Battery heating control method, device, apparatus, storage medium and program product

Abstract

Embodiments of the present application provide a battery heating control method, device, equipment, storage medium and program product. The method comprises: obtaining a reference mileage when a battery of a target vehicle is in a low-temperature environment. If an estimated remaining mileage of the target vehicle for this time is greater than or equal to the reference mileage, the battery is heated. The method of the present application can improve the accuracy of battery heating for the battery of the vehicle.

Description

Technical Field

[0001] This application relates to the field of battery technology, and in particular to a battery heating control method, apparatus, equipment, storage medium, and program product. Background Technology

[0002] In the automotive industry, vehicle electrification has become a current development trend. Current new energy vehicles are powered by batteries. When batteries operate in low-temperature environments, their capacity decreases. Currently, battery heating can be used to increase battery capacity, thereby extending the vehicle's driving range. However, battery heating also consumes the battery's own energy, reducing the vehicle's driving range. Furthermore, current methods for heating vehicle batteries in low-temperature environments suffer from low accuracy.

[0003] Therefore, improving the accuracy of battery heating in vehicles is an urgent problem to be solved. Summary of the Invention

[0004] This application provides a battery heating control method, apparatus, device, storage medium, and program product to achieve accurate battery heating of a vehicle.

[0005] In a first aspect, embodiments of this application provide a battery heating control method, including:

[0006] Obtain reference mileage when the target vehicle's battery is in a low-temperature environment;

[0007] If the estimated remaining mileage of the target vehicle in this trip is greater than or equal to the reference mileage, then the battery is heated.

[0008] Secondly, embodiments of this application provide a battery heating control device, comprising:

[0009] The acquisition module is used to obtain reference mileage when the target vehicle's battery is in a low-temperature environment;

[0010] The processing module is used to heat the battery if the estimated remaining mileage of the target vehicle in this trip is greater than or equal to the reference mileage.

[0011] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor;

[0012] The memory stores computer-executed instructions;

[0013] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0014] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0015] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0016] The battery heating control method, apparatus, device, storage medium, and program product provided in this application, when the battery of a target vehicle is in a low-temperature environment, obtains a reference mileage and compares the estimated remaining mileage of the target vehicle's current journey with the reference mileage. If the estimated remaining mileage of the target vehicle's current journey is greater than or equal to the reference mileage, it indicates that heating the battery can reduce the battery energy consumed by the target vehicle when traveling the estimated remaining mileage, thereby increasing the vehicle's driving range. This determines that the battery should be heated, thus improving the accuracy of battery heating for the vehicle and further increasing the vehicle's driving range. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] Figure 1 A schematic flowchart illustrating a battery heating control method provided in an embodiment of this application;

[0019] Figure 2 A schematic diagram of a battery energy consumption curve provided in an embodiment of this application;

[0020] Figure 3 A schematic flowchart of another battery heating control method provided in an embodiment of this application;

[0021] Figure 4 A schematic flowchart illustrating another battery heating control method provided in this application embodiment;

[0022] Figure 5 A schematic flowchart illustrating another battery heating control method provided in an embodiment of this application;

[0023] Figure 6 A schematic flowchart illustrating another battery heating control method provided in an embodiment of this application;

[0024] Figure 7 A schematic flowchart illustrating another battery heating control method provided in an embodiment of this application;

[0025] Figure 8 A schematic flowchart illustrating another battery heating control method provided in an embodiment of this application;

[0026] Figure 9 A schematic flowchart illustrating another battery heating control method provided in an embodiment of this application;

[0027] Figure 10 A schematic flowchart illustrating another battery heating control method provided in an embodiment of this application;

[0028] Figure 11 A schematic flowchart illustrating another battery heating control method provided in an embodiment of this application;

[0029] Figure 12 This is a schematic diagram of the structure of a battery heating control device provided in an embodiment of this application;

[0030] Figure 13 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0031] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0032] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0033] First, let's introduce the current methods for controlling battery heating:

[0034] Currently, the system monitors the current temperature of the power battery in real time to determine if it is below a preset temperature threshold. If the current temperature is below the threshold, the system determines the battery's equilibrium temperature based on the current temperature and its performance parameters. Then, it determines the heating time required to raise the battery from the current temperature to the equilibrium temperature based on the equilibrium temperature and the current temperature. Finally, it determines the vehicle's estimated driving time and, based on the heating time and the estimated driving time, decides whether to heat the power battery.

[0035] However, the inventors discovered that when the battery is in a low-temperature environment, not only does battery heating lead to additional energy consumption, but low temperatures also affect the vehicle's driving energy consumption. Current technology only compares the estimated driving time with the heating time to determine whether to heat the battery, without considering the battery's specific energy consumption, resulting in low accuracy in determining whether to heat the battery.

[0036] In view of this, this application provides a battery heating control method. When the battery of a target vehicle is in a low-temperature environment, a reference mileage is obtained, and the estimated remaining mileage of the target vehicle in this trip is compared with the reference mileage. If the estimated remaining mileage of the target vehicle in this trip is greater than or equal to the reference mileage, it indicates that heating the battery can reduce the battery energy consumed by the target vehicle when traveling the estimated remaining mileage, thereby increasing the vehicle's driving range. This determines that the battery should be heated, thereby improving the accuracy of battery heating and thus increasing the vehicle's driving range.

[0037] The battery heating control method provided in this application can be executed by a terminal device with data processing capabilities, or by the processing chip of that terminal device, or by software or program code that implements the data processing method. When the executing entity is a terminal device with data processing capabilities, the terminal device can be, for example, a computing device such as a vehicle infotainment system or a computer with computing capabilities. The computing device can be equipped with software or program code that runs the battery heating control method, and the software or program code controls whether the battery is heated.

[0038] The technical solution of this application and how it solves the above-mentioned technical problems will be described in detail below through specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0039] Figure 1 This is a schematic flowchart illustrating a battery heating control method provided in an embodiment of this application. Figure 1 As shown, the method includes:

[0040] S101. Obtain reference mileage when the target vehicle's battery is in a low-temperature environment.

[0041] When the target vehicle's battery is in a low-temperature environment, if the battery is not heated, although the energy consumption of the battery will be reduced (i.e. there is no additional energy consumption caused by heating the battery), the battery temperature will only rise slowly due to the heat generated by the battery's operation. As a result, the battery will be in a low-temperature environment for a long time, resulting in low discharge energy efficiency and low battery capacity retention, which leads to a short driving range for the target vehicle.

[0042] Heating the battery can increase its temperature rise rate, thereby reducing the time it spends in low-temperature environments. This improves the battery's discharge efficiency and capacity retention, ultimately extending the vehicle's range. However, heating the battery incurs additional energy consumption. In this case, the battery's energy consumption includes both the energy consumed by driving the vehicle and the energy consumed by heating the battery.

[0043] Assuming the target vehicles are in the same driving state, Figure 2 This is a schematic diagram of a battery energy consumption curve provided in an embodiment of this application. Wherein, Figure 2 The horizontal axis represents the target vehicle's mileage, and the vertical axis represents the energy consumption corresponding to the battery's energy consumption. For the energy consumption curve under battery heating, at shorter mileages, the initial rate of change in the energy consumption curve is larger due to the additional energy consumption caused by battery heating. As the battery heats up, the rapid rise in battery temperature allows the battery to retain more effective capacity compared to not heating. Therefore, the energy consumption of the battery will be lower when driving the same mileage compared to not heating, resulting in a lower rate of change in the energy consumption curve at this point. Consequently, the energy consumption curve under battery heating will intersect with the energy consumption curve under battery heating. If the target vehicle's mileage is less than the mileage corresponding to this intersection point, the battery energy consumption is lower when not heating, resulting in more remaining battery energy and a longer driving range. Conversely, if the target vehicle's mileage is greater than the mileage corresponding to this intersection point, the battery energy consumption is lower when heating, resulting in more remaining battery energy and a longer driving range.

[0044] Therefore, when the target vehicle's battery is in a low-temperature environment, the energy consumption of the battery is predicted when the target vehicle is driving with the battery heated, and the energy consumption of the battery is predicted when the target vehicle is driving without the battery heated. The mileage corresponding to the same energy consumption under both conditions is used as a reference mileage. The reference mileage is compared with the estimated remaining mileage of the target vehicle in this trip to determine whether to heat the battery to reduce energy consumption and thus improve the target vehicle's driving range.

[0045] If the estimated remaining mileage of the target vehicle is greater than or equal to the reference mileage, it indicates that heating the battery can reduce the energy consumption of the battery, and step S102 is executed; if the estimated remaining mileage of the target vehicle is less than the reference mileage, it indicates that not heating the battery can reduce the energy consumption of the battery, and step S103 is executed to not heat the battery.

[0046] Optionally, since the battery's remaining energy and capacity are the same at the initial moment, when the battery consumes the same amount of energy, its corresponding remaining energy and remaining capacity are also the same. Therefore, changes in the battery's remaining energy or remaining capacity can be used instead of changes in battery energy consumption as the basis for determining the reference mileage.

[0047] One possible implementation is that the reference mileage can be calculated in real time based on the principles described above. Another possible implementation is that the reference mileage can be obtained from a reference mileage mapping relationship obtained through prior experiments, based on the current battery state and battery temperature. For example, by obtaining reference mileage corresponding to different battery temperatures under different battery remaining energy or capacity conditions at initial moments through prior experiments, the corresponding reference mileage can be obtained based on the target vehicle's current battery remaining energy or capacity, and battery temperature.

[0048] Optionally, the reference mileage can be obtained either before the target vehicle starts traveling or during its journey. If the reference mileage is obtained before the target vehicle starts traveling, the estimated remaining mileage for the current trip is the mileage the target vehicle will travel. A comparison between the estimated remaining mileage and the reference mileage determines whether battery heating is necessary. If the reference mileage is obtained during the target vehicle's journey, the estimated remaining mileage for the current trip is the mileage the target vehicle needs to continue traveling. A comparison between the estimated mileage and the reference mileage determines whether battery heating is necessary.

[0049] S102. Heat the battery.

[0050] The battery can be heated by electric heating, self-heating, liquid heating, direct heating, etc. This application does not limit the heating method for heating the battery.

[0051] The method provided in this application embodiment, when the target vehicle's battery is in a low-temperature environment, obtains a reference mileage and compares the estimated remaining mileage of the target vehicle's current journey with the reference mileage. If the estimated remaining mileage of the target vehicle's current journey is greater than or equal to the reference mileage, it indicates that heating the battery can reduce the battery energy consumed by the target vehicle when driving the estimated remaining mileage, thereby increasing the vehicle's driving range. This method determines that the battery should be heated, thus improving the accuracy of heating the vehicle's battery and further increasing the vehicle's driving range.

[0052] Because it's necessary to compare the estimated remaining mileage of the target vehicle's current journey with a reference mileage to determine whether battery heating is required, this method also includes obtaining the estimated remaining mileage of the target vehicle's current journey.

[0053] Optionally, the estimated remaining mileage can be obtained based on the navigation information used by the target vehicle during this trip. For example, if the target vehicle used navigation during this trip, the estimated mileage to be traveled, or the remaining mileage required for this trip, can be obtained from the navigation information provided by the navigation function corresponding to this trip. This navigation information can be obtained, for example, from a navigation application within the vehicle's infotainment system, or from a mobile phone navigation system, tablet navigation system, etc., connected to the vehicle's infotainment system.

[0054] Optionally, the system can also obtain the estimated remaining mileage of the target vehicle for this trip in response to user input. For example, the vehicle's infotainment system can be instructed to output an interface for the user to input the estimated remaining mileage, and the estimated remaining mileage can be obtained in response to the user's input on that interface. Alternatively, after obtaining a reference mileage, the reference mileage can be output so that the user can choose whether to heat the battery based on the reference mileage.

[0055] For example, if the user chooses whether to heat the battery, the vehicle's infotainment system can instruct the user: "The current battery temperature is low. If the estimated remaining range is less than or equal to the reference range X, it is recommended not to turn on battery heating. If the estimated remaining range is greater than the reference range X, it is recommended to turn on battery heating to increase the driving range." If the user chooses to turn on battery heating, the system receives a battery heating confirmation message corresponding to the user's selection and heats the battery accordingly. If the user chooses not to turn on battery heating or makes no selection, it indicates that no battery heating confirmation message has been received, and the battery is not heated.

[0056] In one possible implementation, if no battery heating confirmation is received, it indicates that the user may not have noticed the need to manually select whether to activate battery heating, or the user may not need to heat the battery. If it is the former case, i.e., the user may not have noticed the need to manually select whether to activate battery heating, the battery can be heated when the actual mileage traveled by the target vehicle exceeds the reference mileage, in order to reduce subsequent energy consumption of the battery and increase the driving range of the target vehicle.

[0057] In one possible implementation, if a reference mileage cannot be obtained, or if the estimated remaining mileage is less than the reference mileage, then the battery is not heated. The reason for not heating the battery when a reference mileage is unavailable or the estimated remaining mileage is less than the reference mileage is that, in short-range driving scenarios, the additional energy consumption from heating the battery could have a greater negative impact on the overall range. While not heating the battery may lead to efficiency issues due to low battery temperatures, it avoids the extra energy consumed by heating the battery, potentially reducing total energy consumption within a limited range and ensuring the vehicle can reach its destination.

[0058] Below is a detailed explanation of how to determine whether the target vehicle's battery is in a low-temperature environment. Figure 3 This is a schematic flowchart illustrating another battery heating control method provided in an embodiment of this application. Figure 3 As shown, the method may further include:

[0059] S301. Obtain the battery temperature of the target vehicle.

[0060] The battery temperature can be obtained, for example, through the target vehicle's battery management system or through a temperature sensor on the battery, and this application does not limit this.

[0061] S302. If the battery temperature is less than or equal to the first temperature threshold, it is determined that the battery of the target vehicle is in a low temperature environment.

[0062] The first temperature threshold can be set according to actual needs (e.g., based on the battery's recommended operating environment, battery type, etc.), such as 0 degrees Celsius, -10 degrees Celsius, etc., and this application does not impose any restrictions on it.

[0063] If the battery temperature is less than or equal to a first temperature threshold, it indicates that the battery has low discharge energy efficiency and low capacity retention at that temperature. Heating the battery may be necessary to improve its discharge energy efficiency and capacity retention, thereby increasing the driving range of the target vehicle. Therefore, when the battery temperature is less than or equal to the first temperature threshold, the battery of the target vehicle is determined to be in a low-temperature environment.

[0064] Optionally, since heating the battery incurs additional energy consumption, battery heating is not activated when the battery's State of Charge (SOC) is low to minimize the total energy consumption for the limited remaining range. Therefore, before obtaining the reference range in step S101, in addition to determining whether the battery is in a low-temperature environment based on its temperature, it is also necessary to further consider the battery's State of Charge (SOC), such as determining the relationship between the battery's SOC and a preset threshold. In this implementation, the initial SOC of the battery is obtained (e.g., it can be obtained from the battery management system), and it is determined whether the initial SOC is greater than or equal to a preset SOC threshold, and whether the battery temperature is less than or equal to a second temperature threshold (which has the same function as the first temperature threshold; the second temperature threshold can be the same temperature value as the first temperature threshold or a different one). If the initial SOC is greater than or equal to the preset SOC threshold, and the battery temperature is less than or equal to the second temperature threshold, it indicates that the target vehicle's battery is in a low-temperature environment, and the battery's SOC indicates that the target vehicle has sufficient remaining range. Therefore, it is confirmed that the target vehicle's battery is in a low-temperature environment, and the aforementioned process can continue. Figure 1 The steps in the process are used to determine whether the battery needs to be heated.

[0065] The following section will take the real-time calculation of reference mileage as an example to explain in detail how to obtain reference mileage in the aforementioned step S101. Figure 4 This is a schematic flowchart illustrating another battery heating control method provided in an embodiment of this application. Figure 4 As shown, the aforementioned step S101 may specifically include:

[0066] S401. Obtain first predicted driving data of the target vehicle when the battery is not heated, and second predicted driving data of the target vehicle when the battery is heated.

[0067] The first predicted driving data includes the first remaining energy data and the first mileage data, and the second predicted driving data includes the second remaining energy data and the second mileage data.

[0068] Predicted driving data for the target vehicle is obtained by predicting its future energy and mileage changes. When the target vehicle is in a non-heated battery state, its future energy changes only include the energy changes generated by the vehicle's driving energy consumption. When the target vehicle is in a heated battery state, its future energy changes include both the energy changes generated by the vehicle's driving energy consumption and the energy changes generated by the battery heating.

[0069] Based on the energy change of the target vehicle when the battery is not heated, and the current remaining battery energy of the target vehicle, it is possible to predict the first remaining energy data in the first predicted driving data. Based on the energy change of the target vehicle when the battery is heated, and the current remaining battery energy of the target vehicle, it is possible to predict the second remaining energy data in the second predicted driving data.

[0070] The mileage data for the target vehicle can be calculated based on its predicted speed and predicted travel time. Specifically, the mileage data for the target vehicle at different predicted travel times can be obtained by producting the predicted speed and predicted travel time.

[0071] The predicted speed can be obtained from historical vehicle speed information acquired through big data (e.g., using the average speed from historical data as the predicted speed). Alternatively, the predicted speed can be inferred using artificial intelligence algorithms combined with navigation, traffic conditions, and other information. Optionally, the predicted speed can also be adjusted based on the target vehicle's driving mode, adjusting the user's historical speed information or the results inferred by the artificial intelligence algorithm. For example, different adjustment coefficients can be set for different driving modes (e.g., multiplying Sport mode by 1.4; Normal mode by 1.0; Eco mode by 0.8) to obtain the predicted speed.

[0072] S402. Obtain a reference mileage based on the first predicted driving data and the second predicted driving data.

[0073] Specifically, the target point can be determined based on the first remaining energy data, the first mileage data, the second remaining energy data, and the second mileage data. The target point is the point where the first remaining energy data and the second remaining energy data are the same, and the first mileage data and the second mileage data are also the same.

[0074] For example, a target point can be determined based on the intersection of the first curve of the remaining energy data and mileage data corresponding to the first predicted driving data, and the second curve of the remaining energy data and mileage data corresponding to the second predicted driving data. The target point is the intersection of the first curve and the second curve, which indicates that the first remaining energy data and the second remaining energy data are the same, and the first mileage data and the second mileage data are the same.

[0075] Determine the reference mileage based on the mileage corresponding to the target point.

[0076] The following sections will explain how to obtain the first predicted driving data of the target vehicle when the battery is not heated, and how to obtain the second predicted driving data of the target vehicle when the battery is heated.

[0077] Obtain the first predicted driving data:

[0078] Figure 5 This is a schematic flowchart illustrating another battery heating control method provided in an embodiment of this application. Figure 5 As shown, the aforementioned step S401 may specifically include:

[0079] S501, Obtain the initial remaining energy of the battery, the initial temperature of the battery, the battery parameters, the ambient temperature, and the predicted speed of the target vehicle.

[0080] The initial remaining energy of the battery is the remaining energy of the battery when the reference mileage is obtained. The initial battery temperature is the temperature of the battery when the reference mileage is obtained. Battery parameters may include parameters such as the battery's heat transfer coefficient, surface area, specific heat capacity, and mass. The ambient temperature is the temperature of the environment where the target vehicle is located. The predicted speed of the target vehicle is the predicted speed described in step S401 above; its concept and acquisition method will not be repeated here.

[0081] The initial battery temperature can be obtained through the battery management system or the battery's temperature sensor. Battery parameters are fixed and can be pre-configured data. Ambient temperature can be obtained through the target vehicle's environmental sensors or from a third party (e.g., a network, other electronic devices).

[0082] Optionally, the initial remaining energy of the battery can be obtained directly from the battery, for example, through the target vehicle's battery management system. Alternatively, the initial remaining energy of the battery can also be obtained based on the battery's effective remaining capacity and the battery voltage at the initial time (i.e., the time when the reference mileage is obtained).

[0083] When the initial remaining energy of a battery is obtained based on the battery's effective remaining capacity and battery voltage at the initial moment, the initial remaining energy of the battery can be obtained by multiplying the battery's effective remaining capacity and battery voltage at the initial moment.

[0084] Specifically, the initial effective remaining battery capacity can be obtained based on the battery's rated capacity and the initial state of charge (SOC), and the initial battery voltage can also be obtained based on the initial SOC. The initial battery voltage can be obtained using the correlation function between SOC and battery voltage, as well as the initial SOC. This correlation function can be obtained from the battery's State of Charge-Open Circuit Voltage (SOC-OCV) curve.

[0085] For example, the initial remaining energy of the battery can be calculated using the following formula (1):

[0086] E remain,1=C remain,1 *U current,1 (SOC1)=C rated *SOC1*U current,1 (SOC1) (1)

[0087] Among them, E remain,1 C represents the initial remaining energy of the battery. remain,1 U represents the initial effective remaining battery capacity. current,1 (SOC1) is the battery voltage at the initial time, obtained based on the SOC at the initial time. C rated SOC1 represents the battery's rated capacity and the initial SOC.

[0088] S502. Based on the battery's initial remaining energy, initial battery temperature, predicted speed, ambient temperature, and battery parameters, predict the battery temperature and remaining battery energy for the current cycle.

[0089] In this step, the self-heating energy of the battery varies with the target vehicle's speed, affecting its temperature. Different ambient temperatures also impact heat dissipation, further influencing temperature changes. Additionally, battery parameters such as specific heat capacity, mass, heat transfer coefficient, and surface area also affect temperature. Therefore, the battery temperature for the current cycle can be predicted based on the initial battery temperature, predicted speed, ambient temperature, and battery parameters.

[0090] Different battery temperatures affect the battery's discharge efficiency, thus influencing the energy consumption of the battery during the target vehicle's operation. Furthermore, the energy consumption of the battery varies depending on the target vehicle's speed. Therefore, the energy consumption of the battery in the current cycle can be predicted based on the predicted battery temperature and speed, and the remaining battery energy in the current cycle can be predicted based on the initial remaining energy and the energy consumption in the current cycle.

[0091] S503: Based on the current cycle's battery temperature, predicted speed, ambient temperature, battery parameters, and remaining battery energy, predict the battery temperature and remaining battery energy for the next cycle.

[0092] In this step, the battery temperature of the current cycle is used instead of the initial battery temperature in step S502, and the remaining battery energy of the current cycle is used instead of the initial remaining energy in step S502. Then, the battery temperature and remaining battery energy of the next cycle are predicted using the prediction method in S502.

[0093] That is, referring to S502, the battery temperature for the next cycle can be predicted based on the battery temperature, predicted speed, ambient temperature, and battery parameters of the current cycle. The remaining battery energy for the next cycle can be predicted based on the remaining battery energy of the current cycle, the battery temperature for the next cycle, and the predicted speed.

[0094] S504. Iterate the calculation until the remaining battery energy reaches the target value.

[0095] Through continuous iteration of steps S502-S503 described above, the battery temperature and remaining battery energy for each cycle can be obtained sequentially. A stopping condition for the iteration can be set according to actual needs; that is, the iteration stops when the remaining battery energy reaches the target value.

[0096] Optionally, the target value could be, for example, the remaining battery energy in a certain cycle when the battery is not heated, and the same value as the remaining battery energy in a certain cycle calculated using a similar method when the battery is heated. Alternatively, the target value could be a value set according to actual needs, such as 0. When the target value is 0, i.e., the cycle in which the iterative calculation reaches 0 remaining battery energy, the iteration stops. Alternatively, the target value could be any other arbitrary value, which is not limited in this application.

[0097] S505. Based on the remaining battery energy and predicted driving range corresponding to each cycle in the iterative calculation, obtain the first predicted driving data of the target vehicle in the state where the battery is not heated.

[0098] The predicted mileage is obtained based on the predicted speed. This predicted mileage is calculated based on the predicted speed and the duration of each cycle. For example, the mileage within each cycle is obtained by producting the predicted speed used in each cycle with the corresponding duration of each cycle. Based on the time sequence of each cycle, the mileage within each cycle is accumulated to obtain the predicted mileage for that cycle (i.e., the mileage within that cycle and the cumulative sum of the mileage in all previous cycles).

[0099] Record the remaining battery energy and the predicted driving range for each cycle in the iterative calculation, and generate the first predicted driving data of the target vehicle in the state of battery non-heating based on the remaining battery energy and the predicted driving range for each cycle.

[0100] It should be understood that when the battery is not heated, the temperature change of the battery is only related to the heat generated and the heat dissipated by the battery itself during operation. Therefore, the battery temperature change can be predicted based on the predicted heat generation and heat dissipation of the battery in each cycle, and the predicted battery temperature at the end of each cycle (i.e., the start time of the next cycle) can be obtained based on the battery temperature change and the battery temperature at the beginning of each cycle.

[0101] Figure 6 This is a schematic flowchart illustrating another battery heating control method provided in an embodiment of this application. Figure 6 As shown, based on the current cycle's battery temperature, predicted speed, ambient temperature, and battery parameters, the battery temperature for the next cycle is predicted. Specifically, this can include:

[0102] S601. Obtain the battery state of charge (SOC) for the current cycle.

[0103] Specifically, since SOC is defined as the battery's effective remaining capacity divided by its rated capacity, the SOC for the current cycle can be obtained based on the battery's effective remaining capacity and rated capacity for the current cycle.

[0104] Furthermore, since the effective remaining capacity of the battery can be obtained by dividing the remaining energy of the battery by the battery voltage, the effective remaining capacity of the battery in the current cycle is related to the remaining energy of the battery in the current cycle and the battery voltage in the current cycle. The battery voltage in the current cycle can be obtained by relating it to the state of charge (SOC) of the current cycle.

[0105] In this application, because it predicts driving data and can only obtain the initial SOC of the battery, it cannot obtain the actual SOC at the start of each cycle. Therefore, the duration of each cycle can be shortened as much as possible, and the battery voltage of the previous cycle can be obtained based on the SOC of the previous cycle. This battery voltage is then used to calculate the effective remaining capacity of the battery in the current cycle. This allows the method to perform iterative calculations based on the initial SOC to obtain the corresponding battery voltage, thereby further obtaining the effective remaining capacity of the battery in the current cycle. Finally, the effective remaining capacity of the battery in the current cycle is divided by the rated battery capacity to obtain the SOC of the current cycle.

[0106] Specifically, the SOC for the current cycle can be obtained by dividing the effective remaining capacity of the battery in the current cycle by the rated capacity of the battery.

[0107] S602. Based on the battery temperature, SOC, and predicted speed of the current cycle, obtain the predicted battery heat generation for the current cycle.

[0108] Battery heat generation refers to the heat generated when the battery is in operation. Based on Joule's law, the heat generated by the battery during operation is due to the current flowing through a conductor (i.e., the battery resistance). Therefore, battery heat generation is related to the battery current and the battery resistance. In other words, the predicted battery heat generation for the current cycle is related to the battery current for the current cycle and the resistance of the battery itself.

[0109] According to Joule's law, the predicted heat generation of the battery in the current cycle can be expressed by the following formula (2):

[0110] E self-heat,i= =I i 2 *R DCIR (T current,i SOC i )*Δt (2)

[0111] Where i represents the current period as the i-th period, E self-heat,i This refers to the predicted battery heat generation during the current cycle, specifically from the start of the current cycle (which is also the end of the previous cycle) to the end of the current cycle (which is also the start of the next cycle). i R is the battery current for the current cycle. DCIR (T current,i SOC i The resistance is denoted as ). The battery resistance during the current cycle is related to the battery temperature T. current,i The current period's SOC (i.e., SOC) i Related to ) Δt is the duration of the current period.

[0112] Since the battery current for the current cycle needs to be predicted through iteration, the battery current can be calculated using the battery power and battery voltage for the current cycle that can be predicted during the iteration process. Specifically, step S602 can be implemented through the following sub-steps:

[0113] S6021. Obtain the battery current based on the predicted speed and SOC.

[0114] The driving power can be obtained based on the predicted speed. The driving power of the target vehicle's battery can be obtained through the matching curve between the vehicle's speed and the powertrain. Optionally, artificial intelligence algorithms can be used to combine information such as navigation, road conditions, and altitude to weight and adjust the matching curve between the vehicle's speed and the powertrain, thereby improving the accuracy of the matching curve.

[0115] Then, based on the current SOC and the correlation function between SOC and battery voltage, the battery voltage for the current cycle is obtained. After obtaining the battery voltage for the current cycle, the battery current can be obtained based on the driving power and battery voltage. Specifically, the above formula (2) can be transformed into the following formula (3):

[0116] E self-heat,i+1= =(P drive, i / U current, i (SOC i )) 2 *R DCIR (T current,i SOC i )*Δt (3)

[0117] Among them, P drive, i U represents the driving power for the current cycle. current, i (SOC i The current battery voltage is obtained based on the current cycle's SOC.

[0118] S6022. Obtain the battery internal resistance based on battery temperature and SOC.

[0119] As shown in formulas (2) and (3) above, the battery resistance can be obtained from the current cycle battery temperature, the current cycle SOC, and a correlation function of battery temperature, SOC, and battery resistance. This correlation function is based on the battery's own parameters and can be obtained in advance through experiments.

[0120] S6023. Based on the battery current and battery internal resistance, obtain the predicted heat generation of the battery.

[0121] S603: Based on battery parameters, ambient temperature, and battery temperature of the current cycle, obtain the predicted battery heat dissipation for the current cycle.

[0122] The heat dissipation of a battery is affected by its heat dissipation coefficient, surface area, ambient temperature, and battery temperature. For example, a higher heat dissipation coefficient results in greater heat dissipation. A larger battery surface area also results in greater heat dissipation. Furthermore, a significant temperature difference between the ambient and battery temperatures leads to greater heat dissipation.

[0123] Therefore, the predicted heat dissipation of the battery can be obtained based on the battery's heat dissipation coefficient, surface area, ambient temperature, and battery temperature, which are included in the battery parameters.

[0124] For example, the predicted battery heat dissipation can be expressed by the following formula (4):

[0125] E rejection, i =h(v i )*A pack *(T current, i -T temp )*Δt (4)

[0126] Among them, E rejection, i h(v) represents the predicted battery heat dissipation during the current cycle, specifically the predicted battery heat dissipation from the start to the end of the current cycle. i ) represents the heat dissipation coefficient of the battery, A pack T represents the surface area of ​​the battery. current, i T represents the battery temperature during the current cycle. temp The ambient temperature.

[0127] Among these, the faster the target vehicle travels, the greater the battery's heat dissipation coefficient. Therefore, the battery's heat transfer coefficient h(v) i The heat transfer coefficient h(v) is related not only to the battery's structure and materials but also to the predicted speed. i This is a function related to the predicted speed. The heat transfer coefficient of the battery in the current cycle can be obtained based on the heat transfer coefficient parameter in the battery parameters and the predicted speed of the target vehicle.

[0128] S604. Based on the predicted battery heat generation, predicted battery heat dissipation, and battery temperature of the current cycle, predict the battery temperature for the next cycle.

[0129] Based on the predicted battery heat generation and heat dissipation for the current cycle, the battery temperature change for the current cycle is predicted. Based on the current battery temperature and the predicted battery temperature change for the current cycle, the battery temperature for the next cycle is predicted. In other words, the battery temperature for the next cycle can be predicted by subtracting the predicted battery temperature change for the current cycle from the current battery temperature value.

[0130] Specifically, the battery temperature for the next cycle can be predicted based on the predicted battery heat generation, predicted battery heat dissipation, battery specific heat capacity, battery mass, and battery temperature. For example, this implementation can be represented by the following formula (5):

[0131] T current, no heating, i+1

[0132] =(E self-heat, no heating, i -E rejection, no heating, i ) / (c battery *m battery )+T current, no heating, i (5)

[0133] Among them, T current, no heating, i+1 E represents the battery temperature at the start of the next cycle. self-heat, no heating, i E represents the predicted battery heat generation during the current cycle, specifically the heat generation from the start to the end of cycle i. rejection, no heating, i Let c be the predicted battery heat dissipation during the current cycle, i.e., the heat dissipation from the start of cycle i to the end of cycle i. battery For the specific heat capacity of the battery, m battery For the quality of the battery, T current, no heating, i This represents the battery temperature at the start of the current cycle.

[0134] Figure 7 This is a schematic flowchart illustrating another battery heating control method provided in an embodiment of this application. Figure 7As shown, based on the remaining battery energy in the current cycle, the battery temperature in the next cycle, and the predicted speed, the remaining battery energy in the next cycle is predicted. Specifically, this can include:

[0135] S701. Based on the predicted speed, obtain the energy consumption for the next cycle of driving.

[0136] Based on the predicted speed of the target vehicle in the next cycle, determine the output power of the target vehicle's battery when the target vehicle travels at the predicted speed, i.e., the driving power. Based on this driving power and the duration of the next cycle, obtain the driving energy consumption for the next cycle.

[0137] The driving power of the target vehicle's battery can be obtained based on the matching curve of the vehicle's speed and power system. The driving energy consumption for the next cycle can be expressed by the following formula (6):

[0138] E drive, i+1 =P drive, i+1 *Δt (6)

[0139] Among them, E drive, i+1 For the energy consumption of driving in the next cycle, P drive, i+1 Δt represents the driving power for the next cycle, and Δt represents the duration of the next cycle.

[0140] S702. Obtain the driving energy consumption coefficient for the next cycle based on the battery temperature of the next cycle.

[0141] Because battery discharge efficiency is lower at lower battery temperatures, a lower-temperature battery will consume more energy while traveling the same distance. Therefore, it is necessary to adjust for energy consumption based on a battery temperature-related energy consumption coefficient to improve the accuracy of predicted battery energy levels.

[0142] Specifically, the correlation between driving energy consumption coefficient and battery temperature can be obtained in advance through experiments. For example, the battery discharge energy efficiency can be obtained at several preset specific temperatures (such as 25℃, 0℃, -10℃, -20℃, etc.), and the correlation between driving energy consumption coefficient and battery temperature can be generated based on the discharge energy efficiency at different temperatures.

[0143] Optionally, the correlation data between the driving energy consumption coefficient and the battery temperature can be fitted into a function curve to obtain the driving energy consumption coefficient for the next cycle based on the battery temperature in the next cycle. Alternatively, if the battery temperature in the next cycle does not fall under a specific temperature in the correlation, the driving energy consumption coefficient for the next cycle corresponding to the battery temperature can be obtained through linear interpolation or other methods based on the correlation between the driving energy consumption coefficient and the battery temperature.

[0144] S703. Based on driving energy consumption and driving energy consumption coefficient, predict the energy consumption for the next cycle.

[0145] By adjusting the driving energy consumption coefficient related to battery temperature, the accuracy of predicting energy consumption in the next cycle can be improved at that battery temperature.

[0146] Specifically, this step can be achieved using the following formula (7):

[0147] E total, no heating, i+1 '=E total, no heating, i+1 / β(T current, i+1 (7)

[0148] Among them, E total, no heating, i+1 'E' is the energy consumption for the next cycle. total, no heating, i+1 For the energy consumption of driving in the next cycle, β(T) current, i+1 () is the driving energy consumption coefficient related to battery temperature.

[0149] S704. Based on the remaining battery energy in the current cycle and the energy consumption in the next cycle, predict the remaining battery energy in the next cycle.

[0150] The remaining battery energy for the next cycle can be predicted by subtracting the energy consumption for the next cycle from the remaining battery energy for the current cycle.

[0151] The method provided in this application comprehensively considers factors such as the impact of battery temperature on the driving process and driving energy consumption, as well as the impact of the driving process on battery temperature, thereby improving the accuracy of obtaining predicted driving data and thus improving the accuracy of the reference mileage obtained based on the predicted driving data.

[0152] Obtain the second predicted driving data:

[0153] Figure 8 This is a schematic flowchart illustrating another battery heating control method provided in an embodiment of this application. Figure 8 As shown, the aforementioned step S401 may specifically include:

[0154] S801, obtain the initial remaining energy of the battery, the initial temperature of the battery, the battery parameters, the ambient temperature, the battery heating power, and the predicted speed of the target vehicle.

[0155] In this step, the battery heating power refers to the power required to heat the battery. For example, when heating the battery, the battery performs active heating operation using a rated heating power, which can be used as the battery heating power. This battery heating power can be a preset value, obtained from the battery's parameters or the battery management system.

[0156] For other terms and their acquisition methods in this step, please refer to the aforementioned step S501, which will not be repeated here.

[0157] S802. Based on the battery's initial remaining energy, initial battery temperature, battery heating power, predicted speed, ambient temperature, and battery parameters, predict the battery temperature and remaining battery energy for the current cycle.

[0158] In this step, because the battery is under heating, the battery temperature change is additionally affected by the battery heating behavior compared to the situation in step S502 where the battery is not heated, i.e., it is additionally affected by the battery heating power. Therefore, when predicting the battery temperature for the current cycle, it is necessary to add a battery heating power factor.

[0159] Furthermore, when predicting battery energy consumption and remaining energy, battery heating causes additional energy consumption. Therefore, when calculating the total battery energy consumption, in addition to driving energy consumption, it is also necessary to predict the energy consumption caused by battery heating. The total battery energy consumption is calculated by summing driving energy consumption and energy consumption caused by battery heating. Then, the remaining battery energy for the current cycle is predicted based on the difference between the initial remaining battery energy and the total battery energy consumption.

[0160] S803: Based on the current cycle's battery temperature, battery heating power, predicted speed, ambient temperature, battery parameters, and remaining battery energy, predict the battery temperature and remaining battery energy for the next cycle.

[0161] In this step, the battery temperature of the current cycle is used instead of the initial battery temperature in step S802, and the remaining battery energy of the current cycle is used instead of the initial remaining energy in step S802. Then, the battery temperature and remaining battery energy of the next cycle are predicted using the prediction method in S802.

[0162] That is, referring to S802, the battery temperature for the next cycle can be predicted based on the battery temperature, battery heating power, predicted speed, ambient temperature, and battery parameters of the current cycle. The remaining battery energy for the next cycle can be predicted based on the remaining battery energy of the current cycle, battery heating power, the battery temperature for the next cycle, and the predicted speed.

[0163] S804, iterative calculation until the remaining battery energy is the target value.

[0164] This step can be referred to as step S504 above, and will not be repeated here.

[0165] Optionally, during the iterative calculation, the purpose of battery heating is to reduce the time the battery spends in a low-temperature environment, allowing it to reach its ideal temperature more quickly. Therefore, once the battery temperature reaches the target temperature through battery heating, the heating can be stopped. When battery heating is stopped, the battery heating power is 0. Therefore, the battery temperature needs to be monitored during iteration; if the battery temperature reaches the target temperature, the battery heating power needs to be set to 0 to simulate the realistic situation of stopping battery heating.

[0166] S805. Based on the remaining battery energy and predicted driving range corresponding to each cycle in the iterative calculation, obtain the second predicted driving data of the target vehicle in the battery heating state. The predicted driving range is obtained based on the predicted speed.

[0167] The predicted mileage is obtained based on the predicted speed. This predicted mileage is calculated based on the predicted speed and the duration of each cycle. For example, the mileage within each cycle is obtained by producting the predicted speed used in each cycle with the corresponding duration of each cycle. Based on the time sequence of each cycle, the mileage within each cycle is accumulated to obtain the predicted mileage for that cycle (i.e., the mileage within that cycle and the cumulative sum of the mileage in all previous cycles).

[0168] Record the remaining battery energy and the predicted driving range for each cycle in the iterative calculation, and generate the second predicted driving data of the target vehicle in the battery heating state based on the remaining battery energy and the predicted driving range for each cycle.

[0169] It should be understood that when a battery is heated, its temperature change is related to the heat generated, the heat dissipated, and the amount of heat generated during operation. Therefore, the battery temperature change can be predicted based on the predicted heat generation, heat dissipation, and heating of the battery in each cycle. Furthermore, based on the battery temperature change and the battery temperature at the beginning of each cycle, the predicted battery temperature at the end of each cycle (i.e., the start of the next cycle) can be obtained.

[0170] Figure 9 This is a schematic flowchart illustrating another battery heating control method provided in an embodiment of this application. Figure 9 As shown, based on the current cycle's battery temperature, battery heating power, predicted speed, ambient temperature, and battery parameters, the battery temperature for the next cycle is predicted. Specifically, this can include:

[0171] S901, Get the SOC of the current cycle.

[0172] The implementation method of this step can refer to the aforementioned step S601, and will not be repeated here.

[0173] S902. Based on the battery temperature, SOC, and predicted speed of the current cycle, obtain the predicted battery heat generation for the current cycle.

[0174] The implementation method of this step can refer to the aforementioned step S602, and will not be repeated here.

[0175] S903: Based on battery parameters, ambient temperature, and battery temperature of the current cycle, obtain the predicted battery heat dissipation for the current cycle.

[0176] The implementation method of this step can refer to the aforementioned step S603, and will not be repeated here.

[0177] S904. Obtain the effective battery heating amount for the current cycle based on the battery heating power.

[0178] The effective battery heating amount for the current cycle is calculated based on the battery heating power and the duration of the current cycle (i.e., the equivalent battery heating time). Specifically, the effective battery heating amount for the current cycle can be calculated by multiplying the battery heating power by the duration of the current cycle.

[0179] Optionally, the battery's heating efficiency can be further considered. This means that energy consumption corresponding to the battery's heating power is subject to loss, and the heating amount calculated solely based on the battery's heating power cannot be entirely used to heat the battery. This implementation can be achieved through the following sub-steps:

[0180] S9041. Obtain the heating efficiency of the battery heating system.

[0181] The heating efficiency of a battery heating system reflects the proportion of input energy converted into effective heating energy. To obtain the heating efficiency of a battery heating system, this efficiency can be determined beforehand through experiments. In other words, the heating efficiency is the ratio between the actual energy consumed by the battery and the energy used for heating.

[0182] S9042. Obtain the actual energy consumption of battery heating based on the battery heating power.

[0183] Based on the battery heating power and the duration of the current cycle (i.e., the equivalent battery heating time), the actual energy consumption for battery heating in the current cycle (including the energy consumed for heating and the energy lost) is calculated. Specifically, the actual energy consumption for battery heating in the current cycle can be calculated by producting the battery heating power and the duration of the current cycle.

[0184] S9043. Obtain the effective battery heating amount for the current cycle based on the product of the actual energy consumption of battery heating and the heating efficiency.

[0185] Since the heating efficiency is the quotient of the energy consumed for heating and the actual energy consumed by the battery for heating, the effective battery heating amount for the current cycle can be obtained by multiplying the actual energy consumed by the battery for heating by the heating efficiency.

[0186] S905. Based on the predicted battery heat generation, predicted battery heat dissipation, effective battery heating, and battery temperature of the current cycle, predict the battery temperature for the next cycle.

[0187] Based on the predicted battery heat generation, predicted battery heat dissipation, and effective battery heating for the current cycle, the battery temperature change for the current cycle is predicted. Based on the current battery temperature and the predicted battery temperature change for the current cycle, the battery temperature for the next cycle is predicted. In other words, the battery temperature for the next cycle can be predicted by subtracting the predicted battery temperature change for the current cycle from the current battery temperature value.

[0188] Specifically, the battery temperature for the next cycle can be predicted based on the predicted battery heat generation, predicted battery heat dissipation, effective battery heating, battery specific heat capacity, battery mass, and battery temperature. For example, this implementation can be represented by the following formula (8):

[0189] T current, heatingt, i+1

[0190] =(E self-heat, heating, i -E rejection, heating, i +E heating, i *η heating ) / (c battery *m battery )

[0191] +T current, heating, i (8)

[0192] Among them, T current, heatingt, i+1 E represents the battery temperature at the start of the next cycle under battery heating conditions. self-heat, heating, i E represents the predicted battery heat generation during the current cycle. rejection, heating, i E represents the predicted battery heat dissipation during the current cycle, indicating the battery heating situation. heating, i η represents the actual energy consumption for battery heating during the current cycle. heating For the heating efficiency of the battery heating system, c battery For the specific heat capacity of the battery, m battery For the quality of the battery, T current, heating, i The battery temperature at the start of the current cycle, indicating the battery heating status.

[0193] Figure 10 This is a schematic flowchart illustrating another battery heating control method provided in an embodiment of this application. Figure 10As shown, based on the remaining battery energy in the current cycle, the battery temperature in the next cycle, the battery heating power, and the predicted speed, the remaining battery energy in the next cycle is predicted. Specifically, this can include:

[0194] S1001. Obtain the actual energy consumption of battery heating in the next cycle based on the battery heating power.

[0195] Based on the battery heating power in the next cycle, determine the output power of the battery heating system when heating the battery, i.e., the battery heating power. Based on this battery heating power and the duration of the next cycle, obtain the actual energy consumption for battery heating in the next cycle.

[0196] S1002. Based on the predicted speed, obtain the energy consumption for the next cycle of driving.

[0197] The implementation method of this step can refer to the aforementioned step S701, and will not be repeated here.

[0198] S1003. Based on the battery temperature of the next cycle, obtain the driving energy consumption coefficient for the next cycle.

[0199] The implementation method of this step can refer to the aforementioned step S702, and will not be repeated here.

[0200] S1004. Based on driving energy consumption, driving energy consumption coefficient, and actual battery heating energy consumption, predict the energy consumption for the next cycle.

[0201] By adjusting the driving energy consumption coefficient related to battery temperature, the accuracy of predicting energy consumption in the next cycle can be improved at that battery temperature.

[0202] Specifically, this step can be achieved using the following formula (9):

[0203] E total, heating, i+1 '=(E drive, i+1 +E heating, i+1 ) / β(T current, i+1 (9)

[0204] Among them, E total, heating, i+1 'E' represents the energy consumption for the next cycle when the battery is heated. drive, i+1 For the energy consumption of the next driving cycle, E heating, i+1 β(T) represents the actual energy consumption for battery heating in the next cycle under battery heating conditions. current, i+1 () is the driving energy consumption coefficient related to battery temperature.

[0205] S1005. Based on the remaining battery energy in the current cycle and the energy consumption in the next cycle, predict the remaining battery energy in the next cycle.

[0206] The remaining battery energy for the next cycle can be predicted by subtracting the energy consumption for the next cycle from the remaining battery energy for the current cycle.

[0207] The method provided in this application, by considering the impact of battery temperature on driving process and driving energy consumption, and the impact of driving process on battery temperature, further considers the impact of battery heating on battery temperature and the impact of battery heating on battery energy consumption, comprehensively considers factors that predict the future driving data of the target vehicle under battery heating conditions, improves the accuracy of obtaining the second predicted driving data, and thus improves the accuracy of the reference mileage obtained based on the second predicted driving data.

[0208] Figure 11 This is a schematic flowchart illustrating another battery heating control method provided in an embodiment of this application. Figure 11 As shown, the method may further include:

[0209] S1101. When the iterative calculation continues until the remaining battery energy is 0, determine the predicted driving time corresponding to the remaining battery energy being 0.

[0210] When the iterative calculation continues until the remaining battery energy reaches 0, it indicates that the battery's remaining energy is exhausted and can no longer support the target vehicle's continued operation. Since the calculation is performed iteratively based on cycles, the predicted driving time corresponding to the remaining battery energy reaching 0 can be calculated based on the number of cycles until the remaining battery energy reaches 0, and the duration of each cycle.

[0211] If the duration of each cycle is the same, the predicted driving time when the remaining battery energy is 0 can be determined by the product of the number of cycles and the duration of each cycle. If the duration of each cycle is the same, the predicted driving time when the remaining battery energy is 0 can be determined by the sum of the durations of all cycles.

[0212] S1102. Based on the predicted travel time and the predicted speed, determine the estimated remaining mileage of the target vehicle.

[0213] One possible implementation is that the predicted speed is the same for each cycle, in which case the estimated remaining mileage of the target vehicle can be calculated based on the product of the predicted travel time and the predicted speed.

[0214] Another possible implementation is that the predicted speeds for each cycle are different. In this case, the mileage for each cycle can be calculated based on the predicted speed and the duration of each cycle, and the estimated remaining mileage of the target vehicle can be calculated by summing the mileage for all cycles. Alternatively, the estimated remaining mileage of the target vehicle can be determined by multiplying the mean, median, or other values ​​of the predicted speeds for these cycles with the predicted travel time.

[0215] The method provided in this application embodiment, when iterative calculation continues until the remaining battery energy is 0, determines the predicted driving time corresponding to the remaining battery energy being 0, and determines the estimated remaining mileage of the target vehicle based on the predicted driving time and the predicted speed. In the iterative process, not only is a reference mileage used to determine whether to heat the battery determined, but also the driving range of the target vehicle under the conditions of battery heating and battery not heating is predicted based on the prediction iteration, thereby improving the accuracy of driving range prediction.

[0216] Figure 12 This is a schematic diagram of a battery heating control device provided in an embodiment of this application. Figure 12 As shown, the battery heating control device may include: an acquisition module 11 and a processing module 12. In one possible implementation, it may also include: an output module 13.

[0217] The acquisition module 11 is used to acquire reference mileage when the target vehicle's battery is in a low-temperature environment.

[0218] The processing module 12 is used to heat the battery if the estimated remaining mileage of the target vehicle in this trip is greater than or equal to the reference mileage.

[0219] Optionally, the acquisition module 11 is specifically used to acquire first predicted driving data of the target vehicle when the battery is not heated, and second predicted driving data of the target vehicle when the battery is heated. A reference mileage is obtained based on the first and second predicted driving data. The first predicted driving data includes first remaining energy data and first mileage data, and the second predicted driving data includes second remaining energy data and second mileage data.

[0220] Optionally, the acquisition module 11 is specifically used to determine a target point based on the first remaining energy data, the first mileage data, the second remaining energy data, and the second mileage data. A reference mileage is determined based on the mileage corresponding to the target point. The target point is a point where the first remaining energy data and the second remaining energy data are the same, and the first mileage data and the second mileage data are the same.

[0221] Optionally, the acquisition module 11 is specifically used to acquire the initial remaining energy of the battery, the initial battery temperature, battery parameters, ambient temperature, and the predicted speed of the target vehicle. The processing module 12 is specifically used to predict the battery temperature and remaining energy for the current cycle based on the initial remaining energy, initial battery temperature, predicted speed, ambient temperature, and battery parameters. Based on the current cycle's battery temperature, predicted speed, ambient temperature, battery parameters, and remaining energy, it predicts the battery temperature and remaining energy for the next cycle. Iterative calculations are performed until the remaining battery energy reaches the target value. Based on the remaining battery energy and predicted driving range corresponding to each cycle in the iterative calculations, the first predicted driving data of the target vehicle in a battery-unheated state is acquired, with the predicted driving range obtained based on the predicted speed.

[0222] Optionally, the processing module 12 is specifically used to predict the battery temperature for the next cycle based on the battery temperature, predicted speed, ambient temperature, and battery parameters of the current cycle. It also predicts the remaining battery energy for the next cycle based on the remaining battery energy of the current cycle, the battery temperature for the next cycle, and the predicted speed.

[0223] Optionally, processing module 12 is specifically used to obtain the battery state of charge (SOC) for the current cycle. Based on the battery temperature, SOC, and predicted speed for the current cycle, it obtains the predicted battery heat generation for the current cycle. Based on battery parameters, ambient temperature, and the battery temperature for the current cycle, it obtains the predicted battery heat dissipation for the current cycle. Based on the predicted battery heat generation, predicted battery heat dissipation, and battery temperature for the current cycle, it predicts the battery temperature for the next cycle.

[0224] Optionally, processing module 12 is specifically used to obtain the battery current based on the predicted speed and SOC; to obtain the battery internal resistance based on the battery temperature and SOC; and to obtain the predicted battery heat generation based on the battery current and battery internal resistance.

[0225] Optionally, processing module 12 is specifically used to obtain the battery's driving power based on the predicted speed, obtain the battery voltage based on the SOC, and obtain the battery current based on the driving power and battery voltage.

[0226] Optionally, when the battery parameters include the battery's heat transfer coefficient and surface area, the processing module 12 is specifically used to obtain the predicted battery heat dissipation based on the heat dissipation coefficient, surface area, ambient temperature, and battery temperature.

[0227] Optionally, when the battery parameters also include battery specific heat capacity and battery mass, the processing module 12 is specifically used to predict the battery temperature for the next cycle based on the predicted battery heat generation, predicted battery heat dissipation, battery specific heat capacity, battery mass, and battery temperature.

[0228] Optionally, processing module 12 is specifically used to obtain the driving energy consumption for the next cycle based on the predicted speed; obtain the driving energy consumption coefficient for the next cycle based on the battery temperature for the next cycle; predict the energy consumption for the next cycle based on the driving energy consumption and the driving energy consumption coefficient; and predict the remaining battery energy for the next cycle based on the remaining battery energy for the current cycle and the energy consumption for the next cycle.

[0229] Optionally, the acquisition module 11 is specifically used to acquire the initial remaining energy of the battery, the initial battery temperature, battery parameters, ambient temperature, battery heating power, and the predicted speed of the target vehicle. The processing module 12 is specifically used to predict the battery temperature and remaining energy for the current cycle based on the initial remaining energy, initial battery temperature, battery heating power, predicted speed, ambient temperature, and battery parameters. Based on the current cycle's battery temperature, battery heating power, predicted speed, ambient temperature, battery parameters, and remaining energy, it predicts the battery temperature and remaining energy for the next cycle. Iterative calculations are performed until the remaining battery energy reaches the target value. Based on the remaining battery energy and predicted driving range corresponding to each cycle in the iterative calculations, the second predicted driving data of the target vehicle in the battery heating state is acquired, with the predicted driving range obtained based on the predicted speed.

[0230] Optionally, the processing module 12 is specifically used to predict the battery temperature for the next cycle based on the battery temperature, battery heating power, prediction speed, ambient temperature, and battery parameters of the current cycle. It also predicts the remaining battery energy for the next cycle based on the remaining battery energy of the current cycle, the battery temperature for the next cycle, the battery heating power, and the prediction speed.

[0231] Optionally, processing module 12 is specifically used to obtain the SOC of the current cycle. Based on the battery temperature, SOC, and predicted speed of the current cycle, it obtains the predicted battery heat generation for the current cycle. Based on battery parameters, ambient temperature, and the battery temperature of the current cycle, it obtains the predicted battery heat dissipation for the current cycle. Based on the battery heating power, it obtains the effective battery heating amount for the current cycle. Based on the predicted battery heat generation, predicted battery heat dissipation, effective battery heating amount, and battery temperature of the current cycle, it predicts the battery temperature for the next cycle.

[0232] Optionally, processing module 12 is specifically used to obtain the battery current based on the predicted speed and SOC; to obtain the battery internal resistance based on the battery temperature and SOC; and to obtain the predicted battery heat generation based on the battery current and battery internal resistance.

[0233] Optionally, processing module 12 is specifically used to obtain the battery's driving power based on the predicted speed, obtain the battery voltage based on the SOC, and obtain the battery current based on the driving power and battery voltage.

[0234] Optionally, when the battery parameters include the battery's heat transfer coefficient and surface area, the processing module 12 is specifically used to obtain the predicted battery heat dissipation based on the heat dissipation coefficient, surface area, ambient temperature, and battery temperature.

[0235] Optionally, processing module 12 is specifically used to obtain the heating efficiency of the battery heating system. Based on the battery heating power, it obtains the actual energy consumption of battery heating. Based on the product of the actual energy consumption and the heating efficiency, it obtains the effective battery heating amount for the current cycle.

[0236] Optionally, when the battery parameters also include battery specific heat capacity and battery mass, the processing module 12 is specifically used to predict the battery temperature for the next cycle based on the predicted battery heat generation, predicted battery heat dissipation, effective battery heating, battery specific heat capacity, battery mass, and battery temperature.

[0237] Optionally, processing module 12 is specifically used to: obtain the actual energy consumption of battery heating in the next cycle based on the battery heating power; obtain the driving energy consumption in the next cycle based on the predicted speed; obtain the driving energy consumption coefficient in the next cycle based on the battery temperature in the next cycle; predict the energy consumption in the next cycle based on the driving energy consumption, the driving energy consumption coefficient, and the actual energy consumption of battery heating; and predict the remaining battery energy in the next cycle based on the remaining battery energy in the current cycle and the energy consumption in the next cycle.

[0238] Optionally, during the iterative calculation process, when the battery temperature reaches the target temperature, the processing module 12 is also used to set the battery heating power to 0.

[0239] Optionally, the processing module 12 is specifically used to obtain the SOC of the current cycle based on the battery's effective remaining capacity and rated capacity. The battery's effective capacity of the current cycle is related to the battery's remaining energy of the current cycle and the battery voltage of the previous cycle, while the battery voltage of the previous cycle is related to the SOC of the previous cycle.

[0240] Optionally, the processing module 12 is specifically used to obtain the SOC of the current cycle based on the quotient of the effective remaining capacity of the battery in the current cycle and the rated capacity of the battery.

[0241] Optionally, the acquisition module 11 is specifically used to acquire the battery's effective remaining capacity and battery voltage at the initial moment. The processing module 12 is specifically used to acquire the battery's initial remaining energy based on the battery's effective remaining capacity and battery voltage at the initial moment.

[0242] Optionally, the acquisition module 11 is specifically used to acquire the battery's rated capacity and the initial state of charge (SOC). The processing module 12 is specifically used to acquire the battery's effective remaining capacity at the initial moment based on the battery's rated capacity and the initial SOC. The processing module 12 is also specifically used to acquire the battery voltage at the initial moment based on the initial SOC.

[0243] Optionally, the acquisition module 11 is also used to acquire the estimated remaining mileage of the target vehicle during this trip.

[0244] Optionally, the acquisition module 11 is specifically used to obtain the estimated remaining mileage based on the navigation information of the target vehicle's current journey, or to obtain the estimated remaining mileage of the target vehicle's current journey in response to user input.

[0245] Optionally, after obtaining the reference mileage, the output module 13 outputs the reference mileage. The processing module 12 is also configured to heat the battery if a battery heating confirmation message is received, and not heat the battery if no battery heating confirmation message is received.

[0246] Optionally, if no battery heating confirmation information is received and the actual mileage traveled by the target vehicle this time is greater than the reference mileage, the processing module 12 is also used to heat the battery.

[0247] Optionally, when the iterative calculation continues until the remaining battery energy is 0, the processing module 12 is further configured to determine the predicted driving time corresponding to the remaining battery energy being 0. Based on the predicted driving time and the predicted speed, the estimated remaining range of the target vehicle is determined.

[0248] Optionally, if a reference mileage cannot be obtained, or if the estimated remaining mileage is less than the reference mileage, the processing module 12 is also used to prevent the battery from being heated.

[0249] Optionally, the acquisition module 11 is further configured to acquire the battery temperature of the target vehicle before acquiring the reference mileage. The processing module 12 is further configured to determine that the battery of the target vehicle is in a low-temperature environment if the battery temperature is less than or equal to a first temperature threshold.

[0250] Optionally, the acquisition module 11 is further configured to acquire the battery temperature and initial SOC of the target vehicle before acquiring the reference mileage. The processing module 12 is further configured to determine that the battery of the target vehicle is in a low-temperature environment if the initial SOC is greater than or equal to a preset SOC threshold and the battery temperature is less than or equal to a second temperature threshold.

[0251] The battery heating control device provided in this application embodiment can execute the battery heating control method in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described again here.

[0252] Figure 13 This is a schematic diagram of an electronic device provided in an embodiment of this application. The electronic device is used to execute the aforementioned battery heating control method, and may be, for example, the aforementioned electronic device with data processing capabilities. Figure 13 As shown, the electronic device 1300 may include at least one processor 1301, a memory 1302, and a communication interface 1303.

[0253] The memory 1302 is used to store programs. Specifically, the program may include program code, which includes computer operation instructions.

[0254] The memory 1302 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage.

[0255] The processor 1301 is used to execute computer execution instructions stored in the memory 1302 to implement the method described in the foregoing method embodiments. The processor 1301 may be a CPU, an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0256] The processor 1301 can communicate and interact with external devices through the communication interface 1303. These external devices can be, for example, the aforementioned battery management system. In specific implementations, if the communication interface 1303, memory 1302, and processor 1301 are implemented independently, they can be interconnected via a bus to complete communication. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc., but this does not imply that there is only one bus or one type of bus.

[0257] Optionally, in a specific implementation, if the communication interface 1303, memory 1302 and processor 1301 are integrated on a single chip, then the communication interface 1303, memory 1302 and processor 1301 can communicate through an internal interface.

[0258] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0259] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0260] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0261] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0262] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0263] 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.

[0264] In addition, the functional units in the various embodiments of 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.

[0265] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this 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 a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this 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.

[0266] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0267] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A battery heating control method, characterized in that, include: When the battery of the target vehicle is in a low temperature environment, the first predicted driving data of the target vehicle in the battery unheated state and the second predicted driving data of the target vehicle in the battery heated state are obtained. The first predicted driving data includes first remaining energy data and first mileage data, and the second predicted driving data includes second remaining energy data and second mileage data. Based on the first remaining energy data, the first mileage data, the second remaining energy data, and the second mileage data, a target point is determined, wherein the target point is the point where the first remaining energy data and the second remaining energy data are the same, and the first mileage data and the second mileage data are the same; Based on the mileage corresponding to the target point, obtain the reference mileage; If the estimated remaining mileage of the target vehicle in this trip is greater than or equal to the reference mileage, then the battery is heated. The step of obtaining the first predicted driving data of the target vehicle in the state where the battery is not heated includes: The initial remaining energy of the battery, the initial battery temperature, battery parameters, ambient temperature, and the predicted speed of the target vehicle are obtained. Based on the battery's initial remaining energy, the battery's initial temperature, the predicted speed, the ambient temperature, and the battery parameters, predict the battery temperature and remaining energy for the current cycle. Based on the current cycle's battery temperature, the predicted speed, the ambient temperature, and the battery parameters, predict the battery temperature for the next cycle; Based on the predicted speed, the energy consumption for the next cycle is obtained; Based on the battery temperature of the next cycle, obtain the driving energy consumption coefficient for the next cycle; Based on the driving energy consumption and the driving energy consumption coefficient, predict the energy consumption for the next cycle; Based on the remaining battery energy in the current cycle and the energy consumption in the next cycle, predict the battery temperature and remaining battery energy in the next cycle; The calculation is iterative until the remaining energy of the battery reaches the target value; Based on the remaining battery energy and predicted driving range corresponding to each cycle in the iterative calculation, the first predicted driving range of the target vehicle in the state of battery non-heating is obtained, and the predicted driving range is obtained based on the predicted speed.

2. The method according to claim 1, characterized in that, The step of predicting the battery temperature for the next cycle based on the current cycle's battery temperature, the predicted speed, the ambient temperature, and the battery parameters includes: Obtain the battery state of charge (SOC) for the current cycle; Based on the battery temperature of the current cycle, the SOC, and the predicted speed, obtain the predicted battery heat generation for the current cycle; Based on the battery parameters, the ambient temperature, and the battery temperature of the current cycle, obtain the predicted battery heat dissipation for the current cycle; Based on the predicted battery heat generation, predicted battery heat dissipation, and battery temperature of the current cycle, the battery temperature of the next cycle is predicted.

3. The method according to claim 2, characterized in that, The step of obtaining the predicted battery heat generation for the current cycle based on the battery temperature, the SOC, and the predicted speed includes: The battery current is obtained based on the predicted speed and the SOC. The battery internal resistance is obtained based on the battery temperature and the state of charge (SOC). The predicted heat generation of the battery is obtained based on the battery current and the battery internal resistance.

4. The method according to claim 3, characterized in that, The step of obtaining the battery current based on the predicted speed and the SOC includes: The driving power of the battery is obtained based on the predicted speed; Based on the SOC, obtain the battery voltage of the battery; The battery current is obtained based on the driving power and the battery voltage.

5. The method according to claim 4, characterized in that, The battery parameters include the battery's heat dissipation coefficient and the battery's surface area; obtaining the predicted battery heat dissipation for the current cycle based on the battery parameters, the ambient temperature, and the battery temperature for the current cycle includes: The predicted battery heat dissipation is obtained based on the heat dissipation coefficient, the surface area, the ambient temperature, and the battery temperature.

6. The method according to claim 5, characterized in that, The battery parameters also include battery specific heat capacity and battery mass; predicting the battery temperature for the next cycle based on the predicted battery heat generation, the predicted battery heat dissipation, and the battery temperature for the current cycle includes: The battery temperature for the next cycle is predicted based on the predicted battery heat generation, the predicted battery heat dissipation, the battery specific heat capacity, the battery mass, and the battery temperature.

7. The method according to claim 1, characterized in that, Obtaining the second predicted driving data of the target vehicle in a battery-heated state includes: The initial remaining energy of the battery, the initial temperature of the battery, the battery parameters, the ambient temperature, the battery heating power, and the predicted speed of the target vehicle are obtained. Based on the battery's initial remaining energy, initial battery temperature, battery heating power, predicted speed, ambient temperature, and battery parameters, predict the battery temperature and remaining battery energy for the current cycle. Based on the battery temperature of the current cycle, the battery heating power, the predicted speed, the ambient temperature, the battery parameters, and the remaining battery energy, predict the battery temperature and remaining battery energy for the next cycle. The calculation is iterative until the remaining energy of the battery reaches the target value; Based on the remaining battery energy and predicted driving range corresponding to each cycle in the iterative calculation, the second predicted driving data of the target vehicle in the battery heating state is obtained, and the predicted driving range is obtained based on the predicted speed.

8. The method according to claim 7, characterized in that, The step of predicting the battery temperature and remaining battery energy for the next cycle based on the current cycle's battery temperature, battery heating power, predicted speed, ambient temperature, battery parameters, and remaining battery energy includes: Based on the battery temperature of the current cycle, the battery heating power, the predicted speed, the ambient temperature, and the battery parameters, predict the battery temperature for the next cycle. The remaining battery energy for the next cycle is predicted based on the remaining battery energy in the current cycle, the battery temperature for the next cycle, the battery heating power, and the predicted speed.

9. The method according to claim 8, characterized in that, The step of predicting the battery temperature for the next cycle based on the battery temperature of the current cycle, the battery heating power, the predicted speed, the ambient temperature, and the battery parameters includes: Obtain the SOC of the current cycle; Based on the battery temperature of the current cycle, the SOC, and the predicted speed, obtain the predicted battery heat generation for the current cycle; Based on the battery parameters, the ambient temperature, and the battery temperature of the current cycle, obtain the predicted battery heat dissipation for the current cycle; Based on the battery heating power, the effective battery heating amount for the current cycle is obtained; Based on the predicted battery heat generation, predicted battery heat dissipation, effective battery heating, and battery temperature of the current cycle, the battery temperature of the next cycle is predicted.

10. The method according to claim 9, characterized in that, The step of obtaining the predicted battery heat generation for the current cycle based on the battery temperature, the SOC, and the predicted speed includes: The battery current is obtained based on the predicted speed and the SOC. The battery internal resistance is obtained based on the battery temperature and the state of charge (SOC). The predicted heat generation of the battery is obtained based on the battery current and the battery internal resistance.

11. The method according to claim 10, characterized in that, The step of obtaining the battery current based on the predicted speed and the SOC includes: The driving power of the battery is obtained based on the predicted speed; Based on the SOC, obtain the battery voltage of the battery; The battery current is obtained based on the driving power and the battery voltage.

12. The method according to claim 11, characterized in that, The battery parameters include the battery's heat dissipation coefficient and the battery's surface area; obtaining the predicted battery heat dissipation for the current cycle based on the battery parameters, the ambient temperature, and the battery temperature for the current cycle includes: The predicted battery heat dissipation is obtained based on the heat dissipation coefficient, the surface area, the ambient temperature, and the battery temperature.

13. The method according to claim 12, characterized in that, The step of obtaining the effective battery heating amount for the current cycle based on the battery heating power includes: Obtain the heating efficiency of the battery heating system of the battery; Based on the battery heating power, the actual energy consumption for battery heating is obtained; The effective battery heating amount for the current cycle is obtained by multiplying the actual energy consumption of battery heating by the heating efficiency.

14. The method according to claim 13, characterized in that, The battery parameters also include battery specific heat capacity and battery mass; the prediction of battery temperature for the next cycle based on the predicted battery heat generation, predicted battery heat dissipation, effective battery heating, and battery temperature of the current cycle includes: The battery temperature for the next cycle is predicted based on the predicted battery heat generation, the predicted battery heat dissipation, the effective battery heating amount, the battery specific heat capacity, the battery mass, and the battery temperature.

15. The method according to claim 8, characterized in that, The step of predicting the remaining battery energy for the next cycle based on the remaining battery energy in the current cycle, the battery temperature in the next cycle, the battery heating power, and the predicted speed includes: Based on the battery heating power, the actual energy consumption of battery heating in the next cycle is obtained; Based on the predicted speed, the energy consumption for the next cycle is obtained; Based on the battery temperature of the next cycle, obtain the driving energy consumption coefficient for the next cycle; Based on the driving energy consumption, the driving energy consumption coefficient, and the actual energy consumption of battery heating, predict the energy consumption for the next cycle; Based on the remaining battery energy in the current cycle and the energy consumption in the next cycle, predict the remaining battery energy in the next cycle.

16. The method according to claim 15, characterized in that, Also includes: During the iterative calculation process, when the battery temperature reaches the target temperature, the battery heating power is set to 0.

17. The method according to claim 2 or 9, characterized in that, Obtaining the SOC of the current period includes: Based on the effective remaining battery capacity and rated battery capacity of the current cycle, obtain the SOC of the current cycle; The effective battery capacity in the current cycle is related to the remaining battery energy in the current cycle and the battery voltage in the previous cycle. The battery voltage in the previous cycle is related to the state of charge (SOC) in the previous cycle.

18. The method according to claim 17, characterized in that, The step of obtaining the SOC (State of Charge) for the current cycle based on the battery's effective remaining capacity and rated capacity for the current cycle includes: The SOC for the current cycle is obtained by dividing the effective remaining capacity of the battery in the current cycle by the rated capacity of the battery.

19. The method according to any one of claims 1-16, 18, characterized in that, The process of obtaining the initial remaining energy of the battery includes: Obtain the battery's effective remaining capacity and battery voltage at the initial moment; The initial remaining energy of the battery is obtained based on the effective remaining capacity of the battery and the battery voltage at the initial moment.

20. The method according to claim 19, characterized in that, The process of obtaining the effective remaining battery capacity at the initial moment includes: Obtain the battery's rated capacity and the state of charge (SOC) at the initial moment; Based on the battery's rated capacity and the initial state of charge (SOC), obtain the battery's effective remaining capacity at the initial time. The process of obtaining the battery voltage at the initial moment includes: Obtain the SOC at the initial time; The battery voltage at the initial time is obtained based on the SOC at the initial time.

21. The method according to any one of claims 1-16, 18, and 20, characterized in that, Also includes: Obtain the estimated remaining mileage of the target vehicle during this trip.

22. The method according to claim 21, characterized in that, The step of obtaining the estimated remaining mileage of the target vehicle in this trip includes: The estimated remaining mileage is obtained based on the navigation information of the target vehicle during its current journey; or, The system responds to user input to obtain the estimated remaining mileage of the target vehicle during its current journey.

23. The method according to any one of claims 1-16, 18, and 20, characterized in that, After obtaining the reference mileage, the following is also included: Output the reference mileage; If a battery heating confirmation message is received, the battery is heated. If no confirmation of battery heating is received, the battery will not be heated.

24. The method according to claim 23, characterized in that, Also includes: If no confirmation of battery heating is received, and the actual mileage traveled by the target vehicle this time is greater than the reference mileage, the battery will be heated.

25. The method according to any one of claims 1-16, 18, and 20, characterized in that, Also includes: When the iterative calculation continues until the remaining energy of the battery is 0, the predicted driving time corresponding to the remaining energy of the battery being 0 is determined. Based on the predicted travel time and the predicted speed, the estimated remaining mileage of the target vehicle is determined.

26. The method according to claim 25, characterized in that, Also includes: If the reference mileage cannot be obtained, or if the estimated remaining mileage is less than the reference mileage, then the battery will not be heated.

27. The method according to any one of claims 1-16, 18, 20, 22, 24, and 26, characterized in that, Prior to obtaining the reference mileage, the following is also included: Obtain the battery temperature of the target vehicle; If the battery temperature is less than or equal to a first temperature threshold, then the battery of the target vehicle is determined to be in a low-temperature environment.

28. The method according to any one of claims 1-16, 18, 20, 22, 24, and 26, characterized in that, Prior to obtaining the reference mileage, the following is also included: Obtain the battery temperature and initial SOC of the target vehicle; If the initial SOC is greater than or equal to a preset SOC threshold, and the battery temperature is less than or equal to a second temperature threshold, then the battery of the target vehicle is determined to be in a low-temperature environment.

29. A battery heating control device, characterized in that, include: The acquisition module is used to acquire, when the battery of the target vehicle is in a low-temperature environment, the first predicted driving data of the target vehicle in a non-heated battery state, and the second predicted driving data of the target vehicle in a heated battery state. The first predicted driving data includes first remaining energy data and first mileage data, and the second predicted driving data includes second remaining energy data and second mileage data. Based on the first remaining energy data, the first mileage data, the second remaining energy data, and the second mileage data, a target point is determined, wherein the target point is the point where the first remaining energy data and the second remaining energy data are the same, and the first mileage data and the second mileage data are the same; Based on the mileage corresponding to the target point, obtain the reference mileage; The processing module is used to heat the battery if the estimated remaining mileage of the target vehicle in this trip is greater than or equal to the reference mileage. The acquisition module is specifically used to acquire the initial remaining energy of the battery, the initial temperature of the battery, the battery parameters, the ambient temperature, and the predicted speed of the target vehicle. Based on the battery's initial remaining energy, the battery's initial temperature, the predicted speed, the ambient temperature, and the battery parameters, predict the battery temperature and remaining energy for the current cycle. Based on the current cycle's battery temperature, the predicted speed, the ambient temperature, and the battery parameters, predict the battery temperature for the next cycle; Based on the predicted speed, the energy consumption for the next cycle is obtained; Based on the battery temperature of the next cycle, obtain the driving energy consumption coefficient for the next cycle; Based on the driving energy consumption and the driving energy consumption coefficient, predict the energy consumption for the next cycle; Based on the remaining battery energy in the current cycle and the energy consumption in the next cycle, predict the battery temperature and remaining battery energy in the next cycle; The calculation is iterative until the remaining energy of the battery reaches the target value; Based on the remaining battery energy and predicted driving range corresponding to each cycle in the iterative calculation, the first predicted driving range of the target vehicle in the state of battery non-heating is obtained, and the predicted driving range is obtained based on the predicted speed.

30. An electronic device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-28.

31. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-28.

32. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method of any one of claims 1-28.

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