A method and system for optimizing electrode open circuit potential based on lithium battery electrochemical model

Abstract

The present invention discloses a method and system for optimizing the electrode open circuit potential based on the electrochemical model of a lithium battery. First, the electrode potentials under equal interval concentrations are fitted to obtain the positive electrode equilibrium potential and the negative electrode equilibrium potential. Then, the positive electrode equilibrium potential and the negative electrode equilibrium potential are used to obtain the lithium battery open circuit voltage. Subsequently, the lithium battery electrochemical model is established according to the lithium battery open circuit voltage. The present invention realizes the function of introducing the lithium battery electrochemical model to remove polarization interference, and can significantly improve the fitting performance of the model in the drastic change area of ​​the OCP curve and improve the overall fitting accuracy of the lithium battery electrochemical model by weighted optimization of the region with large OCP curvature. At the same time, by step-by-step optimization of the positive and negative electrode OCP functions and keeping other parameters fixed, the optimization dimension can be effectively reduced and the fitting stability can be improved. The present invention not only has long-term availability, but also has good versatility and engineering expansion space, and is suitable for wide promotion and use.

Description

Technical Field

[0001] The present invention relates to the technical field of lithium-ion batteries, and in particular to a method and system for optimizing the open-circuit potential of an electrode based on an electrochemical model of a lithium battery. Background Art

[0002] In the widespread application of lithium-ion batteries, accurate modeling and parameter optimization play a key role in improving battery performance, extending service life, and ensuring safety. In the common electrochemical model SPMe, the accuracy of battery voltage measurement depends largely on the accurate modeling of the electrode open circuit potential (OCP) curve.

[0003] At present, the drawing of positive and negative electrode OCP-SOC curves generally relies on experimental measurement or literature lookup. However, the positive and negative electrode OCP of each battery are different, which makes it difficult to measure some samples. Deviations are also prone to occur in the measurement and fitting process. At the same time, different experimental conditions, temperature, and aging degree are also likely to cause deviations in the OCP curve. Therefore, it is necessary to design an electrode open circuit potential optimization method and system based on the electrochemical model of lithium batteries. Summary of the Invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art and to better and effectively solve the problem that the OCP-SOC curves of positive and negative electrodes generally rely on experimental measurement or literature table lookup, but the OCP of the positive and negative electrodes of each battery is different, which leads to measurement difficulties for some samples, and deviations are also prone to occur in the measurement and fitting process. At the same time, different experimental conditions, temperature, and aging degree are also prone to cause deviations in the OCP curve. The present invention provides an electrode open circuit potential optimization method and system based on the electrochemical model of a lithium battery, which realizes the function of introducing the lithium battery electrochemical model to remove polarization interference, and through weighted optimization of the area with large OCP curvature, it can significantly improve the fitting performance of the model in the drastic change area of ​​the OCP curve and improve the overall fitting accuracy of the lithium battery electrochemical model. At the same time, by optimizing the positive and negative electrode OCP functions in steps and keeping other parameters fixed, the optimization dimension can be effectively reduced and the fitting stability can be improved. It not only has long-term availability, but also has good versatility and engineering expansion space.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] A method for optimizing the open circuit potential of an electrode based on an electrochemical model of a lithium battery comprises the following steps:

[0007] Step A, fitting the electrode potentials at equal interval concentrations and obtaining the positive electrode equilibrium potential and the negative electrode equilibrium potential;

[0008] Step B, obtaining the open circuit voltage of the lithium battery using the positive electrode equilibrium potential and the negative electrode equilibrium potential;

[0009] Step C, establishing a lithium battery electrochemical model based on the lithium battery open circuit voltage;

[0010] Step D, testing the lithium battery and obtaining test data, and then using the test data to perform parameter identification on the lithium battery electrochemical model and obtain an identified lithium battery electrochemical model;

[0011] Step E: Optimizing the electrode open circuit potential using the identified lithium battery electrochemical model and completing the electrode open circuit potential optimization operation.

[0012] The aforementioned electrode open circuit potential optimization method based on the lithium battery electrochemical model, step A, fits the electrode potential under equal interval concentration and obtains the positive electrode equilibrium potential and the negative electrode equilibrium potential, wherein the positive electrode is made of lithium iron phosphate and the negative electrode is made of graphite. The specific steps are as follows:

[0013] Step A1: Fit the electrode potential at equal interval concentrations and obtain the positive electrode equilibrium potential, where the positive electrode equilibrium potential is shown in formula (1):

[0014] (1)

[0015] in, is the positive electrode equilibrium potential, is a constant parameter term, is the state of charge of the positive electrode of the battery, and , is the normalized positive electrode solid phase concentration, is the maximum solid phase concentration of the positive electrode;

[0016] Step A2, fitting the electrode potentials at equal interval concentrations and obtaining the negative electrode equilibrium potential, where the negative electrode equilibrium potential is shown in formula (2):

[0017] (2)

[0018] in, is the negative electrode equilibrium potential, are all constant parameters. is the state of charge of the negative electrode of the battery, and , is the normalized negative electrode solid phase concentration, is the maximum solid concentration at the negative electrode.

[0019] In the aforementioned method for optimizing the electrode open circuit potential based on the electrochemical model of lithium batteries, step B uses the positive electrode equilibrium potential and the negative electrode equilibrium potential to obtain the lithium battery open circuit voltage. The specific lithium battery open circuit voltage is shown in formula (3):

[0020] (3)

[0021] in, is the open circuit voltage of the lithium battery, The active lithium ion concentration on the positive electrode surface is The positive electrode equilibrium potential at is the normalized active lithium ion concentration on the cathode surface, The active lithium ion concentration on the negative electrode surface is The negative electrode equilibrium potential at is the normalized active lithium ion concentration on the negative electrode surface.

[0022] In the aforementioned method for optimizing the electrode open circuit potential based on the lithium battery electrochemical model, step C is to establish the lithium battery electrochemical model according to the lithium battery open circuit voltage. The specific lithium battery electrochemical model is shown in formula (4).

[0023] (4)

[0024] in, is the fitting voltage, is the reaction overpotential, is the concentration overpotential, is the electrolyte ohmic loss, is the solid phase ohmic loss.

[0025] The aforementioned method for optimizing the open circuit potential of an electrode based on a lithium battery electrochemical model, step D, tests the lithium battery and obtains test data, and then uses the test data to perform parameter identification on the lithium battery electrochemical model and obtain an identified lithium battery electrochemical model. The specific steps are as follows:

[0026] Step D1: Perform a hybrid pulse power characteristic HPPC test and a low current charging test on the battery to obtain HPPC test voltage data. And small current constant current charging test voltage data ;

[0027] Step D2, based on HPPC test voltage data The particle swarm algorithm is used to perform the initial parameter identification of the lithium battery electrochemical model, and then the voltage data of the small current constant current charging test is used A secondary parameter identification is performed on the lithium battery electrochemical model to obtain an identified lithium battery electrochemical model.

[0028] The aforementioned method for optimizing the electrode open circuit potential based on the electrochemical model of lithium batteries, step D1 specifically comprises the following steps:

[0029] Step D11, perform a hybrid pulse power characteristic HPPC test on the battery, wherein the HPPC test specifically applies pulse currents of different durations and amplitudes to the lithium battery to simulate the charge and discharge conditions of the lithium battery in actual operation, thereby collecting the voltage, current and temperature data of the lithium battery during the pulse process, and then obtaining the HPPC test voltage data ;

[0030] Step D12, perform a low current charging test on the battery, wherein the low current charging test specifically uses a current less than 0.05C to charge the lithium battery to obtain the voltage, current, and charging time data during the low current charging process, and then obtain the low current constant current charging test voltage data .

[0031] The aforementioned method for optimizing the electrode open circuit potential based on the electrochemical model of lithium batteries, step D2 specifically comprises the following steps:

[0032] Step D21, based on HPPC test voltage data The particle swarm algorithm is used to perform the initial parameter identification of the lithium battery electrochemical model. Specifically, each particle in the particle swarm algorithm operation process is represented as a set of potential battery parameter solutions. Then, the particles continuously adjust their positions in the battery parameter solution space and gradually approach the optimal solution by tracking individual extreme values ​​and group extreme values. Then, the HPPC test voltage data is used to identify the initial parameters of the lithium battery electrochemical model. Input the lithium battery electrochemical model and aim to minimize the error between the lithium battery electrochemical model output and the actual test data, then continuously optimize the lithium battery electrochemical model parameters through the particle swarm algorithm;

[0033] Step D22, based on the low current constant current charging test voltage data Perform secondary parameter identification on the lithium battery electrochemical model to obtain the identified lithium battery electrochemical model. Specifically, the small current constant current charging test voltage data Input the lithium battery electrochemical model and search within the narrowed parameter range to obtain the battery parameters and initial model fitting voltage .

[0034] The aforementioned method for optimizing the electrode open circuit potential based on the electrochemical model of a lithium battery, step E, optimizes the electrode open circuit potential using the identified electrochemical model of the lithium battery and completes the electrode open circuit potential optimization operation. The specific steps are as follows:

[0035] Step E1: Take the positive electrode OCP equation as the optimization object and obtain the lithium battery parameters after charging with a fixed low current, and then replace the equation (1) with Constructing positive loss function as target identification parameter The difference between the calculated value of the lithium battery electrochemical model after identification and the actual measured value is measured as shown in formula (5).

[0036] (5)

[0037] in, is the voltage calculated by the identified lithium battery electrochemical model at the i-th moment, is the optimized positive electrode equilibrium potential function, Measure the voltage at the i-th moment;

[0038] Step E2, take the negative electrode OCP equation as the optimization object and obtain the lithium battery parameters after charging with a fixed low current, and then replace the negative electrode OCP equation with the negative electrode OCP equation in formula (2). Constructing the negative loss function as the target identification parameter The difference between the calculated value of the lithium battery electrochemical model after identification and the actual measured value is measured as shown in formula (6).

[0039] (6)

[0040] in, is the negative electrode equilibrium voltage function after optimization;

[0041] In step E3, a weighting mechanism is introduced to correct the equilibrium potential of the negative electrode at the phase transition point. Specifically, a higher weight is given when the curvature of the OCP curve changes greatly, as shown in formula (7).

[0042] ;

[0043] (7)

[0044] in, is the regulating factor, is a hyperparameter, The state of charge of the negative electrode of the battery The second derivative of

[0045] Step E4: Establish a regular correction mechanism, specifically re-execute step E1 according to the set time interval or number of charging cycles. Step E3: Update the parameters of the positive and negative electrode OCP equations.

[0046] A lithium battery open circuit potential optimization system based on an electrochemical model of a lithium battery comprises an electrode fitting module, an open circuit voltage acquisition module, a model building module, a battery test identification module and a potential optimization module. The electrode fitting module is used to fit the electrode potential under equal interval concentrations and obtain the positive electrode equilibrium potential and the negative electrode equilibrium potential; the open circuit voltage acquisition module is used to obtain the lithium battery open circuit voltage using the positive electrode equilibrium potential and the negative electrode equilibrium potential; the model building module is used to establish a lithium battery electrochemical model based on the lithium battery open circuit voltage; the battery test identification module is used to test the lithium battery and obtain test data, and then use the test data to perform parameter identification on the lithium battery electrochemical model and obtain the identified lithium battery electrochemical model; the potential optimization module is used to optimize the electrode open circuit potential using the identified lithium battery electrochemical model and complete the electrode open circuit potential optimization operation.

[0047] The beneficial effects of the present invention are as follows: the present invention provides an electrode open circuit potential optimization method and system based on the lithium battery electrochemical model, firstly, the electrode potential under equal interval concentration is fitted and the positive electrode equilibrium potential and the negative electrode equilibrium potential are obtained, then the positive electrode equilibrium potential and the negative electrode equilibrium potential are used to obtain the lithium battery open circuit voltage, then the lithium battery electrochemical model is established according to the lithium battery open circuit voltage, and then the lithium battery is tested and test data is obtained, and then the test data is used to perform parameter identification on the lithium battery electrochemical model and obtain the identified lithium battery electrochemical model, and finally the identified lithium battery electrochemical model is used to optimize the electrode open circuit potential and complete the electrode open circuit potential optimization operation; the electrode open circuit potential optimization method and system have the function of introducing the lithium battery electrochemical model to remove polarization interference, and can significantly improve the model fitting performance in the OCP curve drastically changing area and improve the overall fitting accuracy of the lithium battery electrochemical model by weighted optimization of the region with large OCP curvature, and at the same time, by step-by-step optimization of the positive and negative electrode OCP Function and keeping other parameters fixed can effectively reduce the optimization dimension and improve the fitting stability. By adopting a periodic re-identification mechanism, the lithium battery electrochemical model has long-term availability, which not only enhances its practical value but also has good versatility and engineering expansion space. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 This is an overall flow chart of an electrode open circuit potential optimization method based on a lithium battery electrochemical model of the present invention;

[0049] Figure 2 1 is an OCP curve diagram of the positive electrode equilibrium potential and the negative electrode equilibrium potential in an embodiment of the present invention;

[0050] Figure 3 1 is a graph showing the fitted voltage and measured voltage of a lithium battery before OCP optimization in an embodiment of the present invention;

[0051] Figure 4 2 is a graph showing the fitted voltage and measured voltage after optimizing the positive electrode OCP in an embodiment of the present invention;

[0052] Figure 5 2 is a graph showing the fitted voltage and measured voltage after optimizing the negative electrode OCP in an embodiment of the present invention;

[0053] Figure 6 Schematic diagram of the voltage difference of a lithium battery before and after optimization in an embodiment of the present invention;

[0054] Figure 7 2. This is a comparison curve of the positive electrode OCP before and after optimization in an embodiment of the present invention;

[0055] Figure 8 3 is a comparison curve of the negative electrode OCP before and after optimization in the embodiment of the present invention. DETAILED DESCRIPTION

[0056] The present invention will be further described below with reference to the accompanying drawings.

[0057] like Figure 1 As shown, the present invention provides an electrode open circuit potential optimization method based on the lithium battery electrochemical model, comprising the following steps:

[0058] like Figure 2 As shown, step A is to fit the electrode potential under equal interval concentration and obtain the positive electrode equilibrium potential and the negative electrode equilibrium potential, wherein the positive electrode is made of lithium iron phosphate and the negative electrode is made of graphite. The specific steps are as follows:

[0059] Step A1: Fit the electrode potential at equal interval concentrations and obtain the positive electrode equilibrium potential, where the positive electrode equilibrium potential is shown in formula (1):

[0060] (1)

[0061] in, is the positive electrode equilibrium potential, is a constant parameter term, is the state of charge of the positive electrode of the battery, and , is the normalized positive electrode solid phase concentration, is the maximum solid phase concentration of the positive electrode;

[0062] Step A2, fitting the electrode potentials at equal interval concentrations and obtaining the negative electrode equilibrium potential, where the negative electrode equilibrium potential is shown in formula (2):

[0063] (2)

[0064] in, is the negative electrode equilibrium potential, are all constant parameters. is the state of charge of the negative electrode of the battery, and , is the normalized negative electrode solid phase concentration, is the maximum solid concentration at the negative electrode.

[0065] Step B: Use the positive electrode equilibrium potential and the negative electrode equilibrium potential to obtain the open circuit voltage of the lithium battery. The specific open circuit voltage of the lithium battery is shown in formula (3):

[0066] (3)

[0067] in, is the open circuit voltage of the lithium battery, The active lithium ion concentration on the positive electrode surface is The positive electrode equilibrium potential at is the normalized active lithium ion concentration on the cathode surface, The active lithium ion concentration on the negative electrode surface is The negative electrode equilibrium potential at is the normalized active lithium ion concentration on the negative electrode surface.

[0068] Step C: Establish a lithium battery electrochemical model based on the open circuit voltage of the lithium battery. The specific lithium battery electrochemical model is shown in formula (4).

[0069] (4)

[0070] in, is the fitting voltage, is the reaction overpotential, is the concentration overpotential, is the electrolyte ohmic loss, is the solid phase ohmic loss.

[0071] Step D: Test the lithium battery and obtain test data, then use the test data to perform parameter identification on the lithium battery electrochemical model and obtain the identified lithium battery electrochemical model. The specific steps are as follows:

[0072] Step D1: Perform a hybrid pulse power characteristic HPPC test and a low current charging test on the battery to obtain HPPC test voltage data. And small current constant current charging test voltage data , the specific steps are as follows,

[0073] Step D11, perform a hybrid pulse power characteristic HPPC test on the battery, wherein the HPPC test specifically applies pulse currents of different durations and amplitudes to the lithium battery to simulate the charge and discharge conditions of the lithium battery in actual operation, thereby collecting the voltage, current and temperature data of the lithium battery during the pulse process, and then obtaining the HPPC test voltage data ;

[0074] Step D12, perform a low current charging test on the battery, wherein the low current charging test specifically uses a current less than 0.05C to charge the lithium battery to obtain the voltage, current, and charging time data during the low current charging process, and then obtain the low current constant current charging test voltage data .

[0075] Step D2, based on HPPC test voltage data The particle swarm algorithm is used to perform the initial parameter identification of the lithium battery electrochemical model, and then the voltage data of the small current constant current charging test is used Perform secondary parameter identification on the lithium battery electrochemical model to obtain the identified lithium battery electrochemical model. The specific steps are as follows:

[0076] Step D21, based on HPPC test voltage data The particle swarm algorithm is used to perform the initial parameter identification of the lithium battery electrochemical model. Specifically, each particle in the particle swarm algorithm operation process is represented as a set of potential battery parameter solutions. Then, the particles continuously adjust their positions in the battery parameter solution space and gradually approach the optimal solution by tracking individual extreme values ​​and group extreme values. Then, the HPPC test voltage data is used to identify the initial parameters of the lithium battery electrochemical model. Input the lithium battery electrochemical model and aim to minimize the error between the lithium battery electrochemical model output and the actual test data, then continuously optimize the lithium battery electrochemical model parameters through the particle swarm algorithm;

[0077] Step D22, based on the low current constant current charging test voltage data Perform secondary parameter identification on the lithium battery electrochemical model to obtain the identified lithium battery electrochemical model. Specifically, the small current constant current charging test voltage data Input the lithium battery electrochemical model and search within the narrowed parameter range to obtain the battery parameters and initial model fitting voltage .

[0078] The specific fitting voltage and measurement voltage curves are as follows Figure 3 As shown, the RMSE is 5.7mV.

[0079] Step E: Optimize the electrode open circuit potential using the identified lithium battery electrochemical model and complete the electrode open circuit potential optimization operation. The specific steps are as follows:

[0080] Step E1: Take the positive electrode OCP equation as the optimization object and obtain the lithium battery parameters after charging with a fixed low current, and then replace the equation (1) with Constructing positive loss function as target identification parameter The difference between the calculated value of the lithium battery electrochemical model after identification and the actual measured value is measured as shown in formula (5).

[0081] (5)

[0082] in, is the voltage calculated by the identified lithium battery electrochemical model at the i-th moment, is the optimized positive electrode equilibrium potential function, Measure the voltage at the i-th moment;

[0083] After optimizing the positive electrode OCP, the fitted voltage and measured voltage curves are as follows: Figure 4 As shown in Figure 2, the RMSE is reduced to 4.6mV; the optimized positive electrode OCP curve is as follows Figure 7 shown.

[0084] Step E2, take the negative electrode OCP equation as the optimization object and obtain the lithium battery parameters after charging with a fixed low current, and then replace the negative electrode OCP equation with the negative electrode OCP equation in formula (2). Constructing the negative loss function as the target identification parameter The difference between the calculated value of the lithium battery electrochemical model after identification and the actual measured value is measured as shown in formula (6).

[0085] (6)

[0086] in, is the negative electrode equilibrium voltage function after optimization;

[0087] In step E3, a weighting mechanism is introduced to correct the equilibrium potential of the negative electrode at the phase transition point. Specifically, a higher weight is given when the curvature of the OCP curve changes greatly, as shown in formula (7).

[0088] ;

[0089] (7)

[0090] in, is the regulating factor, is a hyperparameter, The state of charge of the negative electrode of the battery The second derivative of

[0091] After optimizing the negative electrode OCP, the fitted voltage and measured voltage curves are as follows: Figure 5 As shown in Figure 2, the RMSE is reduced to 2.9mV; Figure 6 As shown, the pressure difference between the initial fitting voltage and the measured voltage time is compared with the pressure difference between the fitting voltage and the measured voltage after optimizing the positive and negative electrode OCP; the negative electrode OCP curve after optimization is shown in Figure 8 shown.

[0092] Step E4: Establish a regular correction mechanism, specifically re-execute step E1 according to the set time interval or number of charging cycles. Step E3: Update the parameters of the positive and negative electrode OCP equations.

[0093] A lithium battery open circuit potential optimization system based on an electrochemical model of a lithium battery comprises an electrode fitting module, an open circuit voltage acquisition module, a model building module, a battery test identification module and a potential optimization module. The electrode fitting module is used to fit the electrode potential under equal interval concentrations and obtain the positive electrode equilibrium potential and the negative electrode equilibrium potential; the open circuit voltage acquisition module is used to obtain the lithium battery open circuit voltage using the positive electrode equilibrium potential and the negative electrode equilibrium potential; the model building module is used to establish a lithium battery electrochemical model based on the lithium battery open circuit voltage; the battery test identification module is used to test the lithium battery and obtain test data, and then use the test data to perform parameter identification on the lithium battery electrochemical model and obtain the identified lithium battery electrochemical model; the potential optimization module is used to optimize the electrode open circuit potential using the identified lithium battery electrochemical model and complete the electrode open circuit potential optimization operation.

[0094] In summary, the present invention provides an electrode open circuit potential optimization method and system based on the lithium battery electrochemical model. First, the electrode potential under equal interval concentration is fitted and the positive electrode equilibrium potential and the negative electrode equilibrium potential are obtained. Then, the positive electrode equilibrium potential and the negative electrode equilibrium potential are used to obtain the lithium battery open circuit voltage. Subsequently, a lithium battery electrochemical model is established according to the lithium battery open circuit voltage. The lithium battery is tested and test data is obtained. The test data is used to perform parameter identification on the lithium battery electrochemical model and an identified lithium battery electrochemical model is obtained. Finally, the identified lithium battery electrochemical model is used to optimize the electrode open circuit potential and complete the electrode open circuit potential optimization operation. The electrode open circuit potential optimization method and system have the function of introducing a lithium battery electrochemical model to remove polarization interference, and can significantly improve the model's fitting performance in the drastic change region of the OCP curve and improve the overall fitting accuracy of the lithium battery electrochemical model by weighted optimization of the region with large OCP curvature. At the same time, by optimizing the positive and negative electrode OCP in steps, the electrode open circuit potential is optimized. Function and keeping other parameters fixed can effectively reduce the optimization dimension and improve the fitting stability. By adopting a periodic re-identification mechanism, the lithium battery electrochemical model has long-term availability, which not only enhances its practical value but also has good versatility and engineering expansion space.

[0095] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the foregoing embodiments. The foregoing embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for optimizing the open circuit potential of an electrode based on an electrochemical model of a lithium battery, characterized by: The following steps are included: Step A: Fitting the electrode potentials at equal interval concentrations to obtain the positive electrode equilibrium potential and the negative electrode equilibrium potential, wherein the positive electrode is made of lithium iron phosphate and the negative electrode is made of graphite. The specific steps are as follows: Step A1: Fit the electrode potential at equal interval concentrations and obtain the positive electrode equilibrium potential, where the positive electrode equilibrium potential is shown in formula (1): （1） in, is the positive electrode equilibrium potential, is a constant parameter term, is the state of charge of the positive electrode of the battery, and , is the normalized positive electrode solid phase concentration, is the maximum solid phase concentration of the positive electrode; Step A2, fitting the electrode potentials at equal interval concentrations and obtaining the negative electrode equilibrium potential, where the negative electrode equilibrium potential is shown in formula (2): （2） in, is the negative electrode equilibrium potential, are all constant parameters. is the state of charge of the negative electrode of the battery, and , is the normalized negative electrode solid phase concentration, is the maximum solid concentration at the negative electrode; Step B, obtaining the open circuit voltage of the lithium battery using the positive electrode equilibrium potential and the negative electrode equilibrium potential; Step C, establishing a lithium battery electrochemical model based on the lithium battery open circuit voltage; Step D, testing the lithium battery and obtaining test data, and then using the test data to perform parameter identification on the lithium battery electrochemical model and obtain an identified lithium battery electrochemical model; Step E: Optimize the electrode open circuit potential using the identified lithium battery electrochemical model and complete the electrode open circuit potential optimization operation. The specific steps are as follows: Step E1: Take the positive electrode OCP equation as the optimization object and obtain the lithium battery parameters after charging with a fixed low current, and then replace the equation (1) with Constructing positive loss function as target identification parameter The difference between the calculated value of the lithium battery electrochemical model after identification and the actual measured value is measured as shown in formula (5). （5） in, is the voltage calculated by the identified lithium battery electrochemical model at the i-th moment, is the optimized positive electrode equilibrium potential function, Measure the voltage at the i-th moment; Step E2, take the negative electrode OCP equation as the optimization object and obtain the lithium battery parameters after charging with a fixed low current, and then replace the negative electrode OCP equation with the negative electrode OCP equation in formula (2). Constructing the negative loss function as the target identification parameter The difference between the calculated value of the lithium battery electrochemical model after identification and the actual measured value is measured as shown in formula (6). （6） in, is the negative electrode equilibrium voltage function after optimization; In step E3, a weighting mechanism is introduced to correct the equilibrium potential of the negative electrode at the phase transition point. Specifically, a higher weight is given when the curvature of the OCP curve changes greatly, as shown in formula (7). ； （7） in, is the regulating factor, is a hyperparameter, The state of charge of the negative electrode of the battery The second derivative of Step E4: Establish a regular correction mechanism, specifically re-execute step E1 according to the set time interval or number of charging cycles. Step E3: Update the parameters of the positive and negative electrode OCP equations.

2. The method for optimizing the electrode open circuit potential based on the electrochemical model of a lithium battery according to claim 1, characterized in that: Step B: Use the positive electrode equilibrium potential and the negative electrode equilibrium potential to obtain the open circuit voltage of the lithium battery. The specific open circuit voltage of the lithium battery is shown in formula (3): （3） in, is the open circuit voltage of the lithium battery, The active lithium ion concentration on the positive electrode surface is The positive electrode equilibrium potential at is the normalized active lithium ion concentration on the cathode surface, The active lithium ion concentration on the negative electrode surface is The negative electrode equilibrium potential at is the normalized active lithium ion concentration on the negative electrode surface.

3. The method for optimizing the electrode open circuit potential based on the electrochemical model of a lithium battery according to claim 1, characterized in that: Step C: Establish a lithium battery electrochemical model based on the open circuit voltage of the lithium battery. The specific lithium battery electrochemical model is shown in formula (4). （4） in, is the fitting voltage, is the reaction overpotential, is the concentration overpotential, is the electrolyte ohmic loss, is the solid phase ohmic loss.

4. The method for optimizing the electrode open circuit potential based on the electrochemical model of a lithium battery according to claim 1, characterized in that: Step D: Test the lithium battery and obtain test data, then use the test data to perform parameter identification on the lithium battery electrochemical model and obtain the identified lithium battery electrochemical model. The specific steps are as follows: Step D1: Perform a hybrid pulse power characteristic HPPC test and a low current charging test on the battery to obtain HPPC test voltage data. And small current constant current charging test voltage data ; Step D2, based on HPPC test voltage data The particle swarm algorithm is used to perform the initial parameter identification of the lithium battery electrochemical model, and then the voltage data of the small current constant current charging test is used A secondary parameter identification is performed on the lithium battery electrochemical model to obtain an identified lithium battery electrochemical model.

5. The method for optimizing the electrode open circuit potential based on the electrochemical model of a lithium battery according to claim 4, characterized in that: The specific steps of step D1 are as follows: Step D11, perform a hybrid pulse power characteristic HPPC test on the battery, wherein the HPPC test specifically applies pulse currents of different durations and amplitudes to the lithium battery to simulate the charge and discharge conditions of the lithium battery in actual operation, thereby collecting the voltage, current and temperature data of the lithium battery during the pulse process, and then obtaining the HPPC test voltage data ; Step D12, perform a low current charging test on the battery, wherein the low current charging test specifically uses a current less than 0.05C to charge the lithium battery to obtain the voltage, current, and charging time data during the low current charging process, and then obtain the low current constant current charging test voltage data .

6. The method for optimizing the electrode open circuit potential based on the electrochemical model of a lithium battery according to claim 4, characterized in that: The specific steps of step D2 are as follows: Step D21, based on HPPC test voltage data The particle swarm algorithm is used to perform the initial parameter identification of the lithium battery electrochemical model. Specifically, each particle in the particle swarm algorithm operation process is represented as a set of potential battery parameter solutions. Then, the particles continuously adjust their positions in the battery parameter solution space and gradually approach the optimal solution by tracking individual extreme values ​​and group extreme values. Then, the HPPC test voltage data is used to identify the initial parameters of the lithium battery electrochemical model. Input the lithium battery electrochemical model and aim to minimize the error between the lithium battery electrochemical model output and the actual test data, then continuously optimize the lithium battery electrochemical model parameters through the particle swarm algorithm; Step D22, based on the low current constant current charging test voltage data Perform secondary parameter identification on the lithium battery electrochemical model to obtain the identified lithium battery electrochemical model. Specifically, the small current constant current charging test voltage data Input the lithium battery electrochemical model and search within the narrowed parameter range to obtain the battery parameters and initial model fitting voltage .

7. An electrode open circuit potential optimization system based on a lithium battery electrochemical model, wherein the specific optimization process of the electrode open circuit potential optimization system is based on the electrode open circuit potential optimization method according to any one of claims 1 to 6, characterized in that: It includes an electrode fitting module, an open circuit voltage acquisition module, a model building module, a battery test identification module and a potential optimization module. The electrode fitting module is used to fit the electrode potential under equal interval concentrations and obtain the positive electrode equilibrium potential and the negative electrode equilibrium potential; The open circuit voltage acquisition module is used to obtain the open circuit voltage of the lithium battery using the positive electrode equilibrium potential and the negative electrode equilibrium potential; The model building module is used to build a lithium battery electrochemical model according to the open circuit voltage of the lithium battery; The battery test and identification module is used to test the lithium battery and obtain test data, and then use the test data to perform parameter identification on the lithium battery electrochemical model and obtain the identified lithium battery electrochemical model; The potential optimization module is used to optimize the electrode open circuit potential using the identified lithium battery electrochemical model and complete the electrode open circuit potential optimization operation.

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