A method for constructing a power battery system power simulation model
By selecting representative cells to construct a power battery system power simulation model and combining it with thermoelectric coupling simulation, the problems of simulation deviation and high computational load caused by the inconsistency of individual cells were solved, and efficient and accurate power battery system simulation was achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HEFEI GUOXUAN HIGH TECH POWER ENERGY
- Filing Date
- 2026-02-28
- Publication Date
- 2026-06-09
AI Technical Summary
Existing power battery system simulation models cannot effectively reflect the performance inconsistencies of individual cells, resulting in large deviations between simulation results and reality. Furthermore, complex models have high computational loads and are difficult to coordinate with thermodynamic models for simulation, affecting optimization design and performance evaluation.
A power simulation model for a power battery system is constructed. By selecting representative sample cells with the lowest, highest, and average internal resistance, an equivalent circuit model of the unit is built and extended to a battery module model. Combined with a thermal management model, thermoelectric coupling simulation is performed to accurately predict pulse power capability.
It reduces modeling complexity and simulation computation, improves simulation accuracy and reliability, realizes bidirectional interactive simulation of electrical and thermal performance, and enhances the accuracy and reliability of simulation models, making it suitable for the optimization design and performance evaluation of power battery systems.
Smart Images
Figure CN122174764A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of power battery simulation technology, and more specifically, to a method for constructing a power simulation model of a power battery system. Background Technology
[0002] With the rapid development of electric vehicles, the performance of the power battery system, as its core power source, directly determines the vehicle's range, power performance, and safety. Pulse power capability is one of the key indicators for evaluating the performance of a power battery system, reflecting the battery's output or received energy limit under short-term, high-current charge and discharge conditions. Accurately predicting the pulse power capability of a power battery system is crucial for vehicle energy management, battery system safety boundary control, and lifespan assessment.
[0003] However, a power battery system is a complex nonlinear system composed of dozens to hundreds of individual cells connected in series and parallel. Due to differences in manufacturing processes, usage environments, and aging processes, there are unavoidable performance inconsistencies among individual cells, especially in key electrical characteristics such as internal resistance and capacity. This inconsistency means that the system's performance under pulsed operating conditions is not a simple average of the performance of all cells, but is limited by the worst-performing cell. Current mainstream power battery system modeling methods for power simulation have the following limitations: First, they use a simple linear scaling method to extend the individual cell model into a power battery system model, completely ignoring the performance differences of individual cells in the actual system and failing to reflect the inconsistencies in cell voltage and internal resistance, resulting in significant deviations between simulation results and reality. Second, they construct complex hybrid system models containing a large number of non-uniform individual cells. Such models have complex structures, extremely high computational loads, and are difficult to coordinate with thermodynamic models, electrical components, and other systems for simulation, severely restricting the efficiency of power battery system optimization design and performance evaluation. Summary of the Invention
[0004] To address the aforementioned shortcomings in existing technologies, the present invention aims to provide a method for constructing a power simulation model for a power battery system. This method can characterize the inconsistencies among the battery cells within the system with a minimally simplistic model structure, and accurately predict the pulse power capability of the system under different conditions through efficient thermoelectric coupling simulation.
[0005] According to one aspect of the present invention, a method for constructing a power simulation model of a power battery system is provided, comprising the following steps: S1, selecting sample cells from the individual cells of the power battery system to be studied, wherein the sample cells include a first sample cell with the lowest internal resistance, a second sample cell with the highest internal resistance, and a third sample cell with a representative average internal resistance; S2, based on the characteristic parameters of each sample cell, constructing a first unit equivalent circuit model, a second unit equivalent circuit model, and a third unit equivalent circuit model representing the cell with the lowest internal resistance, the cell with the highest internal resistance, and the cell with the average internal resistance, respectively, wherein the characteristic parameters include at least capacity and open circuit voltage (OCV). Voltage) and internal resistance; S3, according to the configuration of the power battery system under study, the first unit equivalent circuit model is extended to a first equivalent circuit model representing the first battery module of all single cells with the lowest internal resistance, the second unit equivalent circuit model is extended to a second equivalent circuit model representing the second battery module of all single cells with the highest internal resistance, the third unit equivalent circuit model is extended to a third equivalent circuit model representing the third battery module of all remaining single cells, and the first, second, and third equivalent circuit models are connected in series to form a system-level equivalent circuit model; S4 S1. Based on the basic parameters and mass of a single battery cell and the preset thermal management scheme, construct a first thermal management model, a second thermal management model, and a third thermal management model corresponding to the first battery module, the second battery module, and the third battery module, respectively. The basic parameters include density, specific heat capacity, and thermal conductivity. S5. Construct a pulse charge-discharge operating condition model based on the preset power value and duration of pulse charge-discharge. S6. Combine the system-level equivalent circuit model, the first thermal management model, the second thermal management model, the third thermal management model, and the pulse charge-discharge operating condition model through thermoelectric coupling to obtain the power battery system power simulation model.
[0006] More specifically, the selection of sample individual cells in step S1 includes: performing DC internal resistance (DCR) tests on individual cells of the same model produced in batches, and selecting individual cells with the lowest internal resistance, the highest internal resistance, and those at the statistical average internal resistance level based on the test results.
[0007] More specifically, step S2 includes: performing charge-discharge tests on each selected sample cell, calibrating the cell capacity, and collecting HPPC test data at different temperatures and SOCs based on the capacity; identifying and obtaining characteristic parameters of the corresponding cell at different temperatures and SOCs based on the HPPC test data; and constructing the first unit equivalent circuit model, the second unit equivalent circuit model, and the third unit equivalent circuit model based on the characteristic parameters.
[0008] More specifically, in step S3, the first equivalent circuit model, the second equivalent circuit model, and the third equivalent circuit model are extended in the following way: the first equivalent circuit model is composed of m first unit equivalent circuit models connected in series; the second equivalent circuit model is composed of n second unit equivalent circuit models connected in series; the third equivalent circuit model is composed of (Nmn) third unit equivalent circuit models connected in series; where N is the total number of individual cells in the power battery system under study, m and n are both positive integers, representing the number of individual cells with the lowest and highest internal resistance in the power battery system under study, respectively, and m+n< <N。
[0009] Preferably, in the above scheme, the values of m and n are both 1, and the third equivalent circuit model is composed of (N-2) third unit equivalent circuit models connected in series.
[0010] Preferably, the first equivalent circuit model, the second equivalent circuit model, and the third equivalent circuit model further include additional internal resistance of the power battery system connected in series with them.
[0011] More specifically, step S4 includes: constructing a thermal characteristic parameter model of a single battery cell based on the basic parameters of the single battery cell; calculating the total mass of the first, second, and third battery modules according to the number of single battery cells and the mass of a single battery cell represented by the first, second, and third battery modules respectively; associating the thermal characteristic parameter model of the single battery cell with the total mass of each battery module to construct a first thermal mass model, a second thermal mass model, and a third thermal mass model corresponding to the first, second, and third battery modules respectively; and determining the first battery module according to the preset thermal management scheme. The convective heat transfer coefficients of the second and third battery modules with the external environment are used to construct a first convective heat transfer model, a second convective heat transfer model, and a third convective heat transfer model corresponding to the first, second, and third battery modules, respectively. The thermal characteristic parameter model of a single battery cell is coupled with the first, second, and third thermomass models, respectively, and the first, second, and third thermomass models are coupled with the first, second, and third convective heat transfer models, respectively, to obtain the first thermal management model, the second thermal management model, and the third thermal management model, respectively.
[0012] More specifically, the preset thermal management scheme is natural cooling or liquid cooling.
[0013] More specifically, step S6 includes: coupling the system-level equivalent circuit model with the pulse charge-discharge condition model; coupling the first equivalent circuit model with the first convection heat transfer model and the first thermal mass model; coupling the second equivalent circuit model with the second convection heat transfer model and the second thermal mass model; coupling the third equivalent circuit model with the third convection heat transfer model and the third thermal mass model; thereby obtaining the power battery system power simulation model.
[0014] According to another aspect of the present invention, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein the processor implements the above-described method for constructing a power simulation model of a power battery system when executing the computer program.
[0015] The beneficial effects of this invention are as follows: This invention selects three representative sample cells with the lowest, highest, and average internal resistance to construct unit models, and expands the unit models into battery module models according to quantification parameters. This enables the battery module models to accurately characterize the electrical performance of the corresponding cell group without having to model each individual cell in the system, which greatly reduces the modeling complexity and simulation computation. At the same time, it covers the typical distribution of cell consistency differences, ensuring simulation accuracy and achieving a balance between simulation accuracy and computational efficiency.
[0016] This invention constructs a complete thermal management model, which combines thermal characteristic parameter model, thermal mass model and convective heat transfer model to accurately simulate the thermal behavior of the battery module throughout the entire process of "heat generation-heat storage-heat dissipation". At the same time, it introduces two mainstream thermal management solutions, natural cooling and liquid cooling, to improve the versatility of the model.
[0017] This invention achieves complete thermoelectric coupling between the system-level electrical model, the thermal management models of each battery module, and the operating condition model, simulating the two-way interactive relationship of "electricity generating heat and heat converting to electricity". This makes the simulation model closer to the actual working state of the power battery system and greatly improves the accuracy and reliability of power simulation.
[0018] This invention introduces additional internal resistance into the system, restoring the actual circuit structure of the power battery system, avoiding power prediction deviations caused by ignoring the additional resistance of the system, and further improving simulation accuracy.
[0019] This invention selects battery cells and obtains parameters based on standardized testing methods such as DCR testing and HPPC testing. The technical process is clear, highly repeatable, and easy for engineers to implement. It can quickly provide reliable simulation data for the research and development of power battery systems. Attached Figure Description
[0020] Figure 1This is a flowchart of the method for constructing the power simulation model of the power battery system of the present invention.
[0021] Figure 2 This is a schematic diagram of the power simulation model of the power battery system according to the present invention.
[0022] Figure 3 This is a schematic diagram of the equivalent circuit model of the battery module according to the present invention.
[0023] Figure 4 This is a comparison curve of the lowest single cell voltage in simulation and actual measurement according to an embodiment of the present invention.
[0024] Figure 5 This is a schematic diagram comparing the simulated and measured pulse power capabilities according to an embodiment of the present invention.
[0025] Figure 6 This is a schematic diagram of the structure of an electronic device that implements the method for constructing a power simulation model of a power battery system according to the present invention.
[0026] Explanation of reference numerals in the attached figures: 1. First equivalent circuit model; 2. Second equivalent circuit model; 3. Third equivalent circuit model; 4. Thermal management model; 5. Pulse charge / discharge condition model; 41. Thermal characteristic parameter model; 42. First thermal mass model; 43. Second thermal mass model; 44. Third thermal mass model; 45. First convection heat transfer model; 46. Second convection heat transfer model; 47. Third convection heat transfer model. Detailed Implementation
[0027] like Figure 1As shown, this invention provides a method for constructing a power simulation model of a power battery system, comprising the following steps: S1, selecting sample cells from the individual cells of the power battery system to be studied, including a first sample cell with the lowest internal resistance, a second sample cell with the highest internal resistance, and a third sample cell with a representative average internal resistance; S2, based on the characteristic parameters of each sample cell, constructing a first unit equivalent circuit model, a second unit equivalent circuit model, and a third unit equivalent circuit model representing the cell with the lowest internal resistance, the cell with the highest internal resistance, and the cell with the average internal resistance, respectively, wherein the characteristic parameters include at least capacity, open-circuit voltage (OCV), and internal resistance; S3, according to the configuration of the power battery system to be studied, extending the first unit equivalent circuit model to a first equivalent circuit model 1 representing all cells with the lowest internal resistance, and extending the second unit equivalent circuit model to a second equivalent circuit model representing all cells with the highest internal resistance. The second equivalent circuit model 2 of the battery module extends the third unit equivalent circuit model into a third equivalent circuit model 3 representing the third battery module of all other individual cells. The first equivalent circuit model 1, the second equivalent circuit model 2, and the third equivalent circuit model 3 are connected in series to form a system-level equivalent circuit model. S4. Based on the basic parameters and mass of the individual cells and the preset thermal management scheme, the first thermal management model, the second thermal management model, and the third thermal management model corresponding to the first battery module, the second battery module, and the third battery module, respectively, are constructed. The basic parameters include density, specific heat capacity, and thermal conductivity. S5. The pulse charge and discharge condition model 5 is constructed based on the preset power value and duration of pulse charge and discharge. S6. The system-level equivalent circuit model, the first thermal management model, the second thermal management model, the third thermal management model, and the pulse charge and discharge condition model 5 are thermoelectrically coupled and combined to obtain the power battery system power simulation model.
[0028] According to the method for constructing a power battery system power simulation model of the present invention, based on the equivalent modeling principle of "representative samples characterizing the whole", it utilizes the consistency differences in internal resistance of individual cells in the power battery system (there are three typical distributions: lowest, highest, and average). Three representative sample cells are selected to construct unit models, which are then expanded into module-level and system-level models. By constructing equivalent circuit models of three battery modules with the lowest, average, and highest internal resistances in series, and combining the thermoelectric coupling principle, the electrical performance model, thermal management model, and operating condition excitation model are coupled to achieve accurate simulation of the power battery system power, balancing simulation accuracy and computational efficiency. This construction method solves the technical pain points of existing power battery system simulation models, which either ignore individual cell consistency leading to low accuracy or perform full-scale modeling leading to high computational load. This method selects only three representative sample cells, eliminating the need to model every single cell in the system, significantly reducing modeling complexity and simulation computation, and improving simulation efficiency. It also covers three typical distributions of cell internal resistance, accurately reflecting the impact of cell consistency differences on system power output in actual production, ensuring the simulation results match real-world conditions. Furthermore, it integrates electrical, thermal, and operating condition models to achieve full-dimensional simulation of thermoelectric coupling, simultaneously predicting the electrical performance and thermal characteristics of the battery system. This closely aligns with the actual working scenarios of power battery systems, providing integrated and reliable data support for system power assessment and thermal management optimization, filling the technological gap in lightweight, high-precision simulation models.
[0029] More specifically, in step S1 of the method for constructing a power simulation model of a power battery system according to the present invention, selecting sample individual cells includes: performing DC internal resistance tests on mass-produced individual cells of the same model, and selecting individual cells with the lowest, highest, and statistically average internal resistance levels based on the test results. This selection process is based on the statistical distribution principle of internal resistance of mass-produced cells. Internal resistance data of mass-produced cells is obtained through DC internal resistance testing, and statistical analysis is used to screen samples that can characterize extreme internal resistance values (lowest, highest) and intermediate values (statistical average), ensuring the representativeness of the sample cells and the reproducibility of the selection process, providing reliable basic data support for subsequent model construction. Furthermore, the use of DC internal resistance testing is a mature and easy-to-operate method that can quickly obtain cell internal resistance data, reducing the workload of sample selection.
[0030] More specifically, step S2 of the method for constructing a power simulation model of a power battery system according to the present invention includes performing charge and discharge tests on the selected single-cell battery cores with the lowest internal resistance, average internal resistance, and highest internal resistance, calibrating the capacity of the single-cell battery cores, and collecting the process data of the HPPC (Hybrid Pulse Power Characterization) test of the single-cell battery cores at different temperatures and different SOCs based on the capacity; according to the collected HPPC test process data, identifying and obtaining the characteristic parameters of the single-cell battery cores at different temperatures and different SOCs. In one embodiment, the characteristic parameters of the single-cell battery cores can be obtained based on the battery parameter identification tool (Battery Electro-thermal Identification Tool) of Amesim software according to the collected HPPC test process data; constructing a first unit equivalent circuit model, a second unit equivalent circuit model, and a third unit equivalent circuit model based on the characteristic parameters. The HPPC test covers different temperatures and different SOCs, and can comprehensively capture the dynamic electrical characteristics of the battery cores, enabling the unit model to have the full operating condition adaptation ability; parameter identification converts the test data into model-available parameters, which can improve the simulation accuracy of the unit model.
[0031] More specifically, in step S3 of the method for constructing a power simulation model of a power battery system according to the present invention, the first equivalent circuit model 1, the second equivalent circuit model 2, and the third equivalent circuit model 3 can be extended in the following manner: The first equivalent circuit model 1 is composed of m first unit equivalent circuit models connected in series; the second equivalent circuit model 2 is composed of n second unit equivalent circuit models connected in series; the third equivalent circuit model 3 is composed of (N - m - n) third unit equivalent circuit models connected in series; where N is the total number of single-cell battery cores in the power battery system to be studied, and m and n are both positive integers, which are respectively the numbers of the single-cell battery cores with the lowest internal resistance and the highest internal resistance in the power battery system to be studied, and m + n << N. In this way, the unit models of the representative sample battery cores are replicated and extended, and the equivalent circuit models of the corresponding modules are constructed according to the actual numbers of the battery cores of different internal resistance types in the system, ensuring that the electrical performance of the module models is consistent with the electrical performance of the corresponding battery core groups in the actual system. At the same time, the dominant position of the average-value battery cores is highlighted through the quantity constraint that the sum of m and n is much smaller than N, conforming to the battery core distribution law of the actual system. In addition, through the replication and extension of the unit models, there is no need to separately model each battery core, greatly reducing the calculation amount, and the number of units of the module model is the same as the number of battery cores of the corresponding internal resistance type in the actual system, ensuring the simulation accuracy of the module electrical performance.
[0032] Preferably, both m and n are 1, so the third equivalent circuit model 3 is composed of (N-2) third unit equivalent circuit models connected in series. In this way, the most typical and concise extreme cell number is selected, i.e., the system contains only one cell with the lowest internal resistance and one cell with the highest internal resistance, with the rest being cells with average internal resistance. While ensuring that the differences in cell consistency are reflected, the expansion process of the module model is simplified to the maximum extent, reducing the difficulty of modeling and simulation, and improving the engineering feasibility of the technical solution. In fact, setting both m and n to 1 is the most common extreme cell distribution scenario in engineering practice, covering the application needs of most power battery systems. Under this condition, the model structure is the simplest, requiring no complex parameter settings, reducing the difficulty of modeling and the amount of simulation calculation, and improving the simulation speed. This approach simplifies the model while effectively reflecting the impact of cell consistency differences on system power, balancing simplicity and simulation accuracy.
[0033] like Figure 3 As shown, according to an embodiment of the present invention, the first equivalent circuit model 11, the second equivalent circuit model 22, and the third equivalent circuit model 33 further include additional internal resistance (R0) of the power battery system connected in series with them. add This additional internal resistance includes the system internal resistance of components other than individual battery cells, such as busbars and connectors. This invention incorporates these system internal resistances into the model, filling the technical gap in traditional models that only consider individual cell internal resistances and ignore additional system internal resistances. This makes the simulated system terminal voltage, power, and other parameters closer to the actual installed vehicle conditions. Furthermore, by unifying the series-connected additional system internal resistance, it achieves accurate differentiation of the internal resistance characteristics between different modules, avoiding the masking of individual cell internal resistance differences by the system's additional internal resistance, and ensuring the accuracy of consistent simulations.
[0034] Step S4 of the method for constructing a power simulation model of a power battery system according to the present invention further includes: constructing a thermal characteristic parameter model 41 of a single battery cell based on the basic parameters of a single battery cell, which is used to provide the basic physical parameters of heat transfer of the battery cell and characterize the thermophysical characteristics of the battery cell itself; calculating the total mass of the first battery module, the second battery module, and the third battery module according to the number of single battery cells and the mass of a single battery cell represented by the first battery module, the second battery module, and the third battery module respectively; associating the thermal characteristic parameter model 41 of the single battery cell with the total mass of each battery module to construct a first thermal mass model 42, a second thermal mass model 43, and a third thermal mass model 44 corresponding to the first battery module, the second battery module, and the third battery module respectively, which are used to characterize the heat storage capacity and temperature rise change law of each battery module; determining the first battery module's thermal mass according to the preset thermal management scheme. The convective heat transfer coefficients of the first, second, and third battery modules with the external environment are used to construct a first convective heat transfer model 45, a second convective heat transfer model 46, and a third convective heat transfer model 47, respectively, to characterize the heat dissipation capacity of each module with the external environment. The thermal characteristic parameter model 41 of the individual battery cell is coupled with the first thermomass model 42, the second thermomass model 43, and the third thermomass model 44 to provide basic thermophysical parameter support for the thermomass model. The first thermomass model 42, the second thermomass model 43, and the third thermomass model 44 are coupled with the first convective heat transfer model 45, the second convective heat transfer model 46, and the third convective heat transfer model 47, respectively, to realize the thermal dynamic closed loop of "heat storage-heat dissipation", thus obtaining the first thermal management model, the second thermal management model, and the third thermal management model.
[0035] In this scheme, based on the heat transfer principle of power batteries, the thermal behavior of the battery cell includes three processes: heat generation, heat storage, and heat dissipation. The thermal characteristic parameter model 41 provides the thermophysical basis of the battery cell, the thermomass model characterizes the heat storage capacity and temperature rise law, and the convection heat transfer model characterizes the heat dissipation capacity. Through the coupling of these three, a complete thermal management model is constructed, achieving accurate simulation of the thermal behavior of the battery module. In other words, the thermal characteristic parameter model 41 provides the basic physical parameters for heat transfer in the battery cell, characterizing the thermophysical properties of the battery cell itself; the first thermomass model 42, the second thermomass model 43, and the third thermomass model 44 characterize the heat storage capacity and temperature rise change law of each battery module; the first convection heat transfer model 45, the second convection heat transfer model 46, and the third convection heat transfer model 47 characterize the heat dissipation capacity of each battery module relative to the external environment. The coupling of the battery cell's thermophysical properties, the module's heat storage capacity, and the heat dissipation capacity forms a complete thermal management model, capable of simulating the entire process of "heat generation-heat storage-heat dissipation" of the battery module, closely matching actual working scenarios.
[0036] In step S5 of the method for constructing the power simulation model of the power battery system according to the present invention, the pulse charge-discharge condition model 5 is a short-term high-power charge-discharge excitation model set according to the vehicle's operating requirements. It is used to provide dynamic power excitation to the system's equivalent circuit model to achieve simulation evaluation of the power battery system's peak power capability. For example, parameters such as charging pulse power, discharging pulse power, single pulse duration, and pulse period can be set to form a periodic or single high-power pulse excitation signal. This signal is used to simulate the instantaneous charge-discharge behavior of the power battery under conditions such as rapid acceleration, rapid deceleration, and hill climbing, providing simulation input excitation to the system-level equivalent circuit model and making the simulation process closer to the actual vehicle operating state. The pulse charge-discharge condition model 5 is constructed based on pulse conditions and testing methods, which can employ methods disclosed in the prior art; therefore, the specific process will not be elaborated here.
[0037] More specifically, the preset thermal management scheme involved in the construction method of this invention is either natural cooling or liquid cooling. Natural cooling and liquid cooling are the two most mainstream thermal management schemes for power battery systems, each suitable for different application scenarios: natural cooling is suitable for low-power scenarios, while liquid cooling is suitable for high-power scenarios with high heat dissipation requirements. If the natural cooling scheme is selected, the convective heat transfer coefficient between each battery module and the external environment is determined based on parameters such as ambient temperature and wind speed. As one implementation scheme, the convective heat transfer coefficient in the convective heat transfer model between a single cell and the external environment can be set based on historical data. Since the simulation condition is the battery system test condition, and the test is conducted in a temperature chamber with a relatively stable external environment, the convective heat transfer coefficient can be set to 8 W / m² / K. If the liquid cooling scheme is selected, the convective heat transfer coefficient between each battery module and the coolant can be determined based on parameters such as coolant flow rate, coolant temperature, and cooling channel structure.
[0038] More specifically, step S6 of the method for constructing the power simulation model of the power battery system according to the present invention further includes: coupling the system-level equivalent circuit model with the pulse charge-discharge condition model 5, so that the pulse charge-discharge condition model 5 provides a preset charge-discharge excitation signal (power signal) to the system-level equivalent circuit model, simulating the charge-discharge demand in actual vehicle operation, and triggering the electrical performance simulation of the system-level equivalent circuit model. In addition, the first equivalent circuit model 1 is coupled with the first convection heat transfer model 45 and the first thermomass model 42; the second equivalent circuit model 2 is coupled with the second convection heat transfer model 46 and the second thermomass model 43; and the third equivalent circuit model 3 is coupled with the third convection heat transfer model 47 and the third thermomass model 44. During the coupling process, the heat generated by the equivalent circuit model is transferred to the thermomass model. After the thermomass model calculates the module temperature rise, it feeds back the temperature signal to the equivalent circuit model. The equivalent circuit model adjusts the internal resistance parameter according to the temperature change, while the thermomass model transfers heat to the convection heat transfer model, simulating the module heat dissipation process, realizing a two-way feedback of "electricity-heat-electricity", and finally obtaining the following result: Figure 2 The power simulation model of the power battery system shown is presented. This invention achieves bidirectional feedback simulation of electrical and thermal performance, closely aligning with the actual working mechanism of the power battery system and solving the problem of insufficient simulation accuracy of a single electrical or thermal model. Module-level thermoelectric coupling can accurately capture the thermoelectric interaction law of each module, thereby improving the accuracy of system-level power simulation. The coupling of the operating condition model makes the simulation scenario closer to the actual vehicle operating requirements, and the simulation results can more reliably guide the power evaluation, design optimization, and performance verification of the power battery system.
[0039] Figure 6 A schematic diagram of the physical structure of an electronic device for constructing a power simulation model of a power battery system according to the present invention is shown, as follows: Figure 6As shown, the electronic device may include: a processor 110, a communication interface 120, a memory 130, and a communication bus 110, wherein the processor 110, the communication interface 120, and the memory 130 communicate with each other through the communication bus 110. The processor 110 can call the computer program in the memory 130 to execute the method for constructing the power battery system power simulation model of the present invention. The method includes the following steps: S1, selecting sample cells from the individual cells of the power battery system to be studied, including a first sample cell with the lowest internal resistance, a second sample cell with the highest internal resistance, and a third sample cell with a representative average internal resistance; S2, based on the characteristic parameters of each sample cell, constructing a first unit equivalent circuit model, a second unit equivalent circuit model, and a third unit equivalent circuit model representing the cell with the lowest internal resistance, the cell with the highest internal resistance, and the cell with the average internal resistance, respectively, wherein the characteristic parameters include at least capacity, open-circuit voltage (OCV), and internal resistance; S3, according to the configuration of the power battery system to be studied, extending the first unit equivalent circuit model to a first equivalent circuit model 1 representing the first battery module of all cells with the lowest internal resistance, and extending the second unit equivalent circuit model to a first equivalent circuit model 1 representing the first battery module of all cells with the lowest internal resistance. The second equivalent circuit model 2 of the second battery module with the highest internal resistance single cell is used. The third equivalent circuit model of the third unit is extended to the third equivalent circuit model 3 of the third battery module, which represents all the other single cells. The first equivalent circuit model 1, the second equivalent circuit model 2, and the third equivalent circuit model 3 are connected in series to form a system-level equivalent circuit model. S4. Based on the basic parameters and mass of the single cell and the preset thermal management scheme, the first thermal management model, the second thermal management model, and the third thermal management model are constructed respectively, corresponding to the first battery module, the second battery module, and the third battery module. The basic parameters include density, specific heat capacity, and thermal conductivity. S5. The pulse charge and discharge condition model 5 is constructed based on the preset power value and duration of pulse charge and discharge. S6. The system-level equivalent circuit model, the first thermal management model, the second thermal management model, the third thermal management model, and the pulse charge and discharge condition model 5 are thermoelectrically coupled and combined to obtain the power battery system power simulation model.
[0040] Furthermore, when the computer program in memory 130 can be implemented as a software functional 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 invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory, random access memory, magnetic disks, or optical disks.
[0041] The following describes a specific embodiment of the present invention, taking a 1P126S (one parallel branch with 126 cells connected in series) automotive lithium-ion power battery system as an example, to elaborate on the power battery system power simulation model construction method of the present invention. The specific steps are as follows: S1. Select sample individual battery cells DC internal resistance (DCR) tests were performed on 126 identical battery cells within the 1P126S system. Based on the test results, the cell with the lowest internal resistance was selected as the first sample cell; the cell with the highest internal resistance was selected as the second sample cell; and the cell with an internal resistance at the statistical average level was selected as the third sample cell. That is, m=1, n=1, N=126, and the number of cells corresponding to the third battery module is N. m n=124.
[0042] S2, Constructing the equivalent circuit model of the unit The three sample cells were subjected to the following tests: 1. Charge and discharge test to calibrate the rated capacity of a single battery cell; 2. Perform HPPC testing at multiple temperatures and SOC points; 3. Import the collected HPPC test data into Amesim software, and use the software's parameter identification tool to analyze and obtain characteristic parameters such as OCV, ohmic internal resistance, and polarization internal resistance at different temperatures and SOCs. 4. Based on the characteristic parameters, construct the first unit equivalent circuit model (characterizing the cell with the lowest internal resistance), the second unit equivalent circuit model (characterizing the cell with the highest internal resistance), and the third unit equivalent circuit model (characterizing the cell with the average internal resistance).
[0043] S3, Extended to a system-level equivalent circuit model (1P126S) Based on the 1P126S configuration, the cell model is extended to the equivalent circuit model of the corresponding battery module: First equivalent circuit model: It is composed of m=1 first unit equivalent circuit models connected in series, representing a single cell with the lowest internal resistance in the system; Second equivalent circuit model: It is composed of n=1 second unit equivalent circuit models connected in series, representing the single cell with the highest internal resistance in the system. The third equivalent circuit model consists of 124 third-unit equivalent circuit models connected in series, representing the average internal resistance of the remaining 124 individual cells in the system.
[0044] The first equivalent circuit model, the second equivalent circuit model, and the third equivalent circuit model are connected in series to form a system-level equivalent circuit model corresponding to the 1P126S configuration.
[0045] Meanwhile, additional internal resistances (such as bus resistance, connecting piece resistance, and busbar resistance) are connected in series in the equivalent circuit model of each battery module to make the model more closely resemble the actual power battery system.
[0046] S4. Construct the first, second, and third thermal management models. A thermal characteristic parameter model is constructed based on the density, specific heat capacity, and thermal conductivity of a single battery cell; Based on the number of cells and the mass of each cell represented by each battery module, the total mass of each module is calculated, and the first, second, and third thermal mass models are constructed. Based on the preset thermal management scheme, the convective heat transfer coefficient was determined (using the natural cooling thermal management scheme, based on industry experience and test data, the convective heat transfer coefficient between the three battery modules and the external environment was set to 8W / m² / K), and the first, second, and third convective heat transfer models were constructed. By coupling the thermal characteristic parameter model with the thermal mass model, and then coupling the thermal mass model with the convection heat transfer model, the first thermal management model, the second thermal management model, and the third thermal management model are obtained, respectively.
[0047] S5. Construct a pulse charge-discharge operating condition model. like Figure 5 As shown, based on the actual power requirements of the vehicle, the pulse charging and discharging power and duration are set, and a pulse charging and discharging operating condition model is constructed to provide charging and discharging excitation to the system-level equivalent circuit model.
[0048] S6. Thermoelectric coupling yields the final power simulation model. The system-level equivalent circuit model, the first thermal management model, the second thermal management model, the third thermal management model, and the pulse charge-discharge condition model are thermoelectrically coupled together. Specifically, the system-level equivalent circuit model is coupled with the pulse charge-discharge condition model; the first equivalent circuit model is coupled with the first thermomass model and the first convection heat transfer model; the second equivalent circuit model is coupled with the second thermomass model and the second convection heat transfer model; and the third equivalent circuit model is coupled with the third thermomass model and the third convection heat transfer model. This results in a power simulation model suitable for the 1P126S power battery system.
[0049] The accuracy of the simulation model constructed in this embodiment is verified and adjusted. Figure 5 The simulated pulse power value of the medium-power battery system makes Figure 4 The lowest simulated voltage of a single cell is close to the measured voltage. Figure 4 and Figure 5 As can be seen, under the conditions of 25℃ and 10s pulse discharge, when the simulated and measured values of the lowest single-cell voltage are both 2.732V, the simulated pulse discharge power is 173kW and the measured value is 180kW, with a simulation accuracy of 96%. This shows that the power simulation model of the power battery system constructed according to the method of this invention can accurately describe the change in the power capability of the system when the lowest single-cell voltage reaches a certain set value, and the constructed power simulation model is in excellent agreement with the actual system.
[0050] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.
Claims
1. A method for constructing a power simulation model of a power battery system, characterized in that, Includes the following steps: S1. Select sample cells from the individual cells of the power battery system to be studied. The sample cells include the first sample cell with the lowest internal resistance, the second sample cell with the highest internal resistance, and the third sample cell with a representative average internal resistance. S2. Based on the characteristic parameters of each sample cell, construct the first unit equivalent circuit model, the second unit equivalent circuit model, and the third unit equivalent circuit model to represent the cell with the lowest internal resistance, the cell with the highest internal resistance, and the cell with the average internal resistance, respectively. The characteristic parameters include at least capacity, open circuit voltage OCV, and internal resistance. S3. Based on the configuration of the power battery system under study, the first unit equivalent circuit model is extended to a first equivalent circuit model representing the first battery module of all individual cells with the lowest internal resistance. The second unit equivalent circuit model is extended to a second equivalent circuit model representing the second battery module of all individual cells with the highest internal resistance. The third unit equivalent circuit model is extended to a third equivalent circuit model representing the third battery module of all other individual cells. The first equivalent circuit model, the second equivalent circuit model, and the third equivalent circuit model are connected in series to form a system-level equivalent circuit model. S4. Based on the basic parameters and mass of a single battery cell and the preset thermal management scheme, construct a first thermal management model, a second thermal management model, and a third thermal management model corresponding to the first battery module, the second battery module, and the third battery module, respectively. The basic parameters include density, specific heat capacity, and thermal conductivity. S5. Construct a pulse charging and discharging operating condition model based on the preset power value and duration of pulse charging and discharging; S6. Combine the system-level equivalent circuit model, the first thermal management model, the second thermal management model, the third thermal management model, and the pulse charge-discharge condition model in a thermoelectric coupling manner to obtain the power simulation model of the power battery system.
2. The method for constructing a power simulation model of a power battery system according to claim 1, characterized in that, The selection of sample individual cells in step S1 includes: performing DC internal resistance tests on individual cells of the same model produced in batches, and selecting individual cells with the lowest internal resistance, the highest internal resistance, and those at the statistical average internal resistance level based on the test results.
3. The method for constructing a power simulation model of a power battery system according to claim 2, characterized in that, Step S2 further includes: Each selected sample cell was subjected to charge-discharge tests to calibrate its capacity, and HPPC test data at different temperatures and SOCs were collected based on the capacity. Based on the HPPC test data, the characteristic parameters of the corresponding single cell under different temperatures and different SOCs are identified and obtained. Based on the aforementioned characteristic parameters, the first unit equivalent circuit model, the second unit equivalent circuit model, and the third unit equivalent circuit model are constructed.
4. The method for constructing a power simulation model of a power battery system according to claim 1, characterized in that, In step S3, the first equivalent circuit model, the second equivalent circuit model, and the third equivalent circuit model are extended in the following way: The first equivalent circuit model is composed of m first unit equivalent circuit models connected in series; the second equivalent circuit model is composed of n second unit equivalent circuit models connected in series; the third equivalent circuit model is composed of (Nmn) third unit equivalent circuit models connected in series; where N is the total number of individual cells in the power battery system under study, m and n are both positive integers, representing the number of individual cells with the lowest and highest internal resistance in the power battery system under study, respectively, and m+n< <N。 5. The method for constructing a power simulation model of a power battery system according to claim 4, characterized in that, Both m and n take the value 1, and the third equivalent circuit model is composed of (N-2) third unit equivalent circuit models connected in series.
6. The method for constructing a power simulation model of a power battery system according to claim 1, characterized in that, The first equivalent circuit model, the second equivalent circuit model, and the third equivalent circuit model also include additional internal resistance of the power battery system connected in series with them.
7. The method for constructing a power simulation model of a power battery system according to claim 1, characterized in that, Step S4 includes: A thermal characteristic parameter model of a single battery cell is constructed based on the basic parameters of the single battery cell. Based on the number of individual cells and the mass of a single cell represented by the first, second, and third battery modules, the total mass of the first, second, and third battery modules is calculated. The thermal characteristic parameter model of the individual cell is associated with the total mass of each battery module to construct a first thermal mass model, a second thermal mass model, and a third thermal mass model corresponding to the first, second, and third battery modules, respectively. Based on the preset thermal management scheme, the convective heat transfer coefficients between the first battery module, the second battery module, and the third battery module and the external environment are determined, and a first convective heat transfer model, a second convective heat transfer model, and a third convective heat transfer model corresponding to the first battery module, the second battery module, and the third battery module are constructed respectively. The thermal characteristic parameter model of a single cell is coupled with the first thermomass model, the second thermomass model and the third thermomass model, respectively. The first thermomass model, the second thermomass model and the third thermomass model are then coupled with the first convection heat transfer model, the second convection heat transfer model and the third convection heat transfer model, respectively, to obtain the first thermal management model, the second thermal management model and the third thermal management model.
8. The method for constructing a power simulation model of a power battery system according to claim 1, characterized in that, The preset thermal management scheme is natural cooling or liquid cooling.
9. The method for constructing a power simulation model of a power battery system according to claim 7, characterized in that, Step S6 further includes: The system-level equivalent circuit model is coupled with the pulse charge-discharge operating condition model. The first equivalent circuit model is coupled with the first convective heat transfer model and the first thermal mass model; the second equivalent circuit model is coupled with the second convective heat transfer model and the second thermal mass model; the third equivalent circuit model is coupled with the third convective heat transfer model and the third thermal mass model. This leads to the power simulation model of the power battery system.
10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable by the processor, characterized in that, When the processor executes the computer program, it implements the method for constructing a power simulation model of a power battery system as described in any one of claims 1 to 9.