Battery charge state detection method and device, battery management system and battery pack

Abstract

The embodiment of the invention provides a battery charge state detection method and device, a battery management system and a battery pack. The method comprises the steps that the SOC of a target battery is determined according to the current theoretical characteristics of the target battery, the values of at least two component parameters included in an equivalent circuit model of the target battery and a target monotonic function, and the target monotonic function is the state of charge (SOC) of the target battery according to the values of the at least two component parameters included in the equivalent circuit model of the target battery when the tested battery is in each theoretical characteristic; the actual battery voltage corresponding to each SOC of the test battery is determined, and the test battery and the target battery are the same kind of batteries. The method is used for achieving the effect of improving the SOC prediction accuracy.

Description

Technical Field

[0001] The present application relates to the technical field of batteries, and in particular, to a method and device for detecting the state of charge of a battery, a battery management system, and a battery pack. Background Art

[0002] With the development of the battery field, lithium batteries have become a widely used energy storage device. For lithium batteries, the state of charge (SOC) of the battery is an important state index. Essentially, the SOC reflects the amount of remaining power in the battery. Accurately knowing the SOC of the battery is related to many aspects such as the overall performance, safety, and lifespan of the battery. However, currently, the methods for detecting SOC by the open circuit voltage (OCV)-SOC look-up table method and the ampere-hour integration method have the problem of low accuracy.

[0003] Therefore, how to improve the accuracy of SOC detection is an urgent problem to be solved. Summary of the Invention

[0004] The battery state of charge detection method, device, battery management system, and battery pack provided by the embodiments of the present application are used to achieve the effect of improving the accuracy of predicting the SOC.

[0005] In a first aspect, an embodiment of the present application provides a method for constructing a state of charge function, including:

[0006] Determine the state of charge SOC of the target battery according to the current theoretical characteristics of the target battery, the values of at least two component parameters included in the equivalent circuit model of the battery, and a target monotonic function, where the target monotonic function is determined according to the actual battery voltages corresponding to the respective SOCs of the test battery when the test battery is in each theoretical characteristic, and the test battery and the target battery are of the same type.

[0007] Optionally, the current theoretical characteristics include at least one of the current target battery temperature and the current target battery current.

[0008] Optionally, it further includes:

[0009] Obtain the values of at least two of the component parameters included in the equivalent circuit model of the target battery at the current target battery temperature and the current target battery current.

[0010] Optionally, the obtaining the values of at least two of the component parameters included in the equivalent circuit model of the target battery at the current target battery temperature and the current target battery current includes:

[0011] Obtain the current target battery temperature, the current target battery current, and the current target battery voltage of the target battery within a preset duration.

[0012] Based on the equivalent circuit model of the target battery, as well as the current target battery temperature, the current target battery current, and the current target battery voltage, obtain the values of at least two of the component parameters included in the equivalent circuit model.

[0013] Optionally, it further includes:

[0014] When the initial SOC of the target battery is different from the determined SOC of the target battery, calibrate the initial SOC according to the determined SOC of the target battery.

[0015] Optionally, the calibrating the initial SOC according to the determined SOC of the target battery includes:

[0016] Determine a correction parameter for the change rate of the initial SOC according to the difference between the determined SOC of the target battery and the initial SOC;

[0017] Based on the correction parameter, adjust the change rate of the initial SOC to gradually correct the initial SOC until the difference from the SOC of the target battery is less than or equal to a preset difference threshold.

[0018] Optionally, the method further includes:

[0019] According to the actual battery voltages corresponding to the respective SOCs of the test battery when the test battery is in each theoretical characteristic, obtain the mapping relationship between at least two of the component parameters of the equivalent circuit model of the test battery and the SOC of the test battery under each theoretical characteristic;

[0020] According to the mapping relationship between at least two of the component parameters of the equivalent circuit model of the test battery and the SOC of the test battery under each theoretical characteristic, determine the target monotonic function, where the target monotonic function represents the mapping relationship among the theoretical characteristic, the SOC, and at least two of the component parameters.

[0021] Optionally, the theoretical characteristic includes at least one of the test battery temperature and the test battery current.

[0022] Optionally, the determining the target monotonic function according to the mapping relationship between at least two of the component parameters of the equivalent circuit model of the test battery and the SOC of the test battery under each theoretical characteristic includes:

[0023] According to the mapping relationship between each component parameter of the equivalent circuit model of the test battery and the SOC under each of the theoretical characteristics, determine the first function corresponding to each component parameter, where the first function characterizes the functional relationship between each component parameter and the SOC under each of the theoretical characteristics;

[0024] Generate the target monotonic function according to each of the first functions under each of the theoretical characteristics.

[0025] Optionally, the generating the target monotonic function according to each of the first functions under each of the theoretical characteristics includes:

[0026] Determine the initial function according to each of the first functions;

[0027] Adjust the coefficients corresponding to each component parameter in the initial function to generate the target monotonic function under each of the theoretical characteristics.

[0028] Optionally, the adjusting the coefficients corresponding to each component parameter in the initial function to generate the target monotonic function includes:

[0029] Determine the derivative function of the initial function with respect to the SOC;

[0030] According to the derivative function and a preset adjustment target, determine the target values of the coefficients that satisfy the preset adjustment target, where the preset adjustment target includes: the value of the SOC is within the charge and discharge interval, and the derivative function is always greater than 0 or the derivative function is always less than 0;

[0031] Substitute the target values of the coefficients into the initial function to generate the target monotonic function.

[0032] Optionally, the obtaining the mapping relationship between at least two component parameters of the equivalent circuit model of the test battery and the SOC under the theoretical characteristic according to the actual battery voltage corresponding to each state of charge SOC of the test battery when the test battery is in the theoretical characteristic includes:

[0033] According to the change relationship between at least two component parameters and the battery voltage corresponding to multiple times when the test battery is in each of the theoretical characteristics, and the actual battery voltage, obtain an error equation system;

[0034] Obtain at least two target component parameters corresponding to the actual battery voltage according to the error equation system;

[0035] According to the SOC corresponding to the actual battery voltage and at least two of the target component parameters, determine the mapping relationship between at least two component parameters and the SOC of the test battery.

[0036] Optionally, obtaining at least two target component parameters corresponding to the actual battery voltage according to the error equation system includes:

[0037] Obtaining an initial value of the error equation system;

[0038] After iteratively updating the error equation system according to the initial value until the error function of the error equation system meets a preset convergence condition, at least two of the target component parameters are obtained.

[0039] Optionally, the target component parameters include at least one of ohmic internal resistance, polarization resistance, and capacitance. Obtaining the initial value of the error equation system includes:

[0040] Determining an initial value of the ohmic internal resistance according to the transient voltage change of the test battery at the initial moment of discharge;

[0041] And / or,

[0042] Obtaining an initial value of the polarization resistance according to the voltage value when the test battery discharges to a steady state and the change relationship between at least two of the component parameters and the battery voltage of the test battery;

[0043] And / or,

[0044] Obtaining an initial value of the capacitance according to the change relationship.

[0045] Optionally, at least two capacitances are included in the change relationship, and the initial values of the at least two capacitances are the same;

[0046] And / or,

[0047] At least two polarization resistances are included in the target mapping relationship, and the initial values of the at least two polarization resistances are the same.

[0048] Optionally, the equivalent circuit model includes at least one of the following: Rint model, Thevenin model, PNGV model, RC model, Randles model, FOM model.

[0049] In a second aspect, an embodiment of the present application provides a device for constructing a state of charge function. The device includes:

[0050] A processing module, configured to determine the state of charge (SOC) of the target battery according to the current theoretical characteristics of the target battery, the values of at least two component parameters included in the equivalent circuit model of the target battery, and a target monotonic function, where the target monotonic function is determined according to the actual battery voltages corresponding to the respective SOCs of the test battery when the test battery is in each theoretical characteristic, and the test battery and the target battery are of the same type.

[0051] In a third aspect, an embodiment of the present application provides a battery management system, which is configured to execute the battery state of charge detection method according to any one of the first aspects.

[0052] In a fourth aspect, an embodiment of the present application provides a battery pack, which includes the battery management system described in the third aspect.

[0053] In a fifth aspect, an embodiment of the present application provides an electrical device, and the battery pack of the electrical device is the battery pack described in the fourth aspect.

[0054] In a sixth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, they are used to implement various possible implementation manners in the first aspect above.

[0055] In a seventh aspect, an embodiment of the present application provides a computer program product, including a computer program, which when executed by a processor implements various possible implementation manners in the first aspect above.

[0056] The battery state of charge detection method, device, battery management system, and battery pack provided by the embodiments of the present application determine the SOC of the target battery by substituting the current theoretical characteristics of the target battery in the actual use process and at least two component parameters included in the equivalent circuit model of the target battery into the target monotonic function by pre-constructing a target monotonic function based on the mapping relationship among the characterization theoretical characteristics, SOC, and at least two component parameters of the test battery. This method predicts the SOC of the battery through the real-time states of multiple component parameters in the equivalent circuit of the battery. Compared with the current OCV-SOC look-up table method, it can reduce the problem of inaccurate SOC prediction caused by the voltage platform interval of lithium batteries, thereby improving the accuracy of predicting SOC. Description of the Drawings

[0057] The drawings here are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0058] Figure 1A structural schematic diagram of an equivalent circuit model provided by an embodiment of the present application;

[0059] Figure 2 A flowchart of a method for detecting the state of charge of a battery provided by an embodiment of the present application;

[0060] Figure 3 A flowchart of another method for detecting the state of charge of a battery provided by an embodiment of the present application;

[0061] Figure 4 A flowchart of yet another method for detecting the state of charge of a battery provided by an embodiment of the present application;

[0062] Figure 5 A schematic diagram of a mapping relationship provided by an embodiment of the present application;

[0063] Figure 6 A flowchart of still another method for detecting the state of charge of a battery provided by an embodiment of the present application;

[0064] Figure 7 A flowchart of still another method for detecting the state of charge of a battery provided by an embodiment of the present application;

[0065] Figure 8 A structural schematic diagram of a device for detecting the state of charge of a battery provided by an embodiment of the present application.

[0066] Through the above-mentioned drawings, the specific embodiments of the present application have been shown, and there will be more detailed descriptions hereinafter. These drawings and text descriptions are not intended to limit the scope of the concept of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. Detailed Description of the Embodiments

[0067] Here, the exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0068] Currently, the state of charge (SOC) is mainly detected by the OCV-SOC look-up table method and the ampere-hour integration method. Although this method is simple, for lithium batteries (such as ternary lithium batteries, lithium iron phosphate batteries, etc.), there is a voltage plateau in the OCV of the lithium battery when the SOC of the battery is in a specific interval (for example, when the OCV of the lithium iron phosphate battery is in the interval of 20%-90% SOC, there is a voltage plateau). In the SOC interval corresponding to the voltage plateau, the value of the OCV is relatively stable and does not change significantly with the change of the SOC. Therefore, in the SOC interval corresponding to the voltage plateau, if the OCV-SOC look-up table method and the ampere-hour integration method are used to detect the SOC, an accurate SOC cannot be obtained, resulting in a problem of low accuracy in predicting the SOC.

[0069] In view of this, the present application provides a method for detecting the state of charge of a battery, which determines the state of charge (SOC) of the target battery by according to the current theoretical characteristics of the target battery, the values of at least two component parameters included in the equivalent circuit model of the target battery, and a target monotonic function determined based on the actual battery voltages corresponding to each SOC when the test battery corresponding to the target battery is in each theoretical characteristic. This method predicts the SOC of the battery through the real-time states of multiple component parameters in the equivalent circuit of the battery. Compared with the current OCV-SOC look-up table method, it can reduce the problem of inaccurate SOC prediction caused by the voltage plateau interval of the lithium battery, thereby improving the accuracy of predicting the SOC.

[0070] Among them, the execution subject of this method for detecting the state of charge of a battery can be the core control unit of the battery pack, such as a battery management system (BMS), a microprocessor inside the battery pack, etc.; or it can be a dedicated SOC prediction chip. Or, it can be the processing chip of the electrical device carrying the battery pack, etc. Or, the execution subject can also be a third-party device with computing capabilities, such as a mobile phone, a computer, a tablet computer, a server, etc. When the execution subject is a third-party device, the current battery temperature, the current battery current, and the values of each component parameter included in the equivalent circuit model of the battery can be input into the third-party device, and the third-party device calculates to determine the SOC of the battery.

[0071] The technical solution of the present application and how the technical solution of the present application solves the above technical problems will be described in detail below through specific embodiments. These specific embodiments below can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below with reference to the accompanying drawings.

[0072] Determine the state of charge (SOC) of the target battery based on the current theoretical characteristics of the target battery, the values of at least two component parameters included in the equivalent circuit model of the target battery, and a target monotonic function.

[0073] The target monotonic function is determined based on the actual battery voltages corresponding to the respective SOCs of the test battery when the test battery is in each theoretical characteristic. The test battery and the target battery are of the same type. For example, the test battery and the target battery are of the same model, or the difference in battery characteristics (such as capacity, operating parameters, etc.) between the test battery and the target battery is less than or equal to a preset difference threshold, etc. That is, the operating data of the test battery can be used as the reference operating data for the target battery. Specifically, how to construct the target monotonic function can be referred to in the subsequent Figure 6 embodiments and will not be introduced in detail here.

[0074] It should be understood that the current theoretical characteristics and the theoretical characteristics are only for facilitating the distinction of whether they are used in the stage of determining the SOC of the target battery or corresponding to the test battery in the stage of constructing the target monotonic function. The parameter items included in both should be the same so that the target monotonic function has the function of accurately detecting the SOC of the target battery. Among them, the target battery corresponds to the current theoretical characteristics, and the test battery corresponds to the theoretical characteristics.

[0075] Exemplarily, the current theoretical characteristics may include at least one of the current target battery temperature and the current target battery current. The theoretical characteristics are the same as the content included in the current theoretical characteristics. For example, if the current theoretical characteristics include the current target battery temperature and the current target battery current, the theoretical characteristics also include the battery temperature and the battery current.

[0076] The equivalent circuit model of the target battery can be, for example, any one of models such as the Rint model, the Thevenin model, the PNGV model, the RC model, the Randles model, the FOM model, etc., which can be determined according to actual needs and is not limited in this application. For different equivalent circuit models corresponding to the target battery, the component parameters included in the model can also be different.

[0077] Exemplarily, Figure 1 is a schematic structural diagram of an equivalent circuit model provided by an embodiment of this application. As Figure 1 shown, taking the equivalent circuit model of the target battery as a second-order RC model as an example, the component parameters it includes can include: the power supply voltage , the ohmic internal resistance , the first polarization resistance , the first capacitor , the second polarization resistance , the second capacitor , where Figure 1 the V in ois the battery voltage of the target battery.

[0078] In a possible implementation, for different current theoretical characteristics, different target monotonic functions are corresponding. Taking the current theoretical characteristics including the current target battery temperature and the current target battery current as an example, when the current target battery current is I 1 the corresponding target monotonic function is different from the target monotonic function when the current target battery current is I 2 ; when the current target battery temperature is T 1 and the current target battery current is I 1 the corresponding target monotonic function is different from the target monotonic function when the current target battery temperature is T 2 and the current target battery current is I 1 and so on. In this implementation, the corresponding target monotonic function can be determined according to the current theoretical characteristics of the target battery, and then based on the corresponding target monotonic function and the values of at least two component parameters included in the equivalent circuit model of the target battery at the current moment, the corresponding SOC can be determined.

[0079] In another possible implementation, the target monotonic function directly represents the mapping relationship between the current theoretical characteristics and the values of at least two component parameters included in the equivalent circuit model of the target battery. In this implementation, for example, the current theoretical characteristics and the values of at least two component parameters included in the equivalent circuit model of the target battery can be directly substituted into the target monotonic function to obtain the SOC of the battery.

[0080] The method provided by the embodiments of the present application determines the SOC of the target battery by pre-constructing a target monotonic function that represents the mapping relationship among the theoretical characteristics, SOC, and at least two component parameters of the test battery, and substituting the current theoretical characteristics of the target battery in the actual use process corresponding to the test battery and at least two component parameters included in the equivalent circuit model of the target battery into the target monotonic function. This method predicts the SOC of the battery through the real-time states of multiple component parameters in the equivalent circuit of the battery. Compared with the current OCV-SOC look-up table method, it can reduce the problem of inaccurate SOC prediction caused by the voltage platform interval of lithium batteries, thereby improving the accuracy of predicting SOC.

[0081] Optionally, before determining the SOC of the battery according to the current battery temperature, current battery current, the values of each component parameter included in the equivalent circuit model of the battery, and the target monotonic function, the method may further include obtaining the component parameters included in the equivalent circuit model of the battery.

[0082] In a possible implementation, at least two component parameters included in the equivalent circuit model of the target battery can be directly obtained by collecting parameters in the circuit where the target battery is located. For example, taking the equivalent circuit model of the target battery including three component parameters: ohmic internal resistance, polarization resistance, and capacitance as an example, the value of the ohmic internal resistance can be obtained by methods such as the DC discharge method and the AC impedance method; the values of the polarization resistance and capacitance can be obtained by methods such as the pulse discharge method and the electrochemical impedance spectroscopy method. Specifically, how to collect the circuit where the target battery is located through the above methods can refer to the prior art and will not be elaborated here.

[0083] In another possible implementation, based on the current battery temperature, current, and current battery voltage of the target battery within a preset duration, the equivalent circuit model of the target battery can be solved through the iterative algorithm in the embodiments of the subsequent target monotonic function to obtain the values of at least two component parameters included in the equivalent circuit model of the target battery.

[0084] When the values of at least two component parameters included in the equivalent circuit model of the target battery are based on the subsequent target monotonic function to construct the corresponding Figure 6 When the equivalent circuit model of the target battery is solved through the iterative algorithm in the embodiments, it can be implemented through the following Figure 2 steps included. Figure 2 It is a schematic flowchart of a method for detecting the state of charge of a battery provided by an embodiment of the present application. As Figure 2 shown, the method may include:

[0085] S201. Obtain the current target battery temperature, current target battery current, and current target battery voltage of the target battery within a preset duration.

[0086] Among them, the preset duration is determined according to the subsequent Figure 6 iterative algorithm. For example, when the iterative algorithm in the subsequent Figure 6 constructs the mapping relationship between a certain SOC (such as the SOC at time 1) and at least two component parameters included in the corresponding equivalent circuit model, the component parameters are iteratively obtained based on the battery temperature, battery current, and actual battery voltage corresponding to time 1 to time 10, then the preset duration is the duration between time 1 and time 10.

[0087] The current target battery temperature can be obtained by a temperature sensor pre-deployed on the target battery; or it can be predicted based on the historical target battery temperature; or it can be obtained based on the current ambient temperature, the temperature of the target battery at the previous moment, the heat generated by the operation of the target battery, etc.

[0088] The current target battery current can be obtained through a current sensor pre-deployed on the circuit where the target battery is located, or can be calculated based on the internal resistance of the target battery and the current target battery voltage, etc. Among them, the current target battery voltage can be obtained through a voltage sensor pre-deployed on the circuit where the target battery is located, or determined based on the OCV method, etc.

[0089] S202. Based on the equivalent circuit model of the target battery, as well as the current target battery temperature, the current target battery current, and the current target battery voltage, obtain the values of at least two component parameters included in the equivalent circuit model.

[0090] In this step, it can be implemented with reference to the iterative algorithm in the following Figure 6 , with the only difference being that the current target battery temperature and the current target battery current in this step are used to replace Figure 6 the battery temperature and the battery current of the test battery in the Figure 6 method, and then the current target battery voltage in this step is used to replace Figure 6 the actual battery voltage in the

[0091] Next, an introduction to how to construct the target monotonic function will be given.

[0092] The execution entity of the process of constructing the target monotonic function can be implemented by the execution entity of the aforementioned battery state of charge detection method, or can be implemented by a separate execution entity. When implemented by a separate execution entity, the execution entity can be, for example, an electronic device with computing capabilities, such as a computer, a tablet computer, a server, a smart phone, etc. Or, the execution entity can be a hardware with computing capabilities such as a chip of the above-mentioned electronic devices. When the execution entity is an electronic device, a computer program for executing the method of constructing the target monotonic function can be deployed on the electronic device. By executing this computer program, a target monotonic function that characterizes the mapping relationship among the theoretical characteristics, the SOC, and at least two component parameters of the equivalent circuit model of the test battery is constructed.

[0093] Figure 3 is a schematic flowchart of another battery state of charge detection method provided by an embodiment of the present application. As Figure 3 shown, this method may further include:

[0094] S301. According to the actual battery voltages corresponding to the respective SOCs of the test battery when the test battery is in each theoretical characteristic, obtain the mapping relationship between at least two component parameters of the equivalent circuit model of the test battery and the SOC of the test battery under the theoretical characteristic.

[0095] Among them, the theoretical characteristics of the test battery are the same as those included in the current theoretical characteristics of the aforementioned target battery, and may include, for example, at least one of battery temperature and battery current.

[0096] In this step, by setting the test battery at different battery temperatures and / or different battery currents, the actual battery voltage of the test battery can be collected when the test battery is at different SOCs (the collection times corresponding to different SOCs are different, for example, SOC1 corresponds to time 1, SOC2 corresponds to time 2, etc.). And record the time corresponding to the collected actual battery voltage. For example, it can be achieved by adding a corresponding timestamp to each recorded actual battery voltage.

[0097] Among them, the equivalent circuit model of the test battery can be any one of equivalent circuit models such as the Rint model, Thevenin model, PNGV model, RC model, Randles model, FOM model, etc., which can be determined according to actual needs, and this application does not limit this. Among them, the equivalent circuit model of the test battery should be the same as that of the target battery.

[0098] Taking the equivalent circuit model as the aforementioned Figure 1 corresponding second-order RC model as an example, the mathematical expressions of the equivalent circuit model may include the following formulas (1)-(3):

[0099] (1)

[0100] (2)

[0101] (3)

[0102] Among them, is the battery current.

[0103] Based on the above formulas (1)-(3), the relationship between the battery voltage of the test battery during discharge and time can be determined as shown in formula (4):

[0104] (4)

[0105] Among them, the time t is the time difference from the preset initial moment. For example, assuming that the 0 moment of the discharge state of the test battery is taken as the initial moment, that is, the time of the first battery voltage minus the time of this 0 moment, the time t corresponding to the first battery voltage can be determined (assuming that the 0 moment is 10:01:10 and the time of the first battery voltage is 10:01:11, then the time t is 1 second).

[0106] By collecting the actual battery voltage of the test battery at different SOCs and using the above formula (4), the mapping relationship between at least two component parameters of the equivalent circuit model of the test battery and the SOC can be obtained through a non-linear minimization method (such as the Levenberg-Marquardt algorithm). This mapping relationship is used to determine the values of at least two component parameters corresponding to the SOC based on different SOCs, and can be, for example, a mapping table or a mapping curve, etc.

[0107] Among them, the power supply voltage can be obtained through the static OCV after the test battery is left standing (for example, after standing for 2 hours). When the battery voltage is within the voltage platform range, its voltage change is small, and the power supply voltage can be regarded as a constant voltage source. When the OCV changes significantly with the SOC, the power supply voltage can also be used as one of the at least two component parameters and processed together through a non-linear minimization method.

[0108] In a possible implementation, if the ambient temperature of the test battery is the same as the initial temperature of the test battery, it can be considered that the heat generation during the charge and discharge process of the test battery has little effect on the battery temperature of the test battery. In this case, it can be considered that the battery temperature is a constant that does not change. In this situation, the mapping relationship between at least two component parameters of the equivalent circuit model of the test battery and the SOC can be determined by collecting the actual battery voltage of the test battery at different SOCs when the test battery is at different battery currents, that is, without considering the battery temperature factor.

[0109] S302. Determine the target monotonic function according to the mapping relationship between at least two component parameters of the equivalent circuit model of the test battery and the SOC of the test battery under each theoretical feature.

[0110] Among them, the target monotonic function represents the mapping relationship among the theoretical feature, the SOC, and at least two component parameters.

[0111] In this step, the mapping relationship between at least two component parameters and the SOC can be fused to generate a function of at least two component parameters changing with the SOC. And during the fusion process, by controlling the fusion coefficients of each component parameter, the function of at least two component parameters changing with the SOC can be made a monotonic function, that is, the target monotonic function is generated.

[0112] Among them, in this target monotonic function, only a unique parameter value of a component parameter corresponds to the same SOC value, so that subsequently, based on the parameter values of at least two component parameters according to this target monotonic function, the corresponding SOC value can be uniquely determined, avoiding the situation of multiple solutions that may lead to the inability to determine which solution the predicted SOC value specifically corresponds to.

[0113] Optionally, a monotonicity constraint condition can be introduced to perform parametric fitting on the data (such as polynomials, spline functions, etc.) to ensure that the functions of at least two component parameters varying with the SOC are monotonic functions. For example, the sign of the first derivative of the objective function can be constrained to be constant, thereby ensuring monotonicity.

[0114] Alternatively, the mapping relationship between each component parameter and the SOC can be converted into a corresponding monotonic function, and then the mapping relationships between all component parameters and the SOC in at least two component parameters can be fused to generate a target monotonic function of at least two component parameters varying with the SOC.

[0115] The method provided in the embodiments of the present application determines a target monotonic function that characterizes the mapping relationship among the theoretical characteristics, the SOC, and at least two component parameters of the equivalent circuit model of the test battery based on the actual battery voltages corresponding to the SOCs of the test battery under different theoretical characteristics, providing a data basis for subsequently predicting the SOC with high accuracy through multiple component parameters.

[0116] Next, a detailed introduction will be given on how to specifically determine the target monotonic function according to the mapping relationship between at least two component parameters of the equivalent circuit model of the test battery and the SOC in the aforementioned step S302. Figure 4 It is a schematic flowchart of another method for detecting the state of charge of a battery provided by the embodiments of the present application. As Figure 4 shown, the aforementioned step S302 may specifically include the following steps:

[0117] S401. Determine the first function corresponding to each component parameter according to the mapping relationship between each component parameter of the equivalent circuit model of the test battery and the SOC under the theoretical characteristics.

[0118] Among them, the first function characterizes the functional relationship between each component parameter and the SOC under each theoretical characteristic.

[0119] In this step, it is assumed that the mapping relationship between each component parameter and the SOC is a mapping table, that is, for a component parameter, different SOC values correspond to different values of this component parameter. According to this mapping table, the curve of the component parameter with respect to the SOC can be generated by interpolation, and the function of this curve, that is, the first function, can be determined based on this curve.

[0120] Exemplarily,Figure 5 A schematic diagram of a mapping relationship provided by an embodiment of the present application. As Figure 5 shown, it includes the mapping relationship between the values of the parameters of each component in the second-order RC model corresponding to the test battery and different SOC values at a certain specific battery temperature and a certain specific battery current. That is, it respectively includes the ohmic internal resistance , the first polarization resistance , the second polarization resistance , the first capacitance , the second capacitance and the mapping relationship with SOC. Among them, Figure 5 The points in are the values of the parameters of each component at the corresponding SOC value.

[0121] Specifically, according to this mapping table, curves of the parameters of each component with respect to SOC (i.e., the curves in Figure 5 ) can be generated by methods such as Hermite interpolation method and cubic spline interpolation method, and based on these curves, the function of this curve is determined, that is, the first function.

[0122] S402. Generate a target monotonic function according to each first function under each theoretical feature.

[0123] A possible implementation manner is to first convert each first function into a monotonic function, and then based on each first function converted into a monotonic function, fuse them to generate a target monotonic function.

[0124] Another possible implementation manner is to first fuse each first function, and then convert the function generated after fusion into a monotonic function to generate a target monotonic function. This implementation manner can be specifically implemented through the following sub-steps:

[0125] S4021. Generate an initial function according to each first function.

[0126] Among them, the initial function represents the functional relationship between at least two component parameters and SOC.

[0127] In this step, the method of S401 above can be used to obtain the first function corresponding to each component parameter among at least two component parameters. Then, by fusing the first functions corresponding to all component parameters, the functional relationship between at least two component parameters and SOC after fusion is obtained, that is, the initial function.

[0128] Optionally, for example, all the first functions corresponding to the component parameters can be fused by means of weighted average fusion, linear fusion, non-linear fusion, etc. to obtain the initial function.

[0129] Exemplarily, taking linear fusion as an example, assuming that there are 5 component parameters, and the first functions corresponding to each component parameter are respectively , , , , . Then the initial function can be expressed as the following formula (5):

[0130] (5)

[0131] Wherein, , , , , are the coefficients of each first function, and the coefficients can be determined according to actual requirements or experiments.

[0132] S4022. Adjust the coefficients corresponding to the parameters of each component in the initial function to generate a target monotonic function under each theoretical feature.

[0133] Wherein, the target monotonic function characterizes the correlation between at least two component parameters and the SOC.

[0134] A possible implementation method is to define a deviation function between the initial function and the monotonicity, and use optimization algorithms such as the gradient descent method and the Newton method to adjust the coefficients corresponding to the parameters of each component in the initial function. Under the condition of minimizing the deviation function, determine the coefficients corresponding to the parameters of each component in the final target monotonic function.

[0135] Another possible implementation method is to adjust the coefficients by means of derivative function constraints to generate a target monotonic function. In this implementation method, for example, the derivative function of the initial function with respect to the SOC can be obtained. That is, for the initial function, take the derivative with respect to the SOC to obtain the derivative function, and the derivative function is shown in the following formula (6):

[0136] (6)

[0137] Then, by adjusting the values of each coefficient to meet the preset adjustment target, that is, when the value of the SOC is within the charge and discharge interval (for example, 0%-100%), adjust the values of each coefficient so that the value of the coefficient can make the derivative function greater than 0 or less than 0. At this time, the initial function F can be made to be monotonically increasing (the derivative function is always greater than 0) or monotonically decreasing (the derivative function is always less than 0). At this time, the values of each coefficient are the target values of each coefficient. Finally, substitute the target values of each coefficient into the initial function to generate the target monotonic function.

[0138] The method provided by the embodiment of the present application determines the first function corresponding to each component parameter according to the mapping relationship between each component parameter in at least two component parameters and the SOC, generates an initial function representing the functional relationship between at least two component parameters and the SOC according to each first function, and finally adjusts the coefficients corresponding to each component parameter in the initial function to generate a target monotonic function, so that subsequently, based on the parameter values of each component parameter, the corresponding SOC value can be uniquely determined according to the target monotonic function, avoiding the situation of multiple solutions that leads to the inability to determine which solution the predicted SOC value corresponds to, thereby realizing the function of accurately detecting the SOC by the component parameters through the target monotonic function.

[0139] Next, a detailed introduction will be given on how to obtain the mapping relationship between at least two component parameters of the equivalent circuit model of the test battery and the SOC according to the actual battery voltage corresponding to each SOC of the test battery when the test battery is in the theoretical characteristics in the foregoing step S301.

[0140] Figure 6 It is a schematic flowchart of another method for detecting the state of charge of a battery provided by the embodiment of the present application. As Figure 6 shown, the foregoing step S301 may specifically include the following steps:

[0141] S601. Obtain an error equation set according to the change relationship between at least two component parameters and the battery voltage corresponding to multiple times when the test battery is in each theoretical characteristic, and the actual battery voltage.

[0142] Among them, taking the equivalent circuit model of the test battery as a second-order RC model as an example, the change relationship between the component parameters included in at least two component parameters and the battery voltage is the formula (4) mentioned in the foregoing embodiment. If the equivalent circuit model of the test battery is other models, other corresponding change relationships can be selected, and the specific content can refer to the prior art and will not be elaborated here.

[0143] Since this change relationship represents the relationship between the component parameters included in at least two component parameters and the battery voltage, that is, it represents that the corresponding battery voltage can be obtained through the component parameters included in at least two component parameters and this change relationship. And because there are multiple component parameters, that is, there are multiple unknowns, therefore, the nonlinear least squares problem can be solved by using a nonlinear minimization solution method. For example, an error equation can be constructed based on the actual battery voltage corresponding to one time and the above change relationship, and the corresponding error equation set can be obtained through multiple error equations constructed corresponding to multiple times.

[0144] Exemplarily, taking the actual battery voltages collected at m different times as an example, m error equations can be generated according to the actual battery voltages at these m different times and the above change relationship, forming an error equation set as shown below:

[0145] (7)

[0146] Wherein, refers to the difference between the actual battery voltage and the corresponding change relationship.

[0147] S602. Obtain at least two target component parameters corresponding to the actual battery voltage according to the error equation set.

[0148] In this step, for the convenience of understanding, the above example is continued for introduction.

[0149] According to this error equation set, an error function corresponding to the error equation set can be obtained. This error function can be, for example, a function representing the sum of squares of the errors of the error equation set, or an error function can also be generated based on ways such as errors and standard deviations of errors. This application does not limit this. Taking the sum of squares as an example, denote , then the error function can be, for example, as shown in the following formula (8):

[0150] (8)

[0151] By setting the initial value of, and using this initial value for iteration to minimize the error function (that is, minimizing the error), when the iteration reaches the preset convergence condition, the values of the component parameters corresponding to the current iteration obtained at this time can be used as the values of the target component parameters. Based on the values of the target component parameters, at least two target component parameters corresponding to the actual battery voltage can be obtained.

[0152] S603. Determine the mapping relationship between at least two component parameters and the SOC of the test battery according to the SOC corresponding to the actual battery voltage and at least two target component parameters.

[0153] For the at least two target component parameters obtained through the foregoing steps, the values of the respective target component parameters therein represent the values of the component parameters in the equivalent circuit model of the battery when the battery voltage is the actual battery voltage.

[0154] Therefore, based on the corresponding relationship between the actual battery voltage and at least two target component parameters, and the corresponding relationship between the actual battery voltage and the corresponding SOC, the mapping relationship between at least two component parameters and the SOC can be determined.

[0155] ​Next, for the specific acquisition of the above initial value, a detailed introduction will be given. Figure 7 FIG. is a schematic flow chart of another method for detecting the state of charge of a battery provided by an embodiment of the present application. As Figure 7 shown, continuing to take the equivalent circuit model of the battery as a second-order RC model as an example, at least one of the at least two component parameters includes the ohmic internal resistance, the polarization resistance (two polarization resistances are included in the second-order RC model), and the capacitance (two capacitances are included in the second-order RC model) (and it is ensured that the component parameters are at least two, for example, two polarization resistances can be included). Correspondingly, the initial value includes at least one of the initial value of the ohmic internal resistance, the initial value of the polarization resistance, and the initial value of the capacitance. In this case, taking the example that at least two of the component parameters include the ohmic internal resistance, the polarization resistance, and the capacitance, the acquisition of the initial value can be specifically achieved through the following steps:

[0156] S701. Determine the initial value of the ohmic internal resistance according to the transient voltage change of the test battery at the start of discharge.

[0157] In this step, since the battery voltage changes from 0 + to 0 - (that is, the change from to ) is mainly caused by the voltage drop across the ohmic resistance . Therefore, after the test battery is left standing for a sufficient long time (for example, 2 hours), the open-circuit voltage of the test battery (that is, the power supply voltage ) can be measured. Then, a known discharge current is suddenly applied at the start of discharge, and the transient voltage change at this moment is recorded. This transient voltage change is caused by the voltage drop across the ohmic resistance . Therefore, according to Ohm's law, the following formula (9) can be used to calculate the initial value of the ohmic internal resistance :

[0158] (9)

[0159] wherein, is equivalent to , that is, the battery voltage at the moment of discharge.

[0160] S702. Obtain the initial value of the polarization resistance according to the voltage value of the test battery when discharging to a steady state and the change relationship between at least two component parameters and the battery voltage.

[0161] In this step, since when the equivalent circuit model discharges to a specific duration, for example, when the discharge time is infinite, the capacitors are all charged, and the battery voltage converges to a stable value. Therefore, based on the above formula (4), the following formula (10) can be obtained in this case:

[0162] (10)

[0163] The polarization resistance is obtained by solving through the above formula (10). and the initial values.

[0164] Optionally, for the convenience of calculation, when there are multiple polarization resistances in the equivalent circuit model, the initial values of the multiple polarization resistances can be set to be the same. For example, in the above example, there are two polarization resistances, and the initial values of the two polarization resistances can be set to be the same to reduce the model complexity and improve the fitting speed and stability in the foregoing Figure 6 method. At this time, since is the same as , and the initial value of obtaining , the battery current, and the power supply voltage are known, then the polarization resistance can be calculated based on the stable value to which the battery voltage and converges.

[0165] S703. Obtain the initial value of the capacitance according to the variation relationship.

[0166] In this step, specifically, the exponential term in the foregoing formula (4) can be Taylor-expanded, and the terms of the second order and above after the Taylor expansion can be ignored, and the following formula (11) can be obtained

[0167] (11)

[0168] The capacitance and are obtained by solving through the above formula (10).

[0169] Optionally, for the convenience of calculation, when there are multiple capacitances in the equivalent circuit model, the initial values of the multiple capacitances can be set to be the same. For example, in the above example, there are two capacitances, and the initial values of the two capacitances can be set to be the same to reduce the model complexity and improve the fitting speed and stability in the foregoing Figure 6 method. At this time, since is the same as , and the initial value of obtaining , the battery current, and the power supply voltage are known, then the capacitance at the moment of is calculated to obtain the initial values of the capacitance and .

[0170] In a possible implementation, after determining the SOC of the target battery through the foregoing embodiments, the initial SOC of the target battery can be calibrated with this SOC. This initial SOC is the SOC parameter to be calibrated. For example, when the initial SOC is different from the determined SOC, the value of the initial SOC can be directly calibrated to the SOC of the determined target battery. Alternatively, by changing the change rate of the initial SOC, after a preset duration, the value after the change of the initial SOC is the same as the SOC of the target battery at the current moment, so as to calibrate the initial SOC of the target battery and prevent the SOC value from jumping during the calibration of the SOC.

[0171] Exemplarily, taking the case of preventing the SOC value from jumping during the calibration of the SOC as an example, specifically, the correction parameter of the change rate of the initial SOC can be determined according to the difference between the determined SOC of the target battery and the initial SOC. Then, based on the correction parameter, the change rate of the initial SOC is adjusted to gradually correct the initial SOC until the difference from the SOC of the target battery is less than or equal to the preset difference threshold.

[0172] Among them, the correction parameter is used to correct the change rate of the initial SOC. For example, during the discharge process, when the determined SOC of the target battery is greater than the initial SOC, it indicates that the discharge rate of the initial SOC is too large, resulting in inaccurate SOC. Therefore, a negative correction parameter can be determined to slow down the decrease rate of the initial SOC, so as to gradually correct the initial SOC during the discharge process, so that after a preset duration, the difference between the value of the initial SOC and the SOC of the target battery at that moment is less than or equal to the preset difference threshold, that is, the value of the initial SOC is closer to or the same as the SOC of the target battery at that moment, thus realizing the gradual correction of the initial SOC and improving the accuracy of the initial SOC.

[0173] Specifically, for example, the correlation between the difference between the determined SOC of the target battery and the initial SOC and the correction parameter can be established, and the corresponding correction parameter can be determined using the difference. For example, a linear mapping method can be adopted, that is, a fixed coefficient is set, and the difference is multiplied by this coefficient to obtain the correction parameter. Among them, the positive and negative of this correction parameter are related to the charge and discharge state of the target battery, the size relationship between the SOC of the target battery and the initial SOC. If in the charging state, the SOC of the target battery is greater than the initial SOC, it indicates that the change rate of the initial SOC is slow and inaccurate, then the correction parameter can take a positive value; conversely, if the SOC of the target battery is less than the initial SOC, it indicates that the change rate of the initial SOC is fast and inaccurate, then the correction parameter can take a negative value. If in the discharge state, it is opposite to the positive and negative values in the charging state.

[0174] The method provided by the embodiment of the present application determines the correction parameter of the change rate of the initial state of charge (SOC) according to the difference between the determined SOC of the target battery and the initial SOC. Then, based on the correction parameter, the change rate of the initial SOC is adjusted to gradually correct the initial SOC so that the difference from the SOC of the target battery is less than or equal to a preset difference threshold, thereby reducing the problem of SOC value jump caused by correcting the SOC and improving the user experience.

[0175] Figure 8 It is a schematic structural diagram of a state of charge detection device for a battery provided by an embodiment of the present application. As Figure 8 shown, the state of charge detection device for a battery may include: a processing module 11. In a possible implementation manner, it may further include: an acquisition module 12.

[0176] The processing module 11 is configured to determine the state of charge (SOC) of the target battery according to the current theoretical characteristics of the target battery, the values of at least two component parameters included in the equivalent circuit model of the target battery, and a target monotonic function. The target monotonic function is determined according to the actual battery voltages corresponding to the SOCs of the test battery when the test battery is in each theoretical characteristic. The test battery and the target battery are of the same type.

[0177] Optionally, the current theoretical characteristics include at least one of the current target battery temperature and the current target battery current.

[0178] Optionally, the acquisition module 12 is configured to acquire the values of at least two component parameters included in the equivalent circuit model of the target battery under the current target battery temperature and the current target battery current.

[0179] Optionally, the acquisition module 12 is specifically configured to acquire the current target battery temperature, the current target battery current, and the current target battery voltage of the target battery within a preset time period. Based on the equivalent circuit model of the target battery, as well as the current target battery temperature, the current target battery current, and the current target battery voltage, the values of at least two component parameters included in the equivalent circuit model are acquired.

[0180] Optionally, the processing module 11 is further configured to calibrate the initial SOC according to the determined SOC of the target battery when the initial SOC of the target battery is different from the determined SOC of the target battery.

[0181] Optionally, the processing module 11 is specifically configured to determine the correction parameter of the change rate of the initial SOC according to the difference between the determined SOC of the target battery and the initial SOC. Based on the correction parameter, the change rate of the initial SOC is adjusted to gradually correct the initial SOC so that the difference from the SOC of the target battery is less than or equal to a preset difference threshold.

[0182] Optionally, the processing module 11 is further configured to obtain a mapping relationship between at least two component parameters of the equivalent circuit model of the test battery and the SOC of the test battery according to the actual battery voltages corresponding to the states of charge (SOCs) of the test battery when the test battery is under the theoretical characteristics. According to the mapping relationship between at least two component parameters of the equivalent circuit model of the test battery and the SOC of the test battery under the theoretical characteristics, a target monotonic function is determined, and the target monotonic function characterizes the mapping relationship among the theoretical characteristics, the SOC, and at least two component parameters.

[0183] Optionally, the theoretical characteristics include at least one of the test battery temperature and the test battery current.

[0184] Optionally, the processing module 11 is specifically configured to determine a first function corresponding to each component parameter according to the mapping relationship between each component parameter of the equivalent circuit model of the test battery and the SOC under the theoretical characteristics. According to the first functions under the respective theoretical characteristics, a target monotonic function is generated. The first function characterizes the functional relationship between each component parameter and the SOC under each theoretical characteristic.

[0185] Optionally, the processing module 11 is specifically configured to determine an initial function according to the first functions. The coefficients corresponding to the component parameters in the initial function are adjusted to generate the target monotonic function under each theoretical characteristic.

[0186] Optionally, the processing module 11 is specifically configured to determine the derivative function of the initial function with respect to the SOC. According to the derivative function and a preset adjustment target, the target values of the coefficients that meet the preset adjustment target are determined. The target values of the coefficients are substituted into the initial function to generate the target monotonic function. The preset adjustment target includes: the value of the SOC is within the charge and discharge interval, and the derivative function is always greater than 0 or the derivative function is always less than 0.

[0187] Optionally, the processing module 11 is specifically configured to obtain an error equation set according to the variation relationship between at least two component parameters corresponding to multiple times and the battery voltage when the test battery is under each theoretical characteristic, and the actual battery voltage. At least two target component parameters corresponding to the actual battery voltage are obtained according to the error equation set. According to the SOC corresponding to the actual battery voltage and at least two target component parameters, a mapping relationship between at least two component parameters and the SOC of the test battery is determined.

[0188] Optionally, the processing module 11 is specifically configured to obtain an initial value of the error equation set. After iteratively updating the error equation set according to the initial value until the error function of the error equation set meets the preset convergence condition, at least two target component parameters are obtained.

[0189] Optionally, when the target component parameters include at least one of ohmic internal resistance, polarization resistance, and capacitance, the processing module 11 is specifically configured to determine the initial value of the ohmic internal resistance according to the transient voltage change of the test battery at the start of discharge; and / or, obtain the initial value of the polarization resistance according to the voltage value when the test battery discharges to a steady state and the change relationship between at least two component parameters and the battery voltage; and / or, obtain the initial value of the capacitance according to the change relationship.

[0190] Optionally, the change relationship includes at least two capacitances, and the initial values of the at least two capacitances are the same, and / or, the target mapping relationship includes at least two polarization resistances, and the initial values of the at least two polarization resistances are the same.

[0191] Optionally, the equivalent circuit model includes at least one of the following: Rint model, Thevenin model, PNGV model, RC model, Randles model, FOM model.

[0192] The state of charge detection device for a battery provided by the embodiments of the present application can execute the state of charge detection method in the above method embodiments, and its implementation principle and technical effects are similar, which will not be elaborated here.

[0193] The embodiments of the present application further provide a battery management system, and the battery management system is used to execute any one of the state of charge detection methods in the foregoing method embodiments.

[0194] The embodiments of the present application further provide a battery pack, and the battery pack includes the foregoing battery management system.

[0195] The embodiments of the present application further provide an electrical device, and the battery pack of the electrical device is a battery pack including the foregoing battery management system.

[0196] The embodiments of the present application further provide a computer program product, including a computer program, and when the computer program is executed by a processor, the above method is implemented.

[0197] The embodiments of the present application further provide a computer-readable storage medium, and a computer-executable instruction is stored in the computer-readable storage medium. When the processor executes the computer-executable instruction, the above method is implemented.

[0198] The above-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, a magnetic disk or an optical disc. The readable storage medium can be any available medium accessible by a general-purpose or special-purpose computer.

[0199] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an Application Specific Integrated Circuits (ASIC). Of course, the processor and the readable storage medium can also exist as discrete components in a device.

[0200] The division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Additionally, the couplings or direct couplings or communication connections shown or discussed between each other can be indirect couplings or communication connections through some interfaces, devices, or units, and can be in electrical, mechanical, or other forms.

[0201] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0202] Furthermore, in each embodiment of the present invention, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0203] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in each embodiment of the present invention. The aforementioned storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs, etc., which are various media that can store program codes.

[0204] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps including the above method embodiments; and the foregoing storage medium includes: various media such as ROM, RAM, magnetic disks, or optical discs that can store program codes.

[0205] Finally, it should be noted that: after considering the specification and practicing the invention disclosed herein, those skilled in the art will readily conceive of other embodiments of the present invention. The present invention is intended to cover any variations, uses, or adaptations of the present invention, which follow the general principles of the present invention and include known common knowledge or conventional technical means in the technical field not disclosed in the present invention. It is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is only limited by the appended claims.

Claims

1. A method for detecting a battery state of charge, characterized in that: The method comprises: The state of charge SOC of the target battery is determined according to the current theoretical characteristics of the target battery, the values ​​of at least two component parameters included in the equivalent circuit model of the target battery, and a target monotonic function. The target monotonic function is determined according to the actual battery voltage corresponding to each SOC of the test battery when the test battery is in each theoretical characteristic. The test battery and the target battery are the same type of batteries.

2. The method according to claim 1, characterized in that The current theoretical characteristic includes at least one of a current target battery temperature and a current target battery current.

3. The method according to claim 2, characterized in that Also includes: Acquire values ​​of at least two of the component parameters included in the equivalent circuit model of the target battery at the current target battery temperature and the current target battery current.

4. The method according to claim 3, characterized in that The acquiring of values ​​of at least two component parameters included in the equivalent circuit model of the target battery at the current target battery temperature and the current target battery current includes: Obtaining a current target battery temperature, a current target battery current, and a current target battery voltage of the target battery within a preset time period; Based on the equivalent circuit model of the target battery, the current target battery temperature, the current target battery current, and the current target battery voltage, values ​​of at least two of the component parameters included in the equivalent circuit model are acquired.

5. The method according to claim 1, characterized in that Also includes: When the initial SOC of the target battery is different from the determined SOC of the target battery, the initial SOC is calibrated according to the determined SOC of the target battery.

6. The method according to claim 5, characterized in that The step of calibrating the initial SOC according to the determined SOC of the target battery includes: Determining a correction parameter of a rate of change of the initial SOC according to the determined difference between the target battery SOC and the initial SOC; The change rate of the initial SOC is adjusted based on the correction parameter to gradually correct the initial SOC until the difference between the initial SOC and the SOC of the target battery is less than or equal to a preset difference threshold.

7. The method according to any one of claims 1 to 6, characterized in that: The method further comprises: According to the actual battery voltage corresponding to each SOC of the test battery when the test battery is under each theoretical characteristic, obtaining a mapping relationship between at least two component parameters of the equivalent circuit model of the test battery under each theoretical characteristic and the SOC of the test battery; According to the mapping relationship between at least two component parameters of the equivalent circuit model of the test battery under each of the theoretical characteristics and the SOC of the test battery, the target monotonic function is determined, and the target monotonic function characterizes the mapping relationship between the theoretical characteristics, the SOC, and at least two component parameters.

8. The method according to claim 7, characterized in that The theoretical characteristic includes at least one of a test battery temperature and a test battery current.

9. The method according to claim 8, characterized in that The determining of the target monotonic function according to the mapping relationship between at least two component parameters of the equivalent circuit model of the test battery under each of the theoretical characteristics and the SOC of the test battery comprises: Determine, according to the mapping relationship between the component parameters of the equivalent circuit model of the test battery under the theoretical characteristics and the SOC, a first function corresponding to each component parameter, wherein the first function represents the functional relationship between each component parameter and the SOC under the theoretical characteristics; The target monotonic function is generated according to each of the first functions under each of the theoretical characteristics.

10. The method according to claim 9, characterized in that The step of generating the target monotonic function according to each of the first functions under each of the theoretical characteristics comprises: Determine an initial function according to each of the first functions; The coefficients corresponding to the component parameters in the initial function are adjusted to generate the target monotonic function under the theoretical characteristics.

11. The method according to claim 10, characterized in that The step of adjusting the coefficients corresponding to the component parameters in the initial function to generate the target monotonic function includes: Determining a derivative of the initial function with respect to the SOC; According to the derivative function and a preset adjustment target, a target value of each coefficient that satisfies the preset adjustment target is determined, wherein the preset adjustment target includes: the SOC value is within the charge and discharge interval, and the derivative function is always greater than 0 or the derivative function is always less than 0; Substitute the target value of each coefficient into the initial function to generate the target monotonic function.

12. The method according to claim 8, characterized in that The step of obtaining a mapping relationship between at least two component parameters of an equivalent circuit model of the test battery under the theoretical characteristics and the SOC according to the actual battery voltage corresponding to each state of charge SOC of the test battery when the test battery is under the theoretical characteristics includes: Obtaining a group of error equations according to the changing relationship between at least two of the component parameters and the battery voltage corresponding to multiple times when the test battery is under each of the theoretical characteristics, and the actual battery voltage; Acquire at least two target component parameters corresponding to the actual battery voltage according to the error equation group; According to the SOC corresponding to the actual battery voltage and at least two of the target component parameters, a mapping relationship between at least two of the component parameters and the SOC of the test battery is determined.

13. The method according to claim 12, characterized in that The step of obtaining at least two target component parameters corresponding to the actual battery voltage according to the error equation group includes: Obtaining initial values ​​of the error equation group; After the error equation group is iteratively updated according to the initial value until the error function of the error equation group satisfies a preset convergence condition, at least two target component parameters are obtained.

14. The method according to claim 13, characterized in that The target component parameter includes at least one of an ohmic internal resistance, a polarization resistance, and a capacitance. The obtaining of the initial value of the error equation group includes: Determining the initial value of the ohmic internal resistance according to the transient voltage change of the test battery at the start of discharge; and / or, Obtaining the initial value of the polarization resistance according to the voltage value of the test battery when it is discharged to a steady state and the changing relationship between at least two of the component parameters and the battery voltage of the test battery; and / or, The initial value of the capacitance is obtained according to the change relationship.

15. The method according to claim 14, characterized in that The change relationship includes at least two of the capacitors, and the initial values ​​of at least two of the capacitors are the same; and / or, The target mapping relationship includes at least two polarization resistors, and initial values ​​of at least two polarization resistors are the same.

16. The method according to any one of claims 1 to 6, characterized in that: The equivalent circuit model includes at least one of the following: a Rint model, a Thevenin model, a PNGV model, an RC model, a Randles model, and a FOM model.

17. A battery charge state detection device, characterized in that: The device comprises: A processing module is used to determine the state of charge SOC of the target battery according to the current theoretical characteristics of the target battery, the values ​​of at least two component parameters included in the equivalent circuit model of the target battery, and a target monotonic function, wherein the target monotonic function is determined according to the actual battery voltage corresponding to each SOC of the test battery when the test battery is in each theoretical characteristic, and the test battery and the target battery are the same type of batteries.

18. A battery management system, characterized in that: The battery management system is used to execute the battery charge state detection method as described in any one of claims 1-16.

19. A battery pack, characterized in that: The battery pack includes the battery management system described in claim 18.

20. An electrical equipment, characterized in that: The battery pack of the electrical equipment is the battery pack according to claim 19.

21. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 16 when executed by a processor.

22. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 16 when being executed by a processor.

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