, the correspondence between the attenuation rate of the battery in each test sub-stage and the cycle factor to be measured and the factor conditions; wherein the cycle factor to be measured includes the pre-factor, the average activation energy and the characteristic parameter.

[0110] Take the negative of the total post-parameter and take the square root, and then multiply it by the pre-parameter to obtain the decay rate. The decay rate equation is the relationship between the decay rate, the test factor and the cycle factor to be measured, which characterizes the correspondence between the decay rate of the battery in each test sub-stage and the cycle factor to be measured and the factor conditions; the cycle factors to be measured include the pre-factor, the average activation energy and the characteristic parameter, a total of three, so three test sub-stages can be set in the battery cycle stage.

[0111] Alternatively, the relationship can be expressed as:

[0112]

[0113] Where k is the decay rate; b is a constant; R is the free gas constant, usually 8.314 J / (mol K); T is the temperature, in K; A0 is the pre-factor; i1 is the charge rate / power, with the rate unit in A and the power unit in P; i2 is the discharge rate / power, with the rate unit in A and the power unit in P; V1 is the charge voltage, whose value is related to the battery material system; E a is the average activation energy; c0 is the characteristic parameter.

[0114] S506. Obtain a value of each cycle factor to be tested according to the decay rate of the battery in each test sub-stage and the factor conditions.

[0115] The expression has different input values ​​corresponding to each test sub-stage. For example, test sub-stage 1 corresponds to k1, and the test sub-stage 1 has corresponding i1 value, i2 value and T value, as well as b value and R value, and also A0, E a and c0 are three unknowns. Similarly, an equation can be listed in test sub-stage 2 and test sub-stage 3 respectively. By solving the three equations, the numerical solution of each cycle factor to be tested can be obtained. Subsequently, the cycle factor to be tested can be substituted into the relationship as a known number to predict the battery life.

[0116] The embodiments of the present application include constructing a relationship between various data and obtaining the values ​​of various data in a cycle experiment until the cycle factor to be measured can be solved, which facilitates the subsequent prediction of battery life. The battery cycling stage process cycle is short and simple and convenient to implement. The data obtained from the experiment can be used for predictions under different test conditions.

[0117] Below through Figure 6The specific embodiments further illustrate the implementation process of the battery life rapid prediction method proposed in this application.

[0118] Figure 6 A process for quickly predicting battery life provided in an embodiment of the present application Figure 4 .like Figure 6 As shown, the method includes:

[0119] S601. Substitute each cycle factor to be measured as a known number into the corresponding relationship between the decay rate of the battery and the cycle factor to be measured and the factor condition in each test sub-stage.

[0120] The corresponding relationship between the battery attenuation rate and the cycle factor to be measured and the factor conditions has been described in detail in the above embodiments. By substituting the solved cycle factor to be measured as a known number into the above relationship, a relationship that can be used to predict the battery life can be obtained.

[0121] S602. Confirm the predicted attenuation rate of the battery under any one or more of the preset test factors according to the preset test factors; wherein the factor conditions include the temperature of the incubator where the battery is located, the battery cycle rate, and the battery cycle power.

[0122] The relationship includes different test factors. Any one or more test factors are selected as prediction conditions. For example, assuming that the battery operates at a temperature of 10 degrees Celsius, then T = 10°C in the above relationship. Then, based on the cycle rate / cycle power and other values ​​of the battery to be evaluated and the relationship, the predicted attenuation rate of the battery is obtained.

[0123] S603: Acquire a target battery SOH attenuation value according to the current battery SOH value and the target battery SOH value.

[0124] The current SOH value of the battery can be directly obtained based on the reference performance test (RPT). The target battery SOH value can be set to obtain the difference between the current SOH value of the battery and the target battery SOH value to obtain the target battery SOH attenuation value.

[0125] S604: Obtain a total decay rate of the battery according to the predicted decay rate and an exponential factor of the predicted decay rate.

[0126] The exponential factor is used as the exponent of the predicted decay rate and then multiplied by the current SOH value of the battery to obtain the total decay rate of the battery.

[0127] S605 : Obtaining the cycle life of the battery when it decays to the target battery SOH value according to the target battery SOH decay value and the total decay rate.

[0128] Divide the target battery SOH decay value by the total decay rate to obtain the cycle life of the battery when it decays to the target battery SOH value.

[0129] Optionally, the cycle life C (unit number of revolutions) is obtained by the following formula:

[0130]

[0131] Where k is the decay rate; SOH t is the target battery SOH value, in %; m is the exponential factor, generally 1 / 2 or 1; S0 is the current battery SOH value, in %. If the battery being predicted is new, the current battery SOH value is 100%, and S0=100.

[0132] The embodiments of the present application include predicting the battery life by solving the relationship between the cycle factor to be measured and the target battery SOH value. This process is a prediction process after the experiment. The calculation method is simple and there is no need to conduct experiments again. The life of the experimental battery or the same type of battery can be predicted. There is no need to keep the battery in an offline testing state for a long time. The prediction step in the battery production process is optimized, which is beneficial to the further development of subsequent batteries.

[0133] Figure 7 A diagram of a battery life rapid prediction device provided by an embodiment of the present invention, such as Figure 7 As shown, the device includes: a first acquisition module 701, a second acquisition module 702, a first processing module 703, a second processing module 704 and a prediction module 705;

[0134] A first acquisition module 701 is configured to acquire a battery cycle stage based on a cycle factor to be measured and a battery cycle factor; wherein the battery cycle stage includes the number of test substages and factor conditions of each test substage, and the number of test substages is consistent with the number of cycle factors to be measured;

[0135] The second acquisition module 702 is used to obtain the battery SOH decay value corresponding to each test sub-stage, and obtain the equivalent cycle number corresponding to each test sub-stage based on the charge and discharge energy of the battery in each test sub-stage;

[0136] A first processing module 703 is configured to obtain a battery decay rate according to the battery SOH decay value and the equivalent cycle number;

[0137] A second processing module 704 is configured to obtain a value of the cycle factor to be measured according to the decay rate;

[0138] The prediction module 705 is used to predict the cycle life of the battery when it decays to the target battery SOH value based on the value of the cycle factor to be measured and the target battery SOH value.

[0139] The present application also provides a battery life rapid prediction device, comprising: at least one processor and a memory;

[0140] The memory stores computer-executable instructions;

[0141] The at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor performs a battery life rapid prediction method.

[0142] Figure 8 This is a hardware diagram of a device for rapid battery life prediction provided by an embodiment of the present invention. Figure 8 As shown, the battery life rapid prediction device 80 provided in this embodiment includes: at least one processor 801 and a memory 802. The device 80 also includes a communication component 803. The processor 801, the memory 802, and the communication component 803 are connected via a bus 804.

[0143] In a specific implementation process, at least one processor 801 executes the computer-executable instructions stored in the memory 802, so that the at least one processor 801 executes the above-mentioned method for quickly predicting battery life.

[0144] The specific implementation process of the processor 801 can be found in the above method embodiment. Its implementation principle and technical effects are similar and will not be repeated here in this embodiment.

[0145] In the above Figure 8 In the illustrated embodiment, it should be understood that the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASICs), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly executed by a hardware processor or by a combination of hardware and software modules within the processor.

[0146] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (NVM), such as at least one disk memory.

[0147] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be classified into address buses, data buses, and control buses. For ease of illustration, the buses in the drawings of this application are not limited to just one bus or just one type of bus.

[0148] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the battery life rapid prediction method described above is implemented.

[0149] The computer-readable storage medium mentioned above can be implemented by any type of volatile or non-volatile memory device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk. The computer-readable storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0150] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be an integral part of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0151] The division of units described above is merely a logical functional division. In actual implementation, other divisions may be employed. For example, multiple units or components may be combined or integrated into another system, or some features may be omitted or not implemented. Furthermore, any coupling or direct coupling or communication connection shown or discussed between units may be an indirect coupling or communication connection via an interface, device, or unit, and may be electrical, mechanical, or other.

[0152] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0153] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0154] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0155] Those skilled in the art will appreciate that all or part of the steps in the above-described method embodiments can be implemented using hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0156] Finally, it should be noted that those skilled in the art will readily identify other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art not disclosed herein. The present invention is not limited to the precise structure described above and illustrated in the accompanying drawings, and various modifications and variations may be made without departing from the scope thereof. The scope of the present invention is limited solely by the appended claims.

Claims

1. A method for quickly predicting battery life, characterized in that: include: Obtaining a battery cycle stage according to the number of cycle factors to be measured and a battery cycle factor; wherein the battery cycle factor includes multiple test factors, the number of test sub-stages in the battery cycle stage is the same as the number of cycle factors to be measured, and the factor conditions of the test sub-stage include one or more of the test factors; Testing the battery according to the battery cycle stage, obtaining the battery SOH decay value corresponding to each test sub-stage, and obtaining the equivalent number of cycles corresponding to each test sub-stage based on the charge and discharge energy of the battery in each test sub-stage; Obtaining the battery decay rate corresponding to each test sub-stage according to the battery SOH decay value and the equivalent cycle number corresponding to each test sub-stage; According to the decay rate corresponding to each test sub-stage, the value of each cycle factor to be tested is obtained; Substituting each cycle factor to be measured as a known number into the corresponding relationship between the decay rate of the battery and the cycle factor to be measured and the factor condition in each test sub-stage; Determining the predicted degradation rate of the battery under any one or more of the preset test factors according to the preset test factors; wherein the factor conditions include the temperature of the incubator where the battery is located, the battery cycle rate, and the battery cycle power; Obtaining a target battery SOH attenuation value according to the current battery SOH value and the target battery SOH value; Obtaining a total decay rate of the battery according to the predicted decay rate and an exponential factor of the predicted decay rate; The cycle life of the battery when it decays to the target battery SOH value is obtained according to the target battery SOH decay value and the total decay rate.

2. The method according to claim 1, characterized in that Obtaining the battery decay rate corresponding to each test sub-stage according to the battery SOH decay value and the equivalent cycle number corresponding to each test sub-stage includes: Execute the battery cycling stage at least once, and obtain a total attenuation value based on the battery SOH attenuation values ​​corresponding to different execution times of the same test sub-stage; wherein the battery SOH attenuation value is the difference between the battery SOH values ​​before and after the execution of the test sub-stage; Obtaining a total equivalent number of cycles according to the equivalent number of cycles corresponding to different execution times of the same test sub-phase; The decay rate of the battery in each test sub-phase is obtained according to the total decay value and the total equivalent cycle number.

3. The method according to claim 2, characterized in that Obtaining the equivalent number of cycles corresponding to each test sub-stage according to the charge and discharge energy of the battery in each test sub-stage includes: Obtaining the charge and discharge energy of the battery in each test sub-stage according to a preset number of cycles of the battery in each test sub-stage and the single-cycle charge and discharge energy of the battery; According to the charge and discharge energy and the rated energy of the battery, the equivalent number of cycles corresponding to each test sub-stage is obtained.

4. The method according to claim 2, characterized in that The step of obtaining the value of each cycle factor to be tested according to the decay rate corresponding to each test sub-stage includes: Based on the Arrhenius empirical formula, the corresponding relationship between the decay rate of the battery in each test sub-stage and the cycle factor to be measured and the factor conditions is obtained; wherein the cycle factor to be measured includes the pre-factor, the average activation energy and the characteristic parameter; According to the decay rate of the battery in each test sub-stage and the factor conditions, the value of each cycle factor to be measured is obtained.

5. The method according to claim 4, characterized in that The obtaining of the corresponding relationship between the decay rate of the battery in each test sub-stage and the cycle factor to be measured and the factor condition includes: Obtaining pre-parameters according to the discharge rate / power of the battery in each test sub-stage and the pre-factor; Obtaining a first post-parameter according to the average activation energy, the characteristic parameter, the charge rate / power of the battery in each test sub-stage, and the material system of the battery; Obtaining a second post-parameter based on the free gas constant and the temperature of the incubator where the battery is located; Acquire a total post-parameter according to the first post-parameter and the second post-parameter; According to the pre-parameter and the total post-parameter, the corresponding relationship between the attenuation rate of the battery in each test sub-stage and the cycle factor to be measured and the factor condition is obtained.

6. A battery life rapid prediction device, characterized in that: include: A first acquisition module is configured to acquire a battery cycle stage according to the number of cycle factors to be measured and a battery cycle factor; wherein the battery cycle factor includes a plurality of test factors, the number of test sub-stages in the battery cycle stage is the same as the number of cycle factors to be measured, and the factor conditions of the test sub-stage include one or more of the test factors; A second acquisition module is used to test the battery according to the battery cycle stage, obtain the battery SOH decay value corresponding to each test sub-stage, and obtain the equivalent cycle number corresponding to each test sub-stage according to the charge and discharge energy of the battery in each test sub-stage; A first processing module is configured to obtain a battery decay rate corresponding to each test substage according to the battery SOH decay value and the equivalent cycle number corresponding to each test substage; The second processing module is used to obtain the value of each cycle factor to be tested according to the decay rate corresponding to each test sub-stage; A prediction module, configured to bring each cycle factor to be measured as a known number into the corresponding relationship between the decay rate of the battery in each test sub-stage and the cycle factor to be measured and the factor condition; Determining the predicted degradation rate of the battery under any one or more of the preset test factors according to the preset test factors; wherein the factor conditions include the temperature of the incubator where the battery is located, the battery cycle rate, and the battery cycle power; Obtaining a target battery SOH attenuation value according to the current battery SOH value and the target battery SOH value; Obtaining a total decay rate of the battery according to the predicted decay rate and an exponential factor of the predicted decay rate; The cycle life of the battery when it decays to the target battery SOH value is obtained according to the target battery SOH decay value and the total decay rate.

7. A battery life rapid prediction device, characterized in that: include: at least one processor and memory; The memory stores computer-executable instructions; The at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor performs the method for quickly predicting battery life according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for quickly predicting battery life as claimed in any one of claims 1 to 5 are implemented.

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