Power battery thermal management methods, devices, computer equipment and storage media

Abstract

This application relates to a method, apparatus, computer device, storage medium, and computer program product for power battery thermal management. The method includes: acquiring historical vehicle operating data, real-time vehicle battery status data, and real-time vehicle operating data; determining the thermal management start-stop flag power based on the historical vehicle operating data; determining the power battery's discharge capacity based on the real-time vehicle battery status data; determining the vehicle's required power based on the real-time vehicle operating data; and determining whether to activate thermal management based on the thermal management start-stop flag power, the power battery's discharge capacity, and the vehicle's required power. This method can adjust in real time according to the driver's usage needs and actual driving requirements, improving the flexibility and practicality of power battery thermal management.

Description

Technical Field

[0001] This application relates to the field of battery technology, and in particular to a method, apparatus, computer equipment, and storage medium for thermal management of a power battery. Background Technology

[0002] With the development of battery technology, the temperature control of power battery packs has become crucial. Excessively high or low temperatures can affect battery life and performance, and even threaten battery safety. This has led to the development of power battery thermal management technology. Power battery thermal management refers to the temperature control of electric vehicle power battery packs to maintain them within a suitable temperature range, ensuring high performance and lifespan, thereby increasing range and power output.

[0003] In existing technologies, temperature is typically chosen as the condition for thermal management to start and stop. When the temperature meets the thermal management activation standard, thermal management is activated to heat or cool the power battery; when the temperature does not meet the standard, thermal management is not activated and no operation is performed. However, this method of controlling the start and stop of thermal management is too simplistic and does not consider the actual usage conditions of the vehicle. For example, in cold winters, due to shorter vehicle trips and a fixed thermal management standard setting that is too high, thermal management may be activated after assessment to heat the power battery. However, the trip may end before the power battery temperature reaches the target thermal management temperature, resulting in the power battery being in a heated state for the entire trip. This not only fails to achieve the expected benefits but also consumes a large amount of energy during the heating process, causing unnecessary energy loss. In addition, a uniform thermal management start and stop standard cannot meet the driving needs of all drivers, thus reducing the driver's experience.

[0004] Therefore, there is an urgent need in related technologies to improve the flexibility and practicality of thermal management of power batteries. Summary of the Invention

[0005] Therefore, it is necessary to provide a power battery thermal management method, device, computer equipment, and computer-readable storage medium that can improve the flexibility and practicality of power battery thermal management in response to the above-mentioned technical problems.

[0006] Firstly, this application provides a thermal management method for a power battery. The method includes:

[0007] Acquire historical vehicle operating data, real-time vehicle battery status data, and real-time vehicle operating data;

[0008] The power of the thermal management start-stop indicator is determined based on the vehicle's historical operating data.

[0009] The discharge power of the power battery is determined based on the real-time status data of the vehicle battery.

[0010] The required power of the vehicle is determined based on the real-time operating data of the vehicle.

[0011] Whether to activate thermal management is determined based on the thermal management start / stop indicator power, the discharge power of the power battery, and the vehicle's required power.

[0012] Optionally, in one embodiment of this application, determining the thermal management start-stop flag power based on the vehicle's historical operating data includes:

[0013] Based on the vehicle's historical operating data, the vehicle's historical power demand is determined, and based on the vehicle's historical power demand, the thermal management start-stop flag power is determined.

[0014] Optionally, in one embodiment of this application, determining the vehicle's historical power demand based on the vehicle's historical operating data includes:

[0015] The vehicle's historical operating data is divided into preset periods, and clustering and feature extraction are performed to determine the vehicle's historical power demand.

[0016] Optionally, in one embodiment of this application, the real-time status data of the vehicle battery includes at least battery temperature and battery state of charge, and determining the discharge power of the power battery based on the real-time status data of the vehicle battery includes:

[0017] The discharge power of the power battery is determined based on battery temperature, battery state of charge, and a preset mapping relationship, wherein the preset mapping relationship includes the correlation between battery temperature, battery state of charge, and discharge power of the power battery.

[0018] Optionally, in one embodiment of this application, determining the vehicle's required power based on the vehicle's real-time operating data includes:

[0019] The real-time vehicle operation data is input into the trained vehicle demand power prediction model to obtain the vehicle demand power. The vehicle demand power prediction model is trained based on the vehicle's historical operation data and the vehicle's historical demand power. The vehicle's historical operation data includes at least historical vehicle speed, historical pedal opening, and historical battery temperature.

[0020] Optionally, in one embodiment of this application, determining whether to activate thermal management based on the thermal management start-stop flag power, the discharge power of the power battery, and the vehicle's required power includes:

[0021] If the discharge power of the power battery is less than the power of the thermal management start / stop flag, then thermal management is activated.

[0022] Optionally, in one embodiment of this application, determining whether to activate thermal management based on the thermal management start-stop flag power, the discharge power of the power battery, and the vehicle's required power further includes:

[0023] If the discharge power of the power battery is less than the power required by the vehicle, then thermal management is activated.

[0024] Secondly, this application also provides a power battery thermal management device. The device includes:

[0025] The data acquisition module is used to acquire historical vehicle operating data, real-time vehicle battery status data, and real-time vehicle operating data.

[0026] The thermal management start-stop flag power determination module is used to determine the thermal management start-stop flag power based on the vehicle's historical operating data.

[0027] A power battery discharge power determination module is used to determine the power battery discharge power based on the real-time status data of the vehicle battery.

[0028] The vehicle power demand determination module is used to determine the vehicle power demand based on the vehicle's real-time operating data.

[0029] The thermal management activation determination module is used to determine whether to activate thermal management based on the thermal management start / stop flag power, the discharge power of the power battery, and the vehicle's required power.

[0030] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the steps of the methods described in the various embodiments above.

[0031] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps of the methods described in the various embodiments above.

[0032] The aforementioned power battery thermal management method, device, computer equipment, and storage medium first acquire historical vehicle operating data, real-time vehicle battery status data, and real-time vehicle operating data. Then, based on the historical vehicle operating data, they determine the thermal management start-stop indicator power; based on the real-time vehicle battery status data, they determine the power battery's dischargeable power; and based on the real-time vehicle operating data, they determine the vehicle's required power. Finally, based on the thermal management start-stop indicator power, the power battery's dischargeable power, and the vehicle's required power, they determine whether to activate thermal management. In other words, by understanding the driver's recent driving data and determining a more reasonable thermal management start-stop indicator power, and by monitoring the vehicle's power battery's dischargeable power in real time during vehicle operation, predicting future power requirements for the current journey, and comprehensively comparing these factors, they determine whether thermal management needs to be activated in the current vehicle state. This allows for real-time adjustments based on the driver's usage and actual driving needs, improving the flexibility and practicality of power battery thermal management. Attached Figure Description

[0033] Figure 1 This is an application environment diagram of a power battery thermal management method in one embodiment;

[0034] Figure 2 This is a flowchart illustrating a power battery thermal management method in one embodiment;

[0035] Figure 3 This is a schematic diagram illustrating the specific steps of a power battery thermal management method in one embodiment.

[0036] Figure 4 This is a structural block diagram of a power battery thermal management device in one embodiment;

[0037] Figure 5 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0039] The power battery thermal management method provided in this application embodiment can be applied to, for example, Figure 1In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or located in the cloud or on other network servers. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. Portable wearable devices can include smartwatches, smart bracelets, head-mounted devices, etc. Server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0040] For an electric vehicle, temperature control of its battery pack is crucial during daily operation, as both excessively high and low temperatures can negatively impact battery life and performance, and even threaten battery safety. High temperatures reduce battery capacity, shorten lifespan, and accelerate internal chemical reactions, leading to premature aging and failure. Conversely, low temperatures reduce the rate of internal chemical reactions, weakening the battery's discharge capacity and affecting the electric vehicle's driving range. Therefore, power battery thermal management plays a vital role in the performance, safety, and lifespan of an electric vehicle.

[0041] In one embodiment, such as Figure 2 As shown, a power battery thermal management method is provided, which can be applied to... Figure 1 Taking the server in the example, the following steps are included:

[0042] S201: Obtain historical vehicle operation data, real-time vehicle battery status data, and real-time vehicle operation data.

[0043] In this embodiment, firstly, historical vehicle operation data stored in the cloud is acquired, i.e., operation data during vehicle use over a recent period, such as vehicle speed, pedal opening, and motor speed. Secondly, real-time vehicle battery status data stored in the cloud is acquired, such as battery capacity, available battery power, battery temperature, and battery state of charge (SOC), where SOC refers to the ratio of remaining battery capacity to total battery capacity, usually expressed as a percentage. Thirdly, real-time vehicle operation data is acquired, such as current vehicle speed, current pedal opening, and current motor speed.

[0044] S203: Determine the thermal management start-stop flag power based on the vehicle's historical operating data.

[0045] In this embodiment, the power of the thermal management start-stop indicator is determined based on the vehicle's historical operating data. The operating data of the vehicle during a recent period reflects the driver's recent usage experience and habits. By analyzing the recent historical operating data of the vehicle, the driver's actual usage needs are determined, and the power of the thermal management start-stop indicator is determined based on the actual usage needs.

[0046] S205: Determine the discharge power of the power battery based on the real-time status data of the vehicle battery.

[0047] In this embodiment of the application, the discharge power of the power battery is determined based on the real-time status data of the vehicle battery. Optionally, the real-time status data of the vehicle battery includes battery capacity, battery available power, battery temperature, battery state of charge (SOC), etc. Based on the real-time status data of the vehicle battery and according to the corresponding calibration data mapping relationship, the discharge power of the power battery can be determined, that is, the maximum discharge power of the vehicle under the current condition, which reflects the current optimal state of the vehicle battery.

[0048] S207: Determine the required power of the vehicle based on the real-time operating data of the vehicle.

[0049] In this embodiment, the vehicle's power demand is determined based on real-time vehicle operating data. Optionally, the real-time vehicle operating data includes current vehicle speed, current pedal opening, current motor speed, etc. Based on this data, the maximum power that the vehicle may need in the future under its current driving state is estimated. Specifically, a machine learning model can be used to determine the current power demand of the vehicle based on the correspondence between previous vehicle operating data and power demand, using the current vehicle operating data.

[0050] S209: Determine whether to activate thermal management based on the thermal management start / stop indicator power, the discharge power of the power battery, and the vehicle's required power.

[0051] In this embodiment, after obtaining the thermal management start-stop indicator power, the power battery's discharge capacity, and the vehicle's required power, the relationship between these three factors determines whether thermal management needs to be activated in the current state. Specifically, for example, in winter, if the power battery's discharge capacity is less than the thermal management start-stop indicator power, it indicates that the current power battery's discharge capacity does not meet the driver's recent usage needs, and thermal management needs to be activated to heat the battery and increase its discharge capacity. Similarly, if the power battery's discharge capacity is less than the vehicle's required power, it indicates that the current power battery's discharge capacity does not meet the driving needs of the vehicle's current journey, and thermal management needs to be activated to increase the power battery's discharge capacity.

[0052] In the aforementioned power battery thermal management method, firstly, historical vehicle operating data, real-time vehicle battery status data, and real-time vehicle operating data are acquired. Then, based on the historical vehicle operating data, the thermal management start-stop indicator power is determined; based on the real-time vehicle battery status data, the power battery's dischargeable power is determined; and based on the real-time vehicle operating data, the vehicle's required power is determined. Finally, based on the thermal management start-stop indicator power, the power battery's dischargeable power, and the vehicle's required power, it is determined whether thermal management should be activated. In other words, by understanding the driver's recent driving data, a more reasonable thermal management start-stop indicator power is determined. During vehicle operation, the power battery's dischargeable power is monitored in real time, and future power requirements for the current journey are predicted. A comprehensive comparison is then made to determine whether thermal management needs to be activated in the current vehicle state. This allows for real-time adjustments based on the driver's usage and actual driving needs, improving the flexibility and practicality of power battery thermal management.

[0053] In one embodiment of this application, determining the thermal management start-stop flag power based on the vehicle's historical operating data includes:

[0054] Based on the vehicle's historical operating data, the vehicle's historical power demand is determined, and based on the vehicle's historical power demand, the thermal management start-stop flag power is determined.

[0055] In one embodiment of this application, the historical power demand of a vehicle is determined based on historical vehicle operating data, specifically, based on operating data from recent vehicle usage. A dataset is established based on the operating data from recent vehicle usage, and preprocessing is performed, including outlier removal and data standardization. The operating data from recent vehicle usage includes vehicle speed, pedal opening, and motor speed. Then, the relevant characteristics of the dataset are analyzed to determine the historical power demand. Next, the trend of the historical power demand is analyzed, such as the average or maximum probability value of the historical power demand in recent times, to determine its use as the thermal management start-stop indicator power. Optionally, the analysis method can employ a time series decomposition algorithm (Seasonal and Trend decomposition using LOESS, STL) to decompose the time series into three main components: trend, seasonality, and residuals.

[0056] In this embodiment, the historical power demand of the vehicle is determined based on the vehicle's historical operating data, and the power demand of the thermal management start-stop flag is determined based on the historical power demand of the vehicle, so that the power demand of the thermal management start-stop flag can be flexibly set according to user needs.

[0057] In one embodiment of this application, determining the vehicle's historical power demand based on the vehicle's historical operating data includes:

[0058] The vehicle's historical operating data is divided into preset periods, and clustering and feature extraction are performed to determine the vehicle's historical power demand.

[0059] In one embodiment of this application, the acquired historical vehicle operation data, i.e., the operation data during recent vehicle use, is divided according to a preset period, where the preset period refers to one day, one week, or one month. Within the preset period, the historical vehicle operation data is clustered and feature extraction is performed. Optionally, the extracted features include statistical features, frequency domain features, and time domain features. Statistical features include mean, variance, maximum value, minimum value, etc. Frequency domain features include Fourier transform, wavelet transform, etc., and time domain features include autocorrelation coefficient, centroid, etc. Then, the extracted features are standardized to obtain the historical power demand of the vehicle. Optionally, the clustering can employ K-means clustering, mean-shift clustering, density-based clustering, distribution-based clustering, hierarchical clustering, etc.

[0060] In this embodiment, by dividing the vehicle's historical operating data into preset periods and performing clustering and feature extraction, the historical power demand of the vehicle can be determined, thereby accurately obtaining the driver's recent user needs.

[0061] In one embodiment of this application, the real-time status data of the vehicle battery includes at least battery temperature and battery state of charge, and determining the discharge power of the power battery based on the real-time status data of the vehicle battery includes:

[0062] The discharge power of the power battery is determined based on battery temperature, battery state of charge, and a preset mapping relationship, wherein the preset mapping relationship includes the correlation between battery temperature, battery state of charge, and discharge power of the power battery.

[0063] In one embodiment of this application, the real-time status data of the vehicle battery includes at least battery temperature and battery state of charge (SOC). There is a preset mapping relationship between battery temperature, SOC, and the discharge power of the power battery, i.e., a one-to-one association. Each battery temperature and SOC corresponds to a specific discharge power of the power battery. Optionally, the preset mapping relationship can be a map table obtained by calibrating the relationship between battery temperature, SOC, and discharge power of the power battery in the early stages. In specific applications, real-time vehicle battery status data is acquired, and then the discharge power of the power battery corresponding to the current situation is determined based on the preset mapping relationship. The 10s discharge power limit map table is shown below.

[0064]

[0065] In this embodiment, the discharge power of the power battery is determined by a preset mapping relationship based on battery temperature, battery state of charge, and discharge power of the power battery, which can accurately determine the discharge power of the vehicle's power battery under the current conditions.

[0066] In one embodiment of this application, determining the vehicle's required power based on the vehicle's real-time operating data includes:

[0067] The real-time vehicle operation data is input into the trained vehicle demand power prediction model to obtain the vehicle demand power. The vehicle demand power prediction model is trained based on the vehicle's historical operation data and the vehicle's historical demand power. The vehicle's historical operation data includes at least historical vehicle speed, historical pedal opening, and historical battery temperature.

[0068] In one embodiment of this application, after acquiring real-time vehicle operating data, the real-time vehicle operating data is input into a trained vehicle power demand prediction model to obtain the vehicle power demand. The real-time vehicle operating data includes current vehicle speed, current pedal opening, current motor speed, etc. The vehicle power demand prediction model is trained based on historical vehicle operating data and historical vehicle power demand. The historical vehicle operating data includes historical vehicle speed, historical pedal opening, historical battery temperature, historical battery state of charge, etc. First, a training dataset is established based on the historical vehicle operating data and historical vehicle power demand, and this dataset is input into the machine learning model. A loss function and optimizer are defined, and the loss function is minimized using the backpropagation algorithm. The model is then evaluated and tuned. After training, a trained vehicle power demand prediction model is obtained. Inputting the acquired real-time vehicle operating data allows the output of the vehicle power demand. Optionally, the machine learning model can be a Long Short-Term Memory (LSTM) network, a Convolutional Neural Network (CNN), a Neural Transformer model, etc.

[0069] In this embodiment, by inputting the real-time vehicle operation data into the trained vehicle demand power prediction model, the vehicle demand power is obtained, which enables real-time and flexible prediction of the vehicle's current travel power demand.

[0070] In one embodiment of this application, determining whether to activate thermal management based on the thermal management start-stop flag power, the discharge power of the power battery, and the vehicle's required power includes:

[0071] If the discharge power of the power battery is less than the power of the thermal management start / stop flag, then thermal management is activated.

[0072] In one embodiment of this application, after obtaining the power of the thermal management start-stop indicator, the discharge power of the power battery, and the power required by the vehicle, the discharge power of the power battery and the power of the thermal management start-stop indicator are compared. If the discharge power of the power battery is less than the power of the thermal management start-stop indicator, it means that under the current circumstances, the discharge power of the power battery can no longer meet the driver's driving habits, and thermal management is activated to increase the battery power. If the discharge power of the power battery is greater than the power of the thermal management start-stop indicator, it means that under the current circumstances, the vehicle meets the driver's recent driving habits, and thermal management does not need to be activated.

[0073] In this embodiment, by comparing the discharge power of the power battery and the power of the thermal management start / stop flag, the power battery can be flexibly managed in response to actual conditions.

[0074] In one embodiment of this application, determining whether to activate thermal management based on the thermal management start-stop flag power, the discharge power of the power battery, and the vehicle's required power further includes:

[0075] If the discharge power of the power battery is less than the power required by the vehicle, then thermal management is activated.

[0076] In one embodiment of this application, after obtaining the thermal management start-stop indicator power, the discharge power of the power battery, and the vehicle's required power, the discharge power of the power battery and the vehicle's required power are compared. If the discharge power of the power battery is less than the vehicle's required power, it means that the discharge power of the power battery will not be able to meet the driver's driving needs in the future. In this case, thermal management is activated to increase the battery power to meet the driver's driving needs. If the discharge power of the power battery is greater than the driver's required power, it means that the future required power is less than the current discharge power of the power battery, and thermal management does not need to be activated.

[0077] In this embodiment, by comparing the discharge power of the power battery with the power demand of the vehicle, the power battery can be flexibly managed to adapt to actual conditions.

[0078] The following specific embodiment illustrates the detailed implementation steps of the power battery thermal management of this application, such as... Figure 3 As shown, firstly, in step S301, historical vehicle operating data, real-time vehicle battery status data, and real-time vehicle operating data are acquired. Then, in step S303, the thermal management start-stop flag power is determined based on the historical vehicle operating data. Specifically, in step S305, the historical vehicle power demand is determined based on the historical vehicle operating data, and the thermal management start-stop flag power is determined based on the historical vehicle power demand. In step S307, the historical vehicle operating data is divided according to a preset period, and clustering and feature extraction are performed to determine the historical vehicle power demand.

[0079] Next, in step S309, the discharge power of the power battery is determined based on the real-time status data of the vehicle battery. Specifically, in step S311, the real-time status data of the vehicle battery includes at least the battery temperature and the battery state of charge. The discharge power of the power battery is determined based on the battery temperature, the battery state of charge, and a preset mapping relationship, wherein the preset mapping relationship includes the correlation between the battery temperature, the battery state of charge, and the discharge power of the power battery.

[0080] Next, in step S313, the vehicle's power demand is determined based on the real-time vehicle operating data. Specifically, in step S315, the real-time vehicle operating data is input into a trained vehicle power demand prediction model to obtain the vehicle power demand. The vehicle power demand prediction model is trained based on the vehicle's historical operating data and historical power demand. The historical operating data includes at least historical vehicle speed, historical pedal opening, and historical battery temperature.

[0081] Finally, S317, based on the thermal management start-stop indicator power, the discharge power of the power battery, and the vehicle's required power, it is determined whether to activate thermal management. Specifically, S319, if the discharge power of the power battery is less than the thermal management start-stop indicator power, then thermal management is activated; S321, if the discharge power of the power battery is less than the vehicle's required power, then thermal management is activated.

[0082] In one embodiment of this application, the power of the thermal management start-stop sign is determined based on the vehicle's historical operating data. Similarly, the temperature and speed of the thermal management start-stop sign can also be determined.

[0083] In one embodiment of this application, the power battery thermal management method of this application is applicable not only to low-temperature driving heating, but also to high-temperature driving cooling, power battery charging, and other situations.

[0084] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0085] Based on the same inventive concept, this application also provides a power battery thermal management device for implementing the power battery thermal management method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more power battery thermal management device embodiments provided below can be found in the limitations of the power battery thermal management method described above, and will not be repeated here.

[0086] In one embodiment, such as Figure 4 As shown, a power battery thermal management device 400 is provided, including: a data acquisition module 401, a thermal management start / stop flag power determination module 403, a power battery dischargeable power determination module 405, a vehicle demand power determination module 407, and a thermal management start determination module 409, wherein:

[0087] The data acquisition module 401 is used to acquire historical vehicle operation data, real-time vehicle battery status data, and real-time vehicle operation data.

[0088] The thermal management start-stop flag power determination module 403 is used to determine the thermal management start-stop flag power based on the vehicle's historical operating data.

[0089] The power battery discharge power determination module 405 is used to determine the power battery discharge power based on the real-time status data of the vehicle battery.

[0090] The vehicle power demand determination module 407 is used to determine the vehicle power demand based on the real-time operating data of the vehicle.

[0091] The thermal management activation determination module 409 is used to determine whether to activate thermal management based on the thermal management start / stop flag power, the discharge power of the power battery, and the vehicle's required power.

[0092] In one embodiment of this application, the thermal management start / stop flag power determination module is further configured to:

[0093] Based on the vehicle's historical operating data, the vehicle's historical power demand is determined, and based on the vehicle's historical power demand, the thermal management start-stop flag power is determined.

[0094] In one embodiment of this application, the thermal management start / stop flag power determination module is further configured to:

[0095] The vehicle's historical operating data is divided into preset periods, and clustering and feature extraction are performed to determine the vehicle's historical power demand.

[0096] In one embodiment of this application, the real-time status data of the vehicle battery includes at least battery temperature and battery state of charge, and the power battery discharge power determination module is further used for:

[0097] The discharge power of the power battery is determined based on battery temperature, battery state of charge, and a preset mapping relationship, wherein the preset mapping relationship includes the correlation between battery temperature, battery state of charge, and discharge power of the power battery.

[0098] In one embodiment of this application, the vehicle power demand determination module is further configured to:

[0099] The real-time vehicle operation data is input into the trained vehicle demand power prediction model to obtain the vehicle demand power. The vehicle demand power prediction model is trained based on the vehicle's historical operation data and the vehicle's historical demand power. The vehicle's historical operation data includes at least historical vehicle speed, historical pedal opening, and historical battery temperature.

[0100] In one embodiment of this application, the thermal management activation determination module is further configured to:

[0101] If the discharge power of the power battery is less than the power of the thermal management start / stop flag, then thermal management is activated.

[0102] In one embodiment of this application, the thermal management activation determination module is further configured to:

[0103] If the discharge power of the power battery is less than the power required by the vehicle, then thermal management is activated.

[0104] Each module in the aforementioned power battery thermal management device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0105] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 5As shown, the computer device includes a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When executed by the processor, the computer program implements a power battery thermal management method. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0106] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0107] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0108] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0109] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0110] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0111] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A thermal management method for a power battery, characterized in that, The method includes: Acquire historical vehicle operating data, real-time vehicle battery status data, and real-time vehicle operating data; The power of the thermal management start-stop indicator is determined based on the vehicle's historical operating data. The discharge power of the power battery is determined based on the real-time status data of the vehicle battery. The required power of the vehicle is determined based on the real-time operating data of the vehicle. Whether to activate thermal management is determined based on the thermal management start / stop indicator power, the discharge power of the power battery, and the vehicle's required power. Determining the historical power demand of the vehicle based on the historical vehicle operating data, and determining the power demand of the thermal management start-stop flag based on the historical power demand of the vehicle, includes: A dataset was created based on historical vehicle operation data, and the dataset was preprocessed, including outlier removal and data standardization. The historical vehicle operation data included vehicle speed, pedal opening, and motor speed during recent vehicle use. Based on the analysis of the relevant features of the preprocessed dataset, the historical demand power of vehicles is determined, and the trend of historical demand power of vehicles is analyzed by time series decomposition algorithm; the trend of historical demand power of vehicles is the average value or the maximum probability value of historical demand power of vehicles in the recent period. The historical power demand trend of the vehicle is used as the starting and stopping power indicator for thermal management. Determining the historical power demand of a vehicle based on the aforementioned historical vehicle operating data includes: The historical vehicle operation data is divided into preset periods, and clustering and feature extraction are performed. The extracted features are standardized to determine the historical power demand of the vehicle. The extracted features include statistical features, frequency domain features, and time domain features. The statistical features include mean, variance, maximum value, and minimum value. The frequency domain features include Fourier transform and wavelet transform. The time domain features include autocorrelation coefficient and centroid. Determining whether to activate thermal management based on the thermal management start / stop indicator power, the discharge power of the power battery, and the vehicle's required power includes: If the discharge power of the power battery is less than the power of the thermal management start / stop flag, then thermal management is activated; If the discharge power of the power battery is less than the power required by the vehicle, then thermal management is activated.

2. The method according to claim 1, characterized in that, The real-time status data of the vehicle battery includes at least battery temperature and battery state of charge, and determining the discharge power of the power battery based on the real-time status data of the vehicle battery includes: The discharge power of the power battery is determined based on battery temperature, battery state of charge, and a preset mapping relationship, wherein the preset mapping relationship includes the correlation between battery temperature, battery state of charge, and discharge power of the power battery.

3. The method according to claim 1, characterized in that, Determining the vehicle's required power based on the vehicle's real-time operating data includes: The real-time vehicle operation data is input into the trained vehicle demand power prediction model to obtain the vehicle demand power. The vehicle demand power prediction model is trained based on the vehicle's historical operation data and the vehicle's historical demand power. The vehicle's historical operation data includes at least historical vehicle speed, historical pedal opening, and historical battery temperature.

4. A power battery thermal management device, characterized in that, The device includes: The data acquisition module is used to acquire historical vehicle operating data, real-time vehicle battery status data, and real-time vehicle operating data. The thermal management start-stop flag power determination module is used to determine the thermal management start-stop flag power based on the vehicle's historical operating data. A power battery discharge power determination module is used to determine the power battery discharge power based on the real-time status data of the vehicle battery. The vehicle power demand determination module is used to determine the vehicle power demand based on the vehicle's real-time operating data. The thermal management activation determination module is used to determine whether to activate thermal management based on the thermal management start / stop flag power, the discharge power of the power battery, and the vehicle's required power. Determining the historical power demand of the vehicle based on the historical vehicle operating data, and determining the power demand of the thermal management start-stop flag based on the historical power demand of the vehicle, includes: A dataset was created based on historical vehicle operation data, and the dataset was preprocessed, including outlier removal and data standardization. The historical vehicle operation data included vehicle speed, pedal opening, and motor speed during recent vehicle use. Based on the analysis of the relevant features of the preprocessed dataset, the historical demand power of vehicles is determined, and the trend of historical demand power of vehicles is analyzed by time series decomposition algorithm; the trend of historical demand power of vehicles is the average value or the maximum probability value of historical demand power of vehicles in the recent period. The historical power demand trend of the vehicle is used as the starting and stopping power indicator for thermal management. Determining the historical power demand of a vehicle based on the aforementioned historical vehicle operating data includes: The historical vehicle operation data is divided into preset periods, and clustering and feature extraction are performed. The extracted features are standardized to determine the historical power demand of the vehicle. The extracted features include statistical features, frequency domain features, and time domain features. The statistical features include mean, variance, maximum value, and minimum value. The frequency domain features include Fourier transform and wavelet transform. The time domain features include autocorrelation coefficient and centroid. Determining whether to activate thermal management based on the thermal management start-stop indicator power, the discharge power of the power battery, and the vehicle's required power includes: activating thermal management if the discharge power of the power battery is less than the thermal management start-stop indicator power; and activating thermal management if the discharge power of the power battery is less than the vehicle's required power.

5. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 3.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 3.

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