Method, device and vehicle for estimating health status of power battery

Abstract

The present invention discloses a method, device, and vehicle for estimating the state of health of a power battery. The method comprises: obtaining battery state parameters and a target relationship curve for the power battery, wherein the target relationship curve represents the relationship between historical battery capacity decay and historical vehicle mileage; estimating the capacity of the power battery based on the battery state parameters and the target relationship curve to obtain an initial capacity estimate for the power battery; determining a current capacity estimate for the power battery based on the initial capacity estimate; and estimating the state of health of the power battery based on the current capacity estimate and the rated capacity estimate. This invention addresses the technical issue of low accuracy in power battery state of health estimation in related technologies.

Description

Technical Field

[0001] The present invention relates to the field of vehicle technology, and in particular to a method and device for estimating the health status of a power battery and a vehicle. Background Art

[0002] Power batteries are key components for the high-quality development of new energy vehicles. In order to extend the life of power batteries, it is crucial to accurately estimate the battery's state of health (SOH). Current related technologies are mainly based on data-driven battery health estimation, but this method has low accuracy.

[0003] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0004] Embodiments of the present invention provide a method and apparatus for estimating the health status of a power battery and a vehicle, so as to at least solve the technical problem of low accuracy in health status estimation of a power battery in related arts.

[0005] According to one aspect of an embodiment of the present invention, a method for estimating the health status of a power battery is provided, comprising: obtaining battery status parameters and a target relationship curve of the power battery, wherein the target relationship curve is used to represent the relationship between historical battery capacity decay and historical vehicle mileage; estimating the capacity of the power battery based on the battery status parameters and the target relationship curve to obtain an initial capacity estimate of the power battery; determining a current capacity estimate of the power battery based on the initial capacity estimate; and estimating the health status of the power battery based on the current capacity estimate and the rated capacity estimate.

[0006] Optionally, the capacity of the power battery is estimated based on the battery status parameters and the target relationship curve to obtain an initial capacity estimation value of the power battery, including: determining a mileage window based on the target relationship curve; screening the battery status parameters based on the mileage window to obtain an initial charging characteristic segment of the power battery, wherein the difference between the first charge and the second charge in the initial charging characteristic segment is greater than or equal to a preset difference, the first charge is the charge of the power battery at the end of charging, and the second charge is the charge of the power battery at the start of charging; correcting the first charge and the second charge based on a preset correction condition to obtain a first corrected charge and a second corrected charge; screening the initial charging characteristic segment based on the first corrected charge and the second corrected charge to obtain a target charging characteristic segment, wherein the difference between the first corrected charge and the second corrected charge in the target charging characteristic segment is greater than or equal to the preset difference; and estimating the capacity of the power battery based on the target charging characteristic segment to obtain an initial capacity estimation value.

[0007] Optionally, determining the mileage window based on the target relationship curve includes: determining a first mileage and a second mileage based on the target relationship curve, wherein the first mileage is the mileage corresponding to the calibrated capacity estimate value, and the second mileage is the mileage corresponding to the target turning point; and constructing a mileage window based on the first mileage and the second mileage.

[0008] Optionally, determining the current capacity estimate of the power battery based on the initial capacity estimate includes: clustering the initial capacity estimate to obtain clustering results, wherein the clustering results are used to indicate that the initial capacity estimate is divided into different clusters; and determining the current capacity estimate of the power battery based on the dividing points of different clusters.

[0009] Optionally, the capacity of the power battery is estimated based on the target charging characteristic segment to obtain an initial capacity estimation value, including: determining the charging start time, charging end time, current value during the power battery charging process, and charge change value of the power battery in the target charging characteristic segment; determining the battery capacity change value of the power battery based on the charging start time, charging end time and current value; and estimating the capacity of the power battery based on the battery capacity change value and the charge change value to obtain an initial capacity estimation value.

[0010] Optionally, the above method further includes: acquiring an initial relationship curve of the power battery; and interpolating the initial relationship curve based on a preset step size to obtain a target relationship curve.

[0011] Optionally, the above method further includes: determining a preset step length based on a preset ratio and a battery rated capacity of the power battery.

[0012] According to another aspect of an embodiment of the present invention, a device for estimating the health status of a power battery is provided, including: an acquisition module for acquiring battery status parameters and a target relationship curve of the power battery, wherein the target relationship curve is used to represent the relationship between historical battery capacity decay and historical vehicle mileage; a first estimation module for estimating the capacity of the power battery based on the battery status parameters and the target relationship curve to obtain an initial capacity estimation value of the power battery; a determination module for determining a current capacity estimation value of the power battery based on the initial capacity estimation value; and a second estimation module for estimating the health status of the power battery based on the current capacity estimation value and the rated capacity estimation value.

[0013] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is further provided, which includes a stored program, wherein when the program is run, the processor of the device where the program is located is controlled to execute any of the above-mentioned methods for estimating the health status of a power battery.

[0014] According to another aspect of an embodiment of the present invention, a vehicle is also provided, characterized in that it includes: one or more processors; a storage device for storing one or more programs; when the one or more programs are executed by one or more processors, the one or more processors execute any one of the above-mentioned methods for estimating the health status of a power battery.

[0015] According to another aspect of an embodiment of the present invention, a processor is further provided, and the processor is used to run a program, wherein the program executes the above-mentioned method for estimating the health status of a power battery when running.

[0016] In an embodiment of the present invention, a battery state parameter and a target relationship curve of a power battery are obtained, wherein the target relationship curve is used to represent the relationship between historical battery capacity decay and historical vehicle mileage; the capacity of the power battery is estimated based on the battery state parameter and the target relationship curve to obtain an initial capacity estimate of the power battery; a current capacity estimate of the power battery is determined based on the initial capacity estimate; and the health state of the power battery is estimated based on the current capacity estimate and the rated capacity estimate. Through the above method, the capacity of the power battery is estimated based on the battery state parameter and the relationship between battery capacity decay and vehicle mileage to obtain an initial capacity estimate of the power battery; then the current capacity estimate of the power battery is determined; and finally, the health state of the power battery can be estimated based on the current capacity estimate and the rated capacity estimate. This achieves the purpose of determining the current capacity value of the vehicle based on the relationship between battery capacity decay and vehicle mileage and estimating the health state of the power battery, thereby achieving the technical effect of improving the efficiency of power battery health state estimation and solving the technical problem of low accuracy of power battery health state estimation in related technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0018] Figure 1 is a flow chart of a method for estimating the health status of a power battery according to an embodiment of the present invention;

[0019] Figure 2 is a flow chart of an optional method for estimating the health status of a power battery according to an embodiment of the present invention;

[0020] Figure 3 is a schematic diagram of a health status estimation system for a power battery according to an embodiment of the present invention;

[0021] Figure 4 2 is a schematic diagram of a device for estimating the health status of a power battery according to an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only 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 making creative efforts should fall within the scope of protection of the present invention.

[0023] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily 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 devices.

[0024] Example 1

[0025] According to an embodiment of the present invention, a method for estimating the health status of a power battery is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0026] Figure 1 FIG. 1 is a flow chart of a method for estimating the health status of a power battery according to an embodiment of the present invention. Figure 1 As shown, the method includes the following steps:

[0027] Step S102: Obtain a battery state parameter and target relationship curve of the power battery.

[0028] Among them, the battery status parameters can be understood as specific parameters used to represent the status of the power battery, which may include but are not limited to: battery position, time, voltage, current, temperature, etc. The target relationship curve can be understood as a curve representing the relationship between historical battery capacity attenuation and historical vehicle mileage.

[0029] It can be understood that by obtaining the battery status parameters and target relationship curve of the power battery, the real-time status of the vehicle can be obtained, and the mileage window value corresponding to the target turning point of the vehicle model can be determined based on the corresponding relationship between mileage and capacity attenuation.

[0030] In an optional embodiment, the battery status parameters of the power battery may be obtained through corresponding sensors, for example, the voltage of the power battery may be obtained through a voltage sensor, and the temperature of the power battery may be obtained through a temperature sensor.

[0031] Step S104 , estimating the capacity of the power battery based on the battery state parameters and the target relationship curve to obtain an initial capacity estimation value of the power battery.

[0032] The initial capacity estimation value may be understood as a capacity value of the power battery estimated based on specific state parameters of the power battery.

[0033] It is understandable that by estimating the capacity of the power battery based on the battery state parameters, an initial capacity estimation value of the power battery in the current state can be obtained, so that the health state of the power battery can be accurately estimated subsequently.

[0034] In an optional embodiment, the capacity of the power battery can be estimated by calculating the capacity change of the battery during the charging process using a mathematical formula based on the battery state parameters, and then calculating the battery capacity to obtain an initial capacity estimation value of the power battery.

[0035] Step S106 : determining a current estimated capacity value of the power battery according to the initial estimated capacity value.

[0036] The current capacity estimation value may be understood as the current battery capacity value of the power battery.

[0037] It can be understood that determining the current capacity estimate of the power battery based on the initial capacity estimate and estimating the health status of the power battery based on the current capacity estimate can effectively avoid the noise problem of the existing SOH estimated based on the data-driven method and improve the accuracy of the health status estimation of the power battery.

[0038] Step S108 : estimating the health status of the power battery based on the current capacity estimation value and the rated capacity estimation value.

[0039] Among them, the estimated value of rated capacity can be understood as the capacity measured in accordance with national standards when the battery leaves the factory.

[0040] It can be understood that estimating the health status of the power battery based on the current capacity estimation value and the rated capacity estimation value can effectively circumvent the noise problem of the existing SOH estimated based on the data-driven method, improve the accuracy of the health status estimation of the power battery, and achieve the purpose of determining the current capacity value of the vehicle based on the relationship between battery capacity attenuation and vehicle mileage, and estimating the health status of the power battery, thereby achieving the technical effect of improving the efficiency of the health status estimation of the power battery, and further solving the technical problem of low accuracy of the health status estimation of the power battery in the related technology.

[0041] Through the above steps, the battery state parameters and target relationship curve of the power battery are obtained, wherein the target relationship curve is used to represent the relationship between historical battery capacity decay and historical vehicle mileage; the power battery capacity is estimated based on the battery state parameters and the target relationship curve to obtain an initial capacity estimate of the power battery; the current capacity estimate of the power battery is determined based on the initial capacity estimate; and the health state of the power battery is estimated based on the current capacity estimate and the rated capacity estimate. Through the above method, the power battery capacity is estimated based on the battery state parameters and the relationship between battery capacity decay and vehicle mileage to obtain an initial capacity estimate of the power battery; then the current capacity estimate of the power battery is determined; and finally, the health state of the power battery can be estimated based on the current capacity estimate and the rated capacity estimate. This achieves the purpose of determining the current capacity value of the vehicle based on the relationship between battery capacity decay and vehicle mileage and estimating the health state of the power battery, thereby achieving the technical effect of improving the efficiency of power battery health state estimation and solving the technical problem of low accuracy of power battery health state estimation in related technologies.

[0042] Optionally, the capacity of the power battery is estimated based on the battery status parameters to obtain an initial capacity estimation value of the power battery, including: determining a mileage window based on a target relationship curve; screening the battery status parameters based on the mileage window to obtain an initial charging characteristic segment of the power battery, wherein the difference between the first charge and the second charge in the initial charging characteristic segment is greater than or equal to a preset difference, the first charge is the charge of the power battery at the end of charging, and the second charge is the charge of the power battery at the start of charging; correcting the first charge and the second charge based on a preset correction condition to obtain a first corrected charge and a second corrected charge; screening the initial charging characteristic segment based on the first corrected charge and the second corrected charge to obtain a target charging characteristic segment, wherein the difference between the first corrected charge and the second corrected charge in the target charging characteristic segment is greater than or equal to the preset difference; and estimating the capacity of the power battery based on the target charging characteristic segment to obtain an initial capacity estimation value.

[0043] Among them, the initial charging characteristic segment can be understood as the charging characteristic segment obtained after screening the battery status parameters, the first charge can be understood as the charge corresponding to the charging end time, the second charge can be understood as the charge corresponding to the charging start time, the preset difference can be understood as the difference between the charge corresponding to the pre-set charging end time and the charging start time, for example, it can be 60%, but not limited to this, the preset correction condition can be understood as the pre-set correction condition of the battery management system, the first corrected charge can be understood as the charge corresponding to the charging end time after correction that meets the preset correction condition, the second corrected charge can be understood as the charge corresponding to the charging start time after correction that meets the preset correction condition, and the target charging characteristic segment can be understood as the real charging characteristic segment after screening.

[0044] Specifically, the above process can be understood as: screening the battery charging segment, the battery state of charge (State of Charge, referred to as SOC) corresponding to the charging end time and the charging start time needs to meet the SOC end_real -SOC start_real ≥60%, the SOC correction condition of the battery management system must be met when charging starts. According to the corresponding relationship between the uploaded SOC and the actual SOC of the battery, the accurate actual SOC at that moment can be obtained, that is, SOC start_real The charging end time or the start time of the first data segment after charging needs to meet the SOC correction condition of the battery management system. According to the corresponding relationship between the uploaded SOC and the actual SOC of the battery, the accurate actual SOC at that moment can be obtained, that is, the SOC end_real , the actual SOC corresponding to the charging end time and the charging start time needs to meet the SOC end_real -SOC start_real ≥60%.

[0045] It should be noted that the battery charging segments can be screened according to the signal accuracy judgment rule, that is, the charging segments that do not meet the judgment rule are eliminated. The signal accuracy judgment rule is specifically shown in Table 1 below:

[0046] Table 1 Judgment rules for signal accuracy

[0047] Signal Type Threshold judgment condition Cell voltage [0,5V], out of range filtered out Voltage default exclusions All monomer voltages are 0 or set to default values. This invention takes 3.65V as an example. Battery module temperature [-40℃, 210℃], filter out those out of range Current value [-1500A, 1500A], filter out the ones outside the range SOC value [0, 100%], out of range filtered out Vehicle mileage [0,1000000km], filter out the values ​​outside the range

[0048] The integrity of each frame of data is judged as follows: when there is one or more missing values ​​in the cell voltage data, it is recorded as invalid data and the frame data is discarded. The logic of each frame of data is judged as follows: when the current value is valid, the SOC (or mileage, etc.) changes, but the cell voltage value does not change, it is considered that the cell voltage data of this frame may have sampling abnormalities or data delays that cause data unreliability problems, and it is recorded as invalid data, and the frame data is also discarded.

[0049] Optionally, determining the mileage window based on the target relationship curve includes: determining a first mileage and a second mileage based on the target relationship curve, wherein the first mileage is the mileage corresponding to the calibrated capacity estimate value, and the second mileage is the mileage corresponding to the target turning point; and constructing a mileage window based on the first mileage and the second mileage.

[0050] Specifically, the above process can be understood as: the current capacity of the battery is obtained by calibration, which is recorded as Q model_0 , the corresponding mileage is the beginning of the mileage window, denoted as M start , using the empirical value of the relationship between the current target turning point and the mileage window as input, determine (Q model_0 -0.1%*Q C ) The first mileage corresponding to the mileage window is the end of the M end , calculate (Q model_0 -0.1%*Q C )'s mileage window is built.

[0051] Optionally, determining the current capacity estimate of the power battery based on the initial capacity estimate includes: clustering the initial capacity estimate to obtain clustering results, wherein the clustering results are used to indicate that the initial capacity estimate is divided into different clusters; and determining the current capacity estimate of the power battery based on the dividing points of different clusters.

[0052] Specifically, the above process can be understood as: matching the characteristic fragments of capacity calculation for each charging process of the vehicle battery, calculating the capacity value of each battery that meets the calculation conditions, obtaining the corresponding relationship between capacity and mileage, and continuing the capacity calculation until the current mileage M current Infinitely close to the end of the mileage window M end , you can set M end -M current ≤500 km, but not limited to this, get the capacity estimation results list within this mileage window {Q current_1 , Q current_2 ,…,Q current_n}, and then use density clustering algorithm to cluster {Q current_1 , Q current_2 ,…,Q current_n} clustering, theoretically the above set should be clustered into 2 categories, then the current battery capacity is (Q model_0 -0.1%*Q C ).

[0053] The dividing point between category 1 and category 2 is (Q model_0 -0.1%*Q C ) corresponds to the mileage, which is used as (Q model_0 -0.1%*QC ) starting mileage, with (Q model_0 -0.1%*Q C ) as the initial capacity and repeat the above steps to obtain the battery capacity value in the next state.

[0054] In particular, if only one type is clustered in the above steps, the current battery capacity is still To increase the end mileage value in the mileage window, you can select The corresponding first mileage value is regarded as the end of the mileage window, and steps (3) and (4) are repeated until the capacity calculation results can be clustered into two categories, and the battery capacity is obtained as Repeat steps (2)-(4) as the initial capacity to obtain the battery capacity value in the next state. The battery SOH can be obtained by Come get.

[0055] It can be understood that the density clustering algorithm can be understood as a clustering method based on the density of sample points. Compared with the traditional distance-based clustering algorithm, density clustering is more suitable for processing data sets in non-convex, noisy or densely distributed data. Therefore, clustering the initial capacity estimation values ​​through the density clustering algorithm to obtain clustering results can effectively avoid the noise problem in the existing technology and improve the accuracy of the health status estimation of the power battery.

[0056] Optionally, the capacity of the power battery is estimated based on the target charging characteristic segment to obtain an initial capacity estimation value, including: determining the charging start time, charging end time, current value during the power battery charging process, and charge change value of the power battery in the target charging characteristic segment; determining the battery capacity change value of the power battery based on the charging start time, charging end time and current value; and estimating the capacity of the power battery based on the battery capacity change value and the charge change value to obtain an initial capacity estimation value.

[0057] The charge change value can be understood as the current value that changes with time during the charging process, and the battery capacity change value can be understood as the change value of the battery capacity during the charging process.

[0058] Specifically, the above process can be expressed using a mathematical formula: Calculate the capacity change of the battery during the charging process. The specific formula is as follows:

[0059]

[0060] Where ΔQ charge is the amount of electricity charged during the charging process, t0 is the start time of battery charging, t1 is the end time of battery charging, and I(t) is the current that changes with time during the charging process;

[0061] Calculate the battery capacity, the specific formula is as follows:

[0062]

[0063] Among them, Q current is the capacity of the battery, that is, the estimated initial capacity, SOC end_real The actual SOC corresponding to the end of charging, that is, the first corrected charge, SOC start_real is the actual SOC corresponding to the start time of charging, that is, the second corrected charge.

[0064] Optionally, the above method further includes: acquiring an initial relationship curve of the power battery; and interpolating the initial relationship curve based on a preset step size to obtain a target relationship curve.

[0065] Among them, the initial relationship curve can be understood as the relationship curve corresponding to the battery capacity attenuation and vehicle mileage calibrated in advance, and the preset step size can be understood as the pre-set step size for interpolating the initial relationship curve, for example, it can be 0.1% of the battery rated capacity, but is not limited to this.

[0066] Specifically, a relationship curve between battery capacity attenuation and vehicle mileage, i.e., an initial relationship curve, can be calibrated based on the vehicle reliability and durability test. The relationship curve between battery capacity attenuation and vehicle mileage can be interpolated at a step size of 0.1% of the battery rated capacity to obtain the vehicle mileage relationship corresponding to each decrease of 0.1% of the battery rated capacity, i.e., the target relationship curve.

[0067] In an optional embodiment, the initial relationship curve may be determined through a vehicle reliability and durability test.

[0068] In another optional embodiment, determining the capacity decay inflection point and the mileage window based on the target relationship curve can be achieved through the following process: taking the first mileage value corresponding to the battery capacity value as the beginning of the mileage window, and taking the first mileage value corresponding to the battery capacity value minus 0.1% of the battery rated capacity as the end of the mileage window. Through the above process, the mileage window value corresponding to every 0.1% of the battery rated capacity decay of the battery is calibrated as the initial value of the relationship between the capacity decay inflection point and the mileage window. The calculated result of the corresponding relationship between each on-board battery capacity decay value and the mileage window is used as a sample. The start and end of the mileage window corresponding to the same battery capacity are counted and recalibrated with the average value or median to obtain an updated value of the relationship between the target turning point and the mileage window, which is used as the empirical value of the relationship between the target turning point and the mileage window.

[0069] Optionally, the above method further includes: determining a preset step length based on a preset ratio and a battery rated capacity of the power battery.

[0070] The preset ratio may be understood as a ratio preset in advance in the rated capacity of the battery, for example, 0.1%, but not limited thereto. The rated capacity of the battery may be understood as the capacity of the battery under rated working conditions.

[0071] In an optional embodiment, the preset step size determined based on the preset ratio and the rated battery capacity of the power battery may be 0.1% of the rated battery capacity.

[0072] Figure 2 FIG. 1 is a flow chart of an optional method for estimating the state of health of a power battery according to an embodiment of the present invention. Figure 2 As shown, the specific process includes: step S21, power battery signal acquisition and cleaning; step S22, characteristic operating condition identification for battery capacity estimation; step S23, battery capacity estimation; step S24, mileage window determination of target turning point; step S25, battery SOH estimation.

[0073] Figure 3 FIG. 1 is a schematic diagram of a health status estimation system for a power battery according to an embodiment of the present invention. Figure 3 As shown, the system includes a vehicle-side execution system, a cloud computing system and a vehicle-cloud communication system. The vehicle-side execution system also includes: a data acquisition module for real-time on-board battery position, time, voltage, current, temperature and other data during vehicle driving; an information prompt module for receiving and displaying battery SOH estimation results; a battery state control module for receiving the battery SOH estimation results to calculate other battery states and further control the battery; the cloud computing system also includes: a data cleaning module for eliminating data that exceeds a threshold range and does not conform to logical changes; a battery capacity calculation module for performing feature judgment based on the battery charging process and calculating the battery capacity based on charging process data that meets the conditions; a mileage window determination module for SOH estimation, for determining the empirical value of the relationship between the target turning point and the mileage window as a key input for battery SOH estimation; the vehicle-cloud communication system also includes: a data upload module for transferring the collected signals to the cloud big data platform according to certain coding rules; an information dissemination module for sending the battery SOH estimation results to the vehicle-side information display module (or user mobile phone application) and the battery state control module.

[0074] Example 2

[0075] According to another aspect of an embodiment of the present invention, a device for estimating the health status of a power battery is also provided. The device can execute the method for estimating the health status of a power battery in the above-mentioned embodiment 1. The specific implementation scheme and application scenario in this embodiment are the same as those in the above-mentioned embodiment 1 and will not be repeated here.

[0076] Figure 4FIG. 1 is a schematic diagram of a device for estimating the state of health of a power battery according to an embodiment of the present invention. Figure 4 As shown, the device includes: an acquisition module 402, used to obtain battery status parameters and a target relationship curve of the power battery, wherein the target relationship curve is used to represent the relationship between historical battery capacity attenuation and historical vehicle mileage; a first estimation module 404, used to estimate the capacity of the power battery based on the battery status parameters and the target relationship curve, and obtain an initial capacity estimation value of the power battery; a determination module 406, used to determine a current capacity estimation value of the power battery according to the initial capacity estimation value; and a second estimation module 408, used to estimate the health status of the power battery based on the current capacity estimation value and the rated capacity estimation value.

[0077] The first estimation module 404 includes: a window determination unit, which is used to determine a mileage window based on a target relationship curve; a first screening unit, which is used to screen the battery status parameters based on the mileage window to obtain an initial charging characteristic segment of the power battery, wherein the difference between the first charge and the second charge in the initial charging characteristic segment is greater than or equal to a preset difference, the first charge is the charge of the power battery at the end of charging, and the second charge is the charge of the power battery at the start of charging; a correction unit, which is used to correct the first charge and the second charge based on a preset correction condition to obtain a first corrected charge and a second corrected charge; a second screening unit, which is used to screen the initial charging characteristic segment based on the first corrected charge and the second corrected charge to obtain a target charging characteristic segment, wherein the difference between the first corrected charge and the second corrected charge in the target charging characteristic segment is greater than or equal to the preset difference; and an estimation unit, which is used to estimate the capacity of the power battery based on the target charging characteristic segment to obtain an initial capacity estimation value.

[0078] The window determination unit includes: a mileage determination subunit, used to determine a first mileage and a second mileage based on a target relationship curve, wherein the first mileage is the mileage corresponding to the calibrated capacity estimation value, and the second mileage is the mileage corresponding to the target turning point; and a construction subunit, used to construct a mileage window based on the first mileage and the second mileage.

[0079] The determination module 406 includes: a clustering unit for clustering the initial capacity estimation values ​​to obtain a clustering result, wherein the clustering result is used to indicate that the initial capacity estimation values ​​are divided into different clusters; and a capacity determination unit for determining the current capacity estimation value of the power battery based on the dividing points of different clusters.

[0080] The estimation unit includes: a first determination subunit, used to determine the charging start time, charging end time, current value during the power battery charging process, and charge change value of the power battery in the target charging characteristic segment; a second determination subunit, used to determine the battery capacity change value of the power battery based on the charging start time, charging end time and current value; and an estimation subunit, used to estimate the capacity of the power battery based on the battery capacity change value and the charge change value to obtain an initial capacity estimation value.

[0081] The above-mentioned device also includes: a curve acquisition module, which is used to obtain an initial relationship curve of the power battery; and an interpolation module, which is used to interpolate the initial relationship curve based on a preset step size to obtain a target relationship curve.

[0082] The above-mentioned device also includes: a step length determination module, which is used to determine a preset step length based on a preset ratio and a battery rated capacity of the power battery.

[0083] Example 3

[0084] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is further provided, characterized in that the computer-readable storage medium includes a stored program, wherein when the program is running, the processor of the device where the program is located is controlled to execute any of the above-mentioned methods for estimating the health status of a power battery.

[0085] Example 4

[0086] According to another aspect of an embodiment of the present invention, a vehicle is also provided, characterized in that it includes: one or more processors; a storage device for storing one or more programs; when the one or more programs are executed by one or more processors, the one or more processors execute any one of the above-mentioned methods for estimating the health status of a power battery.

[0087] Example 5

[0088] According to another aspect of an embodiment of the present invention, a processor is further provided, and the processor is used to run a program, wherein the program executes the above-mentioned method for estimating the health status of a power battery when running.

[0089] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0090] In the above embodiments of the present invention, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0091] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0092] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0093] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0094] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc. Various media that can store program codes.

[0095] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A method for estimating the health status of a power battery, characterized in that: include: Obtaining a battery state parameter of the power battery and a target relationship curve, wherein the target relationship curve is used to represent the relationship between historical battery capacity attenuation and historical vehicle mileage; Determining a first mileage and a second mileage based on the target relationship curve, wherein the first mileage is the mileage corresponding to the calibrated capacity estimation value, and the second mileage is the mileage corresponding to a target turning point, and the target turning point is the capacity attenuation inflection point of the power battery; constructing a mileage window based on the first mileage and the second mileage; determining an estimated initial capacity of the power battery based on the mileage window, the battery state parameter, a preset difference, and a preset correction condition; Determining a current capacity estimate of the power battery according to the initial capacity estimate; estimating a health state of the power battery based on the current capacity estimate and the rated capacity estimate; Determining an initial capacity estimation value of the power battery based on the mileage window, the battery state parameter, a preset difference, and a preset correction condition, including: screening the battery state parameter based on the mileage window to obtain an initial charging characteristic segment of the power battery, wherein a difference between a first charge and a second charge in the initial charging characteristic segment is greater than or equal to the preset difference, the first charge being the charge of the power battery at the end of charging, and the second charge being the charge of the power battery at the start of charging; correcting the first charge and the second charge based on the preset correction condition to obtain a first corrected charge and a second corrected charge; screening the initial charging characteristic segment based on the first corrected charge and the second corrected charge to obtain a target charging characteristic segment, wherein a difference between the first corrected charge and the second corrected charge in the target charging characteristic segment is greater than or equal to the preset difference; and estimating the capacity of the power battery based on the target charging characteristic segment to obtain the initial capacity estimation value; Determining a current capacity estimate of the power battery based on the initial capacity estimate includes: clustering the initial capacity estimate to obtain a clustering result, wherein the clustering result is used to indicate that the initial capacity estimate is divided into different clusters; and determining the current capacity estimate of the power battery based on a dividing point between the different clusters.

2. The method for estimating the health status of a power battery according to claim 1, characterized in that: Estimating the capacity of the power battery based on the target charging characteristic segment to obtain the initial capacity estimation value includes: Determining the charging start time, charging end time, current value during the charging process of the power battery, and charge change value of the power battery in the target charging characteristic segment; determining a battery capacity change value of the power battery based on the charging start time, the charging end time, and the current value; The capacity of the power battery is estimated based on the battery capacity change value and the charge change value to obtain the initial capacity estimation value.

3. The method for estimating the health status of a power battery according to claim 1, characterized in that: The method further comprises: Obtaining an initial relationship curve of the power battery; The initial relationship curve is interpolated based on a preset step size to obtain the target relationship curve.

4. The method for estimating the health status of a power battery according to claim 3, characterized in that: The method further comprises: The preset step length is determined based on a preset ratio and a rated battery capacity of the power battery.

5. A device for estimating the health status of a power battery, characterized in that: include: an acquisition module, configured to acquire battery state parameters of the power battery and a target relationship curve, wherein the target relationship curve is used to represent the relationship between historical battery capacity attenuation and historical vehicle mileage; a first estimation module, configured to determine a first mileage and a second mileage based on the target relationship curve, wherein the first mileage is the mileage corresponding to the calibrated capacity estimation value, and the second mileage is the mileage corresponding to a target turning point, wherein the target turning point is a capacity attenuation inflection point of the power battery; A construction module, configured to construct a mileage window based on the first mileage and the second mileage; a first determining module, configured to determine an estimated initial capacity value of the power battery based on the mileage window, the battery state parameter, a preset difference, and a preset correction condition; a second determining module, configured to determine a current capacity estimation value of the power battery according to the initial capacity estimation value; a second estimation module, configured to estimate the health state of the power battery based on the current capacity estimation value and the rated capacity estimation value; The first determination module is further configured to determine an initial capacity estimation value of the power battery based on the mileage window, the battery state parameter, a preset difference, and a preset correction condition through the following steps: filtering the battery state parameter based on the mileage window to obtain an initial charging characteristic segment of the power battery, wherein a difference between a first charge and a second charge in the initial charging characteristic segment is greater than or equal to the preset difference, the first charge being the charge of the power battery at the end of charging, and the second charge being the charge of the power battery at the start of charging; correcting the first charge and the second charge based on the preset correction condition to obtain a first corrected charge and a second corrected charge; filtering the initial charging characteristic segment based on the first corrected charge and the second corrected charge to obtain a target charging characteristic segment, wherein a difference between the first corrected charge and the second corrected charge in the target charging characteristic segment is greater than or equal to the preset difference; and estimating the capacity of the power battery based on the target charging characteristic segment to obtain the initial capacity estimation value; The second determination module is further used to determine the current capacity estimation value of the power battery based on the initial capacity estimation value through the following steps: clustering the initial capacity estimation values ​​to obtain clustering results, wherein the clustering results are used to indicate that the initial capacity estimation values ​​are divided into different clusters; and determining the current capacity estimation value of the power battery based on the dividing points of the different clusters.

6. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored program, wherein when the program is executed, the method for estimating the health status of a power battery according to any one of claims 1 to 4 is executed in a processor of a device where the program is controlled.

7. A vehicle, characterized in that: include: one or more processors; a storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors execute the health status estimation method for a power battery according to any one of claims 1 to 4.

Images