Battery Life Prediction Method and Computer-Readable Storage Medium

Abstract

The present invention provides a battery life prediction method and a computer-readable storage medium. The battery life prediction method of the present invention includes the following steps: S1. Select the battery to be evaluated, analyze according to the calibrated life cycle of the battery and the temperature field of the environment where the battery is located, obtain the number of charge-discharge test cycles m of the battery, and analyze according to the number of cycles m to obtain the cycle mileage L2; S2. Based on the temperature distribution of the temperature field, simulate the usage state of the battery at the vehicle end, and formulate a preset working condition for the battery charge-discharge test; S3. Analyze and adjust according to the preset working condition and the cycle mileage L2 to obtain the measured working condition and the measured cycle period for the battery charge-discharge test; S4. Under the measured working condition, continuously perform charge-discharge tests on the battery within the measured cycle period to obtain the measured life cycle of the battery. The battery life prediction method of the present invention can more accurately simulate the usage working condition of the battery at the vehicle end and obtain the actual service life of the battery.

Description

Technical Field

[0001] The present invention relates to the technical field of battery life, and particularly to a method for predicting battery life. At the same time, the present invention also relates to a computer-readable storage medium storing a program capable of executing the battery life prediction method. Background Art

[0002] For power batteries, service life is a very important characterization parameter. The existing battery life test methods are limited by factors such as project cycle and cost, and mainly perform constant rate / operating condition charge and discharge tests, and use the number of cycles and SOH as the end conditions during the test to evaluate the battery life.

[0003] Although the above method can estimate the health trend of battery products, the test conditions of the battery are fixed conditions, lacking consideration of environmental factors in the actual use state of the vehicle, and unable to cope with the diverse aging mechanisms, significant equipment variability, and various dynamic operating conditions at the vehicle end. Therefore, it is impossible to effectively evaluate the service life of the battery. Summary of the Invention

[0004] In view of this, the present invention aims to propose a method for predicting battery life to effectively evaluate the service life of the battery.

[0005] To achieve the above object, the technical solution of the present invention is realized as follows:

[0006] A method for predicting battery life, the method comprising the following steps:

[0007] S1. Select the battery to be evaluated, analyze according to the calibrated life cycle of the battery and the temperature field of the environment where the battery is located, obtain the number of cycles m of the charge and discharge test of the battery, and analyze according to the number of cycles m to obtain the cycle mileage L2;

[0008] S2. Based on the temperature distribution of the temperature field, simulate the use state of the battery at the vehicle end, and formulate a preset working condition for the charge and discharge test of the battery;

[0009] S3. Analyze and adjust according to the preset working condition and the cycle mileage L2 to obtain a determination working condition and a determination cycle period for the charge and discharge test of the battery;

[0010] S4. Continuously perform charge and discharge tests on the battery within the determination cycle period under the determination working condition to obtain the determined life cycle of the battery;

[0011] S5. Compare and analyze the determined life cycle with the calibrated life cycle to determine the actual life cycle of the battery.

[0012] Further, in S1, the calibrated service life includes a calibrated number of years n1 for characterizing the theoretical time life of the battery in the vehicle-end usage state, where n1 = 1, 2, 3... N, N being an integer, and a calibrated mileage L0 (km) within the theoretical cycles of the battery in the vehicle-end usage state; and / or,

[0013] The temperature field distribution is the spring sub-temperature field, summer sub-temperature field, autumn sub-temperature field, and winter sub-temperature field in which the battery is located in the vehicle-end usage state.

[0014] Further, analyze according to the calibrated number of years n1 and the calibrated mileage L0 to obtain the number of large cycles M and the large cycle mileage L1, and the number of large cycles M = n1, the large cycle mileage L1 = L0 / M; according to the distribution of the temperature field and the large cycle mileage L1, obtain the number of cycles m and the cycle mileage L2, the value of the number of cycles m is the number of sub-temperature fields in the temperature field, and the cycle mileage L2 = L1 / m.

[0015] Further, in S2, the preset working conditions include temperature conditions, charge-discharge conditions, and road cycle conditions; among them, the charge-discharge conditions include the single charging time, single discharging time, and standing time of the battery; the road cycle conditions include at least one of high-speed driving conditions, highway driving conditions, and harsh driving conditions; the temperature conditions include the ambient temperature conditions obtained based on the temperature distribution of the temperature field, and the working temperature conditions obtained by analyzing based on the ambient temperature conditions, the charge-discharge conditions, and the road cycle conditions.

[0016] Further, the ambient temperature conditions include the temperature value K with the largest proportion in each of the spring sub-temperature field, summer sub-temperature field, autumn sub-temperature field, and winter sub-temperature field; the working temperature conditions include the self-generated heat temperature and water-cooled temperature of the battery in the vehicle-end usage state.

[0017] Further, in S3, if the measured cycle period is greater than the calibrated cycle period, then adjust and analyze the measured working conditions so that the measured cycle period is not greater than the calibrated cycle period.

[0018] Further, the calibrated cycle period is 365 days.

[0019] Further, in S4, perform an RPT test on the battery during the charge-discharge test process, and analyze according to the RPT measurement parameters and the number of cycles m to obtain the measured service life.

[0020] Further, in S4, the measurement life cycle includes a measurement period n2 for characterizing the actual time life of the battery under the use condition at the vehicle end and a measurement mileage L4 for characterizing the actual cycle within the use condition at the vehicle end of the battery.

[0021] A computer-readable storage medium stores a computer program thereon. When the computer program runs on a processor, it executes the battery life prediction method of the present invention.

[0022] Compared with the prior art, the present invention has the following advantages:

[0023] The battery life prediction method of the present invention can more accurately simulate the use conditions of the battery at the vehicle end by combining the temperature field of the environment where the battery is located, and can effectively evaluate the actual use state of the battery before leaving the production line at the vehicle end by combining the calibrated life cycle of the battery, so as to obtain the actual service life of the battery, which is beneficial to evaluating the service life and system performance of the battery, and enables rapid formulation of battery improvement strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The schematic embodiments and descriptions thereof of the present invention are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0025] Figure 1 is a flowchart of the battery life prediction method according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other.

[0027] The present invention will be described in detail below with reference to the drawings and in conjunction with the embodiments.

[0028] This embodiment relates to a battery life prediction method, which can more accurately simulate the use conditions of the battery at the vehicle end, so as to effectively evaluate the actual use state of the battery before leaving the production line at the vehicle end and obtain the actual service life of the battery.

[0029] In the overall design, as Figure 1 shown, the method includes the following steps:

[0030] S1. Select the battery to be evaluated, analyze according to the calibrated life cycle of the battery and the temperature field of the environment where the battery is located, obtain the number of cycles m of the battery charge and discharge test, and analyze according to the number of cycles m to obtain the cycle mileage L2;

[0031] S2. Based on the temperature distribution of the temperature field, simulate the use state of the battery at the vehicle end and formulate a preset working condition for the battery charge and discharge test;

[0032] S3. Analyze and adjust according to the preset working conditions and the driving range L2 to obtain the determination working conditions and the determination cycle period for the battery charge and discharge test;

[0033] S4. Under the determination working conditions, continuously perform charge and discharge tests on the battery within the determination cycle period to obtain the determination life cycle of the battery;

[0034] S5. Compare and analyze the determination life cycle with the calibrated life cycle to determine the actual life cycle of the battery.

[0035] Preferably, in this embodiment, in S1, the calibrated life cycle includes the calibrated years n1 for characterizing the theoretical time life of the battery under the vehicle-end usage state, where n1 = 1, 2, 3... N, N is an integer, and the calibrated mileage L0 (km) for characterizing the theoretical cycle within the vehicle-end usage state of the battery. At the same time, the temperature field distribution is the spring sub-temperature field, summer sub-temperature field, autumn sub-temperature field, and winter sub-temperature field where the battery is under the vehicle-end usage state.

[0036] The temperature field here refers to the temperature field of the region where the battery is put into use. The temperature ranges of the spring sub-temperature field, summer sub-temperature field, autumn sub-temperature field, and winter sub-temperature field are the temperature ranges corresponding to the spring days, summer days, autumn days, and winter days respectively in the region where the battery is put into use.

[0037] In this embodiment, as a preferred implementation form, analyze according to the calibrated years n1 and the calibrated mileage L0 to obtain the large cycle number M and the large cycle mileage L1. And the large cycle number M = n1, the large cycle mileage L1 = L0 / M. Moreover, according to the distribution of the temperature field and the large cycle mileage L1, obtain the cycle number m and the cycle mileage L2. The cycle number m takes the value of the number of sub-temperature fields in the temperature field, and the cycle mileage L2 = L1 / m. The values of the large cycle number M and the cycle number m here are generally integers.

[0038] In addition, in S2, the above preset working conditions include temperature working conditions, charge and discharge working conditions, and road cycle working conditions. Among them, the charge and discharge working conditions include the single charging time, single discharging time, and static time of the battery. The road cycle working conditions include at least one of high-speed driving conditions, highway driving conditions, and harsh driving conditions. The temperature working conditions include the ambient temperature conditions obtained based on the temperature distribution of the temperature field, and the working temperature conditions obtained by analyzing based on the ambient temperature conditions, charge and discharge working conditions, and road cycle working conditions.

[0039] Of course, the above road cycle conditions are used to characterize the operating conditions of the vehicle end during the road cycle (Drive cycle) test. For the operating conditions under the road cycle test not described in this embodiment, reference can be made to the actual operating conditions in the prior art under the road cycle test.

[0040] During specific implementation, the above environmental temperature conditions include the temperature value K with the largest proportion in each of the spring sub-temperature field, summer sub-temperature field, autumn sub-temperature field, and winter sub-temperature field. At the same time, the operating temperature conditions include the self-generated heat temperature and the water-cooled temperature of the battery in the vehicle end usage state.

[0041] The above temperature value K with the largest proportion refers to the temperature value with the largest proportion among the temperatures of all days in a single-season sub-temperature field. For example, in the spring sub-temperature field, the number of spring days is 90 days, and the temperature range within 90 days is 3 - 16°C. Among them, the number of days with a temperature of 8°C is 68 days, which has the largest proportion. Then the temperature value K is taken as 8°C. Thus, by analogy, the temperature value K with the largest proportion in the summer sub-temperature field, autumn sub-temperature field, and winter sub-temperature field is obtained respectively. For example, the temperature value K can be taken as 31°C, 20°C, and -3°C respectively.

[0042] In this embodiment, in S3, if the measured cycle period is greater than the calibrated cycle period, the measured operating conditions are adjusted and analyzed so that the measured cycle period is not greater than the calibrated cycle period. During specific implementation, the calibrated cycle period generally takes a value of 365 days to control the cycle period and cost of the battery life assessment. That is, when the measured cycle period is greater than the calibrated cycle period, it is necessary to analyze the measured operating conditions and accelerate the test speed by adjusting the parameters in the operating conditions so that the measured cycle period is equal to or less than the calibrated cycle period.

[0043] As a preferred implementation form, in S4 of this embodiment, an RPT test ((Reference Performance Test) is performed on the battery during the charge and discharge test process, and analysis is carried out based on the RPT measurement parameters and the number of cycles m to obtain the measured life cycle. Also as a preferred implementation form, in S4, the above measured life cycle includes the measured number of years n2 used to characterize the actual time life of the battery in the vehicle end usage state and the measured mileage L4 used to characterize the actual cycle within the vehicle end usage state of the battery.

[0044] Specifically, the above RPT measurement parameters may include battery capacity, AC resistance, DC resistance, etc. By analyzing according to the RPT measurement parameters, the single-cycle test life cycle within a single cycle number can be obtained. The above-mentioned measured life cycle includes the single-cycle measured life cycle within a single cycle number and the total measured life cycle after completing the entire cycle number, corresponding to the single-cycle calibration life cycle and the total calibration life cycle in the calibration life cycle respectively. Furthermore, the actual life cycle of the battery within a single cycle number and the total actual life cycle can be obtained through comparison and analysis.

[0045] Next, based on a specific test, the method of the present invention will be further described to verify the feasibility of the method of the present invention. The specific test process and test parameters are as follows:

[0046] (1) Select an EOL (End-of-life) battery product a;

[0047] (2) Determine the calibration life cycle of battery product a: the calibration years n1 = 8 (years), and the calibration mileage L0 = 16w (km);

[0048] (3) Analyze according to the calibration years n1 and the calibration mileage L0 to obtain the large cycle number M and the large cycle mileage L1. And the large cycle number M = n1 = 8, and the large cycle mileage L1 = L0 / M = 16w / 8 = 20000 (km);

[0049] Obtain the temperature field distribution of the area where battery product a is put into use. The temperature field distribution is the spring sub-temperature field, the summer sub-temperature field, the autumn sub-temperature field, and the winter sub-temperature field. Obtain the cycle number m as 4 cycles (spring / summer / autumn / winter);

[0050] At the same time, count the temperature ranges of the spring sub-temperature field, the summer sub-temperature field, the autumn sub-temperature field, and the winter sub-temperature field in the area where the battery product a is put into use, and count the distribution ratio of the temperature in each sub-temperature field with an interval of 5°C;

[0051] (4) According to the distribution ratio of the temperature in each sub-temperature field, obtain the temperature with the largest ratio (the temperature value with the largest proportion among all the temperatures of all days in a single-season sub-temperature field) as the temperature value within a single cycle number. For example, K(spring; spring) = 8°C, K(summer; summer) = 31°C, Q(autumn; autumn) = 20°C, Q(winter; winter) = -3°C.

[0052] (5) Obtain the cycle mileage \(L2 = L1 / m = 20000 / 4 = 5000\) (km), that is, within a single cycle, a driving condition of 5000 (km) needs to be completed. Based on the temperature distribution of the temperature field and the usage scenario, select the corresponding road cycle (Drivecycle) test to simulate the usage state and working conditions of the battery at the vehicle end, and formulate the preset working conditions for the battery charge and discharge test.

[0053] (6) According to the preset working conditions (in addition to fixed working condition parameters such as ambient temperature conditions, charge and discharge working conditions, and road cycle working conditions, add RPT tests to calibrate the life cycle of battery product a within each single cycle, and add working temperature conditions such as water-cooling temperature and speed) and the cycle mileage L2, input the corresponding required condition parameters, and calculate the theoretical cycle period (for example, 500 days) through simulation software;

[0054] At this time, the theoretical cycle period is greater than the calibrated cycle period (for example, 365 days). Therefore, it is necessary to adjust the preset working conditions until the theoretical cycle period is less than or equal to the calibrated cycle period. Thus, obtain the measured working conditions (adjusted preset working conditions) and the measured cycle period (adjusted theoretical cycle period) for the battery charge and discharge test.

[0055] (7) Under the measured working conditions, conduct continuous charge and discharge tests on the battery within the measured cycle period to obtain the measured life cycle of the battery (measured years \(n2\) and measured mileage \(L4\)).

[0056] (8) Compare and analyze the measured life cycle (measured years \(n2\) and measured mileage \(L4\)) with the calibrated life cycle (calibrated years and calibrated mileage) to determine the actual life cycle of the battery, so as to improve battery product a.

[0057] It should be noted that in the above (6), for the convenience of distinction and description, the measured cycle period calculated before the measured cycle period (the final measured cycle period) for the battery charge and discharge test is called the theoretical cycle period.

[0058] The battery life prediction method described in this embodiment can more accurately simulate the working conditions of the battery at the vehicle end by combining the temperature field of the environment where the battery is located, and can effectively evaluate the actual usage state of the battery before leaving the vehicle end by combining the calibrated life cycle of the battery, obtain the actual service life of the battery, and is conducive to evaluating the service life and system performance of the battery, so that a battery improvement strategy can be quickly formulated.

[0059] This embodiment also provides a computer-readable storage medium, on which a computer program is stored. When the computer program runs on a processor, it executes the battery life prediction method in this embodiment.

[0060] For all or part of the processes in the methods of the above embodiments, those skilled in the art can understand that they are completed by computer programs or instructions related hardware. The computer program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, a processor, a computer program or other media used in the embodiments provided in the present application can include non-volatile and / or volatile memories.

[0061] Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory.

[0062] Of course, the above-mentioned RAM can be obtained in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), double data rate SDRAM (DDR SDRAM), Rambus direct RAM (RDRAM), synchronous DRAM (SDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0063] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A battery life prediction method, characterized in that, The method includes the following steps: S1. Select the battery to be evaluated, analyze according to the calibrated service life of the battery and the temperature field of the environment where the battery is located, obtain the number of cycles m of the charge and discharge test of the battery, and analyze according to the number of cycles m to obtain the driving range L2; S2. Based on the temperature distribution of the temperature field, simulate the usage state of the battery at the vehicle end, and formulate a preset working condition for the charge and discharge test of the battery; S3. Analyze and adjust according to the preset working condition and the driving range L2 to obtain a determination working condition and a determination cycle period for the charge and discharge test of the battery; S4. Under the determination working condition, continuously perform charge and discharge tests on the battery within the determination cycle period to obtain the determined service life of the battery; S5. Compare and analyze the determined service life with the calibrated service life to determine the actual service life of the battery; In S1, the calibrated service life includes a calibrated service life n1 for characterizing the theoretical time life of the battery under the usage state at the vehicle end, where n1 = 1, 2, 3... N, N is an integer, and a calibrated driving range L0 (km) for characterizing the theoretical cycle within the usage state of the battery at the vehicle end; and / or, The temperature field distribution is the spring sub-temperature field, summer sub-temperature field, autumn sub-temperature field, and winter sub-temperature field where the battery is located under the usage state at the vehicle end; Analyze according to the calibrated service life n1 and the calibrated driving range L0 to obtain the number of large cycles M and the large driving range L1, and the number of large cycles M = n1, and the large driving range L1 = L0 / M; According to the distribution of the temperature field and the large driving range L1, obtain the number of cycles m and the driving range L2, the value of the number of cycles m is the number of sub-temperature fields in the temperature field, and the driving range L2 = L1 / m; In S3, if the determination cycle period is greater than the calibrated cycle period, adjust and analyze the determination working condition so that the determination cycle period is not greater than the calibrated cycle period.

2. The battery life prediction method according to claim 1, wherein: In S2, the preset working condition includes a temperature working condition, a charge and discharge working condition, and a road cycle working condition; wherein, The charge and discharge working condition includes the single charging time, single discharging time, and static time of the battery; The road cycle working condition includes at least one of a high-speed driving condition, a highway driving condition, and a harsh driving condition; The temperature working condition includes the ambient temperature condition obtained based on the temperature distribution of the temperature field, and the working temperature condition obtained by analyzing based on the ambient temperature condition, the charge and discharge working condition, and the road cycle working condition.

3. The battery life prediction method according to claim 2, wherein: The ambient temperature condition includes the temperature value K with the largest proportion in each of the spring sub-temperature field, summer sub-temperature field, autumn sub-temperature field, and winter sub-temperature field; The working temperature condition includes the self-generated heat temperature and the water-cooled temperature of the battery under the usage state at the vehicle end.

4. The battery life prediction method according to claim 1, wherein: The calibration cycle period is 365 days.

5. The battery life prediction method according to any one of claims 1 to 4, wherein: In S4, perform an RPT test on the battery during the charge and discharge test process, and analyze according to the RPT measurement parameters and the number of cycles m to obtain the measured life cycle.

6. The battery life prediction method according to claim 5, wherein: In S4, the measured life cycle includes the measured number of years n2 for characterizing the actual time life of the battery in the vehicle-end usage state and the measured mileage L4 for characterizing the actual cycles of the battery in the vehicle-end usage state.

7. A computer storage medium, wherein: Computer program instructions are stored on the computer storage medium, and when the computer program instructions are executed by a processor, the battery life prediction method described in any one of claims 1-6 is implemented.

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