A battery cooling demand simulation method, device, equipment and storage medium

Abstract

The application provides a battery cooling demand simulation method and device, equipment and a storage medium, wherein an original battery system model of a battery system is acquired; a capacity parameter in the original battery system model is adjusted to obtain an optimized battery system model; simulation calculation is performed on the optimized battery system model to obtain battery characteristic data of the battery system; a battery fast charging model is constructed based on the battery characteristic data; battery heat generation of the battery system is determined based on the battery fast charging model; and cooling demand power of the battery system is simulated based on the battery heat generation of the battery system. The above method is adopted to ensure the pertinence and effectiveness of the obtained battery system cooling standard, and to improve the effect after the battery system cooling processing based on the obtained battery cooling demand.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and more specifically, to a method, apparatus, device, and storage medium for simulating battery cooling requirements. Background Technology

[0002] A battery is an energy storage and conversion device, its primary function being to provide electrical energy. It is widely used in various electronic devices, such as mobile phones, computers, flashlights, and remote controls, providing the necessary power for these devices to function properly. From household appliances to vehicles, from industrial equipment to medical devices, everything relies on the power of batteries.

[0003] However, batteries in a battery system generate heat during operation. If this heat cannot be effectively dissipated and the battery system cannot be cooled in time, it may lead to a decline in battery performance, a shortened lifespan, or even safety issues. To address these problems, existing technologies typically employ a uniform cooling standard for battery systems, meaning that all types of battery systems are cooled with the same power requirement.

[0004] However, the study found that due to the different characteristics of various battery systems, if a uniform cooling standard is used to cool various battery systems, the cooling effect of some battery systems may be poor, causing these batteries to still have quality and safety problems such as performance degradation and shortened lifespan. It is difficult to achieve the specificity and effectiveness of the battery system cooling standard, and it is also impossible to guarantee the effect of the battery system cooling treatment. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide a method, apparatus, device and storage medium for simulating battery cooling requirements, so as to improve the pertinence and effectiveness of the obtained battery system cooling standards, and at the same time improve the effect of battery system cooling treatment based on the obtained battery cooling requirements.

[0006] In a first aspect, embodiments of this application provide a method for simulating battery cooling demand, the method comprising:

[0007] Obtain the original battery system model;

[0008] An optimized battery system model is obtained by adjusting the capacity parameters in the original battery system model.

[0009] The battery characteristic data of the battery system are obtained by performing simulation calculations on the optimized battery system model;

[0010] A fast-charging model for the battery is constructed based on the battery characteristic data;

[0011] The battery heat generation of the battery system is determined based on the battery fast charging model.

[0012] The cooling power requirement of the battery system is simulated and calculated based on the heat generated by the battery.

[0013] Optionally, adjusting the capacity parameters in the original battery system model to obtain an optimized battery system model includes:

[0014] The optimized battery system model is obtained by increasing or decreasing the rated capacity of the battery system in the original battery system model using simulation software.

[0015] Optionally, the step of performing simulation calculations on the optimized battery system model to obtain the battery characteristic data of the battery system includes:

[0016] The optimized battery system model is simulated and calculated using simulation software to confirm the battery characteristic data of the battery system under different operating conditions. The battery characteristic data includes battery temperature and remaining battery capacity.

[0017] Optionally, the battery fast charging model includes a charging model, a battery model, and a heat transfer model; the charging model is used to input the battery charging power of the battery system into the battery model; the battery model is used to calculate the remaining battery capacity and battery heat generation of the battery system at each moment based on the battery charging power; the heat transfer model is used to calculate the battery temperature based on the remaining battery capacity and battery heat generation.

[0018] Optionally, determining the battery heat generation of the battery system based on the battery fast charging model includes:

[0019] The battery charging power of the battery system is obtained through the charging model.

[0020] The battery charging power of the battery system is input into the battery model to obtain the battery heat generation of the battery system.

[0021] Optionally, the simulation calculation of the cooling power requirement of the battery system based on the battery heat generation of the battery system includes:

[0022] Determine the target fast charging time that the battery system needs to achieve;

[0023] The required cooling power for the battery system is determined based on the battery heat generation of the battery system and the target fast charging time.

[0024] Optionally, the method further includes:

[0025] Develop optimization algorithms;

[0026] Based on the optimization algorithm, the minimum charging power required by the battery system under the target fast charging time is determined;

[0027] Based on the optimized battery system model, the system is verified to meet the target fast charging time when fast charging at the lowest charging power.

[0028] Secondly, embodiments of this application provide a battery cooling demand simulation device, the device comprising:

[0029] The battery system model acquisition module is used to acquire the original battery system model.

[0030] The capacity parameter adjustment module is used to adjust the capacity parameters in the original battery system model to obtain an optimized battery system model.

[0031] The first simulation calculation module is used to perform simulation calculations on the optimized battery system model to obtain battery characteristic data of the battery system.

[0032] A battery fast charging model construction module is used to construct a battery fast charging model based on the battery characteristic data.

[0033] A battery heat generation calculation module is used to determine the battery heat generation of the battery system based on the battery fast charging model.

[0034] The second simulation calculation module is used to simulate and calculate the cooling power requirement of the battery system based on the battery heat generation of the battery system.

[0035] Optionally, adjusting the capacity parameters in the original battery system model to obtain an optimized battery system model includes:

[0036] The optimized battery system model is obtained by increasing or decreasing the rated capacity of the battery system in the original battery system model using simulation software.

[0037] Optionally, the step of performing simulation calculations on the optimized battery system model to obtain the battery characteristic data of the battery system includes:

[0038] The optimized battery system model is simulated and calculated using simulation software to confirm the battery characteristic data of the battery system under different operating conditions. The battery characteristic data includes battery temperature and remaining battery capacity.

[0039] Optionally, the battery fast charging model includes a charging model, a battery model, and a heat transfer model; the charging model is used to input the battery charging power of the battery system into the battery model; the battery model is used to calculate the remaining battery capacity and battery heat generation of the battery system at each moment based on the battery charging power; the heat transfer model is used to calculate the battery temperature based on the remaining battery capacity and battery heat generation.

[0040] Optionally, determining the battery heat generation of the battery system based on the battery fast charging model includes:

[0041] The battery charging power of the battery system is obtained through the charging model.

[0042] The battery charging power of the battery system is input into the battery model to obtain the battery heat generation of the battery system.

[0043] Optionally, the simulation calculation of the cooling power requirement of the battery system based on the battery heat generation of the battery system includes:

[0044] Determine the target fast charging time that the battery system needs to achieve;

[0045] The required cooling power for the battery system is determined based on the battery heat generation of the battery system and the target fast charging time.

[0046] Optionally, the device further includes:

[0047] The algorithm model building module is used to build optimization algorithms;

[0048] The minimum charging power determination module is used to determine the minimum charging power required by the battery system under the target fast charging time based on the optimization algorithm.

[0049] The simulation verification module is used to verify whether the battery system meets the target fast charging time when fast charging at the lowest charging power, based on the optimized battery system model.

[0050] Thirdly, embodiments of this application provide an electronic device, including: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, the steps of the battery cooling demand simulation method described in any of the optional embodiments of the first aspect are performed.

[0051] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the battery cooling demand simulation method described in any of the optional embodiments of the first aspect.

[0052] The technical solution provided in this application includes, but is not limited to, the following beneficial effects:

[0053] This application effectively simulates the heat generation and dissipation of a battery during operation, thereby supporting the design and optimization of the battery thermal management system. Specifically, simulation can accurately calculate the cooling power required by the cooling system for the battery, supporting the detailed design of the cooling system. Furthermore, simulation can model the temperature distribution of the battery system under different operating conditions, including various charging and discharging processes, which helps predict battery heat generation and guides the design and optimization of the cooling system. In addition, simulation can help evaluate the impact of different battery thermal management strategies on battery temperature, including adjustments to parameters such as charging rate, discharging rate, and operating temperature, contributing to the design of more effective battery thermal management systems, extending battery life, and improving performance. Moreover, simulation allows for the evaluation and verification of different design schemes before actual manufacturing, avoiding potential problems during actual manufacturing and saving costs and time. Finally, simulation enables in-depth analysis of the thermodynamic behavior of the battery system, helping to identify potential safety hazards and take corresponding measures to improve the safety and reliability of the battery system.

[0054] The above method involves obtaining the original battery system model; adjusting the capacity parameters in the original battery system model to obtain an optimized battery system model; performing simulation calculations on the optimized battery system model to obtain battery characteristic data; constructing a fast-charging model based on the battery characteristic data; determining the battery heat generation of the battery system based on the fast-charging model; and simulating the cooling power requirement of the battery system based on the battery heat generation. This improves the relevance and effectiveness of the obtained battery system cooling standards, enhances the cooling effect of the battery system after cooling based on the obtained cooling requirements, further helps solve the design and optimization problems of the cooling system, and improves the performance, safety, and reliability of the battery system.

[0055] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0056] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0057] Figure 1 A flowchart of a battery cooling demand simulation method provided in Embodiment 1 of the present invention is shown;

[0058] Figure 2 A schematic diagram of a battery body heat transfer model provided in Embodiment 1 of the present invention is shown.

[0059] Figure 3 This diagram shows a structural schematic of a battery fast charging model provided in Embodiment 1 of the present invention;

[0060] Figure 4 A flowchart of a method for determining cooling power demand provided in Embodiment 1 of the present invention is shown;

[0061] Figure 5 A flowchart of a simulation verification method provided in Embodiment 1 of the present invention is shown;

[0062] Figure 6 This shows a schematic diagram of the structure of a PI control adjustment model provided in Embodiment 1 of the present invention;

[0063] Figure 7 This diagram illustrates the structure of a charging stop strategy model provided in Embodiment 1 of the present invention.

[0064] Figure 8 This diagram illustrates the structure of a battery cooling demand simulation device provided in Embodiment 2 of the present invention.

[0065] Figure 9 A schematic diagram of the structure of an electronic device provided in Embodiment 3 of the present invention is shown. Detailed Implementation

[0066] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0067] Example 1

[0068] To facilitate understanding of this application, the following is combined with... Figure 1 The flowchart of the battery cooling demand simulation method provided in Embodiment 1 of the present invention illustrates the content of Embodiment 1 in detail.

[0069] See Figure 1 As shown, Figure 1 The flowchart of a battery cooling demand simulation method provided in Embodiment 1 of the present invention is shown, wherein the method includes steps S101 to S106:

[0070] S101: Obtain the original battery system model.

[0071] Specifically, the original battery model and its parameters are first obtained from a database or third-party system. The parameters include capacity, internal resistance, and open-circuit voltage (OCV).

[0072] S102: Adjust the capacity parameters in the original battery system model to obtain an optimized battery system model.

[0073] Specifically, based on the available capacity of the battery system, the capacity parameters in the original battery system model are adjusted to the available capacity of the battery system to obtain an optimized battery system model.

[0074] S103: Perform simulation calculations on the optimized battery system model to obtain the battery characteristic data of the battery system.

[0075] Specifically, after adjusting the capacity parameters, simulation software is run to perform simulation calculations. Based on the new capacity parameters, battery characteristic data such as temperature, state of charge (SOC), charging power, capacity, internal resistance, and open-circuit volt-volt (OCV) are calculated under different operating conditions. The simulation results are analyzed to determine whether the battery system meets the requirements.

[0076] S104: Construct a battery fast charging model based on the battery characteristic data.

[0077] Specifically, a fast-charging model is established based on the acquired battery characteristic data. This fast-charging model is either a dynamic model of the battery charging process or a description of how the battery's charging rate changes over time.

[0078] S105: Determine the battery heat generation of the battery system based on the battery fast charging model.

[0079] Specifically, calculating the power required for battery cooling involves considering the heat generation and transfer process of the battery, as well as the heat absorption and dissipation capacity of the cooling system. Therefore, the heat generated by the battery during operation is calculated using a battery fast charging model.

[0080] S106: Simulate and calculate the cooling power requirement of the battery system based on the battery heat generation of the battery system.

[0081] Specifically, based on the heat generated by the battery system, the cooling heat transfer capacity of the battery system is evaluated according to the battery body heat transfer model, that is, the amount of heat that the cooling system can absorb and dissipate. See also Figure 2 As shown, Figure 2 A schematic diagram of a battery body heat transfer model provided in Embodiment 1 of the present invention is shown. The battery body heat transfer model 1 includes Ct as the battery mass block 2, Φ as the battery heat source input port 3, and cooling power input values ​​are input to the battery body heat transfer model through the design parameters of the cooling system to cool the battery in the battery system. The influence of different cooling powers on the battery fast charging time under the same environmental heat exchange is calculated to determine the required cooling power. The cooling power requirement algorithm in the simulation software is a built-in existing algorithm, where k is the proportional coefficient, T is the battery temperature, S is the state of charge, I is the current value, and P is the proportional control.

[0082] After simulating and calculating the cooling power requirement of the battery system based on the battery heat generation, the cooling system in the battery system can be controlled to cool the battery according to the calculated cooling power requirement.

[0083] In an optional implementation, adjusting the capacity parameters in the original battery system model to obtain an optimized battery system model includes:

[0084] The optimized battery system model is obtained by increasing or decreasing the rated capacity of the battery system in the original battery system model using simulation software.

[0085] Specifically, adjusting the battery model capacity is a crucial operation in the initial stages of battery cooling demand simulation. By changing the capacity parameters in the original battery system model, different battery capacities can be simulated to obtain an optimized battery system model. Battery capacity is typically measured in ampere-hours (Ah). The rated capacity of the battery can be increased or decreased to simulate different battery capacities. Capacity parameters can be directly modified in the battery model within the simulation software.

[0086] In an optional implementation, the step of performing simulation calculations on the optimized battery system model to obtain the battery characteristic data of the battery system includes:

[0087] The optimized battery system model is simulated and calculated using simulation software to confirm the battery characteristic data of the battery system under different operating conditions. The battery characteristic data includes battery temperature and remaining battery capacity.

[0088] Specifically, the simulation calculation algorithm in the simulation software is a built-in existing algorithm. When it is necessary to determine the battery characteristic data, the simulation algorithm in the simulation software used to perform simulation calculations on the optimized battery system model to obtain the battery characteristic data of the battery system under different operating conditions is selected.

[0089] In an optional implementation, the battery fast charging model includes a charging model, a battery model, and a heat transfer model; the charging model is used to input the battery charging power of the battery system into the battery model; the battery model is used to calculate the remaining battery capacity and battery heat generation of the battery system at each moment based on the battery charging power; and the heat transfer model is used to calculate the battery temperature based on the remaining battery capacity and battery heat generation.

[0090] For details, see Figure 3 As shown, Figure 3 The diagram illustrates a structural schematic of a battery fast-charging model provided in Embodiment 1 of the present invention. The battery fast-charging model includes a charging model 4, a battery model 5, and a heat transfer model 6. The charging model inputs the battery charging power to the battery model. The battery model calculates the SOC and heat generation of the battery at each moment and outputs them to the heat transfer model. The heat transfer model calculates the battery temperature. In the diagram, S represents SOC, T represents battery temperature, EV refers to the charging station, and BAT refers to the battery.

[0091] In an optional implementation, see Figure 4 As shown, Figure 4 The flowchart of a method for determining cooling power demand provided in Embodiment 1 of the present invention is shown, wherein the step of simulating and calculating the cooling power demand of the battery system based on the battery heat generation of the battery system includes steps S401 to S402:

[0092] S401: Determine the target fast charging time that the battery system needs to achieve.

[0093] Specifically, the target fast charging time that the battery system needs to achieve is determined based on application requirements, market research, or technical standards, usually in minutes.

[0094] S402: Determine the required cooling power of the battery system based on the battery heat generation of the battery system and the target fast charging time.

[0095] Specifically, a battery heat transfer model is prepared in advance. The battery heat generation and target fast charging time of the battery system are input into the battery heat transfer model to determine the cooling power required for the battery system to meet the target fast charging time under the same environmental heat exchange conditions.

[0096] In an optional implementation, see Figure 5 As shown, Figure 5 The flowchart of a simulation verification method provided in Embodiment 1 of the present invention is shown, wherein the method further includes S301 to S303:

[0097] S501: Construct an optimization algorithm.

[0098] S502: Based on the optimization algorithm, determine the minimum charging power required by the battery system at the target fast charging time.

[0099] S503: Verify whether the target fast charging time is met when the battery system is fast charged at the lowest charging power based on the optimized battery system model.

[0100] Specifically, an optimization algorithm is developed to determine the minimum charging power required for a given target fast charging time. Numerical optimization methods are used to perform PI control adjustment based on battery temperature, SOC, and real-time voltage using a PI control adjustment model. See [link to relevant documentation]. Figure 6 As shown, Figure 6 The diagram shows a schematic of a PI control adjustment model provided in Embodiment 1 of the present invention. In the diagram, SOC represents the state of charge, PI represents PI control (i.e., proportional-integral control), Max votage represents the maximum voltage, Ubet represents the current cell voltage, x represents the target fast charging time, and f(x) represents the minimum charging power required for the target fast charging time. The adjustment formula for the PI control adjustment model when performing PI control is as follows:

[0101] P=0.5*c_ele*(umax-umin)*n_ele;

[0102] I=0.5*c_ele*(umax-umin)*n_ele / 10;

[0103] Where P is the P adjustment coefficient of PI control, I is the I adjustment coefficient of PI control, umax is the maximum cell voltage limit, umin is the minimum cell voltage limit, n_ele is the number of batteries connected in series in the whole pack, and c_ele is the battery capacity.

[0104] To analyze the impact of battery charging power on charging time, the maximum value of the PI control is limited to varying degrees to determine the minimum charging power required to meet fast charging targets. The charging power is then converted into charging current using the following formula:

[0105] Imax=max_charge_power_station / n_voltage;

[0106] Where Imax is the output current value, max_charge_power_station is the charging power, and n_voltage is the battery voltage.

[0107] The output power is converted into output current according to the above formula, and the current value is output to the (2) battery model for fast charging process simulation.

[0108] Simultaneously, constraints are set in the optimization algorithm to ensure that the obtained minimum charging power can meet the target fast charging time and does not exceed the battery's safety and performance requirements. Then, the minimum charging power obtained by the optimization algorithm is verified in the optimized battery system model to confirm whether it meets the target fast charging time and complies with the battery's safety and performance requirements.

[0109] Setting appropriate stopping conditions is crucial during simulation to ensure convergence to results within a reasonable timeframe and to avoid infinite loops or overcomputation. The stopping conditions should be set based on the specific simulation problem and the algorithm used. In this application, stopping conditions are triggered by a preset target value and simulation runtime, according to the charging stopping strategy model. See [link to relevant documentation]. Figure 7 As shown, Figure 7 A schematic diagram of a charging stop strategy model provided in Embodiment 1 of the present invention is shown, wherein the target fast charging SOC or the maximum time limit is used as the simulation stop condition f(x), and x is a variable in the stop condition, as explained in detail below. (1) Preset target value: The simulation stops when the preset target is reached. For example, the battery stops charging when the battery SOC reaches the set target fast charging SOC. (2) Preset simulation running time: The maximum time limit for simulation running is set. If the simulation running time exceeds the set time threshold, the simulation stops, even if the convergence condition or the target fast charging SOC has not been reached.

[0110] Example 2

[0111] See Figure 8 As shown, Figure 8 This diagram illustrates the structure of a battery cooling demand simulation device according to Embodiment 2 of the present invention, wherein the device includes:

[0112] Battery system model acquisition module 801 is used to acquire the original battery system model of the battery system;

[0113] The capacity parameter adjustment module 802 is used to adjust the capacity parameters in the original battery system model to obtain an optimized battery system model;

[0114] The first simulation calculation module 803 is used to perform simulation calculations on the optimized battery system model to obtain battery characteristic data of the battery system.

[0115] Battery fast charging model construction module 804 is used to construct a battery fast charging model based on the battery characteristic data;

[0116] The battery heat generation calculation module 805 is used to determine the battery heat generation of the battery system based on the battery fast charging model.

[0117] The second simulation calculation module 806 is used to simulate and calculate the cooling power requirement of the battery system based on the battery heat generated by the battery system.

[0118] In an optional implementation, adjusting the capacity parameters in the original battery system model to obtain an optimized battery system model includes:

[0119] The optimized battery system model is obtained by increasing or decreasing the rated capacity of the battery system in the original battery system model using simulation software.

[0120] In an optional implementation, the step of performing simulation calculations on the optimized battery system model to obtain the battery characteristic data of the battery system includes:

[0121] The optimized battery system model is simulated and calculated using simulation software to confirm the battery characteristic data of the battery system under different operating conditions. The battery characteristic data includes battery temperature and remaining battery capacity.

[0122] In an optional implementation, the battery fast charging model includes a charging model, a battery model, and a heat transfer model; the charging model is used to input the battery charging power of the battery system into the battery model; the battery model is used to calculate the remaining battery capacity and battery heat generation of the battery system at each moment based on the battery charging power; and the heat transfer model is used to calculate the battery temperature based on the remaining battery capacity and battery heat generation.

[0123] In an optional implementation, determining the battery heat generation of the battery system based on the battery fast charging model includes:

[0124] The battery charging power of the battery system is obtained through the charging model.

[0125] The battery charging power of the battery system is input into the battery model to obtain the battery heat generation of the battery system.

[0126] In an optional implementation, the simulation calculation of the cooling power requirement of the battery system based on the battery heat generation of the battery system includes:

[0127] Determine the target fast charging time that the battery system needs to achieve;

[0128] The required cooling power for the battery system is determined based on the battery heat generation of the battery system and the target fast charging time.

[0129] In an optional implementation, the device further includes:

[0130] The algorithm model building module is used to build optimization algorithms;

[0131] The minimum charging power determination module is used to determine the minimum charging power required by the battery system under the target fast charging time based on the optimization algorithm.

[0132] The simulation verification module is used to verify whether the battery system meets the target fast charging time when fast charging at the lowest charging power, based on the optimized battery system model.

[0133] Example 3

[0134] Based on the same application concept, see [link / reference] Figure 9 As shown, Figure 9 The diagram illustrates the structure of an electronic device 900 according to Embodiment 3 of the present invention. The electronic device 900 includes: at least one processor 901, at least one network interface 904 or other user interface 903, a memory 905, and at least one communication bus 902. The communication bus 902 is used to enable communication between these components. The electronic device 900 may optionally include a user interface 903, including a display (e.g., touchscreen, LCD, CRT, holographic imaging, or projector), a keyboard, or a clicking device (e.g., mouse, trackball, touchpad, or touchscreen).

[0135] Memory 905 may include read-only memory and random access memory, and provides instructions and data to processor 901. A portion of memory 905 may also include non-volatile random access memory (NVRAM).

[0136] In some implementations, memory 905 stores executable modules or data structures, or subsets thereof, or extended sets thereof:

[0137] The 9051 operating system contains various system programs used to implement various basic business functions and handle hardware-based tasks.

[0138] Application module 9052 contains various applications, such as desktop launcher, media player, and browser, to implement various application functions.

[0139] In this embodiment, by calling the program or instructions stored in the memory 905, the processor 901 executes steps such as in a battery cooling demand simulation method, which can ensure the relevance and effectiveness of the obtained battery system cooling standard, and at the same time improve the effect of battery system cooling treatment based on the obtained battery cooling demand.

[0140] Example 4

[0141] Based on the same concept, this application also provides a computer-readable storage medium storing a computer program, which, when run by a processor, executes the steps of the battery cooling demand simulation method described in any of the above embodiments.

[0142] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system and apparatus described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0143] The computer program product for simulating battery cooling requirements provided in this embodiment of the invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the preceding method embodiments. For specific implementation details, please refer to the method embodiments, which will not be repeated here.

[0144] The battery cooling demand simulation device provided in this embodiment of the invention can be specific hardware on a device or software or firmware installed on the device. The implementation principle and technical effects of the device provided in this embodiment of the invention are the same as those in the foregoing method embodiments. For the sake of brevity, any parts not mentioned in the device embodiments can be referred to the corresponding content in the foregoing method embodiments. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can all be referred to the corresponding processes in the above method embodiments, and will not be repeated here.

[0145] In the embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0146] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0147] In addition, the functional units in the embodiments provided by the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0148] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, 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 an electronic 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 (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0149] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In addition, the terms "first", "second", "third", etc. are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0150] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the scope of the technology disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention. All should be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for simulating battery cooling demand, characterized in that, The method includes: Obtain the original battery system model; An optimized battery system model is obtained by adjusting the capacity parameters in the original battery system model. The battery characteristic data of the battery system are obtained by performing simulation calculations on the optimized battery system model; A fast-charging model for the battery is constructed based on the battery characteristic data; The battery heat generation of the battery system is determined based on the battery fast charging model. The cooling power requirement of the battery system is simulated and calculated based on the heat generated by the battery system. The process of adjusting the capacity parameters in the original battery system model to obtain an optimized battery system model includes: The optimized battery system model is obtained by increasing or decreasing the rated capacity of the battery system in the original battery system model using simulation software. The simulation calculation of the cooling power requirement of the battery system based on the battery heat generation includes: Determine the target fast charging time that the battery system needs to achieve; The required cooling power for the battery system is determined based on the battery heat generation of the battery system and the target fast charging time.

2. The method according to claim 1, characterized in that, The process of simulating the optimized battery system model to obtain battery characteristic data of the battery system includes: The optimized battery system model is simulated and calculated using simulation software to confirm the battery characteristic data of the battery system under different operating conditions. The battery characteristic data includes battery temperature and remaining battery capacity.

3. The method according to claim 1, characterized in that, The battery fast charging model includes a charging model, a battery model, and a heat transfer model; the charging model is used to input the battery charging power of the battery system into the battery model; the battery model is used to calculate the remaining battery capacity and battery heat generation of the battery system at each moment based on the battery charging power. The heat transfer model is used to calculate the battery temperature based on the remaining battery capacity and the heat generated by the battery.

4. The method according to claim 3, characterized in that, The determination of battery heat generation of the battery system based on the battery fast charging model includes: The battery charging power of the battery system is obtained through the charging model. The battery charging power of the battery system is input into the battery model to obtain the battery heat generation of the battery system.

5. The method according to claim 1, characterized in that, The method further includes: Develop optimization algorithms; Based on the optimization algorithm, the minimum charging power required by the battery system under the target fast charging time is determined; Based on the optimized battery system model, the system is verified to meet the target fast charging time when fast charging at the lowest charging power.

6. A battery cooling demand simulation device, characterized in that, The device includes: The battery system model acquisition module is used to acquire the original battery system model. The capacity parameter adjustment module is used to adjust the capacity parameters in the original battery system model to obtain an optimized battery system model. The first simulation calculation module is used to perform simulation calculations on the optimized battery system model to obtain battery characteristic data of the battery system. A battery fast charging model construction module is used to construct a battery fast charging model based on the battery characteristic data. A battery heat generation calculation module is used to determine the battery heat generation of the battery system based on the battery fast charging model. The second simulation calculation module is used to simulate and calculate the cooling power requirement of the battery system based on the battery heat generation of the battery system. The process of adjusting the capacity parameters in the original battery system model to obtain an optimized battery system model includes: The optimized battery system model is obtained by increasing or decreasing the rated capacity of the battery system in the original battery system model using simulation software. The simulation calculation of the cooling power requirement of the battery system based on the battery heat generation includes: Determine the target fast charging time that the battery system needs to achieve; The required cooling power for the battery system is determined based on the battery heat generation of the battery system and the target fast charging time.

7. An electronic device, characterized in that, include: The device includes a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, they perform the steps of the battery cooling demand simulation method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the battery cooling demand simulation method as described in any one of claims 1 to 5.

Images