Charging information estimation method, charging rate strategy data set optimization and selection method

Abstract

The present disclosure relates to a charging information estimation method, a charging rate strategy data set optimization and selection method, and the estimation method includes: obtaining a charging rate strategy data set and a charging temperature rise curve; determining a target charging rate according to the charging rate strategy data set and the battery temperature of the jth state of charge; determining a target charging time according to the target charging rate, the jth state of charge and the j+1th state of charge; determining an estimated temperature rise for charging the target charging time according to the reference charging rate according to the charging temperature rise curve, the battery temperature at the jth state of charge and the target charging time; determining a target temperature rise for charging the target charging time according to the target charging rate according to the estimated temperature rise and the target charging rate; determining the battery temperature at the j+1th state of charge according to the target temperature rise and the battery temperature at the jth state of charge. Thus, the charging time and battery temperature of any state of charge under any charging rate strategy data set can be quickly estimated.

Description

Technical Field

[0001] The present disclosure relates to the technical field of electric equipment, and in particular to a charging information estimation method, and a charging rate strategy data set optimization and selection method. Background Art

[0002] In the fields of new energy vehicles and electric motorcycles, the long charging time is one of the pain points of consumers. Improving charging efficiency and reducing consumers' waiting time have become one of the core competitiveness of new energy products. Therefore, in the process of battery pack development, it is necessary to evaluate the charging time according to the charging rate strategy data set (or charging map), so as to optimize the charging map in order to obtain a shorter charging time. The charging rate strategy data set includes different states of charge (SOC, State of Charge, used to reflect the remaining power of the battery) and reference charging rates at different battery temperatures (charging rate refers to the current value required for the battery to be charged to the rated capacity within a specified time).

[0003] It is known that the charging time of a battery pack is affected by temperature, SOC, and charging current. In particular, the battery temperature cannot be greater than the temperature limit of the battery pack. Different battery packs and different thermal management methods will cause different temperature rises in the battery. The charging current and the internal resistance of the battery cell will also change with the changes in SOC and temperature. Therefore, evaluating the charging and discharging time of a battery pack is a complex process.

[0004] The existing technology generally obtains the charging time and battery temperature under a certain charging rate strategy data set through physical measurement or three-dimensional thermal simulation, and then optimizes the charging rate strategy data set based on the measured or simulated charging time and battery temperature to obtain the optimal charging rate strategy data set. However, this process usually performs multiple physical measurements or three-dimensional thermal simulations on the charging rate strategy data set, which consumes a long time and the development efficiency of the charging rate strategy data set is low. Even if physical measurement is used, it is necessary to modify the relevant test software program, which requires a certain amount of cost, making the development cost of the charging rate strategy data set high.

[0005] Therefore, how to quickly estimate the battery pack charging time and battery temperature under any charging rate strategy data set needs to be solved urgently. Summary of the invention

[0006] In view of this, the present disclosure proposes a charging information estimation method, a charging rate strategy data set optimization and selection method, which can quickly estimate the charging time and battery temperature corresponding to any state of charge under any charging rate strategy data set, thereby helping to improve the development efficiency of the charging rate strategy data set.

[0007] According to a first aspect of the present disclosure, a method for estimating charging information of a battery pack is provided, comprising: obtaining a charging rate strategy data set of charging information to be estimated for a battery pack, and a charging temperature rise curve of the battery pack at a reference charging rate, wherein the charging information includes a charging time and a battery temperature, the charging rate strategy data set includes reference charging rates at different states of charge and different battery temperatures, and the charging temperature rise curve characterizes a changing relationship between battery temperature and charging time when constant current charging is performed according to the reference charging rate; for a jth state of charge to a j+1th state of charge between an initial state of charge and a termination state of charge of the battery pack, determining a target charging rate corresponding to a state of charge from a jth state of charge to a j+1th state of charge according to the charging rate strategy data set and the battery temperature of the battery pack at the jth state of charge, wherein 1≤j≤J, the first state of charge is the initial state of charge, the Jth state of charge is the termination state of charge, and the There are multiple increasing states of charge between the initial state of charge and the termination state of charge, and the battery temperature of the battery pack at the first state of charge is the actual temperature of the battery pack at the initial state of charge; according to the target charging rate, the jth state of charge and the j+1th state of charge, the target charging time from the jth state of charge to the j+1th state of charge is determined; according to the charging temperature rise curve, the battery temperature of the battery pack at the jth state of charge and the target charging time, the estimated temperature rise after charging from the jth state of charge at the reference charging rate for the target charging time is determined; according to the estimated temperature rise and the target charging rate, the target temperature rise after charging from the jth state of charge at the target charging rate for the target charging time is determined; according to the target temperature rise and the battery temperature of the battery pack at the jth state of charge, the battery temperature of the battery pack at the j+1th state of charge is determined.

[0008] In a first possible implementation manner of the first aspect, determining a target charging rate corresponding to the jth state of charge to the j+1th state of charge based on the charging rate strategy data set and the battery temperature of the battery pack at the jth state of charge includes: querying a reference charging rate corresponding to the jth state of charge and a reference charging rate corresponding to the j+1th state of charge from the charging rate strategy data set based on the battery temperature of the battery pack at the jth state of charge, the jth state of charge, and the j+1th state of charge; and determining an average value between the reference charging rate corresponding to the jth state of charge and the reference charging rate corresponding to the j+1th state of charge as the target charging rate corresponding to the jth state of charge to the j+1th state of charge.

[0009] In a second possible implementation of the first aspect, the estimated temperature rise after charging from the jth state of charge at the reference charging rate for the target charging time is determined based on the charging temperature rise curve, the battery temperature of the battery pack at the jth state of charge, and the target charging time, including: correcting the charging temperature rise curve according to the battery temperature of the battery pack at the jth state of charge to obtain a corrected target charging temperature rise curve; substituting the target charging time into the target charging temperature rise curve to obtain the estimated battery temperature after charging from the jth state of charge at the reference charging rate for the target charging time; and determining the difference between the estimated battery temperature and the battery temperature of the battery pack at the jth state of charge as the estimated temperature rise after charging from the jth state of charge at the reference charging rate for the target charging time.

[0010] In a second possible implementation manner of the first aspect, the charging temperature rise curve is corrected according to the battery temperature of the battery pack at the jth state of charge to obtain a corrected target charging temperature rise curve, including: substituting the battery temperature of the battery pack at the jth state of charge into the charging temperature rise curve to obtain a correction duration; and correcting the charging temperature rise curve using the correction duration to obtain a corrected target charging temperature rise curve.

[0011] In a third possible implementation of the first aspect, determining the target temperature rise after charging at the target charging rate for the target charging time from the jth state of charge according to the estimated temperature rise and the target charging rate includes: querying the first cell internal resistance corresponding to the battery pack from a cell internal resistance data set corresponding to the battery pack according to the reference charging rate, the jth state of charge and the battery temperature of the battery pack at the jth state of charge; the cell internal resistance data set includes the cell internal resistance of the battery pack at different charging rates, different states of charge and different battery temperatures; querying the second cell internal resistance corresponding to the battery pack from the cell internal resistance data set according to the target charging rate, the jth state of charge and the battery temperature of the battery pack at the jth state of charge; determining the target temperature rise after charging at the target charging rate for the target charging time from the jth state of charge according to the ratio of the second cell internal resistance to the first cell internal resistance, the target charging rate and the estimated temperature rise.

[0012] In a fourth possible implementation of the first aspect, the estimation method is to calculate the target charging time corresponding to each state of charge and the battery temperature of the battery pack at each state of charge from the initial state of charge, the initial state of charge includes a fully discharged state, and the terminal state of charge includes a fully charged state. The estimation method also includes: determining whether the battery temperature of the battery pack at the j+1th state of charge exceeds a preset temperature limit, and determining whether the j+1th state of charge reaches the terminal state of charge; when the battery temperature of the battery pack at the j+1th state of charge exceeds the preset temperature limit, or the j+1th state of charge has reached the terminal state of charge, accumulating multiple target charging times calculated segment by segment from the initial state of charge to the j+1th state of charge to obtain a total charging time from the initial state of charge to the j+1th state of charge.

[0013] According to a second aspect of the present disclosure, a method for optimizing a charging rate strategy data set is provided, which includes the estimation method described in the fourth possible implementation manner of the first aspect, and after obtaining the total charging time from the initial state of charge to the j+1th state of charge, the optimization method further includes: when the j+1th state of charge reaches the terminal state of charge, judging whether the total charging time to the j+1th state of charge is greater than a preset time threshold; when the total charging time is greater than the preset time threshold, optimizing the charging rate strategy data set, and re-executing the estimation method described in the fourth possible implementation manner of the first aspect using the optimized charging rate strategy data set, until the accumulated total charging time is less than or equal to the preset time threshold, so as to obtain a qualified charging rate strategy data set.

[0014] In a first possible implementation manner of the second aspect, the optimization method further includes: when the j+1th state of charge has not reached the termination state of charge, optimizing the charging rate strategy data set, and using the optimized charging rate strategy data set to re-execute the estimation method described in the fourth possible implementation manner of the first aspect, until the j+1th state of charge reaches the termination state of charge, executing the determination of whether the total charging time to the j+1th state of charge is greater than a preset time threshold.

[0015] According to the third aspect of the present disclosure, a method for selecting a charging rate strategy data set is provided, the selection method comprising: obtaining multiple charging rate strategy data sets to be selected; for the multiple charging rate strategy data sets, executing the estimation method described in the fourth possible implementation method of the first aspect to obtain the total charging time corresponding to a single charging rate strategy data set; and determining the charging rate strategy data set with the shortest total charging time as a qualified charging rate strategy data set.

[0016] According to a fourth aspect of the present disclosure, a battery pack charging information estimation device is provided, comprising: an acquisition module, used to acquire a charging rate strategy data set of charging information to be estimated for a battery pack, and a charging temperature rise curve of the battery pack at a reference charging rate, wherein the charging information includes a charging time and a battery temperature, the charging rate strategy data set includes reference charging rates at different states of charge and different battery temperatures, and the charging temperature rise curve represents a changing relationship between battery temperature and charging time when constant current charging is performed according to the reference charging rate; a charging rate determination module, used to determine a target charging rate corresponding to a jth state of charge to a j+1th state of charge between an initial state of charge and a termination state of charge of the battery pack according to the charging rate strategy data set and the battery temperature of the battery pack at the jth state of charge, wherein 1≤j≤J, the first state of charge is the initial state of charge, the Jth state of charge is the termination state of charge, and the initial state of charge and the termination state of charge are related to each other. The states include multiple increasing states of charge, the battery temperature of the battery pack at the first state of charge is the actual temperature of the battery pack at the initial state of charge; a charging time determination module, used to determine the target charging time from the jth state of charge to the j+1th state of charge according to the target charging rate, the jth state of charge and the j+1th state of charge; an estimated temperature rise determination module, used to determine the estimated temperature rise after charging from the jth state of charge at the reference charging rate for the target charging time according to the charging temperature rise curve, the battery temperature of the battery pack at the jth state of charge and the target charging time; a target temperature rise determination module, used to determine the target temperature rise after charging from the jth state of charge at the target charging rate for the target charging time according to the estimated temperature rise and the target charging rate; a battery temperature determination module, used to determine the battery temperature of the battery pack at the j+1th state of charge according to the target temperature rise and the battery temperature of the battery pack at the jth state of charge.

[0017] In a possible practice of the fourth aspect, the estimation device calculates the target charging time corresponding to each charge state and the battery temperature of the battery pack at each charge state from the initial charge state, the initial charge state includes a fully discharged state, and the terminal charge state includes a fully charged state. The estimation device also includes: a judgment module, used to judge whether the battery temperature of the battery pack at the j+1th charge state exceeds a preset temperature limit, and to judge whether the j+1th charge state reaches the terminal charge state; a total time determination module, used to accumulate multiple target charging times calculated segment by segment from the initial charge state to the j+1th charge state when the battery temperature of the battery pack at the j+1th charge state exceeds the preset temperature limit, or the j+1th charge state has reached the terminal charge state, to obtain a total charging time from the initial charge state to the j+1th charge state.

[0018] According to a fifth aspect of the present disclosure, a charging rate strategy data set optimization device is provided, which includes the estimation device described in a possible implementation manner of the fourth aspect, and after obtaining the total charging time from the initial state of charge to the j+1th state of charge, the optimization device also includes: a time judgment module, which is used to judge whether the total charging time from the j+1th state of charge to the j+1th state of charge is greater than a preset time threshold when the j+1th state of charge reaches the terminal state of charge; an optimization module, which is used to optimize the charging rate strategy data set when the total charging time is greater than the preset time threshold, and re-execute the estimation device described in a possible implementation manner of the fourth aspect using the optimized charging rate strategy data set, until the accumulated total charging time is less than or equal to the preset time threshold, so as to obtain a qualified charging rate strategy data set.

[0019] According to a sixth aspect of the present disclosure, a charging rate strategy data set selection device is provided, the selection device comprising: a data set acquisition module, used to obtain multiple charging rate strategy data sets to be selected; an execution module, used to execute an estimation device of a possible implementation method of the fourth aspect for multiple charging rate strategy data sets, to obtain the total charging time corresponding to a single charging rate strategy data set; a selection module, used to determine the charging rate strategy data set with the smallest total charging time as a qualified charging rate strategy data set.

[0020] According to a seventh aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to implement the above method when executing the instructions stored in the memory.

[0021] According to an eighth aspect of the present disclosure, a non-volatile computer-readable storage medium is provided, on which computer program instructions are stored, wherein the computer program instructions implement the above method when executed by a processor.

[0022] According to the ninth aspect of the present disclosure, a computer program product is provided, comprising a computer-readable code, or a non-volatile computer-readable storage medium carrying the computer-readable code, and when the computer-readable code runs in a processor of an electronic device, the processor in the electronic device executes the above method.

[0023] According to various aspects of the present disclosure, by utilizing the charging rate strategy data set to determine the target charging rate and target charging time corresponding to any state of charge, and then combining the charging temperature rise curve under the reference charging rate, the charging temperature under any state of charge can be quickly determined, that is, the charging time and battery temperature corresponding to any state of charge under any charging rate strategy data set can be quickly calculated. Compared with the method of performing physical testing or three-dimensional thermal simulation modeling, the calculation efficiency of charging information can be improved, which is beneficial to improving the development efficiency of the charging rate strategy data set and reducing development costs.

[0024] Further features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.

[0026] Figure 1 A flow chart of a method for estimating charging information of a battery pack according to an embodiment of the present disclosure is shown.

[0027] Figure 2 A flow chart of a method for estimating charging information of a battery pack according to an embodiment of the present disclosure is shown.

[0028] Figure 3 A flowchart of a charging rate strategy dataset optimization method according to an embodiment of the present disclosure is shown.

[0029] Figure 4 A block diagram of a battery pack charging information estimation device according to an embodiment of the present disclosure is shown.

[0030] Figure 5 A block diagram of a battery pack charging information estimation device according to an embodiment of the present disclosure is shown.

[0031] Figure 6 A block diagram of an electronic device 1900 according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0032] Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise specified.

[0033] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0034] The term "and / or" herein 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 term "at least one" herein represents any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C can represent including any one or more elements selected from the set consisting of A, B, and C.

[0035] It should be understood that the terms "first", "second", etc. in the claims, specifications and drawings of the present disclosure are used to distinguish different objects rather than to describe a specific order. The terms "include" and "comprise" used in the specifications and claims of the present disclosure indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or their collections.

[0036] In addition, in order to better illustrate the present disclosure, numerous specific details are given in the following specific embodiments. It should be understood by those skilled in the art that the present disclosure can also be implemented without certain specific details. In some examples, methods, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the subject matter of the present disclosure.

[0037] In practical applications, the charging information estimation method, charging rate strategy data set optimization and selection method of the embodiment of the present disclosure can be deployed on various terminal devices through software or hardware modification. The terminal device involved in the embodiment of the present disclosure may refer to a device with a wireless connection function and / or a wired connection function. The wireless connection function refers to the ability to connect to other devices through wireless connection methods such as wifi and Bluetooth. The terminal device involved in the embodiment of the present disclosure can also communicate with other devices through a wired connection function. The terminal device involved in the embodiment of the present disclosure can be a touch screen, a non-touch screen, or a screen-free terminal device. The touch screen can be controlled by clicking and sliding on the display screen with a finger or a stylus. The non-touch screen device can be connected to an input device such as a mouse, keyboard, touch panel, etc., and the terminal device can be controlled through the input device. For example, the device without a screen can be a Bluetooth speaker without a screen. For example, the terminal device of the present application may include but is not limited to user equipment (UE), mobile device, user terminal, terminal, handheld device, tablet computer, laptop computer, PDA, computing device, etc.

[0038] The charging information estimation method, charging rate strategy data set optimization and selection method of the embodiment of the present disclosure can also be deployed on a server, which can be located in the cloud or locally, and can be a physical device or a virtual device, such as a virtual machine, a container, etc., with a wireless communication function, wherein the wireless communication function can be set in the chip (system) or other parts or components of the server. It can refer to a device with a wireless connection function, and the wireless connection function refers to the ability to connect to other servers or terminal devices through wireless connection methods such as Wi-Fi and Bluetooth. The server involved in the embodiment of the present disclosure may also have the function of communicating through a wired connection. For example, the server can receive the charging rate strategy data set sent by the above-mentioned terminal device, and the server executes the charging information estimation method, charging rate strategy data set optimization method or selection method of the embodiment of the present disclosure according to the charging rate strategy data set, obtains charging information, a qualified charging rate strategy data set and returns it to the terminal device, so as to be displayed to the user in the terminal device.

[0039] Figure 1 A flow chart of a battery pack charging information estimation method according to an embodiment of the present disclosure is shown. The estimation method can be applied to electronic devices such as the above-mentioned terminal device or server, and the present disclosure embodiment does not limit this. Figure 1 As shown, the charging information estimation method includes: steps S11 to S16.

[0040] In step S11 , a charging rate strategy data set of charging information to be estimated for a battery pack and a charging temperature rise curve of the battery pack at a reference charging rate are obtained.

[0041] Among them, the charging information includes charging time and battery temperature, the charging rate strategy data set includes reference charging rates under different charge states and different battery temperatures, and the charging temperature rise curve represents the changing relationship between battery temperature and charging time when constant current charging is performed according to the benchmark charging rate.

[0042] It should be understood that in actual scenarios, users can customize the charging rate strategy data set of the cells in the battery pack according to actual needs, or customize the charging rate strategy data set of the charging information to be estimated. The present disclosure embodiment does not limit the form and content of the charging rate strategy data set. For example, Table 1 shows a charging rate strategy data set for a battery pack cell provided by the present disclosure embodiment:

[0043] Table 1 Charging rate strategy dataset

[0044]

[0045] Among them, SOC0 can represent the initial state of charge, which can be the state of charge in a fully discharged state, that is, the state of charge is 0%, SOC m It can represent the end state of charge, which can be the state of charge in a fully charged state, that is, the state of charge is 100%, and the SOC can be divided into m equal parts from 0% to 100%, for example, it can be divided into multiple parts in increments of 5% or 10%; it should be understood that SOC m It can also represent any state of charge in an incompletely charged state, indicating a range from SOC0 to SOC m m equal parts between. rn The battery temperature represents the reference temperature, which can be divided from low to high within the operating temperature range of the battery pack. The operating temperature range includes the minimum temperature limit to the maximum temperature limit allowed by the battery pack. For example, the operating temperature range can be divided into 5°C or 10°C increments from -5°C to 50°C; C nm Represents the battery temperature T rn , State of Charge SOC m The charging rate below is shown in the figure, and the other values ​​are deduced accordingly.

[0046] In practical applications, the charging temperature rise curve of the battery pack at the benchmark charging rate can be obtained through actual measurement or three-dimensional thermal simulation. For example, the temperature rise data obtained by constant current charging of the battery pack at the benchmark charging rate can be tested through actual measurement or three-dimensional thermal simulation, and even the temperature rise data of an approximate battery pack can be used as a reference. Then, the charging temperature rise curve can be fitted based on the temperature rise data, wherein the temperature rise data represents the data on the change of battery temperature with charging time. The benchmark charging rate can be any charging rate. For example, a 1C rate can be used as the benchmark charging rate, so that the charging temperature rise curve at a 1C rate can be fitted based on the temperature rise data of constant current charging at a 1C rate.

[0047] It should be understood that those skilled in the art can use any curve function known in the art to fit the charging temperature rise curve, and the embodiments of the present disclosure are not limited to this. For example, a quadratic curve shown in formula (1) can be fitted based on the temperature rise data as the charging temperature rise curve:

[0048] T=at 2 +bt+T0 (1)

[0049] Among them, t represents the charging time as the independent variable, in seconds, T represents the battery temperature as the dependent variable, T0 represents the initial temperature, a and b are fitting coefficients, and the initial temperature T0 represents the actual temperature (or ambient temperature) of the battery pack before the battery pack starts constant current charging according to the benchmark charging rate, that is, the starting temperature when the constant current charging test is performed to obtain the charging temperature rise curve. For example, if the charging temperature rise curve is measured at a charging starting temperature of 25°C, then the initial temperature is 25°C. If the charging temperature rise curve is measured at a temperature of 40°C when charging starts, then the initial temperature is 40°C.

[0050] In step S12, for the jth state of charge to the j+1th state of charge between the initial state of charge and the final state of charge of the battery pack, the target charging rate corresponding to the jth state of charge to the j+1th state of charge is determined according to the charging rate strategy data set and the battery temperature of the battery pack at the jth state of charge.

[0051] Among them, 1≤j≤J, the first state of charge is the initial state of charge, the Jth state of charge is the final state of charge, there are multiple increasing states of charge between the initial state of charge and the final state of charge, and the battery temperature of the battery pack at the first state of charge is the actual temperature of the battery pack at the initial state of charge.

[0052] Among them, the termination state of charge may include a fully charged state of 100% of the battery pack, or any state of charge higher than the initial state of charge, such as 80%, 90%, etc.; the initial state of charge may include a fully discharged state of 0%, or any incomplete state of charge, such as 10%, 20%, etc., which is not limited by the embodiments of the present disclosure. In practical applications, the actual temperature of the battery pack at the initial state of charge can be measured by a temperature sensor. For example, if the user needs to estimate the charging information of the battery pack from 10% SOC to 80% SOC at the initial state of charge of 25°C, the actual temperature of the battery pack at the initial state of charge refers to the temperature of 25°C before charging starts at 10% SOC. At this time, the current temperature of the battery pack can be measured by the temperature sensor to be 25°C, and the current ambient temperature is also 25°C; of course, the user may also require to estimate the charging information at 45°C, then the actual temperature of the battery pack at the initial state of charge is 45°C, which is not limited by the embodiments of the present disclosure.

[0053] In practical applications, a plurality of increasing states of charge may be divided between the initial state of charge and the final state of charge according to the state of charge division unit (e.g., every 5% or 10%) in the charging rate strategy data set, and the jth state of charge to the j+1th state of charge may be any state of charge between the initial state of charge and the final state of charge, for example, any state of charge between 10% and 100%, between 10% and 20%, between 20% and 30%, ..., between 90% and 100%.

[0054] It should be understood that the estimation method of the embodiment of the present disclosure can calculate the charging information from the jth state of charge to the j+1th state of charge step by step starting from the initial state of charge. Thus, the battery temperature of the battery pack at the jth state of charge can be determined based on the battery temperature of the battery pack at the j-1th state of charge to the jth state of charge. The battery temperature estimation process will be introduced in detail below and will not be elaborated here.

[0055] In a possible implementation, when the battery temperature and the jth state of charge of the battery pack are known, the reference charging rate corresponding to the jth state of charge can be queried from the above charging rate strategy data set as the target charging rate corresponding to the jth state of charge to the j+1th state of charge. For example, for the charging rate strategy data set shown in Table 1, if the battery temperature of the battery pack at the jth state of charge is T r1 , the jth state of charge is SOC3, then the reference charging rate corresponding to the jth state of charge SOC3 is obtained by querying Table 1 as C 13 .

[0056] Considering that the battery temperature T of the battery pack at the jth state of charge i Maybe in T riWith T ri+1 Between, that is, T ri ≤T i <T ri+1 , so that directly using the reference charging rate corresponding to the j-th state of charge as the target charging rate is not accurate enough. Therefore, in a possible implementation, the above step S12, according to the charging rate strategy data set and the battery temperature of the battery pack at the j-th state of charge, determines the target charging rate corresponding to the state of charge from the j-th state of charge to the j+1-th state of charge, which may include:

[0057] According to the battery temperature of the battery pack at the jth state of charge, the jth state of charge and the j+1th state of charge, query the reference charging rate corresponding to the jth state of charge and the reference charging rate corresponding to the j+1th state of charge from the charging rate strategy data set;

[0058] An average value between a reference charging rate corresponding to the jth state of charge and a reference charging rate corresponding to the j+1th state of charge is determined as a target charging rate corresponding to from the jth state of charge to the j+1th state of charge.

[0059] It should be understood that after knowing the battery temperature, jth state of charge and j+1th state of charge of the battery pack at the jth state of charge, the reference charging rate corresponding to the jth state of charge and the reference charging rate corresponding to the j+1th state of charge can be queried from the charging rate strategy data set. Assuming that the battery temperature T i The reference charging rate corresponding to the jth state of charge queried below is expressed as C ij , and the reference charge rate corresponding to the jth state of charge is expressed as C i(j+1) , then the target charging rate C corresponding to the jth state of charge to the j+1th state of charge i It can be expressed as formula (2):

[0060]

[0061] It should be understood that for any state of charge between the initial state of charge and the final state of charge, the target charging rate corresponding to any state of charge can be obtained according to the target charging rate calculation method shown in the above formula (2).

[0062] In step S13 , a target charging time for charging from the jth state of charge to the j+1th state of charge is determined according to the target charging rate, the jth state of charge, and the j+1th state of charge.

[0063] In a possible implementation, the charging time calculation method shown in formula (3) can be used to determine the target charging time from the jth state of charge to the j+1th state of charge according to the target charging rate, the jth state of charge and the j+1th state of charge:

[0064]

[0065] Among them, t i represents the target charging time from the jth state of charge to the j+1th state of charge, C i represents the target charging rate from the jth state of charge to the j+1th state of charge, SOC j+1 Represents the j+1th state of charge, SOC j Represents the jth state of charge. The unit of the target charging time calculated by formula (3) is seconds, so "3600" is used to unify the units. It should be understood that if other time units are used, other values ​​can be used to unify the units, and the embodiments of the present disclosure are not limited to this.

[0066] Based on the above formula (3), according to the target charging rate, the jth state of charge and the j+1th state of charge, determining the target charging time from the jth state of charge to the j+1th state of charge can include: determining the target charging time from the jth state of charge to the j+1th state of charge according to the product of the difference between the j+1th state of charge and the jth state of charge and the target charging rate.

[0067] It should be understood that the method for determining the target charging time shown in the above formula (3) is a possible implementation method provided by the embodiment of the present disclosure. In fact, those skilled in the art can, under the guidance of the embodiment of the present disclosure, independently design a method for calculating the target charging time achieved according to the target charging rate, the jth state of charge and the j+1th state of charge, and the embodiment of the present disclosure does not limit this.

[0068] In step S14 , the estimated temperature rise after charging at the jth state of charge at the reference charging rate for the target charging time is determined according to the charging temperature rise curve, the battery temperature of the battery pack at the jth state of charge, and the target charging time.

[0069] As described above, the charging temperature rise curve shows the relationship between the battery temperature and the charging time when constant current charging is performed according to the reference charging rate. Therefore, in a possible implementation, according to the charging temperature rise curve, the battery temperature of the battery pack at the jth state of charge, and the target charging time, determining the estimated temperature rise after charging at the reference charging rate for the target charging time from the jth state of charge may include:

[0070] Correcting the charging temperature rise curve according to the battery temperature of the battery pack at the jth state of charge to obtain a corrected target charging temperature rise curve;

[0071] Substituting the target charging time into the target charging temperature rise curve, the estimated battery temperature after charging at the reference charging rate from the jth state of charge for the target charging time is obtained;

[0072] The difference between the estimated battery temperature and the battery temperature of the battery pack at the jth state of charge is determined as the estimated temperature rise after charging for a target time at a reference charging rate from the jth state of charge.

[0073] As described above, the charging temperature rise curve is constructed based on the temperature rise data obtained by constant current charging at the reference charging rate and the actual temperature T0 of the battery pack before constant current charging at the reference charging rate. The battery temperature of the battery pack at the jth state of charge may be different from the actual temperature of the battery pack before constant current charging at the reference charging rate. Therefore, when using the charging temperature rise curve to calculate the estimated temperature rise, the charging temperature rise curve can be first corrected according to the battery temperature of the battery pack at the jth state of charge, so as to correct the charging temperature rise curve to a target charging temperature rise curve with the battery temperature of the battery pack at the jth state of charge as the starting temperature, so that the target charging temperature rise curve can be used to accurately calculate the estimated battery temperature after charging for the target charging time at the reference charging rate from the jth state of charge.

[0074] In a possible implementation, the above-mentioned correction of the charging temperature rise curve according to the battery temperature of the battery pack at the jth state of charge to obtain the corrected target charging temperature rise curve may include: substituting the battery temperature of the battery pack at the jth state of charge into the charging temperature rise curve to obtain the correction time; and correcting the charging temperature rise curve using the correction time to obtain the corrected target charging temperature rise curve. In this way, the target charging temperature rise curve can be a curve constructed with the battery temperature of the battery pack at the jth state of charge as the starting temperature, which is conducive to obtaining an accurate estimated battery temperature.

[0075] For example, the charging temperature rise curve shown in the above formula (1) is used as an example to introduce the correction process of the charging temperature rise curve, including: firstly, the battery temperature T of the battery pack at the jth state of charge is calculated. i (that is, the initial temperature of the battery pack at the jth state of charge) is substituted into formula (1), that is, T i =at 2 +bt+T0, solve for T i =at 2 +bt+T0 can be calculated to get T i The corresponding correction time t0, and then the charging temperature rise curve shown in formula (1) can be corrected according to the correction time t0 to obtain the corrected target charging temperature rise curve shown in formula (4), that is, the battery temperature T based on the battery pack at the jth state of charge is obtained. i Target charging temperature rise curve at the benchmark charging rate:

[0076] T * =a(t+t0) 2+b(t+t0)+T0 (4)

[0077] Then, the target charging time t from the jth state of charge to the j+1th state of charge can be calculated as i Substituting the target charging temperature rise curve shown in the above formula (4) into the target charging time t from the jth state of charge according to the reference charging rate, the target charging time t i The estimated battery temperature T i * T i * =a(t i +t0) 2 +b(t i +t0)+T0.

[0078] After obtaining the above estimated battery temperature T i * After that, the estimated battery temperature T can be calculated i * and the battery temperature T of the battery pack at the jth state of charge i The difference between them gives ΔT * =T i * -T i , that is, the estimated temperature rise after charging for the target charging time at the reference charging rate from the jth state of charge is ΔT * .

[0079] In step S15 , a target temperature rise after charging at the target charging rate for a target charging time from the j-th state of charge is determined based on the estimated temperature rise and the target charging rate.

[0080] It can be seen that the heat formula is: Q = c q m ΔT = I 2 ·R·t; where Q represents heat, the unit is joule J; c q is the specific heat capacity, in units of joules J / (kg. Celsius °C); m represents mass, in units of kilograms kg; ΔT is the temperature rise, in units of Celsius °C; I is the current, in units of amperes A, R is the internal resistance, in units of ohms Ω; t is the duration, in units of seconds s. Furthermore, according to the above heat formula, formula (5) can be derived:

[0081]

[0082] Where, ΔT i Represents charging from the jth state of charge according to the target charging rate C i Charging target charging time t i Target temperature rise after ΔT *represents the estimated temperature rise after charging at the reference charging rate C0 for the target charging time from the jth state of charge; I i represents the charging current at the target charging rate; I0 represents the charging current at the reference charging rate; R i Represented in C i Ratio, SOC is SOC j , temperature is T i The internal resistance of the battery cell under C0; R0 represents the C0 rate, SOC is SOC j , temperature is T i The internal resistance of the battery cell under i The ratio to R0.

[0083] In practical applications, R i R0 can be obtained by querying the cell internal resistance data set corresponding to the battery pack (also known as the cell internal resistance Map), where the cell internal resistance data set includes the cell internal resistance of the battery pack at different charging rates, different states of charge, and different battery temperatures. If the corresponding cell internal resistance value is not found in the cell internal resistance data set, it can be obtained by interpolation through adjacent internal resistance values.

[0084] It should be understood that the internal resistance of the battery cells in the battery pack is fixed and known, so the battery cell internal resistance data set corresponding to the battery pack can be obtained through experimental testing. The embodiments of the present disclosure do not limit the acquisition method and expression form of the battery cell internal resistance data set. Among them, the battery cell internal resistance data set can be a three-dimensional table data, including at least one battery cell internal resistance data at a low charging rate and one at a high charging rate. For example, the battery cell internal resistance data at 1C rate and 4C rate can be tested to obtain a resistance core data table, and the internal resistance values ​​at different charging rates between 1C rate and 4C rate can be obtained by interpolation. By way of example, Table 2 shows the battery cell internal resistance data set of a battery pack cell at a certain charging rate.

[0085] Table 2 Cell internal resistance data set at a certain charging rate

[0086]

[0087] Among them, R cnm Represents a charge ratio of c and a battery temperature of T rn 、SOC is SOC m The internal resistance of the battery cell at this time, and other values ​​are similarly deduced.

[0088] Furthermore, based on the above formula (5), the target temperature rise determination method shown in formula (6) can be obtained:

[0089]

[0090] Based on the above formula (6), the above determination of the target temperature rise after charging at the target charging rate for the target charging time from the j-th state of charge according to the estimated temperature rise and the target charging rate may include:

[0091] According to the reference charging rate, the jth state of charge, and the battery temperature of the battery pack at the jth state of charge, query the first battery cell internal resistance corresponding to the battery pack from the battery cell internal resistance data set corresponding to the battery pack; the battery cell internal resistance data set includes the battery cell internal resistance of the battery pack at different charging rates, different states of charge, and different battery temperatures;

[0092] According to the target charging rate, the jth state of charge, and the battery temperature of the battery pack at the jth state of charge, query the second cell internal resistance corresponding to the battery pack from the cell internal resistance data set;

[0093] The target temperature rise after charging at the target charging rate for the target charging time from the jth state of charge is determined according to the ratio of the second battery cell internal resistance to the first battery cell internal resistance, the target charging rate, and the estimated temperature rise.

[0094] The above target temperature rise determination process can be briefly described as follows: first, query the first cell internal resistance R0 of the battery pack at the reference charge rate, the jth state of charge, and the battery temperature of the battery pack at the jth state of charge from the cell internal resistance data set, and query the second cell internal resistance R0 of the battery pack at the target charge rate, the jth state of charge, and the battery temperature of the battery pack at the jth state of charge. i ; Then calculate the internal resistance R of the second battery cell i The ratio α between the internal resistance R0 of the first battery cell and the square value of the jth state of charge Ratio α and estimated temperature rise ΔT * Multiply them to get the target temperature rise ΔT after charging at the target charging rate and target charging time. i .

[0095] In step S16 , the battery temperature of the battery pack at the j+1th state of charge is determined according to the target temperature rise and the battery temperature of the battery pack at the jth state of charge.

[0096] It can be understood that the target temperature rise ΔT after charging the target charging time at the target charging rate from the jth state of charge is known. i And the battery temperature T of the battery pack at the jth state of charge i After that, the battery temperature T i and target temperature rise ΔT i Add together to get the battery temperature T of the battery pack at the j+1th state of charge i+1 , that is, T i+1 =T i +ΔT i .

[0097] According to the estimation method of the embodiment of the present disclosure, the target charging rate and target charging time corresponding to any state of charge are determined by utilizing the charging rate strategy data set, and then the charging temperature under any state of charge can be quickly determined in combination with the charging temperature rise curve under the reference charging rate. That is, the charging time and battery temperature corresponding to any state of charge under any charging rate strategy data set can be quickly calculated. Compared with the method of performing physical testing or three-dimensional thermal simulation modeling, the calculation efficiency of charging information can be improved, which is beneficial to improving the development efficiency of the charging rate strategy data set and reducing development costs.

[0098] In actual applications, after obtaining the battery temperature of the battery pack at the j+1th state of charge, the target charging time from the j+1th state of charge to the j+2th state of charge and the battery temperature of the battery pack at the j+2th state of charge can be calculated based on the battery temperature of the battery pack at the j+1th state of charge, with reference to the above steps S12 to S16, until the calculated battery temperature reaches the preset temperature limit, or the state of charge reaches the termination state of charge; wherein the preset temperature limit can be understood as the maximum battery temperature allowed by the battery pack. That is, the estimation method of the embodiment of the present disclosure can be to calculate the target charging time corresponding to each state of charge and the battery temperature of the battery pack at each state of charge segment by segment from the initial state of charge (such as a fully discharged state) to the final state of charge (such as a fully charged state), and then the total charging time corresponding to each state of charge segment and the battery temperature of the battery pack at each state of charge can be used to calculate the total charging time according to the above charging rate strategy data set, and then the total charging time can be used to optimize the above charging rate strategy data set to obtain a charging rate strategy data set that meets the requirements. Therefore, in a possible implementation, if Figure 2 As shown, the estimation method may further include:

[0099] Step S17, determining whether the battery temperature of the battery pack at the j+1th state of charge exceeds a preset temperature limit (i.e., whether it is greater than or equal to the preset temperature limit), and determining whether the j+1th state of charge reaches a termination state of charge (i.e., whether it is equal to the termination state of charge);

[0100] Step S18, when the battery temperature of the battery pack at the j+1th state of charge exceeds the preset temperature limit, or the j+1th state of charge has reached the terminal state of charge, multiple target charging times calculated segment by segment from the initial state of charge to the j+1th state of charge are accumulated to obtain the total charging time from the initial state of charge to the j+1th state of charge.

[0101] It should be understood that it is also possible that the battery temperature of the battery pack at the j+1th state of charge does not exceed the preset temperature limit (that is, is less than the preset temperature limit) and the j+1th state of charge does not reach the termination state of charge (that is, the j+1th state of charge is less than the termination state of charge). In this case, go to the above steps S12 to S16 to calculate the target charging time and battery temperature corresponding to the next SOC segment until the battery temperature exceeds the preset temperature limit or the state of charge reaches the termination state of charge.

[0102] The calculation process of the above total charging time can be briefly described as follows: If T i+1 ≥T limit or SOC j+1 =SOC m , the calculation is terminated, and the total charging time is the cumulative value of the target charging time of each segment, t total =t1+t2+t3+t4+……+t i , represents the target charging time t1 corresponding to the first state of charge to the second state of charge accumulated to the target charging time corresponding to the jth state of charge to the j+1th state of charge, to obtain the total charging time; if T i+1 <T limit or SOC j+1 <SOC m , then go to the above steps S12 to S16 to calculate the target charging time and battery temperature corresponding to the next SOC segment until T is met. i+1 ≥T limit or SOC j+1 =SOC m , total output charging time t total .

[0103] Based on the above total charging time, the present disclosure also provides the following Figure 3 A charging rate strategy data set optimization method is shown, which includes Figure 2 The estimation method shown is Figure 3 As shown, after obtaining the total charging time from the initial state of charge to the j+1th state of charge, the optimization method further includes:

[0104] Step S19, when the j+1th state of charge reaches the termination state of charge, determining whether the total charging time to the j+1th state of charge is greater than a preset time threshold;

[0105] Step S20: When the total charging time is greater than the preset time threshold, the charging rate strategy data set is optimized, and the charging rate strategy data set is used to re-execute the charging rate strategy data set. Figure 2 The estimation method shown is used until the accumulated total charging time is less than or equal to the preset time threshold, thereby obtaining a qualified charging rate strategy data set.

[0106] Among them, the preset time threshold can be a time customized according to actual needs. For example, if the user requires the battery pack to be charged from the initial state of charge to the final state of charge within 15 minutes, the preset time threshold can be 15 minutes, and the embodiments of the present disclosure are not limited to this. Therefore, if the total charging time calculated according to the charging rate strategy data set is less than or equal to the preset time threshold, the charging rate strategy data set is considered to be qualified, or meets the needs; if the total charging time calculated according to the charging rate strategy data set is greater than the preset time threshold, the charging rate strategy data set is considered to be unqualified, or does not meet the needs, and then the unqualified charging rate strategy data set needs to be optimized, and then the optimized charging rate strategy data set is used to re-execute. Figure 2 The estimation method shown is used until the accumulated total charging time is less than or equal to the preset time threshold, thereby obtaining a qualified charging rate strategy data set.

[0107] In practical applications, technicians in this field can customize the optimization strategy according to actual needs, and optimize the charging rate strategy data set according to the customized optimization strategy. The embodiment of this disclosure does not limit the optimization strategy of the charging rate. For example, because the charging rate is high, the result is that the charging time is reduced, but the temperature will rise too quickly, resulting in too high battery temperature. The two are mutually exclusive and need to be constantly adjusted and tried to find the best balance point; therefore, if the margin of charging temperature rise is relatively large, you can try to increase the charging rate of the low rate segment, so as to further shorten the charging time, until the charging temperature rise (or battery temperature) reaches the limit, so as to obtain the shortest charging time; if the margin of charging time is relatively large, you can try to reduce the charging rate of the high rate segment, so as to control the temperature rise rate.

[0108] It should be understood that through Figure 2 The total charging time obtained by the estimation method shown may be T i+1 ≥T limit But SOC j+1 <SOC m In this case, it can be considered that the charging rate strategy data set is unqualified, or does not meet the requirements. Therefore, Figure 3 As shown, in the case that the j+1th state of charge does not reach the final state of charge, step S20 is also performed to optimize the charging rate strategy data set, and the optimized charging rate strategy data set is used to re-execute Figure 2 The estimation method shown in the figure, after the j+1th state of charge reaches the termination state of charge, step S19 is executed to determine whether the total charging time to charge to the j+1th state of charge is greater than a preset time threshold.

[0109] That is, the above Figure 3The optimization process shown can be briefly described as Figure 2 After the total charging time is obtained by the estimation method shown, the SOC j+1 Does it meet SOC? j+1 =SOC m If not, re-optimize the charging rate strategy data set; if SOC j+1 =SOC m , then further determine t total ≤t limit , that is, whether the total charging time is less than the preset time threshold t limit If t total ≤t limit , then the current charging rate strategy data set meets the requirements; if t total >t limit , the current charging rate strategy data set does not meet the requirements, and it is necessary to re-optimize the charging rate strategy data set, that is, to re-perform the above steps S12 to S18 until a qualified charging rate strategy data set is obtained.

[0110] In practical applications, after obtaining a qualified charging rate strategy data set, physical measurement or three-dimensional thermal simulation technology can be used to verify the qualified charging rate strategy data set to improve the optimization efficiency and data accuracy of the charging rate strategy data set. In this way, compared with the prior art method of directly using physical measurement or three-dimensional thermal simulation technology to optimize the charging rate strategy data set, the optimization method of the embodiment of the present disclosure can reduce the number of physical measurements or three-dimensional thermal simulations, shorten the optimization time, and reduce development costs.

[0111] According to the above-mentioned optimization method of the embodiment of the present disclosure, the charging rate strategy data set can be efficiently optimized to quickly obtain a qualified charging rate strategy data set that meets the needs, which is conducive to reducing the development cost of the charging rate strategy data set and shortening the development time.

[0112] In actual applications, repeat steps 1 to 5 for different charging rate strategies, and select the charging rate strategy with the shortest total charging time as the optimal charging rate strategy.

[0113] based on Figure 2 The estimation method shown in the figure, the embodiment of the present disclosure also provides a charging rate strategy data set selection method, the selection method includes:

[0114] Step S21, obtaining multiple charging rate strategy data sets to be selected;

[0115] Step S22: for multiple charging rate strategy data sets, execute Figure 2 The estimation method shown is used to obtain the total charging time corresponding to a single charging rate strategy data set;

[0116] Step S23: determining the charging rate strategy data set with the shortest total charging time as a qualified charging rate strategy data set.

[0117] The above selection method can be briefly described as repeating the above for different charging rate strategies. Figure 2 Steps S11 to S18 are shown to obtain the total charging time corresponding to each charging rate strategy data set, and then the charging rate strategy with the shortest total charging time can be selected as the optimal charging rate strategy.

[0118] As mentioned above, through Figure 2 The total charging time obtained by the estimation method shown may be T i+1 ≥T limit But SOC j+1 <SOC m Therefore, it is possible to first determine whether the j+1th state of charge corresponding to each charging rate strategy data set has reached the terminal state of charge (such as a fully charged state), and screen out the charging rate strategy data sets that have reached the terminal state of charge, and then select the charging rate strategy data set with the shortest total charging time from the charging rate strategy data sets that have reached the terminal state of charge as a qualified charging rate strategy data set. Therefore, the above-mentioned determination of the charging rate strategy data set with the shortest total charging time as a qualified charging rate strategy data set may include: determining the charging rate strategy data set with the shortest total charging time and the state of charge reaching the terminal state of charge as a qualified charging rate strategy data set.

[0119] In practical applications, after obtaining a qualified charging rate strategy data set, physical measurement or three-dimensional thermal simulation technology can be used to verify the qualified charging rate strategy data set to improve the optimization efficiency and data accuracy of the charging rate strategy data set. In this way, compared with the prior art method of directly using physical measurement or three-dimensional thermal simulation technology to optimize the charging rate strategy data set, the selection method of the embodiment of the present disclosure can reduce the number of physical measurements or three-dimensional thermal simulations, shorten the selection time, and reduce development costs.

[0120] According to the selection method of the embodiment of the present disclosure, a qualified charging rate strategy data set can be efficiently selected from multiple charging rate strategy data sets, that is, a qualified charging rate strategy data set that meets the needs can be quickly obtained, which is conducive to reducing the development cost of the charging rate strategy data set and shortening the development time.

[0121] Figure 4 A block diagram of a battery pack charging information estimation device according to an embodiment of the present disclosure is shown as follows: Figure 4 As shown, the estimation device comprises:

[0122] An acquisition module 401 is used to acquire a charging rate strategy data set of charging information to be estimated for a battery pack, and a charging temperature rise curve of the battery pack at a reference charging rate, wherein the charging information includes a charging time and a battery temperature, the charging rate strategy data set includes reference charging rates at different states of charge and different battery temperatures, and the charging temperature rise curve represents a changing relationship between battery temperature and charging time when constant current charging is performed according to the reference charging rate;

[0123] a charging rate determination module 402, for determining, for the jth state of charge to the j+1th state of charge between the initial state of charge and the final state of charge of the battery pack, a target charging rate corresponding to the jth state of charge to the j+1th state of charge according to the charging rate strategy data set and the battery temperature of the battery pack at the jth state of charge, wherein 1≤j≤J, the first state of charge is the initial state of charge, the Jth state of charge is the final state of charge, a plurality of incremental states of charge are included between the initial state of charge and the final state of charge, and the battery temperature of the battery pack at the first state of charge is the actual temperature of the battery pack at the initial state of charge;

[0124] A charging duration determination module 403, configured to determine a target charging duration for charging from the jth state of charge to the j+1th state of charge according to the target charging rate, the jth state of charge, and the j+1th state of charge;

[0125] An estimated temperature rise determination module 404 is used to determine an estimated temperature rise after charging for the target charging time at the reference charging rate from the jth state of charge according to the charging temperature rise curve, the battery temperature of the battery pack at the jth state of charge, and the target charging time;

[0126] A target temperature rise determination module 405, configured to determine a target temperature rise after charging for a target charging time at the target charging rate from the j-th state of charge according to the estimated temperature rise and the target charging rate;

[0127] The battery temperature determination module 406 is configured to determine the battery temperature of the battery pack at the j+1th state of charge according to the target temperature rise and the battery temperature of the battery pack at the jth state of charge.

[0128] In a possible implementation, determining a target charging rate corresponding to the jth state of charge to the j+1th state of charge based on the charging rate strategy data set and the battery temperature of the battery pack at the jth state of charge includes: querying a reference charging rate corresponding to the jth state of charge and a reference charging rate corresponding to the j+1th state of charge from the charging rate strategy data set based on the battery temperature of the battery pack at the jth state of charge, the jth state of charge, and the j+1th state of charge; and determining an average value between the reference charging rate corresponding to the jth state of charge and the reference charging rate corresponding to the j+1th state of charge as the target charging rate corresponding to the jth state of charge to the j+1th state of charge.

[0129] In one possible implementation, the estimated temperature rise after charging from the jth state of charge at the reference charging rate for the target charging time is determined based on the charging temperature rise curve, the battery temperature of the battery pack at the jth state of charge, and the target charging time, including: correcting the charging temperature rise curve according to the battery temperature of the battery pack at the jth state of charge to obtain a corrected target charging temperature rise curve; substituting the target charging time into the target charging temperature rise curve to obtain the estimated battery temperature after charging from the jth state of charge at the reference charging rate for the target charging time; and determining the difference between the estimated battery temperature and the battery temperature of the battery pack at the jth state of charge as the estimated temperature rise after charging from the jth state of charge at the reference charging rate for the target charging time.

[0130] In a possible implementation, the charging temperature rise curve is corrected according to the battery temperature of the battery pack at the jth state of charge to obtain a corrected target charging temperature rise curve, including: substituting the battery temperature of the battery pack at the jth state of charge into the charging temperature rise curve to obtain a correction duration; and correcting the charging temperature rise curve using the correction duration to obtain a corrected target charging temperature rise curve.

[0131] In a possible implementation, determining the target temperature rise after charging at the target charging rate for the target charging time from the jth state of charge according to the estimated temperature rise and the target charging rate includes: querying the first cell internal resistance corresponding to the battery pack from a cell internal resistance data set corresponding to the battery pack according to the reference charging rate, the jth state of charge and the battery temperature of the battery pack at the jth state of charge; the cell internal resistance data set includes the cell internal resistance of the battery pack at different charging rates, different states of charge and different battery temperatures; querying the second cell internal resistance corresponding to the battery pack from the cell internal resistance data set according to the target charging rate, the jth state of charge and the battery temperature of the battery pack at the jth state of charge; determining the target temperature rise after charging at the target charging rate for the target charging time from the jth state of charge according to the ratio of the second cell internal resistance to the first cell internal resistance, the target charging rate and the estimated temperature rise.

[0132] In a possible implementation, the estimation device calculates the target charging time corresponding to each state of charge and the battery temperature of the battery pack at each state of charge from the initial state of charge, the initial state of charge includes a fully discharged state, and the final state of charge includes a fully charged state, such as Figure 5 As shown, the estimation device also includes:

[0133] A determination module 407 is used to determine whether the battery temperature of the battery pack at the j+1th state of charge exceeds a preset temperature limit, and to determine whether the j+1th state of charge reaches the termination state of charge;

[0134] The total charging time determination module 408 is used to accumulate multiple target charging times calculated segment by segment from the initial state of charge to the j+1th state of charge when the battery temperature of the battery pack at the j+1th state of charge exceeds the preset temperature limit, or the j+1th state of charge has reached the terminal state of charge, to obtain the total charging time from the initial state of charge to the j+1th state of charge.

[0135] According to the estimation device of the embodiment of the present disclosure, the target charging rate and target charging time corresponding to any state of charge are determined by utilizing the charging rate strategy data set, and then the charging temperature under any state of charge can be quickly determined in combination with the charging temperature rise curve under the reference charging rate. That is, the charging time and battery temperature corresponding to any state of charge under any charging rate strategy data set can be quickly calculated. Compared with the method of performing physical testing or three-dimensional thermal simulation modeling, the calculation efficiency of charging information can be improved, which is beneficial to improving the development efficiency of the charging rate strategy data set and reducing development costs.

[0136] Based on the above Figure 5 The present disclosure also provides a charging rate strategy data set optimization device, which includes Figure 5 The estimation device, after obtaining the total charging time from the initial state of charge to the j+1th state of charge, the optimization device further comprises:

[0137] a duration judgment module, configured to judge whether the total charging duration to the j+1th state of charge is greater than a preset duration threshold when the j+1th state of charge reaches the terminal state of charge;

[0138] an optimization module, configured to optimize the charging rate strategy data set when the total charging time is greater than the preset time threshold, and re-execute the charging rate strategy data set using the optimized charging rate strategy data set; Figure 5 The estimation device shown is used to obtain a qualified charging rate strategy data set until the accumulated total charging time is less than or equal to the preset time threshold.

[0139] In a possible implementation, the optimization module is further used to: optimize the charging rate strategy data set when the j+1th state of charge does not reach the termination state of charge, and re-execute the charging rate strategy data set using the optimized charging rate strategy data set. Figure 5 The estimation device shown executes the step of determining whether the total charging time to the j+1th state of charge is greater than a preset time threshold until the j+1th state of charge reaches the termination state of charge.

[0140] According to the above-mentioned optimization device of the embodiment of the present disclosure, the charging rate strategy data set can be efficiently optimized to quickly obtain a qualified charging rate strategy data set that meets the needs, which is conducive to reducing the development cost of the charging rate strategy data set and shortening the development time.

[0141] Based on the above Figure 5 The estimation device shown in the figure, the embodiment of the present disclosure also provides a charging rate strategy data set selection device, the selection device comprising:

[0142] A data set acquisition module, used to acquire multiple charging rate strategy data sets to be selected;

[0143] The execution module is used to execute Figure 5 The estimation device shown obtains the total charging time corresponding to a single charging rate strategy data set;

[0144] The selection module is used to determine the charging rate strategy data set with the shortest total charging time as a qualified charging rate strategy data set.

[0145] According to the selection device of the embodiment of the present disclosure, a qualified charging rate strategy data set can be efficiently selected from multiple charging rate strategy data sets, that is, a qualified charging rate strategy data set that meets the needs can be quickly obtained, which is conducive to reducing the development cost of the charging rate strategy data set and shortening the development time.

[0146] In some embodiments, the functions or modules included in the device provided by the embodiments of the present disclosure can be used to execute the method described in the above method embodiments. The specific implementation can refer to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0147] The embodiment of the present disclosure also provides a computer-readable storage medium on which computer program instructions are stored, and the computer program instructions implement the above method when executed by a processor. The computer-readable storage medium can be a volatile or non-volatile computer-readable storage medium.

[0148] An embodiment of the present disclosure further proposes an electronic device, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to implement the above method when executing the instructions stored in the memory.

[0149] The embodiments of the present disclosure also provide a computer program product, including a computer-readable code, or a non-volatile computer-readable storage medium carrying the computer-readable code. When the computer-readable code runs in a processor of an electronic device, the processor in the electronic device executes the above method.

[0150] Figure 6 1 is a block diagram of an electronic device 1900 according to an embodiment of the present disclosure. For example, the electronic device 1900 may be provided as a server or a terminal device. Figure 6 , the electronic device 1900 includes a processing component 1922, which further includes one or more processors, and a memory resource represented by a memory 1932 for storing instructions executable by the processing component 1922, such as an application. The application stored in the memory 1932 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 1922 is configured to execute instructions to perform the above method.

[0151] The electronic device 1900 may also include a power supply component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input / output interface 1958 (I / O interface). The electronic device 1900 may operate based on an operating system stored in the memory 1932, such as Windows Server 2003.TM , Mac OS X TM , Unix TM ,Linux TM , FreeBSD TM or similar.

[0152] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions, which can be executed by the processing component 1922 of the electronic device 1900 to perform the above method.

[0153] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0154] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0155] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0156] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0157] Various aspects of the present disclosure are described herein with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0158] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0159] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0160] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to multiple embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of the module, program segment or instruction includes one or more executable instructions for realizing the specified logical function. In some alternative implementations, the function marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of special hardware and computer instructions.

[0161] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A method for estimating battery pack charging information, characterized in that: include: Obtaining a charging rate strategy data set of charging information to be estimated for a battery pack, and a charging temperature rise curve of the battery pack at a reference charging rate, wherein the charging information includes charging time and battery temperature, the charging rate strategy data set includes reference charging rates at different states of charge and different battery temperatures, and the charging temperature rise curve represents a changing relationship between battery temperature and charging time when constant current charging is performed according to the reference charging rate; For the jth state of charge to the j+1th state of charge between the initial state of charge and the final state of charge of the battery pack, determine the target charge rate corresponding to the jth state of charge to the j+1th state of charge according to the charge rate strategy data set and the battery temperature of the battery pack at the jth state of charge, wherein 1≤j≤J, the first state of charge is the initial state of charge, the Jth state of charge is the final state of charge, a plurality of incremental states of charge are included between the initial state of charge and the final state of charge, and the battery temperature of the battery pack at the first state of charge is the actual temperature of the battery pack at the initial state of charge; Determining a target charging time from the jth state of charge to the j+1th state of charge according to the target charging rate, the jth state of charge, and the j+1th state of charge; Determine, according to the charging temperature rise curve, the battery temperature of the battery pack at the jth state of charge, and the target charging time, an estimated temperature rise after charging at the reference charging rate from the jth state of charge for the target charging time; Determine, according to the estimated temperature rise and the target charging rate, a target temperature rise after charging from the j-th state of charge at the target charging rate for the target charging time; determining the battery temperature of the battery pack at the j+1th state of charge according to the target temperature rise and the battery temperature of the battery pack at the jth state of charge; The step of determining a target charging rate corresponding to a jth state of charge to a j+1th state of charge according to the charging rate strategy data set and the battery temperature of the battery pack at the jth state of charge includes: According to the battery temperature of the battery pack at the jth state of charge, the jth state of charge and the j+1th state of charge, querying from the charging rate strategy data set a reference charging rate corresponding to the jth state of charge and a reference charging rate corresponding to the j+1th state of charge; Determine the average value of the reference charging rate corresponding to the jth state of charge and the reference charging rate corresponding to the j+1th state of charge as the target charging rate corresponding to the jth state of charge to the j+1th state of charge; Wherein, determining, according to the estimated temperature rise and the target charging rate, the target temperature rise after charging from the j-th state of charge at the target charging rate for the target charging time comprises: According to the reference charging rate, the j-th state of charge and the battery temperature of the battery pack at the j-th state of charge, query the first battery cell internal resistance corresponding to the battery pack from the battery cell internal resistance data set corresponding to the battery pack; the battery cell internal resistance data set includes the battery cell internal resistance of the battery pack at different charging rates, different states of charge and different battery temperatures; According to the target charging rate, the j-th state of charge, and the battery temperature of the battery pack at the j-th state of charge, querying the second battery cell internal resistance corresponding to the battery pack from the battery cell internal resistance data set; A target temperature rise after charging from the jth state of charge at the target charging rate for the target charging time is determined according to the ratio of the second battery cell internal resistance to the first battery cell internal resistance, the target charging rate, and the estimated temperature rise.

2. The estimation method according to claim 1, characterized in that The determining, according to the charging temperature rise curve, the battery temperature of the battery pack at the jth state of charge, and the target charging time, an estimated temperature rise after charging at the reference charging rate from the jth state of charge for the target charging time, comprises: Correcting the charging temperature rise curve according to the battery temperature of the battery pack at the jth state of charge to obtain a corrected target charging temperature rise curve; Substituting the target charging time into the target charging temperature rise curve, to obtain an estimated battery temperature after charging from the j-th state of charge according to the reference charging rate for the target charging time; The difference between the estimated battery temperature and the battery temperature of the battery pack at the jth state of charge is determined as the estimated temperature rise after charging from the jth state of charge at the reference charging rate for the target charging time.

3. The estimation method according to claim 2, characterized in that The method of correcting the charging temperature rise curve according to the battery temperature of the battery pack at the j-th state of charge to obtain a corrected target charging temperature rise curve includes: Substituting the battery temperature of the battery pack at the j-th state of charge into the charging temperature rise curve to obtain a corrected duration; The charging temperature rise curve is corrected using the correction time to obtain a corrected target charging temperature rise curve.

4. The estimation method according to any one of claims 1 to 3, characterized in that: The estimation method calculates the target charging time corresponding to each state of charge and the battery temperature of the battery pack at each state of charge from the initial state of charge, the initial state of charge includes a fully discharged state, and the final state of charge includes a fully charged state. The estimation method also includes: Determining whether a battery temperature of the battery pack at the j+1th state of charge exceeds a preset temperature limit, and determining whether the j+1th state of charge reaches the termination state of charge; When the battery temperature of the battery pack at the j+1th state of charge exceeds the preset temperature limit, or the j+1th state of charge has reached the termination state of charge, multiple target charging times calculated segment by segment from the initial state of charge to the j+1th state of charge are accumulated to obtain the total charging time from the initial state of charge to the j+1th state of charge.

5. A charging rate strategy data set optimization method, wherein: The estimation method according to claim 4 is characterized in that after obtaining the total charging time from the initial state of charge to the j+1th state of charge, the optimization method further comprises: When the j+1th state of charge reaches the termination state of charge, determining whether the total charging time to charge to the j+1th state of charge is greater than a preset time threshold; When the total charging time is greater than the preset time threshold, the charging rate strategy data set is optimized, and the estimation method of claim 4 is re-executed using the optimized charging rate strategy data set until the accumulated total charging time is less than or equal to the preset time threshold, thereby obtaining a qualified charging rate strategy data set.

6. The optimization method according to claim 5, characterized in that: The optimization method further comprises: In the case that the j+1th state of charge has not reached the termination state of charge, the charging rate strategy data set is optimized, and the estimation method of claim 4 is re-executed using the optimized charging rate strategy data set until the j+1th state of charge reaches the termination state of charge, and then the determination of whether the total charging time to the j+1th state of charge is greater than a preset time threshold is executed.

7. A charging rate strategy data set selection method, characterized in that: The selection method includes: Obtaining multiple charging rate strategy data sets to be selected; For multiple charging rate strategy data sets, executing the estimation method described in claim 4 to obtain the total charging time corresponding to a single charging rate strategy data set; The charging rate strategy data set with the shortest total charging time is determined as a qualified charging rate strategy data set.

8. A battery pack charging information estimation device, characterized in that: include: An acquisition module, used to acquire a charging rate strategy data set of charging information to be estimated for a battery pack, and a charging temperature rise curve of the battery pack at a reference charging rate, wherein the charging information includes a charging time and a battery temperature, the charging rate strategy data set includes reference charging rates at different states of charge and different battery temperatures, and the charging temperature rise curve represents a changing relationship between battery temperature and charging time when constant current charging is performed according to the reference charging rate; a charging rate determination module, for determining, for the jth state of charge to the j+1th state of charge between the initial state of charge and the final state of charge of the battery pack, a target charging rate corresponding to the jth state of charge to the j+1th state of charge according to the charging rate strategy data set and the battery temperature of the battery pack at the jth state of charge, wherein 1≤j≤J, the first state of charge is the initial state of charge, the Jth state of charge is the final state of charge, a plurality of incremental states of charge are included between the initial state of charge and the final state of charge, and the battery temperature of the battery pack at the first state of charge is the actual temperature of the battery pack at the initial state of charge; a charging duration determination module, configured to determine a target charging duration for charging from the jth state of charge to the j+1th state of charge according to the target charging rate, the jth state of charge, and the j+1th state of charge; an estimated temperature rise determination module, configured to determine an estimated temperature rise after charging from the jth state of charge at the reference charging rate for the target charging time according to the charging temperature rise curve, the battery temperature of the battery pack at the jth state of charge, and the target charging time; a target temperature rise determination module, configured to determine, based on the estimated temperature rise and the target charging rate, a target temperature rise after charging from the j-th state of charge at the target charging rate for the target charging time; a battery temperature determination module, configured to determine the battery temperature of the battery pack at the j+1th state of charge according to the target temperature rise and the battery temperature of the battery pack at the jth state of charge; The step of determining a target charging rate corresponding to a jth state of charge to a j+1th state of charge according to the charging rate strategy data set and the battery temperature of the battery pack at the jth state of charge includes: According to the battery temperature of the battery pack at the jth state of charge, the jth state of charge and the j+1th state of charge, querying from the charging rate strategy data set a reference charging rate corresponding to the jth state of charge and a reference charging rate corresponding to the j+1th state of charge; Determine the average value of the reference charging rate corresponding to the jth state of charge and the reference charging rate corresponding to the j+1th state of charge as the target charging rate corresponding to the jth state of charge to the j+1th state of charge; Wherein, determining, according to the estimated temperature rise and the target charging rate, the target temperature rise after charging from the j-th state of charge at the target charging rate for the target charging time comprises: According to the reference charging rate, the j-th state of charge and the battery temperature of the battery pack at the j-th state of charge, query the first battery cell internal resistance corresponding to the battery pack from the battery cell internal resistance data set corresponding to the battery pack; the battery cell internal resistance data set includes the battery cell internal resistance of the battery pack at different charging rates, different states of charge and different battery temperatures; According to the target charging rate, the j-th state of charge, and the battery temperature of the battery pack at the j-th state of charge, querying the second battery cell internal resistance corresponding to the battery pack from the battery cell internal resistance data set; A target temperature rise after charging from the jth state of charge at the target charging rate for the target charging time is determined according to the ratio of the second battery cell internal resistance to the first battery cell internal resistance, the target charging rate, and the estimated temperature rise.

9. The estimation device according to claim 8, characterized in that The determining, according to the charging temperature rise curve, the battery temperature of the battery pack at the jth state of charge, and the target charging time, an estimated temperature rise after charging at the reference charging rate from the jth state of charge for the target charging time, comprises: Correcting the charging temperature rise curve according to the battery temperature of the battery pack at the j-th state of charge to obtain a corrected target charging temperature rise curve; Substituting the target charging time into the target charging temperature rise curve, to obtain an estimated battery temperature after charging from the j-th state of charge according to the reference charging rate for the target charging time; The difference between the estimated battery temperature and the battery temperature of the battery pack at the jth state of charge is determined as the estimated temperature rise after charging from the jth state of charge at the reference charging rate for the target charging time.

10. The estimation device according to claim 9, characterized in that The method of correcting the charging temperature rise curve according to the battery temperature of the battery pack at the j-th state of charge to obtain a corrected target charging temperature rise curve includes: Substituting the battery temperature of the battery pack at the j-th state of charge into the charging temperature rise curve to obtain a corrected duration; The charging temperature rise curve is corrected using the correction time to obtain a corrected target charging temperature rise curve.

11. The estimation device according to any one of claims 8 to 10, characterized in that: The estimation device calculates the target charging time corresponding to each state of charge and the battery temperature of the battery pack at each state of charge from the initial state of charge, the initial state of charge includes a fully discharged state, and the final state of charge includes a fully charged state. The estimation device also includes: a judging module, configured to judge whether a battery temperature of the battery pack at the j+1th state of charge exceeds a preset temperature limit, and to judge whether the j+1th state of charge reaches the termination state of charge; A total charging time determination module is used to accumulate multiple target charging times calculated segment by segment from the initial state of charge to the j+1th state of charge when the battery temperature of the battery pack at the j+1th state of charge exceeds the preset temperature limit, or the j+1th state of charge has reached the terminal state of charge, so as to obtain a total charging time from the initial state of charge to the j+1th state of charge.

12. A charging rate strategy data set optimization device, wherein: The estimating device according to claim 11 is characterized in that after obtaining the total charging time from the initial state of charge to the j+1th state of charge, the optimizing device further comprises: a duration judgment module, configured to judge whether the total charging duration to the j+1th state of charge is greater than a preset duration threshold when the j+1th state of charge reaches the terminal state of charge; An optimization module is used to optimize the charging rate strategy data set when the total charging time is greater than the preset time threshold, and use the optimized charging rate strategy data set to re-execute the estimation device described in claim 11 until the accumulated total charging time is less than or equal to the preset time threshold, thereby obtaining a qualified charging rate strategy data set.

13. The optimization device according to claim 12, characterized in that: The optimization module is also used to: In the case that the j+1th state of charge has not reached the termination state of charge, the charging rate strategy data set is optimized, and the estimation device of claim 11 is re-executed using the optimized charging rate strategy data set until the j+1th state of charge reaches the termination state of charge, and then the determination of whether the total charging time to charge to the j+1th state of charge is greater than a preset time threshold is executed.

14. A charging rate strategy data set selection device, characterized in that: The selection device comprises: A data set acquisition module, used to acquire multiple charging rate strategy data sets to be selected; An execution module, configured to execute the estimation device according to claim 11 for a plurality of charging rate strategy data sets, to obtain a total charging time corresponding to a single charging rate strategy data set; The selection module is used to determine the charging rate strategy data set with the shortest total charging time as a qualified charging rate strategy data set.

15. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to implement the method described in any one of claims 1 to 7 when executing the instructions stored in the memory.

16. A non-volatile computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by a processor, the method according to any one of claims 1 to 7 is implemented.

Images