A battery usage estimation method, device, electronic device and readable storage medium

Abstract

The present invention provides a battery usage estimation method, device, electronic device and readable storage medium, the method comprising: obtaining first mileage data of a target battery when it is taken out of a battery swap cabinet and second mileage data when it is put into the battery swap cabinet, as well as first state of charge data when it is taken out of the battery swap cabinet and second state of charge data when it is put into the battery swap cabinet; calculating target indicator data of the target battery according to the first mileage data, the second mileage data, the first state of charge data, the second state of charge data and the standard capacity of the target battery, the target indicator data being used to characterize the battery's mileage per ampere-hour; when the target indicator data is greater than or equal to a preset first threshold value, confirming that the target battery meets the service life condition; when the target indicator data is less than the preset first threshold value, confirming that the target battery does not meet the service life condition, and setting the battery as a battery to be retired.

Description

Technical Field

[0001] The present invention relates to the field of battery technology, and in particular to a battery usage estimation method, device, electronic device and readable storage medium. Background Art

[0002] Batteries can effectively store and release electrical energy and are important energy devices widely used in fields such as electric vehicles. In related technologies, as the battery is used for a longer time, its performance will show a downward trend. In some electronic devices, after the battery performance drops to a certain level, the battery will no longer meet the conditions for use and needs to be replaced. In related technologies, the prediction of the battery life is calculated based on the material characteristic parameters of the battery itself, ignoring the battery's condition during use. There are cases where the battery can still be used but is judged to be unqualified for use, resulting in a large difference between the predicted battery life and the actual service life.

[0003] It can be seen that in the related art, there is a problem that the battery life prediction ignores the usage situation, resulting in low accuracy of the predicted life. Summary of the invention

[0004] Embodiments of the present invention provide a battery usage estimation method, device, electronic device and readable storage medium to solve the problem in the prior art that the battery life prediction ignores the usage and thus has a low accuracy rate in the prediction of life.

[0005] To solve the above problems, the present invention is achieved as follows:

[0006] In a first aspect, an embodiment of the present invention provides a battery usage estimation method, comprising:

[0007] Obtain target mileage data and target state of charge data of the target battery, wherein the target mileage data includes first mileage data when the battery is taken out of the battery swap cabinet and second mileage data when the battery is put into the battery swap cabinet, and the target state of charge data includes first state of charge data when the battery is taken out of the battery swap cabinet and second state of charge data when the battery is put into the battery swap cabinet;

[0008] Subtracting the second mileage data from the first mileage data to obtain a single driving mileage, then subtracting the second state of charge data from the first state of charge data to obtain a single state of charge consumption, then multiplying the quotient of the single driving mileage and the single state of charge consumption by the standard capacity of the target battery to obtain the target indicator data of the target battery, the target indicator data being used to characterize the driving mileage per ampere-hour of the battery;

[0009] When the target indicator data is greater than or equal to a preset first threshold, confirming that the target battery meets the service life condition;

[0010] When the target indicator data is less than the first preset threshold, it is determined that the target battery does not meet the service life condition, and the battery is set as a battery to be retired.

[0011] In a second aspect, an embodiment of the present invention further provides a battery usage estimation device, comprising:

[0012] A first acquisition module is used to acquire target mileage data and target state of charge data of a target battery, wherein the target mileage data includes first mileage data when taken out of a battery swap cabinet and second mileage data when put into a battery swap cabinet, and the target state of charge data includes first state of charge data when taken out of a battery swap cabinet and second state of charge data when put into a battery swap cabinet;

[0013] a first calculation module, configured to subtract the second mileage data from the first mileage data to obtain a single driving mileage, then subtract the second state of charge data from the first state of charge data to obtain a single state of charge consumption, then multiply the quotient of the single driving mileage and the single state of charge consumption by the standard capacity of the target battery to obtain target indicator data of the target battery, wherein the target indicator data is used to characterize the driving mileage per ampere-hour of the battery;

[0014] A first processing module, configured to confirm that the target battery meets the service life condition when the target indicator data is greater than or equal to a preset first threshold;

[0015] The second processing module is used to confirm that the target battery does not meet the service life condition when the target indicator data is less than the first preset threshold value, and set the battery as a battery to be retired.

[0016] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps in the battery usage estimation method as described in the first aspect above.

[0017] In a fourth aspect, an embodiment of the present invention further provides a readable storage medium for storing a program, wherein when the program is executed by a processor, the steps in the battery usage estimation method as described in the first aspect are implemented.

[0018] In an embodiment of the present invention, target indicator data of the target battery is calculated based on the first mileage data, the second mileage data, the first state of charge data, the second state of charge data and the standard capacity of the target battery, and then the target indicator data is compared with the first threshold to confirm whether the target battery meets the service life conditions, thereby realizing the prediction of the battery life according to the usage conditions, and improving the accuracy of the prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0020] Figure 1 is a flow chart of a battery usage estimation method provided by an embodiment of the present invention;

[0021] Figure 2 is a structural diagram of a battery usage estimation device provided by an embodiment of the present invention;

[0022] Figure 3 It is a structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] See also Figure 1 , Figure 1 is a flow chart of a battery usage estimation method provided by an embodiment of the present invention. Figure 1 As shown, the following steps are included:

[0025] Step S101, obtain the target mileage data and target state of charge data of the target battery, the target mileage data includes the first mileage data when taken out of the battery swap cabinet and the second mileage data when put into the battery swap cabinet, the target state of charge data includes the first state of charge data when taken out of the battery swap cabinet and the second state of charge data when put into the battery swap cabinet.

[0026] It can be understood that the battery is taken out of the battery swap cabinet when it is needed, and the battery is put back into the battery swap cabinet after use. The battery has a battery management system (BMS) module. When the battery is installed on the vehicle, the BMS can obtain the vehicle's mileage and record it. Among them, the recording method is to accumulate new mileage on the original mileage data. At the same time, the BMS can record the battery's state of charge (State of Charge, SOC). When the battery is taken out of the battery swap cabinet, the BMS module uploads the battery's current mileage and SOC, that is, the first mileage data and the first state of charge data; when the battery is placed in the battery swap cabinet, the BMS module uploads the battery's current mileage and SOC, that is, the second mileage data and the second state of charge data.

[0027] Step S102, subtracting the second mileage data from the first mileage data to obtain a single driving mileage, then subtracting the second state of charge data from the first state of charge data to obtain a single state of charge consumption, then multiplying the quotient of the single driving mileage and the single state of charge consumption by the standard capacity of the target battery to obtain the target indicator data of the target battery, and the target indicator data is used to characterize the driving mileage per ampere-hour of the battery.

[0028] It is understandable that the battery's mileage per ampere-hour can directly reflect the battery's condition during use. Among them, there are differences in the mileage data and SOC data when the battery is taken out of the battery swap cabinet and put in. By subtracting them, we can get the single mileage and single state of charge consumption. The single state of charge consumption is multiplied by the standard capacity of the battery to get the single power consumption, and then confirm the target indicator data of the target battery.

[0029] Among them, the unit of battery mileage per ampere-hour is Km / Ah.

[0030] Step S103, when the target indicator data is greater than or equal to a preset first threshold, confirming that the target battery meets the service life condition.

[0031] The first threshold is a preset value of the mileage per ampere-hour that the battery meets. If the target indicator data is greater than or equal to the preset first threshold, it can be considered that the battery capacity still meets the vehicle's driving requirements, and it can be confirmed that the target battery meets the service life condition.

[0032] Step S104, when the target indicator data is less than the first preset threshold, it is determined that the target battery does not meet the service life condition, and the battery is set as a battery to be retired.

[0033] Among them, if the target index number is less than the first threshold, it should be considered that the battery does not meet the driving requirements of the vehicle, which means that the target battery does not meet the service life conditions and the battery needs to be retired.

[0034] In this embodiment, the target indicator data of the target battery is calculated based on the first mileage data, the second mileage data, the first state of charge data, the second state of charge data and the standard capacity of the target battery, and then the target indicator data is compared with the first threshold to confirm whether the target battery meets the service life conditions, thereby realizing the prediction of the battery life according to the usage conditions, thereby improving the accuracy of the prediction.

[0035] In one embodiment, before acquiring the target mileage data and the target state of charge data of the target battery, the method further includes:

[0036] Acquire first sampling data, the first sampling data including N sets of mileage data of N first sampling batteries in a single driving process, and N sets of power consumption data in the single driving process, where N is a constant greater than 1;

[0037] The first threshold is obtained according to the ratio of the sum of the N groups of mileage data to the sum of the N groups of power consumption data.

[0038] It can be understood that the N first sampled batteries are batteries that are still in normal use, and some individual batteries do not meet the service life conditions. However, after averaging the data of the N first sampled batteries, the obtained value can be considered to basically meet the service life conditions and can be set as the first threshold.

[0039] In this embodiment, N first sampled batteries are selected from batteries in normal use for calculation to confirm the first threshold of the target indicator data, so that the first threshold can reasonably characterize the service life condition of the battery, thereby effectively confirming whether the target battery meets the service life condition.

[0040] For example, the first sampling is performed and the first sampling data is obtained as shown in the following table:

[0041] serial number Single trip mileage (Km) Single power consumption (Ah) A1 10 12 A2 8 7 A3 15 16 A4 6 5 A5 13 11 A6 13 13 A7 9 10

[0042] According to the above first sampling data, it can be confirmed that the first threshold is 1Km / Ah, that is, when the target indicator data is greater than or equal to 1Km / Ah, it is considered that the battery meets the service life condition.

[0043] In one embodiment, the first sampling data further includes N groups of auxiliary index data of the N first sampling batteries during the single driving process, and the N groups of auxiliary index data are used to characterize the working performance of the battery;

[0044] After obtaining the first threshold value according to the ratio of the sum of the N groups of mileage data to the sum of the N groups of power consumption data, the method further includes:

[0045] Determine a second threshold value of the N first sampled batteries, where the second threshold value is an average value of the N groups of auxiliary indicator data;

[0046] Acquire a target auxiliary indicator data value of the target battery;

[0047] When the target auxiliary indicator data value is less than the second threshold, confirming that the target battery meets the usage quality condition;

[0048] When the target auxiliary indicator data value is greater than or equal to the second threshold, it is confirmed that the target battery does not meet the usage quality condition.

[0049] It is understandable that the auxiliary index data is a hardware-related index of the battery, which is used to characterize the working performance of the battery. For example, the auxiliary index includes parameters such as the number of battery replacements and the number of cycles, as shown in the subsequent embodiments.

[0050] Among them, the auxiliary indicator data is an indicator data evaluated from the battery's own conditions. When the auxiliary indicator data is greater than or equal to the set second threshold, it is considered that the quality of the battery itself is abnormal at this time. Even if the service life conditions are met, the usage quality conditions are not met, and the battery needs to be repaired.

[0051] It can be understood that the second threshold is similar to the first threshold. By collecting and averaging the auxiliary indicator data of each battery in the N first sampled batteries, the obtained value can be used to measure whether the auxiliary indicator data of the battery basically meets the quality conditions, which is the second threshold.

[0052] In this embodiment, the auxiliary indicator data of the battery is measured by the second threshold value, thereby effectively judging whether the battery has quality problems, thereby achieving rapid maintenance of the battery and improving the safety and service life of the battery.

[0053] In one embodiment, when the target auxiliary indicator data value is greater than or equal to the second threshold, after confirming that the battery does not meet the usage quality condition, the method further includes:

[0054] Obtaining the online time of the target battery, where the online time is used to represent the time after the battery leaves the factory;

[0055] When the online time is greater than or equal to a set value, the target battery is set as a battery to be retired;

[0056] When the online time is less than the set value, the target battery is set as a battery requiring maintenance.

[0057] It is understandable that the second threshold is different from the first threshold. The second threshold is used to measure the quality of the battery, while the first threshold is used to measure the life of the battery. For example, if the quality of the battery is abnormal, but its service life can reach the first threshold, the battery can still be used after quality maintenance. For another example, if the quality of the battery is normal, but its service life no longer meets the first threshold, the battery cannot be repaired, and its service life cannot be extended, and it needs to be forced to retire.

[0058] Among them, the online time is related to the maintenance of the battery. If the online time exceeds the time, the battery maintenance cost is high and the economic benefit is low; if the online time does not exceed the time, the battery maintenance cost is low and the economic benefit is high. Therefore, whether to repair the battery when there is a quality problem with the battery needs to refer to the online time.

[0059] In this embodiment, the quality of the battery is confirmed by the second threshold, and the life of the battery is confirmed by the first threshold, so as to achieve an accurate assessment of the quality and life of the battery, thereby quickly confirming whether the battery is in normal use, needs to be retired, or needs maintenance, thereby improving the accuracy of battery life prediction and battery quality prediction.

[0060] In one embodiment, the auxiliary indicator data includes at least one of the following:

[0061] Number of battery replacements, battery cycles, battery power failures, and user feedback.

[0062] It is understandable that, in addition to the above parameters, the auxiliary indicator data may also include the state of health (SOH) or the number of deep discharges, etc., and may be customized accordingly according to different types of batteries.

[0063] For example, the auxiliary indicator data also includes the number of battery replacements, the number of battery cycles, the number of battery power failures, and the number of user feedbacks. During the first sampling, the first sample data obtained is as follows:

[0064] serial number Battery replacement times Battery cycle number Battery power-off times User feedback times A1 14 20 2 1 A2 20 41 0 0 A3 15 33 0 2 A4 17 37 1 0 A5 20 39 0 2 A6 9 17 0 0 A7 11 25 0 0

[0065] From the above table, we can confirm the average values ​​of different parameters. For example, the average number of battery replacements is 15 times. When the number of battery replacements exceeds 15 times, it is determined that there is a greater risk of quality of use. The battery needs to be set as a repair battery and put back into use after the maintenance personnel confirms that there is no quality problem.

[0066] It is understandable that other parameters can also be used to measure and confirm the quality of the battery. The effect is similar to the number of battery replacements, so I will not go into details here.

[0067] In one embodiment, after confirming the second threshold of the N first sampled batteries, the method further includes:

[0068] According to the first threshold and the second threshold, query the database to confirm M sampled battery identifiers, and the M second sampled batteries corresponding to the M sampled battery identifiers meet the battery service life condition and the battery use quality condition, the database includes battery identifiers corresponding to batteries in use, and M is a constant greater than 1;

[0069] Sending the sampled battery identification to a detection device, the detection device is used to detect the single driving mileage and single driving power consumption of the M second sampled batteries, as well as auxiliary indicator data of the M second sampled batteries;

[0070] Receiving M detection data sent by the detection device, the M detection data including M sampled mileage data of the M second sampled batteries, M driving power consumption data, and M auxiliary indicator data;

[0071] Determining M target indicator data of the M second sampled batteries according to the ratio of the M sampled mileage data to the M driving power consumption data;

[0072] Screening the M target indicator data according to the set ratio value and the first threshold value to confirm P batteries that meet the battery life condition, where the P batteries are batteries in the M second sampled batteries, and P is a constant greater than 1;

[0073] Calculate and confirm a first optimization value according to the P sampled mileage data and the P driving power consumption data corresponding to the P batteries, and update the value of the first threshold to the first optimization value, wherein the P sampled mileage data are data among the M sampled mileage data, and the P driving power consumption data are data among the M driving power consumption data;

[0074] According to the P auxiliary indicator data corresponding to the P batteries, an average calculation is performed to confirm a second optimization value, and the value of the second threshold is updated to the second optimization value, wherein the P auxiliary indicator data are data among the M auxiliary indicator data.

[0075] The detection device can perform experimental detection on the second sample battery, and accurately obtain the target index data and auxiliary index data of the battery by using the battery interchangeably or other experimental methods.

[0076] It can be understood that the first threshold and the second threshold values ​​obtained through the first sampling data are preliminary values, which can only simply evaluate the life and quality of the battery, and cannot accurately distinguish whether the battery meets the service life conditions and quality conditions. It is necessary to continuously optimize and iterate the first threshold and the second threshold to improve the prediction accuracy of the battery life conditions and quality conditions.

[0077] Among them, the second sampling battery is different from the first sampling battery. The second sampling battery is a battery that meets both the first threshold and the second threshold. The second sampling battery is detected accordingly, and then the result is corrected based on the detection result to achieve iteration of the first threshold and the second threshold.

[0078] It can be understood that the ratio value is set according to the actual battery usage. For example, the first threshold value is 1Km / Ah, and the ratio value is set to 95%. That is, when the target indicator data of the battery in the test result is greater than 0.95Km / Ah, it can be considered that the battery meets the service life conditions. Then, the revised first threshold value and the second threshold value are confirmed based on the battery that meets the conditions, and an iteration of the first threshold value and the second threshold value is completed.

[0079] For example, a second sampling is performed, and the auxiliary indicator data of the second sampling battery includes the number of battery cycles and the number of user feedbacks. The sampling results are shown in the following table:

[0080]

[0081] In the above table, battery B4 does not meet the conditions and needs to be screened and filtered. After an iteration through other batteries, a value of 1.04Km / Ah is obtained. The first threshold is updated to 1.04Km / Ah, which can be closer to the actual situation of the battery.

[0082] In this embodiment, by updating and iterating the first threshold used to determine the battery life condition and the second threshold used to inventory the battery usage quality condition, the battery life and quality can be predicted more accurately, thereby improving the accuracy of the prediction.

[0083] See also Figure 2 , Figure 2 is a structural diagram of a battery usage estimation device provided by an embodiment of the present invention, such as Figure 2 As shown, the battery usage estimation device 200 includes:

[0084] The first acquisition module 201 is used to acquire the target mileage data and target state of charge data of the target battery, wherein the target mileage data includes the first mileage data when taken out of the battery swap cabinet and the second mileage data when put into the battery swap cabinet, and the target state of charge data includes the first state of charge data when taken out of the battery swap cabinet and the second state of charge data when put into the battery swap cabinet;

[0085] A first calculation module 202 is configured to subtract the second mileage data from the first mileage data to obtain a single driving mileage, then subtract the second state of charge data from the first state of charge data to obtain a single state of charge consumption, and then multiply the quotient of the single driving mileage and the single state of charge consumption by the standard capacity of the target battery to obtain target indicator data of the target battery, wherein the target indicator data is used to characterize the driving mileage per ampere-hour of the battery;

[0086] A first processing module 203 is used to confirm that the target battery meets the service life condition when the target indicator data is greater than or equal to a preset first threshold;

[0087] The second processing module 204 is used to confirm that the target battery does not meet the service life condition and set the battery as a battery to be retired when the target indicator data is less than the first preset threshold.

[0088] Optionally, before the first obtaining module 201, the device further includes:

[0089] A second acquisition module is used to acquire first sampling data, wherein the first sampling data includes N groups of mileage data of N first sampling batteries in a single driving process and N groups of power consumption data in the single driving process, where N is a constant greater than 1;

[0090] The second calculation module is used to obtain the first threshold value according to the ratio of the sum of the N groups of mileage data to the sum of the N groups of power consumption data.

[0091] Optionally, the first sampling data further includes N groups of auxiliary index data of the N first sampling batteries during the single driving process, and the N groups of auxiliary index data are used to characterize the working performance of the battery;

[0092] After the second calculation module, the device further includes:

[0093] A third calculation module, used to determine a second threshold value of the N first sampled batteries, where the second threshold value is an average value of the N groups of auxiliary indicator data;

[0094] A third acquisition module, used to acquire a target auxiliary indicator data value of the target battery;

[0095] A third processing module, configured to confirm that the target battery meets the usage quality condition when the target auxiliary indicator data value is less than the second threshold;

[0096] The fourth processing module is used to confirm that the target battery does not meet the usage quality condition when the target auxiliary indicator data value is greater than or equal to the second threshold.

[0097] Optionally, after the fourth processing module, the device further includes:

[0098] A fourth acquisition module, used to acquire the online time of the target battery, where the online time is used to represent the time after the battery leaves the factory;

[0099] A fifth processing module, configured to set the target battery as a battery to be retired when the online time is greater than or equal to a set value;

[0100] The sixth processing module is used to set the target battery as a battery requiring maintenance when the online time is less than the set value.

[0101] Optionally, the auxiliary indicator data includes at least one of the following:

[0102] Number of battery replacements, battery cycles, battery power failures, and user feedback.

[0103] Optionally, after the third calculation module, the device further includes:

[0104] A query module, configured to query a database according to the first threshold and the second threshold, and confirm that M sampled battery identifiers, M second sampled batteries corresponding to the M sampled battery identifiers meet the battery service life condition and the battery use quality condition, the database includes battery identifiers corresponding to batteries in use, and M is a constant greater than 1;

[0105] A sending module, used for sending the sampled battery identification to a detection device, wherein the detection device is used for detecting the single driving mileage and single driving power consumption of the M second sampled batteries, as well as auxiliary indicator data of the M second sampled batteries;

[0106] A receiving module, used for receiving M detection data sent by the detection device, wherein the M detection data include M sampled mileage data of the M second sampled batteries, M driving power consumption data, and M auxiliary indicator data;

[0107] a fourth calculation module, configured to determine M target indicator data of the M second sampled batteries according to a ratio of the M sampled mileage data to the M driving power consumption data;

[0108] a screening module, configured to screen the M target indicator data according to a set ratio value and the first threshold value, and confirm P batteries that meet the battery service life condition, wherein the P batteries are batteries in the M second sampled batteries, and P is a constant greater than 1;

[0109] a seventh processing module, configured to calculate and confirm a first optimization value according to P sampled mileage data and P driving power consumption data corresponding to the P batteries, and update the value of the first threshold to the first optimization value, wherein the P sampled mileage data are data from the M sampled mileage data, and the P driving power consumption data are data from the M driving power consumption data;

[0110] An eighth processing module is used to calculate and confirm a second optimization value by averaging the P auxiliary indicator data corresponding to the P batteries, and to update the value of the second threshold to the second optimization value, wherein the P auxiliary indicator data are data among the M auxiliary indicator data.

[0111] The battery usage estimation device provided in the embodiment of the present invention is capable of implementing each process of each embodiment of the above-mentioned battery usage estimation method, and the technical features correspond one to one and can achieve the same technical effect. To avoid repetition, they will not be described here.

[0112] It should be noted that the battery usage estimation device in the embodiment of the present invention may be a device, or a component, an integrated circuit, or a chip in an electronic device.

[0113] The embodiment of the present invention further provides an electronic device, see Figure 3 , Figure 3 is a schematic diagram of the structure of an electronic device provided by the present invention, the electronic device includes a memory 301, a processor 302 and a program or instruction stored in the memory 301 and running thereon, and when the program or instruction is executed by the processor 302, it can be realized Figure 1 Any steps in the corresponding method embodiments and achieving the same beneficial effects will not be repeated here.

[0114] The processor 302 may be a CPU, an ASIC, an FPGA or a GPU.

[0115] Those skilled in the art will appreciate that all or part of the steps of implementing the above-mentioned embodiment method can be completed by hardware associated with program instructions, and the program can be stored in a readable medium.

[0116] The embodiment of the present invention further provides a readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the above Figure 1Any steps in the corresponding method embodiments can achieve the same technical effect, and will not be repeated here to avoid repetition. The storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0117] The terms "first", "second" etc. in the embodiments of the present invention are used to distinguish similar objects, and need not be used to describe a specific order or sequential order. In addition, the terms "include" and "have" and any variation thereof are intended to cover non-exclusive inclusions, for example, the process, method, system, product or equipment comprising a series of steps or units need not be limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or equipment. In addition, "and / or" is used in the present application to represent at least one of the connected objects, such as A and / or B and / or C, indicating that A alone, B alone, C alone, and A and B all exist, B and C all exist, A and C all exist, and 7 situations in which A, B and C all exist.

[0118] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0119] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a second terminal device, etc.) to execute the methods of each embodiment of the present application.

[0120] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A battery usage estimation method, characterized in that: include: Obtain target mileage data and target state of charge data of the target battery, wherein the target mileage data includes first mileage data when the battery is taken out of the battery swap cabinet and second mileage data when the battery is put into the battery swap cabinet, and the target state of charge data includes first state of charge data when the battery is taken out of the battery swap cabinet and second state of charge data when the battery is put into the battery swap cabinet; Subtracting the second mileage data from the first mileage data to obtain a single driving mileage, then subtracting the second state of charge data from the first state of charge data to obtain a single state of charge consumption, then multiplying the quotient of the single driving mileage and the single state of charge consumption by the standard capacity of the target battery to obtain the target indicator data of the target battery, the target indicator data being used to characterize the driving mileage per ampere-hour of the battery; When the target indicator data is greater than or equal to a preset first threshold, confirming that the target battery meets the service life condition; When the target indicator data is less than the first preset threshold, confirming that the target battery does not meet the service life condition, and setting the battery as a battery to be retired; Determine a second threshold value, where the second threshold value is an average value of N sets of auxiliary indicator data, where the N sets of auxiliary indicator data are used to characterize the working performance of the battery, and N is a constant greater than 1; Acquire a target auxiliary indicator data value of the target battery; When the target auxiliary indicator data value is less than the second threshold, confirming that the target battery meets the usage quality condition; When the target auxiliary indicator data value is greater than or equal to the second threshold, confirming that the target battery does not meet the usage quality condition; After confirming the second threshold of the N first sampled batteries, the method further includes: According to the first threshold and the second threshold, query the database to confirm M sampled battery identifiers, and the M second sampled batteries corresponding to the M sampled battery identifiers meet the battery service life condition and the battery use quality condition, the database includes battery identifiers corresponding to batteries in use, and M is a constant greater than 1; Sending the sampled battery identification to a detection device, the detection device is used to detect the single driving mileage and single driving power consumption of the M second sampled batteries, as well as auxiliary indicator data of the M second sampled batteries; Receiving M detection data sent by the detection device, the M detection data including M sampled mileage data of the M second sampled batteries, M driving power consumption data, and M auxiliary indicator data; Determining M target indicator data of the M second sampled batteries according to the ratio of the M sampled mileage data to the M driving power consumption data; Screening the M target indicator data according to the set ratio value and the first threshold value to confirm P batteries that meet the battery life condition, where the P batteries are batteries in the M second sampled batteries, and P is a constant greater than 1; Calculate and confirm a first optimization value according to the P sampled mileage data and the P driving power consumption data corresponding to the P batteries, and update the value of the first threshold to the first optimization value, wherein the P sampled mileage data are data among the M sampled mileage data, and the P driving power consumption data are data among the M driving power consumption data; According to the P auxiliary indicator data corresponding to the P batteries, an average calculation is performed to confirm a second optimization value, and the value of the second threshold is updated to the second optimization value, wherein the P auxiliary indicator data are data among the M auxiliary indicator data.

2. The method according to claim 1, characterized in that Before acquiring the target mileage data and the target state of charge data of the target battery, the method further includes: Acquire first sampling data, where the first sampling data includes N sets of mileage data of N first sampling batteries during a single driving process, and N sets of power consumption data during the single driving process; The first threshold is obtained according to the ratio of the sum of the N groups of mileage data to the sum of the N groups of power consumption data.

3. The method according to claim 2, characterized in that The first sampling data also includes N groups of auxiliary index data of the N first sampling batteries during the single driving process.

4. The method according to claim 3, characterized in that When the target auxiliary indicator data value is greater than or equal to the second threshold, after confirming that the battery does not meet the usage quality condition, the method further includes: Obtaining the online time of the target battery, where the online time is used to represent the time after the battery leaves the factory; When the online time is greater than or equal to a set value, the target battery is set as a battery to be retired; When the online time is less than the set value, the target battery is set as a battery requiring maintenance.

5. The method according to claim 3, characterized in that: The auxiliary indicator data includes at least one of the following: Number of battery replacements, battery cycles, battery power failures, and user feedback.

6. A battery usage estimation device, characterized in that: include: A first acquisition module is used to acquire target mileage data and target state of charge data of a target battery, wherein the target mileage data includes first mileage data when taken out of a battery swap cabinet and second mileage data when put into a battery swap cabinet, and the target state of charge data includes first state of charge data when taken out of a battery swap cabinet and second state of charge data when put into a battery swap cabinet; a first calculation module, configured to subtract the second mileage data from the first mileage data to obtain a single driving mileage, then subtract the second state of charge data from the first state of charge data to obtain a single state of charge consumption, then multiply the quotient of the single driving mileage and the single state of charge consumption by the standard capacity of the target battery to obtain target indicator data of the target battery, wherein the target indicator data is used to characterize the driving mileage per ampere-hour of the battery; A first processing module, configured to confirm that the target battery meets the service life condition when the target indicator data is greater than or equal to a preset first threshold; A second processing module is used to confirm that the target battery does not meet the service life condition when the target indicator data is less than the first preset threshold value, and set the battery as a battery to be retired; a third calculation module, used to determine a second threshold value, where the second threshold value is an average value of N groups of auxiliary indicator data, where the N groups of auxiliary indicator data are used to characterize the working performance of the battery, and N is a constant greater than 1; A third acquisition module, used to acquire a target auxiliary indicator data value of the target battery; A third processing module, configured to confirm that the target battery meets the usage quality condition when the target auxiliary indicator data value is less than the second threshold; A fourth processing module, configured to confirm that the target battery does not meet the usage quality condition when the target auxiliary indicator data value is greater than or equal to the second threshold; After the third calculation module, the device further includes: A query module, configured to query a database according to the first threshold and the second threshold, and confirm that M sampled battery identifiers, M second sampled batteries corresponding to the M sampled battery identifiers meet the battery service life condition and the battery use quality condition, the database includes battery identifiers corresponding to batteries in use, and M is a constant greater than 1; A sending module, used for sending the sampled battery identification to a detection device, wherein the detection device is used for detecting the single driving mileage and single driving power consumption of the M second sampled batteries, as well as auxiliary indicator data of the M second sampled batteries; A receiving module, used for receiving M detection data sent by the detection device, wherein the M detection data include M sampled mileage data of the M second sampled batteries, M driving power consumption data, and M auxiliary indicator data; a fourth calculation module, configured to determine M target indicator data of the M second sampled batteries according to a ratio of the M sampled mileage data to the M driving power consumption data; a screening module, configured to screen the M target indicator data according to a set ratio value and the first threshold value, and confirm P batteries that meet the battery service life condition, wherein the P batteries are batteries in the M second sampled batteries, and P is a constant greater than 1; a seventh processing module, configured to calculate and confirm a first optimization value according to P sampled mileage data and P driving power consumption data corresponding to the P batteries, and update the value of the first threshold to the first optimization value, wherein the P sampled mileage data are data from the M sampled mileage data, and the P driving power consumption data are data from the M driving power consumption data; An eighth processing module is used to calculate and confirm a second optimization value by averaging the P auxiliary indicator data corresponding to the P batteries, and to update the value of the second threshold to the second optimization value, wherein the P auxiliary indicator data are data among the M auxiliary indicator data.

7. The device according to claim 6, characterized in that Before the first acquisition module, the device further includes: A second acquisition module is used to acquire first sampling data, wherein the first sampling data includes N groups of mileage data of N first sampling batteries in a single driving process and N groups of power consumption data in the single driving process, where N is a constant greater than 1; The second calculation module is used to obtain the first threshold value according to the ratio of the sum of the N groups of mileage data to the sum of the N groups of power consumption data.

8. An electronic device, characterized in that: The method comprises a processor, a memory and a computer program stored in the memory and executable on the processor, wherein the computer program implements the steps in the battery usage estimation method according to any one of claims 1 to 5 when executed by the processor.

9. A readable storage medium for storing a program, characterized in that: When the program is executed by a processor, the steps of the battery usage estimation method according to any one of claims 1 to 5 are implemented.

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