Power battery capacity correction method, system, device and medium based on mileage

Abstract

The present invention relates to a method, system, device and medium for correcting the capacity of a power battery based on mileage. The method comprises: sampling the battery parameters of a power battery to be tested and the mileage of the corresponding electrified vehicle, obtaining the battery parameters and mileage within a preset sampling period, and dividing the sampling period into a plurality of charging periods and a plurality of discharging periods according to the battery parameters; analyzing each charging period and discharging period, and calculating the maximum available capacity of the period according to the battery parameters within each period; selecting the period to be corrected from all the discharging periods according to all the maximum available capacities of the charging period and the discharging period; and correcting the maximum available capacity of each period to be corrected based on a correction model according to the mileage and the battery parameters. The present invention improves the accuracy of the calculation of the maximum available capacity of the power battery.

Description

Technical Field

[0001] The present invention relates to the field of battery technology, and in particular to a method, system, device and medium for correcting power battery capacity based on mileage. Background Art

[0002] In order to improve the safety and economy of energy storage systems, accurately estimating the state of health (SOH) of power batteries in electrified vehicles has become an issue of increasing concern. Electrified vehicles include but are not limited to electric vehicles, rail transit vehicles, electric ships, electric aircraft, electric bicycles, electric motorcycles, electric agricultural machinery or engineering machinery, etc. Power batteries include but are not limited to lithium-ion batteries, sodium-ion batteries, quasi-solid-state batteries, all-solid-state batteries, etc.

[0003] As the power battery continues to age, its maximum available capacity will gradually decay. Therefore, how to accurately estimate the maximum available capacity of the power battery is of great significance for evaluating the health status of the power battery. At present, the research and development of the maximum available capacity estimation and prediction of power batteries is mainly concentrated on monomers, modules and systems in laboratory environments, while the research and development of power battery systems under actual working conditions is relatively insufficient. The existing method for estimating the maximum available capacity of such power batteries has the following disadvantages: on the one hand, it is impossible to accurately evaluate the performance of the power battery in the actual use environment, and it is highly dependent on the charging data of the electrified vehicle. On the other hand, there are few studies on the estimation of the power battery capacity based on driving data, among which the driving mileage has a strong correlation with the maximum available capacity of the power battery, but the current research methods rarely consider the driving mileage when estimating the capacity of the power battery, so that the capacity estimation of any time or mileage range cannot be obtained. Therefore, in order to obtain the capacity estimation of power batteries of any scale, it is necessary to provide a mileage-based power battery capacity correction method, system, device and medium. Summary of the invention

[0004] The present invention provides a method, system, device and medium for correcting the capacity of a power battery based on mileage, which improves the problem that the maximum available capacity of a power battery calculated in the prior art is not accurate enough.

[0005] A mileage-based power battery capacity correction method provided by the present invention is applied to electric vehicles, and the method includes: sampling the battery parameters of the power battery to be tested and the mileage of the corresponding electric vehicle, obtaining the battery parameters and mileage within a preset sampling period, and dividing the sampling period into multiple charging periods and multiple discharging periods according to the battery parameters, analyzing each charging period and discharging period: calculating the maximum available capacity of each period according to the battery parameters in the period; selecting the period to be corrected from all the discharging periods according to all the maximum available capacities of the charging period and the discharging period; and correcting the maximum available capacity of each period to be corrected based on a correction model according to the mileage and battery parameters.

[0006] In one embodiment of the present invention, the calculation of the maximum available capacity of each time period based on the battery parameters in the time period includes: calculating the charge change in the charging period / discharging period based on the charge amount of the battery parameters at the start and end times of the charging period / discharging period; calculating the charge state change in the charging period / discharging period based on the charge state of the battery parameters at the start and end times of the charging period / discharging period; and taking the ratio of the charge change to the charge state change as the maximum available capacity of the charging period / discharging period.

[0007] In one embodiment of the present invention, the method of selecting the time period to be corrected from all the discharge time periods according to all the maximum available capacities of the charge time periods and the discharge time periods includes: dividing all the maximum available capacities of the charge time periods into a plurality of capacity intervals based on a preset division criterion, counting the number of charge time periods in each capacity interval, and taking the capacity interval with the largest number of charge time periods as the normal capacity interval; comparing the maximum available capacity of each discharge time period with the normal capacity interval, and taking all the discharge time periods that are not in the normal capacity interval as the time periods to be corrected.

[0008] In one embodiment of the present invention, all the maximum available capacities of the charging time period are divided into multiple capacity intervals based on a preset division criterion, and the number of charging time periods in each capacity interval is counted, and the capacity interval with the largest number of charging time periods is taken as a normal capacity interval, including: arranging all the maximum available capacities of the charging time period in sequence to form a maximum available capacity sequence; dividing the maximum available capacity sequence into multiple capacity intervals based on a preset capacity interval; counting the number of charging time periods contained in each capacity interval, screening out the capacity interval with the largest number of charging time periods, and taking it as the normal capacity interval.

[0009] In one embodiment of the present invention, the correction model is an extreme gradient correction model.

[0010] In one embodiment of the present invention, for each time period to be corrected, the maximum available capacity of the time period to be corrected is corrected based on a correction model according to the mileage and the battery parameters, including: determining a battery status parameter according to the mileage and the battery parameters; inputting the battery status parameter into the correction model to obtain a charge change per unit mileage; and correcting the maximum available capacity of the time period to be corrected based on the charge change per unit mileage and the charge state change per unit mile of the battery status parameter.

[0011] In one embodiment of the present invention, the battery status parameters are determined based on the mileage and the battery parameters, including: calculating the change in the state of charge of the time period to be corrected based on the state of charge of the battery parameters at the start and end times of the time period to be corrected; calculating the change in charge of the time period to be corrected based on the charge of the battery parameters at the start and end times of the time period to be corrected; calculating the change in voltage of the time period to be corrected based on the voltage of the battery parameters at the start and end times of the time period to be corrected; taking the ratio of the change in state of charge to the mileage as the change in state of charge per unit mileage; taking the ratio of the voltage change to the change in state of charge as the voltage change per unit state of charge; taking the ratio of the voltage change to the charge change as the voltage change per unit charge.

[0012] In one embodiment of the present invention, a mileage-based power battery capacity correction system is also provided, and the system includes: a data acquisition module, which is used to sample the battery parameters of the power battery to be tested and the mileage of the corresponding electrified vehicle, obtain the battery parameters and mileage within a preset sampling period, and divide the sampling period into multiple charging periods and multiple discharging periods according to the battery parameters; a maximum available capacity determination module, which is used to analyze each charging period and discharging period: calculate the maximum available capacity of the period according to the battery parameters in each period; a to-be-corrected period screening module, which is used to screen out the to-be-corrected period from all the discharging periods according to all the maximum available capacities of the charging period and the discharging period; a correction module, which is used to correct the maximum available capacity of each to-be-corrected period based on a correction model according to the mileage and battery parameters.

[0013] In one embodiment of the present invention, an electronic device is also provided, including: 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 electronic device implements any of the above-mentioned mileage-based power battery capacity correction methods.

[0014] In one embodiment of the present invention, a computer-readable storage medium is further provided, on which a computer program is stored. When the computer program is executed by a processor of a computer, the computer executes any of the above-mentioned methods for correcting the power battery capacity based on mileage.

[0015] As described above, the method, system, device and medium for correcting the power battery capacity based on mileage proposed in the present invention have the following beneficial effects: by sampling the battery parameters and corresponding mileage of the power battery, and dividing the sampling period into a charging period and a discharging period according to the battery parameters, the performance of the battery under different working conditions can be more accurately identified. By analyzing the battery parameters of each charging and discharging period and calculating the maximum available capacity of the period, the actual performance of the power battery under different working conditions can be obtained. According to the maximum available capacity of the charging period and the discharging period, the period to be corrected is selected from the discharging period, and the maximum available capacity of these periods to be corrected is corrected through the correction model. The accuracy of the maximum available capacity calculation is improved, thereby improving the capacity error caused by external factors or aging of the power battery, so that the corrected capacity data more accurately reflects the actual state of the power battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic flow chart of a method for correcting power battery capacity based on mileage provided in an embodiment of the present invention;

[0017] Figure 2 Shown is a structural block diagram of a power battery capacity correction system based on mileage provided by an embodiment of the present invention;

[0018] Figure 3 Shown is a structural schematic diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0020] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0021] In the following description, numerous details are discussed to provide a more thorough explanation of the embodiments of the present invention. However, it is obvious to those skilled in the art that the embodiments of the present invention can be implemented without these specific details. In other embodiments, structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present invention difficult to understand.

[0022] The present invention provides a method for correcting the capacity of a power battery based on mileage, taking into account that the current battery capacity estimation method for electric vehicles mainly focuses on battery charging data, the use of discharge data is not sufficient, and the influence of mileage on the maximum available capacity is not considered. In view of the above problems, the present invention can more accurately identify the performance of the power battery under different working conditions by sampling the battery parameters and the corresponding mileage of the power battery, and dividing the sampling period into a charging period and a discharging period according to the battery parameters. By analyzing the battery parameters of each charging and discharging period and calculating the maximum available capacity of the period, the actual performance of the power battery under different working conditions can be obtained. According to the maximum available capacity of the charging period and the discharging period, the discharging period that deviates from the normal range is screened out, marked as the period to be corrected, and the maximum available capacity of these periods to be corrected is corrected by the correction model. Thereby, the capacity error caused by external factors or aging of the power battery is improved, so that the corrected capacity data more accurately reflects the actual state of the power battery. The present invention can effectively solve the problem of inaccurate charge calculation by the Coulomb counting method in practical applications and the possible large fluctuation of capacity between adjacent mileages, and make full use of the discharge data. Based on different needs, the maximum available capacity within any unit interval (such as year, month, day) or specific mileage (such as per kilometer) can be accurately obtained. Based on these maximum available capacities, users can better plan subsequent charging and discharging strategies according to the status of the power battery, thereby extending the service life of the power battery.

[0023] See also Figure 1 , the mileage-based power battery capacity correction method includes the following steps:

[0024] S1. Sampling the battery parameters of the power battery to be tested and the mileage of the corresponding electric vehicle, obtaining the battery parameters and mileage within a preset sampling period, and dividing the sampling period into multiple charging periods and multiple discharging periods according to the battery parameters.

[0025] The cloud server continuously monitors the state of the power battery to be tested through the battery management system (BMS) according to the preset sampling frequency, and obtains the mileage of the vehicle equipped with the power battery through relevant sensors (such as odometer sensors). Specifically, the battery management system continuously collects battery parameters such as voltage, state of charge (SOC), and charge of the power battery to be tested. During the preset sampling period, the cloud server obtains each battery parameter from the battery management system according to the preset sampling frequency. At the same time, the cloud server also obtains the mileage of the electrified vehicle from the sensor according to the same sampling frequency. It should be noted that the collected battery parameters and mileage are all timestamped with the corresponding sampling time, so as to determine the charging period and discharging period later. Specifically, according to the battery parameters collected during the sampling period, the charging period and the discharging period are identified, and each period represents a charging or discharging process. Among them, the charging period is a period of time when the power battery to be tested is receiving energy. During this period of time, the power battery to be tested is charged by an external power supply, and the state of charge of the power battery to be tested gradually increases. The discharge period is a time period during which the power battery to be tested releases energy for external purposes (such as driving an electrified vehicle or power supply equipment). During this time period, the state of charge of the power battery to be tested gradually decreases.

[0026] S2. Analyze each charging period and discharging period, and calculate the maximum available capacity of each period according to the battery parameters in each period.

[0027] According to the battery parameters at the start and end of each charging and discharging period, it is determined whether the battery energy is increasing or decreasing during the period, and combined with the change in the state of charge during the period, the maximum available capacity of the period is evaluated. The maximum available capacity refers to the maximum amount of electricity that the power battery can store or release in the current period.

[0028] Specifically, in an embodiment of the present invention, the calculating the maximum available capacity of each time period according to the battery parameters in the time period includes:

[0029] Calculating the charge change in the charging period / discharging period according to the charge amount of the battery parameter at the start time and the end time of the charging period / discharging period;

[0030] Calculating the change in the state of charge during the charging period / discharging period according to the state of charge of the battery parameter at the start time and the end time of the charging period / discharging period;

[0031] The ratio of the charge change to the state of charge change is used as the maximum available capacity of the charging period / discharging period.

[0032] For each charging period or discharging period (hereinafter referred to as "period"): determine the start and end time of the period according to the timestamp therein, and determine the charge change within the period according to the charge at the start and end times. The charge change is the difference in charge from the start time to the end time. It can be understood that for the charging period, the charge change is a positive value, and for the discharging period, the charge change is a negative value. Similarly, the charge state change within the period is determined according to the charge state at the start and end times of the period, wherein the charge state is the ratio of the current remaining power of the battery to the full charge. Using the ratio of the charge change to the charge state change, the maximum available capacity of the period is calculated according to formula (1):

[0033]

[0034] Among them, CAP i is the maximum available capacity in the i-th period, ΔQ i ΔSOC is the amount of charge charged or discharged in the i-th time period (in ampere-hours, Ah), which represents the change in charge during the time period. i is the difference between the state of charge of the power battery to be tested at the start and end of the i-th time period, indicating the change in the state of charge during the time period. The maximum available capacity corresponding to each charging and discharging time period is calculated in the above manner, so as to subsequently correct the maximum available capacity of the relevant discharging time period.

[0035] S3. Filter out the time period to be corrected from all the discharge time periods according to the maximum available capacities of all the charge time periods and the discharge time periods.

[0036] After calculating the maximum available capacity of all charging and discharging periods, analyze the maximum available capacity of each discharging period, and select the discharging periods that deviate from the reference range of the charging period. Since these discharging periods deviate from the reference range, it can be considered that there are abnormal conditions in these discharging periods, so these discharging periods are marked as periods to be corrected, which are used to correct the maximum available capacity of the period later.

[0037] Specifically, in one embodiment of the present invention, the step of selecting the time period to be corrected from all the discharge time periods according to all the maximum available capacities of the charge time period and the discharge time period includes:

[0038] Based on a preset division criterion, all maximum available capacities of the charging period are divided into multiple capacity intervals, and the number of charging periods in each capacity interval is counted, and the capacity interval with the largest number of charging periods is taken as a normal capacity interval;

[0039] The maximum available capacity of each discharge period is compared with the normal capacity interval, and all discharge periods that are not in the normal capacity interval are taken as periods to be corrected.

[0040] The maximum available capacity of all charging periods is counted, and based on the preset division criteria, the maximum available capacity of these charging periods is divided into multiple capacity intervals, wherein each capacity interval represents the data of the maximum available capacity within a certain range. For each capacity interval, the number of charging periods contained therein is counted. After all capacity intervals are counted, the capacity interval containing the largest number of charging periods is selected and used as the normal capacity interval. Since this interval contains the largest number of charging periods, it can be regarded as the normal capacity performance of the power battery in the current healthy state. For each discharge period, the corresponding maximum available capacity is compared with the normal capacity interval, and the discharge period that is not in the normal capacity interval is identified and screened out. Among them, the discharge period that is not in the normal capacity interval refers to the discharge period in which the maximum available capacity of the discharge period is less than or greater than the normal capacity interval, and these discharge periods are marked as periods to be corrected. Exemplarily, the normal capacity interval is [130,155], indicating that the current power battery is in a healthy state, and its maximum available capacity usually falls within the range of 130 to 155. If the maximum available capacity of the first discharge period is 120, the maximum available capacity of the second discharge period is 140, and the maximum available capacity of the third discharge period is 110, the first and third discharge periods are marked as periods to be corrected. In the present invention, considering that the charging process is usually carried out under relatively stable conditions compared to the discharge period and is less affected by external factors, the discharge period to be corrected is determined according to the maximum available capacity of the charging period, so that abnormal conditions during the discharge period can be more accurately identified.

[0041] In one embodiment of the present invention, the method of dividing all maximum available capacities of the charging period into multiple capacity intervals based on a preset division criterion, counting the number of charging periods in each capacity interval, and taking the capacity interval with the largest number of charging periods as the normal capacity interval includes:

[0042] Arrange all the maximum available capacities during the charging period in order to form a maximum available capacity sequence;

[0043] Dividing the maximum available capacity sequence into a plurality of capacity intervals based on a preset capacity interval;

[0044] The number of charging periods included in each capacity interval is counted, and the capacity interval with the largest number of charging periods is selected as the normal capacity interval.

[0045] In this embodiment, the division criterion is to arrange the maximum available capacity of the charging time period in ascending order and divide it into multiple capacity intervals. Specifically, the maximum available capacity of all charging time periods is counted, and arranged in ascending order to form a maximum available capacity sequence. It can be understood that in this maximum available capacity sequence, each maximum available capacity may correspond to one charging time period or multiple charging time periods, and the charging time period and the corresponding maximum available capacity are associated through a capacity identifier. According to the preset capacity interval, the maximum available capacity sequence is divided into multiple capacity intervals. For each divided capacity interval, the number of charging time periods contained in the capacity interval is counted. After all capacity intervals are counted, the interval containing the largest number of charging time periods is selected as the normal capacity interval.

[0046] For example, the maximum available capacity calculated from all charging periods is divided into 20Ah intervals. If the maximum available capacity in all charging periods is 300Ah and the minimum is 100Ah, then all charging periods will be divided into (300-100) / 20=10 intervals. After the division, if the number of charging periods in the interval [130, 155) is the largest, then the interval [130, 155) is defined as the normal capacity interval.

[0047] S4. According to the driving mileage and battery parameters, the maximum available capacity of each time period to be corrected is corrected based on the correction model.

[0048] Through the mileage and battery parameters, the correction model is used to adjust the maximum available capacity of each time period to be corrected to correct the capacity estimation error caused by the aging of the power battery or the change of the external environment, so as to improve the accuracy of the power battery performance evaluation. It can be understood that the correction model can be a regression model of any machine learning or deep learning algorithm, which is not limited here. Exemplarily, the correction model includes but is not limited to the support vector machine (Support Vector Machines, SVM) model, random forest (Random Forest, RF) model, deep neural network (Deep Neural Network, DNN), extreme gradient correction (eXtreme Gradient Boosting, XGBoost) model, etc. Further, in order to improve the processing rate and prediction accuracy, in one embodiment of the present invention, the correction model is an extreme gradient correction model.

[0049] Specifically, in one embodiment of the present invention, for each time period to be corrected, the maximum available capacity of the time period to be corrected is corrected based on the correction model according to the mileage and the battery parameters, including:

[0050] determining a battery state parameter according to the driving mileage and the battery parameter;

[0051] Inputting the battery state parameter into the correction model to obtain the charge change per unit mileage;

[0052] Based on the charge change per unit mileage and the charge state change per unit mileage of the battery state parameter, the maximum available capacity of the time period to be corrected is corrected.

[0053] For each period to be corrected, the battery status parameters of the period are calculated based on the collected mileage and battery parameters such as voltage, power, and state of charge. The battery status parameters are used to reflect the working status and health status of the power battery in the period. The battery status parameters of each period to be corrected are input into the pre-trained correction model to predict the charge change per unit mileage in the period (ΔQ d_j / Δm j ) est , where ΔQ d_j is the charge change in the jth period to be corrected, Δm j is the mileage of the jth period to be corrected. According to the correction model output (ΔQ d_j / Δm j ) est , and the above-calculated change in the state of charge per unit mileage, the maximum available capacity of the time period to be corrected is corrected according to formula (2):

[0054]

[0055] Among them, (CAPd _j ) est is the maximum available capacity after correction in the jth period to be corrected, ΔSOC d_j is the charge state change in the jth period to be corrected. In this way, the capacity estimation error caused by power battery aging, external environment changes or other factors can be corrected.

[0056] Specifically, in an embodiment of the present invention, determining the battery status parameter according to the driving mileage and the battery parameter includes:

[0057] Calculating the change in the state of charge of the time period to be corrected according to the state of charge of the battery parameter at the start time and the end time of the time period to be corrected;

[0058] Calculating the charge change in the time period to be corrected according to the charge amount of the battery parameter at the start time and the end time of the time period to be corrected;

[0059] Calculating the voltage variation of the time period to be corrected according to the voltage of the battery parameter at the start time and the end time of the time period to be corrected;

[0060] Taking the ratio of the state of charge change to the mileage as the state of charge change per unit mileage;

[0061] Taking the ratio of the voltage change to the state of charge change as the voltage change per unit state of charge;

[0062] The ratio of the voltage change to the charge change is taken as the voltage change per unit charge.

[0063] For the jth time period to be corrected: based on the charge at the start and end of the time period to be corrected, calculate the difference between the two to obtain the charge change ΔQ in the jth time period d j, the charge change is used to characterize the energy transfer of the power battery in the jth period to be corrected, so as to analyze the actual discharge performance of the power battery. Similarly, based on the state of charge at the start and end of the period, the difference between the two is calculated to obtain the charge state change ΔSOC in the jth period. d_j The charge state change is used as one of the battery state parameters to characterize the power consumption of the power battery in the jth period to be corrected. Based on the voltage at the start and end of the period to be corrected, the difference between the two is calculated to obtain the voltage change ΔV in the period j The voltage change is used to indicate the change of battery voltage during this period. Calculate the charge state change and the mileage Δm during this period j The ratio of the charge state per unit mileage is obtained. The change in state of charge per unit mileage can reflect the energy consumption efficiency of the battery during the operation of the electric vehicle. The ratio of the voltage change to the state of charge change is calculated to obtain the voltage change per unit state of charge. The voltage change per unit state of charge indicates the voltage change caused by the change in the battery's state of charge per unit. The voltage change per unit charge is obtained by calculating the ratio of the voltage change to the charge change. It can reflect the sensitivity of the voltage response of the power battery during discharge.

[0064] ΔSOC d_j , ΔSOC d_j / Δm j , ΔV j / ΔSOC d_j and ΔV j / ΔQ d_j As the battery state parameter, it is input into the pre-trained correction model, and the model outputs the (ΔQ d_j / Δm j ) est , use formula (2) to correct the maximum available capacity of this period.

[0065] It should be noted that the training data in the present invention can be collected by itself or obtained through public data sources. In one example, the training data in the present invention comes from the National Big Data Alliance of New Energy Vehicles (NDANEV), which provides the operation data of 200 electric buses from January 2019 to December 2019. These vehicles include 2 different models, each model contains 100 vehicles. Under this data, there are 12 capacity intervals. In the training phase, the training set is the discharge period in the normal capacity interval, and in the test phase, the test set is all the discharge periods to be corrected.

[0066] See also Figure 2 , the mileage-based power battery capacity correction system 100 includes: a data acquisition module 110, a maximum available capacity determination module 120, a time period to be corrected screening module 130 and a correction module 140. Among them, the above-mentioned data acquisition module 110 is used to sample the battery parameters of the power battery to be tested and the mileage of the corresponding electrified vehicle, obtain the battery parameters and mileage within a preset sampling period, and divide the sampling period into multiple charging periods and multiple discharging periods according to the battery parameters. The maximum available capacity determination module 120 is used to analyze each charging period and discharging period, and calculate the maximum available capacity of the period according to the battery parameters in each period. The time period to be corrected screening module 130 is used to filter out the time period to be corrected from all the discharge periods according to all the maximum available capacities of the charging period and the discharging period. The correction module 140 is used to correct the maximum available capacity of each time period to be corrected based on the correction model according to the mileage and battery parameters.

[0067] For the specific definition of the mileage-based power battery capacity correction system, please refer to the definition of the mileage-based power battery capacity correction method above, which will not be repeated here. Each module in the above-mentioned mileage-based power battery capacity correction system can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in hardware format, or can be stored in the memory of the computer device in software format, so that the processor can call the corresponding operations of each of the above modules.

[0068] It should be noted that, in order to highlight the innovative part of the present invention, the present embodiment does not introduce modules that are not closely related to solving the technical problem proposed by the present invention, but this does not mean that there are no other modules in the present embodiment.

[0069] See also Figure 3The electronic device 1 may include a memory 12, a processor 13 and a bus, and may also include a computer program stored in the memory 12 and executable on the processor 13, such as a power battery capacity correction program based on mileage.

[0070] Among them, the memory 12 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (for example: SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 12 can be an internal storage unit of the electronic device 1, such as a mobile hard disk of the electronic device 1. In other embodiments, the memory 12 can also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device 1. Further, the memory 12 can also include both an internal storage unit of the electronic device 1 and an external storage device. The memory 12 can not only be used to store application software and various types of data installed in the electronic device 1, such as codes for power battery capacity correction based on mileage, etc., but can also be used to temporarily store data that has been output or is to be output.

[0071] In some embodiments, the processor 13 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and a combination of various control chips. The processor 13 is the control core (Control Unit) of the electronic device 1, and uses various interfaces and lines to connect the various components of the entire electronic device 1, and executes or executes the programs or modules stored in the memory 12 (such as the power battery capacity correction program based on mileage, etc.), and calls the data stored in the memory 12 to execute various functions of the electronic device 1 and process data.

[0072] The processor 13 executes the operating system and various installed application programs of the electronic device 1. The processor 13 executes the application programs to implement the steps in the above-mentioned mileage-based power battery capacity correction method.

[0073] Exemplarily, the computer program may be divided into one or more modules, which are stored in the memory 12 and executed by the processor 13 to complete the present application. The one or more modules may be a series of computer program instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer program in the electronic device 1. For example, the computer program may be divided into a data acquisition module 110, a maximum available capacity determination module 120, a to-be-corrected time period screening module 130, and a correction module 140.

[0074] The above-mentioned integrated unit implemented in the form of a software function module can be stored in a computer-readable storage medium, and the computer-readable storage medium can be non-volatile or volatile. The above-mentioned software function module is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, a computer device, or a network device, etc.) or a processor to perform part of the functions of the mileage-based power battery capacity correction method described in each embodiment of the present application.

[0075] In summary, the present invention discloses a method, system, device and medium for correcting the capacity of a power battery based on mileage. By sampling the battery parameters and the corresponding mileage of the power battery, and dividing the sampling period into a charging period and a discharging period according to the battery parameters, the performance of the battery under different working conditions can be more accurately identified. By analyzing the battery parameters of each charging and discharging period and calculating the maximum available capacity of the period, the actual performance of the power battery under different working conditions can be obtained. According to the maximum available capacity of the charging period and the discharging period, the discharging period that deviates from the normal range is screened out, marked as the period to be corrected, and the maximum available capacity of these periods to be corrected is corrected by the correction model. Thereby, the capacity error caused by external factors or aging of the power battery is improved, so that the corrected capacity data more accurately reflects the actual state of the power battery. Through the present invention, the inaccurate calculation of charge by the Coulomb counting method in practical applications and the possible large fluctuation of adjacent mileage capacity can be effectively improved, resulting in the problem of low accuracy of the maximum available capacity finally obtained. And by making full use of the discharge data, based on different needs, the maximum available capacity within any unit interval (such as year, month, day) or specific mileage (such as per kilometer) can be accurately obtained, so that users can achieve better battery management based on their own needs. Therefore, the present invention effectively overcomes various shortcomings in the prior art and has high industrial utilization value.

[0076] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by a person of ordinary skill in the art without departing from the spirit and technical concept disclosed by the present invention shall still be covered by the claims of the present invention.

Claims

1. A method for correcting power battery capacity based on mileage, characterized in that: Applied to an electric vehicle, the method comprises: Sampling the battery parameters of the power battery to be tested and the mileage of the corresponding electrified vehicle, obtaining the battery parameters and mileage within a preset sampling period, and dividing the sampling period into a plurality of charging periods and a plurality of discharging periods according to the battery parameters; Analyze each charging period and discharging period, and calculate the maximum available capacity of each period according to the battery parameters in each period; According to all the maximum available capacities of the charging period and the discharging period, the period to be corrected is selected from all the discharging periods; According to the driving mileage and battery parameters, the maximum available capacity of each time period to be corrected is corrected based on the correction model; According to the mileage and battery parameters, the maximum available capacity of the correction period is corrected based on the correction model, including: determining a battery state parameter according to the driving mileage and the battery parameter; Inputting the battery state parameter into the correction model to obtain the charge change per unit mileage; Based on the charge change per unit mileage and the charge state change per unit mileage of the battery state parameter, correcting the maximum available capacity of the time period to be corrected; Determining a battery state parameter according to the driving mileage and the battery parameter includes: Calculating the change in the state of charge of the time period to be corrected according to the state of charge of the battery parameter at the start time and the end time of the time period to be corrected; Calculating the charge change in the time period to be corrected according to the charge amount of the battery parameter at the start time and the end time of the time period to be corrected; Calculating the voltage variation of the time period to be corrected according to the voltage of the battery parameter at the start time and the end time of the time period to be corrected; Taking the ratio of the state of charge change to the mileage as the state of charge change per unit mileage; Taking the ratio of the voltage change to the state of charge change as the voltage change per unit state of charge; The ratio of the voltage change to the charge change is taken as the voltage change per unit charge.

2. The method for correcting the power battery capacity based on mileage according to claim 1, characterized in that: The calculating the maximum available capacity of each time period according to the battery parameters in the time period includes: Calculating the charge change in the charging period / discharging period according to the charge amount of the battery parameter at the start time and the end time of the charging period / discharging period; Calculating the change in the state of charge during the charging period / discharging period according to the state of charge of the battery parameter at the start time and the end time of the charging period / discharging period; The ratio of the charge change to the state of charge change is used as the maximum available capacity of the charging period / discharging period.

3. The method for correcting the power battery capacity based on mileage according to claim 1, characterized in that: The method of selecting the time period to be corrected from all the discharge time periods according to all the maximum available capacities of the charge time period and the discharge time period includes: Based on a preset division criterion, all maximum available capacities of the charging period are divided into multiple capacity intervals, and the number of charging periods in each capacity interval is counted, and the capacity interval with the largest number of charging periods is taken as a normal capacity interval; The maximum available capacity of each discharge period is compared with the normal capacity interval, and all discharge periods that are not in the normal capacity interval are taken as periods to be corrected.

4. The method for correcting the power battery capacity based on mileage according to claim 3, characterized in that: The method of dividing all the maximum available capacities of the charging period into a plurality of capacity intervals based on a preset division criterion, counting the number of charging periods in each capacity interval, and taking the capacity interval with the largest number of charging periods as a normal capacity interval includes: Arrange all the maximum available capacities during the charging period in order to form a maximum available capacity sequence; Dividing the maximum available capacity sequence into a plurality of capacity intervals based on a preset capacity interval; The number of charging periods included in each capacity interval is counted, and the capacity interval with the largest number of charging periods is selected as the normal capacity interval.

5. The method for correcting power battery capacity based on mileage according to claim 1, characterized in that: The correction model is an extreme gradient correction model.

6. A power battery capacity correction system based on mileage, characterized in that: The system comprises: A data acquisition module, used to sample the battery parameters of the power battery to be tested and the mileage of the corresponding electric vehicle, obtain the battery parameters and mileage within a preset sampling period, and divide the sampling period into multiple charging periods and multiple discharging periods according to the battery parameters; A maximum available capacity determination module is used to analyze each charging period and discharging period and calculate the maximum available capacity of each period according to the battery parameters in each period; A to-be-corrected time period screening module is used to screen out the to-be-corrected time period from all the discharge time periods according to all the maximum available capacities of the charge time period and the discharge time period; A correction module, used for correcting the maximum available capacity of each time period to be corrected based on the correction model according to the driving mileage and battery parameters; According to the mileage and battery parameters, the maximum available capacity of the correction period is corrected based on the correction model, including: determining a battery state parameter according to the driving mileage and the battery parameter; Inputting the battery state parameter into the correction model to obtain the charge change per unit mileage; Based on the charge change per unit mileage and the charge state change per unit mileage of the battery state parameter, correcting the maximum available capacity of the time period to be corrected; Determining a battery state parameter according to the driving mileage and the battery parameter includes: Calculating the change in the state of charge of the time period to be corrected according to the state of charge of the battery parameter at the start time and the end time of the time period to be corrected; Calculating the charge change in the time period to be corrected according to the charge amount of the battery parameter at the start time and the end time of the time period to be corrected; Calculating the voltage variation of the time period to be corrected according to the voltage of the battery parameter at the start time and the end time of the time period to be corrected; Taking the ratio of the state of charge change to the mileage as the state of charge change per unit mileage; Taking the ratio of the voltage change to the state of charge change as the voltage change per unit state of charge; The ratio of the voltage change to the charge change is taken as the voltage change per unit charge.

7. An electronic device, characterized in that: The electronic device comprises: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the electronic device to implement the mileage-based power battery capacity correction method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor of a computer, the computer is caused to execute the mileage-based power battery capacity correction method as described in any one of claims 1 to 5.

Images