Health state determination method and device, vehicle and readable storage medium

Abstract

The invention relates to a state of health determination method and device, a vehicle and a readable storage medium, the method is applied to a battery module, and the method comprises the following steps: determining a first capacity of the battery module from a target inflection point electric quantity of the battery module to a charging end electric quantity according to first charging data of each charging of the battery module in multiple times of charging, wherein the target inflection point electric quantity of the battery module is the electric quantity corresponding to a second maximum value point of a first differential capacity curve obtained based on the first charging data; determining a second capacity; wherein the second capacity is the capacity of a battery cell in the battery module before the target inflection point electric quantity of the battery cell; according to the first capacity and the second capacity, the charging capacity of the battery module in charging corresponding to the first charging data is obtained, and the charging capacity is used for obtaining health state data of the battery module.

Description

Technical Field

[0001] The present disclosure relates to the field of vehicle control technology, and more specifically, to a method and device for determining a health status, a vehicle, and a readable storage medium. Background Art

[0002] With the popularization of new energy vehicles, the life of electric vehicle battery packs has received more and more attention. The state of health (SOH) of the battery pack is used to characterize the life status of the battery pack.

[0003] In the related art, the health status of the battery pack is usually determined based on the rated capacity and the current charging capacity. However, the current charging capacity is determined by the charging SOH interval selected during the charging process. The interval selected must be long enough. Inaccurate estimation of the current charging capacity will cause a large error in the health status of the battery pack. Summary of the invention

[0004] One purpose of the embodiments of the present disclosure is to provide a new method for determining a health status.

[0005] According to a first aspect of the present disclosure, a method for determining a health state is provided, which is applied to a battery module, and the method includes:

[0006] Determine, according to first charging data of each charging of the battery module in multiple chargings, a first capacity of the battery module from a target inflection point capacity of the battery module to a charging end capacity; wherein the target inflection point capacity of the battery module is a capacity corresponding to a second maximum point of a first differential capacity curve obtained based on the first charging data;

[0007] Determine a second capacity; wherein the second capacity is the capacity of the battery cell in the battery module before the target inflection point capacity of the battery cell;

[0008] The charging capacity of the battery module in the charging corresponding to the first charging data is obtained according to the first capacity and the second capacity, and the charging capacity is used to obtain the health status data of the battery module.

[0009] Optionally, determining the second capacity includes:

[0010] Determining the second capacity corresponding to the battery cell type of the battery module according to the battery cell type of the battery module and the first mapping data;

[0011] The first mapping data reflects the corresponding relationship between the battery cell type and the second capacity.

[0012] Optionally, determining the second capacity includes:

[0013] Acquire second charging data of a battery cell sample; wherein the battery cell sample and the battery cell in the battery module are of the same type of battery cell;

[0014] performing dimensionality reduction processing on the second charging data, and obtaining a second differential capacity curve of the second charging data after the dimensionality reduction processing;

[0015] The electric quantity corresponding to the second maximum value point of the second differential capacity curve is used as the target inflection point electric quantity of the battery cell;

[0016] The second capacity is obtained according to the target inflection point capacity of the battery cell.

[0017] Optionally, the charge end power quantity relates to one of the following: a set power threshold, and a power quantity when the charge end voltage of the battery module is greater than a set voltage threshold.

[0018] Optionally, after obtaining the charging capacity of the battery module in the charging corresponding to the first charging data according to the first capacity and the second capacity, the method further includes:

[0019] Obtaining the rated capacity of the battery module;

[0020] According to the charging capacity of the battery module in each charging and the rated capacity of the battery module, health status data of the battery module at each charging is obtained.

[0021] Optionally, the method further comprises:

[0022] Establishing second mapping data reflecting the corresponding relationship between time and health status data of the battery module;

[0023] Performing smoothing filtering on the second mapping data to obtain third mapping data;

[0024] The health status data of the battery module on the prediction day is predicted based on the third mapping data.

[0025] According to a second aspect of the present disclosure, a device for determining a health state is provided, which is applied to a battery module, and includes:

[0026] A first determination module is used to determine a first capacity of the battery module from a target inflection point power of the battery module to a charging end power according to first charging data of each charging of the battery module in multiple chargings; wherein the target inflection point power of the battery module is a power corresponding to a second maximum point of a first differential capacity curve obtained based on the first charging data;

[0027] A second determination module is used to determine a second capacity; wherein the second capacity is the capacity of the battery cell in the battery module before the target inflection point capacity of the battery cell;

[0028] An acquisition module is used to obtain the charging capacity of the battery module in the charging corresponding to the first charging data according to the first capacity and the second capacity, and the charging capacity is used to obtain the health status data of the battery module.

[0029] According to a third aspect of the present disclosure, a vehicle is provided, comprising a memory and a processor, wherein the memory is used to store an executable computer program; and the computer program is used to control the processor to execute the method according to the first aspect of the present disclosure.

[0030] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method described in the first aspect of the present disclosure is implemented.

[0031] According to a fifth aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the steps of the method described in the first aspect of the present disclosure are implemented.

[0032] A beneficial effect of the embodiments of the present disclosure is that it can count the target inflection point power of the battery module in each charge, that is, the power corresponding to the second maximum point of the first differential capacity (DV / DQ) curve obtained based on the first charging data, and determine the first capacity of the battery module from the target inflection point power of the battery module to the charging end power in each charge, and then combine the second capacity of the battery cell before the target inflection point power to obtain the actual charging capacity of the battery module in each charge. That is to say, it can estimate the charging capacity of the battery module in each charge in combination with the DV / DQ curve characteristics of the first charging data of each charge, thereby providing accuracy in charging capacity estimation, avoiding errors in the calculation of the health status data of the battery module caused by inaccurate charging capacity estimation, and improving the accuracy of the estimation of the health status data of the battery module, so that the life of the battery module can be better observed through the health status data of the battery module at each charge.

[0033] Further features and advantages of the present invention will become apparent from the following detailed description of exemplary embodiments of the present invention with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.

[0035] Figure 1A block diagram showing a hardware configuration of an electronic device that can implement an embodiment of the present disclosure;

[0036] Figure 2 is a schematic diagram of a flow chart of a method for determining a health status according to an embodiment of the present disclosure;

[0037] Figure 3 is a schematic diagram comparing a capacity-voltage curve of first charging data and a first differential capacity curve according to an embodiment of the present disclosure;

[0038] Figure 4 is a schematic diagram comparing the second mapping data and the third mapping data according to an embodiment of the present disclosure;

[0039] Figure 5 is a flowchart of an example of a method for determining a health status according to an embodiment of the present disclosure;

[0040] Figure 6 is a block diagram of a device for determining a health status according to an embodiment of the present disclosure;

[0041] Figure 7 is a block diagram of an electronic device according to an embodiment of the present disclosure;

[0042] Figure 8 is a block diagram of a vehicle according to one embodiment of the present disclosure. DETAILED DESCRIPTION

[0043] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that the relative arrangement of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention unless otherwise specifically stated.

[0044] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

[0045] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered as part of the specification.

[0046] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0047] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0048] <Hardware Configuration>

[0049] Figure 1 A block diagram showing a hardware configuration of an electronic device 1000 that can implement an embodiment of the present disclosure is shown.

[0050] The electronic device 1000 may be a portable computer, a desktop computer, a mobile phone, a tablet computer, etc. Figure 1 As shown, the electronic device 1000 may include a processor 1100, a memory 1200, an interface device 1300, a communication device 1400, a display device 1500, an input device 1600, a speaker 1700, a microphone 1800, and the like. Among them, the processor 1100 may be a central processing unit CPU, a microprocessor MCU, and the like. The memory 1200 includes, for example, a ROM (read-only memory), a RAM (random access memory), a non-volatile memory such as a hard disk, and the like. The interface device 1300 includes, for example, a USB interface, a headphone interface, and the like. The communication device 1400 is, for example, capable of wired or wireless communication, and may specifically include Wifi communication, Bluetooth communication, 2G / 3G / 4G / 5G communication, and the like. The display device 1500 is, for example, a liquid crystal display screen, a touch display screen, and the like. The input device 1600 may include, for example, a touch screen, a keyboard, a somatosensory input, and the like. The user may input / output voice information through the speaker 1700 and the microphone 1800.

[0051] Figure 1 The electronic device shown is merely illustrative and does not in any way imply any limitation on the present disclosure, its application or use. In the embodiments of the present disclosure, the memory 1200 of the electronic device 1000 is used to store instructions, and the instructions are used to control the processor 1100 to operate to perform any one of the health status determination methods provided in the embodiments of the present disclosure. It should be understood by those skilled in the art that although Figure 1 In the electronic device 1000, multiple devices are shown, but the present disclosure may only involve some of the devices, for example, the electronic device 1000 only involves the processor 1100 and the storage device 1200. A technician can design instructions according to the scheme disclosed in the present disclosure. How instructions control the processor to operate is well known in the art, so it will not be described in detail here.

[0052] <Method Example>

[0053] The present disclosure embodiment discloses a method for determining a health status, which is applied to a battery module, such as but not limited to a battery pack or a battery module. Of course, the battery module may also be some device including a battery. Figure 2 As shown, the method for determining the health status includes the following steps S2100 to S2300.

[0054] Step S2100 , determining a first capacity of the battery module from a target inflection point power of the battery module to a charging end power according to first charging data of each charging of the battery module in multiple charging processes.

[0055] Among them, one charge corresponds to a set of first charging data, that is, it is necessary to obtain the first charging data of each charge of the battery module in multiple charges. It should be noted that the first charging data is usually AC charging data, that is, it is necessary to obtain the first charging data of each AC charging of the battery module in multiple AC charges. The first charging data of any charge, for example but not limited to, includes the power (State of Charge, SOC), voltage, time, and temperature of the battery module in any charging process. The following is an example in which the first charging data includes the power and voltage of the battery module in any charging process.

[0056] In specific implementation, the background vehicle status data of the target vehicle can be first imported through the target field. The target field includes, for example but not limited to, time, charging connection status, current total current of the battery module, current capacity index of the battery module, minimum single-cell voltage, minimum single-cell number, maximum single-cell voltage, maximum single-cell number, total mileage, minimum temperature, and maximum temperature data. After importing the background vehicle status data of the target vehicle, all AC charging processes of the battery module of the target vehicle can be found from the background vehicle status data, and the power, voltage, time, and temperature of each AC charging process are recorded as the first charging data of the corresponding AC charging process. In other words, all background vehicle status data of the target vehicle within the historical set time period are first imported, and then all AC charging data of the battery module of the target vehicle are found from all the imported background vehicle status data.

[0057] Among them, the charge end power involves one of the following: a set power threshold, and the power when the charge end voltage of the battery module is greater than the set voltage threshold. Among them, the set power threshold is usually at 100SOC, and the set voltage threshold is usually 3.6V. It should be noted that for any number of charging ends, when charging ends, either the power is the set power threshold, or the cut-off voltage is greater than 3.6V. That is to say, when the power reaches the set power threshold, the set power threshold can be used as the charge end power; when the cut-off voltage is greater than 3.6V, the power corresponding to the cut-off voltage can be used as the charge end power. In the related art, it usually only uses the power displayed by the battery management system (Battery Management System, BMS) as the charge end power, and the charge end power determined in this way has low accuracy.

[0058] The target inflection point power of the battery module is the power corresponding to the second maximum point of the first differential capacity (DV / DQ) curve obtained based on the first charging data, that is, each first charging data with a charge start power less than or equal to the target inflection point power corresponds to the target inflection point power of a battery module. In this way, by counting the target inflection point power of the battery module in each charge, that is, the power corresponding to the second maximum point of the first differential capacity (DV / DQ) curve obtained based on the first charging data, the first capacity of the battery module during each charge from the target inflection point power of the battery module to the end of charge power can be determined.

[0059] The first differential capacity (DV / DQ) curve above represents the capacity of the material within a unit voltage range and is used to evaluate the attenuation of the battery module.

[0060] Specifically, for each first charging data, the curve between the highest single-cell voltage and the battery module power can be obtained first, and then the curve is smoothed and filtered, and the first-order derivative of the voltage with respect to the power is taken to obtain the rate of change of the voltage with respect to the power, and the differential capacity (DV / DQ) curve established according to the rate of change and the power. Figure 3 The capacity-voltage curve and differential capacity (DV / DQ) curve shown are based on Figure 3 It can be seen that the differential capacity curve includes two maximum points, the first maximum point is Point1, and the second maximum point is Point2. Usually, the power corresponding to the second maximum point Point2 is used as the target inflection point power of the battery module corresponding to the first charging data, and the capacity from the target inflection point power to the charging end power of the battery module corresponding to the first charging data is used as the first capacity Q2. Usually, the power corresponding to Point2 is at a high power level.

[0061] It should be noted that, for any first charging data, the target inflection point power of the battery module can be understood as the starting power of the any first charging data. In this way, by counting the starting power of each first charging data, for each first charging data, the first capacity from the starting power of the first charging data to the charging end power can be calculated.

[0062] In this embodiment, for each first charging data, the ampere-hour integration method can be used to calculate the first capacity of the battery module from the target inflection point power of the battery module to the charging end power. For example, in one charge, the target inflection point power of the battery module is 62SOC, and the ampere-hour integration method is used to calculate the first capacity Q2 charged from 62SOC to 100SOC.

[0063] After executing the above step S2100, according to the first charging data of each charging of the battery module in multiple chargings, determining the first capacity of the battery module from the target inflection point power of the battery module to the charging end power, proceeding to:

[0064] Step S2200, determining the second capacity.

[0065] The second capacity Q1 is the capacity of the battery cell in the battery module before the target inflection point capacity of the battery cell.

[0066] It should be noted that the cell types of the multiple cells included in the battery module are usually consistent, and the second capacity is usually related to the cell type, which can be understood as the cell model.

[0067] In an optional embodiment, determining the second capacity in step S2200 may further include: determining the second capacity corresponding to the battery cell type of the battery module according to the battery cell type of the battery module and the first mapping data.

[0068] The first mapping data reflects the correspondence between the cell type and the second capacity. In specific implementation, usually after the cell production line is divided into different capacities, the capacity tests are performed on different types of cells respectively. After the second capacities corresponding to different types of cells are obtained based on the capacity tests, the correspondence between the cell type and its corresponding second capacity can be stored in the first mapping data. For example, the first mapping data includes multiple correspondences, one of which is "cell type X, second capacity Q 11 ”, one of the corresponding relationships is “cell type Y, second capacity Q 12 ”, one of the corresponding relationships is “cell type Z, second capacity Q 13 ”.

[0069] For example, the cell type X of the battery module can be determined according to the cell type X of the battery module and one of the corresponding relationships in the first mapping data: cell type X, second capacity Q 11 ", determine that the second capacity corresponding to the battery cell type X of the battery module is Q 11 .

[0070] In an optional embodiment, the step S2200 of determining the second capacity may further include the following steps S2210 to S2240:

[0071] Step S2210, obtaining second charging data of the battery cell sample.

[0072] The battery cell sample and the battery cells in the battery module are of the same type of battery cells. For example, the battery cell type of the battery cell sample is battery cell type X.

[0073] The second charging data is usually charging data obtained by performing a capacity test on the battery cell sample after the cell is divided into different capacities on the production line. For example, the second charging data may be a 0.2C charging curve.

[0074] In specific implementation, after the cell samples are divided into different capacities at the production line, a 0.2C charge and discharge test is performed on the cell samples, and the 0.2C charging curve of the cell samples is recorded. Of course, the 0.2C discharge curve of the cell samples is usually also recorded. This embodiment is mainly described by taking the 0.2C charging curve as an example.

[0075] Step S2220: perform dimensionality reduction processing on the second charging data, and obtain a second differential capacity curve of the second charging data after the dimensionality reduction processing.

[0076] It should be noted that, since the collected 0.2C charging curve includes many data points, the 0.2C charging curve may be first subjected to dimensionality reduction processing to reduce the amount of data, and a voltage differential curve of the 0.2C charging curve after dimensionality reduction processing may be further obtained.

[0077] Among them, the second differential capacity (DV / DQ) curve represents the capacity contained in the material within a unit voltage range and is used to evaluate the attenuation of the battery cell sample.

[0078] Specifically, for the 0.2C charging curve, the 0.2C charging curve can be first smoothed and filtered, and the voltage can be first derived with respect to the charge to obtain the rate of change of the voltage with respect to the charge, and a differential capacity (DV / DQ) curve established based on the rate of change and the charge.

[0079] Step S2230: taking the electric quantity corresponding to the second maximum point of the second differential capacity curve as the target inflection point electric quantity of the battery cell sample.

[0080] Typically, the second differential capacity curve includes two maximum points, the first maximum point is Point1, and the second maximum point is Point2. In addition, due to chemical characteristics, the negative electrode material before Point2 is usually not consumed, that is, the negative electrode material before Point2 will not be consumed, and it is identified as before the EOL (End of Life) state, that is, the identified 70% SOH. Usually, the life decay of the battery cell is after Point2, so the power corresponding to Point2 can be used as the target inflection point power of the battery cell sample. In addition, the power corresponding to Ponit2 is usually at a high power level.

[0081] Step S2240: obtaining the first capacity according to the target inflection point capacity of the battery cell sample.

[0082] In this embodiment, the capacity of the battery sample corresponding to the 0.2C charging curve from the start of charging to the target inflection point of the battery sample can be used as the second capacity Q1. Specifically, the second capacity Q1 of the battery sample from the start of charging to the target inflection point can be calculated using the ampere-hour integration method. The second capacity Q1 can refer to Figure 3 As shown in the figure, the charging start power is usually at 0SOC.

[0083] According to the above steps S2210 to S2240, the second capacity of the battery cell in the battery module before the target inflection point power of the battery cell can be obtained in advance, and then the charging capacity of the battery module in any charging can be obtained based on the second capacity and the first capacity of the battery module in any charging.

[0084] After executing the above step S2200 to determine the second capacity, proceed to:

[0085] Step S2300: Obtaining the charging capacity of the battery module in the charging corresponding to the first charging data according to the first capacity and the second capacity, wherein the charging capacity is used to obtain health status data of the battery module.

[0086] In this embodiment, for any first charging data, the charging capacity Q of the battery module in the any charging is curr Satisfies the following formula:

[0087] Q curr =Q1+Q2

[0088] Among them, Q1 represents the second capacity, and Q2 represents the first capacity of the battery module in any charging. That is to say, by adding the second capacity and the first capacity of the battery module in any charging, the actual charging capacity of the battery module in any charging can be estimated.

[0089] According to the embodiment of the present disclosure, it is possible to count the target inflection point power of the battery module in each charge, that is, the power corresponding to the second maximum point of the first differential capacity (DV / DQ) curve obtained based on the first charging data, and determine the first capacity of the battery module from the target inflection point power of the battery module to the charging end power in each charge, and then combine the second capacity of the battery cell before the target inflection point power to obtain the actual charging capacity of the battery module in each charge. That is to say, it is possible to estimate the charging capacity of the battery module in each charge in combination with the DV / DQ curve characteristics of the first charging data of each charge, thereby providing accuracy in charging capacity estimation, avoiding errors in the calculation of the health status data of the battery module caused by inaccurate charging capacity estimation, and improving the accuracy of the estimation of the health status data of the battery module, so that the life of the battery module can be better observed through the health status data of the battery module at each charge.

[0090] In one embodiment, after executing the above step S2300 to obtain the charging capacity of the battery module in the charging corresponding to the first charging data according to the first capacity and the second capacity, the method for determining the health status of the embodiment of the present disclosure further includes step S2400 to obtain the health status data of the battery module according to the charging capacity of the battery module in each charging.

[0091] In this embodiment, the step S2400 of obtaining the health status data of the battery module according to the charging capacity of the battery module in each charging may further include the following steps S2410 to S2420:

[0092] Step S2410, obtaining the rated capacity of the battery module.

[0093] The rated capacity of the battery module is generally measured by the capacity (Ah) released when a fully charged battery is discharged at room temperature with a current of 1h (A) and reaches the termination voltage. It is usually the capacity value of the battery declared by the manufacturer.

[0094] In this step S2410, the rated capacity Q corresponding to the package model of the battery module can be determined according to the package model of the battery module and the fourth mapping data. rat .

[0095] The fourth mapping data reflects the correspondence between the package model of the battery module and the rated capacity. For example, the fourth mapping data includes multiple correspondences, one of which is "package model of battery module XX, rated capacity Q rat1 ”, one of the corresponding relationships is “battery module package model YY, rated capacity Q rat2”, one of the corresponding relationships is “battery module package model ZZ, rated capacity Q rat3 ”.

[0096] For example, the package model of the battery module is XX, and the rated capacity Q of the battery module can be XX according to the package model of the battery module and one of the corresponding relationships in the fourth mapping data: "package model of the battery module XX, rated capacity Q rat1 ", determine the rated capacity Q corresponding to the battery module package model XX rat Q rat1 .

[0097] Step S2420: Obtain health status data of the battery module during each charging according to the charging capacity of the battery module during each charging and the rated capacity of the battery module.

[0098] In this step S2420, the health status data SOH of the battery module at any charging time satisfies the following formula:

[0099] SOH=Q curr / Q rat

[0100] Among them, Q curr Indicates the charging capacity of the battery module in any charge, Q rat Indicates the rated capacity of the battery module.

[0101] In one embodiment, after executing the above step S2400 to obtain the health status data of the battery module according to the charging capacity of the battery module in each charging, the health status determination method of the embodiment of the present disclosure may further include the following steps S3100 to S3300:

[0102] Step S3100: establishing second mapping data reflecting the corresponding relationship between time and health status data of the battery module.

[0103] The second mapping data can reflect the corresponding relationship between time and the health status data SOH of the battery module, referring to Figure 4 The second mapping data 21 is shown.

[0104] Step S3200: performing smoothing filtering on the second mapping data to obtain third mapping data.

[0105] In this embodiment, since there may be errors in the calculation of the charging capacity in each charging, and there may be abnormal health status data due to background acquisition accuracy errors, temperature differences, etc., the second mapping data can be smoothed and filtered based on the Savitzky-Golay filtering algorithm. After removing the abnormal health status data, a relatively smooth third mapping data that can represent the current battery module life is obtained. Figure 4 The third mapping data 22 is shown, and the life trend of the battery module can be observed based on the third mapping data 22 .

[0106] Step S3300: predicting the health status data of the battery module on the prediction day based on the third mapping data.

[0107] In this embodiment, after the third mapping data representing the life of the battery module is obtained, the health status data of the battery module on the prediction day can be predicted based on the third mapping data.

[0108] <Example>

[0109] Next, refer to Figure 5 , taking the battery module as a battery pack as an example, an example of a method for determining a health state is shown. In this example, the method for determining a health state may further include:

[0110] Step S501, performing a 0.2C charge and discharge test on a battery cell sample to obtain a 0.2C charge and discharge curve.

[0111] Among them, the battery cell samples and the battery cells in the battery pack are of the same type.

[0112] Step S502 , performing dimension reduction processing on the 0.2C charging curve, and obtaining a differential capacity curve of the 0.2C charging curve after the dimension reduction processing.

[0113] Step S503: The power corresponding to the second maximum point of the differential capacity curve of the 0.2C charging curve is used as the target inflection point power of the battery cell.

[0114] Step S504, obtaining a second capacity Q1 according to the target inflection point capacity of the battery cell.

[0115] Step S505, import all background vehicle status data of the target vehicle, the input fields are time, charging connection status, current total current of the battery pack, current capacity index of the battery pack, minimum single-cell voltage, minimum single-cell number, maximum single-cell voltage, maximum single-cell number, total mileage, minimum temperature, and maximum temperature data.

[0116] Step S506, searching the background vehicle status data for the first charging data of all AC charging of the battery pack of the target vehicle.

[0117] Step S507 , for each first charging data, obtaining the power corresponding to the second maximum point of the differential capacity curve of the first charging data as the target inflection point power of the battery pack.

[0118] Step S508 , for each first charging data, determining a first capacity Q2 of the battery pack from the target inflection point capacity of the battery pack to the charging end capacity.

[0119] Step S509, obtaining the charging capacity Q of the battery pack corresponding to the first charging data according to the first capacity and the second capacity. curr =Q1+Q2, wherein Q1 represents the second capacity, and Q2 represents the first capacity from the target inflection point capacity to the charging end capacity of the battery pack in this charging.

[0120] Step S510, according to the charging capacity Q of the battery pack in each charging curr And the rated capacity of the battery pack Q rat , obtain the health status data SOH of the battery pack during each charge.

[0121] It should be noted that the charging time, the depth of discharge (DOD), the initial charging voltage difference, the final charging voltage difference, etc. in each charging can be further calculated.

[0122] Step S511, establishing second mapping data reflecting the corresponding relationship between time and health status data of the battery pack, and performing smoothing filtering on the second mapping data to obtain third mapping data.

[0123] According to this example, on the one hand, it first determines the second capacity of the battery cell in the battery pack before the target inflection point power of the battery cell, and can combine the DV / DQ curve characteristics to find the power in any charging process corresponding to the second maximum point of the DV / DQ curve as the target inflection point power of the battery pack in any charging process, and perform ampere-hour integration method capacity calculation from the target inflection point power of the battery pack to the end-of-charging power to obtain the first capacity of the battery pack in any charging, and obtain the charging capacity of the battery pack in any charging based on the second capacity and the first capacity in any charging, and then obtain the health status data of the battery pack in any charging based on the rated capacity of the battery pack and the charging capacity of the battery pack in any charging.

[0124] On the other hand, it performs smoothing filtering on the second mapping data reflecting the corresponding relationship between time and the health status data of the battery pack to obtain third mapping data, and observes the life trend of the battery pack based on the third mapping data.

[0125] <Device Example>

[0126] The present disclosure also provides a health status determination device 600, such as Figure 6 As shown, it includes a first determining module 610 , a second determining module 620 and an acquiring module 630 .

[0127] A first determination module 610 is used to determine a first capacity of the battery module from a target inflection point capacity of the battery module to a charging end capacity according to first charging data of each charging of the battery module in multiple chargings; wherein the target inflection point capacity of the battery module is the capacity corresponding to the second maximum value point of the first differential capacity curve obtained based on the first charging data;

[0128] A second determination module 620 is used to determine a second capacity; wherein the second capacity is the capacity of the battery cell in the battery module before the target inflection point capacity of the battery cell, and the target inflection point capacity of the battery module is the capacity corresponding to the second maximum point of the first differential capacity curve obtained based on the first charging data;

[0129] The acquisition module 630 is used to obtain the charging capacity of the battery module in the charging corresponding to the first charging data according to the first capacity and the second capacity, and the charging capacity is used to obtain the health status data of the battery module.

[0130] In one embodiment, the first determination module 610 is specifically configured to determine the second capacity corresponding to the battery cell type of the battery module according to the battery cell type of the battery module and the first mapping data;

[0131] The first mapping data reflects the corresponding relationship between the battery cell type and the second capacity.

[0132] In one embodiment, the first determination module 610 is specifically used to obtain second charging data of a battery cell sample; wherein the battery cell sample and the battery cell in the battery module are of the same type of battery cell; perform dimensionality reduction processing on the second charging data, and obtain a second differential capacity curve of the second charging data after the dimensionality reduction processing; use the power corresponding to the second maximum point of the second differential capacity curve as the target inflection point power of the battery cell; and obtain the second capacity based on the target inflection point power of the battery cell.

[0133] In one embodiment, the charge end power quantity relates to one of the following: a set power threshold, and a power quantity when the charge end voltage of the battery module is greater than a set voltage threshold.

[0134] In one embodiment, the acquisition module 630 is also used to acquire the rated capacity of the battery module; and obtain the health status data of the battery module during each charging according to the charging capacity of the battery module during each charging and the rated capacity of the battery module.

[0135] In one embodiment, the apparatus 600 further includes a building module and a prediction module (neither of which are shown in the figure).

[0136] An establishing module, used to establish second mapping data reflecting the corresponding relationship between time and health status data of the battery module;

[0137] An acquisition module 630, configured to perform smoothing filtering on the second mapping data to obtain third mapping data;

[0138] A prediction module is used to predict the health status data of the battery module on a prediction day based on the third mapping data.

[0139] According to the embodiment of the present disclosure, it is possible to count the target inflection point power of the battery module in each charge, that is, the power corresponding to the second maximum point of the first differential capacity (DV / DQ) curve obtained based on the first charging data, and determine the first capacity of the battery module from the target inflection point power of the battery module to the charging end power in each charge, and then combine the second capacity of the battery cell before the target inflection point power to obtain the actual charging capacity of the battery module in each charge. That is to say, it is possible to estimate the charging capacity of the battery module in each charge in combination with the DV / DQ curve characteristics of the first charging data of each charge, thereby providing accuracy in charging capacity estimation, avoiding errors in the calculation of the health status data of the battery module caused by inaccurate charging capacity estimation, and improving the accuracy of the estimation of the health status data of the battery module, so that the life of the battery module can be better observed through the health status data of the battery module at each charge.

[0140] <Electronic equipment>

[0141] In this embodiment, an electronic device 700 is also provided. Figure 7 As shown, it includes a memory 720 and a processor 710 .

[0142] The memory 720 is used to store an executable computer program; the computer program is used to control the processor 710 to execute any one of the health status determination methods provided in this embodiment.

[0143] In this embodiment, the electronic device 700 may be Figure 1 The electronic device 1000 shown may also be a device with other hardware structures, which is not limited here.

[0144] In another embodiment, the electronic device 700 may include the above health status determination device 600.

[0145] In a specific implementation, the charging capacity may be determined by the same electronic device 700, and the health status data of the battery module may be determined based on the charging capacity. Of course, the charging capacity may be determined by one electronic device 700, and the health status data of the battery module may be determined by another electronic device 700 based on the charging capacity.

[0146] <Vehicle>

[0147] In this embodiment, a vehicle 800 is also provided. Figure 8 As shown, it includes a memory 820 and a processor 810 .

[0148] The memory 820 is used to store an executable computer program; the computer program is used to control the processor 810 to execute any one of the health status determination methods provided in this embodiment.

[0149] In this embodiment, the vehicle 800 can detect the health status data of the battery module and display the health status data of the battery module, for example, through a vehicle-mounted terminal, or send the detected health status data of the battery module to a user terminal or upload it to a server.

[0150] <Computer Readable Storage Medium>

[0151] In this embodiment, a computer-readable storage medium is further provided, on which a computer program is stored. When the computer program is executed by a processor, the method of any embodiment of the present disclosure is implemented.

[0152] <Computer Program Product>

[0153] In this embodiment, a computer program product is also provided, including a computer program, and when the computer program is executed by a processor, the method of any embodiment of the present disclosure is implemented.

[0154] The present invention may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present invention.

[0155] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0156] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0157] The computer program instructions for performing the operation of the present invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed entirely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be personalized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present invention.

[0158] Various aspects of the present invention are described herein with reference to the flow charts and / or block diagrams of the methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each box of the flow chart and / or block diagram and the combination of each box in the flow chart and / or block diagram can be implemented by computer-readable program instructions.

[0159] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0160] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0161] The flow charts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a part of a module, a program segment or an instruction, and a part of the module, a program segment or an instruction contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions. It is well known to those skilled in the art that it is equivalent to implement it by hardware, implement it by software, and implement it by combining software and hardware.

[0162] Embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The choice of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements to the technology in the marketplace, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein. The scope of the present invention is defined by the appended claims.

Claims

1. A method for determining a health status, applied to a battery module, characterized in that: The method comprises: Determine, according to first charging data of each charging of the battery module in multiple chargings, a first capacity of the battery module from a target inflection point capacity of the battery module to a charging end capacity; wherein the target inflection point capacity of the battery module is a capacity corresponding to a second maximum point of a first differential capacity curve obtained based on the first charging data; Determine a second capacity; wherein the second capacity is the capacity of the battery cell in the battery module before the target inflection point capacity of the battery cell; The charging capacity of the battery module in the charging corresponding to the first charging data is obtained according to the first capacity and the second capacity, and the charging capacity is used to obtain the health status data of the battery module.

2. The method according to claim 1, characterized in that The determining the second capacity includes: Determining the second capacity corresponding to the battery cell type of the battery module according to the battery cell type of the battery module and the first mapping data; The first mapping data reflects the corresponding relationship between the battery cell type and the second capacity.

3. The method according to claim 1, characterized in that The determining the second capacity includes: Acquire second charging data of a battery cell sample; wherein the battery cell sample and the battery cell in the battery module are of the same type of battery cell; performing dimensionality reduction processing on the second charging data, and obtaining a second differential capacity curve of the second charging data after the dimensionality reduction processing; The electric quantity corresponding to the second maximum value point of the second differential capacity curve is used as the target inflection point electric quantity of the battery cell; The second capacity is obtained according to the target inflection point capacity of the battery cell.

4. The method according to any one of claims 1 to 3, characterized in that The charge end power quantity involves one of the following: a set power threshold, and the power quantity when the charge end voltage of the battery module is greater than the set voltage threshold.

5. The method according to claim 1, characterized in that: After obtaining the charging capacity of the battery module in the charging corresponding to the first charging data according to the first capacity and the second capacity, the method further includes: Obtaining the rated capacity of the battery module; According to the charging capacity of the battery module in each charging and the rated capacity of the battery module, health status data of the battery module at each charging is obtained.

6. The method according to claim 5, characterized in that The method further comprises: Establishing second mapping data reflecting the corresponding relationship between time and health status data of the battery module; Performing smoothing filtering on the second mapping data to obtain third mapping data; The health status data of the battery module on the prediction day is predicted based on the third mapping data.

7. A device for determining a health status, applied to a battery module, characterized in that: The device comprises: A first determination module is used to determine a first capacity of the battery module from a target inflection point power of the battery module to a charging end power according to first charging data of each charging of the battery module in multiple chargings; wherein the target inflection point power of the battery module is a power corresponding to a second maximum point of a first differential capacity curve obtained based on the first charging data; A second determination module is used to determine a second capacity; wherein the second capacity is the capacity of the battery cell in the battery module before the target inflection point capacity of the battery cell; An acquisition module is used to obtain the charging capacity of the battery module in the charging corresponding to the first charging data according to the first capacity and the second capacity, and the charging capacity is used to obtain the health status data of the battery module.

8. A vehicle, characterized in that: The method comprises a memory and a processor, wherein the memory is used to store an executable computer program; and the computer program is used to control the processor to execute the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that The method comprises a computer program, which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 6.

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