Method and device for automatically identifying parameters of an electrochemical model, storage medium

Abstract

The application discloses a method and device for automatically identifying electrochemical model parameters, and a storage medium. The method comprises the following steps: obtaining electrochemical model parameters of a reference battery cell; the reference battery cell and a target battery cell belong to the same type; adjusting an identification range of the electrochemical model parameters of the target battery cell according to the electrochemical model parameters and capacity parameters of the reference battery cell; the capacity parameters comprise a nominal capacity or a state of charge; performing parameter identification on the electrochemical model based on the identification range by using a preset identification algorithm to obtain the electrochemical model parameters of the target battery cell. The application can automatically adjust the identification range of the electrochemical model parameters of the target battery cell, and improve the parameter identification efficiency.

Description

Technical Field

[0001] This application relates to the field of energy storage technology, and in particular to a method and apparatus for parameter identification of an electrochemical model of a lithium battery, and a storage medium. Background Technology

[0002] Electrochemical models of lithium batteries can simulate the charging and discharging process of lithium batteries relatively accurately. However, electrochemical model simulation involves dozens of physical parameters that need to be input, such as solid-phase diffusion coefficient, conductivity, and particle size of active materials. Even obtaining these parameters through experiments is difficult and time-consuming and costly.

[0003] Furthermore, as batteries age, the electrochemical model parameters of the batteries will also change. In a large energy storage power station, there may be hundreds of thousands of battery cells. These cells will age to varying degrees, so it is necessary to frequently identify the parameters of the cells in order to obtain more accurate model parameters. Each time the parameters are identified, the range of parameters must be adjusted accordingly. The range of parameters is often obtained by disassembling the cells, which is time-consuming and labor-intensive, reducing the efficiency of parameter identification. Summary of the Invention

[0004] To address the aforementioned technical problems, this application provides a method, apparatus, and storage medium for automatic identification of electrochemical model parameters.

[0005] Specifically, the technical solution of this application is as follows:

[0006] In a first aspect, this application provides a method for automatic identification of electrochemical model parameters, including:

[0007] Obtain the electrochemical model parameters of a reference cell; the reference cell and the target cell belong to the same type.

[0008] Based on the electrochemical model parameters and capacity parameters of the reference cell, the identification range of the electrochemical model parameters of the target cell is adjusted; the capacity parameters include nominal capacity or state of charge.

[0009] Based on the identification range, a preset identification algorithm is used to identify the parameters of the electrochemical model to obtain the electrochemical model parameters of the target cell.

[0010] In some embodiments, adjusting the identification range of the electrochemical model parameters of the target cell based on the electrochemical model parameters and capacity parameters of the reference cell includes:

[0011] The electrode area range of the target battery cell is determined according to the following formula:

[0012]

[0013]

[0014] Where Amin and Amax are the lower and upper limits of the electrode area of ​​the target battery cell, respectively; α1 and β1 are the adjustment coefficients for the lower and upper limits of the area, respectively; and Q is the nominal capacity of the target battery cell. ref A represents the nominal capacity of the reference cell. ref The electrode area of ​​the reference cell is given.

[0015] In some embodiments, adjusting the identification range of the electrochemical model parameters of the target cell based on the electrochemical model parameters and capacity parameters of the reference cell includes:

[0016] Obtain the identification data of the target battery cell;

[0017] Based on the identification data, the initial state of charge value of the target battery cell is obtained;

[0018] Based on the initial positive / negative electrode concentrations of the reference cell in the first and second states of charge and the positive / negative electrode states of charge of the reference cell, the estimated values ​​of the initial positive / negative electrode concentrations of the target cell are calculated.

[0019] The range of initial electrode concentrations for the target battery cell is determined using the following formula:

[0020] Cmax=max(α2*C est，k C ref，k，1 );

[0021] Cmin=min(β2*C est，k C ref，k，2 );

[0022] Where Cmax is the upper limit of the initial electrode concentration of the target battery cell, Cmin is the lower limit of the initial electrode concentration of the target battery cell, α2 and β1 are the upper and lower limit adjustment coefficients, k represents the polarity of the electrode, and C est，k C is an estimated value of the initial concentration of the positive / negative electrode of the target battery cell. ref，k，1 C ref，k，2 These represent the initial electrode concentrations of the reference cell in the first state of charge and the second state of charge, respectively.

[0023] In some embodiments, obtaining the initial state of charge (SOC) value of the target cell based on the identification data includes:

[0024] If the identification data of the target cell contains state of charge data, the initial state of charge value is directly extracted from the state of charge data;

[0025] If the identification data of the target cell does not include the state of charge data, the open-circuit voltage value is extracted from the identification data of the target cell, and the initial state of charge value is determined according to the relationship between the open-circuit voltage and the state of charge of the reference cell.

[0026] In some implementations, the relationship between the open-circuit voltage and the state of charge of the reference cell is obtained through the following steps:

[0027] Based on preset operating conditions, the electrochemical model parameters of the reference cell are input into the electrochemical model for simulation to obtain the relationship between the open-circuit voltage and the state of charge of the reference cell.

[0028] Secondly, this application provides a device for automatic identification of electrochemical model parameters, comprising:

[0029] The acquisition module is used to acquire the electrochemical model parameters of the reference cell; the reference cell and the target cell belong to the same type.

[0030] The determination module is used to adjust the identification range of the electrochemical model parameters of the target cell based on the electrochemical model parameters and capacity parameters of the reference cell; the capacity parameters include nominal capacity or state of charge.

[0031] The identification module is used to input the identification data of the target cell into a preset electrochemical model for simulation based on the identification range, and to identify the electrochemical model parameters of the target cell.

[0032] In some implementations, the determining module is configured to determine the electrode area range of the target battery cell according to the following formula:

[0033]

[0034]

[0035] Where Amin and Amax are the lower and upper limits of the electrode area of ​​the target battery cell, respectively; α1 and β1 are the adjustment coefficients for the lower and upper limits of the area, respectively; and Q is the nominal capacity of the target battery cell. ref A represents the nominal capacity of the reference cell. ref The electrode area of ​​the reference cell is given.

[0036] In some implementations, the determining module includes:

[0037] The first acquisition unit is used to acquire the identification data of the target battery cell;

[0038] The second acquisition unit is used to acquire the initial state of charge value of the target cell based on the identification data.

[0039] The calculation unit is used to calculate an estimated value of the initial concentration of the positive / negative electrode of the target cell based on the initial concentration of the positive / negative electrode of the reference cell in the first and second states of charge and the positive / negative state of charge of the reference cell.

[0040] The calculation unit is also configured to determine the range of the initial electrode concentration of the target battery cell according to the following formula:

[0041] Cmax=max(α2*C est，k C ref，k，1 );

[0042] Cmin=min(β2*C est，k C ref，k，2 );

[0043] Where Cmax is the upper limit of the initial electrode concentration of the target battery cell, Cmin is the lower limit of the initial electrode concentration of the target battery cell, α2 and β1 are the upper and lower limit adjustment coefficients, k represents the polarity of the electrode, and C est，k C is an estimated value of the initial concentration of the positive / negative electrode of the target battery cell. ref，k，1 C ref，k，2 These represent the initial electrode concentrations of the reference cell in the first state of charge and the second state of charge, respectively.

[0044] In some embodiments, the second acquisition unit is configured to directly extract the initial state of charge value from the identification data if the identification data of the target cell contains the initial state of charge value;

[0045] The second acquisition unit is further configured to extract the open-circuit voltage value from the identification data of the target cell if the initial state of charge value is not included in the identification data of the target cell; and determine the initial state of charge value according to the relationship between the open-circuit voltage and the state of charge of the reference cell.

[0046] Thirdly, this application provides a storage medium storing at least one instruction, which is loaded and executed by a processor to perform the operations performed by the method for automatic identification of electrochemical model parameters described in any of the preceding claims.

[0047] Compared with the prior art, this application has at least one of the following advantages:

[0048] This application uses the electrochemical model parameters of a reference cell as a reference, and can automatically adjust the identification range of the electrochemical model parameters of the target cell, thereby improving the parameter identification efficiency. Attached Figure Description

[0049] The following is a brief introduction to the accompanying drawings used in the description of the embodiments of this application:

[0050] Figure 1 This is a flowchart of an embodiment of the method for automatic identification of electrochemical model parameters in this application;

[0051] Figure 2 This is a schematic diagram of the OCV-SOC relationship curve of the reference cell in this application;

[0052] Figure 3 This is a structural block diagram of one embodiment of the device for automatic identification of electrochemical model parameters in this application. Detailed Implementation

[0053] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the specific implementation methods of this application will be described below with reference to the accompanying drawings. The accompanying drawings described below are merely some embodiments of this application. For those skilled in the art, other drawings and other implementation methods can be obtained based on these drawings without creative effort. Adjustments and improvements made without departing from the concept of this application are all within the protection scope of this application.

[0054] To keep the drawings concise, the figures in this application only schematically show the parts relevant to this application, and they do not represent the actual structure of the product. Furthermore, to make the drawings concise and easy to understand, some figures only schematically show parts of components with the same structure or function; in reality, there may be more or fewer components with the same structure or function.

[0055] In this application, unless otherwise expressly specified and limited, ordinal numbers, such as "first," "second," etc., are used only to distinguish and describe related objects, and should not be construed as indicating or implying the relative importance or order between related objects; furthermore, they do not represent the number of related objects. "And / or" is used to describe the relationship between related objects, which includes any relationship between related objects, such as "a and / or b" including: "a alone," "b alone," or "a and b." The terms "installation" and "connection" should be interpreted broadly. For example, "installation" can be direct installation or installation through other components; "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be a connection within two elements. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0056] Currently, to accurately simulate the charging and discharging process inside lithium batteries, electrochemical models (P2D, pseudo-two-dimensional models) are often used for simulation. Electrochemical models involve multiple partial differential equations and dozens of physical parameters that need to be input, such as the solid-phase diffusion coefficient, conductivity, and particle size of the active material in the battery cell. Even obtaining these parameters through experiments is difficult and time-consuming and costly.

[0057] With the improvement of hardware capabilities, model parameters can be obtained in a data-driven manner through methods such as heuristic algorithms (genetic algorithms, particle swarm optimization, cuckoo algorithm, etc.), neural networks, and Kalman filtering. However, because batteries (cells) age, the electrochemical model parameters of the cells also change. In a large energy storage power station, there may be hundreds of thousands of cells, and these cells will age to varying degrees. Therefore, it is necessary to frequently identify the parameters of the cells to obtain more accurate parameters.

[0058] Each time parameters are identified, the identification range must be adjusted accordingly to ensure that the final identified parameter values ​​fall within this range, thus improving identification efficiency. The conventional approach is to disassemble the battery cells to obtain the identification range for these dozens of physical parameters, but this method is time-consuming and labor-intensive, especially when there are a large number of cells, reducing parameter identification efficiency.

[0059] Based on this, embodiments of this application provide a method for identifying electrochemical model parameters. Based on the electrochemical model parameters of a reference cell, the method automatically identifies the electrochemical model parameters of a target cell using the cell's capacity parameters, thereby improving the efficiency and automation of lithium battery electrochemical model parameter identification.

[0060] The following explanation is provided in conjunction with the accompanying drawings, such as... Figure 1 As shown in the embodiments of this application, a method for automatic identification of electrochemical model parameters is provided, including the following steps:

[0061] The S100 acquires the electrochemical model parameters of the reference cell.

[0062] Specifically, the reference cell is a cell of the same type as the target cell. The same type means that the reference cell and the target cell must simultaneously meet the following conditions: (1) The electrode materials and contents are the same. For example, the positive electrode uses the same ternary material. Taking nickel (Ni), cobalt (Co), and manganese (Mn) as an example, a 333 system with Ni:Co:Mn = 1:1:1 or an 811 system with Ni:Co:Mn = 8:1:1 can be used; (2) The electrolyte composition and ratio are the same. For example, dimethyl carbonate: ethylene carbonate = 1:1. The target cell and the reference cell can be lithium iron phosphate cells or ternary lithium cells. The embodiments of this application do not limit the specific types of the target cell and the reference cell, as long as the target cell and the reference cell can meet the above conditions.

[0063] The electrochemical model parameters of the reference cell can be obtained from publicly available values ​​in existing literature or values ​​obtained from laboratory tests. The electrochemical model parameters mentioned in the embodiments of this application can be individual parameters or a complete set of parameters corresponding to the cell (including dozens of parameters such as solid-phase diffusion coefficient, conductivity, and active material particle size).

[0064] S200 adjusts the identification range of the electrochemical model parameters of the target cell based on the electrochemical model parameters and capacity parameters of the reference cell; the capacity parameters include nominal capacity or state of charge.

[0065] Specifically, as mentioned above, the electrochemical model involves dozens of physical parameters that need to be input. The identification range adjusted in this embodiment refers to the range of electrochemical model parameters related to capacity parameters, such as the concentration of electrolytes in the positive and negative electrodes of the battery cell, the area of ​​the electrode plates, etc. For other parameters unrelated to capacity parameters, their identification range is not adjusted and can be set to a certain upper and lower limit range.

[0066] Based on the identification range, the S300 uses a preset identification algorithm to identify the parameters of the electrochemical model and obtain the electrochemical model parameters of the target cell.

[0067] Specifically, the identification algorithm can be a heuristic algorithm, such as a genetic algorithm, particle swarm optimization algorithm, or cuckoo algorithm, or it can be a neural network algorithm, Kalman filter algorithm, or an improved algorithm based on the above algorithms. In short, the specific implementation of the identification algorithm in the embodiments of this application is not limited.

[0068] The identification range is used to limit the upper and lower limits of the electrochemical model parameters. The electrochemical model parameters of the target cell obtained by identification are located within this identification range.

[0069] This embodiment can automatically identify the electrochemical model parameters related to the capacity parameters of the target cell, improving the efficiency and automation of lithium battery electrochemical model parameter identification.

[0070] In one implementation, a method for automatic identification of electrochemical model parameters includes the following steps:

[0071] S100 obtains the electrochemical model parameters of the reference cell; the reference cell and the target cell belong to the same type.

[0072] S210 acquires identification data of the target battery cell.

[0073] Specifically, identification data refers to data such as current, voltage, and temperature used for parameter identification. This typically includes full charge and discharge data of the battery cell under different operating conditions, ensuring the accuracy of parameter identification and the generalization ability of the identification results. Examples include data from SOC=100% (State of Charge) to SOC=0% under constant current conditions (e.g., 1C conditions), and data from SOC=100% to SOC=0% under dynamic conditions.

[0074] Because it's difficult to obtain data on the constant current operation of a battery cell, from 100% SOC to 0%, and because SOC calculations in power plants often contain errors, even if two initial SOC values ​​are obtained for a single cell, the corresponding initial concentrations are often different. Therefore, in practical applications, it's advisable to obtain one set of data for parameter identification from each cell in the power plant. Furthermore, since a single data set can easily lead to parameter overfitting, multiple identification data sets for the target cell can be obtained through cleaning.

[0075] In summary, the identification data can be full-charge and discharge data of the battery cell under different operating conditions in the laboratory, or it can be a single data point or multiple data points obtained from actual operating condition data through data cleaning. It should be noted that the battery cell is in a state of equilibrium before the identification data is obtained.

[0076] Furthermore, for the multiple identified data points obtained after cleaning, each data point must satisfy the following condition (1), at least one data point must satisfy the following condition (2), and at least one data point must satisfy the following condition (3):

[0077] (1) Before data cleaning, the battery cell should be left to stand still for a sufficient period of time (e.g., more than 1 hour) to ensure that the battery cell is in a balanced state when it starts working.

[0078] (2) It should contain a sufficiently long data set and the range of SOC variation should be large enough, for example, it should involve more than 70% of the SOC fluctuations.

[0079] (3) Dynamic operating condition (non-constant current) data: The current has a certain degree of fluctuation, so it needs to include a certain relaxation process (i.e., the process of voltage change when the current is 0).

[0080] S220 determines whether the identification data contains the initial state of charge value. If the determination is yes, proceed to step S230; otherwise, proceed to step S240.

[0081] S230 extracts the initial state of charge value from the state of charge data and executes S250.

[0082] Specifically, the identification data may or may not include SOC data. If SOC data is included, the initial state of charge (i.e., the SOC value at the start of charging or discharging) of the target cell can be directly extracted from it. If SOC data is not included, the SOC value of the target cell can be determined according to the method in S240.

[0083] S240 extracts the open-circuit voltage value from the identification data of the target cell, and determines the initial state of charge value based on the relationship between the open-circuit voltage and the state of charge of the reference cell, and then executes S250.

[0084] Specifically, for example, the first voltage value from the identification data of the target battery cell can be used as the open circuit voltage (OCV), which is the voltage of the battery cell when it is not charging or discharging. Because the battery cell is in a balanced state before the identification data is acquired, this first voltage value can be directly used as the OCV value. Alternatively, the voltage value when it remains constant (when the battery cell is still not charging or discharging) can also be used as the OCV value.

[0085] After obtaining the OCV value of the target cell, the initial SOC value of the target cell is determined based on the OCV-SOC relationship of the reference cell. The OCV-SOC relationship of the reference cell can be obtained through the following steps:

[0086] Based on preset operating conditions, the electrochemical model parameters of the reference cell are input into the electrochemical model for simulation to obtain the relationship between the open-circuit voltage and state of charge of the reference cell. For example, under low-rate discharge conditions (e.g., constant current discharge not exceeding C / 20), the electrochemical model parameters of the reference cell obtained in step S100 are input to simulate the electrochemical model of the reference cell, thereby obtaining the OCV-SOC relationship of the reference cell. The relationship curve is shown in Figure 1. Figure 2 As shown.

[0087] S250 calculates the estimated value of the initial positive / negative concentration of the target cell based on the initial positive / negative concentration of the reference cell in the first and second states of charge and the positive / negative states of charge of the reference cell.

[0088] S260 determines the range of the initial electrode concentration of the target cell based on the estimated initial concentration of the positive / negative electrode of the target cell and the initial electrode concentration of the reference cell in the first and second states of charge.

[0089] Specifically, after determining the initial SOC value, calculate the estimated initial concentration of the positive / negative electrode of the target cell using the following formula:

[0090] C est，k =SOC k *(C ref，k，2 -C ref，k，1 )+C ref，k，1 ;

[0091] Cmax=max(α2*C est，k C ref，k，1 );

[0092] Cmin=min(β2*C est,k C ref，k，2 );

[0093] Among them, C est，k Here, α0 represents the estimated initial concentration of the positive / negative electrode of the target battery cell, and k represents the electrode polarity; Cmax is the upper limit of the initial electrode concentration of the target battery cell, and Cmin is the lower limit of the initial electrode concentration of the target battery cell; α2 and β1 are the adjustment coefficients for the upper and lower limits of concentration, respectively. ref，k，1 C ref，k，2 These represent the initial electrode concentrations of the reference cell in the first and second states of charge, respectively.

[0094] Based on the range of initial electrode concentrations of the target cell, S300 uses a preset identification algorithm to identify parameters of the electrochemical model and obtain the initial electrode concentrations of the target cell.

[0095] Specifically, the range of initial electrode concentrations for the target cell is obtained through S260, while other parameter values ​​required for parameter identification can be set to specific ranges, such as those based on the range of electrochemical model parameters for a reference cell. After parameter identification is completed, not only the initial electrode concentrations of the target cell will be obtained, but also the specific values ​​of other electrochemical model parameters.

[0096] Furthermore, since the electrode thickness of battery cells with different capacities generally does not vary significantly, and the nominal capacity of the same type of lithium battery is mainly determined by the electrode area, the electrode area can be considered positively correlated with the nominal capacity of the battery cell. Therefore, the electrode area range of the target battery cell can be determined using the following formula:

[0097]

[0098]

[0099] Where Amin and Amax are the lower and upper limits of the electrode area of ​​the target cell, respectively; α1 and β1 are the adjustment coefficients for the lower and upper limits of the area, respectively; and Q is the nominal capacity of the target cell. ref A is the nominal capacity of the reference cell. ref The electrode area is the reference cell.

[0100] This application also provides a storage medium storing at least one instruction, which is loaded and executed by a processor to implement the operation performed in the corresponding embodiment of the method for automatic identification of electrochemical model parameters described above. For example, the storage medium may be a read-only memory (ROM), random access memory (RAM), read-only optical disc (CD-ROM), magnetic tape, floppy disk, or optical data storage device. These can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computing device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, this application is not limited to any particular hardware and software combination.

[0101] Based on the same technical concept, this application also provides a device for automatic identification of electrochemical model parameters, such as... Figure 3 As shown, it includes an acquisition module 100, a determination module 200, and an identification module 300, wherein:

[0102] The acquisition module 100 is used to acquire the electrochemical model parameters of the reference cell; the reference cell and the target cell belong to the same type.

[0103] The determination module 200 is used to adjust the identification range of the electrochemical model parameters of the target cell based on the electrochemical model parameters and capacity parameters of the reference cell; the capacity parameters include nominal capacity or state of charge.

[0104] The identification module 300 is used to input the identification data of the target cell into a preset electrochemical model for simulation based on the identification range, and to identify the electrochemical model parameters of the target cell.

[0105] In one embodiment, the determining module 200 is configured to determine the electrode area range of the target battery cell according to the following formula:

[0106]

[0107]

[0108] Where Amin and Amax are the lower and upper limits of the electrode area of ​​the target cell, respectively; α1 and β1 are the adjustment coefficients for the lower and upper limits of the area, respectively; and Q is the nominal capacity of the target cell. refA is the nominal capacity of the reference cell. ref The electrode area is the reference cell.

[0109] In one embodiment, the determining module 200 includes:

[0110] The first acquisition unit is used to acquire the identification data of the target battery cell.

[0111] The second acquisition unit is used to acquire the initial state of charge value of the target cell based on the identification data.

[0112] The calculation unit is used to calculate the estimated value of the initial concentration of the positive / negative electrode of the target cell based on the initial concentration of the positive / negative electrode of the reference cell in the first and second states of charge and the positive / negative state of charge of the reference cell.

[0113] The calculation unit is also used to determine the range of initial electrode concentrations for the target cell according to the following formula:

[0114] Cmax=max(α2*C est，k C ref，k，1 );

[0115] Cmin=min(β2*C est，k C ref，k，2 );

[0116] Where Cmax is the upper limit of the initial electrode concentration of the target battery cell, Cmin is the lower limit of the initial electrode concentration of the target battery cell, α2 and β1 are the upper and lower limit adjustment coefficients, k represents the polarity of the electrode, and C est，k C represents the estimated initial concentration of the positive / negative electrodes in the target battery cell. ref，k，1 C ref，k，2 These represent the initial electrode concentrations of the reference cell in the first and second states of charge, respectively.

[0117] In one embodiment, based on the above embodiment, the second acquisition unit is configured to directly extract the initial state of charge value from the identification data if the identification data of the target cell contains the initial state of charge value; the second acquisition unit is also configured to extract the open circuit voltage value from the identification data of the target cell if the identification data of the target cell does not contain the initial state of charge value; and determine the initial state of charge value according to the relationship between the open circuit voltage and the state of charge of the reference cell.

[0118] It should be noted that the embodiments of the device for automatic identification of electrochemical model parameters provided in this application and the embodiments of the method for automatic identification of electrochemical model parameters provided above are all based on the same inventive concept and can achieve the same technical effects. Therefore, other specific details of the embodiments of the device for automatic identification of electrochemical model parameters can be referred to the description of the embodiments of the method for automatic identification of electrochemical model parameters provided above.

[0119] Furthermore, the functional units in the various embodiments of this application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The integrated unit described above can be implemented in hardware or as a software functional unit.

[0120] It should be noted that the above embodiments can be freely combined as needed. The above are merely preferred embodiments of this application. It should be pointed out that for those skilled in the art, several improvements and modifications can be made without departing from the principles of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for automatic identification of electrochemical model parameters, characterized in that, include: Obtain the electrochemical model parameters of a reference cell; the reference cell and the target cell belong to the same type. Based on the electrochemical model parameters and capacity parameters of the reference cell, the identification range of the electrochemical model parameters of the target cell is adjusted; the capacity parameters include nominal capacity or state of charge. Based on the identification range, a preset identification algorithm is used to identify the parameters of the electrochemical model to obtain the electrochemical model parameters of the target cell. The process of adjusting the identification range of the electrochemical model parameters of the target cell based on the electrochemical model parameters and capacity parameters of the reference cell includes: Obtain the identification data of the target battery cell; Based on the identification data, the initial state of charge value of the target battery cell is obtained; Based on the initial positive / negative electrode concentrations of the reference cell in the first and second states of charge and the positive / negative electrode states of charge of the reference cell, the estimated values ​​of the initial positive / negative electrode concentrations of the target cell are calculated. The range of initial electrode concentrations for the target battery cell is determined using the following formula: ； ； Wherein, Cmax is the upper limit of the initial electrode concentration of the target battery cell, and Cmin is the lower limit of the initial electrode concentration of the target battery cell. , Here, k represents the upper and lower concentration limit adjustment coefficients, and k represents the electrode polarity. This is an estimate of the initial concentration of the positive / negative electrode of the target battery cell. , These represent the initial electrode concentrations of the reference cell in the first state of charge and the second state of charge, respectively.

2. The method for automatic identification of electrochemical model parameters according to claim 1, characterized in that, The method of adjusting the identification range of the electrochemical model parameters of the target cell based on the electrochemical model parameters and capacity parameters of the reference cell includes: The electrode area range of the target battery cell is determined according to the following formula: ； ； in, , These are the lower and upper limits of the electrode area of ​​the target battery cell, respectively. , These are the lower and upper limit adjustment coefficients for the area, respectively. The nominal capacity of the target battery cell. The nominal capacity of the reference cell is... The electrode area of ​​the reference cell is given.

3. The method for automatic identification of electrochemical model parameters according to claim 1, characterized in that, The step of obtaining the initial state of charge value of the target cell based on the identification data includes: If the identification data of the target cell contains state of charge data, the initial state of charge value is directly extracted from the state of charge data; If the identification data of the target cell does not include the state of charge data, the open-circuit voltage value is extracted from the identification data of the target cell, and the initial state of charge value is determined according to the relationship between the open-circuit voltage and the state of charge of the reference cell.

4. The method for automatic identification of electrochemical model parameters according to claim 3, characterized in that, The relationship between the open-circuit voltage and the state of charge of the reference cell is obtained through the following steps: Based on preset operating conditions, the electrochemical model parameters of the reference cell are input into the electrochemical model for simulation to obtain the relationship between the open-circuit voltage and the state of charge of the reference cell.

5. A device for automatic identification of electrochemical model parameters, characterized in that, include: The acquisition module is used to acquire the electrochemical model parameters of the reference cell; the reference cell and the target cell belong to the same type. The determination module is used to adjust the identification range of the electrochemical model parameters of the target cell based on the electrochemical model parameters and capacity parameters of the reference cell; the capacity parameters include nominal capacity or state of charge. The identification module is used to input the identification data of the target cell into a preset electrochemical model for simulation based on the identification range, and to identify the electrochemical model parameters of the target cell. The determining module includes: The first acquisition unit is used to acquire the identification data of the target battery cell; The second acquisition unit is used to acquire the initial state of charge value of the target cell based on the identification data. The calculation unit is used to calculate an estimated value of the initial concentration of the positive / negative electrode of the target cell based on the initial concentration of the positive / negative electrode of the reference cell in the first and second states of charge and the positive / negative state of charge of the reference cell. The calculation unit is also configured to determine the range of the initial electrode concentration of the target battery cell according to the following formula: ； ； Wherein, Cmax is the upper limit of the initial electrode concentration of the target battery cell, and Cmin is the lower limit of the initial electrode concentration of the target battery cell. , Here, k represents the upper and lower concentration limit adjustment coefficients, and k represents the electrode polarity. This is an estimate of the initial concentration of the positive / negative electrode of the target battery cell. , These represent the initial electrode concentrations of the reference cell in the first state of charge and the second state of charge, respectively.

6. The device for automatic identification of electrochemical model parameters according to claim 5, characterized in that, The determining module is used to determine the electrode area range of the target battery cell according to the following formula: ； ； in, , These are the lower and upper limits of the electrode area of ​​the target battery cell, respectively. , These are the lower and upper limit adjustment coefficients for the area, respectively. The nominal capacity of the target battery cell. The nominal capacity of the reference cell. The electrode area of ​​the reference cell is given.

7. The device for automatic identification of electrochemical model parameters according to claim 5, characterized in that, The second acquisition unit is used to directly extract the initial state of charge value from the identification data if the identification data of the target cell contains the initial state of charge value; The second acquisition unit is further configured to extract the open-circuit voltage value from the identification data of the target cell if the initial state of charge value is not included in the identification data of the target cell; and determine the initial state of charge value according to the relationship between the open-circuit voltage and the state of charge of the reference cell.

8. A storage medium, characterized in that, The storage medium stores at least one instruction, which is loaded and executed by a processor to perform the operations performed by the method for automatic identification of electrochemical model parameters as described in any one of claims 1 to 4.

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