Method, system, terminal and medium for calculating battery capacity based on charging data

Abstract

The present invention provides a method, system, terminal and medium for calculating battery capacity based on charging data, by first collecting battery data for each charge and cleaning it to remove invalid information; then extracting charging process data that meets the effective charging cycle from the cleaned data, and calculating the single capacity of each charge accordingly; then, using these single capacity values ​​to calculate the corresponding equivalent SOH, and then using the sliding window technology to traverse the equivalent SOH arranged in time order to obtain the normal equivalent SOH in each window; finally, based on the sliding window data that meets the sample quantity requirements, the SOH of the target battery at different time points is calculated. Compared with the existing solutions, the present invention is not only simple to operate, but also suitable for various complex scenarios in battery swap stations, and can accurately and effectively obtain the SOH results of the battery.

Description

Technical Field

[0001] The present invention relates to the field of battery health technology, and in particular to a method, system, terminal and medium for calculating battery capacity based on charging data. Background Art

[0002] Battery state of health (SOH) is a core indicator for measuring battery performance and life expectancy. Obtaining the true SOH (State of Health) of the battery is crucial to ensuring the safe, reliable and efficient operation of the battery system and optimizing the operating income of the battery swap station. First of all, the SOH of the battery directly affects its safety. Batteries in poor health may cause safety hazards such as overheating, expansion or even explosion. Accurate understanding of SOH can effectively prevent these risks. Secondly, SOH reflects the remaining capacity and charging and discharging efficiency of the battery, which is the key basis for optimizing battery usage, extending service life and improving equipment performance. Furthermore, by monitoring SOH, signs of battery aging or failure can be discovered in time, preventive maintenance can be performed, sudden failures can be reduced, and maintenance costs can be reduced. In applications such as electric vehicles and energy storage systems, batteries are core components, and their SOH is directly related to the reliability and stability of the system. Accurate evaluation of SOH helps avoid system downtime or performance degradation. In addition, SOH can also help predict the remaining service life of the battery, guide users to replace the battery in time, and prevent performance degradation from affecting system operation. For battery operators and managers, SOH data is an important reference for formulating operating strategies, optimizing management plans, and making investment decisions. In particular, in the operation of battery swap stations, SOH results directly affect the revenue, so accurate evaluation of SOH is of great significance to improving the economic benefits of battery swap stations.

[0003] The assessment of battery health usually relies on sophisticated algorithmic models. These SOH algorithmic models are of various types, ranging from precise modeling based on physical principles to machine learning methods driven by big data. Among them, the empirical model is a common method, which estimates the SOH through formulas or statistical means based on the actual use records and historical experience of the battery. The advantage of such models is that they are simple, intuitive and easy to implement. However, their accuracy is highly dependent on the quality of data and the applicability of historical experience. Therefore, when faced with complex and changing scenarios in battery swap stations, their promotion and application are subject to certain restrictions. In addition to empirical models, electrochemical models are also an important means of evaluating SOH. It is based on the principle of electrochemical reaction or equivalent circuit theory and can simulate the dynamic behavior of batteries more deeply. Although electrochemical models have advantages at the theoretical level, their calculation process is relatively complex and requires detailed battery parameter support, which increases the complexity and implementation difficulty of the model. In recent years, machine learning models have attracted much attention due to their powerful data processing capabilities. By training labeled data, machine learning models can handle complex nonlinear relationships and show extremely high adaptability. However, this method also faces challenges, namely, it requires a large amount of high-quality labeled data and the model's interpretability is relatively poor.

[0004] In a battery swap station environment, the battery charging conditions are particularly complex, including differences in charging temperature, charging battery type and charging strategy, coupled with a low frequency of data collection (usually 30 seconds). These factors pose more severe challenges to accurately estimating battery capacity. Summary of the invention

[0005] In view of the shortcomings of the prior art mentioned above, the purpose of the present invention is to provide a method, system, terminal and medium for calculating battery capacity based on charging data, so as to solve the technical problem that various algorithms in the prior art are used to evaluate battery health, which have the shortcomings of limited accuracy, high model complexity, requirement of a large amount of high-quality data and poor interpretability, and under the complex charging conditions of battery swap stations, the low frequency of data collection further aggravates the challenge of accurately estimating battery capacity.

[0006] To achieve the above-mentioned purpose and other related purposes, the present invention provides a method for calculating battery capacity based on charging data, the method comprising: obtaining battery charging data of each charging of a target battery in a battery swap station within a preset time period; wherein the battery charging data comprises: charging process data and the rated capacity of the battery; performing data cleaning on each battery charging data to eliminate invalid data; extracting charging process data that meets the effective charging cycle based on the charging data of each battery of the target battery; and calculating the corresponding single charging capacity according to each charging process data that meets the effective charging cycle;

[0007] Based on each single charge capacity, the corresponding equivalent SOH is calculated; the equivalent SOHs arranged in chronological order are traversed through the sliding window to obtain the normal equivalent SOH of each sliding window; based on the normal equivalent SOH of the sliding window that meets the sample number requirement, the SOH of the target battery at different time points and the current SOH are calculated.

[0008] In an embodiment of the present invention, the charging process data includes: current and SOC that vary with time during the charging process.

[0009] In one embodiment of the present invention, the extracting charging process data that meets the effective charging cycle based on the charging data of each battery of the target battery includes: determining whether the SOC in the charging data of each battery of the target battery meets the effective charging cycle conditions, and extracting the charging process data that meets the effective charging cycle conditions as the charging process data that meets the effective charging cycle; wherein the effective charging cycle conditions include: the ending SOC is 100%, and the starting SOC is not greater than a set threshold.

[0010] In one embodiment of the present invention, the calculating of the corresponding single charging capacity according to each charging process data conforming to the effective charging cycle includes: calculating the ampere-hour integral of the current that changes with time in each charging process data conforming to the effective charging cycle, and obtaining the single charging capacity corresponding to each charging process data.

[0011] In one embodiment of the present invention, the calculation of the corresponding equivalent SOH based on each single charging capacity includes: calculating the equivalent capacity according to each single charging capacity and the starting SOC and ending SOC in the corresponding charging process data; calculating the corresponding equivalent SOH according to each equivalent capacity and the rated capacity of the corresponding battery.

[0012] In one embodiment of the present invention, traversing the equivalent SOH arranged in chronological order through a sliding window to obtain a normal equivalent SOH for each sliding window includes: traversing the equivalent SOH arranged in chronological order through a sliding window to obtain each equivalent SOH for each sliding window; wherein the size of the sliding window is set to a set time period length; and using the 2σ rule to select the normal equivalent SOH for each sliding window.

[0013] In one embodiment of the present invention, the calculation of the SOH of the target battery at different time points based on the normal equivalent SOH of the sliding window that meets the sample number requirement includes: screening a sliding window of normal equivalent SOH including at least a set threshold number as a target sliding window, and obtaining the normal equivalent SOH of each target sliding window; calculating the average of the normal equivalent SOH of each target sliding window to obtain the SOH at the corresponding time point of each target sliding window.

[0014] To achieve the above-mentioned purpose and other related purposes, the present invention provides a system for calculating battery capacity based on charging data, the system comprising: a data acquisition module, used to obtain battery charging data of each charging of a target battery in a battery swap station within a preset time period; wherein the battery charging data comprises: charging process data and the rated capacity of the battery; a data cleaning module, connected to the data acquisition module, used to clean the charging data of each battery to eliminate invalid data; an effective data extraction module, connected to the data cleaning module, used to extract charging process data that meets the effective charging cycle based on the charging data of each battery of the target battery; a single charging capacity calculation module, connected to the data cleaning module, used to extract charging process data that meets the effective charging cycle; a single charging capacity calculation module, connected to the data acquisition module, used to clean the charging data of each battery to eliminate invalid data; a single charging capacity calculation module, connected to the data cleaning module, used to extract charging process data that meets the effective charging cycle based on the charging data of each battery of the target battery; a single charging capacity calculation module, connected to the data acquisition module, used to clean the charging data of each battery to eliminate invalid data; a single charging capacity calculation module, connected to the data acquisition module, used to clean the charging data of each battery to eliminate invalid data; a single charging capacity calculation module, connected to the data cleaning module, used to extract charging process data that meets the effective charging cycle; a single charging capacity calculation module, connected to the data acquisition module, used to clean the charging data of each battery to eliminate invalid data ... The effective data extraction module is connected to the effective data extraction module, and is used to calculate the corresponding single charging capacity according to each charging process data that meets the effective charging cycle; the equivalent SOH calculation module is connected to the single charging capacity calculation module, and is used to calculate the corresponding equivalent SOH based on each single charging capacity; the data traversal module is connected to the equivalent SOH calculation module, and is used to traverse the equivalent SOH arranged in time order through a sliding window to obtain the normal equivalent SOH of each sliding window; the SOH calculation module is connected to the traversal module, and is used to calculate the SOH of the target battery at different time points and the current SOH based on the normal equivalent SOH of the sliding window that meets the sample number requirement.

[0015] To achieve the above-mentioned purpose and other related purposes, the present invention provides an electronic terminal, comprising: one or more memories and one or more processors; the one or more memories are used to store computer programs; the one or more processors are connected to the memories and are used to run the computer program to execute the method for calculating the battery capacity based on charging data.

[0016] To achieve the above-mentioned purpose and other related purposes, the present invention provides a computer storage medium storing a computer program, which implements the method for calculating battery capacity based on charging data when the computer program is executed.

[0017] As described above, the present invention is a method, system, terminal and medium for calculating battery capacity based on charging data, which has the following beneficial effects: the present invention first collects battery data for each charge and cleans it to remove invalid information; then extracts charging process data that conforms to the effective charging cycle from the cleaned data, and calculates the single capacity of each charge accordingly; then, uses these single capacity values ​​to calculate the corresponding equivalent SOH, and then uses the sliding window technology to traverse the equivalent SOH arranged in time order to obtain the normal equivalent SOH in each window; finally, based on the sliding window data that meets the sample quantity requirements, the SOH of the target battery at different time points is calculated. Compared with the existing solutions, the present invention is not only simple to operate, but also suitable for various complex scenarios in battery swap stations, and can accurately and effectively obtain the SOH results of the battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flow chart of a method for calculating battery capacity based on charging data in one embodiment of the present invention.

[0019] Figure 2 Shown is a schematic diagram of the structure of a system for calculating battery capacity based on charging data in one embodiment of the present invention.

[0020] Figure 3 Shown is a schematic structural diagram of an electronic terminal in an embodiment of the present invention. DETAILED DESCRIPTION

[0021] 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.

[0022] It should be noted that in the following description, reference is made to the accompanying drawings, which describe several embodiments of the present invention. It should be understood that other embodiments may also be used, and that mechanical composition, structural, electrical and operational changes may be made without departing from the spirit and scope of the present invention. The following detailed description should not be considered restrictive, and the scope of the embodiments of the present invention is limited only by the claims of the published patents. The terms used herein are only for describing specific embodiments and are not intended to limit the present invention. Spatially related terms, such as "upper", "lower", "left", "right", "below", "below", "lower", "above", "upper", etc., may be used in the text to facilitate the description of the relationship between an element or feature shown in the figure and another element or feature.

[0023] Throughout the specification, when a part is said to be "connected" to another part, this includes not only the case of "direct connection" but also the case of "indirect connection" by placing other elements therebetween. In addition, when a part is said to "include" a certain constituent element, unless otherwise stated, it does not exclude other constituent elements, but means that other constituent elements may be included.

[0024] The terms first, second and third mentioned herein are used to describe various parts, components, regions, layers and / or segments, but are not limited thereto. These terms are only used to distinguish a certain part, component, region, layer or segment from other parts, components, regions, layers or segments. Therefore, the first part, component, region, layer or segment described below may refer to the second part, component, region, layer or segment within the scope of the present invention.

[0025] Furthermore, as used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless there is an indication to the contrary in the context. It should be further understood that the terms "comprise", "include" indicate the presence of the described features, operations, elements, components, items, kinds, and / or groups, but do not exclude the presence, occurrence or addition of one or more other features, operations, elements, components, items, kinds, and / or groups. The terms "or" and "and / or" used herein are interpreted as inclusive, or mean any one or any combination. Therefore, "A, B or C" or "A, B and / or C" means "any of the following: A; B; C; A and B; A and C; B and C; A, B and C". Exceptions to this definition will only occur when the combination of elements, functions or operations is inherently mutually exclusive in some way.

[0026] The present invention provides a method for calculating battery capacity based on charging data, by first collecting battery data for each charge and cleaning it to remove invalid information; then extracting charging process data that meets the effective charging cycle from the cleaned data, and calculating the single capacity of each charge accordingly; then, using these single capacity values ​​to calculate the corresponding equivalent SOH, and then using the sliding window technology to traverse the equivalent SOH arranged in time order to obtain the normal equivalent SOH in each window; finally, based on the sliding window data that meets the sample quantity requirements, the SOH of the target battery at different time points is calculated. Compared with the existing solutions, the present invention is not only simple to operate, but also suitable for various complex scenarios in battery swap stations, and can accurately and effectively obtain the SOH results of the battery.

[0027] The following is a detailed description of the embodiments of the present invention with reference to the accompanying drawings so that those skilled in the art can easily implement the present invention. The present invention can be embodied in many different forms and is not limited to the embodiments described herein.

[0028] like Figure 1 A flow chart showing a method for calculating battery capacity based on charging data in an embodiment of the present invention.

[0029] The method comprises:

[0030] Step S1: Obtain battery charging data of each charge of a target battery in a battery swap station within a preset time period.

[0031] In detail, the battery charging data of each charge of the target battery in the battery swap station within a preset time period is obtained. Among them, the target battery may refer to one or more specific batteries in the battery swap station that need to be evaluated for health status, and the preset time period is a specific time range set according to demand, such as the past year. The battery charging data includes: charging process data and the rated capacity of the battery. The collected battery charging data contains two types of information: one is the charging process data, which records the charging behavior of the battery in detail; the other is the rated capacity of the battery, that is, the maximum capacity calibrated by the battery when it leaves the factory, which is an important benchmark for evaluating the health status of the battery.

[0032] In one embodiment, the charging process data includes:

[0033] The current that changes over time during the charging process can reflect the charging rate and charging behavior characteristics of the battery; the current data records how the current value fluctuates over time from the beginning to the end of a single charge. This data is critical to understanding the battery's charging efficiency, thermal effects, and potential signs of aging. For example, if the current value fluctuates abnormally during charging, it may mean that there are problems such as increased resistance or capacity attenuation inside the battery.

[0034] SOC (State of Charge): reflects the percentage of the battery's current stored power to its total capacity, and is a key parameter in the battery management system. SOC data provides an intuitive representation of the battery's power changes during the charging process. By monitoring the changes in SOC, we can understand the battery's charging efficiency and remaining capacity at different charging stages. This is important for evaluating the battery's health status, predicting its remaining service life, and optimizing charging strategies. The SOC includes the starting SOC and the ending SOC.

[0035] Step S2: Clean the charging data of each battery to remove invalid data.

[0036] Specifically, each battery charging data is checked for abnormal data, such as null values ​​or missing values, and the abnormal data is removed.

[0037] Step S3: extracting charging process data that meets the effective charging cycle based on the charging data of each battery of the target battery.

[0038] In one embodiment, step S3 includes:

[0039] Determine whether the SOC in the charging data of each battery of the target battery meets the effective charging cycle conditions, and extract the charging process data that meets the effective charging cycle conditions as the charging process data that meets the effective charging cycle;

[0040] Wherein, the effective charging cycle conditions include:

[0041] The end SOC is 100%, and the start SOC is not greater than a set threshold. Preferably, the set threshold is within 20-25%.

[0042] The effective charging cycle condition setting is mainly based on the following purposes: first, the SOC in the fully charged state (i.e. 100%) is considered to be completely reliable because it represents the maximum capacity of the battery; second, when the SOC is lower than 25%, the battery has released most of the power, and charging at this time can more effectively evaluate the battery's charging capacity and health status; finally, setting this threshold can also ensure that we have enough data points for accurate analysis and calculation.

[0043] Step S4: Calculate the corresponding single charging capacity according to each charging process data that meets the effective charging cycle.

[0044] In one embodiment, step S4 includes: calculating the ampere-hour integral of the current that changes with time in each charging process data that meets the effective charging cycle, and obtaining the single charging capacity corresponding to each charging process data.

[0045] The calculation formula for ampere-hour integral is:

[0046] ; (1)

[0047] Where Q is the single charge capacity, and Respectively represent the start time and end time of the charging process, I ( t ) means at time t The current value.

[0048] Step S5: Calculate the corresponding equivalent SOH based on each single charge capacity.

[0049] In one embodiment, step S5 includes:

[0050] Calculate the equivalent capacity based on each single charge capacity and the starting SOC and ending SOC in the corresponding charging process data;

[0051] Specifically, first calculate ΔSOC = End SOC - Start SOC from the start SOC and end SOC. Since ΔSOC is in percentage form, we need to convert it to decimal form for calculation. Then calculate the equivalent capacity based on ΔSOC and single charge capacity: Equivalent capacity = single charge capacity / equivalent ΔSOC (converted to decimal).

[0052] The corresponding equivalent SOH is calculated according to each equivalent capacity and the rated capacity of the corresponding battery.

[0053] Specifically, equivalent SOH is the ratio of equivalent capacity to rated capacity, which indicates the percentage of the actual capacity of the battery relative to its rated capacity. That is, equivalent SOH = equivalent capacity / rated capacity × 100%.

[0054] Through the above steps, we can use the single charge capacity, starting SOC and ending SOC to calculate the equivalent capacity and equivalent SOH, so as to more accurately evaluate the health status of the battery. This is of great significance for battery maintenance, management and replacement decisions.

[0055] Step S6: traverse the equivalent SOHs arranged in time order through the sliding window to obtain the normal equivalent SOH of each sliding window.

[0056] In one embodiment, step S6 includes:

[0057] By traversing the equivalent SOHs arranged in time order through a sliding window, each equivalent SOH of each sliding window is obtained; wherein the size of the sliding window is set to a set time period length; the time point corresponding to each sliding window is the time corresponding to the last equivalent SOH traversed by the window;

[0058] Specifically, determine the size of the sliding window, that is, set the length of the time period. This length can be set according to actual needs, such as one day, one week, or one month. Starting from the starting point of the time series, create a sliding window with a size equal to the length of the set time period. Traverse the equivalent SOH data in chronological order, moving the sliding window one data point at a time until the entire time series is traversed. For each sliding window, record the values ​​of all equivalent SOHs in the window and calculate the time point corresponding to the window (that is, the time corresponding to the last equivalent SOH traversed by the window).

[0059] Using the 2σ rule, the normal equivalent SOH of each sliding window is picked.

[0060] Specifically, for the equivalent SOH data in each sliding window, calculate its mean (μ) and standard deviation (σ). According to the 2σ rule, the range of the mean plus or minus two times the standard deviation is considered the normal range, that is, [μ - 2σ, μ + 2σ]. The equivalent SOH in each sliding window that falls within this range is selected as the normal equivalent SOH.

[0061] Step S7: Based on the normal equivalent SOH of the sliding window that meets the sample number requirement, calculate and obtain the SOH of the target battery at different time points and the current SOH.

[0062] In one embodiment, step S7:

[0063] Screening a sliding window including at least a set threshold number of normal equivalent SOHs as a target sliding window, and obtaining a normal equivalent SOH of each target sliding window;

[0064] Specifically, a threshold is determined, which represents the minimum number of normal equivalent SOHs that must be included in each target sliding window.

[0065] Those sliding windows that contain at least a set threshold number of normal equivalent SOHs are selected as target sliding windows.

[0066] The normal equivalent SOH of each target sliding window is averaged to obtain the SOH of each target sliding window at the corresponding time point.

[0067] Specifically, the average of the normal equivalent SOH values ​​in each target sliding window is calculated, and this average represents the SOH at the corresponding time point of the window.

[0068] For example, suppose we have equivalent SOH data of a time series, the sliding window size is one month (that is, each window contains equivalent SOH data within one month), and the threshold is set to 3. If the number of normal equivalent SOHs in a window is greater than or equal to 3, the window is regarded as the target sliding window. The mean of all normal equivalent SOHs in the target sliding window is calculated as the SOH at the corresponding time point of the window.

[0069] By obtaining the SOH of the target battery at different time points, we can apply it in many aspects: First, the SOH at the latest time point directly reflects the relative capacity of the current target battery, providing a reliable basis for the immediate evaluation of battery performance. Secondly, by tracking the change trajectory of SOH over time, we can deeply analyze the development trend of the battery degradation rate and health status, and provide important clues for predicting battery life. Furthermore, if the SOH value fluctuates significantly in a short period of time, this may indicate that there is a potential fault or abnormality in the battery. Timely monitoring of SOH changes can help us quickly identify and deal with these potential problems, and effectively avoid equipment downtime or safety accidents caused by battery failure. Finally, based on the changing trend of SOH, we can also flexibly adjust the battery management strategy, including optimizing charging and discharging modes, strengthening temperature control, etc., in order to extend the battery life and improve its overall performance.

[0070] For the operation of battery swap stations, the SOH of the target battery at different time points is also of great significance. By understanding the overall health of the battery pack, the battery swap station can arrange the maintenance and replacement plan of the battery more accurately to ensure the efficient and stable operation of the battery swap station. At the same time, based on the analysis of SOH data, the battery swap station can also optimize the battery inventory management, reduce service interruptions caused by battery aging or failure, and improve user experience and operational efficiency.

[0071] We selected two sets of batteries for actual testing to verify the accuracy of the method of the present invention in evaluating the battery health status. The SOH value of each set of batteries calculated by the algorithm of the present invention was compared with the SOH value measured by professional equipment. As shown in the following table:

[0072] Table 1: Comparison of SOH values ​​of two sets of batteries

[0073] Battery serial number Algorithm SOH Test results ****01 94 94.9 ****02 94.5 94.6

[0074] By averaging the difference between the SOH of the two battery algorithms and the measured results, we found that the average error was 0.5, which shows that the algorithm of the present invention is highly consistent with the measured values ​​as a whole. In the comparison of the two sets of batteries, the maximum error is 0.9, which is close to the measured results and has a small error. This fully proves the reliability and practicality of the method of the present invention in battery health status assessment.

[0075] Similar to the principle of the above embodiment, the present invention provides a system for calculating battery capacity based on charging data.

[0076] The following provides specific embodiments in conjunction with the accompanying drawings:

[0077] like Figure 2 A schematic diagram showing the structure of a system for calculating battery capacity based on charging data in an embodiment of the present invention.

[0078] The system comprises:

[0079] The data acquisition module 1 is used to acquire the battery charging data of each charging of the target battery in the battery swap station within a preset time period; wherein the battery charging data includes: charging process data and the rated capacity of the battery;

[0080] A data cleaning module 2, connected to the data acquisition module 1, for cleaning the charging data of each battery to remove invalid data;

[0081] An effective data extraction module 3, connected to the data cleaning module 2, for extracting charging process data that meets an effective charging cycle based on the charging data of each battery of the target battery;

[0082] A single charge capacity calculation module 4, connected to the effective data extraction module 3, is used to calculate the corresponding single charge capacity according to each charging process data that meets the effective charging cycle;

[0083] An equivalent SOH calculation module 5, connected to the single charge capacity calculation module 4, for calculating the corresponding equivalent SOH based on each single charge capacity;

[0084] A data traversal module 6, connected to the equivalent SOH calculation module 5, is used to traverse the equivalent SOHs arranged in time order through a sliding window to obtain a normal equivalent SOH of each sliding window;

[0085] The SOH calculation module 7 is connected to the data traversal module 6 and is used to calculate the SOH of the target battery at different time points and the current SOH based on the normal equivalent SOH of the sliding window that meets the sample number requirement.

[0086] It should be understood that Figure 2 The division of each module in the system embodiment is only a division of logical functions. In actual implementation, they can be fully or partially integrated into one physical entity, or physically separated. And these units can all be implemented in the form of software calling through processing elements; they can also be all implemented in the form of hardware; some units can also be implemented in the form of processing elements calling software, and some units can be implemented in the form of hardware.

[0087] Since the implementation principle of the system for calculating the battery capacity based on the charging data has been described in the above-mentioned embodiment, it will not be repeated here.

[0088] The method for calculating battery capacity based on charging data provided in the embodiment of the present invention can be implemented on the terminal side or the server side. As for the hardware structure of the electronic terminal, please refer to Figure 3 , is an optional hardware structure diagram of an electronic terminal 1000 provided in an embodiment of the present invention. The electronic terminal 1000 may be a mobile phone, a computer device, a tablet device, a personal digital processing device, a factory background processing device, etc. The electronic terminal 1000 includes: at least one processor 1001, a memory 1002, at least one network interface 10010 and a user interface 1009. The various components in the device are coupled together through a bus system 1005. It can be understood that the bus system 1005 is used to achieve connection and communication between these components. In addition to the data bus, the bus system 1005 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity, in Figure 3 In the specification, various buses are labeled as bus systems.

[0089] The user interface 1009 may include a display, a keyboard, a mouse, a trackball, a click gun, keys, buttons, a touch pad or a touch screen.

[0090] It is understood that the memory 1002 can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), which is used as an external cache. By way of exemplary but not limiting explanation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM). The memory described in the embodiments of the present invention is intended to include but is not limited to these and any other suitable categories of memory.

[0091] The memory 1002 in the embodiment of the present invention is used to store various categories of data to support the operation of the electronic terminal 1000. Examples of these data include: any executable program for operating on the electronic terminal 1000, such as an operating system 10021 and an application 10022; the operating system 10021 includes various system programs, such as a framework layer, a core library layer, a driver layer, etc., for implementing various basic services and processing hardware-based tasks. The application 10022 may include various applications, such as a media player (MediaPlayer), a browser (Browser), etc., for implementing various application services. The method for calculating battery capacity based on charging data provided in the embodiment of the present invention may be included in the application 10022.

[0092] The method disclosed in the above embodiment of the present invention can be applied to the processor 1001, or implemented by the processor 1001. The processor 1001 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit in the processor 1001 or the instruction in the form of software. The above processor 1001 may be a general processor, a digital signal processor (DSP, Digital Signal Processor), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor 1001 can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiment of the present invention. The general processor 1001 can be a microprocessor or any conventional processor, etc. In combination with the steps of the accessory optimization method provided in the embodiment of the present invention, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium, which is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0093] In an exemplary embodiment, the electronic terminal 1000 may be implemented by one or more application specific integrated circuits (ASIC), DSP, programmable logic device (PLD), complex programmable logic device (CPLD) to execute the aforementioned method.

[0094] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to the computer program. The aforementioned computer program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk and other media that can store program codes.

[0095] In the embodiments provided in the present application, the computer readable and writable storage medium may include a read-only memory, a random access memory, an EEPROM, a CD-ROM or other optical disk storage device, a disk storage device or other magnetic storage device, a flash memory, a USB flash drive, a mobile hard disk, or any other medium that can be used to store the desired program code in the form of an instruction or data structure and can be accessed by a computer. In addition, any connection can be appropriately referred to as a computer-readable medium. For example, if the instruction is sent from a website, a server or other remote source using a coaxial cable, an optical fiber cable, a twisted pair, a digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwaves, the coaxial cable, optical fiber cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwaves are included in the definition of the medium. However, it should be understood that computer readable and writable storage media and data storage media do not include connections, carriers, signals, or other temporary media, but are intended to be non-temporary, tangible storage media. Disk and disc, as used in this application, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers.

[0096] In summary, the method, system, terminal and medium for calculating battery capacity based on charging data of the present invention first collect the battery data of each charge and clean it to eliminate invalid information; then extract the charging process data that meets the effective charging cycle from the cleaned data, and calculate the single capacity of each charge accordingly; then, use these single capacity values ​​to calculate the corresponding equivalent SOH, and then use the sliding window technology to traverse the equivalent SOH arranged in time order to obtain the normal equivalent SOH in each window; finally, based on the sliding window data that meets the sample quantity requirements, calculate the SOH of the target battery at different time points. Compared with the existing solutions, the present invention is not only simple to operate, but also suitable for various complex scenarios in battery swap stations, and can accurately and effectively obtain the SOH results of the battery. Therefore, the present invention effectively overcomes the various shortcomings of the prior art and has a high industrial utilization value.

[0097] 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 technology may modify or change the above embodiments without violating the spirit and scope of the present invention. Therefore, all equivalent modifications or changes made by a person of ordinary skill in the art without departing from the spirit and technical ideas disclosed by the present invention shall still be covered by the claims of the present invention.

Claims

1. A method for calculating battery capacity based on charging data, characterized in that: The method comprises: Obtaining battery charging data of each charge of a target battery in a battery swap station within a preset time period; wherein the battery charging data includes: charging process data and rated capacity of the battery; Clean the charging data of each battery to remove invalid data; Extracting charging process data that conforms to an effective charging cycle based on charging data of each battery of the target battery; Calculate the corresponding single charge capacity according to each charging process data that meets the effective charging cycle; Based on each single charge capacity, calculate the corresponding equivalent SOH; Traverse the equivalent SOHs in time order through the sliding window to obtain the normal equivalent SOH for each sliding window; Based on the normal equivalent SOH of the sliding window that meets the sample number requirement, calculate the SOH of the target battery at different time points and the current SOH; The step of traversing the equivalent SOHs arranged in time order through a sliding window to obtain a normal equivalent SOH of each sliding window comprises: traversing the equivalent SOHs arranged in time order through a sliding window to obtain each equivalent SOH of each sliding window; wherein the size of the sliding window is set to a set time period length; and selecting a normal equivalent SOH of each sliding window by using a 2σ rule; The method of calculating the SOH of the target battery at different time points based on the normal equivalent SOH of the sliding window that meets the sample number requirement includes: screening a sliding window of normal equivalent SOH including at least a set threshold number as a target sliding window, and obtaining the normal equivalent SOH of each target sliding window; calculating the average of the normal equivalent SOH of each target sliding window to obtain the SOH at the corresponding time point of each target sliding window.

2. The method for calculating battery capacity based on charging data according to claim 1, characterized in that: The charging process data includes: current and SOC that change with time during the charging process.

3. The method for calculating battery capacity based on charging data according to claim 2, characterized in that: The extracting charging process data that meets the effective charging cycle based on the charging data of each battery of the target battery includes: Determine whether the SOC in the charging data of each battery of the target battery meets the effective charging cycle conditions, and extract the charging process data that meets the effective charging cycle conditions as the charging process data that meets the effective charging cycle; Wherein, the effective charging cycle conditions include: The ending SOC is 100%, and the starting SOC is not greater than the set threshold.

4. The method for calculating battery capacity based on charging data according to claim 2, characterized in that: The calculating of the corresponding single charging capacity according to each charging process data conforming to the effective charging cycle comprises: The ampere-hour integral of the current that changes with time in each charging process data that meets the effective charging cycle is calculated respectively to obtain the single charging capacity corresponding to each charging process data.

5. The method for calculating battery capacity based on charging data according to claim 2, characterized in that: The calculation of the corresponding equivalent SOH based on each single charge capacity includes: Calculate the equivalent capacity based on each single charge capacity and the starting SOC and ending SOC in the corresponding charging process data; The corresponding equivalent SOH is calculated according to each equivalent capacity and the rated capacity of the corresponding battery.

6. A system for calculating battery capacity based on charging data, characterized in that: The system comprises: A data acquisition module, used to acquire battery charging data of each charge of a target battery in a battery swap station within a preset time period; wherein the battery charging data includes: charging process data and rated capacity of the battery; A data cleaning module, connected to the data acquisition module, for cleaning the charging data of each battery to remove invalid data; An effective data extraction module, connected to the data cleaning module, for extracting charging process data that meets the effective charging cycle based on the charging data of each battery of the target battery; A single charge capacity calculation module, connected to the effective data extraction module, for calculating the corresponding single charge capacity according to each charging process data that conforms to the effective charging cycle; An equivalent SOH calculation module, connected to the single charge capacity calculation module, for calculating the corresponding equivalent SOH based on each single charge capacity; A data traversal module, connected to the equivalent SOH calculation module, used to traverse the equivalent SOHs arranged in time order through a sliding window to obtain a normal equivalent SOH of each sliding window; An SOH calculation module, connected to the traversal module, is used to calculate the SOH of the target battery at different time points and the current SOH based on the normal equivalent SOH of the sliding window that meets the sample number requirement; The step of traversing the equivalent SOHs arranged in time order through a sliding window to obtain a normal equivalent SOH of each sliding window comprises: traversing the equivalent SOHs arranged in time order through a sliding window to obtain each equivalent SOH of each sliding window; wherein the size of the sliding window is set to a set time period length; and selecting a normal equivalent SOH of each sliding window by using a 2σ rule; The method of calculating the SOH of the target battery at different time points based on the normal equivalent SOH of the sliding window that meets the sample number requirement includes: screening a sliding window of normal equivalent SOH including at least a set threshold number as a target sliding window, and obtaining the normal equivalent SOH of each target sliding window; calculating the average of the normal equivalent SOH of each target sliding window to obtain the SOH at the corresponding time point of each target sliding window.

7. An electronic terminal, characterized in that: include: one or more memories and one or more processors; The one or more memories are used to store computer programs; The one or more processors, connected to the memory, are configured to run the computer program to perform the method according to any one of claims 1 to 5.

8. A computer storage medium, characterized in that A computer program is stored, and when the computer program is executed, the method according to any one of claims 1 to 5 is implemented.

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