Electric quantity estimation method and device, electronic equipment and storage medium

Abstract

The invention provides an electric quantity estimation method and device, electronic equipment and a storage medium, and the method comprises the steps: determining the absolute current electric quantity of a to-be-detected battery, and the current load voltage and the current open-circuit voltage under the absolute current electric quantity based on the current state parameter of the to-be-detected battery; according to the current load voltage, the current open-circuit voltage and a preset battery model, determining a change parameter between the current performance of the to-be-tested battery and the model prediction performance; the preset battery model comprises a mapping relation between the absolute electric quantity of the to-be-tested battery and the load voltage and the open-circuit voltage at different temperatures; and based on the change parameter between the current performance of the to-be-tested battery and the model prediction performance, the absolute current electric quantity and a preset battery model, determining the available residual electric quantity of the to-be-tested battery in the current state. According to the method, the electric quantity of the battery can be estimated more accurately.

Description

Technical Field

[0001] This application belongs to the technical field of batteries, and particularly relates to a method and device for estimating battery power, an electronic device, and a storage medium. Background Art

[0002] Currently, most 3C electronic products (computer, communication, and consumer electronic products) on the market use lithium batteries for power supply and energy storage. The characteristic parameters of lithium batteries are relatively complex. The performance of the battery after aging changes greatly compared with that before aging, and the characteristic parameters of the battery are also different under different working conditions (parameters), making it difficult to accurately estimate the remaining available power of the battery.

[0003] It should be noted that the above statements are only used to provide background technical information related to this application, and do not necessarily constitute prior art. Summary of the Invention

[0004] This application proposes a method and device for estimating battery power, an electronic device, and a storage medium, which can more accurately estimate the battery power.

[0005] The first aspect of the embodiments of this application proposes a method for estimating battery power, including:

[0006] Based on the current state parameters of the battery to be measured, determine the absolute current power of the battery to be measured, as well as the current load voltage and the current open-circuit voltage at the absolute current power;

[0007] According to the current load voltage and the current open-circuit voltage, and a preset battery model, determine the change parameter between the current performance of the battery to be measured and the model-predicted performance; the preset battery model includes the mapping relationship between the absolute power of the battery to be measured and the load voltage and the open-circuit voltage at different temperatures;

[0008] Based on the change parameter between the current performance of the battery to be measured and the model-predicted performance, the absolute current power, and the preset battery model, determine the available remaining power of the battery to be measured in the current state.

[0009] In some embodiments of this application, the step of determining the change parameter between the current performance of the battery to be measured and the model-predicted performance according to the current load voltage, the current open-circuit voltage, and a preset battery model includes:

[0010] According to the current load voltage and the current open-circuit voltage, determine the current actual voltage ratio of the battery to be measured; the voltage ratio is used to characterize the proportional relationship between the load voltage and the open-circuit voltage of the battery in the same state;

[0011] According to the preset battery model, determine the current simulated voltage ratio of the battery to be measured in the current power state;

[0012] Based on the current actual compression ratio and the current simulated compression ratio, determine the compression ratio coefficient between the actual compression ratio and the simulated compression ratio of the battery under test in the current state of charge.

[0013] In some embodiments of the present application, the determining the compression ratio coefficient between the actual compression ratio and the simulated compression ratio of the battery under test in the current state of charge based on the current standard compression ratio and the current simulated compression ratio includes:

[0014] According to the compression ratio coefficient of the current state of charge and the subsequent simulated compression ratio corresponding to the subsequent state of charge in the preset battery model, determine the subsequent actual compression ratio corresponding to the subsequent state of charge; the subsequent state of charge is less than the current state of charge and greater than or equal to the state of charge corresponding to the cut-off voltage;

[0015] Based on the subsequent actual compression ratio and the subsequent simulated compression ratio, determine the estimated compression ratio coefficient of the battery under test corresponding to the subsequent state of charge;

[0016] Substitute the compression ratio coefficient of the current state of charge and the estimated compression ratio coefficient of the subsequent state of charge into a regression model to determine the actual compression ratio coefficient of the battery under test in the current state of charge; the regression model is used to predict the compression ratio coefficient corresponding to the subsequent state of charge.

[0017] In some embodiments of the present application, the determining the compression ratio coefficient between the actual compression ratio and the simulated compression ratio of the battery under test in the current state of charge further includes:

[0018] Perform current normalization and temperature normalization on the current actual compression ratio in sequence to obtain the current standard compression ratio corresponding to the current actual compression ratio;

[0019] Based on the current standard compression ratio and the current simulated compression ratio, determine the compression ratio coefficient between the actual compression ratio and the simulated compression ratio of the battery under test in the current state of charge.

[0020] In some embodiments of the present application, the determining the available remaining charge of the battery under test in the current state based on the change parameter between the current performance and the model prediction performance of the battery under test, the absolute current state of charge, and the preset battery model includes:

[0021] Based on the change parameter between the current performance and the model prediction performance of the battery under test, the absolute current state of charge, and the preset battery model, estimate the absolute cut-off charge corresponding to the battery under test reaching the cut-off voltage;

[0022] Determine the available remaining power of the battery under test based on the absolute current power and the absolute cut-off power of the battery under test.

[0023] In some embodiments of the present application, estimating the absolute cut-off power corresponding to the cut-off voltage of the battery under test based on the change parameter between the current performance and the model prediction performance of the battery under test, the absolute current power, and the preset battery model includes:

[0024] Determine a target simulation iteration method based on the absolute current power and the absolute cut-off power recorded in the preset battery model;

[0025] Match the target simulation iteration with the preset battery model according to the pressure ratio coefficient and the absolute current power, and determine the absolute cut-off power corresponding to the cut-off voltage of the battery under test.

[0026] In some embodiments of the present application, determining the target simulation iteration method based on the absolute current power and the simulated absolute cut-off power recorded in the preset battery model includes:

[0027] Estimate the available remaining power of the battery under test in its current state based on the absolute current power and the simulated absolute cut-off power;

[0028] When the estimated available remaining power is greater than or equal to a preset threshold, or in the case of the first simulation, determine that the target simulation iteration method is a reverse simulation iteration;

[0029] When the estimated available remaining power is less than the preset threshold and it is not the first simulation, determine that the target simulation iteration method is a forward simulation iteration.

[0030] In some embodiments of the present application, matching the target simulation iteration with the preset battery model according to the pressure ratio coefficient and the absolute current power to determine the absolute cut-off power corresponding to the cut-off voltage of the battery under test includes:

[0031] Match the target simulation iteration with the preset battery model according to the pressure ratio coefficient and the absolute current power to determine the grid point load voltage closest to the actual cut-off voltage of the battery under test;

[0032] Based on the simulated cut-off voltage of the battery under test, the grid point load voltage, and the preset battery model, determine the absolute cut-off power corresponding to the cut-off voltage of the battery under test.

[0033] In some embodiments of the present application, after matching the target simulation iteration with the preset battery model according to the pressure ratio coefficient and the absolute current battery level, and determining the grid load voltage closest to the actual cut-off voltage of the battery under test, the following steps are further included:

[0034] Predict the actual voltage cut-off temperature corresponding to the cut-off voltage of the battery under test based on the initial ambient temperature, current state parameters of the battery under test, and the discharge amount before reaching the cut-off voltage.

[0035] Update the grid load voltage based on the actual voltage cut-off temperature of the battery under test.

[0036] In some embodiments of the present application, determining the absolute current battery level of the battery under test, and the current load voltage and current open-circuit voltage at the absolute current battery level based on the current state parameters of the battery under test includes:

[0037] Determine the current load voltage and absolute initial battery level of the battery under test based on the current state parameters of the battery under test.

[0038] Calculate the absolute current battery level of the battery under test based on the absolute initial battery level, chemical battery level, and Coulomb integral battery level.

[0039] Determine the current open-circuit voltage of the battery under test based on the absolute current battery level of the battery under test and the preset battery model.

[0040] In some embodiments of the present application, determining the absolute initial battery level of the battery under test based on the current state parameters of the battery under test includes:

[0041] Determine whether the battery under test meets the preset initial battery level update condition based on the current state parameters of the battery under test.

[0042] When the battery under test meets the preset initial battery level update condition, calculate the actual absolute initial battery level of the battery under test based on the current state parameters of the battery under test and the preset battery model.

[0043] An embodiment of the second aspect of the present application provides a battery level estimation device, which includes:

[0044] A current battery level determination module, configured to determine the absolute current battery level of the battery under test, and the current load voltage and current open-circuit voltage at the absolute current battery level based on the current state parameters of the battery under test;

[0045] A performance change determination module, configured to determine a change parameter between the current performance of the battery under test and the model-predicted performance according to the current load voltage, the current open-circuit voltage, and a preset battery model; the preset battery model includes the mapping relationships between the absolute charge of the battery under test and the load voltage and the open-circuit voltage at different temperatures.

[0046] A remaining charge determination module, configured to determine the available remaining charge of the battery under test in the current state based on the change parameter between the current performance and the model-predicted performance of the battery under test, the absolute current charge, and the preset battery model.

[0047] In some embodiments of the present application, the device is respectively connected to the battery under test and the control main board, obtains the state parameters of the battery under test, and sends the calculated actual remaining charge state to the battery control main board.

[0048] In some embodiments of the present application, the device further includes a data acquisition module and a storage module. The data acquisition module is connected to the battery under test and is configured to detect the current state parameters of the battery under test; the storage module is configured to store the preset battery model.

[0049] In some embodiments of the present application, the data acquisition module includes a current acquisition unit, a voltage acquisition unit, and a charge calculation unit. The charge calculation unit calculates the change amount of charge according to the current acquired by the current acquisition unit.

[0050] An embodiment of the third aspect of the present application provides a chip, on which the battery charge estimation device described in the second aspect is integrated.

[0051] An embodiment of the fourth aspect of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method described in the first aspect is implemented.

[0052] An embodiment of the fifth aspect of the present application provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the method described in the first aspect is implemented.

[0053] The technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0054] The battery power estimation method provided by the embodiment of the present application first determines the current load voltage, the current open-circuit voltage, and the current power state of the battery to be measured. Then, according to the current load voltage, the current open-circuit voltage, and the preset battery model, the change parameter between the current performance of the battery to be measured and the model prediction performance is determined. Furthermore, based on the current power state of the battery to be measured, the change parameter between the current performance of the battery to be measured and the model prediction performance, and the preset battery model, the available remaining power of the battery to be measured in the current state is determined. In this way, based on the change parameter between the current performance of the battery to be measured and the model prediction performance in the current state, the absolute cut-off power predicted in the preset battery model is corrected, so that a more accurate absolute cut-off power and the actual remaining available power can be obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] By reading the following detailed description of the preferred embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present application. Moreover, throughout the drawings, the same reference numerals are used to represent the same components.

[0056] In the drawings:

[0057] Figure 1 The flowchart of the battery power estimation method provided by an embodiment of the present application is shown;

[0058] Figure 2 The specific flowchart of step S1 in the battery power estimation method provided by an embodiment of the present application is shown;

[0059] Figure 3 The schematic diagram of the mapping relationship between the open-circuit voltage (load voltage) and the absolute power provided by an embodiment of the present application is shown;

[0060] Figure 4 The schematic diagram of the mapping relationship between the battery voltage ratio and the absolute power provided by an embodiment of the present application is shown;

[0061] Figure 5 The specific flowchart of determining the absolute initial power SOCAb_zero provided by an embodiment of the present application is shown;

[0062] Figure 6 The schematic diagram of the result error calculated by the linear interpolation method is shown;

[0063] Figure 7 The specific flowchart of step S2 in the battery power estimation method provided by an embodiment of the present application is shown;

[0064] Figure 8Shows the specific process schematic diagram of step S3 in the battery power estimation method provided by an embodiment of the present application;

[0065] Figure 9 Shows the specific process schematic diagram of step S31 in the battery power estimation method provided by an embodiment of the present application;

[0066] Figure 10 Shows the schematic diagram of the process comparison between forward simulation and reverse simulation provided by an embodiment of the present application;

[0067] Figure 11 Shows Figure 10 The partial enlarged schematic diagram of

[0068] Figure 12a Shows the schematic diagram of the simulation result of temperature compensation provided by an embodiment of the present application;

[0069] Figure 12b Shows the schematic diagram of the simulation result of temperature compensation provided by another embodiment of the present application;

[0070] Figure 13 Shows the specific process schematic diagram of the battery power estimation method provided by another embodiment of the present application;

[0071] Figure 14 Shows the process schematic diagram of calculating the pressure ratio coefficient provided by an embodiment of the present application;

[0072] Figure 15 Shows the structural schematic diagram of the battery power estimation device provided by an embodiment of the present application;

[0073] Figure 16 Shows the structural schematic diagram of the battery power estimation device provided by another embodiment of the present application;

[0074] Figure 17 Shows the structural schematic diagram of the battery power estimation device provided by still another embodiment of the present application;

[0075] Figure 18 Shows the structural schematic diagram of an electronic device provided by an embodiment of the present application;

[0076] Figure 19 Shows the schematic diagram of a storage medium provided by an embodiment of the present application. Detailed implementation manners

[0077] Exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present application can be more thoroughly understood and the scope of the present application can be fully conveyed to those skilled in the art.

[0078] It should be noted that unless otherwise specified, the technical terms or scientific terms used in the present application should have the ordinary meanings understood by those skilled in the art to which the present application pertains.

[0079] In the related art, methods such as impedance tracking method, differential pressure updated power estimation method, and simulation iteration method can be used to estimate the remaining available power of a lithium battery (finding the final depth of discharge DOD_end), but there are some defects in the existing algorithms, which reduce the estimation accuracy of the remaining available power.

[0080] Specifically, when using the simulation iteration method to estimate the remaining available power of a lithium battery, the simulation iteration process is either forward simulation or reverse simulation. If only the forward simulation method is used, the iteration process needs to first calculate the current depth of discharge DODpresent (Depth of discharge, during the use of the battery, the percentage of the discharged capacity of the battery to its rated capacity is called the depth of discharge) of the battery, and perform simulation iteratively downward based on DODpresent. When the power is relatively high, the number of simulation iterations is large (more than 20 times), the amount of repeated calculations during the iteration process is large, the computing power requirement is high, the time is long, and the system efficiency is low. During the discharge process, there are many triggering conditions for the remaining power simulation, which will increase the system power consumption, is not conducive to the overall machine endurance, and affects the user experience. If only the reverse simulation method is used, it starts from the point where the real power state is 0, and increases by a fixed step of 1% real ΔSOC, and finally finds the cut-off point. However, due to the influence of the battery impedance R and the load current I, the final cut-off voltage may be at a relatively high position. In the case of low power or low temperature conditions, the number of reverse simulation iterations is more than that of forward simulation.

[0081] The remaining available power of a lithium battery is estimated by using the differential pressure update power method. The remaining power is estimated in a top-down manner. Since the current depth of discharge is estimated based on the initial power and the Coulomb integral power, and there are many simulation trigger conditions, when estimating the remaining power, DODpresent may not be at the model point. Then, iteration is performed by steps (such as 4%). During the iteration process, DOD[i] may not just fall on the battery model grid point either. Algorithms such as linear interpolation can be used to calculate parameters (open-circuit voltage, depth of discharge, impedance, etc.). However, the actual model is a curve, so there will be a certain error between the calculated parameters and the curve, and the error will accumulate continuously (constantly deviate from the actual value) during the iteration process. This error will directly reduce the accuracy of DODend prediction and power estimation.

[0082] When using the impedance tracking method to estimate the remaining available power of a lithium battery, 15 points can be set on the impedance model. The first 7 points use an 11.1% interval, and the last 8 points use a 3.3% interval. For low power, 4 points are used to represent it. Or 12 points can be used on the differential pressure modeling, and for low power, 3 points are used to represent it. Due to the large impedance difference under different power levels, there will be a large error when using the impedance modeling method. Especially when the battery is in a low-power state, the impedance of the battery changes greatly, and the error of the actual impedance modeling data is also large, which can directly affect the accuracy of power estimation.

[0083] To solve the above technical problems and improve the accuracy of estimating the remaining available power of the battery, the embodiments of this application have studied and analyzed various performances presented during the battery discharge process (including but not limited to electrical performance and temperature, etc.). The results show that: 1) Under different power states, the load voltage (the potential difference between the two poles of the battery when the battery is working normally) and the open-circuit voltage (the potential difference between the two poles of the battery when the battery is in an open-circuit state, that is, the positive and negative poles are not connected) of the battery are different, and both will decrease as the power state decreases. And the two voltage change curves are similar, but the degree of decrease and the specific inflection point positions are different; 2) Under the same power state, the actual remaining available power of the battery, that is, the difference between the current power and the remaining power when reaching the cut-off voltage, is not constant, and it will continuously decrease as the battery ages; 3) Different working conditions result in different battery temperatures. Even under the same power state, the load voltage and open-circuit voltage of the battery, as well as the actual remaining available power, may be different; similarly, under the same power state, the battery temperature may also be different; 4) There are also great individual differences during the use of the battery. The current load voltage and current open-circuit voltage of the battery, as well as the actual remaining available power, may all be different from the data calculated in the battery model.

[0084] Based on the above research results, it can be known that the actual remaining available power of the battery is equal to the difference between the current power and the absolute cut-off power under the current state. The current power can be obtained according to the current state parameters of the battery. The absolute cut-off power under the current state can be understood as the battery power when the load voltage reaches the cut-off voltage (this part of the power is often not actually used), which is related to the current state of the battery. The first difference between its actual value and the simulated value calculated according to the battery model is related to the second difference between the available power of the battery under the current state and the corresponding simulated value, and the relationship between the first difference and the second difference is related to the change parameter between the current performance of the battery and the model predicted performance. Therefore, during the actual use of the battery, the actual remaining available power of the battery can be estimated based on the change parameter between the current performance of the battery and the model predicted performance.

[0085] Based on the above findings, an embodiment of the present application provides a battery power estimation method. The method first determines the current load voltage, the current open-circuit voltage, and the current power state of the battery to be measured. Then, according to the current load voltage, the current open-circuit voltage, and a preset battery model, the change parameter between the current performance of the battery to be measured and the model predicted performance is determined. Based on the current power state of the battery to be measured, the change parameter between the current performance of the battery to be measured and the model predicted performance, and the preset battery model, the available remaining power of the battery to be measured under the current state is determined. In this way, based on the change parameter between the current performance of the battery to be measured and the model predicted performance under the current state, the absolute cut-off power predicted in the preset battery model is corrected, so that a more accurate absolute cut-off power and actual remaining available power can be obtained.

[0086] The embodiments of the present application will be described in detail below.

[0087] Please refer to Figure 1 which is a schematic flowchart of battery power estimation provided by an embodiment of the present application. As shown in the appendix Figure 1 shown, the method includes the following steps.

[0088] Step S1, based on the current state parameters of the battery to be measured, determine the absolute current power of the battery to be measured, as well as the current load voltage and the current open-circuit voltage at the absolute current power.

[0089] Among them, the current state parameters include but are not limited to the temperature, voltage, current, heat capacity, and thermal resistance of the battery to be measured, etc., and it can be any parameter value of the battery to be measured. The absolute current power can be the current capacity value of the battery or the power state value, that is, the percentage form of the capacity value. Taking the power state value as an example, the absolute current power is denoted as SOCAb_new.

[0090] In some embodiments, such as Figure 2As shown, step S1 may specifically include the following processes: step S11, based on the current state parameters of the battery under test, determine the current load voltage and the absolute initial power of the battery under test; step S12, based on the absolute initial power, chemical power, and Coulomb integral power, calculate the absolute current power and the current open-circuit voltage of the battery under test; step S13, based on the absolute current power of the battery under test and the preset battery model, determine the current open-circuit voltage of the battery under test.

[0091] The load voltage of the battery under test is denoted as Vbat, and the open-circuit voltage can be denoted as OCV. The load voltage is equal to the difference between the open-circuit voltage of the battery and the voltage of the battery itself, that is, Vbat = OCV - IR, where I is the current of the battery and R is the resistance of the battery. In the actual application process, the load voltage and the current of the battery can be sampled by a voltage acquisition device and a current acquisition device respectively. The resistance of the battery is a known parameter and can also be detected in real time by a resistance detection device. Therefore, the current open-circuit voltage of the battery under test can be calculated through the current load voltage of the battery under test.

[0092] The preset battery model may include the mapping relationships between the absolute power of the battery under test, the load voltage, and the open-circuit voltage at different temperatures. It may include one or more sub-models, and each sub-model can represent one or more mapping relationships. The mapping relationship can be specifically stored and presented in the form of a table, or in the form of a graph and curve. For example, it may include the mapping relationship between the open-circuit voltage (load voltage) and the absolute power OCV / Vbat-SOCAb, the mapping relationship between the absolute power and the battery voltage ratio Vratio (specific explanations are given below), and the corresponding ratio compensation values (which can be but are not limited to temperature compensation values and ratio compensation values) at different temperatures and different absolute powers. Among them, the OCV-SOCAb mapping relationship can be in the form of a chart, such as Figure 3 As shown, the corresponding absolute power value SOCAb can be found through the open-circuit voltage OCV, and the OCV can also be found through the absolute power value SOCAb. The mapping relationship between the battery voltage ratio Vratio and the absolute power can also be in the form of a chart, such as Figure 4 As shown, the standard ratio values at different temperatures and different SOCAb can be calculated through this table. The ratio compensation value is actually the compensation value of the ratio coefficient. The ratio coefficient is a proportional value of the actual ratio of the battery to the simulated ratio, and can be used to characterize the degree of performance change of the battery. Specifically, it can be in the form of a table. As shown in Table 1 below, it is the ratio coefficient compensation value and the reference ratio coefficient value corresponding to different temperatures.

[0093] Table 1 Ratio Coefficient Model Table of the Battery

[0094]

[0095] It is understandable that the above-mentioned preset battery model can directly store the calculated relevant data, or it can be a corresponding mapping relationship, as long as the relevant values ​​can be calculated according to the stored battery model. For example, in Table 1, the data in the 25°C column can be the reference data, and the data in other columns can be the calculated simulation data, or it can be the compensation value of the corresponding row data in the 25°C column. The compensation value can be a difference value or a proportional value, which is not specifically limited in this embodiment.

[0096] The limitation of the absolute initial power in this embodiment is similar to the limitation of the absolute current power, which can also be the capacity value of the battery or the state of power value, that is, the percentage form of the capacity value. Taking the state of power value as an example, the absolute initial power can be recorded as SOCAb_zero. During the use of the battery, SOCAb_zero is positively correlated with OCV_zero. If the open circuit voltage changes, the absolute initial power also changes. The open circuit voltage is a relatively stable quantity, because the battery needs to be in a state of no current or low current for a long time to release the polarization reaction of the battery (polarization impedance influence). Only when the battery is in a state of no current or low current for a long time can the polarization reaction of the battery be released. When the battery does not produce a polarization reaction, the open circuit voltage will maintain the initial value. When the battery has no current for a long time or the current remains less than a certain threshold for a long period of time before the current, the value of the open circuit voltage will change.

[0097] This embodiment updates the initial power based on the set absolute initial power update conditions, which can avoid the influence of small current or false current of precision resistor during the static process, and can more accurately calculate the absolute initial power state SOCAb_zero to improve the accuracy of calculating the available remaining power in the subsequent algorithm.

[0098] Specifically, when determining the absolute initial power of the battery to be tested based on the current state parameters of the battery to be tested, it is possible to first determine whether the battery to be tested meets a preset initial power update condition based on the current state parameters of the battery to be tested; and then, if the battery to be tested meets the preset initial power update condition, calculate the actual absolute initial power of the battery to be tested based on the current state parameters of the battery to be tested and a preset battery model.

[0099] Among them, the initial power of the battery is positively correlated with its open circuit voltage and is also a relatively stable value. The initial power update condition can be consistent with the open circuit voltage update condition, that is, the above-mentioned battery has no current for a long time or the battery current remains less than a certain threshold for a long period of time before the current. The threshold can be obtained by a limited number of tests based on the specific specifications of the battery, and this embodiment does not make specific limitations on this.

[0100] like Figure 5As shown, when determining the absolute initial state of charge SOCAb_zero, it is possible to first determine whether the current satisfies the open-circuit voltage update condition. If it does not, the absolute initial state of charge can be equal to the original absolute initial state of charge. If it satisfies, first determine whether the current is zero. If the current is equal to zero, then OCV_zero = Vbat, and the absolute initial state of charge SOCAb_zero can be directly obtained through the preset battery model based on OCV_zero. If the current is not zero and the update condition is satisfied, Vbat is not equal to OCV_zero. However, since the current is very small and the polarization reaction has a small impact (i.e., the internal resistance of the battery is small), the current open-circuit voltage OCV can be first obtained through the load voltage Vbat of the current battery. The current open-circuit voltage OCV = Vbat + IR, where I is the current of the current battery and R is the internal resistance of the current battery. When I is very small, Vbat can be approximately regarded as the current open-circuit voltage OCV, or an estimated current open-circuit voltage OCV slightly larger than Vbat can be obtained. Then, through the preset battery model, the SOCAb_zero corresponding to this OCV and the battery voltage ratio Vratio_zero at this SOCAb_zero can be calculated. Then, through this voltage ratio Vratio_zero, Vbat, and the formula Vratio_zero = Vbat / OCV_zero_real, a more accurate OCV_zero_real can be calculated. Combining with the preset battery model, the real absolute initial state of charge SOCAb_zero_real (i.e., the real SOCAb_zero) can be obtained.

[0101] When the absolute initial state of charge SOCAb_zero is known, the absolute current state of charge SOCAb_new can be calculated through the absolute initial state of charge (SOCAb_zero) of the battery and the consumed capacity (Qexpend). The consumed capacity can be understood as the capacity released from the absolute initial capacity to the absolute current capacity, and can be obtained by accumulating the charge amount ΔQ per second through a charge detection device (such as but not limited to a coulomb meter) based on the following formula (1). Then, based on the following formula (2), the absolute current state of charge can be calculated through the absolute initial state of charge, the consumed capacity, and the chemical capacity of the battery.

[0102] Qexpend = ∑t1ΔQi (1)

[0103] SOCAb_new = SOCAb_zero - Qexpend / Qchem (2)

[0104] Among them, Qchem is the chemical capacity of the battery, which refers to the sum of the electric charges that can be released after all the substances participating in the electrochemical reaction inside the battery have reacted. The maximum available capacity of a lithium battery under ideal conditions is usually less than the chemical capacity. During use, the actual available capacity of the lithium battery is less than the maximum available capacity under ideal conditions.

[0105] After calculating the absolute current battery charge SOCAb_new, based on the following formula (3), the current open-circuit voltage OCV_new can be calculated through linear interpolation and the battery model.

[0106] y = (x2 - x) * y2 / (x2 - x1) + (x - x1) / (x2 - x1) * y1 (3)

[0107] Among them, x represents the absolute battery charge SOCAb, and y represents the open-circuit voltage value OCV corresponding to the absolute battery charge (x).

[0108] When calculating the current open-circuit voltage OCV_new through linear interpolation and the battery model, first, the position of OCV_new(y) in the model needs to be found. Based on this position SOCAb_new(x), find the upper and lower two points (x1, y1) and (x2, y2) in the model, calculate the slope of this section, import SOCAb_new(x), and calculate OCV_new(y).

[0109] In existing common algorithms, the calculation principle for uncertain positions mainly relies on linear interpolation. However, due to the error between linear interpolation and the original value, as Figure 6 shown, when using linear interpolation to calculate the value between two points, there will be an error interval as shown in the figure, resulting in an interpolation with an error between the true value yreal and the theoretically calculated value y, which will also affect the accuracy of battery charge estimation. When calculating the parameters corresponding to SOCAb_new, if calculated only once, the error is small. If a cyclic iteration process is adopted and the predicted next position is matched with the model, and linear interpolation needs to be used to calculate the position, there will be an error. If a forward cyclic simulation is used, this error will be continuously accumulated during the simulation process, resulting in a large error in the final estimated battery charge state. In this embodiment, before the simulation iteration, the predicted position is first matched with the model, so only one interpolation calculation is required, which can reduce the number of times of using linear interpolation and the error brought by the interpolation algorithm, and can fundamentally improve the algorithm accuracy.

[0110] Step S2: Determine the change parameter between the current performance of the battery under test and the model-predicted performance according to the current load voltage, the current open-circuit voltage, and the preset battery model.

[0111] Among them, the change parameters between the current performance of the battery under test and the model prediction performance may include the above-mentioned voltage ratio and voltage ratio coefficient of the battery. The voltage ratio is denoted as Vratio, which is the proportional relationship between the load voltage of the battery and the open-circuit voltage of the battery. Different state-of-charge corresponds to different battery voltage ratios, which can characterize the performance state of the battery. Since the battery temperature T and current I may change during the battery discharge process, the performance of the battery also changes with conditions such as temperature and load current. The overall change in the battery voltage ratio Vratio is used to characterize the overall change in the performance state of the battery. The current load voltage and the current open-circuit voltage of the battery are both actual values, and their voltage ratio calculation is relatively accurate; and it is relatively convenient to obtain. The battery voltage ratio calculation is relatively simple, which can greatly improve the accuracy of state-of-charge estimation, simplify the calculation process, improve system efficiency, and reduce system power consumption.

[0112] The voltage ratio coefficient refers to the relationship between the actual voltage ratio and the simulated voltage ratio of the battery, which can characterize the degree of change in battery performance. Among them, the actual voltage ratio can be understood as the ratio of the actual load voltage of the battery to the actual open-circuit voltage at the same state-of-charge, and both the actual load voltage and the actual open-circuit voltage are real values under actual working conditions, such as the currently collected load voltage and the currently calculated open-circuit voltage based on the current load voltage. The simulated voltage ratio can be understood as the ratio of the simulated load voltage of the battery to the simulated open-circuit voltage at the same state-of-charge. The simulated load voltage and the simulated open-circuit voltage are both values calculated according to the preset battery model, which can be calculated and stored in advance and called when in use, or can be calculated when in use. This embodiment does not make specific limitations on this.

[0113] In some embodiments, as Figure 7 shown, the above step S2 may include the following processing: Step S21, determine the current actual voltage ratio of the battery under test according to the current load voltage and the current open-circuit voltage; Step S22, determine the current simulated voltage ratio of the battery under test in the current state-of-charge according to the preset battery model; Step S23, based on the current actual voltage ratio and the current simulated voltage ratio, determine the voltage ratio coefficient between the actual voltage ratio and the simulated voltage ratio of the battery under test in the current state-of-charge.

[0114] In this embodiment, the current voltage ratio of the battery can be denoted as Vratio_new, which represents the proportional relationship between the current load voltage Vbat_new and the current open-circuit voltage OCV_new of the battery. The simulated voltage ratio of the battery can be denoted as Vratio_old, which represents the proportional relationship between the simulated load voltage Vbat_old and the simulated open-circuit voltage OCV_old of the battery. The voltage ratio coefficient is denoted as Vratio_scale, which is used to represent the proportional relationship between Vratio_new and Vratio_old under the same working conditions.

[0115] Specifically, under the same operating conditions, the difference between the current pressure ratio and the simulated pressure ratio is denoted as ΔVratio, as shown in Equation (4). Then, the pressure ratio coefficient is calculated based on Equation (5) below, and the pressure ratio model as shown in Equation (6) below can be obtained.

[0116] ΔVratio = Vratio_new - Vratio_old (4)

[0117] Vratio_scale = ΔVratio / (1 - Vratio_old) (5)

[0118] Vratio(i)_new = (1 - Vratio(i)_old) * Vratio_scale + Vratio(i)_old (6)

[0119] Among them, (1 - Vratio(i)_old) * Vratio_scale can be understood as the difference between the simulated pressure ratio and the actual pressure ratio in the case of electricity quantity i, and this difference is related to the pressure ratio coefficient Vratio_scale. Here, the pressure ratio coefficient is the pressure ratio coefficient after being corrected and updated according to the pressure ratio coefficient of the battery under test in the current electricity state.

[0120] Furthermore, the above step S23 may include the following processing: determining the subsequent actual pressure ratio corresponding to the subsequent electricity state according to the pressure ratio coefficient of the current electricity state and the subsequent simulated pressure ratio corresponding to the subsequent electricity state in the preset battery model; determining the estimated pressure ratio coefficient of the battery under test corresponding to the subsequent electricity state based on the subsequent actual pressure ratio and the subsequent simulated pressure ratio; substituting the pressure ratio coefficient of the current electricity state and the estimated pressure ratio coefficient of the subsequent electricity state into the regression model to determine the actual pressure ratio coefficient of the battery under test in the current electricity state.

[0121] Among them, the subsequent electricity state can be understood as the electricity state less than the current electricity state. In view of the fact that this embodiment needs to obtain the electricity state corresponding to the cut-off voltage, this subsequent electricity state can be greater than or equal to the electricity state value corresponding to the cut-off voltage. The regression model is used to predict the pressure ratio coefficient corresponding to the subsequent electricity state.

[0122] In this embodiment, after calculating the pressure ratio coefficient of the battery under test in the current state of charge, the actual pressure ratio corresponding to the subsequent state of charge can be estimated first based on this pressure ratio coefficient and the simulated pressure ratio corresponding to the subsequent state of charge in the preset battery model. Then, according to the simulated pressure ratio and the actual pressure ratio corresponding to the subsequent state of charge, the pressure ratio coefficient corresponding to the subsequent state of charge is calculated. Then, the calculated current pressure ratio coefficient and the estimated pressure ratio coefficient of the subsequent state of charge can be substituted into the regression model to calculate the actual pressure ratio and pressure ratio coefficient corresponding to the next subsequent state of charge. Then, the pressure ratio coefficient corresponding to the subsequent state of charge is also substituted into the regression model. Based on this quadratic regression model, the actual pressure ratio coefficient of the battery under test in the current state of charge can be accurately calculated. In this way, both the pressure ratio coefficient and the actual pressure ratio are substituted into the regression model for quadratic regression, which can improve the data nodes in the regression model, further improve the accuracy of the pressure ratio model, and enhance the accuracy of the state-of-charge estimation.

[0123] Specifically, as Figure 4 and Figure 5 shown, the abscissa of the battery pressure ratio model can be divided into multiple grid points. A regression model is established based on the data of each grid point. According to the actual pressure ratio and pressure ratio coefficient of the current state of charge, the actual pressure ratio and pressure ratio coefficient corresponding to the subsequent state of charge are predicted. For example, the pressure ratio coefficient Vratio_scale of the current state of charge, which is also the degree of battery performance change, is synchronized to the next grid point (SOCAb_new_linelater, Vratio_new_linelater) of the battery model, and the actual pressure ratio Vratio_new_linelater of the next grid point is calculated. Then, the actual pressure ratio Vratio_new_linelate of the next grid point is also added to the regression model. After quadratic regression, the true pressure ratio Vratio_real_later (the value after quadratic regression) of the next grid point is calculated. Then, according to Vratio_real_later and the grid point data Vratio_flash_later in the battery model, the true degree of battery performance change of the next grid point, that is, the pressure ratio coefficient Vratio_scale, is calculated.

[0124] In some other embodiments, during the process of calculating the pressure ratio coefficient, the pressure ratio can be normalized. That is, the above step S23 can further include the following processing: sequentially perform current normalization and temperature normalization on the current actual pressure ratio to obtain the current standard pressure ratio corresponding to the current actual pressure ratio; based on the current standard pressure ratio and the current simulated pressure ratio, determine the pressure ratio coefficient between the actual pressure ratio and the simulated pressure ratio of the battery under test in the current state of charge.

[0125] Among them, current normalization means converting the original data into corresponding values after being converted to a specified current according to the current correspondence relationship, and then transforming the corresponding values through transformation into a dimensionless expression to become a scalar. Temperature normalization is similar to current normalization. First, convert the original data into corresponding values after being converted to a specified temperature according to the temperature correspondence relationship, and then transform the corresponding values through transformation into a dimensionless expression to become a scalar. It can be understood that in order to improve the calculation efficiency and the accuracy of calculation results, the simulated pressure ratios involved in this embodiment are all standard pressure ratio values after current normalization and temperature normalization, and the pressure ratio coefficients in Table 1 are also calculated using the standard pressure ratio values after current normalization and temperature normalization.

[0126] In practical applications, in view of the fact that the current and temperature of the battery may be different under the same power state, after calculating the pressure ratio coefficient of the current power state, current normalization and temperature normalization can be performed first to improve the accuracy and convenience of calculation using the regression model.

[0127] Specifically, normalization can be performed according to the following formulas (7) and (8).

[0128] Vratio_new(SOCAb_new,T,I)=Vbat / OCV=1-IR / OCV(SOCAb_new,T) (7)

[0129] Vratio_new(SOCAb_new,T,I) is normalized to Vratio_new_ref(SOCAb_new, T ref , I ref )(8)

[0130] Among them, I ref is the standard current, which can be a unit current or an integer multiple of the unit current, such as 0.1C or 0.2C. Among them, 0.1C or 0.2C represents the relationship between current and capacity. Generally speaking, 0.1C means that the discharge current of a battery with a capacity of 10AH is 1A. T ref is the standard temperature, which can be room temperature, that is, 25 degrees Celsius. Of course, it can also be other values, and this embodiment does not make specific limitations on this.

[0131] First, perform current normalization to represent the battery pressure ratio as the battery pressure ratio at the current temperature and standard current, that is, Vratio(SOCAb_new, T, 0.1C)=1-(1-Vratio(SOCAb_new, T, I))*0.1C / I

[0132] =(I-((1-Vratio(SOCAb_new, T, I))*0.1C) / I

[0133] Then, perform temperature normalization at 25°C, and characterize the battery voltage ratio at the current temperature and current current value as the battery voltage ratio at 25°C and standard current, i.e.:

[0134] Vratio(SOCAb_new, T, 0.1C) → Vratio(SOCAb_new, 25°C, 0.1C).

[0135] Vratio_new(SOCAb, 25, 0.1C) =

[0136] 1 - Scale_SOC_T * ∣25 - T∣ / 25 * (1 - Vratio_new(SOCAb, T, 0.1C))

[0137] Among them, Vratio(SOCAb_new, 25°C, 0.1C) is the parameter after temperature normalization and current normalization. Scale_SOC_T is the battery voltage ratio compensation coefficient, and the purpose is to make Vratio_new(SOCAb, 25, 0.1C) always less than 1. Its specific value can be set according to the actual electrical performance of the battery and can be obtained through a limited number of tests. This embodiment does not make specific limitations on this.

[0138] Step S3: Based on the change parameter between the current performance of the battery under test and the model predicted performance, the absolute current state of charge, and the preset battery model, determine the available remaining state of charge of the battery under test in the current state.

[0139] In this embodiment, after calculating the above absolute current state of charge and the current voltage ratio coefficient, the degree of change in the current performance of the battery can be judged based on the current voltage ratio coefficient, and then combined with the simulated remaining state of charge in the voltage ratio model, the available remaining state of charge of the battery under test in the current state can be determined.

[0140] In some embodiments, as Figure 8 shown, step S3 may include the following processing: Step S31: Based on the change parameter between the current performance of the battery under test and the model predicted performance, the absolute current state of charge, and the preset battery model, estimate the absolute cut-off state of charge corresponding to the battery under test reaching the cut-off voltage; Step S32: Based on the absolute current state of charge and the absolute cut-off state of charge of the battery under test, determine the available remaining state of charge of the battery under test in the current state.

[0141] Among them, the cut-off voltage, also known as the end voltage, refers to the lowest working voltage value at which the voltage of the battery drops during discharge and the battery is not suitable for further discharge. The absolute cut-off charge can be understood as the charge state of the battery when it reaches this cut-off voltage. In this case, the battery is not suitable for further discharge, that is, the absolute cut-off charge cannot be used for the external discharge of the battery. Therefore, the available remaining charge to be calculated in this embodiment is the difference between the current charge of the battery and the absolute cut-off charge. The limitation of the absolute cut-off charge in this embodiment is similar to the limitation of the absolute current charge. It can also be the capacity value of the battery or the charge state value, that is, the percentage form of the capacity value. And the expression forms of the current charge, the absolute cut-off charge, and the available remaining charge should be the same.

[0142] In practical applications, under different working conditions, the performance change degree of the battery and the cut-off voltage of the battery are different, and the charge state corresponding to the cut-off voltage is also different. Therefore, it is necessary to determine the actual cut-off voltage of the battery and the absolute cut-off charge when reaching this actual cut-off voltage according to the actual performance change degree of the current charge state. Then, based on this absolute cut-off charge and the absolute current charge, the available remaining charge of the battery under test in the current state can be accurately obtained.

[0143] Further, as Figure 9 shown, the above step S31 may include the following processes: Step S311, determine the target simulation iteration method based on the absolute current charge and the absolute cut-off charge recorded in the preset battery model; Step S312, according to the pressure ratio coefficient and the absolute current charge, use the target simulation iteration to match with the preset battery model to determine the absolute cut-off charge corresponding to the battery under test when reaching the cut-off voltage.

[0144] Among them, the simulated absolute cut-off charge is the absolute cut-off charge of the battery under test when it reaches the simulated cut-off voltage recorded in the preset battery model, and the simulated cut-off voltage is the simulated cut-off voltage of the battery under test recorded in the preset battery model.

[0145] In this embodiment, to estimate the simulated absolute cut-off charge corresponding to the battery under test when reaching the cut-off voltage, the simulated cut-off charge of the battery under test can be directly determined according to the preset battery model, and then based on the fact that the available remaining charge is equal to the difference between the current charge and the cut-off charge, the available remaining charge of the battery under test can be estimated. Then, the target simulation iteration method is determined according to the estimated available remaining charge.

[0146] Although the actual absolute cut-off power may not be equal to the simulated absolute cut-off power, it is often relatively close to the simulated absolute cut-off power, and the difference between the actual absolute cut-off power and the simulated absolute cut-off power is also positively correlated with the degree of battery performance change. Therefore, based on the current voltage ratio coefficient of the battery under test and the estimated voltage ratio coefficient corresponding to the cut-off voltage, a simulation iteration method can be used to match with a preset battery model to determine the absolute cut-off power of the battery under test in its current state.

[0147] Specifically, when determining the target simulation method, if the estimated available remaining power is greater than or equal to a preset threshold, or it is the first time to perform simulation, then the target simulation iteration method is determined as reverse simulation iteration; if the estimated available remaining power is less than the preset threshold and it is not the first time to perform simulation, then the target simulation iteration method is determined as forward simulation iteration.

[0148] Among them, the preset threshold can be determined according to the actual performance of the battery and the specific battery model. In this embodiment, no specific limitation is imposed on its specific value. For example, it can be more than ten percent. Forward simulation means running the simulation according to the logic designed by the system, gradually advancing the simulation process until the simulation ends, that is, simulating according to the battery discharge process, gradually advancing the simulation process from the current power until simulating to SOCAb_end. Reverse simulation means performing reverse operations during the simulation process, and deducing the input conditions from the simulation results, that is, performing reverse simulation according to the battery discharge process, gradually advancing the simulation process from 0 power until simulating to SOCAb_end.

[0149] The above step S312 may include the following processing: According to the voltage ratio coefficient and the absolute current power, use the target simulation iteration to match with the preset battery model to determine the grid point load voltage closest to the actual cut-off voltage of the battery under test; Based on the simulated cut-off voltage, grid point load voltage of the battery under test, and the preset battery model, determine the absolute cut-off power corresponding to the battery under test reaching the cut-off voltage.

[0150] Such as Figure 10 and Figure 11 As shown, it is a flow comparison diagram of forward simulation and reverse simulation and its partial enlarged view. It can be seen from the figure that during the discharge process, if the forward simulation method is used to search for SOCAb_end, as shown by the solid arrow in the figure, when the power (close to 100%) is relatively high, if the step of each simulation is 4%, it may be necessary to perform more than 20 simulations to find SOCAb_end. Therefore, if the power is at a high level, using reverse simulation, as shown by the dashed arrow in the figure, will greatly reduce the number of simulation iterations and improve the simulation speed and the estimation efficiency of the remaining power. Forward simulation is suitable for the end stage of battery discharge. When the estimated SOCAb_end of the battery is less than the preset threshold, at this time, using forward simulation, the calculation rate and system efficiency are both relatively high.

[0151] In some other embodiments, the temperature of the battery can also be compensated. That is, the step of estimating the predicted voltage ratio coefficient corresponding to the cut-off voltage of the battery to be measured based on the voltage ratio coefficient of the battery to be measured in the current state of charge and the preset battery model may further include the following processing: According to the initial ambient temperature, current state parameters, and the discharge amount before reaching the cut-off voltage of the battery to be measured, predict the actual voltage cut-off temperature corresponding to the battery to be measured when reaching the cut-off voltage; Based on the actual voltage cut-off temperature of the battery to be measured, update the calculated grid load voltage.

[0152] Wherein, the actual voltage cut-off temperature is the actual temperature of the battery when reaching the cut-off voltage.

[0153] In practical applications, the voltage ratio Vratio of the battery is affected by the state of charge SOCAb, temperature, and current. Under the same SOCAb, different temperature values result in different Vratio; under the same temperature, different SOCAb also result in different Vratio, as shown in the parameters in Table 1. And in the process of iteratively finding the absolute cut-off state of charge SOCAb_end, the temperature under SOCAb_later or SOCAb_front needs to be calculated. Therefore, temperature compensation is required to determine the actual voltage cut-off temperature of the battery to be measured, and based on this actual voltage cut-off temperature, update the predicted voltage ratio coefficient when the battery reaches the cut-off voltage, so as to improve the estimation accuracy of the available remaining battery capacity.

[0154] Specifically, a battery temperature and heat capacity - thermal resistance model can be established first. According to the current battery working conditions, the battery temperature after discharging a ΔQ amount of electricity can be predicted. Among them, the heat heat(t)=I(t)2*Rin[i], Rin is the current battery impedance, the initial ambient temperature is denoted as Tambient, the current battery temperature is denoted as Ts[i], the thermal resistance is denoted as Rt, the heat capacity is denoted as Ct, the sampling frequency of key data during the battery discharge process is denoted as Δf, the temperature to be predicted is Ts[i + 1], and the current - to - predicted - point current discharge time is t. Then, the battery temperature and heat capacity - thermal resistance model as shown in formula (9) can be obtained. This model does not require measuring the mass and area of the battery, and does not need to consider the influence of battery inconsistency caused by battery production process during the estimation process, and is more accurate than the battery temperature estimated using specific heat capacity, mass, and battery area. And in this embodiment, by collecting key data such as voltage, current, temperature, capacity, etc. during the battery discharge process and updating the heat capacity and thermal resistance at the model nodes, the temperature prediction model can maintain a higher accuracy.

[0155] Ts[i + 1]=e -Δf / RtCt Ts[i]+(1 - e -Δf / RtCt )Tambient+(1 - e -Δf / RtCt )Rt*heat(t) (9)

[0156] Among them, after calculating the consumed power Qexpend, the discharge time t can be calculated according to the current load current I(t). If there is no simulated temperature in the previous time, the simulated temperature Ts[i] can be equal to the initial ambient temperature Tambient. By default, the initial ambient temperature does not change during the temperature prediction process. The heat capacity Ct and the thermal resistance Rt can be updated according to the data during the discharge process.

[0157] This embodiment also conducts a simulation test based on the battery temperature and heat capacity - thermal resistance model. The simulated temperature is the temperature after temperature compensation at different discharge depths through the model of formula (9) based on the actually collected temperature at a certain discharge depth. The simulation results under different working conditions are respectively as Figure 12a and Figure 12b shown. It can be seen from the figure that by using the battery temperature and heat capacity - thermal resistance model provided in this embodiment to compensate the battery temperature during the battery discharge process, the compensated temperature is relatively close to the actual temperature. Except for a very few values with large temperature differences, most of the temperature differences are within 3°C. It can be seen that the battery temperature and heat capacity - thermal resistance model provided in this embodiment estimates the battery temperature more accurately.

[0158] Further, when both the absolute current power and the absolute cut - off power are in percentage form, step S32 can specifically include the following processing: First, according to the following formula (10), calculate the remaining available capacity value Qrem of the battery to be tested based on the absolute current power, the absolute cut - off power, and the chemical capacity Qchem of the battery to be tested.

[0159] Qrem=(SOCAb_new - SOCAb_end)*Qchem (10)

[0160] The full - charge capacity Qfcc of the battery to be tested = Qstart + Qexpend+Qrem, where Qstart is the consumed capacity before the update of the initial capacity SOCAb_zero. When the battery is fully charged, the absolute full - charge capacity SOCAb_full can be recorded, and Qstart is obtained through (SOCAb_full - SOCAb_zero)*Qchem. Qexpend is the consumed capacity after the update of the initial capacity SOCAb_zero point.

[0161] Then the available remaining power of the battery to be tested is equal to the ratio of the remaining available capacity value of the battery to be tested to the full - charge capacity, that is, SOCAb_end = Qrem / Qfcc.

[0162] In another embodiment, the above - mentioned preset threshold can be equal to 12%. The specific remaining power estimation process can refer to Figure 13 and Figure 14 shown, where Figure 14Schematic diagram of the process for calculating the pressure ratio coefficient.

[0163] First, as Figure 13 shown, it is necessary to obtain the absolute initial battery charge SOCAb_zero to be measured. Then, the absolute current battery charge SOCAb_new to be measured can be calculated through the absolute initial battery charge SOCAb_zero, the Coulomb integral capacity ΔQ, and the chemical capacity Qchem. Again, as Figure 14 shown, based on the absolute current battery charge SOCAb_new, the current open circuit voltage OCV_new of the battery is calculated through linear interpolation and a preset battery model. Then, according to the currently measured battery load voltage Vbat_new and the current open circuit voltage OCV_new, the current actual pressure ratio Vratio_current is calculated. And the current actual pressure ratio Vratio_current is normalized to the standard battery pressure ratio Vratio_new at a current of 0.1C and a temperature of 25 °C. Based on the normalized current pressure ratio Vratio_new and the simulated pressure ratio Vratio_old calculated in the preset battery model, the battery performance change coefficient Vratio_sacle is obtained. The pressure ratio coefficient of the next point in the preset battery model is synchronously updated through this coefficient, and the actual pressure ratio Vratio_new_linlater of the next point is calculated. Then, the actual pressure ratio Vratio_new_linlater of this next point is added to the regression model, and finally the true pressure ratio value Vratio_new_later of this point is calculated. Based on the model pressure ratio Vratio_old_later stored at this point in the model, the true pressure ratio coefficient Vratio_sacle of this point is obtained.

[0164] After calculating the above true pressure ratio coefficient Vratio_sacle, it is necessary to judge the operating condition parameters before the capacity estimation simulation to determine whether to trigger the re - simulation mechanism. For example, overall pressure ratio update, large temperature change, state transition, etc. will trigger the re - simulation mechanism, and the simulation is not triggered at all times during the discharge process.

[0165] After triggering the simulation mechanism, it is necessary to judge the estimated remaining available battery charge SOC to determine whether it is greater than or equal to 12%, or whether it is the first simulation (the simulation count will be reset in case of system power - off, reset, or re - flashing, etc.). If so, after temperature compensation, the reverse simulation method is used to calculate SOCAb_end; if not, after temperature compensation, the forward simulation method is used to calculate SOCAb_end. Then, the remaining available capacity Qrmc, the full - charge capacity QFCC, and the remaining available battery charge SOC of the battery are calculated.

[0166] In summary, for the battery power estimation method provided in this embodiment, first, the current load voltage, the current open-circuit voltage, and the current power state of the battery to be measured are determined. Then, based on the current load voltage, the current open-circuit voltage, and the preset battery model, the change parameter between the current performance of the battery to be measured and the model-predicted performance is determined. Next, based on the current power state of the battery to be measured, the change parameter between the current performance of the battery to be measured and the model-predicted performance, and the preset battery model, the available remaining power of the battery to be measured in the current state is determined. In this way, based on the change parameter between the current performance of the battery to be measured and the model-predicted performance in the current state, the absolute cut-off power predicted in the preset battery model is corrected, so that a more accurate absolute cut-off power and the actual remaining available power can be obtained.

[0167] Based on the same concept as the above power estimation method, this embodiment also provides a battery power estimation device, as Figure 15 shown. The battery power estimation device includes:

[0168] A current power determination module, configured to determine the absolute current power of the battery to be measured, as well as the current load voltage and the current open-circuit voltage at the absolute current power, based on the current state parameters of the battery to be measured;

[0169] A performance change determination module, configured to determine the change parameter between the current performance of the battery to be measured and the model-predicted performance according to the current load voltage, the current open-circuit voltage, and the preset battery model; the preset battery model includes the mapping relationship between the absolute power of the battery to be measured and the load voltage and the open-circuit voltage at different temperatures;

[0170] A remaining power determination module, configured to determine the available remaining power of the battery to be measured in the current state based on the change parameter between the current performance of the battery to be measured and the model-predicted performance, the absolute current power, and the preset battery model.

[0171] The battery power estimation device provided in this embodiment is based on the same concept as the above power estimation method, so it can at least achieve the beneficial effects that can be achieved above, and any of the above embodiments can be applied to the battery power estimation device provided in this embodiment, which will not be elaborated here.

[0172] In some other embodiments, as Figure 16 shown, the battery power estimation device can be respectively connected to the battery to be measured and the control main board, obtain the state parameters of the battery to be measured, and send the calculated actual remaining power state to the control main board to realize communication with the battery and the control main board.

[0173] Specifically, the battery power estimation device can also be provided with a communicator, which is connected to the control main board through the communicator to transmit the battery state information required by the control main board, and the control main board can modify the data stored in the battery power estimation device through the communicator.

[0174] Furthermore, as Figure 17 shown, the battery power estimation device can also include a data acquisition module and a storage module. The data acquisition module is connected to the battery to be measured and is used to detect the current state parameters of the battery to be measured; the storage module is used to store a preset battery model.

[0175] Among them, the current state parameters can include but are not limited to the current of the battery, the current voltage, and the charge change amount, etc. In addition to storing the preset battery model, the storage module can also store other parameters, and can also include a reference module for storing reference data.

[0176] Specifically, the data acquisition module can include a current acquisition unit, a voltage acquisition unit, and a charge calculation unit. The charge calculation unit calculates the charge change amount according to the current collected by the current acquisition unit.

[0177] Among them, the current acquisition unit can include a sensor for measuring current and an analog-to-digital converter for current. After the sensor detects the analog signal of the current, it can convert the analog signal of the current into a digital signal through the analog-to-digital converter for current, and send the digital signal to the charge calculation unit. The charge calculation unit can calculate the charge change amount according to the received current digital signal. Specifically, the charge calculation unit can include but is not limited to a coulomb meter. The voltage acquisition unit can include an analog-to-digital converter for voltage. The analog-to-digital converter can directly obtain the voltage analog signal of the battery from the battery and convert the voltage analog signal into a digital signal.

[0178] Based on the same concept as the above power estimation method, this embodiment also provides a chip on which the above battery power estimation device is integrated.

[0179] The chip provided in this embodiment is based on the same concept as the above power estimation method, so it can at least achieve the beneficial effects that can be achieved above, and any of the above embodiments can be applied to the chip provided in this embodiment, which will not be elaborated here.

[0180] The embodiments of the present application also provide an electronic device to execute the above power estimation method. Please refer to Figure 18 , which shows a schematic diagram of an electronic device provided by some embodiments of the present application. As shown in the appendix Figure 18As shown, the electronic device 40 includes: a processor 400, a memory 401, a bus 402, and a communication interface 403. The processor 400, the communication interface 403, and the memory 401 are connected via the bus 402. A computer program that can run on the processor 400 is stored in the memory 401. When the processor 400 runs the computer program, it executes the battery power estimation method provided in any of the foregoing embodiments of the present application.

[0181] Among them, the memory 401 may include a high-speed random access memory (RAM: Random ACCess Memory), and may also include a non-volatile memory, such as at least one disk memory. The communication connection between this device network element and at least one other network element is realized through at least one communication interface 403 (which can be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. can be used.

[0182] The bus 402 may be an ISA bus, a PCI bus, an EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. Among them, the memory 401 is used to store a program. After receiving an execution instruction, the processor 400 executes the program. The battery power estimation method disclosed in any of the foregoing embodiments of the present application can be applied to the processor 400 or implemented by the processor 400.

[0183] The processor 400 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit in the hardware of the processor 400 or by instructions in the form of software. The above-mentioned processor 400 may be a general-purpose processor, including a central processing unit (CPU for short), a network processor (NP for short), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as being executed by a hardware battery power estimator, or completed by a combination of hardware and software modules in the battery power estimator. The software module may be located in a mature storage medium in the art, such as a random access memory, flash memory, read-only memory, programmable read-only memory, or electrically erasable programmable memory, register, etc. This storage medium is located in the memory 401, and the processor 400 reads the information in the memory 401 and combines its hardware to complete the steps of the above method.

[0184] The electronic device provided by the embodiment of the present application and the battery power estimation method provided by the embodiment of the present application are based on the same inventive concept and have the same beneficial effects as the method adopted, run, or implemented by it.

[0185] The embodiment of the present application also provides a computer-readable storage medium corresponding to the battery power estimation provided by the foregoing embodiment. Please refer to Figure 19 , which shows that the computer-readable storage medium is an optical disc 30, on which a computer program (i.e., a program product) is stored. When the computer program is run by a processor, it will execute the battery power estimation method provided by any of the foregoing embodiments.

[0186] It should be noted that examples of computer-readable storage media may also include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory, or other optical and magnetic storage media, which will not be elaborated here one by one.

[0187] The computer-readable storage medium provided by the above embodiment of the present application and the battery power estimation method provided by the embodiment of the present application are based on the same inventive concept and have the same beneficial effects as the method adopted, run, or implemented by the application program stored in it.

[0188] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application, and they should all be covered by the scope of the claims and the description of the present application. In particular, as long as there is no structural conflict, the technical features mentioned in each embodiment can be combined in any way. The present application is not limited to the specific embodiments disclosed in the text, but includes all technical solutions falling within the scope of the claims.

Claims

1. A method for estimating battery power, characterized in that, The method includes: Based on the current state parameters of the battery under test, determining the absolute current power of the battery under test, as well as the current load voltage and the current open-circuit voltage at the absolute current power; According to the current load voltage and the current open-circuit voltage, as well as a preset battery model, determining the change parameter between the current performance of the battery under test and the model predicted performance; the preset battery model includes the mapping relationship between the absolute power of the battery under test and the load voltage and the open-circuit voltage at different temperatures; Based on the change parameter between the current performance of the battery under test and the model predicted performance, the absolute current power, and the preset battery model, determining the available remaining power of the battery under test in the current state.

2. The method according to claim 1, characterized in that, The determining the change parameter between the current performance of the battery under test and the model predicted performance according to the current load voltage and the current open-circuit voltage, as well as the preset battery model, includes: According to the current load voltage and the current open-circuit voltage, determining the current actual voltage ratio of the battery under test; the voltage ratio is used to characterize the proportional relationship between the load voltage and the open-circuit voltage of the battery in the same state; According to the preset battery model, determining the current simulated voltage ratio of the battery under test in the current power state; Based on the current actual voltage ratio and the current simulated voltage ratio, determining the voltage ratio coefficient between the actual voltage ratio and the simulated voltage ratio of the battery under test in the current power state.

3. The method according to claim 2, characterized in that, The determining the voltage ratio coefficient between the actual voltage ratio and the simulated voltage ratio of the battery under test in the current power state based on the current standard voltage ratio and the current simulated voltage ratio includes: According to the voltage ratio coefficient in the current power state, as well as the subsequent simulated voltage ratio corresponding to the subsequent power state in the preset battery model, determining the subsequent actual voltage ratio corresponding to the subsequent power state; the subsequent power state is less than the current power state and greater than or equal to the power state corresponding to the cut-off voltage; Based on the subsequent actual voltage ratio and the subsequent simulated voltage ratio, determining the estimated voltage ratio coefficient of the battery under test corresponding to the subsequent power state; Substituting the voltage ratio coefficient in the current power state and the estimated voltage ratio coefficient in the subsequent power state into a regression model to determine the actual voltage ratio coefficient of the battery under test in the current power state; the regression model is used to predict the voltage ratio coefficient corresponding to the subsequent power state.

4. The method according to claim 3, characterized in that, The determining the voltage ratio coefficient between the actual voltage ratio and the simulated voltage ratio of the battery under test in the current power state based on the current actual voltage ratio and the current simulated voltage ratio further includes: Successively performing current normalization and temperature normalization on the current actual voltage ratio to obtain the current standard voltage ratio corresponding to the current actual voltage ratio; Based on the current standard voltage ratio and the current simulated voltage ratio, determining the voltage ratio coefficient between the actual voltage ratio and the simulated voltage ratio of the battery under test in the current power state.

5. The method according to any one of claims 2 - 4, characterized in that, The determining the available remaining power of the battery under test in the current state based on the change parameter between the current performance of the battery under test and the model predicted performance, the absolute current power, and the preset battery model includes: Estimate the absolute cut-off power corresponding to the cut-off voltage of the battery under test based on the change parameter between the current performance and the model predicted performance of the battery under test, the absolute current power, and the preset battery model; Determine the available remaining power of the battery under test in the current state based on the absolute current power and the absolute cut-off power of the battery under test.

6. The method according to claim 5, characterized in that, The estimating the absolute cut-off power corresponding to the cut-off voltage of the battery under test based on the change parameter between the current performance and the model predicted performance of the battery under test, the absolute current power, and the preset battery model includes: Determine the target simulation iteration method based on the absolute current power and the absolute cut-off power recorded in the preset battery model; Match the target simulation iteration with the preset battery model according to the pressure ratio coefficient and the absolute current power to determine the absolute cut-off power corresponding to the cut-off voltage of the battery under test.

7. The method according to claim 6, characterized in that, The determining the target simulation iteration method based on the absolute current power and the simulated absolute cut-off power recorded in the preset battery model includes: Estimate the available remaining power of the battery under test in the current state based on the absolute current power and the simulated absolute cut-off power; When the estimated available remaining power is greater than or equal to the preset threshold or when performing simulation for the first time, determine the target simulation iteration method as reverse simulation iteration; When the estimated available remaining power is less than the preset threshold and the simulation is not performed for the first time, determine the target simulation iteration method as forward simulation iteration.

8. The method according to claim 6, characterized in that, The matching the target simulation iteration with the preset battery model according to the pressure ratio coefficient and the absolute current power to determine the absolute cut-off power corresponding to the cut-off voltage of the battery under test includes: Match the target simulation iteration with the preset battery model according to the pressure ratio coefficient and the absolute current power to determine the grid point load voltage closest to the actual cut-off voltage of the battery under test; Determine the absolute cut-off power corresponding to the cut-off voltage of the battery under test based on the simulated cut-off voltage of the battery under test, the grid point load voltage, and the preset battery model.

9. The method according to claim 8, characterized in that, After matching the target simulation iteration with the preset battery model according to the pressure ratio coefficient and the absolute current power to determine the grid point load voltage closest to the actual cut-off voltage of the battery under test, it further includes: Predict the actual voltage cut-off temperature corresponding to the cut-off voltage of the battery under test based on the initial ambient temperature, the current state parameters of the battery under test, and the discharge amount before reaching the cut-off voltage; Update the grid point load voltage based on the actual voltage cut-off temperature of the battery under test.

10. The method according to claim 1, wherein The determining the absolute current power of the battery under test and the current load voltage and the current open circuit voltage at the absolute current power based on the current state parameters of the battery under test includes: Determine the current load voltage and the absolute initial power of the battery under test based on the current state parameters of the battery under test; Calculate the absolute current power of the battery under test based on the absolute initial power, chemical power, and Coulomb integral power; Determine the current open-circuit voltage of the battery under test based on the absolute current power of the battery under test and the preset battery model.

11. The method according to claim 10, wherein The determining the absolute initial power of the battery under test based on the current state parameters of the battery under test includes: Determine whether the battery under test meets the preset initial power update condition based on the current state parameters of the battery under test; When the battery under test meets the preset initial power update condition, calculate the absolute initial power of the battery under test based on the current state parameters of the battery under test and the preset battery model.

12. A battery power estimation device, wherein The device includes: A current power determination module, configured to determine the absolute current power of the battery under test based on the current state parameters of the battery under test, and the current load voltage and current open-circuit voltage at the absolute current power; A performance change determination module, configured to determine the change parameter between the current performance of the battery under test and the model predicted performance according to the current load voltage, the current open-circuit voltage, and the preset battery model; the preset battery model includes the mapping relationship between the absolute power of the battery under test and the load voltage and open-circuit voltage at different temperatures; A remaining power determination module, configured to determine the available remaining power of the battery under test in the current state based on the change parameter between the current performance and the model predicted performance of the battery under test, the absolute current power, and the preset battery model.

13. The device according to claim 12, wherein The device is respectively connected to the battery under test and the control main board, obtains the state parameters of the battery under test, and sends the calculated actual remaining power state to the control main board.

14. The device according to claim 13, wherein The device further includes a data acquisition module and a storage module, the data acquisition module is connected to the battery under test and is configured to detect the current state parameters of the battery under test; the storage module is configured to store the preset battery model.

15. The device according to claim 14, wherein The data acquisition module includes a current acquisition unit, a voltage acquisition unit, and a charge calculation unit, and the charge calculation unit calculates the charge change amount according to the current acquired by the current acquisition unit.

16. A chip, wherein Integrated thereon is the battery power estimation device according to any one of claims 12-15.

17. An electronic device, wherein Including a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor executes the program to implement the method according to any one of claims 1-11.

18. A computer-readable storage medium having a computer program stored thereon, wherein The program is executed by the processor to implement the method according to any one of claims 1-11.

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