Parameter identification method and device of battery equivalent circuit model, and readable storage medium

Abstract

The embodiment of the application provides a parameter identification method and device of a battery equivalent circuit model and a readable storage medium, the method comprises the following steps: obtaining a target direct current resistance of a battery to be measured under a preset temperature and a preset state of charge in a first working condition; obtaining a first resistance value of the battery under the preset temperature and the preset state of charge in a second working condition, wherein the first resistance value represents the resistance value of the ohmic resistance of the battery; determining a target constraint condition according to the target direct current resistance and the first resistance value, wherein the target constraint condition is used to constrain the relationship between the target direct current resistance, the first resistance value and the resistance values of all resistances to be identified in the equivalent circuit model; and performing parameter identification on the equivalent circuit model corresponding to the battery according to the target constraint condition and a preset identification algorithm to obtain target resistance and capacitance parameters of the equivalent circuit model.

Description

Technical Field

[0001] This disclosure relates to the field of lithium-ion battery technology, and more specifically, to a method for parameter identification of a battery equivalent circuit model, an electronic device, and a computer-readable storage medium; this disclosure also relates to a battery pack state assessment method. Background Technology

[0002] Lithium-ion batteries are currently the preferred power source for electric vehicles and electronic products such as mobile phones and laptops. Common methods for state estimation of lithium-ion batteries are based on battery models. The most widely used lithium-ion battery model is the equivalent circuit model, and the key to determining the equivalent battery model is to identify the model parameters based on test data.

[0003] In related technologies, when identifying parameters of equivalent circuit models, the focus is usually on the algorithm for parameter identification. That is, it is all based on test data obtained under pulse test conditions, and different algorithms, such as genetic algorithm (GA) and particle swarm optimization algorithm (PSO), are used to identify model parameters. This method has the problem that the identified parameters are not universal, resulting in inaccurate evaluation results of equivalent circuit models and the inability to accurately evaluate the performance of lithium batteries under other operating conditions. Summary of the Invention

[0004] One objective of this disclosure is to provide a new technical solution for identifying parameters of a battery equivalent circuit model, in order to solve the problem that the parameters identified by existing methods are not universal, resulting in inaccurate evaluation results of the equivalent circuit model.

[0005] According to a first aspect of this disclosure, a method for parameter identification of a battery equivalent circuit model is provided, comprising:

[0006] Obtain the target DC internal resistance of the battery under test at the preset temperature and the preset state of charge under the first operating condition.

[0007] Obtain the first resistance value of the battery at the preset temperature and the preset state of charge under the second operating condition, wherein the first resistance value represents the ohmic internal resistance of the battery.

[0008] Based on the target DC internal resistance and the first resistance value, a target constraint condition is determined, wherein the target constraint condition is used to constrain the relationship between the target DC internal resistance and the first resistance value and the resistance values ​​of all resistors to be identified in the equivalent circuit model.

[0009] Based on the target constraints and the preset identification algorithm, the equivalent circuit model corresponding to the battery is parameter identified to obtain the target resistance and capacitance parameters of the equivalent circuit model.

[0010] Optionally, the first operating condition includes a constant current charge-discharge operating condition, and the second operating condition includes a pulse test operating condition;

[0011] The step of determining the target constraint conditions based on the target DC internal resistance and the first resistance value includes:

[0012] Calculate the target difference between the target DC internal resistance and the first resistance value, and determine the target constraint condition as the sum of the resistance values ​​of all resistors in the equivalent circuit model other than the ohmic internal resistance under the preset temperature and preset charging state of the second operating condition, which is the target difference.

[0013] Optionally, the equivalent circuit model includes a second-order equivalent circuit model;

[0014] The step of identifying parameters of the equivalent circuit model corresponding to the battery based on the target constraints and a preset identification algorithm to obtain the target resistance and capacitance parameters of the equivalent circuit model includes:

[0015] Using the values ​​of electrochemical polarization internal resistance, concentration polarization internal resistance, electrochemical polarization capacitance corresponding to the electrochemical polarization internal resistance, and concentration polarization capacitance corresponding to the concentration polarization internal resistance in the second-order equivalent circuit model as variables, and with the target difference being the sum of the resistance values ​​of the electrochemical polarization internal resistance and the concentration polarization internal resistance as constraints, an initial population containing a preset number of individuals is constructed.

[0016] Based on the initial population, the variables are iteratively solved using a preset objective function and a preset fitness function used to determine the fitness of individuals, in order to obtain the target resistance and capacitance parameters that satisfy the preset conditions.

[0017] Optionally, the first operating condition includes a constant current charge-discharge condition; obtaining the target DC internal resistance of the battery under test at a preset temperature and under a preset state of charge in the first operating condition includes:

[0018] At the preset temperature, a constant current charge-discharge test is performed on the battery to obtain the current terminal voltage value, current current value, and current battery capacity value of the battery.

[0019] The preset state of charge is obtained based on the current battery capacity value and the first mapping data, wherein the first mapping data reflects the correspondence between battery capacity and battery state of charge;

[0020] The current open-circuit voltage of the battery is obtained based on the preset state of charge and the second mapping data, wherein the second mapping data reflects the correspondence between the battery state of charge and the battery open-circuit voltage.

[0021] The target DC internal resistance is obtained based on the current terminal voltage value, the current open circuit voltage value, and the current current value.

[0022] Optionally, obtaining the target DC internal resistance based on the current terminal voltage value, the current open-circuit voltage value, and the current current value includes:

[0023] Obtain the first difference between the current terminal voltage value and the current open-circuit voltage value;

[0024] The absolute value of the ratio between the first difference and the current current value is taken as the target DC internal resistance.

[0025] Optionally, the second operating condition includes a pulse test condition; obtaining the preset temperature and the first resistance value of the battery under the preset state of charge in the second operating condition includes:

[0026] During the pulse test of the battery at the preset temperature and preset state of charge, a first voltage value and a second voltage value corresponding to the battery are acquired, wherein the first voltage value and the second voltage value are respectively the voltage values ​​of the battery at the first sampling point and the second sampling point during the pulse test; and...

[0027] Obtain the second current value of the battery at the second sampling point;

[0028] The first resistance value is obtained based on the first voltage value, the second voltage value, and the second current value.

[0029] Optionally, obtaining the first resistance value based on the first voltage value, the second voltage value, and the second current value includes:

[0030] Obtain the second difference between the second voltage value and the first voltage value;

[0031] The ratio between the second difference and the second current value is taken as the first resistance value.

[0032] According to a second aspect of this disclosure, a method for assessing the state of a battery pack is also provided, the method comprising:

[0033] Obtain an equivalent circuit model corresponding to the battery pack to be evaluated, wherein the target resistance and capacitance parameters of the equivalent circuit model are determined according to the parameter identification method of the battery equivalent circuit model described in the first aspect of this disclosure.

[0034] Based on the equivalent circuit model, evaluate the operating status of the battery pack during normal use;

[0035] The operating state includes at least one of the following: the electrical performance of the battery pack, the operating temperature, and the battery health status.

[0036] According to a third aspect of this disclosure, an electronic device is also provided, comprising:

[0037] Memory is used to store executable instructions;

[0038] A processor, configured to operate the electronic device according to the instructions to perform the methods described in the first or second aspect of this specification.

[0039] According to a fourth aspect of this disclosure, a computer-readable storage medium is also provided, on which a computer program is stored, which, when executed by a processor, implements the method described according to a first or second aspect of this disclosure.

[0040] One beneficial effect of this disclosure is that, unlike the prior art method of parameter identification based solely on test data obtained under a single pulse test condition, the method provided by this disclosure obtains the target DC internal resistance of the battery under test at a preset temperature and preset state of charge under a first operating condition; and obtains the first resistance value of the battery at a preset temperature and preset state of charge under a second operating condition; then, based on the target constraint conditions reflecting the relationship between the target DC internal resistance and the first resistance value and all resistance values ​​in the equivalent circuit model corresponding to the battery, and a preset identification algorithm, the parameters of the model are identified, thereby obtaining an equivalent circuit model that can adapt to different operating conditions. Based on this equivalent circuit model, the battery performance, operating temperature, battery health status, and other operating states can be accurately evaluated.

[0041] Other features and advantages of this specification will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0042] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments of this specification and, together with their description, serve to explain the principles of this specification.

[0043] Figure 1 This is a flowchart illustrating a parameter identification method for a battery equivalent circuit model provided in an embodiment of this disclosure.

[0044] Figure 2 This is a schematic diagram of the structure of the second-order equivalent circuit model provided in the embodiments of this disclosure.

[0045] Figure 3 This is the first voltage pool curve provided in the embodiments of this disclosure.

[0046] Figure 4 This is the second voltage pool curve provided in the embodiments of this disclosure.

[0047] Figure 5 This is a schematic flowchart of a battery pack status assessment method provided in an embodiment of this disclosure.

[0048] Figure 6 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0049] Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the invention.

[0050] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use.

[0051] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0052] In all the examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0053] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0054] <Method Example 1>

[0055] In existing technologies, when identifying parameters in the equivalent circuit model of a lithium battery, it is usually based on a set of test data obtained by performing a hybrid power pulse characteristic (HPPC) test on the battery under a single operating condition of pulse testing. The focus is on using different parameter identification algorithms to identify parameters, which makes the identification results obtained by solving lack universality. That is, the equivalent circuit model based on the identification results cannot accurately evaluate the state of the battery under different operating conditions.

[0056] To address this problem, embodiments of this disclosure provide a method for parameter identification of a battery equivalent circuit model. Please refer to... Figure 1 This is a flowchart illustrating the parameter identification method for the battery equivalent circuit model provided in this embodiment. This method can be implemented in electronic devices, for example, by a device with a built-in Battery Management System (BMS). It should be noted that, unless otherwise specified, lithium batteries will be referred to simply as batteries in the following description.

[0057] like Figure 1 As shown, the method of this embodiment may include the following steps S1100-S1400, which will be described in detail below.

[0058] Step S1100: Obtain the preset temperature and target DC internal resistance of the battery under test in the first operating condition.

[0059] Commonly used equivalent circuit models include the Thevenin model, the PNGV model, and multi-order equivalent circuit models. For ease of explanation, in the embodiments of this disclosure, a second-order equivalent circuit model from the multi-order equivalent circuit model is used as an example to illustrate the equivalent circuit model used to evaluate the battery under test. Please refer to [link / reference]. Figure 2 This is a schematic diagram of the structure of the second-order equivalent circuit model provided in the embodiments of this disclosure. For example... Figure 2 As shown, R0 represents the ohmic internal resistance of the battery, R1 represents the electrochemical polarization internal resistance of the battery, C1 represents the electrochemical polarization capacitance of the battery, R2 represents the concentration polarization internal resistance of the battery, and C2 represents the concentration polarization capacitance of the battery.

[0060] To address the issue of non-universality in parameter identification based on test data obtained from a battery under a single operating condition, i.e., pulse testing, in the embodiments of this disclosure, based on the fact that after the battery has been operating under constant current charge-discharge conditions for a period of time, the current flowing through the resistor branch is consistent with the total current, i.e., the current does not pass through the capacitor, and the battery's polarization voltage is the product of the current and the total resistance, the total resistance of the battery can be derived. That is, the sum of all resistances of the battery in the equivalent circuit model is the DC internal resistance under constant current charge-discharge conditions at the same temperature and under the same state of charge. For example, in... Figure 2 In the second-order equivalent circuit model shown, the total resistance of the battery in this case, namely the sum of the ohmic internal resistance, the electrochemical polarization internal resistance and the concentration polarization internal resistance, is the DC internal resistance of the battery under the same temperature and the same charging state.

[0061] In the embodiments of this disclosure, unless otherwise specified, the first operating condition of the battery under test is described as a constant current charge-discharge condition. Under this first operating condition, obtaining the target DC internal resistance of the battery under test at a preset temperature and a preset state of charge includes: performing a constant current charge-discharge test on the battery at the preset temperature to obtain the current terminal voltage value, current current value, and current battery capacity value; obtaining a preset state of charge based on the current battery capacity value and first mapping data, wherein the first mapping data reflects the correspondence between battery capacity and battery state of charge; obtaining the current open-circuit voltage value of the battery based on the preset state of charge and second mapping data, wherein the second mapping data reflects the correspondence between battery state of charge and battery open-circuit voltage; and obtaining the target DC internal resistance based on the current terminal voltage value, current open-circuit voltage value, and current current value.

[0062] The step of obtaining the target DC internal resistance based on the current terminal voltage value, the current open circuit voltage value, and the current current value includes: obtaining a first difference between the current terminal voltage value and the current open circuit voltage value; and taking the absolute value of the ratio between the first difference and the current current value as the target DC internal resistance.

[0063] Specifically, in order to improve the accuracy of the identification results, in the embodiments of this disclosure, the battery to be tested can be a lithium-ion battery of the same batch with excellent consistency. Taking a preset temperature of 25°C as an example, before the constant current charge-discharge test and the subsequent pulse test, i.e., the Hybrid Pulse Power Characteristic (HPPC) test, the battery needs to be tested for capacity in order to obtain the above-mentioned first mapping data.

[0064] In the embodiments of this disclosure, the specific steps for testing the battery capacity are as follows: 1. At room temperature, let the battery to be tested stand for 10 minutes, discharge the battery at 1C (i.e., 1 times the power) at a constant current to 2.8V, and then let it rest for 60 minutes; 2. Charge the battery at 1C at a constant current and constant voltage to 4.25V, cut off the current at 0.05C, and let it rest for 60 minutes; 3. Discharge the battery at 1C at a constant current to 2.8V, and let it rest for 60 minutes; 4. Repeat the above second step 3 times, record the charge and discharge capacity, capability, and charge and discharge curve of the second and third cycles, and construct the above first mapping data based on the discharge capacity of the third cycle.

[0065] After performing the capacity testing steps described above on the battery to be tested, a constant current charge-discharge test can be performed. Please refer to [link / reference needed]. Figure 3The voltage relaxation curve, obtained from a constant current charge-discharge test, reflects the voltage change of the battery. The specific steps of this constant current charge-discharge test are as follows: 1. Charge the battery at 1C constant current and constant voltage to 4.25V, then charge at constant voltage until the cutoff current is 0.05C, i.e., 100% SOC, with a sampling frequency of 1 second; 2. Let the battery rest for 30 minutes, with a sampling frequency of 1 minute; 3. Adjust the temperature to 25℃ and let the battery rest for 6 hours until the battery temperature changes by less than 1℃ per hour; 4. Let the battery rest for 30 minutes, with a sampling frequency of 1 minute; 5. Discharge the battery at 1C constant current to the lower limit voltage, with a sampling frequency of 1 second; 6. Let the battery rest for 30 minutes, with a sampling frequency of 1 minute; 7. Adjust the temperature to 25℃ and let the battery rest for 6 hours until the battery temperature changes by less than 1℃ per hour; 8. Let the battery rest for 30 minutes, with a sampling frequency of 1 minute; 9. Charge the battery at 1C constant current to the upper limit voltage, with a sampling frequency of 1 second; 10. Let the battery rest for 30 minutes, with a sampling frequency of 1 minute.

[0066] The equivalent circuit model corresponding to the battery under test is used as... Figure 2 Taking the second-order equivalent circuit model shown as an example, its terminal voltage can be calculated using the following formula:

[0067]

[0068] Where U represents the terminal voltage, i represents the battery current, and U ocv Indicates open-circuit voltage. i represents the current flowing through the electrochemically polarized internal resistance R1. R2 This represents the current flowing through the electrochemically polarized internal resistance R2, regarding i R2 The detailed calculation method is explained in detail in existing technology and will not be repeated here;

[0069] Considering that after the battery has been operating under constant current charge and discharge conditions for a period of time, the current flowing through the resistor branch is consistent with the total current, that is, the current does not pass through the capacitor. At this time, the polarization voltage of the battery is the product of the current and the total resistance. Therefore, the specific steps for calculating the target DC internal resistance of the battery at the preset state of charge at 25℃ can be as follows: First, extract the current terminal voltage, current value, battery capacity, and temperature column from the 1C constant current charge and discharge test data at the corresponding temperature; then, obtain the current state of charge of the battery from the first mapping data reflecting the change of battery capacity over time, which is the corresponding preset state of charge; then, based on the second mapping data reflecting the correspondence between the state of charge and the terminal voltage, obtain the current open circuit voltage value at the corresponding temperature and the corresponding state of charge through one-dimensional interpolation; then, according to the formula target DC internal resistance = ABS((current terminal voltage value - current open circuit voltage value) / current current value), the target DC internal resistance of the battery under test at the preset temperature and the preset state of charge can be obtained. After the above steps, the DC internal resistance of the battery at different temperatures and under different states of charge can be obtained, that is, the total resistance of the battery. It should be noted that in specific implementation, the DC internal resistance of the battery at a specific temperature and under a specific state of charge can also be obtained by interpolation. The detailed interpolation algorithm will not be elaborated here.

[0070] Step S1200: Obtain the first resistance value of the battery at the preset temperature and the preset state of charge under the second operating condition, wherein the first resistance value represents the ohmic internal resistance of the battery.

[0071] To address the problems existing in the prior art where parameter identification is based solely on test data obtained from pulse testing of the battery, in the embodiments of this disclosure, in order to improve the universality of the identified parameters, while testing the battery under the second operating condition, i.e., the pulse testing condition, to obtain the corresponding first test data, the battery is also tested under the aforementioned first operating condition to obtain second test data. Furthermore, in addition to the original constraints on which parameter identification is based, target constraints are added to improve the universality and accuracy of the identified parameters.

[0072] Specifically, considering that in the second operating condition, namely the pulse test condition, the pulse test duration is relatively short, it can be assumed that the test temperature and state of charge are approximately constant. Therefore, the following constraint can be determined: under the same temperature and state of charge, the DC internal resistance (DCIR) of the battery obtained under constant current charge and discharge conditions is the sum of the resistance values ​​of all the resistors to be identified in the equivalent circuit.

[0073] For example, in the nth-order equivalent circuit model, this constraint can be expressed as: obtained under constant current charging and discharging conditions. Where n is a positive integer greater than 0, K is a positive integer not less than 0, and R k This represents the corresponding internal resistance in the nth-order equivalent circuit model.

[0074] Please refer to Figure 4 The second voltage relaxation curve, obtained by HPPC testing of the battery, reflects the voltage change of the battery. In the embodiments of this disclosure, the pulse test on the battery under test can specifically be an HPPC test on the same batch of batteries as those subjected to constant current charge-discharge testing. The specific steps of the HPPC test can be: 1. Charge the battery at a constant current of 1C at room temperature for 3 minutes until the 5% SOC upper limit voltage is cut off; 2. Use a micro-ohmmeter to test the impedance values ​​of the positive and negative terminals, the positive terminal-wire, and the negative terminal-wire (the impedance between the wire and the terminal is controlled within 1 ohm); 3. Place the battery at 25°C for 1 hour and record the voltage E1 at the end of the placement. 4. Discharge the battery at a constant current of 1C for 30 seconds (cutoff voltage 0.01V), collecting data every 100ms and recording the discharge voltage E2. Let it rest for 2 minutes. 5. Charge the battery at a constant current of 0.2C for 150 seconds, cut off at the upper limit voltage, and let it rest for 10 minutes. 6. Charge the battery at a constant current of 1C for 3 minutes, cut off at the upper limit voltage, and let it rest for 1 hour. 7. Repeat steps 4 to 6 above 19 times to complete the discharge test at 5%, 10%, 15%, 20%, 25%, 30%, 34%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, and 95% SOC.

[0075] In one embodiment, obtaining the first resistance value of the battery at a preset temperature and a preset state of charge under a second operating condition includes: during a pulse test of the battery at the preset temperature and the preset state of charge, obtaining a first voltage value and a second voltage value corresponding to the battery, wherein the first voltage value and the second voltage value are the voltage values ​​of the battery at the first sampling point and the second sampling point during the pulse test, respectively; and obtaining a second current value of the battery at the second sampling point; and obtaining the first resistance value based on the first voltage value, the second voltage value, and the second current value.

[0076] The step of obtaining the first resistance value based on the first voltage value, the second voltage value, and the second current value includes: obtaining a second difference between the second voltage value and the first voltage value; and using the ratio between the second difference and the second current value as the first resistance value.

[0077] The equivalent circuit model of the battery under test is as follows: Figure 2Taking the second-order equivalent circuit model shown as an example, specifically, because the sampling interval of the pulse test is very short, the voltage response of the battery can be considered to be caused only by the ohmic internal resistance R0 within a very short time. Therefore, based on the first voltage value U1 at the first sampling point of the pulse test and the second voltage value U2 at the second sampling point, the first resistance value of the ohmic internal resistance R0 can be obtained as ABS((second voltage value - first voltage value) / second current value). Among them, the first sampling point is the point where the battery current is 0A, and the voltage at this point is the open-circuit voltage of the battery (the voltage at the point where the current i is 0 is the open-circuit voltage). The second sampling point is the point where the battery current is not 0A, and the voltage at this point can be, for example, the terminal voltage at 0.1 seconds.

[0078] Step S1300: Based on the target DC internal resistance and the first resistance value, determine the target constraint condition, wherein the target constraint condition is used to constrain the relationship between the target DC internal resistance and the first resistance value and the resistance values ​​of all resistors to be identified in the equivalent circuit model.

[0079] In one embodiment, determining the target constraint based on the target DC internal resistance and the first resistance value includes: calculating the target difference between the target DC internal resistance and the first resistance value, and determining the target constraint as the sum of the resistance values ​​of the other resistors in the equivalent circuit model, excluding the ohmic internal resistance, at the preset temperature and the preset charging state under the second operating condition, as the target difference.

[0080] Specifically, after step S1100, by acquiring the first test data of the battery under test in the first operating condition, i.e., the constant current charge-discharge condition, and then obtaining the target DC resistance of the battery under test at different temperatures and different states of charge, i.e., the total resistance of the battery at a certain temperature and a certain state of charge, directly or indirectly based on the first test data; and after step S1200, by acquiring the second test data of the battery under test in the second operating condition, i.e., the pulse test condition, and then obtaining the ohmic internal resistance of the battery at the same temperature and the same state of charge, i.e., the resistance value of R0, then under the above constraints: Based on this, by calculating the target difference between the target DC internal resistance and the first resistance value, the target constraint condition is determined to be: at the preset temperature and the preset charging state of the second operating condition, the sum of the resistance values ​​of the other resistors in the equivalent circuit model, excluding the ohmic internal resistance, is the target difference.

[0081] by Figure 2Taking the second-order equivalent circuit model shown as an example, by performing a constant current charge-discharge test on the battery under test, the total resistance of the battery at 25℃ and 20% SOC can be obtained as the DC internal resistance dcir1. Furthermore, by performing a pulse test on the battery under test, the ohmic internal resistance of the battery at 25℃ and 20% SOC can be obtained, i.e., the first resistance value is... Therefore, according to R0 + R1 + R2 = DCIR, the target constraint condition corresponding to this second-order equivalent circuit model is: R1 + R2 = DCIR - R0. That is, the sum of the electrochemical polarization resistance R1 and concentration polarization resistance R2 of the battery can be fixed at this temperature and charging state as follows:

[0082] Step S1400: Based on the target constraints and the preset identification algorithm, the equivalent circuit model corresponding to the battery is parameter identified to obtain the target resistance and capacitance parameters of the equivalent circuit model.

[0083] After fixing the sum of other resistors in the equivalent circuit model to the target difference value according to the target constraints determined in step 1300, the preset identification algorithm can be used to identify the parameters of the equivalent circuit model to obtain the target resistance and capacitance parameters, i.e., the target RC parameters. The following provides a detailed explanation of how to use the preset identification algorithm to identify the parameters of the equivalent circuit model based on the target constraints.

[0084] In one embodiment, the preset identification algorithm can be a genetic algorithm, and the equivalent circuit model can be, for example, a second-order equivalent circuit model. The step of identifying the parameters of the equivalent circuit model corresponding to the battery according to the target constraints and the preset identification algorithm to obtain the target resistance and capacitance parameters of the equivalent circuit model includes: using the values ​​of electrochemical polarization resistance, concentration polarization resistance, electrochemical polarization capacitance corresponding to electrochemical polarization resistance, and concentration polarization capacitance corresponding to concentration polarization resistance in the second-order equivalent circuit model as variables, and using the target difference as the sum of the resistance values ​​of electrochemical polarization resistance and concentration polarization resistance as constraints, constructing an initial population containing a preset number of individuals; and iteratively solving the variables based on the initial population, using a preset objective function and a preset fitness function used to determine the fitness of individuals, to obtain the target resistance and capacitance parameters that satisfy the preset conditions.

[0085] It should be noted that the definitions of the objective function used to constrain whether a group is the optimal solution in the genetic algorithm, and the fitness function used to determine the fitness of each individual, are explained in detail in the existing technology and will not be repeated here.

[0086] Specifically, such as Figure 2As shown, R0 represents the ohmic internal resistance of the battery, R1 represents the electrochemical polarization internal resistance of the battery, C1 represents the electrochemical polarization capacitance of the battery, R2 represents the concentration polarization internal resistance of the battery, and C2 represents the concentration polarization capacitance of the battery. Then, R1+R2=DCIR-R0 can be used as the target constraint condition. R1, R2, C1, and C2 are used as variables. By defining the length of each variable, the chromosome length is fixed. Then, by randomly initializing an initial population containing a preset number, such as 500 individuals, and by iteratively performing the process, the target RC parameters that meet the preset conditions can be obtained.

[0087] For example, R1, R2, C1, and C2 can be represented as four variables, and each variable can be set to a binary value represented by 5 bits. Then, the length of each chromosome is 4 * 5 = 20 bits. With a preset population size of 500, an initial population of 500 rows and 20 columns, each composed of 0s and 1s, can be obtained. Each bit can be randomly set to either 0 or 1, resulting in 500 random combinations. Each combination contains four variables, and each combination can be considered as one individual. Upper and lower threshold values ​​for each variable can be set as needed. During the identification process, each variable is constrained to vary within its corresponding upper and lower threshold ranges, and the sum of R1 and R2 in each combination is the target difference, that is, all satisfy the target constraint conditions described in the embodiments of this disclosure; after obtaining the initial population, the objective function and the fitness function corresponding to each individual can be customized, and the crossover probability and mutation probability can be set as needed, so that the population of each iteration is obtained from the previous generation population through selection, crossover and mutation. By setting the number of iterations as needed, the optimal solution that satisfies the preset conditions can be obtained through multiple iterations, that is, the target RC parameters.

[0088] The above uses the genetic algorithm as a preset identification algorithm to illustrate how to perform parameter identification. It should be noted that in specific implementations, the preset identification algorithm can also be other algorithms, such as particle swarm optimization, population optimization, and least squares algorithms, which will not be elaborated here.

[0089] As can be seen from the above description, the method provided by the embodiments of this disclosure addresses the problem in the prior art that parameter identification relies solely on test data under a single pulse test condition, resulting in resistance and capacitance parameters that lack universality. In the parameter identification process, this application constructs target constraints based on test data from multiple operating conditions, making the identified target resistance and capacitance parameters truly effective and highly applicable. The equivalent circuit model based on these target resistance and capacitance parameters can accurately assess the battery state.

[0090] After identifying and determining the equivalent circuit model corresponding to the battery under test based on the above method, the working status of the battery or the battery pack built with the battery as the cell can be evaluated during normal use based on the equivalent circuit model.

[0091] Specifically, for a battery pack constructed using the battery under test as a cell, when evaluating the operating state of the battery pack during normal use, an equivalent circuit model corresponding to the battery pack under test can be obtained first. The target resistance and capacitance parameters in the equivalent circuit model can be determined according to any of the methods provided in the embodiments of this disclosure. After determining the equivalent circuit model, the operating state of the battery pack during normal use can be evaluated based on the equivalent circuit model. The operating state can be at least one of the electrical performance, operating temperature, and battery health status of the battery pack.

[0092] For example, after obtaining the target resistance and capacitance parameters, i.e. RC parameters, in the equivalent circuit model corresponding to the battery under test, the electrical performance and operating temperature characteristics of the entire pack model, i.e., the battery pack, constructed by connecting the cells of this type of battery in series or parallel, can be accurately evaluated.

[0093] Specifically, since the overall system model corresponding to the battery pack contains multiple cell models, and each cell model includes an equivalent circuit model and a thermal model, if the equivalent circuit model has a deviation, the performance prediction deviation of the entire pack will be even greater. Therefore, after identifying the RC parameters of the corresponding equivalent circuit model using the above methods, the formula Q=U*i+i*T*d can be used. U / d T Solve for the heat generation power Q of the battery pack, where T represents temperature and d is the heat generation power. U / d T This represents the entropy-thermal coefficient; the battery's heat generation power is coupled into the thermal model, according to the formula C*M*ΔT=QQ. 散 The temperature can be calculated, where C represents the battery's capacitance, M represents the battery's mass, ΔT represents the battery's temperature rise, and Q... 散 This represents the heat dissipated by the battery. After calculating this temperature, it is coupled back into the equivalent circuit model to simulate the cell characteristics.

[0094] For example, an equivalent circuit model built based on the target resistance and capacitance parameters can be applied to a health status assessment model to more accurately simulate the health status of a battery during normal use.

[0095] In summary, the method provided by the embodiments of this disclosure obtains the target DC internal resistance of the battery under test at a preset temperature and a preset state of charge under a first operating condition; and obtains the first resistance value of the battery at a preset temperature and a preset state of charge under a second operating condition; then, based on the target constraint conditions reflecting the relationship between the target DC internal resistance and the first resistance value and all resistances in the equivalent circuit model corresponding to the battery, and a preset identification algorithm, the parameters of the model are identified, thereby obtaining an equivalent circuit model that can adapt to different operating conditions. Based on the equivalent circuit model, the battery performance, operating temperature, battery health status, and other operating states can be accurately evaluated.

[0096] <Method Example 2>

[0097] Compared with the above-described method embodiments, the embodiments of this disclosure also provide a battery pack state assessment method, please refer to... Figure 5 This is a flowchart illustrating the battery pack status assessment method provided in this embodiment. This method can be implemented in an electronic device, for example, by a device with a built-in battery management system. The battery pack can be, for example, a battery pack constructed using the batteries in Method Embodiment 1 as cells, connected in series or parallel. Figure 5 As shown, the method of this embodiment may include the following steps S5100-S5200.

[0098] Step S5100: Obtain the equivalent circuit model corresponding to the battery pack to be evaluated, wherein the target resistance and capacitance parameters of the equivalent circuit model are determined according to the parameter identification method of the battery equivalent circuit model described in any one of the method embodiments.

[0099] Step S5200: Based on the equivalent circuit model, evaluate the operating state of the battery pack during normal use; wherein the operating state includes at least one of the electrical performance of the battery pack, operating temperature, and battery health status.

[0100] <Equipment Example>

[0101] Corresponding to the above method embodiments, this embodiment also provides an electronic device, which may be, for example, a device with a built-in battery management system. Please refer to [link / reference]. Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure.

[0102] like Figure 6 As shown, the electronic device 6000 may include a processor 6200 and a memory 6100, the memory 6100 being used to store executable instructions; the processor 6200 being used to operate the electronic device according to the instructions to perform a method according to any embodiment of the method of this disclosure.

[0103] <Media Example>

[0104] Corresponding to the above-described method embodiments one and two, this embodiment also provides a computer-readable storage medium on which a computer program is stored, which, when executed by a processor, implements the methods described in any of the method embodiments of this disclosure.

[0105] One or more embodiments of this specification may be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this specification.

[0106] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination thereof. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0107] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0108] Computer program instructions used to perform the operations of the embodiments described herein may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing state information from the computer-readable program instructions. This electronic circuitry can execute the computer-readable program instructions to implement various aspects of this specification.

[0109] Various aspects of this specification are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this specification. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0110] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0111] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0112] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this specification. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction, which contains one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions. It is well known to those skilled in the art that implementation in hardware, implementation in software, and implementation using a combination of software and hardware are equivalent.

[0113] The various embodiments of this specification have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or technical improvements to the embodiments in the market, or to enable others skilled in the art to understand the embodiments disclosed herein. The scope of this application is defined by the appended claims.

Claims

1. A method for parameter identification of a battery equivalent circuit model, characterized in that, include: Obtain the target DC internal resistance of the battery under test at the preset temperature and the preset state of charge under the first operating condition. Obtain the first resistance value of the battery at the preset temperature and the preset state of charge under the second operating condition, wherein the first resistance value represents the ohmic internal resistance of the battery. Based on the target DC internal resistance and the first resistance value, a target constraint condition is determined, wherein the target constraint condition is used to constrain the relationship between the target DC internal resistance and the first resistance value and the resistance values ​​of all resistors to be identified in the equivalent circuit model. Based on the target constraints and the preset identification algorithm, the equivalent circuit model corresponding to the battery is parameter identified to obtain the target resistance and capacitance parameters of the equivalent circuit model. The first operating condition includes a constant current charge-discharge condition, and the second operating condition includes a pulse test condition; determining the target constraint conditions based on the target DC internal resistance and the first resistance value includes: Calculate the target difference between the target DC internal resistance and the first resistance value, and determine the target constraint condition as the sum of the resistance values ​​of all resistors in the equivalent circuit model other than the ohmic internal resistance under the preset temperature and preset charging state of the second operating condition, which is the target difference.

2. The method according to claim 1, characterized in that, The equivalent circuit model includes a second-order equivalent circuit model; The step of identifying parameters of the equivalent circuit model corresponding to the battery based on the target constraints and a preset identification algorithm to obtain the target resistance and capacitance parameters of the equivalent circuit model includes: Using the values ​​of electrochemical polarization internal resistance, concentration polarization internal resistance, electrochemical polarization capacitance corresponding to the electrochemical polarization internal resistance, and concentration polarization capacitance corresponding to the concentration polarization internal resistance in the second-order equivalent circuit model as variables, and with the target difference being the sum of the resistance values ​​of the electrochemical polarization internal resistance and the concentration polarization internal resistance as constraints, an initial population containing a preset number of individuals is constructed. Based on the initial population, the variables are iteratively solved using a preset objective function and a preset fitness function used to determine the fitness of individuals, in order to obtain the target resistance and capacitance parameters that satisfy the preset conditions.

3. The method according to claim 1, characterized in that, The first operating condition includes a constant current charge-discharge condition; obtaining the target DC internal resistance of the battery under test at a preset temperature and under a preset state of charge in the first operating condition includes: At the preset temperature, a constant current charge-discharge test is performed on the battery to obtain the current terminal voltage value, current current value, and current battery capacity value of the battery. The preset state of charge is obtained based on the current battery capacity value and the first mapping data, wherein the first mapping data reflects the correspondence between battery capacity and battery state of charge; The current open-circuit voltage of the battery is obtained based on the preset state of charge and the second mapping data, wherein the second mapping data reflects the correspondence between the battery state of charge and the battery open-circuit voltage. The target DC internal resistance is obtained based on the current terminal voltage value, the current open circuit voltage value, and the current current value.

4. The method according to claim 3, characterized in that, The step of obtaining the target DC internal resistance based on the current terminal voltage value, the current open-circuit voltage value, and the current current value includes: Obtain the first difference between the current terminal voltage value and the current open-circuit voltage value; The absolute value of the ratio between the first difference and the current current value is taken as the target DC internal resistance.

5. The method according to claim 1, characterized in that, The second operating condition includes the pulse test condition; The step of obtaining the preset temperature and the first resistance value of the battery under the second operating condition includes: During the pulse test of the battery at the preset temperature and preset state of charge, a first voltage value and a second voltage value corresponding to the battery are acquired, wherein the first voltage value and the second voltage value are respectively the voltage values ​​of the battery at the first sampling point and the second sampling point during the pulse test; and... Obtain the second current value of the battery at the second sampling point; The first resistance value is obtained based on the first voltage value, the second voltage value, and the second current value.

6. The method according to claim 5, characterized in that, The step of obtaining the first resistance value based on the first voltage value, the second voltage value, and the second current value includes: Obtain the second difference between the second voltage value and the first voltage value; The ratio between the second difference and the second current value is taken as the first resistance value.

7. A method for assessing the state of a battery pack, characterized in that, include: Obtain the equivalent circuit model corresponding to the battery pack to be evaluated, wherein the target resistance and capacitance parameters of the equivalent circuit model are determined by the parameter identification method of the battery equivalent circuit model according to any one of claims 1-6. Based on the equivalent circuit model, evaluate the operating status of the battery pack during normal use; The operating state includes at least one of the following: the electrical performance of the battery pack, the operating temperature, and the battery health status.

8. An electronic device, characterized in that, include: Memory is used to store executable instructions; A processor, configured to operate the electronic device according to the instructions to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, which, when executed by a processor, implements the method according to any one of claims 1-7.

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