A battery SOH estimation method and device, electronic equipment and storage medium

Abstract

The application discloses a battery SOH estimation method and device, electronic equipment and storage medium. The method is to analyze the voltage relaxation curve of the battery and find that the voltage relaxation curve difference integral of the battery and the SOH value have a function relationship. Therefore, the voltage relaxation curve of the battery is classified in detail according to the classification basis of the charge-discharge rate. The voltage relaxation curve difference integral is obtained by performing the difference and integral operation on the limited voltage relaxation curve part. Then, the function relationship between the voltage relaxation curve difference integral and the SOH value under different charge-discharge rates is determined according to the function fitting. Finally, the SOH value of the battery to be measured is estimated based on the function relationship between the voltage relaxation curve difference integral and the SOH value under different charge-discharge rates.

Description

Technical Field

[0001] This invention relates to the field of battery technology, and in particular to a battery SOH estimation method, apparatus, electronic device, and storage medium. Background Technology

[0002] The new energy vehicle industry is booming, and new energy vehicles using lithium batteries as energy storage devices are becoming increasingly popular. However, lithium batteries have a limited lifespan, and in order to ensure the safe use of new energy vehicles, retired power batteries need to be replaced in a timely manner.

[0003] Currently, retired power batteries from electric vehicles or buses are primarily processed through multiple stages of disassembly, charging and discharging, and long-term static storage to screen out cells with good appearance, high safety, and high consistency. These cells are then reassembled for reuse in applications such as UPS systems, communication base stations, site vehicles, wind and solar power generation and energy storage, and streetlights. The State of Harm (SOH) value of retired batteries is closely related to their reuse applications; therefore, SOH value estimation is necessary. However, current SOH value estimation for retired batteries requires very comprehensive battery data, resulting in slow estimation speeds.

[0004] Therefore, existing technologies suffer from a slow speed in obtaining SOH estimates for batteries. Summary of the Invention

[0005] In view of this, it is necessary to provide a battery SOH estimation method, apparatus, electronic device and storage medium to address the problem of slow speed in obtaining SOH estimation values ​​in the existing technology.

[0006] To address the above problems, this invention provides a battery SOH estimation method, comprising:

[0007] Obtain SOH value samples of battery samples, and multiple voltage relaxation curve samples of battery samples at different charge and discharge rates;

[0008] By subtracting and integrating multiple voltage relaxation curve samples, we obtain multiple voltage relaxation curve difference and integral samples of the battery sample.

[0009] Based on multiple voltage relaxation curve difference integral samples and SOH value samples, the functional relationship between the voltage relaxation curve difference integral and SOH value under different charge and discharge rates is determined.

[0010] Obtain the voltage relaxation curve difference integral and charge / discharge rate of the battery under test, and determine the SOH value of the battery under test based on the functional relationship between the voltage relaxation curve difference integral corresponding to the charge / discharge rate and the SOH value, and the voltage relaxation curve difference integral.

[0011] Furthermore, the functional relationship between the voltage relaxation curve difference integral and the SOH value is as follows:

[0012] S ξ =f(SOH)=a×exp(b×SOH)+c×exp(d×SOH)

[0013] SOH=f -1 (S ξ )

[0014] Among them, S ξ Let SOH be the difference integral of the voltage relaxation curve, SOH be the SOH value, and a, b, c, and d be constants.

[0015] Furthermore, multiple voltage relaxation curve samples of the battery samples at different charge / discharge rates were obtained, including:

[0016] Adjust the SOC of the battery sample to obtain the target battery sample;

[0017] The target battery sample was subjected to pulse discharge, rest, pulse charge and rest in sequence according to constant current pulses with different charge and discharge rates, and the voltage relaxation curve sample of the target battery sample was obtained.

[0018] The durations of pulse discharge, rest, pulse charging, and rest are all preset to a first time.

[0019] Furthermore, the SOC of the battery sample is adjusted to obtain the target battery sample, including:

[0020] The battery sample is charged with a constant current at a first preset rate until the cutoff voltage is reached;

[0021] The battery sample is then charged using a constant voltage charging method until the cutoff current is reached.

[0022] The battery sample is discharged at a constant current of the first preset rate until the cutoff voltage is reached, and the first discharge time is recorded.

[0023] The target discharge time is determined based on the first discharge time, the SOC value, and the discharge time calculation formula.

[0024] The battery sample is discharged according to the target discharge time and then left to stand for a second preset time to obtain the target battery sample.

[0025] Furthermore, the formula for calculating the discharge time is:

[0026] t = (1 - N%) × t 放

[0027] Where t is the target discharge time, t 放 The first discharge time is N%, and N% is the SOC value.

[0028] Furthermore, the voltage relaxation curve samples include charging voltage relaxation curve samples and discharging voltage relaxation curve samples; by subtracting and integrating multiple voltage relaxation curve samples, multiple voltage relaxation curve difference-integral samples of the battery samples are obtained, including:

[0029] The voltage relaxation curve difference is obtained by subtracting the charging voltage relaxation curve samples and the discharging voltage relaxation curve samples at the same charge / discharge rate.

[0030] The voltage relaxation curve difference is integrated with a first preset time period to obtain multiple integrated samples of the voltage relaxation curve difference of the battery sample.

[0031] Furthermore, the first preset time is set to 10-30 seconds, and the second preset time is set to 30-120 minutes.

[0032] To address the above problems, the present invention also provides a battery SOH estimation device, comprising:

[0033] The sample acquisition module is used to acquire SOH value samples of battery samples, as well as multiple voltage relaxation curve samples of battery samples at different charge and discharge rates.

[0034] The voltage relaxation curve difference integral sample acquisition module is used to subtract and integrate multiple voltage relaxation curve samples to obtain multiple voltage relaxation curve difference integral samples of the battery sample.

[0035] The function relationship determination module is used to determine the functional relationship between the voltage relaxation curve difference integral and the SOH value at different charge / discharge rates based on multiple voltage relaxation curve difference integral samples and SOH value samples.

[0036] The SOH value estimation module is used to obtain the voltage relaxation curve difference integral and charge / discharge rate of the battery under test, and determine the SOH value of the battery under test based on the functional relationship between the voltage relaxation curve difference integral corresponding to the charge / discharge rate and the SOH value, and the voltage relaxation curve difference integral.

[0037] To address the aforementioned problems, the present invention also provides an electronic device, including a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, it implements the battery SOH estimation method as described above.

[0038] To address the aforementioned problems, the present invention also provides a storage medium storing computer program instructions, which, when executed by a computer, cause the computer to perform the battery SOH estimation method described above.

[0039] The beneficial effects of adopting the above technical solution are as follows: This invention provides a battery SOH estimation method, device, electronic device, and storage medium. This method, through data analysis of the battery's voltage relaxation curve, discovers that there is a functional relationship between the voltage relaxation curve difference integral and the SOH value. Therefore, the battery's voltage relaxation curve is meticulously classified based on the charge / discharge rate. By performing subtraction and integration operations on the defined voltage relaxation curve portions, the voltage relaxation curve difference integral is obtained. Then, based on function fitting, the functional relationship between the voltage relaxation curve difference integral and the SOH value under different charge / discharge rates is determined. Finally, based on the functional relationship between the voltage relaxation curve difference integral and the SOH value under different charge / discharge rates, the SOH value of the battery under test is estimated. Attached Figure Description

[0040] Figure 1 This is a flowchart illustrating an embodiment of the battery SOH estimation method provided by the present invention;

[0041] Figure 2 This is a schematic flowchart of an embodiment of the present invention for obtaining multiple voltage relaxation curve samples of battery samples at different charge-discharge rates.

[0042] Figure 3 This is a schematic flowchart of an embodiment of obtaining a target battery sample provided by the present invention;

[0043] Figure 4 This is a schematic flowchart of an embodiment of the present invention for obtaining multiple voltage relaxation curve difference integral samples of a battery sample.

[0044] Figure 5 This is a schematic diagram of the results of an embodiment of the voltage relaxation curve provided by the present invention;

[0045] Figure 6 A schematic diagram showing the results of an embodiment of the voltage relaxation curve difference provided by the present invention;

[0046] Figure 7 A schematic diagram of the result of an embodiment of the function fitting result provided by the present invention;

[0047] Figure 8 This is a schematic diagram of an embodiment of the battery SOH estimation device provided by the present invention;

[0048] Figure 9 A structural block diagram of an embodiment of the electronic device provided by the present invention. Detailed Implementation

[0049] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0050] Before describing the embodiments, let's first explain SOH and SOC:

[0051] State of Health (SOH), also known as battery health, represents the ratio of a battery's current capacity to its factory-set capacity, usually expressed as a percentage. Its value ranges from 0% to 100%. When SOH = 0%, the battery is completely unusable; when SOH = 100%, the battery is in excellent health.

[0052] Battery SOC refers to the state of charge of a battery, that is, the usable state of the remaining charge in the battery. Numerically, battery SOC is defined as the ratio of remaining capacity to battery capacity, usually expressed as a percentage, and ranges from 0 to 1. When SOC = 0, the battery is fully discharged. When SOC = 1, the battery is fully charged. Battery SOC cannot be measured directly; it can only be measured through the battery's terminal voltage.

[0053] A battery's relaxation curve is a curve showing how its capacity changes over time during charging and discharging. The relaxation curve reflects factors such as the battery's charge / discharge rate, aging level, and safety. By observing the relaxation curve, battery performance and lifespan can be assessed, and its behavior under different charge / discharge conditions can be predicted.

[0054] The new energy vehicle industry is booming, and new energy vehicles using lithium batteries as energy storage devices are becoming increasingly popular. However, lithium batteries have a limited lifespan, and in order to ensure the safe use of new energy vehicles, retired power batteries need to be replaced in a timely manner.

[0055] Currently, retired power batteries from electric vehicles or buses are primarily processed through multiple stages of disassembly, charging and discharging, and long-term static storage to screen out cells with good appearance, high safety, and high consistency. These cells are then reassembled for reuse in applications such as UPS systems, communication base stations, site vehicles, wind and solar power generation and energy storage, and streetlights. The State of Harm (SOH) value of retired batteries is closely related to their reuse applications; therefore, SOH value estimation is necessary. However, current SOH value estimation for retired batteries requires very comprehensive battery data, resulting in slow estimation speeds.

[0056] Therefore, existing technologies suffer from a slow speed in obtaining SOH estimates for batteries.

[0057] To address the aforementioned problems, this invention provides a battery SOH estimation method, apparatus, electronic device, and storage medium, which are described in detail below.

[0058] like Figure 1 As shown, Figure 1A flowchart illustrating an embodiment of the battery SOH estimation method provided by the present invention includes:

[0059] Step S101: Obtain the SOH value sample of the battery sample, and multiple voltage relaxation curve samples of the battery sample under different charge and discharge rates;

[0060] Step S102: Subtract and integrate multiple voltage relaxation curve samples respectively to obtain multiple voltage relaxation curve difference integral samples of the battery sample.

[0061] Step S103: Based on multiple voltage relaxation curve difference integral samples and SOH value samples, determine the functional relationship between the voltage relaxation curve difference integral and the SOH value at different charge / discharge rates;

[0062] Step S104: Obtain the voltage relaxation curve differential integral and charge / discharge rate of the battery under test, and determine the SOH value of the battery under test based on the functional relationship between the voltage relaxation curve differential integral corresponding to the charge / discharge rate and the SOH value, and the voltage relaxation curve differential integral.

[0063] In this embodiment, firstly, SOH value samples of battery samples and multiple voltage relaxation curve samples of battery samples at different charge / discharge rates are obtained; secondly, the multiple voltage relaxation curve samples are subtracted and integrated respectively to obtain multiple voltage relaxation curve difference integral samples of battery samples; then, based on the multiple voltage relaxation curve difference integral samples and SOH value samples, the functional relationship between the voltage relaxation curve difference integral and SOH value at different charge / discharge rates is determined; finally, the voltage relaxation curve difference integral and charge / discharge rate of the battery under test are obtained, and the SOH value of the battery under test is determined based on the functional relationship between the voltage relaxation curve difference integral and SOH value corresponding to the charge / discharge rate and the voltage relaxation curve difference integral.

[0064] In this embodiment, data analysis of the battery's voltage relaxation curves revealed a functional relationship between the voltage relaxation curve difference integral and the state of equilibrium (SOH) value. Therefore, the battery's voltage relaxation curves were meticulously classified based on the charge / discharge rate. By performing subtraction and integration operations on the defined portions of the voltage relaxation curves, the voltage relaxation curve difference integral was obtained. Then, based on function fitting, the functional relationship between the voltage relaxation curve difference integral and the SOH value under different charge / discharge rates was determined. Finally, based on the functional relationship between the voltage relaxation curve difference integral and the SOH value under different charge / discharge rates, the SOH value of the battery under test was estimated.

[0065] In a preferred embodiment, in step S101, for the obtained battery sample, in order to further obtain multiple voltage relaxation curve samples of the battery sample under different charge / discharge rates, such as... Figure 2 As shown, Figure 2This is a schematic flowchart illustrating an embodiment of the present invention for obtaining multiple voltage relaxation curve samples of a battery sample at different charge / discharge rates, including:

[0066] Step S111: Adjust the SOC of the battery sample to obtain the target battery sample;

[0067] Step S112: Perform pulse discharge, rest, pulse charge and rest on the target battery sample in sequence according to constant current pulses with different charge and discharge rates to obtain the voltage relaxation curve sample of the target battery sample.

[0068] The durations of pulse discharge, rest, pulse charging, and rest are all preset to a first time.

[0069] In this embodiment, firstly, the SOC of the battery sample is adjusted to obtain the target battery sample; then, the target battery sample is subjected to pulse discharge, rest, pulse charge and rest in sequence according to constant current pulses of different charge and discharge rates to obtain the voltage relaxation curve sample of the target battery sample.

[0070] In this embodiment, by adjusting all battery samples to the target state and performing a series of pulse discharge, rest, pulse charge and rest operations on the obtained target battery, the voltage relaxation curve of the target battery sample is obtained, which effectively ensures the reliability of the voltage relaxation curve and avoids errors caused by different initial states of the battery samples.

[0071] It should be noted that the duration of pulse discharge, rest, pulse charging, and rest is the same, all defined as the first preset time.

[0072] In a preferred embodiment, in step S111, in order to adjust the SOC of the battery sample to obtain the target battery sample, such as... Figure 3 As shown, Figure 3 A schematic flowchart of an embodiment of obtaining a target battery sample provided by the present invention includes:

[0073] Step S1111: Charge the battery sample with a constant current at a first preset rate until the cutoff voltage is reached;

[0074] Step S1112: Charge the battery sample again using constant voltage charging until the cutoff current is reached;

[0075] Step S1113: Discharge the battery sample with a constant current at a first preset rate until the cutoff voltage is reached, and record the first discharge time;

[0076] Step S1114: Determine the target discharge time based on the first discharge time, SOC value, and discharge time calculation formula;

[0077] Step S1115: Discharge the battery sample according to the target discharge time and let it stand for a second preset time to obtain the target battery sample.

[0078] In this embodiment, firstly, the battery sample is charged with a constant current at a first preset rate until the cutoff voltage is reached; then, the battery sample is charged with a constant voltage until the cutoff current is reached; next, the battery sample is discharged with a constant current at the first preset rate until the cutoff voltage is reached, and the first discharge time is recorded; and the target discharge time is determined based on the first discharge time, the SOC value, and the discharge time calculation formula; finally, the battery sample is discharged according to the target discharge time and left to stand for a second preset time to obtain the target battery sample.

[0079] In this embodiment, by strictly controlling the charge / discharge rate and the corresponding target discharge time and resting time, the standardization of the obtained target battery samples is effectively guaranteed, laying a solid foundation for obtaining voltage relaxation curve samples of the target battery samples in the future.

[0080] In a preferred embodiment, the formula for calculating the discharge time in step S1114 is:

[0081] t = (1 - N%) × t 放

[0082] Where t is the target discharge time, t 放 The first discharge time is N%, and N% is the SOC value.

[0083] In one specific embodiment, at room temperature, the lithium battery is charged to the cutoff voltage using a 0.5C constant current charging method, wherein the cutoff voltage for lithium iron phosphate is 3.65V and the cutoff voltage for ternary lithium batteries is 4.2V; then, it is charged to the cutoff current of 0.01C using a constant voltage charging method, at which point the charging is terminated, and the battery's SOC = 100%; next, the lithium battery is discharged to the cutoff voltage using a 0.5C constant current method, and the first discharge time t is recorded. 放 In other words, we obtained a fully charged battery.

[0084] Furthermore, the fully charged battery needs to be adjusted to SOC=N% according to the target discharge time, and then left to stand for a second preset time t1 to obtain the adjusted target battery sample.

[0085] In one specific embodiment, the second preset time t1 is set to 30-120 minutes.

[0086] Furthermore, in order to obtain voltage relaxation curves at different charge / discharge rates, composite pulse tests need to be performed at different charge / discharge rates.

[0087] In one specific embodiment, a constant current pulse discharge is first performed at 0.1C for a first preset time t2, followed by a resting period of t2; then a constant current pulse charge is performed at 0.1C for a charging period of t2, followed by a resting period of t2.

[0088] In one specific embodiment, the value of t2 is set to range from 10 to 30 seconds.

[0089] Obviously, it is also necessary to perform composite pulse tests at other charge / discharge rates, such as 0.2C, 0.3C, 0.4C, 0.5C, etc., which are not limited here.

[0090] In addition, to facilitate obtaining the voltage relaxation curve of the battery at any charge / discharge rate, the same battery can be subjected to pulse discharge, rest, pulse charge and rest operations at different rates in sequence, thereby enabling the rapid acquisition of multiple voltage relaxation curves of the battery.

[0091] It should be noted that, in order to ensure data consistency, for a specific battery or in the same test process, all the first preset times are set to be exactly the same.

[0092] In a preferred embodiment, in step S102, the voltage relaxation curve samples include charging voltage relaxation curve samples and discharging voltage relaxation curve samples; to obtain multiple voltage relaxation curve difference and integration samples of the battery samples by subtracting and integrating the multiple voltage relaxation curve samples respectively, such as... Figure 4 As shown, Figure 4 A schematic flowchart of an embodiment of the present invention for obtaining multiple voltage relaxation curve difference integral samples of a battery sample includes:

[0093] Step S121: Subtract the charging voltage relaxation curve samples and the discharging voltage relaxation curve samples at the same charge / discharge rate to obtain the voltage relaxation curve difference;

[0094] Step S122: Integrate the voltage relaxation curve difference, with the integration period being a first preset time, to obtain multiple integrated samples of the voltage relaxation curve difference of the battery sample.

[0095] In this embodiment, firstly, the difference between the charging voltage relaxation curve sample and the discharging voltage relaxation curve sample at the same charge / discharge rate is calculated to obtain the voltage relaxation curve difference; then, the voltage relaxation curve difference is integrated for a first preset time period to obtain multiple integrated samples of the voltage relaxation curve difference of the battery sample.

[0096] In this embodiment, the battery voltage relaxation curve is segmented to obtain the charging voltage relaxation curve and the discharging voltage relaxation curve at the same charge / discharge rate. Then, the difference between the charging voltage relaxation curve and the discharging voltage relaxation curve is obtained. Since the duration of pulse discharge, rest, pulse charging and rest are all the first preset time during the process of obtaining the voltage relaxation curve, it can be ensured that the time corresponding to the voltage relaxation curve difference is also the first preset time. Furthermore, the voltage relaxation curve difference is integrated with the integration period of the first preset time to obtain the corresponding voltage relaxation curve difference integral.

[0097] In one specific embodiment, such as Figure 5 As shown, Figure 5 This is a schematic diagram of the results of an embodiment of the voltage relaxation curve provided by the present invention. In this diagram, A1 and A2 correspond to the voltage relaxation curves when constant current pulse charging and discharging is performed at 0.1C, B1 and B2 correspond to the voltage relaxation curves when constant current pulse charging and discharging is performed at 0.2C, and C1 and C2 correspond to the voltage relaxation curves when constant current pulse charging and discharging is performed at 0.3C. These details will not be elaborated upon here.

[0098] Specifically, A1 corresponds to the voltage relaxation curve ξ of a 0.1C pulse discharge. n1 A2 corresponds to the voltage relaxation curve ξ of a 0.1C pulse charge. n2 Then the voltage relaxation curve difference ξ n =ξ n2 -ξ n1 In other words, the difference between the two parts of the image is calculated to obtain a completely closed area on the image. Finally, the voltage relaxation curve difference integral is obtained by integrating the difference between the voltage relaxation curves.

[0099] In one specific embodiment, such as Figure 6 As shown, Figure 6 This is a schematic diagram illustrating the results of an embodiment of the voltage relaxation curve difference provided by the present invention. Further, regarding the voltage relaxation curve difference ξ... n Integrating, we get:

[0100]

[0101] Among them, S ξ This is the difference integral of the voltage relaxation curve.

[0102] In a preferred embodiment, in step S103, the functional relationship between the voltage relaxation curve difference integral and the SOH value is as follows:

[0103] S ξ =f(SOH)=a×exp(b×SOH)+c×exp(d×SOH)

[0104] SOH=f -1 (S ξ )

[0105] Among them, S ξ Let SOH be the difference integral of the voltage relaxation curve, SOH be the SOH value, and a, b, c, and d be constants.

[0106] In one specific embodiment, such as Figure 7 As shown, Figure 7 This is a schematic diagram of the result of an embodiment of the function fitting result provided by the present invention, wherein SSE indicates that the function fitting error has reached the level of 10⁻⁶, R-squared indicates the reliability of the function fitting before adjustment, and adjusted squared indicates the reliability of the function fitting after adjustment.

[0107] It is evident that there is a relatively clear functional relationship between the voltage relaxation curve difference integral and the SOH value, and therefore, it can be used as a basis for estimating the SOH value of the battery.

[0108] Through data analysis of the battery's voltage relaxation curves using the above method, it was found that there is a functional relationship between the voltage relaxation curve difference integral and the SOH value. Therefore, the battery's voltage relaxation curves are further classified based on the charge / discharge rate. By performing subtraction and integration operations on the defined voltage relaxation curve portions, the voltage relaxation curve difference integral is obtained. Then, based on function fitting, the functional relationship between the voltage relaxation curve difference integral and the SOH value at different charge / discharge rates is determined. Finally, based on the functional relationship between the voltage relaxation curve difference integral and the SOH value at different charge / discharge rates, the SOH value of the battery under test is estimated.

[0109] To address the aforementioned problems, the present invention also provides a battery SOH estimation device, such as... Figure 8 As shown, Figure 8 This is a schematic diagram of an embodiment of the battery SOH estimation device provided by the present invention. The battery SOH estimation device 800 includes:

[0110] The sample acquisition module 801 is used to acquire the SOH value sample of the battery sample and multiple voltage relaxation curve samples of the battery sample under different charge and discharge rates.

[0111] The voltage relaxation curve difference integral sample acquisition module 802 is used to perform subtraction and integration on multiple voltage relaxation curve samples to obtain multiple voltage relaxation curve difference integral samples of the battery sample.

[0112] The function relationship determination module 803 is used to determine the function relationship between the voltage relaxation curve difference integral and the SOH value under different charge and discharge rates based on multiple voltage relaxation curve difference integral samples and SOH value samples.

[0113] The SOH value estimation module 804 is used to obtain the voltage relaxation curve difference integral and charge / discharge rate of the battery under test, and determine the SOH value of the battery under test based on the functional relationship between the voltage relaxation curve difference integral corresponding to the charge / discharge rate and the SOH value, and the voltage relaxation curve difference integral.

[0114] The present invention also provides an electronic device, such as... Figure 9 As shown, Figure 9 This is a structural block diagram of an embodiment of the electronic device provided by the present invention. The electronic device 900 can be a computing device such as a mobile terminal, desktop computer, laptop, handheld computer, and server. The electronic device 900 includes a processor 901, a memory 902, and a display 903, wherein the memory 902 stores a battery SOH estimation program.

[0115] In some embodiments, memory 902 may be an internal storage unit of a computer device, such as a hard disk or memory. In other embodiments, memory 902 may be an external storage device of a computer device, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc. Further, memory 902 may include both internal and external storage units of the computer device. Memory 902 is used to store application software and various types of data installed on the computer device, such as program code for installing the computer device. Memory 902 can also be used to temporarily store data that has been output or will be output. In one embodiment, the battery SOH estimation program can be executed by processor 901 to implement the battery SOH estimation methods of various embodiments of the present invention.

[0116] In some embodiments, processor 901 may be a central processing unit (CPU), microprocessor or other data processing chip, used to run program code stored in memory 902 or process data, such as executing a battery SOH estimation program.

[0117] In some embodiments, display 903 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. Display 903 is used to display information from electronic device 900 and to display a visual user interface. Components 901-903 of electronic device 900 communicate with each other via a system bus.

[0118] This embodiment also provides a computer-readable storage medium storing a battery SOH estimation program thereon. When the computer processor executes the program, it implements the battery SOH estimation method as described in any of the above technical solutions.

[0119] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, database, or other storage media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0120] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for estimating the state of harmonics (SOH) of a battery, characterized in that, include: Obtain SOH value samples of battery samples, and multiple voltage relaxation curve samples of the battery samples at different charge and discharge rates; The multiple voltage relaxation curve samples are subtracted and integrated respectively to obtain multiple voltage relaxation curve difference integral samples of the battery sample. Based on the multiple voltage relaxation curve difference integral samples and the SOH value samples, the functional relationship between the voltage relaxation curve difference integral and the SOH value under different charge / discharge rates is determined; Obtain the voltage relaxation curve difference integral and charge / discharge rate of the battery under test, and determine the SOH value of the battery under test based on the functional relationship between the voltage relaxation curve difference integral corresponding to the charge / discharge rate and the SOH value, and the voltage relaxation curve difference integral.

2. The battery SOH estimation method according to claim 1, characterized in that, The functional relationship between the voltage relaxation curve difference integral and the SOH value is as follows: S ξ =f(SOH)=a×exp(b×SOH)+c×exp(d×SOH) SOH=f -1 (S ξ ) Among them, S ξ The voltage relaxation curve difference integral is given, SOH is the SOH value, and a, b, c, and d are all constants.

3. The battery SOH estimation method according to claim 1, characterized in that, Obtain multiple voltage relaxation curve samples of the battery sample at different charge / discharge rates, including: Adjust the SOC of the battery sample to obtain the target battery sample; The target battery sample was subjected to pulse discharge, rest, pulse charge and rest in sequence according to constant current pulses with different charge and discharge rates, and the voltage relaxation curve sample of the target battery sample was obtained. The duration of pulse discharge, rest, pulse charging, and rest is a first preset time.

4. The battery SOH estimation method according to claim 3, characterized in that, The adjustment of the SOC of the battery sample to obtain the target battery sample includes: The battery sample is charged with a constant current at a first preset rate until the cutoff voltage is reached; The battery sample is then charged using a constant voltage charging method until the cutoff current is reached; The battery sample is discharged at a constant current of a first preset rate until the cutoff voltage is reached, and the first discharge time is recorded. The target discharge time is determined based on the first discharge time, SOC value, and discharge time calculation formula; The battery sample is discharged according to the target discharge time and left to stand for a second preset time to obtain the target battery sample.

5. The battery SOH estimation method according to claim 4, characterized in that, The formula for calculating the discharge time is: t=(1-N%)×t 放 Where t is the target discharge time, t 放 The first discharge time is N%, and the SOC value is N%.

6. The battery SOH estimation method according to claim 5, characterized in that, The voltage relaxation curve samples include charging voltage relaxation curve samples and discharging voltage relaxation curve samples; The step of subtracting and integrating the plurality of voltage relaxation curve samples to obtain a plurality of voltage relaxation curve difference-integral samples of the battery sample includes: The voltage relaxation curve difference is obtained by subtracting the charging voltage relaxation curve sample and the discharging voltage relaxation curve sample at the same charge / discharge rate. The voltage relaxation curve difference is integrated, with the integration period being the first preset time, to obtain multiple integrated samples of the voltage relaxation curve difference of the battery sample.

7. The battery SOH estimation method according to claim 4, characterized in that, The first preset time is set to 10-30 seconds, and the second preset time is set to 30-120 minutes.

8. A battery SOH estimation device, characterized in that, include: The sample acquisition module is used to acquire the SOH value sample of the battery sample, and multiple voltage relaxation curve samples of the battery sample under different charge and discharge rates. The voltage relaxation curve difference integral sample acquisition module is used to perform subtraction and integration on the multiple voltage relaxation curve samples respectively to obtain multiple voltage relaxation curve difference integral samples of the battery sample. The function relationship determination module is used to determine the function relationship between the voltage relaxation curve difference integral and the SOH value under different charge / discharge rates based on the multiple voltage relaxation curve difference integral samples and the SOH value samples. The SOH value estimation module is used to obtain the voltage relaxation curve difference integral and charge / discharge rate of the battery under test, and determine the SOH value of the battery under test based on the functional relationship between the voltage relaxation curve difference integral and the SOH value corresponding to the charge / discharge rate and the voltage relaxation curve difference integral.

9. An electronic device, characterized in that, It includes a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, it implements the battery SOH estimation method as described in any one of claims 1-7.

10. A storage medium, characterized in that, The storage medium stores computer program instructions, which, when executed by a computer, cause the computer to perform the battery SOH estimation method according to any one of claims 1 to 7.

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