Method and device for determining internal resistance of battery, equipment and storage medium

Abstract

The invention discloses a method and device for determining the internal resistance of a battery, equipment and a storage medium, and relates to the technical field of batteries. The method for determining the internal resistance of the battery comprises: acquiring historical data of the battery; determining historical internal resistance data of the battery according to the historical data of the battery; cleaning historical internal resistance data of the battery; and correcting the historical internal resistance data of the battery according to the cleaned historical internal resistance data to determine the internal resistance data of the battery. According to the method for determining the internal resistance of the battery provided by the embodiment of the invention, the historical internal resistance data can be calculated on line by using the enough historical data, and the calculated historical internal resistance data is cleaned, so that the accuracy of the determined internal resistance data is higher.

Description

Technical Field

[0001] The present application belongs to the field of battery technology, and in particular, relates to a method, device, equipment and storage medium for determining the internal resistance of a battery. Background Art

[0002] As batteries are widely used in electric vehicles, the evaluation of battery performance has become very important. For electric vehicles, the internal resistance of the battery can affect the efficiency of the battery's external energy output and the amount of heat generated by the battery itself. Therefore, how to determine the internal resistance of the battery plays an important role in the evaluation of battery performance.

[0003] However, the method for determining the internal resistance of a battery provided by the related art has the problem of low accuracy. Summary of the invention

[0004] In view of the above problems, the present application provides a method, device, equipment and storage medium for determining the internal resistance of a battery, so as to improve the accuracy of determining the internal resistance of the battery.

[0005] In a first aspect, the present application provides a method for determining the internal resistance of a battery, comprising: obtaining historical data of a battery; determining historical internal resistance data of the battery based on the historical data of the battery; cleaning the historical internal resistance data of the battery; and correcting the historical internal resistance data of the battery based on the cleaned historical internal resistance data to determine the internal resistance data of the battery.

[0006] In the technical solution of the embodiment of the present application, the historical internal resistance data of the battery is determined by the historical data of the battery, and the internal resistance of the battery can be determined online. Moreover, as the amount of historical data increases, the accuracy of the determined historical internal resistance data can be improved. The calculated historical internal resistance data is then cleaned, and then the historical internal resistance data of the battery is corrected based on the cleaned historical internal resistance data to determine the internal resistance data of the battery. Therefore, the technical solution of the embodiment of the present application can use a sufficient amount of historical data to calculate the historical internal resistance data online, and by cleaning the calculated historical internal resistance data, the accuracy of the determined internal resistance data can be higher.

[0007] In some embodiments, determining historical internal resistance data of the battery based on historical data of the battery includes: cleaning the historical data of the battery to obtain target historical data; and determining the historical internal resistance data of the battery based on the target historical data.

[0008] In an embodiment of the present application, double data cleaning can be achieved by cleaning the historical data of the battery before calculating the historical internal resistance data, and cleaning the historical internal resistance data after calculating the historical internal resistance data, thereby improving the accuracy of the calculated historical internal resistance data, and improving the accuracy of the correction of the historical internal resistance data of the battery, thereby improving the accuracy of the determined internal resistance data.

[0009] In some embodiments, the battery's historical data is cleaned to obtain target historical data, including: cleaning the battery's historical data whose values ​​are outside a preset range, and using the battery's historical data whose values ​​are within the preset range as target historical data.

[0010] In an embodiment of the present application, based on the numerical range limit of the battery's historical data, the historical data of the battery whose values ​​are outside the preset range can be cleaned to obtain high-quality cleaned historical data, which can improve the accuracy of the determined historical internal resistance data.

[0011] In some embodiments, historical data of batteries whose values ​​are outside a preset range are cleaned so that historical data in the battery whose values ​​are within a preset range are used as target historical data, including: when the value of historical data at a first sampling moment is outside the preset range, the historical data at the first sampling moment is replaced according to the value of the historical data at a previous sampling moment and the value of the historical data at a subsequent sampling moment to obtain the target historical data.

[0012] In an embodiment of the present application, the abnormal data is replaced according to the value of the historical data at the previous sampling moment and the value of the historical data at the next sampling moment to obtain high-quality cleaned historical data, which can improve the accuracy of the determined historical internal resistance data.

[0013] In some embodiments, the historical data of the battery includes at least one of voltage, current, and temperature.

[0014] The historical data of the battery is cleaned to obtain target historical data, including: when the voltage, current and temperature at the first sampling moment are respectively the same as the voltage, current and temperature at the previous sampling moment, the voltage, current and temperature at the first sampling moment are cleaned to obtain the target historical data.

[0015] In the embodiment of the present application, the voltage, current and temperature at the first sampling moment can be cleaned according to the characteristics of the battery to obtain high-quality cleaned historical data, which can improve the accuracy of the calculated historical internal resistance data.

[0016] In some embodiments, the historical data of the battery includes multiple data segments.

[0017] Cleaning the historical data of the battery to obtain target historical data includes: cleaning data segments whose data missing degree is greater than or equal to a first threshold among the multiple data segments to obtain the target historical data.

[0018] In an embodiment of the present application, a first threshold is set to define whether any data segment is a data anomaly as a whole, so that any data segment can be cleaned according to the degree of data missing of any data segment to obtain high-quality cleaned historical data, thereby improving the accuracy of the calculated historical internal resistance data.

[0019] In some embodiments, a data segment includes at least one group of sampled data, and one sampling moment corresponds to a group of sampled data.

[0020] The degree of data missing of a data segment is determined by the ratio of the number of abnormal data groups to the total number of groups of at least one group of sampled data. Wherein, for any group of sampled data, if the ratio of the number of data anomalies to the number of data in any group of sampled data is greater than or equal to a first ratio, then any group of sampled data is an abnormal data group.

[0021] In an embodiment of the present application, by determining the number of abnormal data groups, it is possible to determine whether any data segment as a whole is data abnormal based on the degree of data missing in any data segment, thereby obtaining high-quality target historical data and improving the accuracy of the determined historical internal resistance data.

[0022] In some embodiments, determining the historical internal resistance data of the battery based on the historical data of the battery includes: determining the mathematical relationship between the historical data of the battery and the historical internal resistance data of the battery based on an equivalent circuit model of the battery; and calculating the historical internal resistance data of the battery based on the mathematical relationship and the historical data of the battery.

[0023] In the embodiment of the present application, the equivalent circuit model of the battery is used to establish a mathematical relationship between the historical data of the battery and the historical internal resistance data of the battery, and the historical internal resistance data of the battery can be calculated. In addition, since the battery is a time-varying nonlinear system, as the amount of historical data increases, the accuracy of solving the mathematical relationship can be improved by calculating the historical internal resistance data of the battery using the historical data of the battery, so as to improve the accuracy of the calculated historical internal resistance data.

[0024] In some embodiments, the historical internal resistance data of the battery is calculated based on the mathematical relationship and the historical data of the battery, including: optimizing and modeling the mathematical relationship using a mathematical optimization modeling method to obtain an optimized model; identifying parameters of the optimized model based on the historical data of the battery; and calculating the historical internal resistance data of the battery based on the identified parameters.

[0025] In the embodiment of the present application, a mathematical optimization modeling method and a parameter identification method are used to simplify the solution of the above-mentioned determined mathematical relationship, which can reduce the complexity of the calculation process and is conducive to applying the method for determining the internal resistance of the battery provided in the embodiment of the present application to actual scenarios.

[0026] In some embodiments, the parameter identification method is a recursive algorithm with a forgetting factor.

[0027] In the embodiment of the present application, a recursive algorithm with a forgetting factor is used to identify parameters of the optimization model, which can improve the accuracy of the determined historical open circuit voltage, historical ohmic internal resistance, historical polarization capacitance, and historical polarization internal resistance.

[0028] In some embodiments, the historical data of the battery includes at least N groups of sampling data, one group of sampling data corresponds to one sampling moment, and N is an integer.

[0029] N is determined by at least one of a convergence characteristic of a parameter identification method and a stable characteristic of a battery.

[0030] In the embodiment of the present application, the accuracy of the determined historical internal resistance data can be improved by determining the minimum data amount included in the historical data or target historical data of the battery through at least one of the convergence characteristics of the parameter identification method and the stability characteristics of the battery.

[0031] In some embodiments, determining historical internal resistance data of the battery based on historical data of the battery includes: determining historical internal resistance data of the battery under different operating conditions based on the historical data of the battery.

[0032] In the embodiment of the present application, the historical internal resistance data of the battery under different operating conditions can be determined based on the historical data of the battery. The internal resistance data of the battery finally determined will be more objective and less susceptible to the influence of driving habits.

[0033] In some embodiments, based on the historical data of the battery, the historical internal resistance data of the battery under different operating conditions is determined, including: aggregating the historical data of the battery to obtain the historical data of the battery under any operating condition; and calculating the historical internal resistance data of the battery under any operating condition based on the historical data of the battery under any operating condition.

[0034] In the embodiment of the present application, the internal resistance data of the battery under different working conditions is determined through historical data under different working conditions, and the obtained internal resistance data will be more objective and less susceptible to driving habits.

[0035] In some embodiments, cleaning the historical internal resistance data of the battery includes: cleaning outliers in the historical internal resistance data of the battery.

[0036] In the embodiment of the present application, the accuracy of the determined internal resistance data can be improved by cleaning the outliers in the historical internal resistance data of the battery and correcting the historical internal resistance data of the battery to determine the internal resistance data of the battery.

[0037] In some embodiments, outliers in the historical internal resistance data of the battery are cleaned, including: using statistical graphics to clean the outliers in the historical internal resistance data of the battery.

[0038] In the embodiment of the present application, outliers in the historical internal resistance data of the battery are cleaned by using statistical graphics, and the cleaning process has the advantages of being simple and intuitive.

[0039] In some embodiments, the historical internal resistance data of the battery is corrected based on the historical internal resistance data after cleaning to determine the internal resistance data of the battery, including: based on a fitting function between a first parameter of the battery and the historical internal resistance data after cleaning, the historical internal resistance data of the battery is corrected to determine the internal resistance data of the battery regarding the first parameter.

[0040] In the embodiment of the present application, the historical internal resistance data after cleaning is corrected by fitting the function, so that the accuracy of the internal resistance data determined about the first parameter can be improved. In this way, given the specific value of the first parameter, the internal resistance of the battery when the first parameter is equal to the specific value can be quickly determined according to the fitting function.

[0041] In some embodiments, the first parameter includes at least one of temperature, open circuit voltage, state of charge, and state of health.

[0042] In some embodiments, when the first parameter includes temperature, the historical internal resistance data of the battery is corrected according to a fitting function between the first parameter of the battery and the historical internal resistance data after cleaning to determine the internal resistance data of the battery with respect to the first parameter, including: performing function fitting on the first parameter of the battery and the historical internal resistance data after cleaning according to the Arrhenius formula; and correcting the historical internal resistance data of the battery according to the fitting function to determine the internal resistance data of the battery with respect to the first parameter.

[0043] In the embodiment of the present application, when the first parameter includes temperature, the accuracy of the determined internal resistance data about the first parameter can be improved by fitting the function through the Arrhenius formula to correct the historical internal resistance data after cleaning.

[0044] In some embodiments, obtaining historical data of a battery includes: obtaining first historical data of the battery in a first time period; and selecting data in a second time period from the first historical data as the historical data of the battery, wherein the second time period is within the first time period.

[0045] In an embodiment of the present application, the historical internal resistance data of the battery can be determined by cyclically acquiring the first historical data within the first time period, and selecting the data within the second time period as the historical data for calculating the historical internal resistance data of the battery. This can achieve cyclic iterative determination of the historical internal resistance data of the battery, and cyclic iterative determination of the internal resistance data of the battery, thereby improving the accuracy of determining the internal resistance of the battery.

[0046] In a second aspect, the present application provides a device for determining the internal resistance of a battery, comprising a module for executing the method described in any of the above embodiments.

[0047] In a third aspect, the present application provides a computer-readable storage medium, which stores a program. When the program is executed by a processor, the method described in any of the above embodiments is implemented.

[0048] In a fourth aspect, the present application provides an electronic device, comprising: a memory, a processor, and a program stored in the memory and executable on the processor, wherein when the processor executes the program, the method described in any of the above embodiments is implemented.

[0049] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only used for the purpose of illustrating the preferred embodiments and are not to be considered as limitations of the present application. In addition, the same reference numerals are used throughout the drawings to represent the same components.

[0051] Figure 1a This is a schematic diagram of the structure of a vehicle in some embodiments of the present application;

[0052] Figure 1b A schematic diagram of an application environment of a method for determining a battery internal resistance in some embodiments of the present application;

[0053] Figure 2 A flowchart of a method for determining the internal resistance of a battery provided in an embodiment of the present application;

[0054] Figure 3 A schematic flow chart of another method for determining the internal resistance of a battery provided in an embodiment of the present application;

[0055] Figure 4 A schematic flow chart of another method for determining the internal resistance of a battery provided in an embodiment of the present application;

[0056] Figure 5 A schematic flow chart of another method for determining the internal resistance of a battery provided in an embodiment of the present application;

[0057] Figure 6 A schematic flow chart of another method for determining the internal resistance of a battery provided in an embodiment of the present application;

[0058] Figure 7 A schematic flow chart of another method for determining the internal resistance of a battery provided in an embodiment of the present application;

[0059] Figure 8 A schematic diagram of the structure of the Thevenin equivalent circuit model provided in the embodiment of the present application;

[0060] Fig. 9 A schematic flow chart of another method for determining the internal resistance of a battery provided in an embodiment of the present application;

[0061] Fig.10 A schematic flow chart of another method for determining the internal resistance of a battery provided in an embodiment of the present application;

[0062] Fig.11 A schematic diagram of historical internal resistance data of different batteries provided in an embodiment of the present application;

[0063] Fig.12 A schematic flow chart of another method for determining the internal resistance of a battery provided in an embodiment of the present application;

[0064] Fig.13 A schematic diagram of the box plot principle provided for an embodiment of the present application;

[0065] Fig.14 A schematic flow chart of another method for determining the internal resistance of a battery provided in an embodiment of the present application;

[0066] Fig.15 A schematic flow chart of another method for determining the internal resistance of a battery provided in an embodiment of the present application;

[0067] Fig.16 A schematic diagram of a fitting curve of temperature and historical internal resistance data provided in an embodiment of the present application;

[0068] Fig.17 A schematic flow chart of another method for determining the internal resistance of a battery provided in an embodiment of the present application;

[0069] Fig.18 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0070] The following embodiments of the technical solution of the present application are described in detail in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present application, and are therefore only used as examples, and cannot be used to limit the scope of protection of the present application.

[0071] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" in the specification and claims of this application and the above-mentioned figure descriptions and any variations thereof are intended to cover non-exclusive inclusions.

[0072] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "multiple" is more than two, unless otherwise clearly and specifically defined.

[0073] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0074] In the description of the embodiments of the present application, the term "and / or" is only a description of the association relationship of the associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0075] In the related art, determining the internal resistance of a battery plays an important role in evaluating battery performance. For example, the internal resistance of a battery can affect the efficiency of the battery's external energy output and the amount of heat generated by the battery itself. To this end, the related art provides the following two methods for determining the internal resistance of a battery:

[0076] One method to determine the internal resistance of a battery is to use professional instruments to measure the internal resistance of the battery in a laboratory. However, in actual battery application scenarios, there are no corresponding professional instruments, and setting up a laboratory measurement environment will affect the normal service of the battery. That is, if the environmental requirements for the normal service of the battery are to be met, it is impossible to build the measurement environment required for professional instruments to measure the internal resistance of the battery, thereby affecting the measurement accuracy of the professional instruments. Therefore, this method is not suitable for actual application scenarios, that is, the internal resistance of the battery cannot be determined online, or the accuracy of the online determined internal resistance of the battery is poor.

[0077] Another method to determine the battery internal resistance is to simulate the characteristics of a battery in normal service by means of an equivalent circuit, and estimate the battery internal resistance by combining limited data on the power-consuming device. However, due to the limitation of software and hardware resources, the quality of limited data on the power-consuming device is not high, resulting in low accuracy of the battery internal resistance determined by this method.

[0078] In view of this, an embodiment of the present application provides a method for determining the internal resistance of a battery. First, the historical data of the battery is obtained to obtain enough battery data. Secondly, based on the historical data of the battery, the historical internal resistance data of the battery is determined, that is, the internal resistance data of the battery in the past period of time is determined. Then, the historical internal resistance data is cleaned to obtain the cleaned historical internal resistance data with higher accuracy. Finally, based on the cleaned historical internal resistance data, the historical internal resistance data of the battery is corrected, that is, the internal resistance data of the battery in the past period of time is corrected, and finally the internal resistance data with higher accuracy is obtained, which can better reflect the internal resistance of the battery in the past period of time, so as to evaluate the battery performance.

[0079] The internal resistance of the battery in the embodiment of the present application refers to the resistance encountered by the current flowing through the battery when the battery is working, which includes ohmic internal resistance and polarization internal resistance. Optionally, the polarization internal resistance includes electrochemical polarization internal resistance and concentration polarization internal resistance.

[0080] The battery in the embodiment of the present application may be a secondary battery. The battery in the embodiment of the present application may be used in an electrical device that uses the battery as a power source or in various energy storage systems that use the battery as an energy storage element. The electrical device may be, but is not limited to, a mobile phone, a tablet computer, a laptop computer, an electric toy, an electric tool, a battery car, an electric car, a ship, a spacecraft, and the like. Among them, the electric toy may include a fixed or mobile electric toy, for example, a game console, an electric car toy, an electric ship toy, and an electric airplane toy, and the like. Spacecraft may include airplanes, rockets, space shuttles, and spacecraft, and the like. For the sake of convenience of explanation, the scenario example of the embodiment of the present application is described by taking an electrical device as a vehicle as an example.

[0081] See also Figure 1a , Figure 1aA schematic diagram of the structure of the vehicle 1000 provided for this scenario example. The vehicle 1000 may be a new energy vehicle, which may be a pure electric vehicle, a hybrid vehicle, or an extended-range vehicle, etc. A battery 100 is provided inside the vehicle 1000, and the battery 100 may be provided at the bottom, head, or tail of the vehicle 1000. The battery 100 may be used to power the vehicle 1000, for example, the battery 100 may be used as an operating power source for the vehicle 1000. The vehicle 1000 may also include a controller 200 and a motor 300, and the controller 200 is used to control the battery 100 to power the motor 300, for example, for the starting, navigation, and working power requirements of the vehicle 1000 during driving. In this scenario example, the battery 100 may be used not only as an operating power source for the vehicle 1000, but also as a driving power source for the vehicle 1000 to provide driving power for the vehicle 1000.

[0082] See also Figure 1b , Figure 1b This is a schematic diagram of the application environment of the method for determining the internal resistance of a battery provided in this scenario example. The method for determining the internal resistance of a battery can be applied to Figure 1b The battery management system (BMS) in the vehicle 1000 in the embodiment of the present invention may be used in other devices (such as Figure 1b It can be understood that, in some embodiments, the mobile terminal 130 may be installed with a battery internal resistance determination application, the mobile terminal 130 obtains the historical data of the battery through the network, and the method for determining the battery internal resistance provided in the embodiment of the present application may be called during the operation of the battery internal resistance determination application to determine the internal resistance data of the battery.

[0083] In this scenario example, the method for determining the internal resistance of the battery is applied to the cloud server 120 as an example for explanation. Specifically, a variety of sensors are installed on the vehicle 1000 to collect historical data of the battery 100, such as at least one of current, voltage, temperature, and state of charge (SOC). The vehicle 1000 sends the historical data of the battery 100 collected by at least one sensor to the cloud server 120 through the communication module. The cloud server 120 determines the historical internal resistance data of the battery 100 based on the historical data of the battery 100. Then, the cloud server 120 cleans the historical internal resistance data of the battery 100, and finally the cloud server 120 determines the internal resistance data of the battery 100 based on the cleaned historical internal resistance data.

[0084] It is worth noting that the specific implementation of the vehicle or mobile terminal 130 determining the internal resistance data of the battery 100 can also refer to the specific process of the cloud server 120 determining the internal resistance data of the battery 100, which will not be repeated here.

[0085] It is understandable that the cloud server 120 may be connected to a display device, and the determined internal resistance data of the battery 100 may be displayed via the connected display device.

[0086] In this scenario example, the cloud server 120 can send the determined internal resistance data of the battery 100 to the mobile terminal 130. The mobile terminal 130 displays the internal resistance data of the battery 100 via a display screen.

[0087] Exemplarily, the mobile terminal 130 or the cloud server 120 may also evaluate the battery performance according to the internal resistance data of the battery 100 .

[0088] The embodiment of the present application can also provide another scenario example, the method for determining the internal resistance of a battery is applied to Figure 1b In the battery management system of the vehicle 1000. The battery management system collects historical data of the battery 100, determines historical internal resistance data of the battery 100 based on the historical data of the battery 100, then cleans the historical internal resistance data of the battery 100, and finally determines the internal resistance data of the battery 100 based on the cleaned historical internal resistance data.

[0089] In the above scenario example, the battery internal resistance can be determined online by using the battery's historical data, and as the amount of historical data increases, the accuracy of the determined battery internal resistance can be improved. In addition, in the process of determining the battery internal resistance, the calculated historical internal resistance data is cleaned so that the historical internal resistance data of the battery can be corrected based on the cleaned historical internal resistance data to determine the battery's internal resistance data, which can improve the accuracy of the determined battery internal resistance.

[0090] In order to illustrate the technical solution described in this application, a specific embodiment is provided below for illustration.

[0091] The following describes a method for determining the internal resistance of a battery provided by an embodiment of the present application, taking an electronic device as an example in which the execution subject of the embodiment of the present application is an electronic device.

[0092] See also Figure 2 Some embodiments of the present application provide a method for determining the internal resistance of a battery. The method for determining the internal resistance of a battery may include the following steps:

[0093] S210: The electronic device obtains historical data of the battery of the power-consuming device.

[0094] The historical data of a battery refers to the data generated by the battery of an electrical device in the past period of time that can be used to calculate the internal resistance of the battery. For example, the historical data may include the operating status data of the battery at different times. For example, the operating status data may be at least one of the voltage, current, temperature and state of charge of the battery. For another example, the historical data may also include the environmental data of the battery at different times. For example, the environmental data may be at least one of the ambient temperature, ambient humidity and ambient air pressure. Of course, the historical data of the battery may also include the operating status data corresponding to the environment in which the battery is located at different times. For example, at time T1, when the ambient temperature is 30°C, at least one of the voltage, current, temperature and state of charge corresponding to the battery. For another example, at time T2, when the ambient temperature is -10°C, at least one of the voltage, current, temperature and state of charge corresponding to the battery.

[0095] For example, the electrical equipment is a vehicle, such as a new energy vehicle.

[0096] As time goes by and the battery is used, the amount of historical data generated by the battery will increase. Therefore, as time goes by, step S210 can eventually obtain a sufficient amount of historical data. And this sufficient amount of historical data can be obtained online, that is, during the use of the electrical device, the historical data that can be continuously generated and collected is obtained.

[0097] The electronic device in the embodiments of the present application may refer to the above-mentioned vehicle, mobile terminal, cloud server or battery management system.

[0098] As an example, taking the electronic device as a device other than the cloud server, the vehicle can periodically send the collected battery operating status data and / or environmental data to the electronic device, or the vehicle can periodically upload the collected battery operating status data and / or environmental data to the cloud server, and the electronic device obtains it from the cloud server.

[0099] For example, the vehicle may periodically send the collected operating status data of the battery in the first time period to the cloud server, and the electronic device may obtain the operating status data of the battery in the second time period from the operating status data of the battery in the first time period to calculate the battery internal resistance of the battery in the second time period. The second time period is within the first time period. Optionally, the first time period may be the same as the second time period.

[0100] For example, taking the first time period as one month, the vehicle can upload the operating status data and / or environmental data collected within one month from time 1 to time 4 to the cloud server, and then the electronic device can obtain the operating status data and / or environmental data in the time period from time 1 to time 2 or time 2 to time 4 from the cloud server for use in calculating the battery internal resistance in the second time period.

[0101] S220: The electronic device determines historical internal resistance data of the battery according to the historical data of the battery.

[0102] In this step, the electronic device can determine the internal resistance data of the battery in the past period of time based on the historical data of the battery.

[0103] It should be understood that, based on the historical data of the battery, relevant technical means can be used to calculate the historical internal resistance data of the battery. For example, the electronic device can calculate the historical internal resistance data of the battery by substituting the historical data of the battery into the historical data of the battery according to the mathematical relationship between the historical data of the battery and the historical internal resistance data of the battery.

[0104] It should be noted that as the amount of historical data increases, the accuracy of the determined historical internal resistance data can be improved.

[0105] As an example, the electronic device can obtain an equivalent model of the battery, and then determine the mathematical relationship between the historical data of the battery and the historical internal resistance data of the battery according to the equivalent model of the battery, and then substitute the historical data of the battery for calculation to calculate the historical internal resistance data of the battery. For example, the equivalent model of the battery includes but is not limited to: electrical characteristic model, thermal model, electrothermal coupling model, aging model, etc. Among them, the electrical characteristic model includes but is not limited to: black box model, equivalent circuit model, electrochemical mechanism model, etc. The embodiment of the present application can select the corresponding model to calculate the historical internal resistance data of the battery according to actual needs.

[0106] S230: The electronic device cleans the historical internal resistance data of the battery.

[0107] Data cleaning is the process of detecting damaged or inaccurate records from a record set, database table or database, and correcting or deleting the records. It means identifying the incomplete, incorrect, inaccurate or irrelevant parts of the data, and then replacing, modifying or deleting the data to complete the cleaning. The above incomplete, incorrect, inaccurate or irrelevant parts of the data can be called abnormal data.

[0108] Therefore, step S230 is used to identify abnormal data in the historical internal resistance data of the battery, and clean the abnormal data by using at least one operation of replacement, modification and deletion.

[0109] It should be understood that the historical internal resistance data after cleaning can more accurately reflect the internal resistance data of the battery over a period of time in the past.

[0110] It is understandable that, since the change rate of the battery internal resistance is generally relatively slow, the historical internal resistance data after cleaning as a whole meets the characteristic that the change rate of the battery internal resistance is relatively slow. For example, the change rate is equal to the change value of the battery internal resistance divided by the time corresponding to the change value. For example, the change value of the battery internal resistance is 1mΩ, and the corresponding time is one week, then the change rate is 1 / 7. Exemplarily, it can be defined that the change rate corresponding to any two battery internal resistances in the historical internal resistance data after cleaning is less than or equal to the first change threshold.

[0111] S240: The electronic device corrects the historical internal resistance data of the battery according to the historical internal resistance data after cleaning to determine the internal resistance data of the battery.

[0112] It should be noted that, since historical data has the characteristic of large data volume, the historical internal resistance data after cleaning can still have a large amount of available data, so the historical internal resistance data after cleaning can be used to correct the historical internal resistance data of the battery to determine the internal resistance data of the battery.

[0113] It should be understood that as time goes by, the amount of historical data gradually increases, and the calculated historical internal resistance data will also increase, so that the determined internal resistance data can be continuously updated, making the accuracy of the determined battery internal resistance data higher and higher.

[0114] The above method for determining the internal resistance of a battery can use sufficient historical data to calculate the historical internal resistance data online, and clean the calculated historical internal resistance data so as to correct the historical internal resistance data of the battery according to the cleaned historical internal resistance data to determine the internal resistance data of the battery. The internal resistance data determined in this way has a higher accuracy.

[0115] As an example, after determining the internal resistance data of the battery, the electronic device may also output the internal resistance data of the battery, for example, by displaying it with the aid of a display device, or sending the internal resistance data of the battery to a vehicle or a mobile terminal.

[0116] See also Figure 3 In some embodiments of the present application, determining the historical internal resistance data of the battery according to the historical data of the battery may specifically include the following steps:

[0117] S310: The electronic device cleans the historical data of the battery to obtain target historical data.

[0118] Since the collected historical data of the battery may be abnormal, in order to improve the accuracy of determining the internal resistance of the battery, the historical data of the battery may be cleaned.

[0119] In this way, step S310 can be used to identify abnormal data in the historical data of the battery, and clean the abnormal data by using at least one operation of replacement, modification and deletion.

[0120] As an example, abnormal data in historical data include but are not limited to: historical data of batteries whose values ​​are outside a preset range, historical data of batteries with a large degree of data missing, and historical data of batteries whose data should change in real time but do not change. How to judge these abnormal data and how to clean these abnormal data will be described below.

[0121] For example, cleaning the historical data of a battery to obtain target historical data may refer to: cleaning the historical data of the battery, and then using the cleaned historical data of the battery as the target historical data.

[0122] For example, the target historical data includes historical data of batteries whose values ​​are within a preset range, historical data of batteries whose data missing is relatively small, and historical data of batteries whose data should change in real time.

[0123] S320: The electronic device determines historical internal resistance data of the battery according to the target historical data.

[0124] It should be noted that since historical data has the characteristic of large data volume, the historical data after cleaning can still have a large amount of available data, that is, the target historical data still has a large amount of available data, so that the historical internal resistance data of the battery can be calculated based on the target historical data to improve the accuracy of the calculated historical internal resistance data.

[0125] The above method for determining the internal resistance of a battery can achieve double data cleaning by cleaning the historical data of the battery before calculating the historical internal resistance data, and cleaning the historical internal resistance data after calculating the historical internal resistance data, thereby improving the accuracy of the calculated historical internal resistance data, and improving the accuracy of correcting the historical internal resistance data of the battery, thereby improving the accuracy of the determined internal resistance data.

[0126] See also Figure 4 In some embodiments of the present application, the historical data of the battery is cleaned to obtain the target historical data, which may specifically include the following steps:

[0127] S410: The electronic device cleans the historical data of the battery whose values ​​are outside a preset range, so as to use the historical data of the battery whose values ​​are within the preset range as the target historical data.

[0128] It should be understood that in some embodiments, based on the characteristics of the battery and / or the scenarios in which the battery is used, the historical data of the battery has a certain value range limit. In other words, the value range of the historical data of the battery can be determined by at least one of the characteristics of the battery and / or the scenarios in which the battery is used. Therefore, historical data with values ​​within the preset range can be regarded as normal data, and historical data with values ​​outside the preset range can be regarded as abnormal data.

[0129] As an example, based on the characteristics of the battery, the battery voltage has a numerical range limit. For example, the battery voltage has a numerical range of 2.8V to 4.2V. When the obtained battery voltage is 5V, the data is abnormal data, and at least one of replacement, modification and deletion is used to clean the abnormal data.

[0130] As an example, based on the scenario of using the battery, the battery temperature has a numerical range limit. For example, if the temperature around the battery is 20°C, the numerical range of the battery temperature is greater than or equal to 20°C. When the obtained battery temperature is 15°C, the data is abnormal data, and at least one of replacement, modification and deletion is used to clean the abnormal data.

[0131] The above method for determining the internal resistance of a battery can clean the historical data of the battery whose values ​​are outside the preset range based on the numerical range limit of the historical data of the battery to obtain high-quality cleaned historical data, which can improve the accuracy of the determined historical internal resistance data.

[0132] In some embodiments, cleaning the historical data of the battery whose values ​​are outside the preset range, so as to use the historical data of the battery whose values ​​are within the preset range as the target historical data, may specifically include the following steps:

[0133] S411. When the value of the historical data at the first sampling moment is outside a preset range, the electronic device replaces the historical data at the first sampling moment according to the value of the historical data at the previous sampling moment and the value of the historical data at the next sampling moment to obtain target historical data.

[0134] As an example, the battery voltage has a numerical range of 2.8V to 4.2V, the voltage at the first sampling moment is 5V, the voltage at the previous sampling moment is 4.12V, and the voltage at the next sampling moment is 4.08V. Then, the voltage at the first sampling moment is replaced according to 4.12V and 4.08V. For example, the voltage at the first sampling moment is replaced with the average value of 4.12V and 4.08V, 4.1V. For example, any one of the voltage at the previous sampling moment and the voltage at the next sampling moment can be used as the voltage at the first sampling moment, or the voltage at the previous sampling moment and the voltage at the next sampling moment that has the smallest difference with the voltage at the first sampling moment can be used as the voltage at the first sampling moment.

[0135] The above method for determining the internal resistance of the battery replaces abnormal data according to the value of the historical data at the previous sampling moment and the value of the historical data at the next sampling moment to obtain high-quality cleaned historical data, which can improve the accuracy of the determined historical internal resistance data.

[0136] See also Figure 5 In some embodiments of the present application, the historical data of the battery includes at least one of voltage, current and temperature.

[0137] The above-mentioned cleaning of the historical data of the battery to obtain the target historical data may specifically include the following steps:

[0138] S510: When the voltage, current and temperature at the first sampling moment are respectively the same as the voltage, current and temperature at the previous sampling moment, the electronic device cleans the voltage, current and temperature at the first sampling moment to obtain target historical data.

[0139] According to the characteristics of the battery, the voltage, current and temperature of the battery will change continuously. Therefore, if the voltage, current and temperature of the battery do not change at the same time in the collected data for a period of time, it means that the data is abnormal. For example, if the voltage, current and temperature at the first sampling moment are the same as the voltage, current and temperature at the previous sampling moment, it means that the voltage, current and temperature at the first sampling moment are abnormal data and need to be cleaned to obtain high-quality cleaned historical data.

[0140] In some embodiments, when an abnormality occurs in the data transmission channel (for example, the transmission link is interrupted, or the transmission link is long resulting in data loss), the voltage, current and temperature at the first sampling moment may be the same as the voltage, current and temperature at the previous sampling moment.

[0141] In some embodiments, the above-mentioned cleaning of the voltage, current and temperature at the first sampling moment includes: deleting the voltage, current and temperature at the first sampling moment; or replacing the abnormal data (voltage, current and temperature) at the first sampling moment according to the value of the historical data (voltage, current and temperature) at the previous sampling moment and the value of the historical data (voltage, current and temperature) at the next sampling moment.

[0142] The above method for determining the internal resistance of the battery can clean the voltage, current and temperature at the first sampling moment according to the characteristics of the battery to obtain high-quality cleaned historical data, which can improve the accuracy of the calculated historical internal resistance data.

[0143] See also Figure 6 In some embodiments of the present application, the historical data of the battery includes multiple data segments. Since the amount of historical data increases over time, the historical data can be divided into multiple data segments according to different sampling time periods. At this time, the target historical data does not include data segments whose data missing degree is greater than or equal to the first threshold. In other words, the missing degree of the data segments included in the target historical data is less than the first threshold.

[0144] After such setting, the historical data of the battery is cleaned to obtain the target historical data, which may specifically include the following steps:

[0145] S610: The electronic device cleans data segments whose data missing degree is greater than or equal to a first threshold among multiple data segments to obtain target historical data.

[0146] It should be noted that, when the degree of data missing of any data segment is greater than or equal to the first threshold, it means that the data segment as a whole is abnormal data and needs to be cleaned.

[0147] The above method for determining the internal resistance of the battery sets a first threshold value to define whether any data segment is an overall data anomaly, so as to clean any data segment according to the degree of data missing of any data segment to obtain high-quality cleaned historical data, thereby improving the accuracy of the calculated historical internal resistance data.

[0148] For example, if the data missing degree of a data segment is greater than or equal to a first threshold, the data segment can be removed from multiple data segments, or the data segment can be repaired so that the data missing degree of the repaired data segment is less than the first threshold.

[0149] In some embodiments of the present application, a data segment includes at least one group of sampled data, and one sampling moment corresponds to a group of sampled data.

[0150] Since a set of sampled data can be sampled at each sampling moment, for example, a set of sampled data including voltage, current, temperature, state of charge and the like, the historical data of the battery includes multiple sets of sampled data. According to different sampling moments, the multiple sets of sampled data can be divided into multiple data segments, that is, one data segment can include at least one set of sampled data.

[0151] In the embodiment of the present application, the degree of data missing of a data segment is determined by the ratio of the number of abnormal data groups to the total number of data groups in a data segment.

[0152] For any set of sampled data, if the ratio of the number of abnormal data to the number of data in any set of sampled data is greater than or equal to a first ratio, then any set of sampled data is regarded as an abnormal data set.

[0153] As an example, a group of sampled data includes four data, namely, current, voltage, temperature and state of charge, and the first ratio is 30%. If both the voltage and current of the battery are abnormal, the number of abnormal data is 2, and the ratio of the number of abnormal data to the number of data in the group of sampled data is 50%, which is greater than 30%, so the group of sampled data can be determined as an abnormal data group.

[0154] As an example, a data segment includes 10 groups of sampled data. If the number of abnormal data groups is 1, the data missing degree of the data segment is 10%. If the 10% is greater than or equal to the first threshold, the data segment is regarded as having data anomalies as a whole and needs to be cleaned.

[0155] The above method for determining the internal resistance of the battery determines the number of abnormal data groups so as to determine whether any data segment is abnormal as a whole according to the degree of data missing of any data segment, thereby obtaining high-quality target historical data and improving the accuracy of the determined historical internal resistance data.

[0156] See also Figure 7 In some embodiments of the present application, determining the historical internal resistance data of the battery according to the historical data of the battery may specifically include the following steps:

[0157] S710: Determine a mathematical relationship between historical data of the battery and historical internal resistance data of the battery according to an equivalent circuit model of the battery.

[0158] It should be noted that the equivalent model of the battery includes but is not limited to: electrical characteristic model, thermal model, electrothermal coupling model, aging model, etc. Among them, the electrical characteristic model includes but is not limited to: black box model, equivalent circuit model, electrochemical mechanism model, etc.

[0159] Since the embodiment of the present application is used to determine the internal resistance of the battery, an equivalent circuit model in the electrical characteristic model is used to determine the mathematical relationship between the historical data of the battery and the historical internal resistance data of the battery, which is beneficial to improving the accuracy of the determined historical internal resistance data.

[0160] S720: The electronic device calculates historical internal resistance data of the battery according to the mathematical relationship and historical data of the battery.

[0161] On the basis of determining the mathematical relationship between the historical data of the battery and the historical internal resistance data of the battery, a mathematical relationship between the historical data of the battery and the historical internal resistance data of the battery can be obtained. By substituting the historical data of the battery, the historical internal resistance data of the battery can be solved.

[0162] The above method for determining the internal resistance of a battery uses an equivalent circuit model of a battery to establish a mathematical relationship between the historical data of the battery and the historical internal resistance data of the battery, and the historical internal resistance data of the battery can be calculated. In addition, since the battery is a time-varying nonlinear system, as the amount of historical data increases, the accuracy of solving the mathematical relationship can be improved by using the historical data of the battery to calculate the historical internal resistance data of the battery, so as to improve the accuracy of the calculated historical internal resistance data.

[0163] In some embodiments, if different equivalent circuit models are selected, the specific content of the historical internal resistance data solved is different. For example, the above-mentioned equivalent circuit model can be a first circuit network including a resistor and a voltage source, or a second circuit network including a resistor, a capacitor and a voltage source. Exemplarily, the historical internal resistance data solved using the first circuit network includes the ohmic internal resistance of the battery. The historical internal resistance data solved using the second circuit network includes the ohmic internal resistance and polarization internal resistance of the battery.

[0164] See also Figure 8 As an example, a Thevenin equivalent circuit model of a battery is provided. oc is the open circuit voltage of the battery, R o is the ohmic internal resistance of the battery, C p is the polarization capacitance of the battery, R p is the polarization internal resistance of the battery, U t is the load voltage output by the battery, and I is the output current of the battery.

[0165] Therefore, according to the Thevenin equivalent circuit model of the battery, the mathematical relationship between the historical data of the battery and the historical internal resistance data of the battery can be determined as follows:

[0166]

[0167]

[0168] Where k represents the sampling time, is the polarization internal resistance R at time k p The voltage across the terminals, I k is the output current of the battery at time k, Δt is the sampling time interval between time k and time (k-1), is the polarization internal resistance R at time (k-1) p The voltage across the terminals, is the load voltage output by the battery at time k, is the open circuit voltage of the battery at time k.

[0169] According to the above equations (1) and (2), the voltage and current data in the historical data of the battery can be used in combination with the sampling time to obtain the open circuit voltage, ohmic internal resistance, polarization capacitance and polarization internal resistance of the battery at each sampling time, thereby obtaining the historical open circuit voltage, historical ohmic internal resistance, historical polarization capacitance and historical polarization internal resistance of the battery. Among them, the historical internal resistance data described in the embodiment of the present application may include historical ohmic internal resistance and / or historical polarization internal resistance.

[0170] The above method for determining the internal resistance of a battery calculates the historical open circuit voltage, historical ohmic internal resistance, historical polarization capacitance and historical polarization internal resistance of the battery based on the Thevenin equivalent circuit model of the battery, which can improve the accuracy of the determined historical internal resistance data of the battery.

[0171] See also Fig. 9 In some embodiments of the present application, the historical internal resistance data of the battery is calculated according to the mathematical relationship and the historical data of the battery, which may specifically include the following steps:

[0172] S910. The electronic device optimizes and models the mathematical relationship using a mathematical optimization modeling method to obtain an optimized model.

[0173] It should be understood that since it is relatively complicated to directly solve the above equations (1) and (2), relevant mathematical optimization modeling methods can be used to obtain approximate solutions to the above equations (1) and (2) to reduce the complexity of the calculation process.

[0174] S920: The electronic device identifies parameters of the optimization model according to historical data of the battery.

[0175] The above-mentioned mathematical optimization modeling method is used to optimize the mathematical relationship and to obtain an optimization model. Then, the parameters of the optimization model can be identified by using the historical data of the battery.

[0176] It should be noted that parameter identification is a technology that combines theoretical models with test data for prediction. In the embodiment of the present application, parameter identification refers to determining the parameters of the optimization model based on the historical data of the battery and the optimization model, so that the numerical results calculated by the parameters of the optimization model can better fit the historical internal resistance data of the battery.

[0177] S930: The electronic device calculates historical internal resistance data of the battery according to the identified parameters.

[0178] After parameter identification, the identified parameters can be converted into historical internal resistance data of the battery to complete the calculation.

[0179] The above method for determining the internal resistance of the battery adopts a mathematical optimization modeling method and a parameter identification method to simplify the mathematical relationship determined in the solution step S710, which can reduce the complexity of the calculation process and is conducive to applying the method for determining the internal resistance of the battery provided in the embodiment of the present application to actual scenarios.

[0180] In some embodiments, the above-mentioned use of the mathematical optimization modeling method to optimize the mathematical relationship modeling may specifically include the following steps:

[0181] S911. The electronic device converts the mathematical relationship between the historical data of the battery and the historical internal resistance data of the battery into a least square method relationship.

[0182] As an example, the above equations (1) and (2) are transformed to obtain the following optimization model equation:

[0183]

[0184]

[0185] R o = - β2 (5)

[0186]

[0187]

[0188] Among them, β0, β1, β2, and β3 are the parameters of the optimization model.

[0189] Then, by solving the above optimization model parameters β0, β1, β2, and β3 through the parameter identification method, the open circuit voltage, ohmic internal resistance, polarization capacitance, and polarization internal resistance of the battery can be obtained, thereby obtaining the historical open circuit voltage, historical ohmic internal resistance, historical polarization capacitance, and historical polarization internal resistance of the battery.

[0190] The above method for determining the internal resistance of the battery adopts the least squares method to optimize the modeling and perform parameter identification on the optimization model, which simplifies the process of solving the mathematical relationship determined in step S710, can reduce the complexity of the calculation process, and is conducive to applying the method for determining the internal resistance of the battery provided in the embodiment of the present application to actual scenarios.

[0191] In some embodiments, the parameter identification method is a recursive algorithm with a forgetting factor. Therefore, the parameter identification of the optimization model based on the historical data of the battery may specifically include the following steps:

[0192] S921. The electronic device uses a recursive algorithm with a forgetting factor to perform parameter identification on the optimization model, thereby identifying the optimization model parameters β0, β1, β2, and β3.

[0193] It should be noted that a recursive algorithm refers to a method of solving a problem by repeatedly decomposing the problem into similar sub-problems. In the embodiment of the present application, as time goes by, the amount of historical data will increase, so it is necessary to cyclically substitute the newly generated historical data into the optimization model relationship to perform parameter identification on the optimization model, which is to use a recursive algorithm for parameter identification.

[0194] Since the battery is a time-varying system, the weights of the old historical data and the new historical data should be inconsistent, that is, the weight of the new historical data is greater, while the weight of the old historical data is smaller. Therefore, by using a recursive algorithm with a forgetting factor, the accuracy of parameter identification can be improved by adjusting the weights of the old historical data and the new historical data, so that the identified parameters are more in line with the actual situation of the battery, thereby improving the accuracy of the calculated open circuit voltage, ohmic internal resistance, polarization capacitance and polarization internal resistance of the battery.

[0195] The above method for determining the internal resistance of the battery adopts a recursive algorithm with a forgetting factor to perform parameter identification on the optimization model, which can improve the accuracy of the determined historical open circuit voltage, historical ohmic internal resistance, historical polarization capacitance and historical polarization internal resistance.

[0196] As an example, in combination with the above steps S911 and S921, the recursive algorithm with forgetting factor provided in the embodiment of the present application is specifically a recursive least squares method with forgetting factor.

[0197] In some embodiments, since it is necessary to combine historical data of the battery to identify parameters of the optimization model, a sufficient amount of historical data is required to ensure that the identified parameters have sufficient credibility.

[0198] It should be noted that the characteristics of the battery are unstable in the initial stage, for example, the output voltage is unstable in the initial stage. Generally, the characteristics of the battery will become stable after a period of use. This is the inherent stability characteristic of the battery.

[0199] It should also be noted that, in the process of parameter identification of the optimization model based on the historical data of the battery, as the amount of historical data increases, the convergence of the parameter identification method will gradually improve. In other words, when the amount of historical data is small, the convergence of the parameter identification method is poor, and the accuracy of the parameters identified and the open circuit voltage, ohmic internal resistance, polarization capacitance and polarization internal resistance calculated thereby are all low. When the amount of historical data is large, the convergence of the parameter identification method is good, and the accuracy of the parameters identified and the open circuit voltage, ohmic internal resistance, polarization capacitance and polarization internal resistance calculated thereby are all high. This is the convergence characteristic of the parameter identification method.

[0200] Based on the above analysis, in the embodiment of the present application, when the historical data of the battery includes at least N groups of sampled data, it can be ensured that the identified parameters have sufficient credibility. N can be determined by at least one of the convergence characteristics of the parameter identification method and the stability characteristics of the battery. Among them, a group of sampled data corresponds to a sampling moment, and N is an integer.

[0201] The above method for determining the internal resistance of a battery can improve the accuracy of the determined historical internal resistance data by determining the minimum data amount included in the historical data or target historical data of the battery through at least one of the convergence characteristics of the parameter identification method and the stability characteristics of the battery.

[0202] In some embodiments, if the characteristics of the battery tend to be stable after the battery is used for a first time, then based on the first time and the sampling interval, it can be calculated that the first set of sampled data can be collected within the first time. If the historical data of the battery includes the second set of sampled data, the convergence of the parameter identification method is better. Therefore, based on the larger of the first set and the second set, the value of N can be determined. For example, N is greater than or equal to the larger of the first set and the second set.

[0203] In some embodiments, the historical data or target historical data of the battery involved in calculating the historical internal resistance data includes at least N groups of sampling data to ensure the accuracy of the calculated historical internal resistance data.

[0204] As an example, as shown in Table 1 below, the target historical data includes at least 500 groups of sampled data, and each group of sampled data includes voltage, current, temperature, and state of charge at 500 sampling moments.

[0205] Table 1

[0206] Group number Sampling time Voltage Current temperature State of Charge 1 0s 3300 100 25 99％ 2 10s 3290 80 25 98％ … … … … … … 500 … … … … …

[0207] See also Fig.10 In some embodiments of the present application, determining the historical internal resistance data of the battery according to the historical data of the battery may specifically include the following steps:

[0208] S1010. The electronic device determines historical internal resistance data of the battery under different operating conditions based on historical data of the battery.

[0209] In the actual use of the battery, there are various working conditions, including but not limited to charging conditions, discharging conditions, static conditions, etc. Among them, the charging conditions include but are not limited to the parking fast charging conditions and the parking slow charging conditions. The discharging conditions include but are not limited to the high rate discharge conditions and the low rate discharge conditions.

[0210] Therefore, as an example, the historical internal resistance data of the battery under different operating conditions may be determined based on the historical data of the battery.

[0211] The above method for determining the internal resistance of a battery can determine the historical internal resistance data of the battery under different operating conditions based on the historical data of the battery. The internal resistance data of the battery finally determined will be more objective and less susceptible to the influence of driving habits.

[0212] In some embodiments, determining the historical internal resistance data of the battery under different working conditions based on the historical data of the battery may specifically include the following steps:

[0213] S1011. The electronic device aggregates the historical data of the battery to obtain the historical data of the battery under any working condition.

[0214] For example, the historical data of the battery is aggregated to obtain first historical data under a first operating condition, second historical data under a second operating condition, third historical data under a third operating condition, etc. The first operating condition, the second operating condition, and the third operating condition are different operating conditions.

[0215] As an example, according to the meaning of operating condition types such as WLPT (World Light Vehicle Test Procedure), CLTC (China light-duty vehicle test cycle-passenger), and NEDC (New European Driving Cycle), data that conforms to these operating condition types can be selected from the battery's historical data for aggregation, thereby splicing out historical data under WLPT conditions, CLTC conditions, or NEDC conditions, thereby determining the internal resistance data of the battery under these conditions, which helps to more comprehensively evaluate the battery internal resistance.

[0216] S1012. The electronic device determines historical internal resistance data of the battery under any operating condition based on historical data of the battery under any operating condition.

[0217] By first aggregating the historical data of the battery to obtain the historical data of the battery under any operating condition, and then determining the historical internal resistance data of the battery under any operating condition, a multi-faceted evaluation of the battery internal resistance can be achieved, and ultimately the internal resistance data of the battery under different operating conditions can be obtained.

[0218] The above method for determining the internal resistance of the battery determines the internal resistance data of the battery under different working conditions through historical data under different working conditions. The obtained internal resistance data will be more objective and less susceptible to the influence of driving habits.

[0219] As an example, before aggregating the historical data of the battery, the historical data can be cleaned first to obtain target historical data, and then the target historical data can be aggregated to obtain historical data under any working condition, and the historical data under each working condition contains at least N groups of sampling data, which can improve the accuracy of the final determined internal resistance data of the battery.

[0220] See also Fig.11 , in some embodiments of the present application, a schematic diagram of the historical internal resistance data determined in step S220 is shown.

[0221] like Fig.11 As shown, 55-64 are serial numbers of different batteries, the horizontal axis represents the sampling time, and the vertical axis represents the internal resistance value of different batteries.

[0222] according to Fig.11 The curve graph shown can intuitively show the differences between different batteries, so as to determine the consistency of different batteries.

[0223] See also Fig.12 In some embodiments of the present application, the above-mentioned cleaning of the historical internal resistance data of the battery may specifically include the following steps:

[0224] S1210: The electronic device cleans outliers in the historical internal resistance data of the battery.

[0225] In statistics, outliers are data points that are significantly different from other observed values. Since the internal resistance of a battery theoretically does not undergo rapid mutations, outliers are obviously abnormal. The amount of historical data is large enough, so it is suitable to use statistical thinking to clean up outliers.

[0226] The above method for determining the internal resistance of a battery can improve the accuracy of the determined internal resistance data by cleaning outliers in the historical internal resistance data of the battery and correcting the historical internal resistance data of the battery to determine the internal resistance data of the battery.

[0227] In some embodiments, the above-mentioned cleaning of outliers in the historical internal resistance data of the battery may specifically include the following steps:

[0228] S1211. The electronic device uses statistical graphics to clean outliers in the historical internal resistance data of the battery.

[0229] It should be noted that statistical graphs refer to information graphs used to visualize quantitative data in the field of statistics. In the embodiment of the present application, the statistical graphs can intuitively reflect the differences between various historical internal resistance data and the changing trends of the historical internal resistance data.

[0230] As an example, statistical graphics include, but are not limited to, scatter plots, histograms, probability plots, residual plots, box plots, block plots, and biplots.

[0231] The above method for determining the internal resistance of a battery uses a statistical graphic method to clean outliers in the historical internal resistance data of the battery, and the cleaning process has the advantages of being simple and intuitive.

[0232] See also Fig.13 As an example, the embodiment of the present application uses a box plot to clean up outliers in the historical internal resistance data of the battery.

[0233] It should be noted that one advantage of the box plot is that it is not affected by outliers, can accurately and stably depict the discrete distribution of data, and is conducive to data cleaning.

[0234] like Fig.13 As shown, the box plot is based on the idea of ​​data statistics to exclude outliers outside the interval (Q1-1.5×IQR, Q3+1.5×IQR). Among them, Q1 is the lower quartile, Median is the median, and Q3 is the upper quartile, so the upper limit is Q3+1.5×IQR, IQR is the interquartile range, and IQR=Q3-Q1. Therefore, the lower limit is Q1-1.5×IQR, and the upper limit is Q3+1.5×IQR.

[0235] Therefore, the above method for determining the internal resistance of the battery can improve the accuracy of the determined internal resistance data by cleaning the outliers in the historical internal resistance data of the battery through the box plot.

[0236] See also Fig.14In some embodiments, the above-mentioned method of correcting the historical internal resistance data of the battery according to the historical internal resistance data after cleaning to determine the internal resistance data of the battery may specifically include the following steps:

[0237] S1410: The electronic device corrects the historical internal resistance data of the battery according to a fitting function between the first parameter of the battery and the historical internal resistance data after cleaning, so as to determine the internal resistance data of the battery with respect to the first parameter.

[0238] Since the calculated historical internal resistance data is the internal resistance data at each sampling moment, the historical internal resistance data after cleaning can be corrected by fitting a function. To this end, it is necessary to select a first parameter for fitting the historical internal resistance data after cleaning.

[0239] The above method for determining the internal resistance of the battery can improve the accuracy of the internal resistance data determined about the first parameter by correcting the historical internal resistance data after cleaning by means of a fitting function. In this way, given a specific value of the first parameter, the internal resistance of the battery when the first parameter is equal to the specific value can be quickly determined according to the fitting function.

[0240] In some embodiments, the first parameter includes at least one of temperature, open circuit voltage, state of charge, and state of health.

[0241] For example, when the first parameter includes temperature, the internal resistance of the battery at any temperature can be determined. Exemplarily, the ohmic internal resistance and / or the polarization internal resistance at any temperature can be determined.

[0242] For another example, when the first parameter includes the state of charge, the internal resistance of the battery at any state of charge can be determined. Exemplarily, the ohmic internal resistance and / or the polarization internal resistance at any state of charge can be determined.

[0243] For another example, when the first parameter includes temperature and open circuit voltage, the internal resistance of the battery at any temperature and any open circuit voltage can be determined. Exemplarily, the ohmic internal resistance and / or polarization internal resistance at any temperature and any open circuit voltage can be determined.

[0244] See also Fig.15 In some embodiments, when the first parameter includes temperature, the above method of correcting the historical internal resistance data of the battery according to the fitting function between the first parameter of the battery and the historical internal resistance data after cleaning to determine the internal resistance data of the battery with respect to the first parameter may specifically include the following steps:

[0245] S1510. The electronic device performs function fitting on the first parameter of the battery and the historical internal resistance data after cleaning according to the Arrhenius formula.

[0246] The Arrhenius equation is the relationship between the rate constant of a chemical reaction and temperature. Specifically, the Arrhenius equation is:

[0247] R=a*e b / T (8)

[0248] Among them, R is the internal resistance, a and b are the unknowns to be fitted, e is a natural constant, and T is the temperature.

[0249] As an example, the fitting process is:

[0250] (1) Perform a first-order Taylor expansion on the above Arrhenius formula and convert it into a linear formula.

[0251] (2) Use the least squares method to solve a and b, thereby determining the fitting function and obtaining the fitting curve. For example, Fig.16 The fitting curve is shown.

[0252] S1520: The electronic device corrects historical internal resistance data of the battery according to the fitting function to determine internal resistance data of the battery with respect to the first parameter.

[0253] For example, according to Fig.16 The fitting curve shown can provide the internal resistance data of the battery at any temperature, that is, the internal resistance of the battery at any temperature.

[0254] In the above method for determining the internal resistance of the battery, when the first parameter includes temperature, the Arrhenius formula fitting function is used to correct the historical internal resistance data after cleaning, thereby improving the accuracy of the internal resistance data determined about the first parameter.

[0255] See also Fig.17 In some embodiments, the above-mentioned acquisition of historical data of the battery may specifically include the following steps:

[0256] S1710. The electronic device obtains first historical data of the battery in a first time period.

[0257] As an example, first historical data such as sampling time, temperature, voltage, current, state of charge, etc. within a first time period may be obtained from a battery management system.

[0258] S1720: The electronic device selects data within a second time period from the first historical data as historical data of the battery.

[0259] As an example, data within the second time period may be selected from the first historical data as the historical data of the battery.

[0260] As an example, the first time period is nearly a month, a quarter or a year. The second time period is the beginning time period, the middle time period or the end time period of the first time period. For example, the second time period is two weeks in the middle of nearly a month.

[0261] The above method for determining the internal resistance of the battery can realize cyclically iteratively determining the historical internal resistance data of the battery and cyclically iteratively determining the internal resistance data of the battery by cyclically acquiring the first historical data within the first time period, and selecting the data within the second time period as the historical data for calculating the historical internal resistance data of the battery, thereby improving the accuracy of determining the internal resistance of the battery.

[0262] In some embodiments, historical data of batteries sampled in the battery management system may be stored in a cloud server.

[0263] In some embodiments of the present application, a method for determining the internal resistance of a battery is provided, which may specifically include the following steps:

[0264] (1) The electronic device stores the historical data of the battery sampled in the battery management system in the cloud server;

[0265] (2) the electronic device cleans the historical data of the battery stored in the cloud server to obtain target historical data;

[0266] (3) The electronic device aggregates the target historical data to obtain aggregated historical data under different working conditions;

[0267] (4) establishing a mathematical relationship between the aggregated historical data and the historical internal resistance data based on the Thevenin equivalent circuit model;

[0268] (5) Convert the above mathematical relationship into a least squares relationship, and use the recursive least squares method with forgetting factor to perform parameter identification;

[0269] (6) Calculate the historical internal resistance data of the battery based on the identified parameters;

[0270] (7) Clean the historical internal resistance data of the battery;

[0271] (8) According to the Arrhenius formula, a function is fitted to the temperature of the battery and the historical internal resistance data after cleaning;

[0272] (9) The historical internal resistance data of the battery is corrected according to the fitting function to determine the internal resistance data of the battery with respect to temperature, thereby obtaining the internal resistance data of the battery at any temperature.

[0273] The above method for determining the internal resistance of a battery can use a sufficient amount of historical data to calculate the historical internal resistance data online, and by double cleaning the historical data and the calculated historical internal resistance data, the accuracy of the determined internal resistance data of the battery is higher.

[0274] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0275] In some embodiments of the present application, a device for determining the internal resistance of a battery is provided. The device for determining the internal resistance of a battery includes a module for executing the method steps in any of the above method embodiments.

[0276] The process of each module implementing its own function in the device for determining the internal resistance of a battery provided in the embodiment of the present application can be specifically referred to in the foregoing Figure 2 The description of the illustrated embodiment and other related method embodiments will not be repeated here.

[0277] The device for determining the internal resistance of a battery provided in the embodiment of the present application also has the above-mentioned beneficial effects, namely, it can utilize a sufficient amount of historical data to calculate the historical internal resistance data online, and by double cleaning the historical data and the calculated historical internal resistance data, the accuracy of the determined internal resistance data of the battery is higher.

[0278] The method for determining the internal resistance of a battery provided in the embodiment of the present application can be applied to devices such as battery management systems, mobile phones, desktop computers, notebooks, PDAs, and cloud servers. The embodiment of the present application does not impose any restrictions on the specific types of electronic devices.

[0279] Fig.18 Schematic diagram of the structure of an electronic device provided by an embodiment of the present application. Fig.18 As shown, the electronic device 18 of this embodiment includes: at least one processor 180 ( Fig.18 Only one is shown in the figure), a memory 181, wherein the memory 181 stores a computer program 182 that can be run on the processor 180. When the processor 180 executes the computer program 182, the steps in the above-mentioned method for determining the internal resistance of the battery are implemented, for example Figure 2 Steps S210 to S240 are shown.

[0280] The electronic device 18 may be, but is not limited to, a battery management system, a mobile phone, a desktop computer, a notebook, a PDA, a cloud server, etc. The electronic device may include, but is not limited to, a processor 180 and a memory 181. Those skilled in the art will appreciate that Fig.18It is only an example of the electronic device 18 and does not constitute a limitation of the electronic device 18. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device may also include an input sending device, a network access device, a bus, etc.

[0281] The processor 180 may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0282] In some embodiments, the memory 181 may be an internal storage unit of the electronic device 18, such as a hard disk or memory of the electronic device 18. The memory 181 may also be an external storage device of the electronic device 18, such as a plug-in 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 18. Further, the memory 181 may also include both an internal storage unit of the electronic device 18 and an external storage device. The memory 181 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program, etc. The memory 181 may also be used to temporarily store data that has been sent or is to be sent.

[0283] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.

[0284] An embodiment of the present application provides a computer program product. When the computer program product runs on an electronic device, the electronic device can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0285] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for determining the internal resistance of a battery, characterized in that: include: Get historical data of the battery; Determining historical internal resistance data of the battery according to historical data of the battery; Cleaning the historical internal resistance data of the battery; The historical internal resistance data of the battery is corrected according to the historical internal resistance data after cleaning to determine the internal resistance data of the battery.

2. The method according to claim 1, characterized in that: The determining, according to the historical data of the battery, the historical internal resistance data of the battery comprises: Cleaning the historical data of the battery to obtain target historical data; According to the target historical data, historical internal resistance data of the battery is determined.

3. The method according to claim 2, characterized in that The cleaning of the historical data of the battery to obtain target historical data includes: The historical data of the battery whose values ​​are outside a preset range are cleaned, so that the historical data of the battery whose values ​​are within the preset range are used as target historical data.

4. The method according to claim 3, characterized in that The cleaning of the historical data of the battery whose values ​​are outside the preset range, so as to use the historical data of the battery whose values ​​are within the preset range as the target historical data, includes: When the value of the historical data at the first sampling moment is outside the preset range, the historical data at the first sampling moment is replaced according to the value of the historical data at the previous sampling moment and the value of the historical data at the next sampling moment to obtain the target historical data.

5. The method according to any one of claims 2 to 4, characterized in that: The historical data of the battery includes at least one of voltage, current and temperature; The cleaning of the historical data of the battery to obtain target historical data includes: When the voltage, current and temperature at the first sampling moment are respectively the same as the voltage, current and temperature at the previous sampling moment, the voltage, current and temperature at the first sampling moment are cleaned to obtain target historical data.

6. The method according to any one of claims 2 to 5, characterized in that: The historical data of the battery includes a plurality of data segments; The cleaning of the historical data of the battery to obtain target historical data includes: Data segments whose data missing degree is greater than or equal to a first threshold value among the multiple data segments are cleaned to obtain target historical data.

7. The method according to claim 6, characterized in that A data segment includes at least one set of sampled data, and one sampling moment corresponds to a set of sampled data; The degree of data missing of a data segment is determined by the ratio of the number of abnormal data groups to the total number of groups of the at least one group of sampled data; Among them, for any group of sampling data, if the ratio of the number of abnormal data to the number of data in any group of sampling data is greater than or equal to a first ratio, then the any group of sampling data is the abnormal data group.

8. The method according to any one of claims 1 to 7, characterized in that: The determining, according to the historical data of the battery, the historical internal resistance data of the battery comprises: Determining a mathematical relationship between historical data of the battery and historical internal resistance data of the battery according to an equivalent circuit model of the battery; The historical internal resistance data of the battery is calculated according to the mathematical relationship and the historical data of the battery.

9. The method according to claim 8, characterized in that The calculating the historical internal resistance data of the battery according to the mathematical relationship and the historical data of the battery includes: Using a mathematical optimization modeling method to optimize the mathematical relationship to obtain an optimized model; performing parameter identification on the optimization model according to the historical data of the battery; According to the identified parameters, historical internal resistance data of the battery is calculated.

10. The method according to claim 9, characterized in that The parameter identification method is a recursive algorithm with a forgetting factor.

11. The method according to claim 9 or 10, characterized in that: The historical data of the battery includes at least N groups of sampling data, one group of sampling data corresponds to one sampling time, and N is an integer; N is determined by at least one of a convergence characteristic of the parameter identification method and a stable characteristic of the battery.

12. The method according to any one of claims 1 to 11, characterized in that: The determining, according to the historical data of the battery, the historical internal resistance data of the battery comprises: According to the historical data of the battery, historical internal resistance data of the battery under different operating conditions is determined.

13. The method according to claim 12, characterized in that Determining historical internal resistance data of the battery under different operating conditions according to the historical data of the battery includes: Aggregating the historical data of the battery to obtain the historical data of the battery under any working condition; According to the historical data of the battery under any of the operating conditions, the historical internal resistance data of the battery under any of the operating conditions is calculated.

14. The method according to any one of claims 1 to 13, characterized in that: The cleaning of the historical internal resistance data of the battery includes: Outliers in the historical internal resistance data of the battery are cleaned.

15. The method according to claim 14, characterized in that The cleaning of outliers in the historical internal resistance data of the battery includes: The outliers in the historical internal resistance data of the battery are cleaned by using statistical graphics.

16. The method according to any one of claims 1 to 15, characterized in that The method of correcting the historical internal resistance data of the battery according to the historical internal resistance data after cleaning to determine the internal resistance data of the battery includes: The historical internal resistance data of the battery is corrected according to a fitting function between the first parameter of the battery and the historical internal resistance data after cleaning to determine the internal resistance data of the battery with respect to the first parameter.

17. The method according to claim 16, characterized in that The first parameter includes at least one of temperature, open circuit voltage, state of charge, and state of health.

18. The method according to claim 17, characterized in that In the case where the first parameter includes temperature, the correcting the historical internal resistance data of the battery according to the fitting function between the first parameter of the battery and the historical internal resistance data after cleaning to determine the internal resistance data of the battery with respect to the first parameter includes: According to the Arrhenius formula, function fitting is performed on the first parameter of the battery and the historical internal resistance data after cleaning; The historical internal resistance data of the battery is corrected according to the fitting function to determine the internal resistance data of the battery with respect to the first parameter.

19. The method according to any one of claims 1 to 18, characterized in that The obtaining of historical data of the battery includes: Acquire first historical data of the battery in a first time period; Data within a second time period is selected from the first historical data as historical data of the battery, and the second time period is within the first time period.

20. A device for determining the internal resistance of a battery, characterized in that: Comprising a module for executing the method according to any one of claims 1 to 19.

21. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program, and when the program is executed by a processor, the method according to any one of claims 1 to 19 is implemented.

22. An electronic device, characterized in that: include: A memory, a processor, and a program stored in the memory and executable on the processor, wherein when the processor executes the program, the method according to any one of claims 1 to 19 is implemented.

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