Battery charge state estimation method, device, equipment, medium and product

Abstract

The invention provides a method, a device, equipment, a medium and a product for estimating the state of charge of a battery, and relates to the technical field of batteries, and the method comprises the steps: obtaining a pre-constructed discharge characteristic curve of a target battery in a constant power state; and acquiring the current voltage and current of the target battery, and estimating the target state of charge of the target battery based on the current voltage, the current current and the discharge characteristic curve. According to the technical scheme, the data of the target battery except the constant power state does not need to be obtained, compared with the prior art, less experimental data are depended on, the charge state of the target battery is estimated based on the combination of the current voltage, the current current and the discharge characteristic curve of the target battery, higher accuracy is achieved, and in addition, the method is suitable for popularization and application. According to the method, the charge states of various batteries in the constant power state can be determined, and compared with a method for constructing an electrochemical model, the method has a wider application range.

Description

Technical Field

[0001] The present invention relates to the field of battery technology, and in particular to a method, device, equipment, medium and product for estimating the state of charge of a battery. Background Art

[0002] As an important component of energy storage systems and other fields, accurate estimation of the state of charge (SOC) of lithium-ion batteries is crucial to system performance and safety.

[0003] At present, the existing technology often adopts the estimation method based on electrochemical model. However, the estimation method based on electrochemical model may face problems such as low accuracy and limited application scope. Especially when the charging and discharging curve of lithium-ion battery changes nonlinearly, it is more difficult to accurately estimate SOC. In addition, the existing technology also needs to rely on a large amount of experimental data for batteries. Summary of the invention

[0004] The present invention provides a method, device, equipment, medium and product for estimating the state of charge of a battery, so as to solve the defects in the prior art that a large amount of experimental data on the battery is relied on in the process of estimating the state of charge, and the accuracy is low and the scope of application is limited. The technical solution of the present invention does not need to obtain data of the target battery outside the constant power state, and relies on less experimental data than the prior art. In addition, the technical solution of the present invention estimates the state of charge of the target battery based on the combination of the current voltage, current current and discharge characteristic curve of the target battery, and has higher accuracy and a wider scope of application.

[0005] The present invention provides a method for estimating the state of charge of a battery, comprising the following steps.

[0006] Obtaining a pre-built discharge characteristic curve of a target battery under a constant power state; A current voltage and a current current of the target battery are acquired, and a target state of charge of the target battery is estimated based on the current voltage, the current current and the discharge characteristic curve.

[0007] According to a method for estimating the state of charge of a battery provided by the present invention, a discharge characteristic curve of a target battery under a constant power state is constructed, including: Acquire first voltage data and first current data of the target battery when fully charged in a constant power state, and second voltage data and second current data of the target battery when fully discharged in a constant power state; The discharge characteristic curve is constructed based on the first voltage data, the first current data, the second voltage data, and the second current data.

[0008] According to a method for estimating a state of charge of a battery provided by the present invention, the method for estimating a target state of charge of the target battery based on the current voltage, the current current and the discharge characteristic curve includes: Determining characteristic parameters based on the discharge characteristic curve; the characteristic parameters represent a parameter relationship between the voltage, current, and state of charge of the target battery; Determining a first state of charge of the target battery based on a ratio of the current current to the current voltage and the characteristic parameter; determining a second state of charge of the target battery based on the current current by an ampere-hour integration method; The target state of charge is determined based on the first state of charge and the second state of charge.

[0009] According to a method for estimating a state of charge of a battery provided by the present invention, determining the target state of charge based on the first state of charge and the second state of charge includes: Determine, by recursive least squares method, a first weight corresponding to the first state of charge and a second weight corresponding to the second state of charge based on the first state of charge and the second state of charge; The target state of charge is determined based on the first state of charge, the second state of charge, the first weight, and the second weight.

[0010] According to a method for estimating a state of charge of a battery provided by the present invention, the method of determining a first weight corresponding to the first state of charge and a second weight corresponding to the second state of charge based on the first state of charge and the second state of charge by a recursive least squares method includes: constructing a recursive least squares input vector based on the first state of charge and the second state of charge; Based on the recursive least squares input vector, a weight vector is calculated in real time by the recursive least squares method until the slope of the weight vector is zero, and the first weight and the second weight are determined based on the weight vector corresponding to the moment when the slope is zero.

[0011] According to a method for estimating a state of charge of a battery provided by the present invention, the method of calculating a weight vector in real time by using the recursive least squares method based on the recursive least squares input vector includes: For each moment corresponding to the first state of charge and the second state of charge, determine a gain matrix corresponding to the current moment based on a preset forgetting factor and a recursive least squares input vector corresponding to the current moment, and a covariance matrix corresponding to the previous moment; Determine the covariance matrix corresponding to the current moment based on the preset forgetting factor and the gain matrix corresponding to the current moment, and the covariance matrix corresponding to the previous moment; Determine a weight vector corresponding to the current moment based on the gain matrix and the third state of charge corresponding to the current moment, and the weight vector corresponding to the previous moment; the third state of charge is determined based on the first current data and the second current data; Among them, for the starting moment, the covariance matrix and weight vector corresponding to the previous moment are both preset.

[0012] The present invention also provides a battery state of charge estimation device, comprising the following modules: A construction module, used to obtain a pre-constructed discharge characteristic curve of a target battery under a constant power state; An estimation module is used to obtain a current voltage and a current current of the target battery, and estimate a target state of charge of the target battery based on the current voltage, the current current and the discharge characteristic curve.

[0013] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for estimating the state of charge of a battery as described above is implemented.

[0014] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for estimating the state of charge of a battery as described in any one of the above is implemented.

[0015] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method for estimating the state of charge of a battery as described above is implemented.

[0016] The battery state of charge estimation method, device, equipment, medium and product provided by the present invention obtain a pre-constructed discharge characteristic curve of a target battery under a constant power state; obtain the current voltage and current current of the target battery, and estimate the target state of charge of the target battery based on the current voltage, current current and discharge characteristic curve. The technical solution of the present invention does not need to obtain data of the target battery outside the constant power state, and relies on less experimental data than the prior art. The technical solution of the present invention estimates the state of charge of the target battery based on a combination of the current voltage, current current and discharge characteristic curve of the target battery, and has higher accuracy. In addition, the present invention can determine the state of charge of various types of batteries under a constant power state, and has a wider range of application than the method of constructing an electrochemical model. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 It is a flow chart of the method for estimating the state of charge of a battery provided by the present invention.

[0019] Figure 2 It is a structural schematic diagram of a battery state of charge estimation device provided by the present invention.

[0020] Figure 3 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] In view of the above problems in the prior art, the present invention provides a method for estimating the state of charge of a battery. Figure 1 FIG. 1 is a flow chart of a method for estimating the state of charge of a battery provided by the present invention. Figure 1 As shown, the method includes the following steps 110 and 120.

[0023] Step 110: Obtain a pre-constructed discharge characteristic curve of the target battery under a constant power state.

[0024] Specifically, a pre-constructed discharge characteristic curve of the target battery under a constant power state may be obtained, and the discharge characteristic curve may characterize the relationship among the voltage, current and state of charge of the target battery.

[0025] In one embodiment, the discharge characteristic curve of the target battery under constant power state is constructed, including: Acquire first voltage data and first current data of the target battery when fully charged in a constant power state, and second voltage data and second current data of the target battery when fully discharged in a constant power state; The discharge characteristic curve is constructed based on the first voltage data, the first current data, the second voltage data, and the second current data.

[0026] Specifically, under the premise of ensuring that the target battery is in a constant power state, the first voltage data and the first current data of the target battery under full charge can be obtained, and the second voltage data and the second current data of the target battery under full discharge can also be obtained.

[0027] Furthermore, a discharge characteristic curve may be constructed based on the first voltage data, the first current data, the second voltage data, and the second current data.

[0028] In the above embodiment, the first voltage data and the first current data of the target battery when fully charged under the constant power state, as well as the second voltage data and the second current data of the target battery when fully discharged under the constant power state are obtained. Only the voltage data and the current data under the constant power state are required, which reduces the demand for experimental data, and the constructed discharge characteristic curve can more accurately reflect the relationship among the voltage, current and charge state of the target battery.

[0029] Step 120: Acquire the current voltage and current of the target battery, and estimate the target state of charge of the target battery based on the current voltage, the current current and the discharge characteristic curve.

[0030] Specifically, the current voltage and current of the target battery can be acquired in real time through the sensor, wherein the acquisition accuracy of the current voltage is not less than 1 millivolt, the acquisition accuracy of the current current is not less than 1%, and the sampling rates of the current voltage and current current are not less than 100 Hz.

[0031] In one embodiment, estimating the target state of charge of the target battery based on the current voltage, the current current and the discharge characteristic curve includes: Determining characteristic parameters based on the discharge characteristic curve; the characteristic parameters represent a parameter relationship between the voltage, current, and state of charge of the target battery; Determining a first state of charge of the target battery based on a ratio of the current current to the current voltage and the characteristic parameter; determining a second state of charge of the target battery based on the current current by an ampere-hour integration method; The target state of charge is determined based on the first state of charge and the second state of charge.

[0032] Specifically, the characteristic parameters can be determined based on the discharge characteristic curve, and the current With the current voltage Ratio , that is .

[0033] Furthermore, the first state of charge of the target battery may be determined based on the ratio and the characteristic parameter. This process may be represented by the following formula:

[0034] in, represents the first state of charge, , , , , , , , and All represent characteristic parameters. represents the natural exponential function.

[0035] In addition, the second state of charge of the target battery can be determined based on the current by the ampere-hour integration method. The ampere-hour integration method is a conventional algorithm for estimating the SOC, which estimates the SOC of the battery by integrating the charge and discharge current of the battery. There are methods in the prior art that estimate the SOC of the battery only by the ampere-hour integration method, but the accuracy of the SOC estimated by the ampere-hour integration method alone is low.

[0036] Further, a target state of charge of the target battery may be determined based on the first state of charge and the second state of charge.

[0037] In the above embodiment, the first state of charge of the target battery is determined based on the ratio of the current current to the current voltage and the characteristic parameters. The first state of charge can more accurately reflect the actual state of charge of the target battery. Furthermore, the second state of charge can be estimated based on the ampere-hour integration method. The combination of the states of charge solved by different methods can further improve the accuracy of the target state of charge.

[0038] In one embodiment, determining the target state of charge based on the first state of charge and the second state of charge includes: Determine, by recursive least squares method, a first weight corresponding to the first state of charge and a second weight corresponding to the second state of charge based on the first state of charge and the second state of charge; The target state of charge is determined based on the first state of charge, the second state of charge, the first weight, and the second weight.

[0039] Specifically, Recursive Least Squares (RLS) is an online estimation method for recursively estimating the parameters of a linear system. The first weight corresponding to the first state of charge and the second weight corresponding to the second state of charge can be determined based on the first state of charge and the second state of charge by the recursive least squares method. Further, the target state of charge can be determined based on the first state of charge, the second state of charge, the first weight and the second weight. Target state of charge It can be expressed by the following formula:

[0040] in, represents the first weight, represents the second weight, Indicates the second state of charge.

[0041] In the above embodiment, the first weight and the second weight are determined by the recursive least squares method, which has the characteristics of strong real-time performance, high computational efficiency, strong adaptability, high robustness and good stability, making the determination of the first weight and the second weight more reasonable and efficient, and further determining the target state of charge based on the first state of charge, the second state of charge, the first weight and the second weight, so that the target state of charge is more accurate and closer to the actual state of charge of the target battery.

[0042] In one embodiment, the determining, based on the first state of charge and the second state of charge, a first weight corresponding to the first state of charge and a second weight corresponding to the second state of charge by a recursive least squares method includes: constructing a recursive least squares input vector based on the first state of charge and the second state of charge; Based on the recursive least squares input vector, a weight vector is calculated in real time by the recursive least squares method until the slope of the weight vector is zero, and the first weight and the second weight are determined based on the weight vector corresponding to the moment when the slope is zero.

[0043] Specifically, a recursive least squares input vector may be constructed based on the first state of charge and the second state of charge. The recursive least squares input vector It can be expressed by the following formula:

[0044] in, Indicates time. , Indicates the preset initial state of charge. Indicates the nominal capacity of the battery.

[0045] Furthermore, the recursive least squares input vector , the weight vector is iteratively calculated by the recursive least square method until the slope of the weight vector is zero, and the first weight and the second weight are determined based on the weight vector corresponding to the moment when the slope is zero. The slope of the weight vector is zero, which means that the weight vector representing multiple consecutive moments does not change.

[0046] For example, the slope of the weight vector It can be determined according to the following formula:

[0047] in, represents the weight vector corresponding to the previous moment, represents transpose, Indicates a third state of charge, the third state of charge is determined based on the first current data and the second current data, the third state of charge It can be determined according to the following formula:

[0048]

[0049] in, Indicates the first current data The current at the moment, Indicates charging time. represents the sum of the first current data when fully charged, Indicates the second current data The current at the moment, Indicates the discharge time, Indicates the sum of the second current data when fully discharged.

[0050] The relationship between the weight vector, the first weight, and the second weight can be expressed by the following formula:

[0051] in, represents the weight vector, represents the first weight, Represents the second weight.

[0052] In the above embodiment, the optimal weight vector is determined through iterative calculation, so that the first weight and the second weight can be made more reasonable.

[0053] In one embodiment, the real-time calculation of the weight vector by the recursive least squares method based on the recursive least squares input vector includes: For each moment corresponding to the first state of charge and the second state of charge, determine a gain matrix corresponding to the current moment based on a preset forgetting factor and a recursive least squares input vector corresponding to the current moment, and a covariance matrix corresponding to the previous moment; Determine the covariance matrix corresponding to the current moment based on the preset forgetting factor and the gain matrix corresponding to the current moment, and the covariance matrix corresponding to the previous moment; Determine a weight vector corresponding to the current moment based on the gain matrix and the third state of charge corresponding to the current moment, and the weight vector corresponding to the previous moment; the third state of charge is determined based on the first current data and the second current data; Among them, for the starting moment, the covariance matrix and weight vector corresponding to the previous moment are both preset.

[0054] Specifically, for each time instant corresponding to the first state of charge and the second state of charge, the recursive least squares input vector corresponding to the current time instant can be and preset forgetting factor , and the covariance matrix corresponding to the previous moment Determine the gain matrix corresponding to the current moment , the gain matrix It can be expressed by the following formula:

[0055] Among them, the preset forgetting factor is a regularization parameter that prevents the denominator from being zero and controls the smoothness of the estimate. It can be set as needed, and is usually between 0.95 and 0.99.

[0056] Furthermore, the covariance matrix corresponding to the current moment can be determined based on the gain matrix and the preset forgetting factor corresponding to the current moment, as well as the covariance matrix corresponding to the previous moment: , the process can be expressed by the following formula:

[0057] The weight vector corresponding to the current moment can also be determined based on the gain matrix and the third state of charge corresponding to the current moment, and the weight vector corresponding to the previous moment. , the process can be expressed by the following formula:

[0058] It is easy to understand that for the starting moment, the covariance matrix and weight vector corresponding to the previous moment are preset, that is, and These are preset values.

[0059] In the above embodiment, the determination of the weight vector can be adjusted dynamically through the recursive least squares calculation, and the experimenter can also adjust the preset parameters as needed to control the weight vector, thereby controlling the first weight and the second weight.

[0060] The method for estimating the state of charge of a battery provided by the present invention obtains a pre-constructed discharge characteristic curve of a target battery under a constant power state; obtains the current voltage and current current of the target battery, and estimates the target state of charge of the target battery based on the current voltage, current current and discharge characteristic curve. The technical solution of the present invention does not need to obtain data of the target battery outside the constant power state, and relies on less experimental data than the prior art. The technical solution of the present invention estimates the state of charge of the target battery based on a combination of the current voltage, current current and discharge characteristic curve of the target battery, and has higher accuracy. In addition, the present invention can determine the state of charge of various types of batteries under a constant power state, and has a wider range of application than the method of constructing an electrochemical model.

[0061] The battery state of charge estimation device provided by the present invention is described below. The battery state of charge estimation device described below and the battery state of charge estimation method described above can be referred to each other.

[0062] Figure 2 is a schematic diagram of the structure of the battery state of charge estimation device provided by the present invention, such as Figure 2 As shown, the battery state of charge estimation device 200 includes the following modules: A construction module 210 is used to obtain a pre-constructed discharge characteristic curve of a target battery under a constant power state; The estimation module 220 is used to obtain the current voltage and current of the target battery, and estimate the target state of charge of the target battery based on the current voltage, the current current and the discharge characteristic curve.

[0063] In one embodiment, the construction module 210 is specifically used to: Acquire first voltage data and first current data of the target battery when fully charged in a constant power state, and second voltage data and second current data of the target battery when fully discharged in a constant power state; The discharge characteristic curve is constructed based on the first voltage data, the first current data, the second voltage data, and the second current data.

[0064] In one embodiment, the estimation module 220 is specifically configured to: Determining characteristic parameters based on the discharge characteristic curve; the characteristic parameters represent a parameter relationship between the voltage, current, and state of charge of the target battery; Determining a first state of charge of the target battery based on a ratio of the current current to the current voltage and the characteristic parameter; determining a second state of charge of the target battery based on the current current by an ampere-hour integration method; The target state of charge is determined based on the first state of charge and the second state of charge.

[0065] In one embodiment, the estimation module 220 is further configured to: Determine, by recursive least squares method, a first weight corresponding to the first state of charge and a second weight corresponding to the second state of charge based on the first state of charge and the second state of charge; The target state of charge is determined based on the first state of charge, the second state of charge, the first weight, and the second weight.

[0066] In one embodiment, the estimation module 220 is further configured to: constructing a recursive least squares input vector based on the first state of charge and the second state of charge; Based on the recursive least squares input vector, a weight vector is calculated in real time by the recursive least squares method until the slope of the weight vector is zero, and the first weight and the second weight are determined based on the weight vector corresponding to the moment when the slope is zero.

[0067] In one embodiment, the estimation module 220 is further configured to: For each moment corresponding to the first state of charge and the second state of charge, determine a gain matrix corresponding to the current moment based on a preset forgetting factor and a recursive least squares input vector corresponding to the current moment, and a covariance matrix corresponding to the previous moment; Determine the covariance matrix corresponding to the current moment based on the preset forgetting factor and the gain matrix corresponding to the current moment, and the covariance matrix corresponding to the previous moment; Determine a weight vector corresponding to the current moment based on the gain matrix and the third state of charge corresponding to the current moment, and the weight vector corresponding to the previous moment; the third state of charge is determined based on the first current data and the second current data; Among them, for the starting moment, the covariance matrix and weight vector corresponding to the previous moment are both preset.

[0068] The battery state of charge estimation device provided by the present invention obtains a pre-constructed discharge characteristic curve of a target battery under a constant power state; obtains the current voltage and current current of the target battery, and estimates the target state of charge of the target battery based on the current voltage, current current and discharge characteristic curve. The technical solution of the present invention does not need to obtain data of the target battery outside the constant power state, and relies on less experimental data than the prior art. The technical solution of the present invention estimates the state of charge of the target battery based on a combination of the current voltage, current current and discharge characteristic curve of the target battery, and has higher accuracy. In addition, the present invention can determine the state of charge of various types of batteries under a constant power state, and has a wider range of application than the method of constructing an electrochemical model.

[0069] Figure 3 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 3 As shown, the electronic device may include: a processor 310, a communication interface 320, a memory 330 and a communication bus 340, wherein the processor 310, the communication interface 320 and the memory 330 communicate with each other through the communication bus 340. The processor 310 may call the logic instructions in the memory 330 to execute the battery state of charge estimation method, which includes: Obtaining a pre-built discharge characteristic curve of a target battery under a constant power state; A current voltage and a current current of the target battery are acquired, and a target state of charge of the target battery is estimated based on the current voltage, the current current and the discharge characteristic curve.

[0070] In addition, the logic instructions in the above-mentioned memory 330 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0071] On the other hand, the present invention further provides a computer program product, the computer program product includes a computer program, the computer program can be stored in a non-transitory computer-readable storage medium, when the computer program is executed by a processor, the computer can execute the battery state of charge estimation method provided by the above methods, the method comprising: Obtaining a pre-built discharge characteristic curve of a target battery under a constant power state; A current voltage and a current current of the target battery are acquired, and a target state of charge of the target battery is estimated based on the current voltage, the current current and the discharge characteristic curve.

[0072] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the computer program is executed by a processor to perform the battery state of charge estimation method provided by the above methods, the method comprising: Obtaining a pre-built discharge characteristic curve of a target battery under a constant power state; A current voltage and a current current of the target battery are acquired, and a target state of charge of the target battery is estimated based on the current voltage, the current current and the discharge characteristic curve.

[0073] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0074] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0075] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for estimating a battery state of charge, characterized in that: include: Obtaining a pre-built discharge characteristic curve of a target battery under a constant power state; Obtaining the current voltage and current of the target battery; Determining characteristic parameters based on the discharge characteristic curve; the characteristic parameters represent a parameter relationship between the voltage, current, and state of charge of the target battery; Determining a first state of charge of the target battery based on a ratio of the current current to the current voltage and the characteristic parameter; determining a second state of charge of the target battery based on the current current by an ampere-hour integration method; The target state of charge is determined based on the first state of charge and the second state of charge.

2. The method for estimating the state of charge of a battery according to claim 1, characterized in that: The discharge characteristic curve of the target battery constructed under constant power state includes: Acquire first voltage data and first current data of the target battery when fully charged in a constant power state, and second voltage data and second current data of the target battery when fully discharged in a constant power state; The discharge characteristic curve is constructed based on the first voltage data, the first current data, the second voltage data, and the second current data.

3. The method for estimating the state of charge of a battery according to claim 1, characterized in that: The determining the target state of charge based on the first state of charge and the second state of charge includes: Determine, by recursive least squares method, a first weight corresponding to the first state of charge and a second weight corresponding to the second state of charge based on the first state of charge and the second state of charge; The target state of charge is determined based on the first state of charge, the second state of charge, the first weight, and the second weight.

4. The method for estimating the state of charge of a battery according to claim 3, characterized in that: The determining, based on the first state of charge and the second state of charge, a first weight corresponding to the first state of charge and a second weight corresponding to the second state of charge by a recursive least squares method includes: constructing a recursive least squares input vector based on the first state of charge and the second state of charge; Based on the recursive least squares input vector, a weight vector is calculated in real time by the recursive least squares method until the slope of the weight vector is zero, and the first weight and the second weight are determined based on the weight vector corresponding to the moment when the slope is zero.

5. The method for estimating the state of charge of a battery according to claim 4, characterized in that: The step of calculating the weight vector in real time by the recursive least squares method based on the recursive least squares input vector comprises: For each moment corresponding to the first state of charge and the second state of charge, determine a gain matrix corresponding to the current moment based on a preset forgetting factor and a recursive least squares input vector corresponding to the current moment, and a covariance matrix corresponding to the previous moment; Determine the covariance matrix corresponding to the current moment based on the preset forgetting factor and the gain matrix corresponding to the current moment, and the covariance matrix corresponding to the previous moment; Determine a weight vector corresponding to the current moment based on the gain matrix and the third state of charge corresponding to the current moment, and the weight vector corresponding to the previous moment; the third state of charge is determined based on the first current data and the second current data; Among them, for the starting moment, the covariance matrix and weight vector corresponding to the previous moment are both preset.

6. A battery state of charge estimation device, characterized in that: include: A construction module is used to obtain a pre-constructed discharge characteristic curve of a target battery under a constant power state; An estimation module, used for obtaining a current voltage and a current current of the target battery; Determining characteristic parameters based on the discharge characteristic curve; the characteristic parameters represent a parameter relationship between the voltage, current, and state of charge of the target battery; Determining a first state of charge of the target battery based on a ratio of the current current to the current voltage and the characteristic parameter; determining a second state of charge of the target battery based on the current current by an ampere-hour integration method; The target state of charge is determined based on the first state of charge and the second state of charge.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the method for estimating the state of charge of a battery as claimed in any one of claims 1 to 5 is implemented.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for estimating the state of charge of a battery as claimed in any one of claims 1 to 5 is implemented.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for estimating the state of charge of a battery as claimed in any one of claims 1 to 5 is implemented.

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