Thermal management simulation method of energy storage system, storage medium and computer equipment

Abstract

The invention provides a thermal management simulation method of an energy storage system, a storage medium and computer equipment. The thermal management simulation method comprises the following steps: obtaining reduced order models of all liquid-cooled battery packs in an energy storage system; acquiring a battery cell heat production rate and a battery cell operation environment temperature of a battery cell in each liquid-cooled battery pack, and an inlet cooling liquid flow rate and an inlet cooling liquid temperature of each liquid-cooled battery pack; and inputting the battery cell heat production rate, the battery cell operation environment temperature, the inlet cooling liquid flow velocity and the inlet cooling liquid temperature into a corresponding order reduction model of the liquid-cooled battery pack to obtain a whole cabin temperature data set of the energy storage system, the pack reduced order model of each liquid-cooled battery is used for representing the relationship between the inlet cooling liquid flow rate and the inlet cooling liquid temperature of the corresponding liquid-cooled battery pack and the temperature data of the whole cabin under the battery cell heat production rate and the battery cell operation environment temperature.

Description

Background Art

[0002] As the scale and complexity of energy storage systems continue to expand, thermal management of energy storage cells becomes particularly important. Since energy storage cells generate a lot of heat during the charging and discharging process, if this heat cannot be effectively managed and controlled, it will lead to a decrease in performance, shortened life, and even safety hazards.

[0003] At present, energy storage battery compartments are mainly liquid-cooled battery compartments, and the bottom of the battery pack is cooled by a liquid cooling plate. For the thermal management simulation of liquid-cooled battery compartments, the simulation size is between millimeters and meters, the size span is large, the simulation difficulty is high, and the simulation time is long. In addition, the number of battery clusters in the battery compartment is increasing, which greatly increases the difficulty of simulation. Simulation can only perform steady-state simulation analysis, and transient simulation analysis is relatively complex.

[0004] The current three-dimensional thermal management simulation modeling of energy storage battery compartments is complex and has high requirements for computers. For transient simulation of thermal management, the simulation time is long and it is difficult to converge. In addition, the current heating simulation of energy storage cells usually sets a constant heating rate, which is different from the heating conditions of real cells. Summary of the invention

[0005] One of the objectives of the present disclosure is to provide a thermal management simulation method that can accurately obtain the temperature of the entire cabin of an energy storage system.

[0006] One of the objectives of the present disclosure is to provide a method capable of performing rapid thermal management simulation on an energy storage system.

[0007] According to one aspect of the present disclosure, a thermal management simulation method for an energy storage system is provided, the thermal management simulation method comprising: obtaining reduced-order models of all liquid-cooled battery packs in the energy storage system; obtaining the cell heat generation rate of the battery cells in each liquid-cooled battery pack, the cell operating environment temperature, the inlet coolant flow rate and the inlet coolant temperature of each liquid-cooled battery pack; inputting the cell heat generation rate, the cell operating environment temperature, the inlet coolant flow rate and the inlet coolant temperature into the reduced-order model of the corresponding liquid-cooled battery pack to obtain a whole-cabin temperature data set of the energy storage system, wherein the reduced-order model of each liquid-cooled battery pack is used to characterize the relationship between the inlet coolant flow rate and the inlet coolant temperature of the corresponding liquid-cooled battery pack and the whole-cabin temperature data under the cell heat generation rate and the cell operating environment temperature.

[0008] According to an embodiment of the present disclosure, the step of obtaining reduced-order models of all liquid-cooled battery packs in an energy storage system may include: for each liquid-cooled battery pack in the energy storage system, establishing a three-dimensional simulation model of the corresponding liquid-cooled battery pack based on the layout of each liquid-cooled battery pack; simulating the three-dimensional simulation model of the corresponding liquid-cooled battery pack based on the thermal physical properties of the battery cells in each liquid-cooled battery pack, the heat generation rate of the battery cells, and the boundary conditions of the liquid-cooled battery pack to obtain a reduced-order model of each liquid-cooled battery pack in the energy storage system.

[0009] According to an embodiment of the present disclosure, based on the cell thermophysical property parameters, cell heat generation rate and liquid-cooled battery pack boundary conditions of the battery cells in each liquid-cooled battery pack, a three-dimensional simulation model of the corresponding liquid-cooled battery pack is simulated, and the step of obtaining a reduced-order model of each liquid-cooled battery pack in the energy storage system may include: performing a three-dimensional thermal-fluid simulation on the three-dimensional simulation model of the liquid-cooled battery pack using the cell thermophysical property parameters, cell heat generation rate and liquid-cooled battery pack boundary conditions to obtain a temperature data set of the liquid-cooled battery pack under different liquid-cooled battery pack boundary conditions; determining the reduced-order model of the liquid-cooled battery pack based on the temperature data set, wherein the liquid-cooled battery pack boundary conditions may include the inlet coolant temperature and the inlet coolant flow rate of the liquid-cooled battery pack.

[0010] According to an embodiment of the present disclosure, the thermal management simulation method may further include: establishing a three-dimensional model of the liquid cooling pipelines of the entire cabin according to the liquid cooling pipeline layout of the battery cabin of the energy storage system; performing a three-dimensional fluid simulation of the liquid cooling pipelines of the entire cabin on the three-dimensional model of the liquid cooling pipelines of the entire cabin using different liquid cooling pipeline boundary conditions to obtain the inlet coolant flow data of each liquid-cooled battery pack under different liquid cooling pipeline boundary conditions; determining a reduced-order model of the liquid cooling pipeline system based on the inlet coolant flow data of each liquid-cooled battery pack under different liquid cooling pipeline boundary conditions, wherein the liquid cooling pipeline boundary conditions include the total inlet coolant flow rate of the liquid cooling pipeline, and the inlet coolant flow data include the inlet coolant flow rate of each liquid-cooled battery pack.

[0011] According to an embodiment of the present disclosure, the inlet coolant flow rate may be determined by the detected total inlet coolant flow rate and a reduced-order model of the cooling pipe system.

[0012] According to an embodiment of the present disclosure, the inlet coolant temperature is obtained from the energy management system of the energy storage system, and the thermal management simulation method may also include: obtaining temperature acquisition data of the entire cabin of the energy storage system; using the temperature acquisition data and the entire cabin temperature data to render a predetermined three-dimensional model of the entire cabin battery cell structure to obtain a temperature cloud map of the entire cabin.

[0013] According to an embodiment of the present disclosure, the thermal management simulation method may further include: determining an error between the temperature acquisition data and the whole cabin temperature data; and generating a warning signal in response to the error exceeding a first threshold.

[0014] According to an embodiment of the present disclosure, the inlet coolant temperature may be determined according to a refrigeration system thermal management strategy of the energy storage system and a predetermined one-dimensional refrigeration system simulation model.

[0015] According to the embodiments of the present disclosure, the thermal physical parameters and heat generation rate of the battery cells of each liquid-cooled battery pack can be obtained through the following steps: obtaining the thermal physical parameters, electrochemical parameters and charge and discharge cycle temperature rise curves of the battery cells in the liquid-cooled battery pack; performing three-dimensional thermal simulation on the battery cells using the thermal physical parameters to obtain the temperature data of the battery cells; performing one-dimensional electrochemical simulation on the battery cells using the electrochemical parameters to obtain the heat generation rate of the battery cells; performing electrochemical-thermal coupling joint simulation on the battery cells using the temperature data of the battery cells and the heat generation rate of the battery cells to obtain the temperature simulation curve of the battery cells; adjusting the thermal physical parameters and electrochemical parameters so that the error between the temperature simulation curve obtained by the electrochemical-thermal coupling joint simulation and the charge and discharge cycle temperature rise curve is less than a second threshold; determining the thermal physical parameters and heat generation rate corresponding to the adjusted final thermal physical parameters and final electrochemical parameters as the thermal physical parameters and heat generation rate of the battery cells.

[0016] According to a second aspect of the present disclosure, a computer device includes a memory and a processor, wherein the memory stores instructions or programs, and when the instructions or programs are loaded and executed by the processor, the processor is prompted to execute a thermal management simulation method for an energy storage system.

[0017] According to a third aspect of the present disclosure, a computer-readable storage medium stores a program or instruction, which, when loaded and executed by a processor, prompts the processor to execute a thermal management simulation method for an energy storage system.

[0018] The thermal management simulation method according to the embodiment of the present disclosure can accurately simulate the heating condition of the battery cell, and the temperature simulation accuracy is high. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings.

[0020] Figure 1 is a flow chart of a thermal management simulation method for an energy storage system according to an embodiment of the present disclosure;

[0021] Figure 2 is a flowchart of steps for generating a reduced-order model of a liquid-cooled battery pack according to the first embodiment of the present disclosure;

[0022] Figure 3 is a flow chart of steps for generating a reduced-order model of a liquid cooling pipeline system according to the first embodiment of the present disclosure;

[0023] Figure 4is a flow chart of cell parameter fitting simulation according to the first embodiment of the present disclosure;

[0024] Figure 5 is a cell parameter fitting simulation flow chart according to the second embodiment of the present disclosure;

[0025] Figure 6 is a flowchart of steps for generating a reduced-order model of a liquid-cooled battery pack according to a second embodiment of the present disclosure;

[0026] Figure 7 is a flow chart of steps for generating a reduced-order model of a liquid cooling pipeline system according to a second embodiment of the present disclosure;

[0027] Figure 8 is a schematic diagram showing a device operation monitoring principle according to an embodiment of the present disclosure; and

[0028] Fig. 9 is a diagram showing a principle of device operation prediction according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0029] The following detailed description is provided to help gain a comprehensive understanding of the methods, devices and / or systems described herein. However, the order of operations described herein is only an example and is not limited to those orders set forth herein, but may be equivalently replaced or changed except for operations that must occur or be performed in a specific order. In addition, for greater clarity and simplicity, the description of content known in the art will be omitted or simplified.

[0030] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by a person of ordinary skill in the art to which the present disclosure belongs after understanding the present disclosure. Unless explicitly defined as such herein, terms (such as those defined in a general dictionary) should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and the present disclosure, and should not be interpreted in an idealized or overly formal manner.

[0031] Unless otherwise specified, the same reference numerals generally refer to the same elements (e.g., components, steps, and methods). Reference numerals described in the previous embodiments may be omitted if they appear again in the subsequent embodiments. In addition, the technical features described in different or the same embodiments may be combined in any manner, as long as the combined embodiments or technical solutions are complete and can solve the technical problems of the present application or achieve the technical effects described or not described in the present disclosure but can be determined based on the above complete technical solutions. It should be noted that these embodiments and their features may be combined with each other in the absence of conflicts between the various embodiments. Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process and related instructions of the system described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0032] A battery cell is the smallest energy storage unit of an energy storage system. The energy storage system in the present disclosure may include one or more battery packs, each of which includes multiple battery cells. The models of the battery cells included in each battery pack are usually the same, the models of the battery cells included in each energy storage system may all be the same, and the models of the battery cells in different battery packs may be different.

[0033] In addition to the battery cells, the battery pack may also include thermal management system components such as liquid cooling plates. In addition to the battery pack, the energy storage system may also include auxiliary components such as PCS, thermal management system, energy management system (EMS), and monitoring system.

[0034] The present disclosure greatly shortens the simulation time by using the reduced-order model of the liquid-cooled battery pack and the reduced-order model of the liquid-cooling pipeline system. In addition, the present disclosure uses the electrochemical and thermal coupling methods of the battery cell to fit the heating rate of the battery cell, which can more accurately simulate the heat generation of the battery cell and facilitate accurate monitoring and prediction of the temperature of the energy storage system. The following is a description of the embodiments of the present disclosure.

[0035] Figure 1 is a flow chart of a thermal management simulation method for an energy storage system according to an embodiment of the present disclosure; Figure 2 is a flowchart of steps for generating a reduced-order model of a liquid-cooled battery pack according to the first embodiment of the present disclosure;

[0036] Figure 3 is a flow chart of steps for generating a reduced-order model of a liquid cooling pipeline system according to the first embodiment of the present disclosure; Figure 4 is a flow chart of cell parameter fitting simulation according to the first embodiment of the present disclosure; Figure 5 is a cell parameter fitting simulation flow chart according to the second embodiment of the present disclosure; Figure 6 is a flowchart of steps for generating a reduced-order model of a liquid-cooled battery pack according to a second embodiment of the present disclosure; Figure 7is a flow chart of steps for generating a reduced-order model of a liquid cooling pipeline system according to a second embodiment of the present disclosure; Figure 8 is a schematic diagram showing a device operation monitoring principle according to an embodiment of the present disclosure; and Fig. 9 is a diagram showing a principle of device operation prediction according to an embodiment of the present disclosure.

[0037] Reference Figure 1 According to an embodiment of the present disclosure, the thermal management simulation method of the energy storage system may include step S110, step S120 and step S130.

[0038] In step S110, the reduced-order models of all liquid-cooled battery packs in the energy storage system are obtained. The reduced-order models of each liquid-cooled battery pack are used to characterize the relationship between the inlet coolant flow rate and the inlet coolant temperature of the corresponding liquid-cooled battery pack and the whole cabin temperature data under the heat generation rate of the battery cell and the operating environment temperature of the battery cell. The reduced-order model of the liquid-cooled battery pack here can be a pre-established reduced-order model and can be obtained by simulation.

[0039] In addition, as an example, different liquid-cooled battery packs may have different reduced-order models. However, the present disclosure is not limited thereto, and if the types of cells included in each liquid-cooled battery pack are the same, each liquid-cooled battery pack may have the same reduced-order model. The coolant here may be water, but the present disclosure is not limited thereto.

[0040] In addition, the reduced-order model of the liquid-cooled battery pack disclosed in the present invention can be a linear model. Compared with the existing high-order simulation model using finite element output, the reduced-order model of the liquid-cooled battery pack disclosed in the present invention can obtain the temperature of the entire cabin at a faster speed, thereby improving the efficiency of thermal management.

[0041] Here, the reduced-order model of the liquid-cooled battery pack may be a reduced-order model at a certain cell heat generation rate and a certain cell operating environment temperature, and different cell heat generation rates and different cell operating environment temperatures may have different reduced-order models. As an example, a cell heat generation rate and a cell operating environment temperature may correspond to a reduced-order model of a liquid-cooled battery pack, or a certain range of cell heat generation rates and a certain range of cell operating environment temperatures may correspond to the same reduced-order model of the liquid-cooled battery pack, however, the present disclosure is not limited thereto.

[0042] In addition, such a reduced-order model can be obtained for each liquid-cooled battery pack of the energy storage system. The reduced-order model of the liquid-cooled battery pack can characterize the relationship between the inlet coolant flow rate and the inlet coolant temperature of the liquid-cooled battery pack and the temperature data of the entire cabin under the heat generation rate of the battery cell and the operating environment temperature of the battery cell.

[0043] Here, the inlet coolant flow rate (for example, the inlet flow rate or the water inlet flow rate) refers to the flow rate of the coolant entering the cooling system of the liquid-cooled battery pack, which directly affects the ability of the coolant to remove the heat generated by the liquid-cooled battery pack, thereby affecting the temperature control effect of the liquid-cooled battery pack. The greater the flow rate, the better the cooling effect is generally; the inlet coolant temperature (for example, the water inlet temperature) refers to the temperature of the coolant when it enters the cooling system of the liquid-cooled battery pack. A lower water inlet temperature helps to better remove the heat generated by the liquid-cooled battery pack and keep the liquid-cooled battery pack operating within an appropriate temperature range.

[0044] During the simulation process, the inlet coolant flow rate and inlet coolant temperature are important boundary conditions that have a significant impact on the simulation results. The inlet coolant flow rate affects the speed at which the coolant passes through the liquid-cooled battery pack, which in turn affects the cooling effect. A higher flow rate usually means better cooling capacity. The inlet coolant temperature determines the initial temperature of the coolant, and a lower temperature is conducive to improving the cooling effect. When performing simulations, by changing the values ​​of these two parameters, the changes in the cell voltage and temperature in the liquid-cooled battery pack can be obtained.

[0045] As an example, a reduced-order model of a liquid-cooled battery pack can be obtained by simulation. For example, a three-dimensional simulation model of each liquid-cooled battery pack in the energy storage system can be established based on the layout of each liquid-cooled battery pack; based on the thermal physical parameters of the battery cells in each liquid-cooled battery pack, the heat generation rate of the battery cells, and the boundary conditions of the liquid-cooled battery pack, the three-dimensional simulation model of the corresponding liquid-cooled battery pack is simulated to obtain a reduced-order model of each liquid-cooled battery pack in the energy storage system.

[0046] Reference Figure 2 The step of obtaining a reduced-order model of a liquid-cooled battery pack by simulation may include step S210 and step S220.

[0047] In step S210, a three-dimensional thermal-fluid simulation is performed on the three-dimensional simulation model of the liquid-cooled battery pack using the thermal physical properties of the battery cells, the heat generation rate of the battery cells, and the boundary conditions of the liquid-cooled battery pack to obtain a temperature data set of the liquid-cooled battery pack under different boundary conditions of the liquid-cooled battery pack.

[0048] The three-dimensional model of the liquid-cooled battery pack can be established according to the layout of the liquid-cooled battery pack.

[0049] For example, the specific layout of the liquid-cooled battery pack can be determined first, including the size and shape of the battery pack, the arrangement of the cells in the battery pack, etc. As an example, the layout of the liquid-cooled battery pack can also include the design and direction of the liquid cooling pipeline. The flow direction of the coolant, the location of the pipeline, the diameter of the pipeline, and other parameters can be determined based on the layout of the battery pack and the liquid cooling pipeline. Then, combining the battery pack layout and the liquid cooling pipeline layout, use simulation software (for example, ANSYS, etc.) to establish a three-dimensional model of the liquid-cooled battery pack.

[0050] The heat generation rate of the battery cell, the boundary conditions of the liquid-cooled battery pack, and the thermal physical parameters of the battery cell obtained by simulation can be used to perform a three-dimensional thermal-fluid simulation on the three-dimensional simulation model of the liquid-cooled battery pack to obtain the temperature set under different boundary conditions of the liquid-cooled battery pack. At the same time, the battery cell voltage under different boundary conditions of the liquid-cooled battery pack can be obtained as needed.

[0051] As an example, the heat generation rate of the battery cell can be determined by the relevant thermal physical property parameters of the battery cell. In addition, the operating environment temperature of the battery cell can also be used as a simulation condition, and the specific operating environment temperature of the battery cell can be determined by monitoring. For example, the operating environment temperature of the battery cell can be obtained by a temperature sensor, and the temperature sensor can be installed in the battery compartment to monitor the actual working environment temperature of the battery cell. The actual working environment temperature of the battery cell can be monitored by multiple sensors installed at different positions in the battery compartment.

[0052] In addition, the heat generation rate of the battery cell can be indirectly calculated by the parameters related to heat generation in the product identification. As an example, the heat generation rate of the battery cell can be determined by simulation. For example, the heat generation rate of the battery cell can be fitted by the battery cell electrochemical and thermal coupling method, thereby simulating the heat generation of the battery cell more accurately.

[0053] For details, please refer to Figure 4 The thermal physical property parameters of the battery cell and the heat generation rate of the battery cell can be obtained through steps S410, S420, S430, S440, S450 and S460.

[0054] In step S410, the thermophysical parameters, electrochemical parameters and charge-discharge cycle temperature rise curve of the battery cells in the liquid-cooled battery pack are obtained.

[0055] The thermophysical parameters of the battery cell may include density, specific heat capacity, thermal conductivity, etc. These parameters can be obtained by thermophysical property testing. As an example, the density can usually be obtained by a balance weighing method, or by other methods such as the buoyancy method. The specific heat capacity can be measured by adiabatic calorimeter or differential scanning calorimetry, and the thermal conductivity can be measured by a steady-state method or a transient method. The specific test can be carried out using existing related equipment, which will not be described in detail here.

[0056] The electrochemical parameters of a battery cell are parameters that describe the electrochemical reaction characteristics inside the battery. The electrochemical parameters of a battery cell may include conductivity, diffusion rate, diaphragm thickness, capacity of electrode active materials, electrode porosity, exchange current density, etc. The electrochemical parameters of a battery cell can all be obtained through testing.

[0057] The charge and discharge cycle temperature rise curve of the battery cell can be determined based on the data provided by the battery cell manufacturer. The battery cell performance data provided by the battery cell manufacturer may include the charge and discharge cycle temperature rise curve. These data are usually based on the typical use conditions of the battery cell, such as specific charge and discharge currents, temperature ranges, etc. In addition, the charge and discharge cycle temperature rise curve of the battery cell can also be obtained by testing, for example, collecting temperature data under different charge and discharge cycles. When collecting temperature, the corresponding voltage data can be obtained.

[0058] The thermal management simulation method disclosed in the present invention may not separately include the testing steps and / or collection steps described above, but may directly obtain and use data that has been tested or collected in advance (eg, thermophysical parameters, electrochemical parameters, and charge-discharge cycle temperature rise curves).

[0059] In step S420 , a three-dimensional thermal simulation is performed on the battery cell using the thermophysical property parameters to obtain temperature data of the battery cell.

[0060] For three-dimensional thermal simulation of battery cells, a three-dimensional model can be established in software (for example, COMSOL) according to the size of the battery cells. Then, the thermal property parameters such as density, specific heat capacity, thermal conductivity, etc. obtained in the thermal property test are input into the three-dimensional model for simulation to obtain the temperature data of the battery cells.

[0061] In step S430 , a one-dimensional electrochemical simulation is performed on the battery cell using the electrochemical parameters to obtain a heat generation rate of the battery cell.

[0062] The one-dimensional electrochemical simulation here may include the establishment and calculation and solution process of a one-dimensional electrochemical model. Specifically, the electrochemical process inside the battery cell can usually be simulated by establishing a one-dimensional electrochemical model along the length of the battery cell. The model can be meshed to ensure that the mesh is fine enough to capture the details of the electrochemical process. In addition, the one-dimensional electrochemical simulation process may also include physical field settings, boundary condition settings, and input of electrochemical parameters (for example, conductivity, diffusion rate, diaphragm thickness, capacity of electrode active materials, electrode porosity, and exchange current density, etc.).

[0063] In step S440 , an electrochemical-thermal coupling joint simulation is performed on the battery cell using the temperature data of the battery cell and the heat generation rate of the battery cell to obtain a temperature simulation curve of the battery cell.

[0064] Electrochemical-thermal coupling co-simulation means that the temperature of the 3D thermal model will affect the heat generation rate of the 1D electrochemical model, and the heat generation rate of the 1D electrochemical model will in turn affect the temperature of the 3D thermal model. Therefore, in the co-simulation, the temperature of the 3D thermal model is input into the 1D electrochemical model, and the heat generation rate obtained by the 1D electrochemical model is in turn input into the 3D thermal model, so as to achieve co-simulation, make the simulation process more precise, and obtain more accurate temperature data.

[0065] In step S450, the thermophysical parameters and the electrochemical parameters are adjusted so that the error between the temperature simulation curve obtained by the electrochemical-thermal coupling simulation and the charge-discharge cycle temperature rise curve is less than a second threshold.

[0066] The error between the temperature simulation curve and the charge and discharge cycle temperature rise curve can be a fitting error. For example, the temperature rise simulation curve can be fitted and compared with the temperature simulation curve obtained by the test, that is, the simulation results and the test results are fitted and compared. As an example, the least squares fitting method can be used to determine the fitting error. If the fitting error exceeds a preset threshold, the simulation parameters (for example, density, specific heat capacity, thermal conductivity, electrochemical parameters, at least one of them) can be adjusted until the fitting error is less than 5% or other preset thresholds. This value can be determined according to actual conditions.

[0067] In step S460, the thermophysical parameters corresponding to the adjusted final thermophysical parameters and the final electrochemical parameters and the heat generation rate are determined as the cell thermophysical parameters and the cell heat generation rate. Different types or models of cells can be simulated separately to obtain the heat generation rates of different types of cells.

[0068] The thermal physical parameters of the battery cell and the heat generation rate of the battery cell can also be measured by Figure 5 Refer to the steps shown. Figure 5 According to the second embodiment of the present disclosure, the cell parameter fitting simulation step may include step S510, step S520, step S530, step S540, step S550, step S560, step S570, step S580, step S590 and step S591.

[0069] In step S510, the battery cell model is determined: first, the target battery cell model needs to be determined so that subsequent work can test and simulate the specific type of battery cell.

[0070] In step S520, a thermal property test of the battery cell is performed. A series of thermal property tests may be performed on the battery cell, for example, a density test, a specific heat capacity test, and a thermal conductivity test. As described above, the specific heat capacity may be measured by a calorimeter, the thermal conductivity may be measured using a heat flow meter, and the density may be measured using a balance.

[0071] In step S530, a three-dimensional thermal simulation of the battery cell is performed, and a three-dimensional thermal simulation model of the battery cell is constructed and run by using the acquired thermal physical property parameters, so as to simulate the temperature distribution of the battery cell under different working conditions.

[0072] In step S540, the electrochemical parameters of the positive and negative electrodes and the separator electrolyte of the battery cell are obtained. Specifically, as described above, the internal material properties of the battery cell are tested. The required electrochemical parameters can be obtained by performing electrochemical performance tests on the internal components of the battery cell (such as the positive electrode, negative electrode, separator and electrolyte).

[0073] In step S550, a one-dimensional electrochemical simulation is performed on the battery cell.

[0074] In step S560, an electrochemical-thermal coupling joint simulation of the battery cell is performed, and the electrochemical reaction and thermal effect can be considered simultaneously to establish an electrochemical-thermal coupling joint simulation model of the battery cell to more comprehensively understand the behavior of the battery cell.

[0075] In step S570, the voltage-temperature rise simulation curve (including the voltage simulation curve and the temperature simulation curve) of the battery cell is obtained. The voltage curve obtained by the test is relatively accurate, so the present disclosure can only obtain temperature data or temperature curve by simulation.

[0076] In step S580, the battery cell charge-discharge cycle temperature rise curve is obtained. As described above, the battery cell charge cycle temperature rise test can be performed, and specifically, the temperature change of the battery cell during the charge cycle can be recorded by experimental means to obtain the real battery cell temperature data.

[0077] In step S590, it is determined whether the error between the simulation result and the experimental data is less than a preset threshold value (e.g., 5%). As described above, if the error is greater than or equal to 5%, the simulation parameters (at least one of the thermophysical parameters and the electrochemical parameters) are adjusted. In addition, during the comparative verification process, only the temperature simulation data and the temperature test data may be verified without verifying the voltage data.

[0078] In step S591, if the error is less than 5%, the final battery cell thermal properties parameters, battery cell heat generation rate (for example, chronological heat generation rate), and voltage curve are determined. In other words, if the error is small, it means that the simulation model reflects the actual situation well, and these parameters can continue to be used to perform subsequent steps. When the fitting error is less than the preset threshold, the thermal properties parameters and electrochemical parameters at this time can be determined as the battery cell thermal properties parameters and the battery cell heat generation rate. The above-mentioned electrochemical-thermal coupling joint simulation can accurately determine the heat generation rate of the battery cell, which is conducive to accurately monitoring and predicting the temperature of the entire cabin of the energy storage system.

[0079] The specific process of the above-mentioned electrochemical-thermal coupling joint simulation is only an example, and the present disclosure is not limited thereto. The thermal management simulation method of the present disclosure can also use various existing simulation methods to determine the thermophysical parameters and the heat generation rate of the battery cell. In addition, although the various steps of the battery cell parameter fitting simulation step according to the second embodiment of the present disclosure are described in detail above (including the steps for obtaining the various data required for the battery cell parameter fitting), however, the present disclosure is not limited thereto, and those skilled in the art can omit or merge some steps according to the needs and the deployment method of the thermal management simulation method, and can also add some steps.

[0080] Reference Figure 2 In step S220, a reduced-order model of the liquid-cooled battery pack is determined based on the temperature data, wherein the boundary conditions of the liquid-cooled battery pack include an inlet coolant temperature of the liquid-cooled battery pack (e.g., water inlet temperature) and an inlet coolant flow rate of the liquid-cooled battery pack (e.g., inlet flow rate).

[0081] As an example, when the input boundary conditions are: water inlet temperature T1, inlet flow rate q1, the simulation results will obtain the cell voltage V1 and the cell temperature set X1: Ta1, Tb1, ... Tx1. When the input boundary conditions are: water inlet temperature T2, inlet flow rate q2, the simulation results will obtain the cell voltage V2 and the cell temperature set X2: Ta2, Tb2, ... Tx2. Similarly, when the input boundary conditions are: water inlet temperature Tn, inlet flow rate qn, the simulation results will obtain the cell voltage Vn and the temperature set Xn: Tan, Tbn, ... Txn.

[0082] Finally, the reduced-order model of the liquid-cooled battery pack is obtained according to T1, q1, V1, X1; T2, q2, V2, X2; ... Tn, qn, Vn, Xn. As an example, the above data can be input into the relevant model or software for data training, and the linear relationship between the inlet water temperature T, the inlet flow rate q and the battery cell voltage V, the battery cell temperature X can be obtained. This process can be performed in ANSYS software, and the obtained linear relationship can be called the reduced-order model of the liquid-cooled battery pack. As an example, the above data can be fitted to obtain the linear relationship between the inlet water temperature T, the inlet flow rate q and the battery cell voltage V, the battery cell temperature X, respectively, and the linear relationship between the inlet water temperature T, the inlet flow rate q and the battery cell voltage V, the battery cell temperature X, respectively, can also be obtained by machine learning.

[0083] Although not shown, the reduced-order model of the corresponding liquid-cooled battery pack can be determined under a predetermined battery cell operating environment temperature and / or battery cell thermal physical property parameter. That is, different battery cell operating environment temperatures and / or different battery cell thermal physical property parameters can correspond to different reduced-order models of the liquid-cooled battery pack.

[0084] For details, please refer to Figure 6 According to the second embodiment of the present disclosure, the step of generating the reduced-order model of the liquid-cooled battery pack may include step S610, step S620, step S630, step S640 and step S650.

[0085] In step S610, the battery pack layout is determined. The specific structure and layout of each battery pack of the energy storage system may be determined, including the number of cells, arrangement, routing of cooling pipes, etc.

[0086] In step S620, three-dimensional thermal-fluid simulation modeling of the liquid-cooled battery pack is performed: a three-dimensional simulation model of the liquid-cooled battery pack is established based on the battery pack layout, pre-acquired thermal physical parameters of the battery cells and the heat generation rate of the battery cells, different battery pack boundary conditions (S1, S2...Sn), etc. The battery pack boundary conditions may include the flow rate and temperature of the inlet coolant of the liquid-cooled battery pack, etc. However, the present disclosure is not limited thereto, and the battery pack boundary conditions may also include the specific heat capacity and thermal conductivity of the coolant, etc.

[0087] In step S630, a three-dimensional thermal-fluid simulation of the liquid-cooled battery pack is performed. Specific steps may include meshing, boundary condition setting, etc., which will not be repeated here.

[0088] In step S640, a battery pack temperature data set under different boundary conditions is obtained. That is, the temperature data set can be formed by simulating the temperature distribution of the battery pack under different boundary conditions.

[0089] In step S650, data training is performed on the data set. As an example, the data set may be input into a machine learning algorithm for training to generate a reduced-order model of a liquid-cooled battery pack. However, this is merely an example and the present disclosure is not limited thereto.

[0090] In addition, although the steps for generating the reduced-order model of the liquid-cooled battery pack according to the second embodiment of the present disclosure are described in detail above, the present disclosure is not limited thereto, and those skilled in the art may omit, merge, or add some steps according to needs and the deployment method of the thermal management simulation method.

[0091] Reference Figure 1 In step S120, the heat generation rate of the battery cells in each liquid-cooled battery pack, the battery cell operating environment temperature, the inlet coolant flow rate and the inlet coolant temperature of each liquid-cooled battery pack are obtained.

[0092] As an example, the heat generation rate of the battery cells of each battery pack of the energy storage system may be the same, and the heat generation rate of the battery cells of the energy storage system may be obtained by detection. The specific process is as described above and will not be repeated here.

[0093] The operating environment temperature of the battery cell can be detected by a temperature sensor installed in the battery compartment, or it can be read from the energy management system.

[0094] In step S130, the heat generation rate of the battery cell, the operating environment temperature of the battery cell, the inlet coolant flow rate and the inlet coolant temperature are input into the reduced-order model of the corresponding liquid-cooled battery pack to obtain the whole cabin temperature data of the energy storage system.

[0095] That is, the reduced-order model of the corresponding liquid-cooled battery pack can be determined or selected based on the actual heat generation rate of the battery cell and the temperature of the battery cell operating environment, and then the inlet coolant flow rate (e.g., water inlet flow rate) and the inlet coolant temperature (e.g., water inlet temperature) are input into the reduced-order model of the corresponding liquid-cooled battery pack, thereby obtaining the temperature of each liquid-cooled battery pack, where the temperature of each battery pack can be the temperature of a certain battery cell included therein, the highest temperature of a single battery cell, or the average temperature of all the battery cells included therein. Similarly, the temperature of the energy storage system (e.g., the temperature of the entire cabin) can be the temperature distribution at different locations inside the battery cabin, and can be determined based on the simulated temperature of each battery pack and / or temperature sensors set at different locations.

[0096] Reference Figure 3 According to the embodiment of the present disclosure, the thermal management simulation method may further include step S310, step S320 and step S330.

[0097] In step S310, a three-dimensional model of the liquid cooling pipeline of the entire cabin is established according to the layout of the liquid cooling pipeline of the battery cabin of the energy storage system. As an example, the detailed layout of the liquid cooling pipeline in the battery cabin can be determined, such as the location, shape, diameter, length, connection method and other information of the pipeline, and then a three-dimensional model of the liquid cooling pipeline of the entire cabin can be created, and the three-dimensional model can include components such as the liquid cooling pipeline. As an example, the three-dimensional model of the liquid cooling pipeline can be created using computer-aided design software or other professional tools.

[0098] In step S320, a three-dimensional fluid simulation of the entire cabin liquid cooling pipeline is performed on the entire cabin liquid cooling pipeline three-dimensional model using different liquid cooling pipeline boundary conditions to obtain inlet coolant flow data under different liquid cooling pipeline boundary conditions. The liquid cooling pipeline boundary conditions here may include the total inlet coolant flow rate of the liquid cooling pipeline, and the inlet coolant flow data may include the inlet coolant flow rate.

[0099] As an example, after the model of the liquid cooling pipeline is established, fluid simulation is performed. When the boundary condition is input: total water inlet flow rate V1, the simulation result will obtain the inlet flow rate set A1, B1, C1, ... Z1 for each battery pack. When the boundary condition is input: total water inlet flow rate V2, the simulation result will obtain the inlet flow rate set A2, B2, C2, ... Z2 for each battery pack. Similarly, when the boundary condition is input: total water inlet flow rate Vn, the simulation result will obtain the inlet flow rate set An, Bn, Cn, ... Zn for each battery pack.

[0100] In step S330, a reduced-order model of the liquid cooling pipeline system is determined based on the inlet coolant flow data under different liquid cooling pipeline boundary conditions.

[0101] As an example, data training can be performed using data such as V1, A1, B1, C1, ... Z1, V2, A2, B2, C2, ... Z2, Vn, An, Bn, Cn, ... Zn to obtain a linear relationship between the total water inlet flow rate V and the inlet flow rate A, B, ... N of the battery pack (i.e., a reduced-order model of the liquid cooling pipeline system). This process can be performed in simulation software (e.g., ANSYS), or the reduced-order model of the liquid cooling pipeline system can be obtained through another artificial intelligence model training.

[0102] In addition, refer to Figure 7 According to the second embodiment of the present disclosure, the steps of generating the reduced-order model of the liquid cooling pipeline system may include steps S710, S720, S730, S740 and S750.

[0103] In step S710, the layout of the liquid cooling pipeline in the battery compartment is determined: the specific position, direction and structure of the liquid cooling pipeline in the battery compartment can be determined first to facilitate subsequent simulation modeling.

[0104] In step S720, three-dimensional simulation modeling of the liquid cooling pipeline of the entire cabin is performed: three-dimensional simulation modeling can be performed based on the liquid cooling pipeline layout of the battery cabin and different liquid cooling pipeline boundary conditions S1, S2...Sn, and the three-dimensional simulation model may include liquid cooling pipelines, etc.

[0105] In step S730, a three-dimensional fluid simulation of the liquid cooling pipelines of the entire cabin is performed. Specifically, the three-dimensional fluid simulation of the liquid cooling pipelines of the entire cabin can be performed using simulation software such as COMSOL. The basic steps may include meshing, boundary condition setting, etc., which will not be repeated here.

[0106] In step S740, a data set of flow rates at the water inlet of each battery pack under different boundary conditions is obtained, that is, the flow rate data at the water inlet of the battery pack under different boundary conditions is obtained through simulation.

[0107] In step S750, data training is performed on the data set. As an example, the data set can be input into a machine learning algorithm for training to generate a reduced-order model of the liquid cooling pipe system. However, the present disclosure is not limited to this, and other methods can also be used to obtain the reduced-order model of the liquid cooling pipe system.

[0108] It should be noted that the various models required for the thermal management simulation method of the present invention can be predetermined, and these models can be directly called when the thermal management method of the present invention is used for temperature detection and temperature prediction.

[0109] The above steps included in the thermal management simulation method of the energy storage system according to the various embodiments of the present disclosure are merely examples, and those skilled in the art may add or delete some of the steps according to actual conditions, or may select some of the steps to execute according to the execution subject of the thermal management method.

[0110] The thermal management simulation method disclosed in the present invention can be used for temperature monitoring and temperature prediction. When the thermal management simulation method disclosed in the present invention is used for temperature monitoring, the inlet coolant flow rate can be determined by the detected total inlet coolant flow rate and the reduced-order model of the cooling pipeline system, and the inlet coolant temperature can be obtained from the energy management system (EMS); when the thermal management simulation method disclosed in the present invention is used for temperature prediction, the inlet coolant flow rate can be determined by the detected total inlet coolant flow rate and the reduced-order model of the cooling pipeline system, and the inlet coolant temperature (i.e., the predicted coolant outlet temperature) can be determined by the refrigeration system thermal management strategy (e.g., temperature control timing) and the one-dimensional refrigeration system simulation model.

[0111] When the thermal management simulation method disclosed in the present invention is used for temperature monitoring, the thermal management simulation method disclosed in the present invention may also include: obtaining temperature collection data of the entire cabin; using the temperature collection data and the entire cabin temperature data to render a predetermined three-dimensional model of the entire cabin battery cell structure to obtain a temperature cloud map of the entire cabin.

[0112] For details, please refer to Figure 8 , Figure 8 A schematic diagram of a device operation monitoring system according to an embodiment of the present disclosure is shown.

[0113] like Figure 8 As shown, the detected total inlet coolant flow rate can be input into the reduced-order model of the cooling pipeline system to determine the inlet coolant flow value (e.g., inlet coolant flow rate) of each battery pack, and the reduced-order model of the corresponding liquid-cooled battery pack is determined based on the pre-obtained heat generation rate of the battery cell and the environmental boundary conditions (e.g., the operating environment temperature of the battery cell). Then, the inlet coolant flow value of the battery pack and the coolant outlet water temperature of the liquid cooling device (i.e., the inlet coolant temperature) are input into the reduced-order model of the corresponding liquid-cooled battery pack, and the temperature data of each battery pack can be obtained. The temperature data of each battery pack can be used to determine the whole cabin temperature simulation data. The collected temperature data and the simulated temperature data can be input into the pre-established three-dimensional model of the whole cabin battery cell structure for temperature rendering, so as to obtain the whole cabin temperature cloud map. The three-dimensional model of the whole cabin battery cell structure can be determined according to the specific structure of the battery cabin of the energy storage system.

[0114] When the thermal management simulation method of the present invention is used for temperature monitoring, the thermal management simulation method of the present invention may also include: determining the error between the temperature acquisition data and the temperature data of the entire cabin; generating a warning signal in response to the error exceeding the first threshold. As an example, if the error exceeds 20%, a warning signal may be generated, indicating that there is an abnormality in the battery cell. If the error does not exceed 20% and is greater than 5%, the correction as described above may be performed, which will not be repeated here.

[0115] When the thermal management simulation method disclosed in the present invention is used for temperature prediction, the inlet coolant temperature can be determined according to the thermal management strategy of the refrigeration system of the energy storage system and a predetermined one-dimensional refrigeration system simulation model. The one-dimensional refrigeration system simulation model can be modeled according to the schematic diagram of the actual refrigeration system. A common refrigeration system may include a compressor, a condenser, a throttling device, an evaporator, etc. As an example, the existing one-dimensional refrigeration system simulation model can be used for simulation, so that the predicted coolant outlet water temperature can be obtained in combination with the thermal management strategy of the refrigeration system.

[0116] For details, please refer to Fig. 9 , Fig. 9 A schematic diagram of a device operation prediction principle according to an embodiment of the present disclosure is shown.

[0117] like Fig. 9 As shown, the predicted coolant outlet temperature can be obtained by combining the one-dimensional refrigeration system simulation model and the thermal management strategy of the refrigeration system. The predicted coolant outlet temperature here refers to the predicted inlet coolant temperature of each liquid-cooled battery pack. The thermal management strategy may include the temperature control method of the refrigeration system, for example, the activation sequence of the refrigeration system, the set temperature, etc. In addition, the total inlet coolant flow rate detected can be input into the reduced-order model of the cooling pipeline system to determine the inlet coolant flow value (for example, the inlet coolant flow rate) of each battery pack, and the corresponding reduced-order model of the liquid-cooled battery pack is determined based on the pre-obtained heat generation rate of the battery cell and the environmental boundary conditions (that is, the operating environment temperature of the battery cell). Then, the inlet coolant flow value of the battery pack and the predicted coolant outlet temperature (that is, the inlet coolant temperature) of the coolant pack are input into the reduced-order model of the corresponding liquid-cooled battery pack, and the temperature data of each battery pack can be obtained. The temperature data of each battery pack can be used to form the whole cabin temperature simulation data. The simulated temperature data can be input into the pre-established three-dimensional model of the whole cabin battery cell structure for temperature rendering, so as to obtain the whole cabin temperature cloud map.

[0118] The thermal management simulation method according to the embodiment of the present disclosure has a fast running speed and can perform real-time temperature monitoring of the operation of the energy storage system and future temperature prediction.

[0119] According to an embodiment of the present disclosure, a computer-readable storage medium stores a computer program or code. When the computer program or code is loaded and executed by a processor, the processor is prompted to execute the thermal management simulation method of the energy storage system.

[0120] According to an embodiment of the present disclosure, a computer device includes a memory and a processor, wherein the memory stores instructions or programs. When the instructions or programs are loaded and run by the processor, the processor is prompted to execute the thermal management simulation method of the energy storage system.

[0121] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process and related instructions of the storage device and processing device described above can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0122] The instructions stored in the computer-readable storage medium can be executed in an environment deployed in a computer device such as a client, a host, an agent device, a server, etc. It should be noted that the instructions can also be used to perform additional steps in addition to the above steps or perform more specific processing when performing the above steps. The contents of these additional steps and further processing have been described in detail in reference to Figures 1 to 9 It is mentioned in the description of the related method, so it will not be repeated here to avoid repetition.

[0123] It should be noted that the thermal management simulation method of the above-mentioned energy storage system according to the exemplary embodiment of the present disclosure can completely rely on the operation of computer programs or instructions to realize the corresponding functions, that is, each device corresponds to each step in the functional architecture of the computer program, so that the entire system is called through a special software package (for example, lib library) to realize the corresponding function.

[0124] On the other hand, when the systems, units or modules shown in the drawings are implemented in software, firmware, middleware or microcode, the program code or code segments for performing the corresponding operations can be stored in a computer-readable medium such as a storage medium, so that at least one processor or at least one computing device can perform the corresponding operations by reading and running the corresponding program code or code segments. In addition, the computer-readable medium or storage medium can cause the processor to execute the above-mentioned thermal management simulation method of the energy storage system when the computer program is executed by the processor.

[0125] Examples of computer-readable storage media here include: read-only memory (ROM), random-access programmable read-only memory (PROM), electrically erasable programmable read-only memory (EEPROM), random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), flash memory, non-volatile memory, etc.

[0126] The thermal management simulation method according to the embodiment of the present disclosure can accurately obtain the entire cabin temperature of the energy storage system.

[0127] The thermal management simulation method according to the embodiment of the present disclosure can perform rapid thermal management simulation on an energy storage system.

[0128] The thermal management simulation method according to the embodiment of the present disclosure can accurately simulate the heating condition of the battery cell, and the temperature simulation accuracy is high.

[0129] The thermal management simulation method according to the embodiment of the present disclosure has a fast running speed and can perform real-time temperature monitoring of the operation of the energy storage system and future temperature prediction.

[0130] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A thermal management simulation method for an energy storage system, characterized in that: The thermal management simulation method comprises: Obtain reduced-order models of all liquid-cooled battery packs in the energy storage system; Obtaining the heat generation rate of the battery cells in each of the liquid-cooled battery packs, the battery cell operating environment temperature, the inlet coolant flow rate of each liquid-cooled battery pack, and the inlet coolant temperature; The heat generation rate of the battery cell, the operating environment temperature of the battery cell, the inlet coolant flow rate and the inlet coolant temperature are input into the reduced-order model of the corresponding liquid-cooled battery pack to obtain a whole cabin temperature data set of the energy storage system. Among them, the reduced-order model of each liquid-cooled battery pack is used to characterize the relationship between the inlet coolant flow rate and the inlet coolant temperature of the corresponding liquid-cooled battery pack and the entire cabin temperature data under the heat generation rate of the battery cell and the operating environment temperature of the battery cell.

2. The thermal management simulation method of the energy storage system according to claim 1, characterized in that: The steps to obtain the reduced-order models of all liquid-cooled battery packs in the energy storage system include: For each of the liquid-cooled battery packs in the energy storage system, a three-dimensional simulation model of the corresponding liquid-cooled battery pack is established based on the layout of each of the liquid-cooled battery packs; Based on the thermal physical property parameters of the battery cells in each of the liquid-cooled battery packs, the heat generation rate of the battery cells and the boundary conditions of the liquid-cooled battery packs, the three-dimensional simulation model of the corresponding liquid-cooled battery pack is simulated to obtain a reduced-order model of each liquid-cooled battery pack in the energy storage system.

3. The thermal management simulation method of the energy storage system according to claim 2, characterized in that: Based on the cell thermophysical property parameters of the cells in each of the liquid-cooled battery packs, the cell heat generation rate, and the boundary conditions of the liquid-cooled battery pack, the three-dimensional simulation model of the corresponding liquid-cooled battery pack is simulated to obtain the reduced-order model of each liquid-cooled battery pack in the energy storage system, including: Using the battery cell thermophysical property parameters, the battery cell heat generation rate and the liquid-cooled battery pack boundary conditions, a three-dimensional thermal-fluid simulation is performed on the three-dimensional simulation model of the liquid-cooled battery pack to obtain a temperature data set of the liquid-cooled battery pack under different liquid-cooled battery pack boundary conditions; determining a reduced-order model of the liquid-cooled battery pack according to the temperature data set, Among them, the boundary conditions of the liquid-cooled battery pack include the inlet coolant temperature and the inlet coolant flow rate of the liquid-cooled battery pack.

4. The thermal management simulation method of the energy storage system according to claim 1, characterized in that: The thermal management simulation method further comprises: Establishing a three-dimensional model of the liquid cooling pipelines of the entire cabin according to the layout of the liquid cooling pipelines of the battery cabin of the energy storage system; Using different boundary conditions of the liquid cooling pipeline, the three-dimensional model of the whole cabin liquid cooling pipeline is subjected to three-dimensional fluid simulation of the liquid cooling pipeline of the whole cabin, so as to obtain the inlet coolant flow data of each liquid-cooled battery pack under different boundary conditions of the liquid cooling pipeline; The reduced-order model of the liquid cooling pipeline system is determined based on the inlet coolant flow data of each liquid-cooled battery pack under different liquid cooling pipeline boundary conditions. Among them, the liquid cooling pipeline boundary condition includes the total inlet coolant flow rate of the liquid cooling pipeline, and the inlet coolant flow data includes the inlet coolant flow rate of each liquid-cooled battery pack.

5. The thermal management simulation method of the energy storage system according to claim 4, characterized in that: The inlet coolant flow rate is determined by the detected total inlet coolant flow rate and the reduced-order model of the cooling pipe system.

6. The thermal management simulation method of the energy storage system according to claim 5, characterized in that: The inlet coolant temperature is obtained from the energy management system of the energy storage system, The thermal management simulation method further comprises: Obtaining temperature collection data of the entire cabin of the energy storage system; The temperature collection data and the whole cabin temperature data are used to render a predetermined three-dimensional model of the whole cabin battery cell structure to obtain a whole cabin temperature cloud map.

7. The thermal management simulation method of the energy storage system according to claim 5, characterized in that: The thermal management simulation method further comprises: Determining the error between the temperature acquisition data and the whole cabin temperature data; A warning signal is generated in response to the error exceeding a first threshold.

8. The thermal management simulation method of the energy storage system according to claim 5, characterized in that: The inlet coolant temperature is determined according to a refrigeration system thermal management strategy of the energy storage system and a predetermined one-dimensional refrigeration system simulation model.

9. The thermal management simulation method of the energy storage system according to claim 2, characterized in that: The thermal physical property parameters and heat generation rate of the battery cells of each liquid-cooled battery pack are obtained by the following steps: Obtaining thermophysical parameters, electrochemical parameters and charge-discharge cycle temperature rise curves of the battery cells in the liquid-cooled battery pack; Performing a three-dimensional thermal simulation on the battery cell using the thermal physical property parameters to obtain temperature data of the battery cell; Performing a one-dimensional electrochemical simulation on the battery cell using the electrochemical parameters to obtain a heat generation rate of the battery cell; Performing electrochemical-thermal coupling joint simulation on the battery cell by using the temperature data of the battery cell and the heat generation rate of the battery cell to obtain a temperature simulation curve of the battery cell; Adjusting the thermophysical property parameters and the electrochemical parameters so that the error between the temperature simulation curve obtained by electrochemical-thermal coupling joint simulation and the charge-discharge cycle temperature rise curve is less than a second threshold; The thermophysical parameters and the heat generation rate corresponding to the adjusted final thermophysical parameters and the final electrochemical parameters are determined as the battery cell thermophysical parameters and the battery cell heat generation rate.

10. A computer device, characterized in that: The computer device includes a memory and a processor, wherein the memory stores instructions or programs, and when the instructions or programs are loaded and run by the processor, the processor is prompted to execute the thermal management simulation method for the energy storage system according to any one of claims 1 to 9.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program or instruction, which, when loaded and executed by a processor, prompts the processor to execute the thermal management simulation method for an energy storage system according to any one of claims 1 to 9.

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