Power battery multi-domain joint digital twin modeling method and device

Abstract

The invention provides a power battery multi-domain joint digital twinning modeling method and device, and belongs to the technical field of power batteries, and the method comprises the steps: employing a second-order equivalent circuit model to carry out the modeling of a battery electric domain twinning system; modeling a battery thermal domain twin system by adopting a lumped parameter model; based on two intermediate variables of battery temperature and heat production, a battery electric domain twinning system and a battery heat domain twinning system are coupled, and a multi-domain combined battery twinning system based on an electric domain and a heat domain is constructed; and verifying the battery parameter estimation of the multi-domain combined battery twinning system by using open source battery data. Therefore, the battery electric domain twinning system and the battery thermal domain twinning system are combined, a multi-domain combined battery twinning system using the battery temperature and the battery SOC as time-varying parameters is established, and the temperature and terminal voltage of the battery can be accurately simulated.

Description

Technical Field

[0001] The present application relates to the technical field of power batteries, and specifically, to a method and device for multi-domain joint digital twin modeling of power batteries. Background Art

[0002] With the rapid popularization of electric vehicles, consumers and automobile manufacturers are paying more and more attention to battery safety issues. Power batteries are not only the main power source and core components of electric vehicles, but also the main technical barrier to their rapid development. Lithium batteries are widely used in many fields such as mobile phones, electric vehicles, and mobile power supplies due to their high energy density, high cycle life, and high environmental protection. However, safety accidents such as lithium battery fires caused by thermal runaway and battery management systems have become a huge challenge facing the development of new energy vehicles. In addition, as the energy density of positive electrode materials approaches its limit, it is difficult to significantly increase the capacity of lithium-ion batteries and meet the needs of the development of new energy vehicles.

[0003] Digital twin is a technology that uses data such as physical models, sensor updates, and operation history to complete mapping in virtual space through a multi-disciplinary, multi-physical, multi-scale, and multi-probability simulation process. It reflects the entire life cycle of the corresponding physical equipment and can be regarded as a digital mapping system of one or more important, interdependent equipment systems. The twin system is to completely replicate the operating status of the battery pack throughout its life cycle in the physical space, analyze the working characteristics of the battery, and complete its modeling work, which is a basic and important part of building a twin system.

[0004] Usually, when mathematical modeling of lithium-ion batteries is performed, the electrical characteristics are always considered. However, in addition to the complex reactions of the battery itself that affect the battery performance, changes in the external environment temperature and the self-heating of the battery will also affect the battery life to a certain extent. Therefore, the existing mathematical modeling of lithium-ion batteries is not accurate enough and cannot accurately estimate the battery SOC and temperature. Summary of the invention

[0005] In view of this, the purpose of this application is to provide a multi-domain joint digital twin modeling method and device for a power battery, which can improve the accuracy of the twin system and accurately simulate the temperature and terminal voltage of the battery.

[0006] In a first aspect, the present application provides a method for modeling a multi-domain joint digital twin of a power battery, the method comprising the following steps:

[0007] The battery electric domain twin system is modeled using a second-order equivalent circuit model;

[0008] The battery thermal domain twin system is modeled using a lumped parameter model;

[0009] Based on the two intermediate variables of battery temperature and heat generation, the battery electric domain twin system and the battery thermal domain twin system are coupled to build a multi-domain joint battery twin system based on the electric domain and the thermal domain.

[0010] The battery parameter estimation of the multi-domain joint battery twin system is verified using open source battery data.

[0011] In a possible implementation, the use of a second-order equivalent circuit model to model the battery electric domain twin system includes the following steps:

[0012] According to Kirchhoff's law, the battery terminal voltage is calculated as follows:

[0013] U k =U oc -R0I k -U1-U2; among them, U oc represents the open circuit voltage of the battery, R0 represents the ohmic internal resistance, I k represents the battery current, U1 and U2 represent the first terminal voltage of the first-order RC circuit and the second terminal voltage of the second-order RC circuit in the second-order equivalent circuit model, respectively;

[0014] Calculate the battery SOC using the following formula:

[0015]

[0016] are the battery SOC at time t and t0 respectively; η is the charge and discharge efficiency; Q is the maximum available capacity of the battery;

[0017] Under different working conditions and different ambient temperatures, the battery performance is tested and the battery parameters are recorded; wherein, the battery open circuit voltage and battery SOC obtained under the first temperature T1 condition during the battery pulse discharge are fitted, and the parameters a, b, c, and d to be fitted in the fitting formula are obtained, wherein the fitting formula is U oc =a+bSOC+cSOC 2 +dSOC 3 ;

[0018] Obtain the fitting curve of the battery open circuit voltage and battery SOC during battery pulse discharge under the conditions of the second temperature T2, the third temperature T3, and the fourth temperature T4, and perform spatial plane fitting to obtain the battery open circuit voltage U oc , the relationship between battery SOC and ambient temperature T.

[0019] In a possible implementation, the use of a lumped parameter model to model the battery thermal domain twin system includes the following steps:

[0020] Calculate the heat generated by the battery using the following formula:

[0021] Q=I k [(U oc -U k )-T(dU oc / dT)]; where I k Represents the battery current, U oc Indicates the battery open circuit voltage, U k represents the battery terminal voltage, T represents the battery temperature, dU oc / dT represents the temperature entropy coefficient;

[0022] By fitting the formula U oc =x+yT+zT 2 The relationship between the battery open circuit voltage and the battery temperature is obtained; wherein x, y, and z are parameters to be fitted;

[0023] By fitting the formula dU oc / dT=m+nSOC+oSOC 2 +pSOC 3 +qSOC 4 +rSOC 5 The relationship between the temperature entropy coefficient and the battery SOC is obtained; where m, n, o, p, q, and r are parameters to be fitted.

[0024] In a possible implementation manner, the temperature entropy coefficient is obtained by a direct measurement method.

[0025] In a possible implementation, the multi-domain joint battery twin system takes the battery current, battery temperature and battery SOC as inputs, and first calculates the battery terminal voltage and the battery open circuit voltage through the battery electric domain twin system; then the temperature entropy coefficient and the obtained battery terminal voltage and the battery open circuit voltage are input into the battery thermal domain twin system to calculate the battery heat generation and the battery temperature as the input of the multi-domain joint battery twin system.

[0026] In a possible implementation, the use of open source battery data to verify the battery parameter estimation of the multi-domain joint battery twin system includes the following steps:

[0027] Obtaining the battery temperature output by the multi-domain joint battery twin system simulation and the actually measured battery surface temperature, and comparing the errors between the two;

[0028] If the error is not less than a set threshold, the battery temperature output by the multi-domain joint battery twin system simulation is corrected based on the actually measured battery surface temperature and the Kalman filter algorithm;

[0029] If the error is less than a set threshold, the battery temperature simulated and output by the multi-domain joint battery twin system is combined with the actually measured battery surface temperature, and the average battery temperature is calculated by the Kalman filter algorithm.

[0030] In a possible implementation, if the error is not less than a set threshold, the battery temperature simulated and output by the multi-domain joint battery twin system is corrected based on the actually measured battery surface temperature and the Mann filter algorithm, including the following steps:

[0031] The actually measured battery surface temperature is used as the battery temperature output by the multi-domain joint battery twin system simulation, and it is re-determined whether the difference between the two is less than the set threshold.

[0032] In the second aspect, the present application provides a multi-domain joint digital twin modeling device for a power battery, which is applied to a hybrid vehicle. The hybrid vehicle includes a vehicle energy distribution system, a battery management system and a cloud platform. The battery management system includes a lithium deposition detection mode setting module, a power system power control module, a lithium deposition characteristic parameter calculation module, a lithium deposition parameter cloud platform interaction module and a lithium deposition response module; the identification device includes:

[0033] A setting module, used to set the lithium deposition identification working condition of the vehicle lithium battery based on the lithium deposition detection mode setting module, and start the lithium deposition detection mode when the battery management system recognizes that the vehicle lithium battery meets the lithium deposition identification working condition; wherein the lithium deposition identification working condition includes the temperature range of the vehicle lithium battery after it is fully charged;

[0034] A control module, configured to generate a constant low-rate discharge request based on the power system power control module, and send the request to the vehicle energy distribution system, so that the vehicle energy distribution system maintains the discharge of the vehicle lithium battery within the temperature range through energy distribution according to the constant low-rate discharge request;

[0035] A calculation module is used to calculate the lithium deposition characteristic parameters of the vehicle lithium battery during constant low-rate discharge in real time based on the lithium deposition characteristic parameter calculation module, and upload them to the cloud platform through the lithium deposition parameter cloud platform interaction module. The cloud platform calculates the lithium deposition capacity of the vehicle lithium battery based on the received lithium deposition characteristic parameters and in combination with historical data, and sends them to the battery management system.

[0036] In a third aspect, the present application provides an electronic device, comprising: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the steps of the multi-domain joint digital twin modeling method of power batteries as described in the first aspect are performed.

[0037] In a fourth aspect, the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the power battery multi-domain joint digital twin modeling method as described in the first aspect are executed.

[0038] The present embodiment provides a method and device for modeling a multi-domain joint digital twin of a power battery. The second-order equivalent circuit model is used to model the battery electric domain twin system; the lumped parameter model is used to model the battery thermal domain twin system; based on the two intermediate variables of battery temperature and heat generation, the battery electric domain twin system and the battery thermal domain twin system are coupled to construct a multi-domain joint battery twin system based on the electric domain and the thermal domain; and the battery parameter estimation of the multi-domain joint battery twin system is verified using open source battery data. Thus, the battery electric domain twin system and the battery thermal domain twin system are combined to establish a multi-domain joint battery twin system that uses battery temperature and battery SOC as time-varying parameters, which can accurately simulate the temperature and terminal voltage of the battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 It is a flow chart of the multi-domain joint digital twin modeling method for power batteries described in one embodiment of the present application;

[0041] Figure 2 This is a schematic diagram of the structure of the battery power domain twin system described in one embodiment of the present application;

[0042] Figure 3 It is a schematic diagram of spatial plane fitting between the battery open circuit voltage Uoc, the battery SOC and the ambient temperature T described in one embodiment of the present application;

[0043] Figure 4 This is a schematic diagram of the structure of the battery thermal domain twin system described in one embodiment of the present application;

[0044] Figure 5 A schematic diagram of fitting between the temperature entropy coefficient and the battery SOC in an embodiment of the present application;

[0045] Figure 6 This is a schematic diagram of the structure of the multi-domain joint battery twin system described in one embodiment of the present application;

[0046] Figure 7 A flowchart for verifying the battery parameter estimation of the multi-domain joint battery twin system using open source battery data in one embodiment of the present application;

[0047] Figure 8 This is a structural block diagram of a multi-domain joint digital twin modeling device for a power battery described in one embodiment of the present application;

[0048] Fig. 9 It is a structural block diagram of an electronic device described in an embodiment of the present application. DETAILED DESCRIPTION

[0049] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the drawings in the present application only serve the purpose of explanation and description and are not used to limit the scope of protection of the present application. In addition, it should be understood that the schematic drawings are not drawn in real proportion. The flowchart used in this application shows the operations implemented according to some embodiments of the present application. It should be understood that the operations of the flowchart can be implemented out of sequence, and the steps without logical context can be reversed in order or implemented simultaneously. In addition, those skilled in the art can add one or more other operations to the flowchart under the guidance of the content of the present application, or remove one or more operations from the flowchart.

[0050] In addition, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application usually described and marked in the drawings here can be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0051] It should be noted that the term "comprising" will be used in the embodiments of the present application to indicate the existence of the features declared thereafter, but does not exclude the addition of other features.

[0052] Based on the technical problems raised by the background technology, the present application provides a multi-domain joint digital twin modeling method and device for a power battery, which can improve the accuracy of the twin system and accurately simulate the temperature and terminal voltage of the battery.

[0053] See the instruction manual Figure 1 In one embodiment, the present application provides a power battery multi-domain joint digital twin modeling method, comprising the following steps:

[0054] S1. Use the second-order equivalent circuit model to model the battery electric domain twin system;

[0055] S2. Modeling the battery thermal domain twin system using a lumped parameter model;

[0056] S3. Based on the two intermediate variables of battery temperature and heat generation, the battery electric domain twin system and the battery thermal domain twin system are coupled to build a multi-domain joint battery twin system based on the electric domain and the thermal domain;

[0057] S4. Use open source battery data to verify the battery parameter estimation of the multi-domain joint battery twin system.

[0058] Specifically, in step S1, after analyzing the working mechanism of the battery power domain, a second-order equivalent circuit model is selected as the twin model of the power domain, as shown in the attached manual. Figure 2 As shown in the figure, the HPPC (Hybrid Pulse Power Characterization) test condition is used to identify the parameters of the electric domain twin model, record the battery open circuit voltage Uoc, ohmic internal resistance R0 and polarization parameters at different temperatures and different SOC (State of Charge), and verify the accuracy of the battery electric domain twin system. The specific process is as follows:

[0059] According to Kirchhoff's law, the battery terminal voltage is calculated as follows:

[0060] U k =U oc -R0I k -U1-U2;

[0061] Among them, U oc represents the open circuit voltage of the battery, R0 represents the ohmic internal resistance, Ik represents the battery current, U1 and U2 represent the first terminal voltage of the first-order RC circuit and the second terminal voltage of the second-order RC circuit in the second-order equivalent circuit model respectively;

[0062] The battery state of charge (SOC) is an important parameter for determining the battery state. The current SOC of the battery is equal to the SOC of the battery at a certain moment plus the integral of the current during this period of time. The calculation formula for the battery SOC is:

[0063]

[0064] Among them, SOC(t) and SOC(t0) are the battery SOC at time t and t0 respectively; η is the charge and discharge efficiency; Q is the maximum available capacity of the battery;

[0065] In order to obtain the corresponding relationship between battery polarization parameters, ohmic internal resistance and battery open circuit voltage at different temperatures and different SOC, it is necessary to complete various performance tests of lithium-ion batteries under different working conditions and different ambient temperatures, screen and store battery parameters, and facilitate the subsequent verification of the accuracy of the lithium-ion battery model. According to the experimental steps, data is collected and calculated to obtain the data of battery open circuit voltage and battery SOC during battery pulse discharge under the first temperature T1 condition. There is a proportional relationship between the battery open circuit voltage Uoc and the battery SOC, which changes in a positive correlation. In order to obtain the specific mathematical relationship between the two, fitting is performed in matlab-Simulink, and the fitting formula is U oc =a+bSOC+cSOC 2 +dSOC 3 ; The corresponding parameters a, b, c, and d to be fitted can be obtained.

[0066] In one embodiment, data is collected and calculated according to the experimental steps to obtain experimental data of the battery open circuit voltage and the battery SOC during pulse discharge of the battery at 25° C. The results are shown in Table 1.

[0067] SOC 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 <![CDATA[U oc / v]]> 3.4 3.5 3.63 3.7 3.8 3.9 4.0 4.08

[0068] Table 1

[0069] It can be seen from Table 1 that there is a proportional relationship between the battery open circuit voltage Uoc and the battery SOC, which changes in a positive correlation. In order to obtain the specific mathematical relationship between the two, fitting is performed in Simulink. The curve fitting results at 25°C are a=3.213, b=0.9759, c=0.1027, d=-0.1164; the residual sum of squares of the curve RSSE=0.0007995, which proves that the curve has a good fitting degree.

[0070] Similarly, fitting curves under other temperatures, such as the second temperature T2, the third temperature T3, and the fourth temperature T4, can be obtained, and then the above data can be fitted in a spatial plane again to obtain the relationship between the battery open circuit voltage Uoc, the battery SOC, and the ambient temperature T.

[0071] In one embodiment, the battery open circuit voltage Uoc and the battery SOC at the other three temperatures (0°C, 10°C, 40°C) are fitted, and the results of the fitting parameters are shown in Table 2. The above data are fitted in a spatial plane to obtain the relationship between the battery open circuit voltage Uoc, the battery SOC and the ambient temperature T as shown in the attached manual. Figure 3 shown.

[0072] Fitting parameters 0℃ 10℃ 25℃ 40℃ a 2.94 3.17 3.21 3.10 b 2.25 1.27 0.98 1.50 c -1.84 -0.32 1.10 -0.71 d 0.83 0.06 -0.12 0.30

[0073] Table 2

[0074] In step S2, the present application considers that the temperature change caused by the internal reaction and heat exchange of the battery will also affect the battery characteristics, and then analyzes the heat generation and heat dissipation mechanism of the battery, calibrates the battery temperature entropy coefficient, and establishes a thermal domain twin model, as shown in the attached manual. Figure 4 The specific process is as follows:

[0075] The heat generated by the battery, Q, can be calculated using the Bernardi equation:

[0076] Q=I k [(U oc -U k )-T(dU oc / dT)]; where I k Represents the battery current, U oc Indicates the battery open circuit voltage, U k represents the battery terminal voltage, T represents the battery temperature, dU oc / dT represents the temperature entropy coefficient; the temperature entropy coefficient dU oc / dT is used to calculate the entropy change heat generated by the disordered movement inside the battery, that is, the reversible heat of the battery. When dUoc / dT is less than 0, the rate of heat generation of the battery will be accelerated. When dUoc / dT is greater than 0, the rate of heat generation of the battery will be reduced. It is one of the factors that affect the temperature change of the battery and can be obtained through direct measurement.

[0077] First, by fitting the formula U oc =x+yT+zT 2 The relationship between the battery open circuit voltage and the battery temperature is obtained; wherein x, y, z are the parameters to be fitted; through the fitting formula dU oc / dT=m+nSOC+oSOC 2 +pSOC 3 +qSOC 4 +rSOC 5 The relationship between the temperature entropy coefficient and the battery SOC is obtained; where m, n, o, p, q, and r are parameters to be fitted.

[0078] In one embodiment, the temperature entropy coefficient dUoc / dT is obtained by direct measurement. The specific experimental steps are: first, adjust the temperature of the high and low temperature test box to 25°C, put in the battery, and let it stand for 2 hours. After the battery is stable, use the constant current and constant voltage method to fully charge the battery, and then let it stand for 3 hours; secondly, adjust the temperature of the high and low temperature test box to 0°C, 10°C, 25°C and 40°C in turn to ensure that the battery can stand for 3 hours at each temperature. During this period, 10% of the available capacity of the battery is discharged each time in the form of constant current discharge; finally, the temperature of the test box is repeatedly adjusted to discharge the battery, and the test is stopped when the battery voltage is the cut-off voltage. During the entire test period, the temperature will change each time the test box is adjusted; each time the constant current discharge occurs, the battery SOC will change, and the battery open circuit voltage value when the battery temperature and battery SOC change is recorded, and the temperature entropy coefficient can be obtained by fitting. The specific values ​​are shown in Table 3, and the fitting curve is shown in the attachment of the instruction manual Figure 5 , the curve fitting correlation coefficient is 0.9917, indicating that the curve fitting result is very close to the actual measurement result; Figure 5 It can be seen that the temperature entropy coefficient of lithium-ion batteries in the entire temperature range shows a parabolic trend of first increasing and then decreasing. Temperature entropy heat will promote battery heating, causing the battery to heat up rapidly. When the SOC is between 0.4 and 1, the temperature entropy coefficient is greater than 0, and the reaction heat is endothermic; when the SOC is between 0 and 0.3, the temperature entropy coefficient is less than 0, and the reaction heat is exothermic.

[0079] Fitting parameters m n o p q r value -0.2373 1.221 -5.938 21.1 -29.2 13.07

[0080] Table 3

[0081] In step S1 and step S2, the present application summarizes the analysis process of the internal electrical and thermal domains of the power battery and the analysis and testing methods, which can be applied to the analysis of other types of lithium-ion batteries (including solid-state batteries) and is extensible.

[0082] In step S3, the battery electric domain twin system and the battery thermal domain twin system are coupled through two intermediate variables, battery temperature and heat generation, to build a multi-domain joint battery twin system based on the electric domain and thermal domain, which can more accurately simulate the terminal voltage Uk and temperature T of the lithium-ion battery in actual working conditions. The specific process is as follows: select the battery SOC and battery temperature T as the input variables of the model to update the internal parameters in real time and calculate a more accurate battery terminal voltage Uk. k , battery open circuit voltage Uoc and battery heat generation Q, and U k As the intermediate variables of the coupling model, Uoc and Q can act as a bridge between the electrical model and the thermal model, coupling the electrical model and the thermal model, as shown in the attached manual. Figure 6As shown, it can simultaneously reflect the voltage dynamic characteristics and temperature rise characteristics of the battery, and fully grasp the working mechanism of the lithium-ion battery.

[0083] Attached to the instruction manual Figure 6 It can be seen that the multi-domain joint battery twin system takes the battery current Ik, battery temperature T and battery SOC as input, and first calculates the battery terminal voltage U through the electrical model k And the battery open circuit voltage Uoc, the two results and the temperature entropy coefficient dUoc / dT are used as the input of the battery heat generation model to calculate the battery's heat generation Q, and then the battery temperature T at this time is calculated, and then the temperature T is fed back to the electrical model for calibration. In this way, the battery's electrical model and thermal model are coupled together, making the battery twin model more accurate and replicating the working characteristics of lithium-ion batteries in physical space from multiple angles.

[0084] In step S4, the voltage and temperature simulations of the electrothermal coupling twin model are performed under different discharge rates and variable current discharge conditions, and compared with the experimental collected data to evaluate the accuracy of parameters such as voltage and temperature output by the electrothermal coupling twin model.

[0085] Specifically, when using the KF algorithm (Kalman Filter) to correct the battery model output temperature, the temperature T output by the twin model simulation is compared with the actual measured battery surface temperature T ck The error between the two, when the error is large, it means that the temperature T obtained by model simulation is not accurate enough and there is a deviation, and it is necessary to use the measured battery surface temperature T ck And KF algorithm is used to correct the output temperature of the twin model: when the error is small, it means that the simulation temperature and the measured temperature are close. KF will be more willing to believe the accuracy of the output temperature of the twin model and regard it as the estimated result of the battery temperature.

[0086] The process of using KF to correct the battery model temperature is as follows: Figure 7 When the initial temperature difference is 0, the temperature T output by the twin model simulation and the actual measured battery surface temperature T are set. ck The temperature difference threshold is 2K. When the temperature T output by the twin model simulation is different from the actual measured battery surface temperature T ck When the temperature difference is less than 2K, it proves that the simulation temperature T has no deviation. At this time, T can better reflect the temperature of the entire battery. ck The KF algorithm is used to calculate the average battery temperature T^ as the final battery temperature. ck When the temperature difference between the two is greater than 2K, it proves that the model simulation temperature T has deviated. At this time, the measured surface temperature Tck The input is used as the model output temperature, and then the temperature difference between the two is judged again, and the battery temperature is corrected with the help of KF.

[0087] The present application provides a multi-domain joint digital twin modeling method for a power battery. First, after analyzing the working mechanism of the battery electric domain, a second-order equivalent circuit model is selected as the twin model of the electric domain. The parameters of the electric domain twin model are identified using the HPPC (hybrid power pulse characteristic) test condition, and the results of the open circuit voltage Uoc, ohmic internal resistance R0 and polarization parameters at different temperatures and different SOCs are recorded, and the accuracy of the electric domain twin model is verified. Secondly, considering that the temperature changes caused by the internal reaction and heat exchange of the battery will also affect the battery characteristics, the heat generation and heat dissipation mechanism of the battery is analyzed, the battery temperature entropy coefficient is calibrated, and a thermal domain twin model is established. Then, the electric domain twin model and the thermal domain twin model are coupled through two intermediate variables, temperature and heat generation, to build a multi-domain joint battery digital twin system, which can more accurately simulate the terminal voltage U of the lithium-ion battery in actual working conditions. k and temperature T. Finally, the voltage and temperature simulations of the electrothermal coupling twin model were performed under different discharge rates and variable current discharge conditions, and compared with the experimental data, the accuracy of the parameters such as voltage and temperature output by the electrothermal coupling twin model was evaluated. This improves the accuracy of the twin system and accurately simulates the temperature and terminal voltage of the battery.

[0088] As the instruction manual Figure 8 As shown, the present application also provides a power battery multi-domain joint digital twin modeling device, the device comprising:

[0089] The first modeling module 801 is used to model the battery electric domain twin system using a second-order equivalent circuit model;

[0090] The second modeling module 802 is used to model the battery thermal domain twin system using a lumped parameter model;

[0091] The third modeling module 803 is used to couple the battery electric domain twin system and the battery thermal domain twin system based on two intermediate variables, namely, battery temperature and heat generation, to construct a multi-domain joint battery twin system based on the electric domain and the thermal domain;

[0092] The verification module 804 is used to verify the battery parameter estimation of the multi-domain joint battery twin system using open source battery data.

[0093] In some embodiments, the first modeling module 801 uses a second-order equivalent circuit model to model the battery power domain twin system, including: calculating the battery terminal voltage according to Kirchhoff's law, the formula is as follows: U k =U oc -R0I k-U1-U2; among them, U oc represents the open circuit voltage of the battery, R0 represents the ohmic internal resistance, I k Represents the battery current, U1 and U2 represent the first terminal voltage of the first-order RC circuit and the second terminal voltage of the second-order RC circuit in the second-order equivalent circuit model respectively; calculate the battery SOC, the formula is as follows: Wherein, SOC(t) and SOC(t0) are the battery SOC at time t and time t0 respectively; η is the charge and discharge efficiency; Q is the maximum available capacity of the battery; the battery performance is tested under different working conditions and different ambient temperatures, and the battery parameters are recorded; wherein, the battery open circuit voltage and battery SOC obtained during the battery pulse discharge under the first temperature T1 condition are fitted, and the parameters a, b, c, and d to be fitted in the fitting formula are obtained, wherein the fitting formula is U oc =a+bSOC+cSOC 2 +dSOC 3 ; Obtain the fitting curve of the battery open circuit voltage and battery SOC during the battery pulse discharge under the conditions of the second temperature T2, the third temperature T3, and the fourth temperature T4, and perform spatial plane fitting to obtain the battery open circuit voltage U oc , the relationship between battery SOC and ambient temperature T.

[0094] In some embodiments, the second modeling module 802 uses a lumped parameter model to model the battery thermal domain twin system, including: calculating the heat generated by the battery, the formula is as follows: Q = I k [(U oc -U k )-T(dU oc / dT)]; where I k Represents the battery current, U oc Indicates the battery open circuit voltage, U k represents the battery terminal voltage, T represents the battery temperature, dU oc / dT represents the temperature entropy coefficient; through the fitting formula U oc =x+yT+zT 2 The relationship between the battery open circuit voltage and the battery temperature is obtained; wherein x, y, z are the parameters to be fitted; through the fitting formula dU oc / dT=m+nSOC+oSOC 2 +pSOC 3 +qSOC 4 +rSOC 5 The relationship between the temperature entropy coefficient and the battery SOC is obtained; wherein m, n, o, p, q, and r are parameters to be fitted; and the temperature entropy coefficient is obtained by a direct measurement method.

[0095] In some embodiments, the multi-domain joint battery twin system constructed by the third modeling module 803 takes battery current, battery temperature and battery SOC as inputs, and first calculates the battery terminal voltage and battery open circuit voltage through the battery electric domain twin system; then the temperature entropy coefficient and the obtained battery terminal voltage and battery open circuit voltage are input into the battery thermal domain twin system to calculate the battery heat generation and the battery temperature as the input of the multi-domain joint battery twin system.

[0096] In some embodiments, the verification module 804 uses open source battery data to verify the battery parameter estimation of the multi-domain joint battery twin system, including: obtaining the battery temperature simulated and output by the multi-domain joint battery twin system, and the actually measured battery surface temperature, and comparing the errors between the two. If the error is not less than a set threshold, the battery temperature simulated and output by the multi-domain joint battery twin system is corrected based on the actually measured battery surface temperature and the Kalman filter algorithm, and the actually measured battery surface temperature is used as the battery temperature simulated and output by the multi-domain joint battery twin system, and it is re-determined whether the difference between the two is less than the set threshold; if the error is less than the set threshold, the battery temperature simulated and output by the multi-domain joint battery twin system is combined with the actually measured battery surface temperature, and the battery average temperature is calculated by the Kalman filter algorithm.

[0097] The present application provides a multi-domain joint digital twin modeling device for power batteries. The first modeling module uses a second-order equivalent circuit model to model the battery electric domain twin system; the second modeling module uses a lumped parameter model to model the battery thermal domain twin system; the third modeling module couples the battery electric domain twin system and the battery thermal domain twin system based on the two intermediate variables of battery temperature and heat generation to construct a multi-domain joint battery twin system based on the electric domain and thermal domain; the verification module uses open source battery data to verify the battery parameter estimation of the multi-domain joint battery twin system. Thus, the battery electric domain twin system and the battery thermal domain twin system are combined to establish a multi-domain joint battery twin system that uses battery temperature and battery SOC as time-varying parameters, which can accurately simulate the temperature and terminal voltage of the battery.

[0098] Based on the same concept of the present invention, the specification is attached Fig. 9As shown, the structure of an electronic device 900 provided in an embodiment of the present application includes: at least one processor 901, at least one network interface 904 or other user interface 903, a memory 905, and at least one communication bus 902. The communication bus 902 is used to realize the connection and communication between these components. The electronic device 900 optionally includes a user interface 903, including a display (for example, a touch screen, LCD, CRT, holographic imaging (Holographic) or projection (Projector), etc.), a keyboard or a pointing device (for example, a mouse, a trackball (trackball), a touch pad or a touch screen, etc.).

[0099] The memory 905 may include a read-only memory and a random access memory, and provides instructions and data to the processor 901. A portion of the memory 905 may also include a non-volatile random access memory (NVRAM).

[0100] In some implementations, the memory 905 stores the following elements, executable modules or data structures, or a subset thereof, or an extended set thereof:

[0101] Operating system 9051, including various system programs for implementing various basic services and processing hardware-based tasks;

[0102] The application module 9052 includes various application programs, such as a launcher, a media player, a browser, etc., which are used to implement various application services.

[0103] In an embodiment of the present application, by calling the program or instructions stored in the memory 905, the processor 901 is used to execute steps in a multi-domain joint digital twin modeling method for a power battery, which can improve the accuracy of the twin system and accurately simulate the temperature and terminal voltage of the battery.

[0104] The present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps in the multi-domain joint digital twin modeling method for power batteries are executed.

[0105] Specifically, the storage medium can be a general storage medium, such as a mobile disk, a hard disk, etc. When the computer program on the storage medium is run, the above-mentioned power battery multi-domain joint digital twin modeling method can be executed.

[0106] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0107] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0108] In addition, each functional unit in the embodiments provided in the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0109] If the function is implemented in the form of a business function unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0110] Finally, it should be noted that the above embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the aforementioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the aforementioned embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application. They should all be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A multi-domain joint digital twin modeling method for power batteries, characterized in that: The method comprises the following steps: The battery electric domain twin system is modeled using a second-order equivalent circuit model; The battery thermal domain twin system is modeled using a lumped parameter model; Based on the two intermediate variables of battery temperature and heat generation, the battery electric domain twin system and the battery thermal domain twin system are coupled to build a multi-domain joint battery twin system based on the electric domain and the thermal domain. The battery parameter estimation of the multi-domain joint battery twin system is verified using open source battery data.

2. According to claim 1, a power battery multi-domain joint digital twin modeling method is characterized in that: The method of modeling the battery electric domain twin system using a second-order equivalent circuit model includes the following steps: According to Kirchhoff's law, the battery terminal voltage is calculated as follows: U k =U oc -R0I k -U1-U2; among them, U oc represents the open circuit voltage of the battery, R0 represents the ohmic internal resistance, I k represents the battery current, U1 and U2 represent the first terminal voltage of the first-order RC circuit and the second terminal voltage of the second-order RC circuit in the second-order equivalent circuit model, respectively; Calculate the battery SOC using the following formula: SOC(t)=SOC(t0)+∫ t0t t[ηI k (τ) / Q]dτ; where SOC(t) and SOC(t0) are the battery SOC at time t and t0 respectively; η is the charge and discharge efficiency; Q is the maximum available capacity of the battery; Under different working conditions and different ambient temperatures, the battery performance is tested and the battery parameters are recorded; wherein, the battery open circuit voltage and battery SOC obtained under the first temperature T1 condition during the battery pulse discharge are fitted, and the parameters a, b, c, and d to be fitted in the fitting formula are obtained, wherein the fitting formula is U oc =a+bSOC+cSOC 2 +dSOC 3 ; Obtain the fitting curve of the battery open circuit voltage and battery SOC during battery pulse discharge under the conditions of the second temperature T2, the third temperature T3, and the fourth temperature T4, and perform spatial plane fitting to obtain the battery open circuit voltage U oc , the relationship between battery SOC and ambient temperature T.

3. According to claim 2, a power battery multi-domain joint digital twin modeling method is characterized in that: The method of modeling the battery thermal domain twin system using a lumped parameter model includes the following steps: Calculate the heat generated by the battery, the formula is as follows: Q=I k [(U oc -U k )-T(dU oc / dT)]; where I k Indicates the battery current, U oc Indicates the battery open circuit voltage, U k represents the battery terminal voltage, T represents the battery temperature, dU oc / dT represents the temperature entropy coefficient; By fitting the formula U oc =x+yT+zT 2 The relationship between the battery open circuit voltage and the battery temperature is obtained; wherein x, y, and z are parameters to be fitted; By fitting the formula dU oc / dT=m+nSOC+oSOC 2 +pSOC 3 +qSOC 4 +rSOC 5 The relationship between the temperature entropy coefficient and the battery SOC is obtained; where m, n, o, p, q, and r are parameters to be fitted.

4. According to claim 3, a power battery multi-domain joint digital twin modeling method is characterized in that: The temperature entropy coefficient is obtained by a direct measurement method.

5. According to claim 4, a power battery multi-domain joint digital twin modeling method is characterized in that: in, The multi-domain joint battery twin system takes battery current, battery temperature and battery SOC as inputs, and first calculates the battery terminal voltage and battery open circuit voltage through the battery electric domain twin system; then the temperature entropy coefficient and the obtained battery terminal voltage and battery open circuit voltage are input into the battery thermal domain twin system to calculate the battery heat generation and the battery temperature as the input of the multi-domain joint battery twin system.

6. According to claim 5, a power battery multi-domain joint digital twin modeling method is characterized in that: The method of verifying the battery parameter estimation of the multi-domain joint battery twin system by using open source battery data includes the following steps: Obtaining the battery temperature output by the multi-domain joint battery twin system simulation and the actually measured battery surface temperature, and comparing the errors between the two; If the error is not less than a set threshold, the battery temperature output by the multi-domain joint battery twin system simulation is corrected based on the actually measured battery surface temperature and the Kalman filter algorithm; If the error is less than a set threshold, the battery temperature simulated and output by the multi-domain joint battery twin system is combined with the actually measured battery surface temperature, and the average battery temperature is calculated by the Kalman filter algorithm.

7. A power battery multi-domain joint digital twin modeling method according to claim 6, characterized in that: If the error is not less than the set threshold, the battery temperature output by the multi-domain joint battery twin system simulation is corrected based on the actually measured battery surface temperature and the Mann filter algorithm, including the following steps: The actually measured battery surface temperature is used as the battery temperature output by the multi-domain joint battery twin system simulation, and it is re-determined whether the difference between the two is less than the set threshold.

8. A multi-domain joint digital twin modeling device for power batteries, characterized in that: The device comprises: The first modeling module is used to model the battery electric domain twin system using a second-order equivalent circuit model; The second modeling module is used to model the battery thermal domain twin system using a lumped parameter model; The third modeling module is used to couple the battery electric domain twin system and the battery thermal domain twin system based on two intermediate variables, battery temperature and heat generation, to build a multi-domain joint battery twin system based on the electric domain and the thermal domain; A verification module is used to verify the battery parameter estimation of the multi-domain joint battery twin system using open source battery data.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate through the bus. When the machine-readable instructions are executed by the processor, the steps of the multi-domain joint digital twin modeling method for power batteries as described in any one of claims 1 to 7 are performed.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed by a processor, executes the steps of the power battery multi-domain joint digital twin modeling method as described in any one of claims 1 to 7.

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