Power control method of vehicle, vehicle and computer readable storage medium

Abstract

The embodiment of the application provides a kind of electric quantity control method of vehicle, vehicle and computer readable storage medium, the method comprises: obtaining the historical charging frequency of vehicle in historical time period and current vehicle position;Determine a plurality of charging devices to be selected, and obtain the distance between current vehicle position and any one of the charging devices to be selected, wherein the plurality of charging devices to be selected are determined by counting the frequency of vehicle using charging device;Based on the distance between the vehicle and any one of the charging devices to be selected, determine the target charging position from the charging position corresponding to the plurality of charging devices to be selected;Based on historical charging frequency and target charging position, determine target electric quantity state value, wherein target electric quantity state value is used to determine the driving strategy of vehicle.The application solves the technical problem of low accuracy of electric quantity control of vehicle in the related art.

Description

Technical Field

[0001] This application relates to the field of vehicle control, and more specifically, to a method for controlling the battery level of a vehicle, a vehicle, and a computer-readable storage medium. Background Technology

[0002] In the field of vehicle technology, hybrid electric vehicles (HEVs) are widely used due to their combined advantages in fuel economy and environmental friendliness. The vehicle's energy management system aims to improve overall vehicle energy consumption by coordinating the power output of the engine and electric motor. Among these, the battery control strategy is a core element determining vehicle operating efficiency and driving experience. However, the battery control strategies in related technologies struggle to cope with special scenarios such as long-distance driving or short commutes, resulting in low energy utilization, poor engine performance, and limited user experience. Therefore, the low accuracy of battery control in related technologies remains a technical challenge.

[0003] There is currently no good solution to the above problems. Summary of the Invention

[0004] This application provides a vehicle power control method, a vehicle, and a computer-readable storage medium to at least solve the technical problem of low accuracy in vehicle power control in related technologies.

[0005] According to one aspect of the embodiments of this application, a vehicle battery control method is provided, comprising: acquiring the historical charging frequency of the vehicle during a historical time period and the current vehicle location; determining a plurality of charging devices to be selected, and acquiring the distance between the current vehicle location and any one of the charging devices to be selected, wherein the plurality of charging devices to be selected is determined by statistically analyzing the frequency of the vehicle's use of the charging devices; determining a target charging location from the charging locations corresponding to the plurality of charging devices to be selected based on the distance between the vehicle and any one of the charging devices to be selected; and determining a target battery status value based on the historical charging frequency and the target charging location, wherein the target battery status value is used to determine the vehicle's driving strategy.

[0006] Furthermore, based on historical charging frequency and target charging location, the target battery status value is determined, including: determining the interval distance between the current vehicle location and the target charging location; and determining the target battery status value based on the interval distance and historical charging frequency.

[0007] Furthermore, based on the interval distance and historical charging frequency, the target power status value is determined, including: determining the first charging fraction corresponding to the historical charging frequency; determining the second charging fraction of the interval distance based on the interval distance and a preset distance; and determining the target power status value based on the first charging fraction and the second charging fraction.

[0008] Further, determining the first charging score corresponding to the historical charging frequency includes: determining the adjacent triggering time points of the vehicle's charging event based on the historical charging frequency; determining the triggering interval duration of the charging event based on the adjacent triggering time points; and updating the initial charging score based on the triggering interval duration to obtain the first charging score.

[0009] Furthermore, based on the trigger interval duration, the initial charging score is updated to obtain a first charging score, including: in response to the trigger interval duration being less than a preset trigger interval duration, determining the first charging score based on the sum of the initial charging score and the preset score; in response to the trigger interval duration being greater than or equal to the preset trigger interval duration, determining the first charging score based on the difference between the initial charging score and the preset score.

[0010] Further, determining the first charging score based on the sum of the initial charging score and the preset score includes: determining the first preset score as the first charging score in response to the sum being greater than the first preset value; and determining the sum as the first charging score in response to the sum being less than or equal to the first preset value.

[0011] Further, determining the first charging score based on the difference between the initial charging score and the preset score includes: determining the second preset score as the first charging score in response to the difference being less than a second preset value; and determining the difference as the first charging score in response to the difference being greater than or equal to the second preset value.

[0012] Further, based on the interval distance and the preset distance, determining the second charging fraction for the interval distance includes: determining a third preset value for the second charging fraction in response to the interval distance being greater than the preset distance; and determining a fourth preset value for the second charging fraction in response to the interval distance being less than or equal to the preset distance.

[0013] Furthermore, the method also includes: in response to detecting that the vehicle triggers a charging event by updating the charging device, obtaining the charging frequency of the vehicle at the updating charging device, wherein the updating charging device is a charging device other than the multiple charging devices to be selected; in response to the charging frequency of the updating charging device being greater than that of any one of the multiple charging devices to be selected, updating the multiple charging devices to be selected based on the updating charging device.

[0014] Furthermore, updating the selected multiple charging devices based on the updated charging device includes: in response to the number of selected multiple charging devices being less than a preset threshold, adding an updated charging device to the selected multiple charging devices to update the selected multiple charging devices; in response to the number of selected multiple charging devices being greater than or equal to the preset threshold, determining a preset charging device among the selected multiple charging devices, and replacing the preset charging device with the updated charging device to update the selected multiple charging devices, wherein the charging frequency of the preset charging device is lower than that of other charging devices among the selected multiple charging devices excluding the preset charging device.

[0015] According to another aspect of the embodiments of this application, a vehicle is also provided, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of this application when it runs.

[0016] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0017] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the methods of various embodiments of this application.

[0018] According to another aspect of the embodiments of this application, a computer program product is also provided, including a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods in various embodiments of this application.

[0019] According to another aspect of the embodiments of this application, a computer program is also provided, which, when executed by a processor, implements the methods of the various embodiments of this application.

[0020] In this embodiment, the historical charging frequency and current vehicle location of the vehicle during a historical charging period are obtained; multiple charging devices to be selected are determined, and the distance between the current vehicle location and any one of the selected charging devices is obtained. The multiple charging devices to be selected are determined by statistically analyzing the frequency of vehicle use of charging devices; based on the distance between the vehicle and any one of the selected charging devices, a target charging location is determined from the charging locations corresponding to the multiple selected charging devices; based on the historical charging frequency and the target charging location, a target battery status value is determined, whereby the target battery status value is used to determine the vehicle's driving strategy. This embodiment is based on a multi-dimensional feature fusion reasoning method using historical charging frequency and spatial location. It uses statistical analysis of historical vehicle charging records to quantitatively represent user charging habits, and combines the real-time vehicle location with the locations of commonly used charging devices to calculate the distance representing geographical convenience. The target battery status value is derived using the historical charging frequency and the aforementioned distance. This allows for accurate setting of the target battery status value for the vehicle's energy management boundary based on the driver's actual charging habits and the convenience of the current geographical environment, thereby improving energy utilization efficiency and achieving the technical effect of intelligent battery management. This solves the technical problem of low accuracy in vehicle battery control. Attached Figure Description

[0021] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0022] Figure 1 This is a flowchart of a vehicle power control method according to an embodiment of this application;

[0023] Figure 2 This is a schematic diagram of an intelligent control strategy for the battery balance value based on the driver's charging habits, according to an embodiment of this application.

[0024] Figure 3 This is a schematic diagram of a smart control strategy for the battery balance value based on the driver's charging habits, according to an embodiment of this application.

[0025] Figure 4 This is a schematic diagram of an algorithm module for updating frequently used locations in an intelligent control strategy for battery balance values ​​based on driver charging habits, according to an embodiment of this application.

[0026] Figure 5 This is a flowchart of an optional vehicle battery control method according to an embodiment of this application;

[0027] Figure 6 This is a schematic diagram of a vehicle power control device according to an embodiment of this application. Detailed Implementation

[0028] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0029] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0030] According to an embodiment of this application, a method for controlling the battery power of a vehicle is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0031] This embodiment provides a method for controlling the battery level of a vehicle. Figure 1 This is a flowchart of a vehicle battery control method according to an embodiment of this application, such as... Figure 1 As shown, the process includes the following steps:

[0032] Step S102: Obtain the historical charging frequency and current vehicle location of the vehicle during the historical charging period.

[0033] The aforementioned vehicle refers to an automobile equipped with an electric drive system and charging function, specifically a hybrid electric vehicle or a pure electric vehicle. The vehicle executes the power control method of the embodiments of this application.

[0034] The aforementioned historical time period refers to a continuous or discontinuous time period in the past used to statistically analyze vehicle charging behavior characteristics. The historical time period defines the scope of data collection. It defines the time boundary for data analysis and can be a fixed calendar period. The essence of the historical time period is to define the collection interval for sample data to ensure the representativeness and timeliness of the statistical results and to exclude interference from irrelevant historical data.

[0035] The aforementioned historical period can be the past three months, and can be set as needed during actual use.

[0036] The aforementioned historical charging frequency refers to the statistical count of the number of times a vehicle uses a specific charging device or performs a charging operation within the aforementioned historical time period, reflecting the driver's charging habits and preferences. Historical charging frequency quantifies the driver's charging behavior patterns, characterizing the driver's dependence on and preference for charging facilities by calculating the number of charging times per unit time or the frequency of use at a specific location. It is a key data dimension for constructing a personalized charging habit model.

[0037] The aforementioned charging refers to the process of inputting electrical energy into a vehicle's battery pack through an external power source. Charging includes two main forms: fast charging and slow charging, both aimed at restoring the battery's state of charge. The charging process encompasses the complete physical behavior from connecting the charging interface to completing the energy transfer. Whether it's fast DC charging or slow AC charging, the essence of charging is to convert external grid electrical energy into battery chemical energy for storage, in order to replenish the energy consumed by the vehicle while driving and maintain the battery's state of charge.

[0038] The aforementioned current vehicle location refers to the geographical coordinates of the vehicle when historical charging frequencies were acquired. This information is typically provided by the vehicle's positioning system and used for subsequent distance calculations. The historical charging frequencies and current vehicle location are the foundational input data for determining the target charging location and target battery status; together, they constitute a combination of driver habits and real-time status.

[0039] In one optional embodiment, the vehicle's charging logs for past historical periods are read through the vehicle terminal's historical record module, the usage frequency of each charging facility is counted to generate historical charging frequency, and the vehicle's current latitude and longitude coordinates are obtained by calling the global positioning system as the current vehicle location.

[0040] In another optional embodiment, in response to vehicle power-on or a specific triggering event, the power control system synchronizes the vehicle's historical charging behavior data from a cloud server to calculate the historical charging frequency, and combines the onboard inertial navigation unit with satellite positioning signals to calculate a higher-precision current vehicle location information.

[0041] The data processing in this embodiment supports three modes: cloud-based, vehicle-based, and cloud-vehicle collaborative. In cloud-based processing mode, the vehicle uploads raw charging event data and its current location. The cloud server then performs historical charging frequency statistics, common location clustering, and target battery status value calculation, and sends the target battery status value back to the vehicle. In vehicle-based processing mode, the vehicle locally stores historical data, and the onboard processor directly performs interval calculation, score updates, and target location matching locally, achieving offline real-time control. In cloud-vehicle collaborative mode, the vehicle is responsible for acquiring the current location and historical charging frequency, while the cloud is responsible for recording long-term historical charging frequencies, dynamically maintaining common charging locations, and improving complex strategies. The two collaborate by periodically synchronizing data or sending parameters as needed.

[0042] This application embodiment obtains historical charging frequencies to reflect driver habits and combines them with the current vehicle location to provide real-time status, providing accurate data support for subsequent selection of target charging equipment and determination of improved battery status values, thereby enhancing the personalization and adaptability of the strategy.

[0043] Step S104: Determine multiple charging devices to be selected and obtain the distance between the current vehicle location and any one of the charging devices to be selected. The multiple charging devices to be selected are determined by statistically analyzing the frequency of vehicle use of the charging devices.

[0044] The aforementioned multiple charging devices to be selected refer to a set of candidate charging facilities filtered based on historical data. These candidate charging facilities are the target objects chosen by the driver. The set of candidate charging facilities excludes infrequent or never-used devices and retains representative charging nodes, aiming to narrow the search scope, improve the efficiency of subsequent target location determination, and ensure that the recommended results match the driver's actual usage preferences and habits.

[0045] Each of the aforementioned charging devices refers to a single charging facility entity in the set of devices to be selected, possessing a unique geographical identifier and attribute information. During the distance calculation process, the power control system needs to traverse each of the multiple charging devices to be selected, treating them as independent calculation objects, to obtain the spatial distance between the vehicle and each charging device to be selected, thereby providing basic data for subsequent sorting, filtering, or scoring.

[0046] The aforementioned statistics on the frequency of vehicle charging equipment use refer to the process of quantitatively analyzing the number of times each device was selected in the vehicle's historical charging records. By sorting through historical data, the proportion or frequency of specific devices in the total charging events is calculated, thereby generating indicators reflecting the strength of driver preferences. These indicators are used to assess the "frequent use" of each device and serve as the basis for determining the candidate set, reflecting a data-driven decision-making logic.

[0047] The aforementioned distance refers to the spatial metric between the vehicle's current location and the charging location corresponding to any of the candidate charging devices. This distance can be a straight-line distance, road travel distance, or estimated travel time, used to quantify the ease or convenience of reaching each candidate device. It is an important evaluation factor for subsequently determining the target charging location, reflecting the impact of geographical location factors on the charging strategy.

[0048] In one optional embodiment, the vehicle's processor reads historical charging log data from the onboard storage medium, extracts the charging facility identifier (ID) associated with each charging event, and counts the frequency of each ID. Then, the charging facilities are sorted from high to low frequency, and several of the top-ranked facilities are selected as candidate charging devices. Simultaneously, the positioning module is invoked to obtain the vehicle's real-time latitude and longitude, and a spatial geometric algorithm is used to calculate the distance between the vehicle and each candidate device. This spatial geometric algorithm refers to a calculation method that uses specific mathematical formulas to calculate the spatial distance or geometric relationship between the vehicle's real-time latitude and longitude coordinates and the charging facility's preset latitude and longitude coordinates. This algorithm typically involves converting spherical coordinates to planar coordinates or directly applying spherical trigonometric functions to overcome errors caused by the Earth's curvature, thereby accurately measuring the physical distance between locations.

[0049] In another optional embodiment, the vehicle sends a location request and historical data query command to the cloud server via the vehicle-to-everything (V2X) module. The cloud server analyzes historical charging behavior based on user profiles, filters out frequently used charging areas and specific device lists, and returns them to the vehicle. Upon receiving the list, the vehicle, combined with its local high-precision positioning data, calculates the real-time navigation distance or straight-line distance from its current location to each charging device in the list through a map service interface. The aforementioned user profile refers to a digital set of user characteristics constructed using data analysis and modeling techniques based on multi-dimensional information such as the vehicle's long-term accumulated charging behavior data, geographic location trajectory, time preferences, and vehicle status. The user profile records the driver's charging habits, frequently used location distribution, dependence on charging facilities, and potential travel patterns, providing data for understanding personalized user needs. By constructing user profiles, the power control system can extract representative behavioral patterns from massive amounts of historical data, such as frequently used charging areas and preferred charging types, thereby providing accurate personalized basis for intelligently recommending frequently used charging devices and improving target power status control strategies, enhancing user experience and energy efficiency.

[0050] This application embodiment achieves a shift from full-scale search to accurate recommendation by filtering devices based on historical frequency and calculating distance, reducing computational complexity, improving the personalization and practicality of target location recommendations, and thus improving the user charging experience.

[0051] Step S106: Based on the distance between the vehicle and any one of the selectable charging devices, determine the target charging location from the charging locations corresponding to the multiple selectable charging devices.

[0052] The aforementioned target charging location refers to the final recommended or determined charging location selected from multiple charging locations corresponding to available charging devices, based on factors such as distance. The target charging location is a superior or near-optimal solution derived by comprehensively considering driver habits and real-time geographical location, used to guide subsequent vehicle charging behavior and representing the output of a personalized power management strategy.

[0053] In one optional embodiment, the vehicle's processor compares the current vehicle location coordinates with the charging location coordinates of each of the multiple candidate charging devices, and calculates the distance from the vehicle to each candidate device using a spatial distance algorithm. Then, based on a preset distance selection strategy, such as selecting the charging device with the shortest distance, or weighting the distances according to historical frequency, a unique or high-priority charging location is finally determined from the candidate list as the target charging location.

[0054] The aforementioned preset distance selection strategy refers to the set of algorithmic logic or rules followed by the power control system when filtering or sorting from a list of multiple candidate charging devices to determine the target charging location. The preset distance selection strategy aims to transform abstract spatial distance data into concrete decision-making criteria, ensuring that the selected target charging location meets both the user's geographical convenience needs and their historical charging habits. The preset distance selection strategy can be a single-dimensional distance minimization principle, unconditionally selecting the charging facility with the closest geographical location. Alternatively, it can be a multi-dimensional weighted fusion principle, combining historical charging frequency with real-time distance to construct a comprehensive scoring function, balancing the relationship between proximity and usage frequency through weight allocation.

[0055] For example, the power control system directly calculates the straight-line distance between the vehicle and all candidate devices, selecting the one with the smallest value as the target charging location. A comprehensive strategy, such as a weighted ranking strategy, can be used. This involves setting the comprehensive score as weight × normalized distance + weight × normalized historical frequency, and selecting the device with the best score. Alternatively, a threshold filtering strategy can be used, retaining only devices with a distance less than a set threshold and a frequency higher than the set threshold, and then selecting the best from among them. The specific implementation of these strategies depends on the power control system's emphasis on response speed, user satisfaction, and energy management goals. The aim is to accurately identify the most suitable target charging location from multiple candidates using quantifiable mathematical logic, providing reliable spatial input parameters for subsequently determining the target power state value.

[0056] In another optional embodiment, the vehicle obtains a comprehensive score from the cloud based on the user's historical charging frequency and real-time traffic conditions via a vehicle-to-everything (V2X) module. This score incorporates the spatial distance between the vehicle and each candidate charging location. The processor receives this score data, sorts multiple candidate charging locations, and selects the charging location with the highest comprehensive score or one whose distance meets a specific threshold condition as the target charging location for the current trip, thus balancing distance convenience with user preferences.

[0057] This application embodiment achieves accurate positioning from the candidate set to the specific location by filtering target charging locations based on distance, ensuring the geographical proximity of recommended charging points, reducing user travel costs, and providing a definite spatial benchmark for subsequent adjustments to the power strategy based on geographical location, thereby improving the pertinence and effectiveness of energy management.

[0058] Step S108: Based on the historical charging frequency and the target charging location, determine the target battery status value, wherein the target battery status value is used to determine the vehicle's driving strategy.

[0059] The aforementioned target state of charge (SOC) value refers to a preset target threshold for battery charge calculated by the battery control system based on the driver's historical charging habits and current geographical location information. It is typically expressed as a percentage of State of Charge (SOC). As a control command of the energy management system, the target SOC value defines the boundary conditions for engine intervention in charging or pure electric driving in hybrid mode. By comprehensively considering user charging convenience and frequency, it achieves a shift from a fixed, conservative strategy to a personalized, adaptive strategy. This aims to improve the engine's operating range, balance fuel economy and battery retention needs, and ensure that the vehicle maintains optimal energy efficiency and driving experience under different usage scenarios.

[0060] The aforementioned driving strategy refers to the process by which the vehicle control system formulates the operating mode and power distribution scheme of the engine and electric motor based on the target battery state value. The driving strategy determines whether the vehicle is driven purely electric, in a hybrid mode, or in engine charging mode during operation. It aims to achieve energy conservation, emission reduction, and performance balance by improving the order and efficiency of energy use. It is the final execution instruction of the vehicle's energy management system and is directly related to the vehicle's operating status and economy. In one optional embodiment, the vehicle's processor first extracts the vehicle's historical charging frequency data, maps this data to a charging preference score, and simultaneously obtains the geographical information of the target charging location and calculates the distance to the current location. Subsequently, based on a preset mapping function or lookup table, the charging preference score and distance factors are weighted and fused to calculate the corresponding target battery state value, which is then written into the energy management control module to guide subsequent driving mode switching.

[0061] In another alternative embodiment, the vehicle receives personalized power control parameters based on big data from a cloud server. The cloud server uses a model to predict an optimal power maintenance level based on the vehicle's historical charging frequency characteristics and the currently planned target charging location. The vehicle receives the aforementioned target power status value and uses it as the baseline power level for the current driving cycle, dynamically adjusting the engine start threshold and energy recovery intensity to achieve adaptive energy management.

[0062] The aforementioned model refers to a predictive energy management model built based on supervised learning or reinforcement learning algorithms. The feature vector input to the model typically includes the vehicle's historical charging frequency, charging interval duration, spatial distribution of frequently used charging locations, real-time geographical location, remaining driving range, historical driving condition data (e.g., average speed, acceleration distribution), and external environmental factors such as temperature and gradient. This model utilizes deep neural networks (DNNs), long short-term memory networks (LSTMs), or gradient boosting trees, such as extreme gradient boosting (XGBoost) and lightweight gradient boosting machines (LightGBM). The model is trained on massive amounts of historical data to capture the nonlinear mapping between driver charging behavior patterns and the optimal battery maintenance level, i.e., the target battery state value.

[0063] During the inference phase, the battery control model combines current vehicle state parameters, such as the real-time location and distance to the target charging point, and historical charging frequency scores, to predict the optimal battery baseline value that maximizes fuel economy and meets the user's charging habits within the current driving cycle. This model has online learning capabilities and can continuously iterate and update as vehicle usage data accumulates, thereby fitting the personalized habits of different drivers. This ensures that the generated target battery state value conforms to both the vehicle's physical limitations and the user's actual lifestyle, achieving intelligent adaptive energy management.

[0064] This application embodiment determines the target power status value by combining historical habits and geographical location, realizing personalized and scenario-based power management, avoiding the limitations of fixed strategies, and improving energy utilization efficiency.

[0065] In this embodiment, the historical charging frequency and current vehicle location of the vehicle during a historical charging period are obtained; multiple charging devices to be selected are determined, and the distance between the current vehicle location and any one of the selected charging devices is obtained. The multiple charging devices to be selected are determined by statistically analyzing the frequency of vehicle use of charging devices; based on the distance between the vehicle and any one of the selected charging devices, a target charging location is determined from the charging locations corresponding to the multiple selected charging devices; based on the historical charging frequency and the target charging location, a target battery status value is determined, whereby the target battery status value is used to determine the vehicle's driving strategy. This embodiment is based on a multi-dimensional feature fusion reasoning method using historical charging frequency and spatial location. It uses statistical analysis of historical vehicle charging records to quantitatively represent user charging habits, and combines the real-time vehicle location with the locations of commonly used charging devices to calculate the distance representing geographical convenience. The target battery status value is derived using the historical charging frequency and the aforementioned distance, achieving the goal of accurately setting the target battery status value of the vehicle's energy management boundary based on the driver's actual charging habits and the convenience of the current geographical environment. This implementation, for example, improves energy utilization efficiency, achieves the technical effect of intelligent battery management, and solves the technical problem of low accuracy in vehicle battery control.

[0066] Optionally, the target battery status value is determined based on historical charging frequency and target charging location, including: determining the interval distance between the current vehicle location and the target charging location; and determining the target battery status value based on the interval distance and historical charging frequency.

[0067] The aforementioned interval distance refers to a spatial metric between the current vehicle location and the target charging location, which can be calculated by determining the difference in their geographical coordinates. The interval distance reflects how close the vehicle is to the designated charging facility and serves as a basis for assessing charging convenience and planning remaining travel distance. The interval distance can influence user acceptance of charging behavior and the feasibility of strategy implementation, ensuring the spatial rationality of the power management strategy.

[0068] In one optional embodiment, the positioning module is first invoked to obtain the vehicle's real-time latitude and longitude, and the latitude and longitude information is extracted from the stored target charging location data. The straight-line distance or road travel distance between the two locations, i.e., the interval distance, is calculated using a spatial geometric algorithm. Subsequently, the vehicle's historical charging frequency data can be read, converted into a quantitative score, and combined with the interval distance to calculate the target battery status value through a preset mapping model, which is then output to the energy management controller.

[0069] The aforementioned pre-defined mapping model refers to a set of mathematical functions or logical rules that convert historical charging frequency and interval distance into a quantitative target energy state value. The pre-defined mapping model can be constructed using weighted linear combination, lookup table interpolation, or nonlinear fitting. The logic of the pre-defined mapping model lies in balancing charging convenience with energy reserve requirements.

[0070] For example, the preset mapping model first normalizes the historical charging frequency score, with high scores representing high-frequency charging and low scores representing low-frequency charging. Simultaneously, it normalizes or segments the interval distance, with greater distances indicating lower convenience. Then, the preset mapping model fuses these two factors according to preset weighting coefficients, typically employing a reverse weighting strategy. A higher historical charging frequency score and shorter interval distance result in a lower target SOC baseline value, allowing the vehicle to use more battery power. Conversely, a lower historical charging frequency and longer interval distance result in a higher target SOC baseline value, requiring the vehicle to reserve more battery power to address range anxiety. Finally, the preset mapping model outputs a target battery state value with boundary constraints. This target battery state value serves as a direct instruction for the energy management controller to adjust the engine intervention point and energy recovery intensity, thereby achieving accurate battery control based on user habits and geographical location.

[0071] In another optional embodiment, the vehicle receives location- and service-based charging network data via a cloud interface, determines the target charging location, and calculates the distance between the vehicle's current location and the target charging location. Simultaneously, the cloud analyzes historical charging frequency characteristics based on the user's historical charging records, integrates the distance with the historical charging frequency, and uses a machine learning algorithm to predict a better target battery status value. This target battery status value is then sent to the vehicle to adjust the driving strategy.

[0072] This application embodiment determines the target power status value by combining the interval distance and historical charging frequency, thereby achieving accuracy and personalization of power control, improving the accuracy of charging convenience assessment, and improving energy management strategy.

[0073] Optionally, determining the target power status value based on the interval distance and historical charging frequency includes: determining a first charging fraction corresponding to the historical charging frequency; determining a second charging fraction for the interval distance based on the interval distance and a preset distance; and determining the target power status value based on the first charging fraction and the second charging fraction.

[0074] The aforementioned First Charging Score refers to a numerical indicator quantified based on the vehicle's historical charging frequency, used to characterize the driver's preference intensity or habitual characteristics regarding charging behavior. The First Charging Score is obtained by statistically analyzing historical charging event time intervals and frequencies, and then transforming the data using a specific algorithm. It reflects the user's dependence on charging services and serves as a parameter for evaluating user behavior patterns. Its aim is to transform abstract charging habits into calculable and comparable quantitative data, providing a personalized basis for subsequent power consumption strategies.

[0075] The aforementioned preset distance refers to a reference distance threshold pre-set by the power control system, used to divide the interval distance into different levels or intervals. Using the preset distance as a judgment standard, continuous distance values ​​are discretized into specific evaluation levels, thereby simplifying the calculation logic and enabling a unified quantification of charging convenience at different distances. The preset distance is typically set based on the user's psychological acceptance range, the density of urban charging facilities, or the average driving radius, serving as a benchmark for determining the second charging score.

[0076] The aforementioned second charging score is a numerical value quantified based on the comparison between the interval distance and the preset distance, used to characterize the geographical convenience of the target charging location. If the interval distance is less than or equal to the preset distance, it indicates that the charging facility is nearby, and a higher score is assigned. If the interval distance is greater than the preset distance, it indicates that the charging facility is far away, and a lower score is assigned. The second charging score transforms spatial location information into weights that influence the charging strategy, ensuring that the impact of geographical location on the user's charging experience is fully considered when determining the target charging status value, thus achieving a fusion of location factors and habit factors.

[0077] In one optional embodiment, the vehicle's processor first reads the vehicle's historical charging frequencies and maps them to corresponding first charging scores to quantify the user's charging preferences. Simultaneously, it obtains the distance between the vehicle's current location and the target charging location, compares the current vehicle location with a preset distance, and assigns a higher second charging score if the distance is less than or equal to the preset distance; otherwise, it assigns a lower score. Finally, the first and second charging scores are weighted and summed or fused according to preset weights or an algorithm model to obtain the final target battery status value.

[0078] In another optional embodiment, the vehicle obtains the user's historical charging frequency data through a cloud service interface, converting the historical charging frequency into a first charging score representing charging habits. Simultaneously, the vehicle navigation system calculates the real-time navigation distance from the vehicle's current location to the target charging location as an interval distance, and compares it with a preset distance threshold synchronized to the cloud to determine a second charging score representing geographical convenience. Subsequently, based on the first and second charging scores, and combined with current road conditions or traffic conditions, the cloud uses an improved algorithm to calculate a better target battery status value and sends it to the vehicle.

[0079] The process of converting historical charging frequency into a first charging score that represents charging habits refers to the process by which the vehicle or cloud server generates a numerical indicator that reflects the user's charging dependence or convenience based on the vehicle's actual charging behavior data within a historical time period through a quantitative algorithm.

[0080] For example, the power control system first extracts key features from historical charging records, including but not limited to the number of days between single charges, charging frequency, and cumulative charging duration, and calculates the average charging interval duration. Subsequently, the interval duration is mapped according to a preset scoring rule.

[0081] The process of mapping the interval distance to a second charging score that represents geographical convenience refers to the process by which the cloud server receives the current vehicle location reported by the vehicle terminal and converts the current vehicle location into a standardized numerical index through a preset mapping rule or piecewise function.

[0082] This application embodiment obtains historical charging frequency and interval distance by separately quantifying charging habits, and integrates the two to determine the target power status value, thereby realizing the accuracy and personalization of energy management strategy and improving the rationality of charging decisions and user satisfaction.

[0083] Optionally, determining the first charging score corresponding to the historical charging frequency includes: determining adjacent triggering time points of the vehicle's charging event based on the historical charging frequency; determining the triggering interval duration of the charging event based on the adjacent triggering time points; and updating the initial charging score based on the triggering interval duration to obtain the first charging score.

[0084] The aforementioned vehicle-triggered charging event refers to a specific moment or status marker indicating that a vehicle has completed a valid charging operation. A vehicle-triggered charging event signifies the end or confirmation of a charging cycle. It is not simply a matter of plugging in the charging gun; specific conditions must be met, such as charging duration and changes in battery level, to be considered a vehicle-triggered charging event. It serves as the fundamental unit for recording historical charging data and analyzing user behavior patterns. Vehicle-triggered charging events are used to determine adjacent trigger times to calculate charging intervals, ensuring the accuracy and effectiveness of charging frequency statistics.

[0085] The aforementioned adjacent trigger time points refer to the records of two consecutive valid charging operations performed by the vehicle. These two time points represent the time when the previous charging was completed and the time when the next charging was completed, respectively. These two time points constitute the basic time unit for evaluating the continuity of charging behavior and are the basis for calculating the time span between two charging behaviors, ensuring the timing accuracy of charging frequency analysis.

[0086] The trigger interval mentioned above refers to the time difference between two adjacent charging trigger times, that is, the time span between two charging actions. The trigger interval directly reflects the cyclical pattern of the driver's charging and is a direct quantitative indicator for measuring the charging frequency. A shorter interval usually corresponds to a higher charging frequency, and vice versa. It is an input variable for updating the charging score.

[0087] For example, users can set whether to charge daily, every two days, or weekly, depending on their needs during actual use.

[0088] The initial charging score mentioned above refers to the baseline value when the system begins calculating or resetting the charging frequency score. As the starting point for cumulative updates, the initial charging score carries the accumulated score results that are continuously adjusted as historical charging events occur. By increasing or decreasing the initial score based on the trigger interval, the power control system can dynamically reflect the changing trends of users' charging habits, ensuring that the scoring model has memory and adaptability, thereby accurately depicting the current charging behavior pattern.

[0089] In one optional embodiment, firstly, valid charging events are retrieved from the vehicle's historical charging records. The times corresponding to two consecutive charging events are extracted as adjacent trigger time points, and the time difference between these two time points is calculated to obtain the trigger interval duration. Subsequently, the trigger interval duration is compared with a preset trigger interval threshold. If the trigger interval duration is less than the preset trigger interval threshold, the initial charging score is added to the preset score to obtain a first charging score. If the trigger interval duration is greater than or equal to the preset trigger interval threshold, the initial charging score is subtracted from the preset score to obtain the first charging score.

[0090] In one optional embodiment, a sliding time window mechanism can be used for analysis. First, valid charging events and their corresponding trigger times within the historical time period of the current moment are extracted. Multiple trigger intervals between adjacent trigger times are calculated, and an interval duration sequence is generated. Then, the interval duration sequence is weighted and averaged or exponentially smoothed to eliminate fluctuations caused by single abnormal intervals, resulting in a smoothed trigger interval duration. Finally, the trigger interval duration is input into a preset nonlinear mapping function. The corresponding score adjustment is output according to the preset nonlinear mapping function, and the score adjustment is accumulated to the initial charging score. Simultaneously, a dynamic threshold constraint mechanism is used to apply boundary constraints to the updated first charging score, thereby obtaining a first charging score that can more stably and smoothly reflect long-term charging habit trends. This embodiment of the application dynamically updates the charging score by quantifying adjacent charging time intervals, achieving accurate evaluation of charging frequency and enabling energy management strategies to more accurately adapt to the charging rhythms of different users.

[0091] Optionally, updating the initial charging score based on the trigger interval duration to obtain a first charging score includes: determining the first charging score based on the sum of the initial charging score and the preset score in response to the trigger interval duration being less than a preset trigger interval duration; and determining the first charging score based on the difference between the initial charging score and the preset score in response to the trigger interval duration being greater than or equal to the preset trigger interval duration.

[0092] The aforementioned preset trigger interval refers to a time threshold pre-set by the power control system, serving as a standard boundary to distinguish between high-frequency and low-frequency charging. As a benchmark for logical judgment, the preset trigger interval divides consecutive trigger intervals into short and long ranges, thereby triggering different first-charge score update strategies. The preset trigger interval is typically set based on statistical analysis or experimental calibration of typical user charging habits, aiming to balance the sensitivity and stability of the score, avoiding drastic changes in the score due to minor fluctuations, and ensuring the robustness of the strategy.

[0093] The aforementioned preset score refers to a fixed increment or decrement value used to adjust the initial charging score, representing the contribution weight of a single charging frequency determination to the total score. The preset score determines the step size of the score change, that is, the magnitude of the score change each time a high-frequency or low-frequency condition is triggered. The setting of the preset score needs to balance the granularity of the score and the convergence speed. Too large a score will cause score oscillations, while too small a score will result in a slow response. By setting the preset score reasonably, the first charging score can smoothly and stably reflect the subtle changes in the user's charging frequency, improving the adaptability of the strategy.

[0094] In one optional embodiment, the vehicle's processor reads the timestamps of the two most recent charging events to calculate the trigger interval duration and compares it with a preset trigger interval duration. If the trigger interval duration is less than the preset trigger interval duration, the initial charging score is added to the preset score to obtain a new score. In response to a trigger interval duration greater than or equal to the preset trigger interval duration, the initial charging score is subtracted from the preset score to obtain a new score. Subsequently, the vehicle's processor checks whether the new score is within a valid range. If it exceeds the range, a limiting process is performed, and the final output serves as the first charging score for subsequent modules, achieving dynamic updating of the score.

[0095] This application embodiment classifies the trigger interval duration by setting a time threshold, and updates the initial charging score accordingly, thereby realizing dynamic adaptive adjustment of the charging frequency score and improving the sensitivity and accuracy of the scoring model in response to changes in user behavior.

[0096] Optionally, determining a first charging score based on the sum of an initial charging score and a preset score includes: determining a first preset score as the first charging score in response to a sum greater than a first preset value; and determining the sum as the first charging score in response to a sum less than or equal to the first preset value.

[0097] The aforementioned first preset value refers to the maximum upper limit threshold that the first charging score is allowed to reach, set by the power control system. This first preset value is used to prevent numerical overflow or distortion caused by the infinite accumulation of scores due to high-frequency charging. If the sum exceeds the first preset value, it indicates that the user's charging frequency is extremely high. The power control system will no longer continue to increase the score but will fix it at this upper limit, thereby maintaining the stability of the scoring system and ensuring that the score differentiation between high-frequency users and other users remains within an effective range, preventing strategy failure.

[0098] The aforementioned first preset score refers to a fixed value corresponding to the first preset value, which is usually the maximum allowed score. If the calculated sum exceeds the first preset value, the first charging score is forcibly set to this fixed value, thus limiting the range. This mechanism ensures that no matter how frequently the user charges, the score will not increase indefinitely, thereby guaranteeing the robustness of the energy management strategy in extremely high-frequency charging scenarios, preventing the target power state value from being set too aggressively due to an excessively high score, and maintaining the stability of system operation.

[0099] In one optional embodiment, the vehicle's processor first reads the stored initial charging score and preset score, and performs an addition operation to obtain a sum. Then, the vehicle's processor compares the sum with a first preset value. If the sum is greater than the first preset value, the first preset score is directly assigned as the first charging score. If the sum is less than or equal to the first preset value, the sum is directly assigned as the first charging score, thereby completing the high-segment limiting logic and ensuring that the output score does not exceed the limit.

[0100] This application embodiment limits the sum value by setting an upper limit threshold, preventing the charging score from growing indefinitely, ensuring the stability and robustness of the scoring model, and enabling a reasonable quantitative expression of high-frequency charging behavior.

[0101] Optionally, determining a first charging score based on the difference between an initial charging score and a preset score includes: determining a second preset score as the first charging score in response to a difference less than a second preset value; and determining the difference as the first charging score in response to a difference greater than or equal to the second preset value.

[0102] The aforementioned second preset value refers to the minimum lower threshold that the system sets for the first charging score. This second preset value is used to prevent numerical overflow or distortion caused by the score decreasing indefinitely due to low-frequency charging. If the difference is below this threshold, it indicates that the user's charging frequency is extremely low. The power control system will no longer reduce the score but will fix it at this lower limit, thereby maintaining the stability of the scoring system and ensuring that the score differentiation between low-frequency users and other users remains within an effective range, preventing the strategy from failing due to excessively low scores.

[0103] The aforementioned second preset score refers to a fixed value corresponding to the second preset value, which is usually the minimum allowed score. If the calculated difference is less than the second preset value, the first charging score is forcibly set to this fixed value, thus acting as a limit. This mechanism ensures that even if the user charges infrequently, their score will not decrease indefinitely, thereby guaranteeing the robustness of the energy management strategy in extremely low-frequency charging scenarios, preventing the target power state value from being set too conservatively due to an excessively low score, and maintaining the stability of system operation.

[0104] In one optional embodiment, the vehicle's processor first reads the stored initial charging score and preset score, and performs a subtraction operation to obtain the difference. Then, the vehicle's processor compares the difference with a second preset value. If the difference is less than the second preset value, the second preset score is directly assigned to the first charging score. If the difference is greater than or equal to the second preset value, the difference is directly assigned to the first charging score, thereby completing the low-segment limiting logic and ensuring that the output score does not fall below the minimum threshold.

[0105] This application embodiment limits the difference by setting a lower threshold, preventing the charging score from decreasing indefinitely, ensuring the stability and robustness of the scoring model, and enabling a reasonable quantitative expression of low-frequency charging behavior, thus avoiding strategy loss of control.

[0106] Optionally, determining a second charging fraction based on the interval distance and a preset distance includes: determining a third preset value as the second charging fraction in response to the interval distance being greater than the preset distance; and determining a fourth preset value as the second charging fraction in response to the interval distance being less than or equal to the preset distance.

[0107] The aforementioned third preset value refers to a fixed value assigned to the second charging score by the power control system when the distance between charging facilities exceeds a preset distance. This typically represents a lower convenience score. The third preset value reflects the increased user resistance to charging or the increased time cost when charging facilities are far away, thus assigning it a lower weight. The purpose of setting this third preset value is to quantify the negative impact of long distances, reducing reliance on distant charging points when determining the target power status value, and guiding the strategy towards closer charging options, thereby improving user experience and charging efficiency.

[0108] The aforementioned fourth preset value refers to a fixed value assigned to the second charging score by the power control system when the interval distance is less than or equal to the preset distance. It typically represents a higher convenience score. The fourth preset value reflects the user's convenience and high willingness to charge when charging facilities are nearby, and therefore carries a higher weight. The purpose of setting the fourth preset value is to quantify the positive incentives brought by proximity, enabling the matching of nearby charging points when determining the target power status value. This encourages users to charge in convenient locations, thereby improving the spatial adaptability of the energy management strategy and achieving accurate control.

[0109] In one optional embodiment, the vehicle's processor first obtains the vehicle's real-time latitude and longitude, i.e., the current vehicle location, through the onboard positioning module, and extracts the latitude and longitude from the stored target charging location data. It then uses a spatial geometry algorithm to calculate the straight-line distance between the two locations as the interval distance. Subsequently, the vehicle's processor compares this interval distance with a preset distance. If the interval distance is greater than the preset distance, a third preset value is assigned as the second charging score. If the interval distance is less than or equal to the preset distance, a fourth preset value is assigned as the second charging score, thereby completing the location-based convenience scoring.

[0110] This application embodiment discretizes the interval distance into high or low convenience scores by setting a distance threshold, which simplifies the quantification process of spatial factors, ensures the rapid response and stable execution of the charging strategy in the geographical dimension, and improves the user charging experience.

[0111] Optionally, the method further includes: in response to detecting that the vehicle triggers a charging event by updating the charging device, obtaining the charging frequency of the vehicle at the updating charging device, wherein the updating charging device is a charging device other than the multiple charging devices to be selected; in response to the charging frequency of the updating charging device being greater than that of any one of the multiple charging devices to be selected, updating the multiple charging devices to be selected based on the updating charging device.

[0112] The aforementioned updated charging equipment refers to charging facilities that are actually being charged by the vehicle but have not yet been included in the current system's list of frequently used charging equipment candidates. These updated charging facilities represent charging locations newly discovered or occasionally used by the user, and are the objects that the power control system needs to evaluate to include as long-term frequently used locations. By identifying such equipment, the power control system can dynamically expand the user's coverage, ensure the completeness and timeliness of charging habit records, and avoid deviations in the calculation of target power status values ​​due to omissions in location data, thereby achieving self-improvement and iteration of the charging database.

[0113] The charging frequency of the aforementioned updated charging equipment refers to the cumulative number of charging events within the statistical period for this specific updated charging equipment. The charging frequency of updated charging equipment is used to measure the popularity or importance of the newly discovered equipment relative to the equipment in the existing candidate set. By comparing this frequency with the frequencies of the equipment in the candidate set, the power control system can objectively assess whether existing low-frequency equipment needs to be replaced. This process achieves dynamic optimization of the frequently used location list, ensuring that the charging locations that best suit the user's current habits are always retained, thus improving the adaptability and personalization of the strategy.

[0114] In one optional embodiment, the vehicle controller monitors the geographical coordinates of the charging devices in real time during the charging process. If the geographical coordinates of the charging device do not match the coordinates of any device in the candidate set, the device is marked as an updated charging device and the charging event is recorded. The power control system then queries the historical charging records of the updated charging device to calculate the charging frequency and compares the charging frequency with the lowest frequency device in the candidate set. If the updated charging device has a high usage frequency, update logic is triggered to add the new device to the set or replace the original low-frequency device, thereby maintaining the activity of the frequently used location list.

[0115] This application embodiment achieves adaptive improvement of the user charging habit model by dynamically evaluating the frequency of new charging locations and updating the set of commonly used devices. This ensures that the power control strategy is always based on the latest and most relevant charging preferences, thereby improving the intelligence level of the power control system and user satisfaction.

[0116] Optionally, updating the selected multiple charging devices based on the updated charging device includes: in response to the number of the selected multiple charging devices being less than a preset threshold, adding an updated charging device to the selected multiple charging devices to update the selected multiple charging devices; in response to the number of the selected multiple charging devices being greater than or equal to the preset threshold, determining a preset charging device among the selected multiple charging devices, and replacing the preset charging device with the updated charging device to update the selected multiple charging devices, wherein the charging frequency of the preset charging device is lower than that of the other charging devices among the selected multiple charging devices excluding the preset charging device.

[0117] The aforementioned preset threshold refers to the maximum capacity limit set by the system for multiple sets of charging devices to be selected, used to limit the size of the list of frequently used charging locations. The preset threshold ensures both limited data storage and efficient management, preventing excessive memory consumption or reduced retrieval efficiency due to the unlimited accumulation of charging locations. The preset threshold is typically set based on device storage capacity, system processing performance, and statistics on the number of locations frequently used by typical users, aiming to balance the comprehensiveness of records with system operating efficiency, ensuring that representative charging locations are retained with limited resources, and maintaining the real-time performance and accuracy of policy execution.

[0118] The aforementioned preset charging devices refer to the charging facilities with the lowest charging frequency selected from a pool of potential charging devices. These preset charging devices represent the locations least relied upon or used by the user in the current list of frequently used locations, and are the targets the system decides to eliminate. By identifying preset charging devices, the power control system can locate the lowest-value element in the set, providing a target for replacement operations. The determination of preset charging devices is based on frequency ranking, ensuring that their frequency is lower than that of other devices in the set, thereby guaranteeing the rationality of the replacement operation.

[0119] In one optional embodiment, the vehicle's processor first queries the current number of elements in the set of multiple charging devices to be selected and compares the current number of elements with a preset threshold. If the current number of elements is less than the preset threshold, the vehicle's processor directly adds the identifier and frequency information of the updated charging device to the set, maintaining the original order, thus completing the expansion and update of the set. If the current number of elements is greater than or equal to the preset threshold, the processor traverses the set to find the device with the lowest charging frequency as the preset charging device, removes the preset charging device from the set, and inserts the updated charging device into the correct position according to the frequency sorting, thereby completing the replacement and update of the set.

[0120] In another optional embodiment, the cloud server receives the status of the selectable charging device sets and updated charging device information reported by the vehicle, and executes set management logic in the cloud database. If the size of the selectable charging device sets is not full, the cloud directly adds and updates the charging devices and synchronously updates the list. If the selectable charging device sets are full, the cloud uses a sorting algorithm to determine the device with the lowest frequency, performs a replacement operation, updates the user data in the cloud database, and sends the updated list of frequently used locations to the vehicle, achieving intelligent management and data synchronization.

[0121] This application embodiment ensures that the scale of commonly used charging equipment sets is controllable and the content is of high quality through dynamic capacity management and elimination mechanisms, thereby improving the accuracy of data storage efficiency strategy decisions.

[0122] Figure 2 This is a schematic diagram of an intelligent control strategy for the battery balance value based on the driver's charging habits, according to an embodiment of this application. Figure 2 As shown, the power balance control strategy comprises six modules: a charging preparation module, a charging date recording and storage module, a charging day interval module, a charging frequency module, a charging location module, and a target power status module. The charging device sends a signal to the charging preparation module, which in turn sends charging conditions to the charging frequency module, which outputs the charging frequency and location. The charging preparation module sends the charging date to the charging date recording and storage module, and based on the stored charging dates, sends charging interval parameters to the charging frequency module. The charging preparation module sends charging conditions to the charging location module. The charging location module, based on the vehicle navigation system, sends frequently used charging locations to the target power status module, which outputs the target power status and its latitude and longitude.

[0123] The charging preparation module mainly handles the conditions and parameters required for vehicle charging, including fast charging, slow charging, battery current, SOC after charging, and charging time. Its primary purpose is to ensure the vehicle is actually charging and prevent the following situations: the charging gun is plugged in but no charging is actually occurring (e.g., a malfunctioning charging station); insufficient charging time (e.g., the driver only charges for 2 minutes before the charging station malfunctions or they have to stop charging temporarily). This embodiment sets the charging time to 12 minutes; charging is only considered complete if the charging time reaches 12 minutes. This 12 minutes can be calibrated based on testing. Insufficient charging capacity (e.g., assuming the driver charges from 20% to 40% of the reserve capacity; this embodiment sets the capacity to 50% for a single charge to be considered complete). Therefore, charging below 50% is not considered a full charge.

[0124] The module for recording and storing charging dates mainly records the date when the car is currently charging, for example, the date includes the year, month, and day, and stores the charging date after charging is completed, in preparation for obtaining the charging interval days later.

[0125] The charging day interval module uses an algorithm to calculate the difference between the current charging date and the previous charging date to obtain the number of days between charging days. It further records the historical charging frequency, thus preparing for the scoring of the first and second charging scores.

[0126] The charging frequency module primarily scores based on the number of days between charging intervals. For example, 0.1 points are added for intervals within 3 days (the specified 3 days can be determined based on test results), and 0.1 points are deducted for intervals exceeding 3 days. Furthermore, this embodiment of the application sets upper and lower limits for the score, with the upper limit being 2 points and the lower limit being 1 point. When the final score is between 1.3 and 1.7, it indicates a high charging frequency, and the charging frequency flag is set to 1.

[0127] The charging location module primarily obtains frequently used charging locations from in-vehicle navigation information to determine the target charging location. This embodiment uses latitude and longitude coordinates for location marking. Furthermore, an algorithm module is added to the charging location module. This algorithm module first provides ten empty arrays to record and store multiple frequently used charging locations, and then scores these ten locations, adding points for each visit. The locations are also sorted from highest to lowest score. If all ten empty arrays are full and an eleventh new frequently used location appears, the algorithm eliminates the ten locations with the lowest scores, thus achieving real-time updates and saving memory.

[0128] The target battery status module manages the target battery status value by subtracting the location of a frequently used location from the current vehicle location, using the distance between the vehicle and the charging location. In this embodiment, a circle is drawn with the frequently used location as the center. If the distance between the vehicle and the center of the circle is less than or equal to the radius, it is determined that the vehicle is close to the frequently used location. In this case, the vehicle does not need to start the engine and can operate in pure electric mode, thereby maximizing energy utilization and achieving energy saving.

[0129] Figure 3 This is a schematic diagram of a smart control strategy for battery balance value based on driver charging habits, according to an embodiment of this application. Figure 3 As shown in the diagram. First, the charging preparation module obtains and stores the current charging date (year, month, and day). The charging interval in days is calculated by subtracting the current date from the previously stored date. A scoring mechanism is used to rate this interval, thus determining the driver's historical charging frequency. Simultaneously, the charging location module obtains frequently used charging locations. The target battery level is then calculated by subtracting the latitude and longitude of the current location from the frequently used charging locations, based on the coordinates of the current location from those coordinates in the vehicle's navigation system.

[0130] This application embodiment also establishes triggering conditions, the specific contents of which are as follows: Condition 1 is that the vehicle's fast charging state is True. Condition 2 is that the vehicle's slow charging state is True. Condition 3 is that the charging current is less than 0.

[0131] The True and False values ​​mentioned above are two basic values ​​in Boolean logic, representing true / yes / true and false / no / false, respectively. In the hardware or software code of a power control system, they typically correspond to high and low level signals, such as 1 and 0.

[0132] If conditions 1 and 3 or conditions 2 and 3 are met simultaneously, the conditions for triggering the vehicle charging state are met.

[0133] This application further improves upon the above-mentioned charging state triggering conditions by adding two special conditions to satisfy certain special situations. Condition 4 is that the charging time exceeds 12 minutes. Condition 5 is that the target SOC exceeds 50%.

[0134] Condition 4 is to prevent unforeseen circumstances such as temporary interruption of charging by the driver or sudden malfunction of the charging station. For example, in this embodiment, a charge is not considered complete if the charging time is less than 12 minutes. Condition 5 is to address situations where some drivers need a full tank of gas and a full battery for a long trip the next day, but the battery level is not yet sufficient for charging. For example, assuming a charge from 80% to 100%, this is also not considered a complete charge in this embodiment.

[0135] Therefore, a charging cycle is considered complete only when conditions 1, 3, 4, 1, 3, 5, 2, 3, 4, or 2, 3, 5 are met. At this point, the charging date, i.e., the year, month, and day of the charging, can be recorded and stored.

[0136] As a further improvement to the embodiments of this application, the embodiments of this application also include a date delay module when storing the date. This module is designed to ensure that the charging interval is within 3 days. This is to prepare for the scoring in the later stages of the embodiments of this application. The aforementioned 3 days can also be adjusted according to the actual situation. This is because the user meets the charging conditions, but the daily power consumption is very low, requiring 5 days to charge. In this case, the date needs to be delayed to within 3 days to meet the strategy requirements of the embodiments of this application.

[0137] Finally, in this embodiment of the application, the difference between the last charging date and the current charging date can be used to obtain the number of days between charging and charging.

[0138] This application's embodiment further improves the scheme by applying a scoring mechanism to a strategy for implementing driver charging habits for the first time. The conditions for triggering the scoring mechanism are as follows: Condition 6 is that the vehicle has completed one charge. Condition 7 is that the interval between charges is less than 3 days.

[0139] If condition 6 is triggered, then condition 7 will be triggered next. In this embodiment, an initial score of 0 will be input into the scoring module. If the interval is less than 3 days, 0.1 points will be added, up to a maximum of 2 points. If the interval is 3 days or more, 0.1 points will be subtracted, down to a maximum of 1 point. This embodiment will obtain a score and store it. The next time, the score will be added or subtracted from the previously stored score. Finally, this embodiment will obtain a charging frequency represented by a Boolean value based on the score. The aforementioned Boolean value is a data type with only two possible values.

[0140] To prevent sudden changes in scores, this application embodiment designs a module with an upper limit of 1.7 and a lower limit of 1.3 for the score hysteresis interval. If the score is less than 1.3, the output is 0; if it is greater than 1.7, the output is 1. Decrease from 1.7 and output 1 until it reaches 1.3, at which point 0 is output. Conversely, increase from 1.3 and output 0 until it reaches 1.7, at which point 1 is output.

[0141] This embodiment adds a switch module to accommodate vehicle power-on and power-off scenarios. When the vehicle is powered off and then back on, the power control system resets. Regardless of whether the previous score was True or False, it will all be False after the reset. This embodiment requires a switch in this case. If the charging frequency before the vehicle was powered off was True, this embodiment manually inputs a True score of 2, thus matching the score before the power was off. If the last charging frequency before the vehicle was powered off was False, then the score before the power was off can be used directly.

[0142] This embodiment of the application records the driver's charging location, ultimately obtaining the target SOC and the charging location error boolean value. To trigger charging location recording, conditions 1 and 3 or 2 and 3 above must be met, and the latitude and longitude of the charging location at this time must be input using the vehicle navigation system. At this point, this embodiment of the application obtains the latitude and longitude information of the charging location.

[0143] Figure 4 This is a schematic diagram of an algorithm module for updating frequently used locations in an intelligent control strategy for battery balance values ​​based on driver charging habits, according to an embodiment of this application. Figure 4 As shown, the current latitude and longitude, current date and time, stored date and time, stored latitude and longitude, and the stored array are input into the frequently used charging location record storage update algorithm module, which outputs the latitude and longitude of frequently used charging locations. This application achieves dynamic updating and memory improvement of frequently used charging locations by introducing a scoring mechanism and an array elimination algorithm. The above module can automatically identify and retain frequently used charging locations and eliminate low-frequency or invalid locations, ensuring the timeliness and representativeness of the stored data. This application embodiment not only avoids the memory overflow problem caused by data accumulation, but also improves the accuracy of frequently used location data, thereby improving the target SOC control strategy based on more accurate geographical information and enhancing the intelligence level and range economy of the energy management system.

[0144] To obtain and update the latitude and longitude of multiple charging locations in real time, this application employs a scoring mechanism to design an algorithm. First, 10 empty arrays are initialized. Whenever a vehicle arrives at a location, a location is added to one of these 10 arrays until all 10 arrays are full. If duplicate locations exist, their frequency is updated; locations with higher frequency receive more points. This process continues until the 11th new location appears, at which point the lowest-scoring locations in the previous 10 are discarded. This process saves space and ensures the reusability of locations.

[0145] Finally, by calculating the difference between the latitude and longitude of the vehicle during its journey and the latitude and longitude of the commonly used charging locations, when the difference is less than or equal to 5 kilometers, the target SOC and the boolean error of the charging location are output.

[0146] According to an embodiment of this application, a method for controlling the battery power of a vehicle is also provided. Figure 5 This is a flowchart of an optional vehicle battery control method according to an embodiment of this application, such as... Figure 5 As shown, the method includes the following steps:

[0147] Step S502: Obtain the historical charging frequency and current vehicle location of the vehicle during the historical charging period.

[0148] Step S504: Determine multiple charging devices to be selected, and obtain the distance between the current vehicle location and any one of the charging devices to be selected.

[0149] In this process, the frequency of vehicle use of charging equipment is used to determine the multiple charging devices to be selected.

[0150] Step S506: Based on the distance between the vehicle and any one of the selectable charging devices, determine the target charging location from the charging locations corresponding to the multiple selectable charging devices.

[0151] Step S508: Determine the distance between the current vehicle location and the target charging location; determine the adjacent triggering time points of the vehicle's charging event based on the historical charging frequency; determine the triggering interval duration of the charging event based on the adjacent triggering time points.

[0152] Step S510: In response to the trigger interval being less than the preset trigger interval, a first charging score is determined based on the sum of the initial charging score and the preset score.

[0153] In step S512, in response to the trigger interval being greater than or equal to the preset trigger interval, a first charging score is determined based on the difference between the initial charging score and the preset score.

[0154] Step S514: Determine the second charging fraction of the interval distance based on the interval distance and the preset distance.

[0155] Step S516: Determine the target power status value based on the first charging fraction and the second charging fraction.

[0156] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0157] According to an embodiment of this application, an apparatus embodiment for a vehicle battery control method is provided. It should be noted that the apparatus can be used to execute the above-described vehicle battery control method. Figure 6 This is a schematic diagram of a vehicle power control device according to an embodiment of this application, such as... Figure 6 As shown, the device includes: an acquisition module 602, a first determination module 604, a second determination module 606, and a third determination module 608.

[0158] The acquisition module 602 is used to acquire the historical charging frequency of the vehicle during a historical time period and the current vehicle location; the first determination module 604 is used to determine multiple charging devices to be selected and acquire the distance between the current vehicle location and any one of the charging devices to be selected, wherein the multiple charging devices to be selected are determined by statistically analyzing the frequency of the vehicle's use of the charging devices; the second determination module 606 is used to determine the target charging location from the charging locations corresponding to the multiple charging devices to be selected based on the distance between the vehicle and any one of the charging devices to be selected; the third determination module 608 is used to determine the target battery status value based on the historical charging frequency and the target charging location, wherein the target battery status value is used to determine the vehicle's driving strategy.

[0159] The third determining module is also used to determine the interval distance between the current vehicle location and the target charging location; and to determine the target battery status value based on the interval distance and historical charging frequency.

[0160] The third determining module is also used to determine the first charging fraction corresponding to the historical charging frequency; determine the second charging fraction of the interval distance based on the interval distance and the preset distance; and determine the target power status value based on the first charging fraction and the second charging fraction.

[0161] The third determining module is also used to determine the adjacent triggering time points of the vehicle's charging event based on the historical charging frequency; determine the triggering interval duration of the charging event based on the adjacent triggering time points; and update the initial charging score based on the triggering interval duration to obtain the first charging score.

[0162] The third determining module is further configured to determine a first charging score based on the sum of the initial charging score and the preset score in response to a trigger interval duration being less than a preset trigger interval duration; and to determine a first charging score based on the difference between the initial charging score and the preset score in response to a trigger interval duration being greater than or equal to the preset trigger interval duration.

[0163] The third determining module is also used to determine the first preset score as the first charging score in response to the sum being greater than the first preset value; and to determine the sum as the first charging score in response to the sum being less than or equal to the first preset value.

[0164] The third determining module is also used to determine the second preset score as the first charging score in response to the difference being less than the second preset value; and to determine the difference as the first charging score in response to the difference being greater than or equal to the second preset value.

[0165] The third determining module is also used to determine the third preset value as the second charging fraction in response to the interval distance being greater than the preset distance; and to determine the fourth preset value as the second charging fraction in response to the interval distance being less than or equal to the preset distance.

[0166] The device is also used to: in response to detecting that the vehicle triggers a charging event by updating the charging equipment, obtain the charging frequency of the vehicle at the updating charging equipment, wherein the updating charging equipment is a charging equipment other than the multiple charging equipment to be selected; and in response to the charging frequency of the updating charging equipment being greater than that of any one of the multiple charging equipment to be selected, update the multiple charging equipment to be selected based on the updating charging equipment.

[0167] The device is also used to: in response to the number of multiple charging devices to be selected being less than a preset threshold, add an update charging device to the multiple charging devices to be selected to update the multiple charging devices to be selected; in response to the number of multiple charging devices to be selected being greater than or equal to the preset threshold, determine a preset charging device among the multiple charging devices to be selected, and replace the preset charging device with the update charging device to update the multiple charging devices to be selected, wherein the charging frequency of the preset charging device is lower than that of other charging devices among the multiple charging devices to be selected excluding the preset charging device.

[0168] Embodiments of this application also provide a vehicle, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods described in various embodiments of this application when it runs.

[0169] Embodiments of this application also provide a computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0170] Embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the methods of various embodiments of this application.

[0171] Embodiments of this application also provide a computer program product, including a non-volatile computer-readable storage medium for storing a computer program that, when executed by a processor, implements the methods in various embodiments of this application.

[0172] Embodiments of this application also provide a computer program that, when executed by a processor, implements the methods described in the various embodiments of this application.

[0173] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0174] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0175] 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 units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0176] Furthermore, the functional units in the various embodiments of this application 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. The integrated unit can be implemented in hardware or as a software functional unit.

[0177] If the integrated unit 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 application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0178] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for controlling the battery level of a vehicle, characterized in that, include: Obtain the historical charging frequency and current vehicle location of the vehicle during a historical time period; Multiple charging devices to be selected are determined, and the distance between the current vehicle location and any one of the charging devices to be selected is obtained. The multiple charging devices to be selected are determined by statistically analyzing the frequency with which the vehicle uses the charging devices. Based on the distance between the vehicle and any one of the selected charging devices, the target charging location is determined from the charging locations corresponding to the multiple selected charging devices. Based on the historical charging frequency and the target charging location, a target battery status value is determined, wherein the target battery status value is used to determine the vehicle's driving strategy.

2. The method according to claim 1, characterized in that, Based on the historical charging frequency and the target charging location, the target power status value is determined, including: Determine the distance between the current vehicle location and the target charging location; The target power status value is determined based on the interval distance and the historical charging frequency.

3. The method according to claim 2, characterized in that, Determining the target battery status value based on the interval distance and the historical charging frequency includes: Determine the first charging fraction corresponding to the historical charging frequency; Based on the interval distance and the preset distance, a second charging fraction of the interval distance is determined; The target power status value is determined based on the first charging score and the second charging score.

4. The method according to claim 3, characterized in that, Determining the first charging fraction corresponding to the historical charging frequency includes: Based on the historical charging frequency, determine the adjacent triggering time points of the vehicle's charging event; Based on the adjacent trigger time points, the trigger interval duration of the charging event is determined; Based on the trigger interval duration, the initial charging score is updated to obtain the first charging score.

5. The method according to claim 4, characterized in that, Based on the trigger interval duration, the initial charging score is updated to obtain the first charging score, including: In response to the trigger interval being less than a preset trigger interval, the first charging score is determined based on the sum of the initial charging score and the preset score; In response to the trigger interval being greater than or equal to the preset trigger interval, the first charging score is determined based on the difference between the initial charging score and the preset score.

6. The method according to claim 5, characterized in that, The first charging score is determined based on the sum of the initial charging score and the preset score, including: In response to the sum being greater than a first preset value, the first preset score is determined to be the first charging score; In response to the sum being less than or equal to the first preset value, the sum is determined to be the first charging score.

7. The method according to claim 5, characterized in that, Determining the first charging score based on the difference between the initial charging score and the preset score includes: In response to the difference being less than a second preset value, the second preset score is determined to be the first charging score; In response to the difference being greater than or equal to the second preset value, the difference is determined to be the first charging score.

8. The method according to claim 3, characterized in that, Based on the interval distance and the preset distance, a second charging fraction for the interval distance is determined, including: In response to the interval distance being greater than the preset distance, a third preset value is determined to be the second charging fraction; In response to the interval distance being less than or equal to the preset distance, a fourth preset value is determined to be the second charging fraction.

9. The method according to any one of claims 1 to 8, characterized in that, The method further includes: In response to detecting that the vehicle triggers a charging event while updating the charging equipment, the charging frequency of the vehicle at the updating charging equipment is obtained, wherein the updating charging equipment is a charging equipment other than the plurality of charging equipment to be selected; In response to the updated charging device having a charging frequency greater than any of the selected charging devices, the selected charging devices are updated based on the updated charging device.

10. The method according to claim 9, characterized in that, Updating the multiple selectable charging devices based on the updated charging device includes: In response to the fact that the number of the multiple charging devices to be selected is less than a preset threshold, the updated charging device is added to the multiple charging devices to be selected to update the multiple charging devices to be selected; In response to the number of the plurality of charging devices to be selected being greater than or equal to the preset threshold, a preset charging device is determined among the plurality of charging devices to be selected, and the preset charging device is replaced with the updated charging device to update the plurality of charging devices to be selected, wherein the charging frequency of the preset charging device is lower than that of the other charging devices among the plurality of charging devices to be selected, excluding the preset charging device.

11. A vehicle, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, performs the method according to any one of claims 1 to 10.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device on which the storage medium is located to perform the method according to any one of claims 1 to 10.

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