Battery life prediction method and device

Abstract

The invention belongs to the technical field of battery health management, and particularly relates to a battery life prediction method and device. According to the method, alternate testing is carried out in each unit time: charging and discharging cycle testing of cycle times in the unit time is carried out on a battery according to cycle parameters, then shelving testing is carried out on the battery according to calendar parameters in remaining time of the unit time, and capacity loss of the battery is detected every set period in the testing process. And fitting the detected capacity loss and the corresponding test time to obtain a battery life model about the capacity loss and the test time, determining the corresponding test time when the capacity is attenuated to the end point of the battery life according to the battery life model, and taking the test time as the battery life. The obtained prediction result can accurately reflect calendar life attenuation, cycle life attenuation and interaction between the calendar life attenuation and the cycle life attenuation, and the test process is closer to the use condition of the battery, so that the accuracy of battery life evaluation is improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of battery health management, and particularly relates to a battery life prediction method and device. BACKGROUND

[0002] The battery usage state is divided into charging, discharging and shelving. Correspondingly, the battery life is divided into cycle life and calendar life. The existing battery life evaluation technology generally evaluates the cycle life and calendar life of the battery respectively, and then directly accumulates the cycle life and calendar life to predict the battery life. For example, the Chinese patent application file with the publication number CN119224623A discloses a method for evaluating the life of an energy storage battery and related devices. Cycle life experiments and calendar life experiments are respectively carried out under different experimental simulation conditions to obtain corresponding experimental data, and the cycle life experimental data and the calendar life experimental data under different experimental simulation conditions are respectively fitted and superimposed to obtain cycle life attenuation functions and calendar life attenuation functions. The actual historical data of the energy storage battery are used to divide intervals, and the sum of the cycle life attenuation function and the calendar life attenuation function in each interval is used as the energy storage battery life attenuation function. This method separately tests the cycle life and the calendar life under the simulation condition parameters, directly superimposes the cycle life attenuation and the calendar life attenuation, and does not consider the interaction between the calendar life attenuation and the cycle life attenuation when they are superimposed, resulting in low prediction accuracy. Moreover, the existing technology does not consider the daily atmospheric temperature in different regions and different seasons, and does not consider the battery temperature rise caused by solar radiation when evaluating the calendar life of the battery in the shelving state, thereby causing prediction deviation. SUMMARY

[0003] The present application aims to provide a battery life prediction method and device to solve the problem of low battery life prediction accuracy caused by directly superimposing the cycle life attenuation and the calendar life attenuation obtained from separate tests.

[0004] The application provides a battery life prediction method to solve the above technical problems, which comprises the following steps: determining cycle parameters and calendar parameters of battery testing; the cycle parameters comprise cycle times per unit time, cycle temperature, charge-discharge rate and discharge depth; the calendar parameters comprise storage temperature and SOC; performing alternating testing in each unit time: performing charge-discharge cycle testing of the battery according to the cycle parameters for the cycle times per unit time, and then performing storage testing of the battery according to the calendar parameters for the remaining time of the unit time; the unit time is divided according to the storage condition of the battery, and the battery storage is performed only once in one unit time; detecting the capacity loss of the battery every set period during the testing process, fitting a battery life model about the capacity loss and the testing time by using the detected capacity loss and the corresponding testing time, determining the testing time corresponding to the capacity attenuation to the end of the battery life according to the battery life model, and taking the testing time as the battery life.

[0005] Further, the cycle temperature is determined according to the atmospheric environment temperature in the cycle state and the temperature rise in the cycle state in the actual working condition of the battery; and the storage temperature is determined according to the indoor environment temperature or the atmospheric environment temperature outdoors in the storage state in the actual working condition of the battery.

[0006] Further, the cycle temperature and the storage temperature are both N; the determination process of the N cycle temperatures is: counting the atmospheric environment temperature in the cycle state and the corresponding temperature rise in the cycle state in the actual working condition of the battery in a set time period, determining the corresponding N typical temperatures in the cycle state according to the temperature interval and the cycle times under each temperature obtained by counting, and taking the N typical temperatures as the cycle temperatures; the determination process of the N storage temperatures is: counting the indoor environment temperature or the atmospheric environment temperature outdoors in the storage state in the actual working condition of the battery in a set time period, determining the corresponding N typical temperatures in the storage state according to the temperature interval and the storage time under each temperature obtained by counting, and taking the N typical temperatures as the storage temperatures; N≥2, and the set time period comprises at least one annual time.

[0007] Further, one cycle temperature and one storage temperature are taken as a group, the cycle temperature and the storage temperature in each group are in the same position in the corresponding typical temperature sorting, and the testing is performed in groups, that is, the cycle temperature of the charge-discharge cycle testing and the storage temperature of the storage testing are in the same group in each unit time.

[0008] Further, the testing in groups is performed in the following process: first, alternating testing is performed in each unit time under one group of cycle temperature and storage temperature, and then the testing under the next group of cycle temperature and storage temperature is performed after the testing under the cycle temperature corresponding to the cycle times in the set time period and the testing under the storage temperature corresponding to the storage time in the set time period in the group are completed, and the testing under all cycle temperatures and storage temperatures is completed.

[0009] Further, the number of cycles in a unit time is determined according to the use frequency of the device in which the battery is located in a unit time, and the charge-discharge rate and the discharge depth are determined according to the charge-discharge rate and the discharge depth under the actual working condition of the battery; and the SOC is determined according to the electric quantity when the battery is left under the actual working condition.

[0010] Further, when the alternating test is performed, the same pre-tightening force as that in actual use is also applied to the battery.

[0011] The beneficial effects of the above technical solution are as follows: the present application is an open-type invention, after the battery is subjected to charge-discharge cycle in each unit time, the battery is left in the remaining time, so that the cycle life test and the calendar life test are alternately performed in each unit time, and the capacity loss of the battery after alternating cycle and leaving is periodically obtained, the battery life model of the capacity loss and the test time is fitted according to the capacity loss of the battery and the corresponding test time, and then the battery life is determined according to the model, compared with the capacity loss after the cycle life test and the capacity loss after the calendar life test, the present application can accurately reflect the calendar life attenuation, the cycle life attenuation and the interaction therebetween, and the test process is closer to the working condition of the battery, so that the accuracy of the battery life evaluation is improved.

[0012] To solve the above technical problem, the present application further provides a battery life prediction device, comprising a processor and an accelerated test module, the accelerated test module is used for providing a test environment; the processor is used for determining the cycle parameters and the calendar parameters of the battery test, controlling the accelerated test module to perform charge-discharge cycle test on the battery according to the cycle parameters in each unit time, and then performing leaving test on the battery according to the calendar parameters in the remaining time of the unit time, detecting the capacity loss of the battery every set period in the test process, fitting the battery life model about the capacity loss and the test time by using the detected capacity loss and the corresponding test time, determining the test time when the capacity attenuation reaches the end of the battery life according to the battery life model, and taking the test time as the battery life; the cycle parameters include the number of cycles in a unit time, cycle temperature, charge-discharge rate and discharge depth; the calendar parameters include leaving temperature and SOC; the unit time is divided according to the leaving condition of the battery, so that the battery leaving is only performed once in a unit time.

[0013] Further, the accelerated test module comprises a pressurizing unit, the pressurizing unit is used for applying the same pre-tightening force as that in actual use to the battery; the pressurizing unit comprises a fixed plate provided with a groove on both sides and a binding wire, the fixed plate is used for being arranged on both sides of the battery, and the binding wire is used for binding the fixed plate and the battery together at the groove.

[0014] Further, the cycle temperature and the standing temperature are both N; the determination process of the N cycle temperatures is: counting the atmospheric environment temperature in the cycle state and the temperature rise corresponding to the cycle state in the actual working condition of the battery in a set time period, determining the N typical temperatures corresponding to the cycle state according to the temperature interval and the cycle times at each temperature obtained by the counting, and taking the N typical temperatures as the cycle temperatures; the determination process of the N standing temperatures is: counting the indoor environment temperature or the atmospheric environment temperature outside in the standing state in the actual working condition of the battery in a set time period, determining the N typical temperatures corresponding to the standing state according to the temperature interval and the standing time at each temperature obtained by the counting, and taking the N typical temperatures as the standing temperatures; N is greater than or equal to 2, and the set time period includes at least one annual time.

[0015] The beneficial effects of the above technical solution are: the present application is an opening-type invention, after the battery is subjected to the charge-discharge cycle in each unit time, the battery is subjected to the standing in the remaining time, so that the cycle life test and the calendar life test are alternately performed in each unit time, and the battery capacity loss after the alternately performed cycle and standing is periodically obtained, the battery life model of the capacity loss and the test time is fitted according to the capacity loss of the battery and the corresponding test time, and then the battery life is determined according to the model, compared with the capacity loss after the cycle life test and the capacity loss after the calendar life test, the present application can accurately reflect the calendar life attenuation, the cycle life attenuation and the interaction between the two, the test process is closer to the use condition of the battery, so that the accuracy of the battery life evaluation is improved. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 is the cycle life test and calendar life test flowchart of the method embodiment of the present application;

[0017] Figure 2 is the battery life prediction device schematic diagram of the device embodiment of the present application;

[0018] Figure 3 is the top view of the pressurizing unit of the device embodiment of the present application;

[0019] Figure 4 is the top view of the pressurizing unit after fixing the battery of the device embodiment of the present application;

[0020] The reference signs: 1-aluminum plate; 2-bolt hole; 3-glass fiber; 4-battery. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical scheme and advantages of the present application more clear, the specific embodiments of the present application are further described below with reference to the drawings.

[0022] The present invention adopts a test method in which cycle life test and calendar life test are performed alternately, and determines the battery life based on the capacity loss after the alternation, thereby improving the accuracy of battery life prediction.

[0023] Method implementation

[0024] A battery life prediction method of the present invention comprises the following steps:

[0025] 1. Determine the cycle parameters and calendar parameters for battery testing.

[0026] Cycling parameters include the number of cycles per unit time, cycle temperature, charge / discharge rate, and depth of discharge. Calendar parameters include shelf temperature and SOC. The unit time can be 1, 2, or 3 days, depending on the battery's shelf life. Only one battery shelf is performed per unit time.

[0027] When evaluating battery life, the existing technology does not take into account the daily atmospheric temperature in different regions and seasons, as well as the battery temperature rise caused by solar radiation, which leads to deviations in the prediction results. Therefore, as a preferred embodiment, in order to more accurately evaluate the battery operating life, the cycle parameters and calendar parameters are set according to the operating conditions of the battery during actual use. At this time, the working conditions of the battery are identified, and the working conditions such as the geographical area of ​​battery use, actual frequency of use, charge and discharge rate, discharge depth, storage environment and battery SOC status are obtained. The working conditions of the battery during actual use are decomposed, and the number of cycles per unit time is determined according to the frequency of use of the device where the battery is located per unit time. The frequency of use can be the historical frequency of use or the planned frequency of use. The cycle temperature is determined according to the atmospheric environment temperature and the temperature rise under the cycle state in the actual working condition of the battery. The charge and discharge rate and discharge depth are determined according to the charge and discharge rate and discharge depth under the actual working condition of the battery.

[0028] The shelf temperature is determined based on the indoor or outdoor ambient temperature during the battery's actual operating conditions. The SOC is determined based on the battery's actual charge level during shelf operation. The temperature rise is estimated based on the daily maximum and minimum temperatures, as well as the diurnal temperature difference, corresponding to the region and season of battery use. This allows for more accurate assessment of the battery's cycle and shelf temperatures, improving prediction accuracy.

[0029] The battery is used at multiple temperatures, and therefore, to further improve the prediction accuracy, both the cycle temperatures and the storage temperatures are N, N≥2. The determination process of the N cycle temperatures is as follows: the ambient temperature in the cycle state and the temperature rise corresponding to the cycle state in the actual working condition of the battery in a set time period are counted, the N typical temperatures corresponding to the cycle state are determined according to the temperature interval and the cycle times at each temperature obtained by counting, and the N typical temperatures are taken as the cycle temperatures. The determination process of the N storage temperatures is as follows: the indoor ambient temperature or the outdoor ambient temperature in the storage state in the actual working condition of the battery in a set time period is counted, the N typical temperatures corresponding to the storage state are determined according to the temperature interval and the storage time at each temperature, and the N typical temperatures are taken as the storage temperatures. The set time period includes at least one annual time. When the cycle temperatures and the storage temperatures are N, one cycle temperature and one storage temperature are taken as a group, the positions of the cycle temperatures and the storage temperatures in the corresponding typical temperature sorting are the same in each group, and the storage temperature of each group is lower than the cycle temperature. The cycle temperatures and the storage temperatures are generally classified and divided according to different seasons and months, and the cycle temperature and the corresponding storage temperature in the same month or season can be divided into a group, and the total cycle time and the total storage time in each group are generally the same.

[0030] 2. Alternating tests are performed in each unit time.

[0031] The tests include cycle life tests and calendar life tests. The cycle life tests and the calendar life tests are alternately performed in each unit time. The battery is subjected to charge-discharge cycle tests (i.e., cycle life tests) according to the cycle parameters for the cycle times in a unit time, and then is subjected to storage tests (i.e., calendar life tests) according to the calendar parameters for the remaining time in a unit time.

[0032] When the cycle temperatures and the storage temperatures are N, the cycle times corresponding to the cycle temperatures and the storage times corresponding to the storage temperatures of the battery in a set time period are determined, and the tests are performed in groups, i.e., the cycle temperature of the charge-discharge cycle test and the storage temperature of the storage test are in the same group in each unit time. Specifically, alternating tests are performed in each unit time at a group of cycle temperatures and storage temperatures, until the tests of the cycle times corresponding to the cycle temperatures in a set time period and the storage times corresponding to the storage temperatures in a set time period in the group are completed, and then the tests at the next group of cycle temperatures and storage temperatures are performed, until the tests at all cycle temperatures and storage temperatures are completed.

[0033] For example, for a certain battery, it is determined that the battery performs n times of charge-discharge cycles per day according to the frequency of use of the device in which the battery is located, and the rest of the time is left. Then for the battery, the unit time is 1 day, the total time of one charge and discharge of the battery is t1, the cycle use time per day is n*t1, and the remaining time after the cycle ends per day is the standby time, that is, the standby time of the battery per day is 24-n*t1. The determined cycle temperatures are T1, T2 and T3, etc. (for example, T1=25℃, T2=40℃, T3=55℃). The determined standby temperatures are T4, T5 and T6, etc. (for example, T4=-5℃, T5=20℃, T6=35℃). The discharge rate is set according to the discharge rule that the device in which the battery is located discharges at a high rate when taking off and landing, and discharges at a normal small rate at other times, and the charging rate is set using the step charging strategy. The depth of discharge is determined according to the difference in electric quantity when the battery is charged twice. The SOC state of the battery is confirmed according to the electric quantity when the battery is left. The required cycle times in different cycle temperature conditions (T1, T2 and T3, etc.) are determined as n1, n2 and n3, etc. The standby times in different standby temperature conditions (T4, T5 and T6, etc.) are determined as t4, t5 and t6, etc. The cycle temperatures T1, T2 and T3 and the calendar temperatures T4, T5 and T6 have the same time period.

[0034] T1 and T4 are taken as the first group, T2 and T5 are taken as the second group, and T3 and T6 are taken as the third group. The test process is as shown in Figure 1 When the cycle life test and the calendar life test are alternately performed, the first group test is performed first, that is, the cycle life test and the calendar life test are alternately performed per day at the cycle temperature T1 and the standby temperature T4: the battery is subjected to n times of charge-discharge cycles per unit time at the corresponding charge-discharge rate and the depth of discharge DOD at the cycle temperature T1, and then the battery with the standby electric quantity of SOC is subjected to standby for (24-n*t1) per unit time at the standby temperature T4. The cycle life test and the calendar life test are alternately performed per day according to the test process, until the cycle times n1 at the cycle temperature T1 and the standby times t4 at the standby temperature T4 are met, and then the second group test is performed according to the process, that is, the test at the cycle temperature T2 and the standby temperature T5, until the test at all cycle temperatures and standby temperatures is completed. Since the battery capacity will be attenuated after multiple charge-discharge, the total time of one charge and discharge of the battery will change as the battery capacity loss, for example, t1 at the beginning, and then t2 and t3, etc. as the battery capacity loss.

[0035] As another embodiment, the normal temperature of the four seasons of a year should be low-high-low, and the test at different cycle temperatures and standby temperatures can be performed according to the order of low-high-low corresponding to the four seasons of a year.

[0036] As a preferred embodiment, in order to accelerate the test process, the test can be started from high temperature cycling and high temperature storage, that is, when the cycle life test and the calendar life test are alternately performed, the cycle temperature and the storage temperature are tested in the order from high to low. For example, the cycle life test and the calendar life test are first performed at T3 and T6, then the cycle life test and the calendar life test are performed at T2 and T5, and finally the cycle life test and the calendar life test are performed at T1 and T4. As an embodiment, in order to reduce the prediction error, the same pre-tightening force as that in actual use is also applied to the battery when the alternating test is performed.

[0037] 3. During the test, the capacity loss of the battery is detected every set period, the battery life model about the capacity loss and the test time is fitted by using the detected capacity loss and the corresponding test time, the test time corresponding to the capacity decay to the end of the battery life is determined according to the battery life model, and the test time is taken as the battery life.

[0038] The capacity loss of the battery after the cycle life test and the calendar life test are alternately performed every day is accumulated, and the capacity loss of the battery is obtained every set period, for example, the standard capacity test at room temperature is performed on the battery once every 30 days to obtain the capacity loss of the battery corresponding to the test time.

[0039] The capacity loss of the battery obtained by the test after the cycle decay and the calendar decay is used to construct a life decay model of the battery by using the Arrhenius model, and the life decay model is a life model of the capacity loss Qloss of the battery and the battery life t. The battery life model is:

[0040]

[0041] Wherein, Qloss is the capacity loss of the battery; A is a pre-exponential factor; Ea is an activation energy, with a unit of eV; K is a constant, with a value of 8.62*10-5eV / K; T is an absolute temperature, with a value of 25℃; t is a test time, and z is a decay factor.

[0042] The end of the battery life refers to that the capacity of the battery is 80% or 70% of the original capacity, the test time corresponding to the capacity loss of 20% or 30% obtained by using the life decay model, that is, the test time corresponding to the capacity decay to the end of the battery life, is taken as the battery life, so as to be used as a simple evaluation of the warranty period.

[0043] Device embodiment

[0044] A battery life prediction device of the present application is used to realize the battery life prediction method introduced in the method embodiment. As shown in FIG. 1, the device comprises a battery life prediction device 1, a battery 2, a cycle life test device 3, a calendar life test device 4, a capacity test device 5, a data acquisition device 6, a data processing device 7, and a data storage device 8. Figure 2As shown, the device includes a processor and an accelerated test module, the accelerated test module is used to provide a test environment, and the processor is used to decompose the working condition according to the use area of the battery, the use frequency of the device where the battery is located, the storage environment and the SOC state of the battery, the charge / discharge rate and the discharge depth, etc. Get the cycle parameters of the cycle life test and the calendar parameters of the calendar life test. Control the accelerated test module to perform charge / discharge cycle test on the battery according to the cycle parameters in each unit time, and then perform storage test on the battery according to the calendar parameters in the remaining time of the unit time. During the test process, the capacity loss of the battery is detected every set period, and the battery life model about the capacity loss and the test time is fitted by using the detected capacity loss and the corresponding test time. According to the battery life model, the test time corresponding to the capacity decay to the end of the battery life is determined, and the test time is used as the battery life; the cycle parameters include the number of cycles in a unit time, the cycle temperature, the charge / discharge rate and the discharge depth; the calendar parameters include the storage temperature and the SOC; the unit time is divided according to the storage condition of the battery, so that the battery storage is only performed once in a unit time.

[0045] In order to more accurately simulate the battery state and reduce the prediction error, the accelerated test module includes a pressurizing unit, which is used to apply the same pre-tightening force to the battery as in the actual use. The pressurizing unit includes a fixed plate provided with grooves on both sides and a binding wire, the fixed plate is used to be arranged on both sides of the battery, and the binding wire is used to bind the fixed plate and the battery together at the grooves.

[0046] For example, for a certain battery, the battery has the characteristics of high energy, high density, small module volume, light weight and simple structure. Therefore, the pressurizing unit also needs to be light in weight, small in size and small in space occupation. At this time, as a preferred embodiment, specifically, as shown in Figure 3 and Figure 4 The fixed plate is an aluminum plate 1, and the binding wire is a glass fiber 3. Two light aluminum plates are fixed on both sides of the battery 4, and the two sides of the aluminum plate have four grooves of the same size. The glass fiber is wound on the four grooves to apply a certain size of pre-tightening force to the battery 4. The aluminum plate 1 has four bolt holes 2 at the corners, and when the fixed pressure is applied, the four corners are tightened in turn by bolts. Then the glass fiber 3 is wound on the four grooves of the aluminum plate 1, and finally the bolts are removed to complete the pre-tightening process. Then the battery 4 is subjected to cycle life test and calendar life test. By using the same pre-tightening force control method as the battery system to apply pre-tightening force to the battery for cycle life test and calendar life test, the battery state is closer to the unmanned aerial vehicle system state, and the prediction result is more accurate.

[0047] The application discloses a pressurizing unit for battery cycle life and calendar life test, which is innovatively designed and developed, so that the battery state is the same as that in the equipment, the obtained data is more accurate, and the evaluation accuracy is improved in the test. When the battery life is evaluated, the atmospheric environment temperature of the use area is combined, the temperature of the battery during the cycle use and the storage is more accurately judged and classified, the cycle life test and the calendar life test are alternately performed, the use working condition of the battery is closer, and the accuracy of the battery life prediction is improved. The application can be applied to the battery life evaluation in different projects, such as vehicle-mounted, energy storage and unmanned aerial vehicle.

Claims

1. A battery life prediction method, characterized in that: include: Determine the cycle parameters and calendar parameters for battery testing; cycle parameters include the number of cycles per unit time, cycle temperature, charge and discharge rate, and depth of discharge; calendar parameters include shelf temperature and SOC; Perform alternating tests within each unit time: perform charge and discharge cycle tests on the battery for the number of cycles within the unit time according to the cycle parameters, and then perform a shelf test on the battery according to the calendar parameters during the remaining time of the unit time; the unit time is divided according to the shelf status of the battery, and the battery is only shelf-tested once within one unit time; During the test process, the battery capacity loss is detected at set intervals. The detected capacity loss and the corresponding test time are used to fit a battery life model about capacity loss and test time. The test time corresponding to when the capacity decays to the end of the battery life is determined according to the battery life model, and this test time is used as the battery life.

2. The battery life prediction method according to claim 1, characterized in that: The circulation temperature is determined according to the atmospheric environment temperature and the temperature rise in the circulation state in the actual working condition of the battery; the shelf temperature is determined according to the indoor ambient temperature or the outdoor atmospheric environment temperature in the shelf state in the actual working condition of the battery.

3. The battery life prediction method according to claim 1, wherein: There are N cycle temperatures and N shelf temperatures. The process for determining the N cycle temperatures is as follows: the atmospheric ambient temperature and the corresponding temperature rise in the cycle state are calculated under the actual working conditions of the battery in a set time period, and the N typical temperatures corresponding to the cycle state are determined based on the statistically obtained temperature range and the number of cycles at each temperature. These N typical temperatures are used as the cycle temperatures. The process for determining the N shelf temperatures is as follows: the indoor ambient temperature or outdoor atmospheric ambient temperature in the shelf state is calculated under the actual working conditions of the battery in a set time period, and the N typical temperatures corresponding to the shelf state are determined based on the statistically obtained temperature range and the shelf time at each temperature. These N typical temperatures are used as the shelf temperatures. N ≥ 2, and the set time period includes at least one annual time.

4. The battery life prediction method according to claim 3, characterized in that: A cycle temperature and a shelf temperature are taken as a group. The cycle temperature and the shelf temperature in each group are in the same position in the corresponding typical temperature sorting. The tests are performed in groups. That is, the cycle temperature of the charge and discharge cycle test and the shelf temperature of the shelf test are in the same group per unit time.

5. The battery life prediction method according to claim 4, characterized in that: The process of testing in groups is: first, perform alternating tests at a group of cycling temperatures and shelf temperatures in each unit time until the number of cycles corresponding to the cycling temperature within the set time period and the shelf time corresponding to the shelf temperature within the set time period in the group are completed, and then perform tests at the next group of cycling temperatures and shelf temperatures until the tests at all cycling temperatures and shelf temperatures are completed.

6. The battery life prediction method according to claim 1, characterized in that: The number of cycles per unit time is determined based on the frequency of use of the device in which the battery is located per unit time; the charge and discharge rate and depth of discharge are determined based on the charge and discharge rate and depth of discharge under the actual working conditions of the battery; and the SOC is determined based on the amount of power of the battery when it is idle under the actual working conditions.

7. The battery life prediction method according to claim 1, characterized in that: During the alternating test, the battery is also subjected to the same preload force as it would be subjected to in actual use.

8. A battery life prediction device, comprising a processor and an accelerated test module, wherein the accelerated test module is used to provide a test environment; characterized in that: The processor is used to determine cycle parameters and calendar parameters for a battery test, control an accelerated test module to perform a charge-discharge cycle test on the battery for the number of cycles per unit time according to the cycle parameters within each unit time, and then perform a shelf test on the battery according to the calendar parameters within the remaining time of the unit time, detect the capacity loss of the battery at set intervals during the test, and use the detected capacity loss and the corresponding test time to fit a battery life model related to the capacity loss and the test time, determine the test time corresponding to when the capacity decays to the end of the battery life according to the battery life model, and use the test time as the battery life; the cycle parameters include the number of cycles per unit time, the cycle temperature, the charge-discharge rate, and the depth of discharge; the calendar parameters include the shelf temperature and the SOC; The unit time is divided according to the battery storage situation, so that the battery is only stored once per unit time.

9. The battery life prediction device according to claim 8, characterized in that: The accelerated test module includes a pressurizing unit, which is used to apply the same preload force to the battery as it is subjected to during actual use; the pressurizing unit includes a fixing plate with grooves on both sides and a binding wire, the fixing plate is used to be arranged on both sides of the battery, and the binding wire is used to bind the fixing plate and the battery together at the groove.

10. The battery life prediction device according to claim 8 or 9, characterized in that: There are N cycle temperatures and N shelf temperatures. The process for determining the N cycle temperatures is as follows: the atmospheric ambient temperature and the corresponding temperature rise in the cycle state are calculated under the actual working conditions of the battery in a set time period, and the N typical temperatures corresponding to the cycle state are determined based on the statistically obtained temperature range and the number of cycles at each temperature. These N typical temperatures are used as the cycle temperatures. The process for determining the N shelf temperatures is as follows: the indoor ambient temperature or outdoor atmospheric ambient temperature in the shelf state is calculated under the actual working conditions of the battery in a set time period, and the N typical temperatures corresponding to the shelf state are determined based on the statistically obtained temperature range and the shelf time at each temperature. These N typical temperatures are used as the shelf temperatures. N ≥ 2, and the set time period includes at least one annual time.

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