Battery equivalent circuit parameter identification method and system

Abstract

The present invention provides a battery equivalent circuit parameter identification method and system, the method comprising: receiving a battery equivalent circuit parameter identification requirement; determining a corresponding test scheme according to the identification requirement; testing a battery sample according to the test scheme to obtain the equivalent circuit parameters of the battery sample. The system comprises: a battery sample; an environmental chamber for providing a corresponding ambient temperature when testing the battery sample; a charging and discharging device for controlling the battery sample to charge and discharge; a control device for controlling the environmental chamber and the charging and discharging device to test the battery sample to obtain the battery equivalent circuit parameters of the battery sample; a model building device for importing the equivalent circuit parameters into the battery equivalent circuit model of the battery sample to obtain a simulation model of the battery equivalent circuit of the battery sample. The present invention can identify the parameter information of the battery equivalent circuit model based on a small amount of actual battery tests, thereby building a simulation model of the battery equivalent circuit.

Description

Technical Field

[0001] The present invention relates to the field of battery modeling, and in particular to a battery equivalent circuit parameter identification method and system. Background Art

[0002] Lithium-ion batteries (referred to as lithium batteries) have rapidly developed into a new generation of energy storage power due to their high energy density, long cycle life, no memory effect, and green environmental protection. In order to ensure the safe and reliable operation of battery energy storage systems, a complete battery management system must be established based on accurate battery models to estimate and predict battery status.

[0003] There are two commonly used battery digital twin models: electrochemical models and equivalent circuit models. The electrochemical model expresses the basic electrochemical reaction through complex nonlinear partial differential algebraic equations. Although it can accurately capture various characteristics of the battery, it requires a large number of complex calculations to obtain the solution of the equation, and the computing power of the processor is very high. Therefore, this type of model is generally suitable for battery design rather than system-level simulation. In contrast, the equivalent circuit model is based on the working principle of the battery and uses a circuit network composed of electronic components such as resistors and capacitors to describe the working characteristics of the battery. Because the physical meaning is clear and clear, it is convenient for mathematical analysis and parameter identification, and is widely used in new energy vehicle simulation. The accuracy of the equivalent circuit model depends largely on the structure of the model and the accuracy of the model parameter identification. In theory, a higher-order equivalent circuit model can characterize more types of batteries and generate more accurate voltage estimates, but it has the disadvantages of increasing the computational burden and reducing the numerical stability of the later battery state parameter estimation. Therefore, considering the three aspects of model accuracy, computational burden and numerical stability, the present invention adopts a second-order RC equivalent circuit model as the research object.

[0004] For the second-order RC equivalent circuit model, the quality of the model parameter identification method directly determines the reliability and accuracy of the parameters in the model. The least squares fitting method is simple to calculate, but the error is large; the Kalman filter method can obtain the optimal estimate of the state variable, but the value of the system noise will directly affect the accuracy of the identification; the genetic algorithm has good global identification accuracy, but the local search ability is poor. At the same time, the online parameter identification technology is mostly used for battery state estimation, but not used in battery model construction; the offline parameter identification technology is mostly used for battery model construction, but its accuracy and granularity are somewhat different from online identification. Therefore, only by integrating the advantages of several algorithms and combining online and offline identification can the model parameters be accurately identified. Since the second-order RC equivalent circuit model belongs to a nonlinear system, for nonlinear systems, current research usually uses nonlinear parameter linearization, and then uses the linear least squares fitting method to achieve parameter identification. However, there are nonlinear parameters in the second-order RC equivalent circuit model that cannot be linearized, which makes it impossible to accurately identify the parameters in the model.

[0005] The preceding description is intended to provide general background information and does not necessarily constitute prior art. Summary of the invention

[0006] In view of the shortcomings of the prior art described above, an object of the present invention is to provide a battery equivalent circuit parameter identification method and system, which is used to solve the problem that there are nonlinear parameters in the second-order RC equivalent circuit model in the prior art that cannot be linearized, resulting in the inability to accurately identify the parameters in the model.

[0007] To achieve the above-mentioned object and other related objects, the present invention provides a battery equivalent circuit parameter identification method, the battery equivalent circuit parameter identification method comprising:

[0008] Receive the identification requirements of battery equivalent circuit parameters;

[0009] Determine a corresponding test plan according to the identification requirements;

[0010] The battery sample is tested according to the test plan to obtain equivalent circuit parameters of the battery sample.

[0011] Preferably, the test scheme includes at least: a SOC-OCV test scheme and a HPPC test scheme.

[0012] Preferably, when the test scheme is a SOC-OCV test scheme, the step of testing the battery sample according to the test scheme to obtain the equivalent circuit parameters of the battery sample includes:

[0013] S11, controlling the battery sample to perform the first operation according to the SOC-OCV pre-research test plan;

[0014] S12, optimizing the SOC-OCV formal test plan based on the first operation result;

[0015] S13, controlling the battery sample to perform a second run according to the optimized SOC-OCV formal test plan;

[0016] S14, processing the second operation result to obtain a two-dimensional graph of the open circuit voltage of the battery sample.

[0017] Preferably, the step of S11, controlling the battery sample to perform a first run according to the SOC-OCV preliminary research test plan, comprises:

[0018] S111, controlling the battery sample to be processed according to a first rule to obtain an actual capacity of the battery sample;

[0019] S112 controls the battery sample to be processed according to a second rule based on the actual capacity to obtain the first operation result.

[0020] Preferably, the step of S13, controlling the battery sample to perform a second run according to the optimized SOC-OCV formal test scheme, comprises:

[0021] S131, controlling the battery sample to be processed according to a first rule to obtain an actual capacity of the battery sample;

[0022] S132: Based on the actual capacity, control the battery sample to be processed according to a third rule to obtain the second operation result.

[0023] Preferably, the step of controlling the battery sample to be processed according to the first rule to obtain the actual capacity of the battery sample includes:

[0024] Based on a first preset temperature, the battery sample is controlled to repeatedly perform a charge and discharge process to a first preset number of times;

[0025] determining an average value of the discharge capacities of the battery samples based on a second preset number of times as the actual capacity of the battery samples;

[0026] Wherein, the second preset number of times is less than the first preset number of times.

[0027] Preferably, the step of controlling the battery sample to repeatedly perform the charge and discharge process to a first preset number of times based on the first preset temperature includes:

[0028] Controlling the battery sample to be subjected to a static treatment at a first preset temperature;

[0029] When the static treatment time length satisfies a first preset time length, controlling the battery sample to perform constant current discharge at a first preset current under the first preset temperature;

[0030] When the voltage of the battery sample is less than the discharge cut-off voltage, controlling the battery sample to be placed at the first preset temperature;

[0031] When the static treatment time meets the first preset time, controlling the battery sample to perform constant current charging at the first preset temperature and the first preset current;

[0032] When the voltage of the battery sample is greater than the charging cut-off voltage, the battery sample is controlled to switch to constant voltage charging;

[0033] When the charging current of the battery sample is less than the preset current, the battery sample is controlled to repeatedly execute the above steps to the first preset number of times.

[0034] Preferably, the step of S112, controlling the battery sample to be processed according to a second rule based on the actual capacity to obtain the voltage stabilization time of the battery sample under different conditions, includes:

[0035] S1121, controlling the battery sample to perform a static treatment at a first preset temperature based on the actual capacity, and detecting the battery terminal voltage at the first preset temperature;

[0036] S1122, when the static treatment time at the first preset temperature meets the second preset time, adjusting the first preset temperature to a second preset temperature, controlling the battery sample to perform static treatment at the second preset temperature, and detecting the battery terminal voltage at the second preset temperature;

[0037] S1123, when the static treatment time at the second preset temperature meets the third preset time, adjusting the second preset temperature to a third preset temperature, controlling the battery sample to perform static treatment at the third preset temperature, and detecting the battery terminal voltage at the third preset temperature;

[0038] S1124, when the static treatment time at the third preset temperature meets the fourth preset time, adjusting the third preset temperature to a fourth preset temperature, controlling the battery sample to perform static treatment at the fourth preset temperature, and detecting the battery terminal voltage at the fourth preset temperature;

[0039] S1125, when the static treatment time at the fourth preset temperature satisfies the fourth preset time, adjusting the fourth preset temperature to a fifth preset temperature, controlling the battery sample to perform a static treatment at the fifth preset temperature, and detecting the battery terminal voltage at the fifth preset temperature;

[0040] S1126, when the static treatment time at the fifth preset temperature meets the fourth preset time, controlling the battery sample to perform constant current discharge according to the first preset current;

[0041] S1127: When the discharged capacity reaches the first preset capacity, control the battery sample to repeatedly execute steps S1121-S1127 to a third preset number of times.

[0042] Preferably, the step of S132, controlling the battery sample to be processed according to a third rule based on the actual capacity, includes:

[0043] S1321, controlling the battery sample to perform a static treatment at a first preset temperature based on the actual capacity;

[0044] S1322: When the static treatment time at the first preset temperature satisfies a fifth preset time, adjusting the first preset temperature to a second preset temperature, and controlling the battery sample to perform a static treatment at the second preset temperature;

[0045] S1323, when the static treatment time at the second preset temperature meets the sixth preset time, adjusting the second preset temperature to a third preset temperature, and controlling the battery sample to perform static treatment at the third preset temperature;

[0046] S1324, when the static treatment time at the third preset temperature meets the seventh preset time, adjusting the third preset temperature to a fourth preset temperature, and controlling the battery sample to perform static treatment at the fourth preset temperature;

[0047] S1325, when the static treatment time at the fourth preset temperature meets the seventh preset time, adjusting the fourth preset temperature to the first preset temperature, and controlling the battery sample to perform the static treatment at the first preset temperature;

[0048] S1326: When the static treatment time at the first preset temperature meets a seventh preset time, controlling the battery sample to perform constant current discharge according to a first preset current;

[0049] S1327, when the discharged capacity reaches the first preset capacity, adjusting the first preset temperature to the second preset temperature, controlling the battery sample to perform a static treatment at the second preset temperature, and detecting the battery terminal voltage at the second preset temperature;

[0050] S1328, when the static treatment time at the second preset temperature satisfies an eighth preset time, adjusting the second preset temperature to a third preset temperature, controlling the battery sample to perform a static treatment at the third preset temperature, and detecting the battery terminal voltage at the third preset temperature;

[0051] S1329, when the static treatment time at the third preset temperature satisfies an eighth preset time, adjusting the third preset temperature to a fourth preset temperature, controlling the battery sample to perform a static treatment at the fourth preset temperature, and detecting the battery terminal voltage at the fourth preset temperature;

[0052] S1330: When the static treatment time at the fourth preset temperature satisfies the eighth preset time, adjusting the fourth preset temperature to the first preset temperature, controlling the battery sample to perform static treatment at the first preset temperature, and detecting the battery terminal voltage at the first preset temperature;

[0053] S1331. When the static treatment time at the first preset temperature satisfies an eighth preset time, the battery sample is controlled to repeatedly execute steps S1326-S1330 to a fourth preset number of times.

[0054] Preferably, when the test scheme is an HPPC test scheme, the step of testing the battery sample according to the test scheme to obtain the equivalent circuit parameters of the battery sample includes:

[0055] S21, controlling the battery sample to be processed according to a fourth rule so as to satisfy a first preset condition;

[0056] S22, the battery sample after control processing is processed according to the fifth rule to obtain HPPC test data;

[0057] S23. Obtaining equivalent circuit parameters of the battery sample according to a preset method based on the HPPC test data.

[0058] Preferably, the step of controlling the processed battery sample to be processed according to the fifth rule in S22 includes:

[0059] S221, controlling the processed battery sample to perform constant current discharge according to a second preset current;

[0060] S222, when the amount of electricity discharged by the battery sample reaches a second preset capacity, controlling the battery sample to be placed in a static state for a ninth preset time period;

[0061] S223, controlling the battery sample to perform pulse discharge according to a third preset current;

[0062] S224, when the pulse discharge duration meets the tenth preset duration, controlling the battery sample to be placed in a static state for an eleventh preset duration;

[0063] S225, controlling the battery sample to perform pulse charging according to a third preset current;

[0064] S226, when the pulse charging duration meets the tenth preset duration, controlling the battery sample to be placed in a static state for the eleventh preset duration;

[0065] The battery sample is controlled to repeatedly execute steps S221-S226, and the process stops when the power level of the battery sample is less than the second preset capacity.

[0066] Preferably, the step of obtaining the equivalent circuit parameters of the battery sample according to a preset method based on the HPPC test data in S23 includes:

[0067] The equivalent circuit parameters are obtained by identifying the HPPC test data of the first preset rest time stage according to the least squares online parameter identification method; and / or,

[0068] Based on the HPPC test data of the second preset rest time stage, the equivalent circuit parameters are obtained by identifying the equivalent circuit parameters according to the genetically optimized neural network offline parameter identification method; and / or,

[0069] The equivalent circuit parameters are obtained by identifying the HPPC test data of the first preset charge and discharge time stage according to the least squares online parameter identification method; and / or,

[0070] The equivalent circuit parameters are obtained by identifying the HPPC test data of the second preset charge and discharge time stage according to the genetically optimized neural network offline parameter identification method.

[0071] The present invention also provides a method for constructing a battery equivalent circuit simulation model, the method for constructing the simulation model comprising:

[0072] Construct a battery equivalent circuit model of a battery sample;

[0073] The parameters obtained by the battery equivalent circuit parameter identification method as described above are introduced into the circuit model to obtain a battery equivalent circuit simulation model of the battery sample.

[0074] Preferably, after the step of obtaining the battery equivalent circuit simulation model of the battery sample, the method further includes:

[0075] Running the simulation model according to a second preset condition to obtain a battery terminal voltage value of the simulation model;

[0076] Comparing and analyzing the battery terminal voltage value of the simulation model with the actual terminal voltage value;

[0077] The accuracy of the simulation model is determined based on the results of the comparative analysis.

[0078] Preferably, the step of constructing a battery equivalent circuit model of the battery sample comprises:

[0079] The circuit equation for determining the battery equivalent circuit model of the battery sample based on Kirchhoff's law is:

[0080]

[0081] Wherein, V1 is the electrochemical polarization voltage, and V2 is the concentration polarization voltage;

[0082] Simultaneous equations and equation (1), with SOC , V 1 and V 2 is the state variable, I is the input, and V is the output. The state space equation of the battery equivalent circuit model is obtained, and the state space equation is discretized to obtain the system state equation:

[0083]

[0084] Where T is the sampling time, τ1=R1C1, τ2=R2C2, C=battery nominal capacity × nominal voltage;

[0085] The mathematical equation of the battery sample is obtained:

[0086]

[0087] The battery equivalent circuit model is generated based on the mathematical equation.

[0088] The present invention also provides a battery equivalent circuit parameter identification system, the battery equivalent circuit parameter identification system comprising:

[0089] Battery samples;

[0090] An environmental chamber, used to provide a corresponding environmental temperature when testing the battery sample;

[0091] A charging and discharging device, used to control the charging and discharging of the battery sample;

[0092] A control device, used for controlling the environmental chamber and the charging and discharging equipment to test the battery sample to obtain battery equivalent circuit parameters of the battery sample;

[0093] The model building device is used to import the battery equivalent circuit parameters into the battery equivalent circuit model of the battery sample to obtain a simulation model of the battery equivalent circuit of the battery sample.

[0094] Preferably, the control device comprises:

[0095] An SOC-OCV testing unit, used to control the environmental chamber and the charging and discharging equipment to complete the SOC-OCV test on the battery sample, and obtain a two-dimensional graph of open circuit voltage based on the SOC-OCV test data;

[0096] The HPPC test unit is used to control the environmental chamber and the charging and discharging equipment to complete the HPPC test on the battery sample, and obtain the equivalent circuit parameters of the battery sample based on the HPPC test data.

[0097] Preferably, the model building device comprises:

[0098] A construction unit, used to establish a mathematical equation of a battery equivalent circuit model of the battery sample;

[0099] An importing unit, used for importing the test result into the mathematical equation;

[0100] A building unit is used to build the battery equivalent circuit simulation model based on the mathematical equation imported into the test result.

[0101] As described above, the method and system for building a battery equivalent circuit simulation model of the present invention can identify the parameter information of the battery equivalent circuit model based on a small amount of actual battery tests, thereby building a simulation model of the battery equivalent circuit. At the same time, it reduces the testing cost, helps battery research and development, and promotes the development of battery virtual testing technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0102] Figure 1 It is a flow chart of the battery equivalent circuit parameter identification method of the present invention.

[0103] Figure 2 It is a schematic diagram of the flow chart of the method for building a battery equivalent circuit simulation model of the present invention.

[0104] Figure 3 The figure is a flow chart of testing a battery sample according to the SOC-OCV test scheme to obtain equivalent circuit parameters according to the present invention.

[0105] Figure 4 A schematic diagram of a process of testing a battery sample according to the HPPC test scheme of the present invention to obtain equivalent circuit parameters;

[0106] Figure 5A schematic diagram of a flow chart of executing a SOC-OCV preliminary research test scheme for a control battery sample of the present invention;

[0107] Figure 6 A schematic diagram of a process for controlling and obtaining the actual capacity of a battery sample according to the present invention;

[0108] Figure 7 A schematic diagram of a flow chart of a control battery sample of the present invention for executing a step of obtaining actual capacity;

[0109] Figure 8 A schematic flow chart of the steps of performing a SOC-OCV preliminary research test on a control battery sample of the present invention;

[0110] Figures 9A-9J It is a schematic diagram showing the effect of the stability of the battery terminal voltage of the battery sample of the present invention at different power levels;

[0111] Fig.10 A schematic diagram of a process for executing a SOC-OCV formal test scheme for a control battery sample of the present invention;

[0112] Fig.11 A schematic diagram of the process of performing the SOC-OCV formal test steps for the control battery sample of the present invention;

[0113] Fig.12 It is a flow chart of the method for constructing a battery equivalent circuit simulation model of the present invention.

[0114] Fig.13 is a schematic diagram of a battery equivalent circuit simulation model of the present invention;

[0115] Fig.14 It is a schematic diagram of the effect of the nearest neighbor point interpolation method of the present invention;

[0116] Fig.15 A schematic diagram of a flow chart of verifying a battery equivalent circuit simulation model according to the present invention;

[0117] Fig.16 A schematic diagram of the structure of a system for building a battery equivalent circuit simulation model of the present invention;

[0118] Fig.17 It is a structural schematic diagram of the control device of the present invention;

[0119] Fig.18 It is a structural schematic diagram of the model building device of the present invention;

[0120] Fig.19 A schematic diagram of the effect of a system for building a battery equivalent circuit simulation model according to an embodiment of the present invention;

[0121] Fig. 20It is a schematic diagram of the two-dimensional effect of the open circuit voltage according to an embodiment of the present invention;

[0122] Figures 21A-21G A schematic diagram of parameter identification and voltage simulation results of an embodiment of the present invention;

[0123] Fig. 22 It is a schematic diagram of battery terminal voltage simulation results under HPPC working conditions according to an embodiment of the present invention;

[0124] Fig.23 Schematic diagram of a battery equivalent circuit simulation model according to an embodiment of the present invention. DETAILED DESCRIPTION

[0125] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0126] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0127] See also Figure 1 As shown, the present invention provides a battery equivalent circuit parameter identification method, the battery equivalent circuit parameter identification method comprising:

[0128] Receive the identification requirements of battery equivalent circuit parameters;

[0129] Determine a corresponding test plan according to the identification requirements;

[0130] The battery sample is tested according to the test plan to obtain equivalent circuit parameters of the battery sample.

[0131] In an embodiment of the present application, when constructing a corresponding battery equivalent circuit simulation model for different battery samples, it is necessary to obtain different parameters of different battery samples. In order to facilitate operation, a variety of test schemes are set in the scheme of the present application for obtaining different parameters of battery samples through testing. In this embodiment, before obtaining the parameters of the battery sample, it is necessary to receive the identification requirements of the battery sample parameters, and determine the corresponding test scheme through the identification requirements. For example, when the parameter identification requirements of the received battery sample are to obtain the open circuit voltage value of the battery sample under different conditions, such as different temperatures and different SOCs, the corresponding test scheme is determined to be the SOC-OCV test scheme; for example, when the parameter identification requirements of the received battery sample are to obtain the ohmic internal resistance value, electrochemical polarization internal resistance value, electrochemical polarization capacitance value, concentration polarization internal resistance value and concentration polarization capacitance value of the battery sample, the corresponding test scheme is determined to be the HPPC test scheme, and the battery sample is tested by executing the test scheme to obtain the equivalent circuit parameters of the battery sample.

[0132] In the embodiment of the present application, before building a battery equivalent circuit simulation model for a battery sample, it is necessary to obtain the performance of the battery terminal voltage of the battery sample at different temperatures and different SOCs, and obtain a two-dimensional graph of the open circuit voltage of the battery sample through temperature, SOC and the corresponding terminal voltage. In the example of the present application, when obtaining the terminal voltage of the battery sample at different temperatures and different SOCs, the SOC-OCV test scheme is used to test the battery sample. This test scheme can be used to set different temperatures, SOCs, test cycles, test periods, etc. according to actual test requirements.

[0133] See also Figure 2 As shown, the steps of testing the battery sample according to the SOC-OCV test scheme to obtain the equivalent circuit parameters of the battery sample include:

[0134] S11, controlling the battery sample to perform the first operation according to the SOC-OCV pre-research test plan;

[0135] S12, optimizing the SOC-OCV formal test plan based on the first operation result;

[0136] S13, controlling the battery to perform a second operation according to the optimized SOC-OCV formal test scheme;

[0137] S14, processing the second operation result to obtain a two-dimensional graph of the open circuit voltage of the battery.

[0138] In the embodiment of the present application, when obtaining the SOC-OCV test data of the battery sample through the SOC-OCV test scheme, the SOC-OCV test scheme is firstly pre-studied, that is, the battery sample is controlled to be tested according to the SOC-OCV pre-research test scheme to obtain the battery terminal voltage information of the battery sample. For example, at 10% SOC, 20% SOC, 30% SOC, 40% SOC, 60% SOC, 80% SOC, and 90% SOC, there is a situation where the battery terminal voltage is not stabilized within the preset static time, and at 100% SOC, the battery terminal voltage shows a downward trend when it is static. Then, according to the test data of the SOC-OCV pre-research test scheme, the SOC-OCV pre-research test scheme is optimized, for example, the static time of the battery at 90% SOC and below is lengthened, and the static time of the battery at 100% SOC is shortened, etc. Then, according to the optimized SOC-OCV formal test plan, the formal test process is performed on the battery samples to obtain the open circuit voltage values ​​of battery samples at different temperatures and different SOCs under the SOC-OCV formal test plan. By adopting the battery SOC-OCV test plan with different static time, the accuracy of battery open circuit voltage identification under different operating conditions is effectively improved.

[0139] In one example, after obtaining the open circuit voltage value of the battery sample at the test operating point through the above test scheme, several identified open circuit voltage values ​​are used as target points, and a two-dimensional 8th-order polynomial fitting is performed on the open circuit voltage with temperature and SOC as dimensions, thereby obtaining a two-dimensional graph of the open circuit voltage of the battery sample.

[0140] In an embodiment of the present application, before building a battery equivalent circuit simulation model for a battery sample, it is also necessary to obtain the values ​​of preset parameters of the battery sample, such as ohmic internal resistance, electrochemical polarization internal resistance, electrochemical polarization capacitance, concentration polarization internal resistance, and concentration polarization capacitance. In an exemplary scenario, before obtaining the values ​​of the preset parameters, it is necessary to first obtain the HPPC test data of the battery sample through an HPPC test, and then process the HPPC test data of the battery sample based on the least squares method combined with the online and offline identification algorithms to obtain the values ​​of the preset parameters.

[0141] For example, the HPPC test data of the battery sample in the first preset standing time stage is obtained as the data segment to be identified, such as the HPPC test data of the first 50% standing time stage of the total standing process is used as the data segment to be identified. Since the polarization influence of the battery in this stage is relatively large, this influence is difficult to be accurately simulated by the offline algorithm. The voltage error simulated by the battery equivalent model built based on the offline parameter identification algorithm is relatively large. Therefore, it is necessary to use the relevant online identification algorithm to improve the parameter identification accuracy. The least squares method has simple calculation logic and fast calculation speed. Therefore, this application preferably uses the least squares method of online parameter identification algorithm to identify the above-mentioned preset parameters. The input of the least squares method of online parameter identification algorithm is the real-time current and real-time voltage of the operating condition section to be identified, and the output is the calculated values ​​of the above-mentioned 5 preset impedance parameters at each moment, that is, an impedance parameter array based on the time axis.

[0142] For example, the HPPC test data of the battery sample in the second preset rest time stage is obtained as the data segment to be identified, such as the HPPC test data of the last 50% rest time stage of the total rest process is used as the data segment to be identified. Since the polarization effect of the battery is relatively small at this stage, the battery terminal voltage is relatively stable, and the accuracy of the offline parameter identification algorithm can meet the requirements; at the same time, since I=0 and dV=0 will appear at this stage, the denominator will be 0 in the parameter decoupling process of the online identification algorithm, and the parameter value cannot be obtained. Therefore, an offline identification method must be used. Although the neural network parameter identification method based on genetic optimization has a slow calculation speed, it has a high identification accuracy for the parameters. Therefore, the present invention preferably uses a neural network offline parameter identification algorithm based on genetic optimization to identify the above-mentioned preset parameters. The input of the neural network offline parameter identification algorithm based on genetic optimization is the rated capacity of the battery, the actual time, actual current, actual voltage of the operating condition to be identified, and the open circuit voltage value with a smaller granularity obtained through the SOC-OCV test, and the output is the numerical value of the above five preset impedance parameters identified through the operating condition.

[0143] For example, the HPPC test data of the battery sample in the first preset charge and discharge time stage is obtained as the data segment to be identified, such as the HPPC test data of the battery sample in the first 50% time stage of the total charge or total discharge process is taken as the data segment to be identified. It can be seen from the values ​​of a series of impedance parameter groups based on the time axis obtained by the online identification method that in the initial stage of charge and discharge, the parameters fluctuate violently, and it is difficult to obtain accurate parameter identification results by offline identification. Therefore, the present invention preferably adopts the least squares method online parameter identification to improve the identification accuracy of the parameters. The input of the algorithm is the real-time current and real-time voltage of the working condition segment to be identified, and the output is the calculated values ​​of the above 5 preset impedance parameters at each moment, that is, an impedance parameter array based on the time axis.

[0144] For example, the HPPC test data of the second preset charge and discharge time stage of the battery sample is obtained as the data segment to be identified, such as the HPPC test data of the battery sample in the last 50% time stage of the total charge or total discharge process is taken as the data segment to be identified. It can be seen from the values ​​of a series of impedance parameter groups based on the time axis obtained by the online identification method that in the later stage of charging and discharging, the fluctuations of each parameter are relatively gentle, the state of the battery sample is stable, and the error of the parameter obtained by the offline algorithm identification can meet the accuracy requirements. Therefore, the present invention preferably uses a neural network offline parameter identification algorithm based on genetic optimization to identify the above-mentioned preset parameters. Here, the input of the algorithm is the battery rated capacity, the actual time, actual current, actual voltage of the operating condition segment to be identified, and the open circuit voltage value with a smaller granularity obtained through the SOC-OCV test, and the output is the values ​​of the above-mentioned 5 preset impedance parameters identified through the operating condition segment.

[0145] refer to Figure 3 The steps of testing the battery sample according to the HPPC test scheme to obtain the equivalent circuit parameters of the battery sample include:

[0146] S21, controlling the battery sample to be processed according to a fourth rule so as to satisfy a first preset condition;

[0147] S22, the battery sample after the control process is processed according to the fifth rule to obtain HPPC test data;

[0148] S23. Obtaining equivalent circuit parameters of the battery sample according to a preset method based on the HPPC test data.

[0149] In an embodiment of the present application, when obtaining HPPC test data, the battery sample is first processed according to the fourth rule so that the battery sample meets the first preset condition. In an exemplary scenario, before starting the HPPC test, the battery sample is fully charged by constant voltage and current limiting, and then the battery sample with an SOC of 100% is left to stand until the voltage is in a stable state, that is, the amount of electricity in the battery sample at this time is the actual capacity of the battery sample. Further, the battery is controlled to be processed according to the fifth rule to obtain HPPC test data.

[0150] refer to Figure 4 As shown, the step of controlling the processed battery to be processed according to the fifth rule includes:

[0151] S221, the battery after the control process is discharged at a constant current according to a second preset current;

[0152] S222, when the amount of electricity discharged by the battery reaches a second preset capacity, controlling the battery to be placed in a static state for a ninth preset time period;

[0153] S223, controlling the battery to perform pulse discharge according to a third preset current;

[0154] S224, when the pulse discharge duration meets the tenth preset duration, controlling the battery to be placed in a static state for an eleventh preset duration;

[0155] S225, controlling the battery to perform pulse charging according to a third preset current;

[0156] S226, when the pulse charging duration meets the tenth preset duration, controlling the battery to be placed in a static state for the eleventh preset duration;

[0157] The battery sample is controlled to repeatedly execute steps S221 - S226 , and the process stops when the capacity of the battery sample is less than the second preset capacity.

[0158] In the embodiment of the present application, when obtaining the HPPC test data of the battery sample, after the above-mentioned fully charged and voltage-stable battery sample is discharged at a constant current, a static treatment is performed to make the voltage of the battery sample stable, and then the control is continued to perform pulse discharge on the battery sample. Since the pulse discharge usually has a large current, the battery power will drop sharply in a short time, and further static treatment is required until the battery terminal voltage of the battery sample is stable, and the battery sample is charged with the same pulse current, and the charged battery sample is statically treated until the battery terminal voltage is stable. Repeat the above steps until the battery power is lower than the preset capacity.

[0159] In an exemplary scenario, when the battery is fully charged and the voltage is stable, the battery is controlled to discharge at a constant current of 1C. When the amount of electricity released by the battery sample is 5% of the actual capacity of the battery sample, that is, the SOC of the battery drops by 5%, the battery sample is left to stand for 10 hours to stabilize the battery terminal voltage of the battery sample. Then, the battery is controlled to pulse discharge at a current of 3C for 10S, and then left to stand for 5 hours until the battery terminal voltage is stable. Then, the battery is controlled to pulse charge at a current of 3C for 10S, and then left to stand for 5 hours. The above steps are repeated until the current of the battery sample is 5% SOC. In this embodiment, the currents of the above-mentioned constant current discharge, pulse discharge, and pulse charging can be adjusted according to the actual test requirements. At the same time, the discharge interval of 5% SOC each time can also be adjusted according to the actual application scenario. The above is only an exemplary description and cannot be used as a limitation on the scope of protection of this application.

[0160] refer to Figure 5 As shown, when the control battery sample is tested according to the SOC-OCV pre-research test plan, follow the following steps:

[0161] S111, controlling the battery sample to be processed according to a first rule to obtain an actual capacity of the battery sample;

[0162] In the embodiments of the present application, since the chemical reaction inside the battery is not stable when it is just fully charged, especially in the overcharged state, taking lithium batteries as an example, overcharging can cause the chemical reaction inside the lithium battery to get out of control or even explode. Therefore, the battery needs to be left to stand for a period of time after being fully charged before it can start working to avoid getting out of control or exploding. In this embodiment, in order to accurately obtain the actual capacitance of the battery sample, after the battery is fully charged, the battery sample needs to be processed according to the preset rules so that the battery sample can be kept at full power and the battery terminal voltage is stable for the actual capacitance test.

[0163] refer to Figure 6 As shown, the step of controlling the battery sample to be processed according to the first rule to obtain the actual capacity of the battery sample includes:

[0164] S1111, controlling the battery sample to repeatedly perform charge and discharge processing to a first preset number of times based on a first preset temperature;

[0165] S1112, determining an average value of the discharge capacity of the battery sample based on a second preset number of times as the actual capacity of the battery sample;

[0166] Wherein, the second preset number of times is less than the first preset number of times.

[0167] In the embodiment of the present application, in order to ensure more accurate acquisition of the actual capacity of the battery sample, the battery sample is controlled to be repeatedly charged and discharged under a preset temperature environment. For example, the battery sample is repeatedly charged and discharged under a normal temperature of 25°C, and the battery capacity of the battery sample at full charge and stable voltage after each charge and discharge is obtained. The actual capacity of the battery sample is determined by averaging the multiple battery capacities. For example, the battery sample is controlled to perform the charge and discharge process 4 times under a normal temperature of 25°C, and the last three charge and discharge capacities are recorded. By calculating the average of the three charge and discharge capacities, the average capacity is used as the actual capacity of the battery sample.

[0168] refer to Figure 7 As shown, the step of controlling the battery to repeat the charge and discharge process to a first preset number of times includes:

[0169] S11111, controlling the battery sample to be placed at a first preset temperature for static treatment;

[0170] S11112: When the static treatment time meets the first preset time, controlling the battery to perform constant current discharge at the first preset temperature and according to the first preset current;

[0171] S11113, when the voltage of the battery is less than the discharge cut-off voltage, controlling the battery to be placed at the first preset temperature;

[0172] S11114: When the static treatment time meets the first preset time, controlling the battery to perform constant current charging at the first preset temperature and according to the first preset current;

[0173] S11115, when the voltage of the battery is greater than the charging cut-off voltage, controlling the battery to switch to constant voltage charging;

[0174] S11116. When the charging current is less than a preset current, control the battery to repeatedly execute the above steps to the first preset number of times.

[0175] In an exemplary scenario, as shown in Table 1, under a temperature of 25°C, the battery is controlled to stand for 1 hour when fully charged. When the battery terminal voltage of the battery sample is stable, the battery sample is controlled to be discharged at a constant current of 0.33C. When it is detected that the voltage of the battery sample is less than the discharge cut-off voltage of the battery, that is, the battery is discharged and cannot be discharged, the battery is controlled to stand for 1 hour to stabilize the chemical reaction inside the battery. Then, the battery sample is charged at a constant current of 0.33C. When it is detected that the battery terminal voltage of the battery sample is greater than the charge cut-off voltage of the battery, the battery sample is controlled to be charged at a constant voltage. When it is detected that the charging current is less than 0.05C, the battery sample is controlled to repeat the above steps. The above is only an exemplary description. In the actual operation process of measuring the actual capacity of the battery sample, the ambient temperature, the charge and discharge current, and the length of the standing time can be adjusted according to the needs, which will not be elaborated here.

[0176]

[0177] Table 1

[0178] S112: Based on the actual capacity, control the battery sample to be processed according to a second rule to obtain the first operation result.

[0179] In an embodiment of the present application, the actual capacity of the battery sample is obtained based on the above method, and the battery sample is controlled to be processed according to the second rule, so as to obtain the stabilization time of the battery terminal voltage of the battery sample under working conditions of different temperatures and different power SOCs.

[0180] refer to Figure 8As shown, the step of controlling the battery sample to be processed according to the second rule includes:

[0181] S1121, controlling the battery to perform a static treatment at a first preset temperature based on the actual capacity, and detecting the battery terminal voltage at the first preset temperature;

[0182] S1122, when the static treatment time at the first preset temperature meets the second preset time, adjusting the first preset temperature to a second preset temperature, controlling the battery to perform a static treatment at the second preset temperature, and detecting the battery terminal voltage at the second preset temperature;

[0183] S1123, when the static treatment time at the second preset temperature meets the third preset time, adjusting the second preset temperature to a third preset temperature, controlling the battery to perform a static treatment at the third preset temperature, and detecting the battery terminal voltage at the third preset temperature;

[0184] S1124, when the static treatment time at the third preset temperature meets the fourth preset time, adjusting the third preset temperature to a fourth preset temperature, controlling the battery to perform a static treatment at the fourth preset temperature, and detecting the battery terminal voltage at the fourth preset temperature;

[0185] S1125, when the static treatment time at the fourth preset temperature satisfies the fourth preset time, adjusting the fourth preset temperature to a fifth preset temperature, controlling the battery to perform a static treatment at the fifth preset temperature, and detecting the battery terminal voltage at the fifth preset temperature;

[0186] S1126, when the static treatment time at the fifth preset temperature meets the fourth preset time, controlling the battery to perform constant current discharge according to the first preset current;

[0187] S1127: When the discharged capacity reaches the first preset capacity, control the battery to repeatedly execute steps S1121-S1127 to a third preset number of times.

[0188] In an exemplary scenario, referring to Table 2, first, the capacity of the battery sample is controlled to be the actual capacity, and the battery sample is controlled to be stationary for 3 hours in an environment of 25°C, and the battery terminal voltage of the battery sample during the 3-hour stationary period is detected and saved; then, the battery sample is controlled to be stationary for 12 hours in an environment of 0°C, and the battery terminal voltage of the battery sample during the 12-hour stationary period is detected and saved; then, the battery sample is controlled to be stationary for 8 hours in an environment of 15°C, and the battery terminal voltage of the battery sample during the 8-hour stationary period is detected and recorded; then, the battery sample is controlled to be stationary for 8 hours in an environment of 35°C, Detect and save the battery terminal voltage of the battery sample during the 8-hour static period; then, control the battery to be statically treated for 8 hours in an environment of 25°C, detect and save the battery terminal voltage of the battery sample during the 8-hour static period; then, control the battery to discharge at a constant current of 0.33C, and repeat the above steps when it is detected that the discharge capacity reaches 10% of the actual capacity, that is, when the static treatment is performed for the second time, the battery sample power is 90% of the original actual capacity, and the battery sample power for the third time is 80% of the original actual capacity, and so on, until the battery sample power is 0, and the battery sample can be subjected to 10 OCV tests according to the discharge amount of 10% of the actual capacity each time. In this embodiment, the above is only an exemplary explanation. In the actual test process, the user can adjust different static temperatures according to the needs of the actual scene, and can also process according to different discharge amounts, which will not be elaborated here.

[0189]

[0190] Table 2

[0191] In the embodiment of the present application, based on the above SOC-OCV pre-research test scheme, it can be obtained that the battery sample has a situation where the battery terminal voltage is not stable within the preset static time at 10% SOC, 20% SOC, 30% SOC, 40% SOC, 60% SOC, 80% SOC, and 90% SOC, respectively. Figures 9A-9I As shown, at 100% SOC, the battery terminal voltage shows a downward trend when it is static, which indicates that the battery has self-discharged in this state. Figure 9J shown.

[0192] refer to Fig.10 As shown, the steps of controlling the battery sample to perform a second run according to the optimized SOC-OCV formal test scheme include:

[0193] S131, controlling the battery to be processed according to a first rule to obtain an actual capacity of the battery;

[0194] In an embodiment of the present application, when testing a battery sample based on the SOC-OCV formal test scheme, it is also necessary to fully charge the battery sample, and then process the battery sample according to the above-mentioned steps S11111-S11116. As shown in Table 3, the average value of the discharge capacity detected multiple times is taken as the actual capacity of the battery sample, which will not be repeated here.

[0195]

[0196] Table 3

[0197] S132: Based on the actual capacity, control the battery to perform processing according to a third rule to obtain the second operation result.

[0198] In an embodiment of the present application, the actual capacity of the battery sample is obtained based on the above method, and the battery sample is controlled to be processed according to the third rule, so as to obtain the stabilization time of the battery terminal voltage of the battery sample under working conditions of different temperatures and different power SOCs.

[0199] refer to Fig.11 As shown, the step of controlling the battery to be processed according to the third rule based on the actual capacity includes:

[0200] S1321, controlling the battery to perform a static treatment at a first preset temperature based on the actual capacity;

[0201] S1322: When the static treatment time at the first preset temperature satisfies a fifth preset time, adjusting the first preset temperature to a second preset temperature, and controlling the battery to perform a static treatment at the second preset temperature;

[0202] S1323, when the static treatment time at the second preset temperature satisfies a sixth preset time, adjusting the second preset temperature to a third preset temperature, and controlling the battery to perform a static treatment at the third preset temperature;

[0203] S1324, when the static treatment time at the third preset temperature satisfies a seventh preset time, adjusting the third preset temperature to a fourth preset temperature, and controlling the battery to perform a static treatment at the fourth preset temperature;

[0204] S1325: When the standing treatment time at the fourth preset temperature satisfies the seventh preset time, adjusting the fourth preset temperature to the first preset temperature, and controlling the battery to perform standing treatment at the first preset temperature;

[0205] S1326: When the static treatment time at the first preset temperature satisfies a seventh preset time, controlling the battery to perform constant current discharge according to the first preset current;

[0206] S1327, when the discharged capacity reaches the first preset capacity, adjusting the first preset temperature to the second preset temperature, controlling the battery to perform a static treatment at the second preset temperature, and detecting the battery terminal voltage at the second preset temperature;

[0207] S1328: When the static treatment time at the second preset temperature satisfies an eighth preset time, adjusting the second preset temperature to a third preset temperature, controlling the battery to perform a static treatment at the third preset temperature, and detecting the battery terminal voltage at the third preset temperature;

[0208] S1329, when the static treatment time at the third preset temperature satisfies an eighth preset time, adjusting the third preset temperature to a fourth preset temperature, controlling the battery to perform a static treatment at the fourth preset temperature, and detecting the battery terminal voltage at the fourth preset temperature;

[0209] S1330: When the static treatment time at the fourth preset temperature satisfies the eighth preset time, adjusting the fourth preset temperature to the first preset temperature, controlling the battery to perform static treatment at the first preset temperature, and detecting the battery terminal voltage at the first preset temperature;

[0210] S1331. When the static treatment time at the first preset temperature satisfies an eighth preset time, the battery is controlled to repeatedly execute steps S1326-S1330 to a fourth preset number of times.

[0211] In an exemplary scenario, referring to Table 4, first, the capacity of the battery sample is controlled to be the actual capacity, and the battery sample is controlled to be at 25°C, 0°C, 15°C, 35°C and 25°C, and the battery sample is controlled to stand at the five temperatures for 24 hours respectively; then, the battery sample is controlled to be discharged at a constant current of 0.33C, and when it is detected that the discharge capacity reaches 10% of the actual capacity, that is, the remaining capacity of the battery is 90% SOC, the battery is controlled to stand at 0°C, 15°C, 35°C and 25°C for 24 hours respectively, and the battery terminal voltage at the last step of each standing stage is detected and saved, and then, the test is repeated according to steps 11-15 of Table 4, and the battery terminal voltage after each standing stage is obtained when the battery capacity is 80% SOC, 70% SOC, 60% SOC, 50% SOC, 40% SOC, 30% SOC, 20% SOC, 10% SOC, respectively. In this embodiment, the above is only an exemplary explanation. In the actual test process, the user can adjust different static temperatures according to the needs of the actual scene, and can also process according to different discharge amounts, which will not be elaborated here.

[0212]

[0213] Table 4

[0214] refer to Fig.12 As shown, the present invention provides a method for constructing a battery equivalent circuit simulation model, and the method for constructing a battery equivalent circuit simulation model includes:

[0215] Construct a battery equivalent circuit model of a battery sample;

[0216] The parameters obtained by the above-mentioned battery equivalent circuit parameter identification method are introduced into the circuit model to obtain a battery equivalent circuit simulation model of the battery sample.

[0217] In an embodiment of the present application, after obtaining the parameters of the equivalent circuit of the battery sample, further, a corresponding battery equivalent circuit model is constructed for the battery sample, and the equivalent circuit parameters of the battery sample obtained through the SOC-OCV test and the HPPC test are imported into the battery equivalent circuit model, thereby obtaining a battery equivalent circuit simulation model of the battery sample.

[0218] In an embodiment of the present application, before the two-dimensional graph of the open circuit voltage obtained by the above-mentioned SOC-OCV test and the parameters obtained by the HPPC test are imported into the battery equivalent circuit model, it is first necessary to establish a circuit equation of the corresponding equivalent circuit model according to the battery sample. In one example, according to Kirchhoff's law, the circuit equation of the battery equivalent circuit model is sorted out as follows:

[0219]

[0220] in, V 1 is the electrochemical polarization voltage, V 2 is the concentration polarization voltage;

[0221] Simultaneous equations and equation (1), with SOC , V 1 and V 2 is the state variable, I is the input, and V is the output. The state space equation of the battery equivalent circuit model is obtained, and the state space equation is discretized to obtain the system state equation:

[0222]

[0223] Where T is the sampling time, τ1=R1C1, τ2=R2C2, C=battery nominal capacity (mAh) × nominal voltage;

[0224] The mathematical equation of the battery is obtained:

[0225]

[0226] The battery equivalent circuit model is generated based on the mathematical equation.

[0227] In an embodiment of the present application, the obtained two-dimensional graph of the open circuit voltage of the battery sample and the values ​​of the preset parameters, such as the ohmic internal resistance value, the electrochemical polarization internal resistance value, the electrochemical polarization capacitance value, the concentration polarization internal resistance value, and the concentration polarization capacitance value, are imported into the battery equivalent circuit model of the battery sample, and a one-dimensional dynamic battery equivalent circuit simulation model is generated by a visual simulation tool, with reference to Fig.13 shown.

[0228] In an embodiment of the present application, the five preset impedance parameters obtained through the HPPC test: ohmic internal resistance, electrochemical polarization internal resistance, electrochemical polarization capacitance, concentration polarization internal resistance and concentration polarization capacitance are imported into the battery equivalent circuit model, which requires the use of other algorithms to import. Since the present application is only a test completed for a certain operating point through the HPPC test, the values ​​of the above five preset parameters obtained are also only the impedance parameter values ​​at the determined operating point. Therefore, it is also necessary to determine the values ​​of the impedance parameters at the non-determined operating point. In an embodiment of the present application, the impedance parameters of any other operating point in the test operating point interval are obtained by the nearest neighbor interpolation method.

[0229] Exemplarily, the five impedance parameters of the non-test operating point are obtained by the nearest neighbor interpolation method: ohmic internal resistance, electrochemical polarization internal resistance, electrochemical polarization capacitance, concentration polarization internal resistance, and concentration polarization capacitance. In the present invention, the nearest neighbor interpolation method has three dimensions, namely SOC, temperature, and charge and discharge rate. The following selects SOC and temperature as two dimensions for expansion and explanation, and reference is made to Fig.14 As shown:

[0230] For each impedance parameter, each determined operating point covers a four-square grid. All operating points falling within the four-square grid use the parameter identification results of this determined operating point. For the operating points located on the four sides of the entire grid, the four-square grid covers all operating points outside itself and its range. For example, the red operating point is [SOC=37.5%, temperature=-5℃], then the 5 impedance parameters of the red operating point use the identification results of the [SOC=40%, temperature=0℃] operating point; the dark green operating point is [SOC=53%, temperature=-30℃], and the 5 impedance parameters of the dark green operating point use the identification results of the [SOC=50%, temperature=-20℃] operating point. The above is only an exemplary explanation based on the two dimensions of SOC and temperature. When the charge and discharge rate needs to be added, the charge and discharge rate needs to be used as the third dimension. At that time, you only need to Fig.14 The two-dimensional graph shown is converted into a three-dimensional graph, that is, the plane four-square grid of the working condition is divided into a working condition cube in three-dimensional space. In this example, when the density of the test working condition points increases, the accuracy of the five impedance parameters of the non-test working condition points will also be greatly improved, and at the same time, the impact of parameter mutations on the simulation voltage will also be reduced.

[0231] The above is only an exemplary description. In the actual test process, the five impedance parameters of the non-test operating points can also be obtained by other means. Other methods of obtaining non-test operating points based on the above ideas are within the protection scope of this application and will not be repeated here.

[0232] refer to Fig.15 As shown in FIG. 1 , the steps for verifying the battery equivalent circuit simulation model include:

[0233] Running the simulation model according to a second preset condition to obtain a battery terminal voltage value of the simulation model;

[0234] Comparing and analyzing the battery terminal voltage value of the simulation model with the actual terminal voltage value;

[0235] The accuracy of the simulation model is determined based on the results of the comparative analysis.

[0236] In an embodiment of the present application, after the open circuit voltage two-dimensional graph and preset parameter values ​​are imported into the battery equivalent circuit model of the battery sample to obtain a simulation model of the battery equivalent circuit, the battery equivalent circuit simulation model is controlled to operate according to the same current operating conditions as the battery in the actual test to obtain the battery terminal voltage of the simulation model, and the battery terminal voltage of the simulation model is compared with the actual terminal voltage of the battery sample. When the difference between the battery terminal voltage of the simulation model and the actual terminal voltage of the battery sample is less than the preset difference, it can be verified that the accuracy of the battery equivalent circuit simulation model is high; if it is greater than the preset value, it can be verified that the accuracy of the battery equivalent circuit simulation model is low.

[0237] In another exemplary scenario, different difference ranges are set, and different accuracy levels are determined according to different difference ranges. That is, the accuracy level of the battery equivalent circuit simulation model is determined by judging the difference range corresponding to the difference between the battery terminal voltage of the simulation model and the actual terminal voltage of the battery sample.

[0238] refer to Fig.16 As shown, the present invention also provides a battery equivalent circuit parameter identification system, which includes: a battery sample, an environmental chamber, a charging and discharging device, a control device, and a model building device.

[0239] In the embodiments of the present application, the battery targeted by the present application scheme can be a lithium iron phosphate battery, a lead-acid battery, or other energy storage batteries; before building a simulation model of the battery, the battery sample needs to be placed in an environmental chamber, that is, the environmental chamber is used to provide the ambient temperature during the battery test, and at the same time, the battery sample is controlled by a charging and discharging device to perform constant current discharge, constant current charging, pulse discharge, pulse charging, etc. During the test, the control device controls the environmental chamber to adjust the temperature according to the test requirements and test rules, and controls the charging and discharging device to adjust the charging and discharging current and the charging and discharging time, such as conducting SOC-OCV tests, HPPC tests, etc.; the model building device imports the relevant data obtained from the test into the battery equivalent circuit model of the battery sample to obtain a simulation model of the battery equivalent circuit.

[0240] refer to Fig.17 As shown, the control device includes: a SOC-OCV test unit and a HPPC test unit.

[0241] In an embodiment of the present application, the control device performs a SOC-OCV test on a battery sample through a SOC-OCV test unit. Specifically, the battery sample is first controlled to be tested in accordance with the SOC-OCV pre-research test method, and the SOC-OCV pre-research test scheme is optimized according to the test results. For example, the standing time of the battery at 90% SOC and below is lengthened, and the standing time of the battery at 100% SOC is shortened, etc. Then, the battery sample is tested here according to the optimized SOC-OCV formal test scheme, and the test results are processed. For example, several open circuit voltage values ​​that have been identified are used as target points, and temperature and SOC are used as dimensions to perform a two-dimensional 8th-order polynomial fitting on the open circuit voltage, thereby obtaining a two-dimensional graph of the open circuit voltage of the battery sample. The SOC-OCV test of the battery sample refers to the aforementioned test steps, which will not be repeated here.

[0242] In an embodiment of the present application, the control device also performs an HPPC test on the battery sample through the HPPC test unit. Specifically, the battery sample is first charged and then placed in a static state. When the battery sample is fully charged and the voltage is stable, the HPPC test is performed on the battery sample. After processing the HPPC test data based on the least squares method combined with the online and offline identification algorithm, preset impedance parameters are obtained, such as: ohmic internal resistance value, electrochemical polarization internal resistance value, electrochemical polarization capacitance value, concentration polarization internal resistance value and concentration polarization capacitance value.

[0243] refer to Fig.18 As shown, the model building device includes: a construction unit, an introduction unit and a building unit.

[0244] In an embodiment of the present application, before building a battery equivalent circuit simulation model of a battery, it is necessary to establish a circuit equation of a corresponding battery equivalent circuit model according to relevant information of the battery and based on Kirchhoff's law through a construction unit, for example:

[0245]

[0246] in, V 1 is the electrochemical polarization voltage, V 2 is the concentration polarization voltage;

[0247] Simultaneous equations and equation (1), with SOC , V 1 and V 2 is the state variable, I is the input, and V is the output. The state space equation of the battery equivalent circuit model is obtained, and the state space equation is discretized to obtain the system state equation:

[0248]

[0249] Where T is the sampling time, τ1=R1C1, τ2=R2C2, C=battery nominal capacity (mAh) × nominal voltage;

[0250] The mathematical equation of the battery is obtained:

[0251]

[0252] The battery equivalent circuit model is generated based on the mathematical equation.

[0253] Further, the open circuit voltage or the two-dimensional graph of the open circuit voltage obtained by the SOC-OCV test unit and the value of the preset impedance parameter obtained by the HPPC test unit are imported into the mathematical equation of the battery equivalent circuit model by the import unit, and the building unit builds the battery equivalent circuit simulation model of the battery sample according to the mathematical equation of the imported test results, referring to Fig.13 shown.

[0254] In an embodiment of the present application, the model building device also includes a verification unit, which controls the battery equivalent circuit simulation model to operate according to the same current operating conditions as the battery in the actual test to obtain the battery terminal voltage of the simulation model, and compares the battery terminal voltage of the simulation model with the actual terminal voltage of the battery sample. When the difference between the battery terminal voltage of the simulation model and the actual terminal voltage of the battery sample is less than a preset difference, it can be verified that the accuracy of the battery equivalent circuit simulation model is high; if it is greater than the preset value, it can be verified that the accuracy of the battery equivalent circuit simulation model is low.

[0255] refer to Fig.19 As shown, the construction system of the battery equivalent circuit simulation model of the present invention, wherein a single charge and discharge device with a maximum discharge circuit of 300A, a maximum discharge voltage of 5V, and an accuracy of 0.02% is selected, and the battery is controlled to perform constant current discharge, constant current charging, pulse discharge, and pulse charging operations, and a high and low temperature test box with an adjustable temperature range of -40°C to 150°C is selected to provide the ambient temperature required for the test for the battery to be tested; during the test process, the user controls the single charge and discharge device through a control computer to complete the test of the battery according to the SOC-OCV test process and the HPPC test process, and controls the high and low temperature test box through a control computer to adjust the ambient temperature of the battery sample during the test process, and the control computer generates a battery equivalent circuit simulation model based on the test results and the battery equivalent circuit model of the battery sample. In an example case, during the test process, the user can also directly control the high and low temperature test box to adjust the ambient temperature of the test according to the test requirements.

[0256] In the embodiment of the present application, the battery sample is a lithium iron phosphate battery for SOC-OCV test, wherein the basic parameters of the battery sample are shown in Table 5:

[0257]

[0258] Table 5

[0259] The ternary lithium battery is placed in the high and low temperature test box, and is tested by a single-cell charge and discharge device according to the SOC-OCV test conditions shown in Table 6 to obtain SOC-OCV test data.

[0260]

[0261] Table 6

[0262] After testing according to the SOC-0CV test condition, the battery open circuit voltage identification results under several fixed operating points are obtained, and the battery open circuit voltage value under all operating conditions is obtained.

[0263] After the above SOC-OCV test, the open circuit voltages of 11 determined operating points at 25°C were obtained, as shown in Table 7:

[0264]

[0265] Table 7

[0266] According to the open circuit voltage values ​​of the 11 determined operating points obtained above, a two-dimensional 8th-order polynomial fitting process is performed to obtain the fitting curve as shown in FIG. Fig. 20 shown.

[0267] The ternary lithium battery is placed in the high and low temperature test chamber, and is tested by a single-cell charge and discharge device according to the HPPC test conditions shown in Table 8 to obtain HPPC test data.

[0268]

[0269] Table 8

[0270] After identifying the HPPC test data using multi-algorithm fusion, offline combination and working condition identification methods, the ohmic internal resistance value R0, electrochemical polarization internal resistance value R1, electrochemical polarization capacitance value C1, concentration polarization internal resistance value R2, and concentration polarization capacitance value C2 of the battery equivalent circuit model are obtained.

[0271] Among them, according to the above-mentioned least squares method online parameter identification method, the online parameter identification is performed on the charging pulse stage of 90% SOC (charging rate is 1C) in an environment of 25°C, as follows Figures 21A-21G From the parameter identification and voltage simulation results shown, it can be seen that the online identification method has a small error and can meet the accuracy requirements.

[0272] Among them, according to the above-mentioned genetic optimization neural network offline parameter identification method, offline parameter identification is performed for pulse charging (charging rate 1C), pulse discharging (discharging rate 1C), and SOC adjustment (discharging rate 1 / 3C) stages under each SOC state in an environment of 25°C. The parameter identification results are shown in Table 9. The battery terminal voltage simulation results under HPPC conditions are shown in Table 9. Fig. 22 As shown, it can be seen from the results that the offline identification method has high accuracy in the second half of charging and discharging and the second half of standing, which can meet the accuracy requirements.

[0273]

[0274] Table 9

[0275] The above Fig. 20 The voltage fitting curve shown is directly imported into the Simulink model as the simulation value of the battery open circuit voltage, and the five impedance parameters (ohmic internal resistance value R0, electrochemical polarization internal resistance value R1, electrochemical polarization capacitance value C1, concentration polarization internal resistance value R2, concentration polarization capacitance value C2) are imported into the Simulink model through the nearest neighbor interpolation method. Then, a battery equivalent circuit simulation model equivalent to the actual battery can be obtained, as shown in Fig.23 shown.

[0276] In summary, the method and system for building a battery equivalent circuit simulation model of the present invention can greatly improve the parameter identification accuracy of the battery model based on a small amount of actual battery tests and with the help of a series of intelligent algorithms, thereby building a battery equivalent circuit simulation model with high accuracy. This method reduces testing costs, helps battery research and development, and promotes the development of battery virtual testing technology. Therefore, the present invention effectively overcomes the various shortcomings of the prior art and has a high industrial utilization value.

[0277] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by a person of ordinary skill in the art without departing from the spirit and technical concept disclosed by the present invention shall still be covered by the claims of the present invention.

Claims

1. A battery equivalent circuit parameter identification method, characterized in that: The battery equivalent circuit parameter identification method comprises: Receive the identification requirements of battery equivalent circuit parameters; Determine a corresponding test scheme according to the identification requirements, the test scheme at least including: a SOC-OCV test scheme and a HPPC test scheme; Testing the battery sample according to the test scheme to obtain equivalent circuit parameters of the battery sample; Wherein, when the test scheme is a SOC-OCV test scheme, the step of testing the battery sample according to the test scheme to obtain the equivalent circuit parameters of the battery sample includes: S11, controlling the battery sample to perform the first operation according to the SOC-OCV pre-research test plan; S12, optimizing the SOC-OCV formal test plan based on the first operation result; S13, controlling the battery sample to perform a second run according to the optimized SOC-OCV formal test plan; S14, processing the second operation result to obtain a two-dimensional graph of the open circuit voltage of the battery; Wherein, when the test scheme is the HPPC test scheme, the step of testing the battery sample according to the test scheme to obtain the equivalent circuit parameters of the battery sample includes: S21, controlling the battery sample to be processed according to a fourth rule so as to satisfy a first preset condition; S22, the battery sample after the control process is processed according to the fifth rule to obtain HPPC test data; S23, obtaining equivalent circuit parameters of the battery sample according to a preset method based on the HPPC test data; The step S23 includes: The equivalent circuit parameters are obtained by identifying the HPPC test data of the first 50% of the rest time of the total rest process using the least squares online parameter identification method; and / or, The equivalent circuit parameters are obtained by identifying the HPPC test data of the last 50% of the rest time of the total rest process according to the genetically optimized neural network offline parameter identification method; and / or, The equivalent circuit parameters are obtained by identifying the HPPC test data of the first 50% time stage of the total charge or total discharge process according to the least squares online parameter identification method; and / or, The equivalent circuit parameters are obtained by identifying the HPPC test data of the last 50% time stage of the total charge or discharge process according to the genetically optimized neural network offline parameter identification method.

2. The battery equivalent circuit parameter identification method according to claim 1, characterized in that: The step of controlling the battery sample to perform the first operation according to the SOC-OCV preliminary research test plan in S11 includes: S111, controlling the battery sample to be processed according to a first rule to obtain an actual capacity of the battery sample; S112: Based on the actual capacity, control the battery sample to be processed according to a second rule to obtain the first operation result.

3. The battery equivalent circuit parameter identification method according to claim 1, characterized in that: The step of controlling the battery sample to perform a second operation according to the optimized SOC-OCV formal test scheme in S13 includes: S131, controlling the battery sample to be processed according to a first rule to obtain an actual capacity of the battery sample; S132: Based on the actual capacity, control the battery sample to be processed according to a third rule to obtain the second operation result.

4. The battery equivalent circuit parameter identification method according to claim 2 or 3, characterized in that: The step of controlling the battery sample to be processed according to the first rule to obtain the actual capacity of the battery sample includes: Based on a first preset temperature, the battery sample is controlled to repeatedly perform a charge and discharge process to a first preset number of times; determining an average value of the discharge capacities of the battery samples based on a second preset number of times as the actual capacity of the battery; Wherein, the second preset number of times is less than the first preset number of times.

5. The battery equivalent circuit parameter identification method according to claim 4, characterized in that: The step of controlling the battery sample to repeatedly perform charge and discharge processing to a first preset number of times based on a first preset temperature includes: Controlling the battery sample to be subjected to a static treatment at a first preset temperature; When the static treatment time length satisfies a first preset time length, controlling the battery sample to perform constant current discharge at a first preset current under the first preset temperature; When the voltage of the battery sample is less than the discharge cut-off voltage, controlling the battery sample to be placed at the first preset temperature; When the static treatment time meets the first preset time, controlling the battery sample to perform constant current charging at the first preset temperature and the first preset current; When the voltage of the battery sample is greater than the charging cut-off voltage, the battery sample is controlled to switch to constant voltage charging; When the charging current of the battery sample is less than the preset current, the battery sample is controlled to repeatedly execute the above steps to the first preset number of times.

6. The battery equivalent circuit parameter identification method according to claim 2, characterized in that: The step of controlling the battery sample to be processed according to a second rule based on the actual capacity in S112 includes: S1121, controlling the battery sample to perform a static treatment at a first preset temperature based on the actual capacity, and detecting the battery terminal voltage at the first preset temperature; S1122, when the static treatment time at the first preset temperature meets the second preset time, adjusting the first preset temperature to a second preset temperature, controlling the battery sample to perform static treatment at the second preset temperature, and detecting the battery terminal voltage at the second preset temperature; S1123, when the static treatment time at the second preset temperature meets the third preset time, adjusting the second preset temperature to a third preset temperature, controlling the battery sample to perform static treatment at the third preset temperature, and detecting the battery terminal voltage at the third preset temperature; S1124, when the static treatment time at the third preset temperature meets the fourth preset time, adjusting the third preset temperature to a fourth preset temperature, controlling the battery sample to perform static treatment at the fourth preset temperature, and detecting the battery terminal voltage at the fourth preset temperature; S1125, when the static treatment time at the fourth preset temperature satisfies the fourth preset time, adjusting the fourth preset temperature to a fifth preset temperature, controlling the battery sample to perform a static treatment at the fifth preset temperature, and detecting the battery terminal voltage at the fifth preset temperature; S1126, when the static treatment time at the fifth preset temperature meets the fourth preset time, controlling the battery sample to perform constant current discharge according to the first preset current; S1127: When the discharged capacity reaches the first preset capacity, control the battery sample to repeatedly execute steps S1121-S1127 to a third preset number of times.

7. The battery equivalent circuit parameter identification method according to claim 3, characterized in that: The step of controlling the battery sample to be processed according to a third rule based on the actual capacity in S132 includes: S1321, controlling the battery sample to perform a static treatment at a first preset temperature based on the actual capacity; S1322: When the static treatment time at the first preset temperature satisfies a fifth preset time, adjusting the first preset temperature to a second preset temperature, and controlling the battery sample to perform a static treatment at the second preset temperature; S1323, when the static treatment time at the second preset temperature satisfies a sixth preset time, adjusting the second preset temperature to a third preset temperature, and controlling the battery sample to perform a static treatment at the third preset temperature; S1324, when the static treatment time at the third preset temperature meets the seventh preset time, adjusting the third preset temperature to a fourth preset temperature, and controlling the battery sample to perform static treatment at the fourth preset temperature; S1325, when the static treatment time at the fourth preset temperature meets the seventh preset time, adjusting the fourth preset temperature to the first preset temperature, and controlling the battery sample to perform the static treatment at the first preset temperature; S1326: When the static treatment time at the first preset temperature meets a seventh preset time, controlling the battery sample to perform constant current discharge according to a first preset current; S1327, when the discharged capacity reaches the first preset capacity, adjusting the first preset temperature to the second preset temperature, controlling the battery sample to perform a static treatment at the second preset temperature, and detecting the battery terminal voltage at the second preset temperature; S1328, when the static treatment time at the second preset temperature satisfies an eighth preset time, adjusting the second preset temperature to a third preset temperature, controlling the battery sample to perform a static treatment at the third preset temperature, and detecting the battery terminal voltage at the third preset temperature; S1329, when the static treatment time at the third preset temperature satisfies an eighth preset time, adjusting the third preset temperature to a fourth preset temperature, controlling the battery sample to perform a static treatment at the fourth preset temperature, and detecting the battery terminal voltage at the fourth preset temperature; S1330: When the static treatment time at the fourth preset temperature satisfies the eighth preset time, adjusting the fourth preset temperature to the first preset temperature, controlling the battery sample to perform static treatment at the first preset temperature, and detecting the battery terminal voltage at the first preset temperature; S1331. When the static treatment time at the first preset temperature satisfies an eighth preset time, the battery sample is controlled to repeatedly execute steps S1326-S1330 to a fourth preset number of times.

8. The battery equivalent circuit parameter identification method according to claim 1, characterized in that: The step of controlling the processed battery sample to be processed according to the fifth rule in S22 includes: S221, controlling the processed battery sample to perform constant current discharge according to a second preset current; S222, when the amount of electricity discharged by the battery sample reaches a second preset capacity, controlling the battery sample to be placed in a static state for a ninth preset time period; S223, controlling the battery sample to perform pulse discharge according to a third preset current; S224, when the pulse discharge duration meets the tenth preset duration, controlling the battery sample to be placed in a static state for an eleventh preset duration; S225, controlling the battery sample to perform pulse charging according to a third preset current; S226, when the pulse charging duration meets the tenth preset duration, controlling the battery sample to be placed in a static state for the eleventh preset duration; The battery sample is controlled to repeatedly execute steps S221-S226, and the process stops when the power level of the battery sample is less than the second preset capacity.

9. A method for constructing a battery equivalent circuit simulation model, characterized in that: The method for constructing the battery equivalent circuit model includes: Construct a battery equivalent circuit model of a battery sample; The parameters obtained by the battery equivalent circuit parameter identification method according to any one of claims 1 to 8 are introduced into the circuit model to obtain a battery equivalent circuit simulation model of the battery sample.

10. The method for constructing a battery equivalent circuit simulation model according to claim 9, characterized in that: After the step of obtaining the battery equivalent circuit simulation model of the battery sample, the method further includes: Running the simulation model according to a second preset condition to obtain a battery terminal voltage value of the simulation model; Comparing and analyzing the battery terminal voltage value of the simulation model with the actual terminal voltage value; The accuracy of the simulation model is determined based on the results of the comparative analysis.

11. The method for constructing a battery equivalent circuit simulation model according to claim 9, characterized in that: The step of constructing a battery equivalent circuit model of the battery sample includes: The circuit equation for determining the battery equivalent circuit model of the battery sample based on Kirchhoff's law is: in, V 1 is the electrochemical polarization voltage, V 2 is the concentration polarization voltage; Simultaneous equations and equation (1), with SOC , V 1 and V 2 is the state variable, I is the input, and V is the output. The state space equation of the battery equivalent circuit model is obtained, and the state space equation is discretized to obtain the system state equation: Where T is the sampling time, τ1=R1C1, τ2=R2C2, C=battery nominal capacity × nominal voltage; The mathematical equation of the battery is obtained: The battery equivalent circuit model is generated based on the mathematical equation.

12. A battery equivalent circuit parameter identification system, characterized in that: The battery equivalent circuit parameter identification system comprises: Battery samples; An environmental chamber, used to provide a corresponding environmental temperature when testing the battery sample; A charging and discharging device, used to control the charging and discharging of the battery sample; A control device, used for controlling the environmental chamber and the charging and discharging equipment to test the battery sample to obtain battery equivalent circuit parameters of the battery sample; A model building device, used for importing the equivalent circuit parameters into the battery equivalent circuit model of the battery sample to obtain a simulation model of the battery equivalent circuit of the battery sample; Wherein, the control device comprises: An SOC-OCV testing unit, used to control the environmental chamber and the charging and discharging equipment to complete the SOC-OCV test on the battery sample, and obtain a two-dimensional graph of open circuit voltage based on the SOC-OCV test data; The HPPC test unit is used to control the environmental chamber and the charging and discharging device to complete the HPPC test on the battery sample, and obtain the equivalent circuit parameters of the battery sample based on the HPPC test data, including: The equivalent circuit parameters are obtained by identifying the HPPC test data of the first 50% of the rest time of the total rest process using the least squares online parameter identification method; and / or, The equivalent circuit parameters are obtained by identifying the HPPC test data of the last 50% of the rest time of the total rest process according to the genetically optimized neural network offline parameter identification method; and / or, The equivalent circuit parameters are obtained by identifying the HPPC test data of the first 50% time stage of the total charge or total discharge process according to the least squares online parameter identification method; and / or, The equivalent circuit parameters are obtained by identifying the HPPC test data of the last 50% time stage of the total charge or discharge process according to the genetically optimized neural network offline parameter identification method.

13. The battery equivalent circuit parameter identification system according to claim 12, characterized in that: The model building device comprises: A construction unit, used to establish a mathematical equation of a battery equivalent circuit model of the battery sample; An importing unit, used for importing the test result into the mathematical equation; A building unit is used to build the battery equivalent circuit simulation model based on the mathematical equation imported into the test result.

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