Charging management method and device of vehicle, computer device and storage medium

Abstract

The present application relates to the technical field of charging management, and discloses a charging management method and device for a vehicle, computer equipment and a storage medium, wherein the present application generates a charging strategy according to the historical charging habits of the vehicle itself and charging records of the same vehicle model, so that the charging duration and charging power can match the actual use of the vehicle, thereby improving the matching degree of the charging strategy and the demand of the vehicle. When the migration condition is met, the target charging position is automatically determined according to the demand priority, and the vehicle is controlled to migrate, thereby avoiding manual judgment and operation of the user, and taking into account the charging efficiency and cost. After reaching the target charging position, the charging state is synchronized to the user terminal in real time, so that the user can know the charging progress without actively inquiring, thereby improving the intelligent degree of charging management and improving the user experience.

Description

Technical Field

[0001] This invention relates to the field of charging management technology, and more specifically to a method, device, computer equipment, and storage medium for vehicle charging management. Background Technology

[0002] In the field of vehicle charging management technology, users usually need to select a suitable charging location and manually drive the vehicle into the charging position when charging their vehicle.

[0003] In related technologies, vehicle charging strategies typically employ fixed, factory-preset parameters, failing to adapt to varying usage patterns or overall charging data across different vehicle models. This results in a low match between the charging strategy and actual vehicle needs. Furthermore, when users need to charge, they face the challenge of choosing from multiple available charging locations within the parking platform. Users often rely on personal experience to make random selections, failing to consider factors such as charging efficiency and cost, leading to an inefficient choice of charging location. Moreover, during or after charging, users must continuously monitor the progress, manually determine if relocation conditions are met, and move the vehicle to another location. During charging, users can only obtain information about the charging status through active monitoring or inquiry, lacking timely updates. These shortcomings interact, resulting in an overall lack of intelligence in vehicle charging management and a poor user experience. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a vehicle charging management method, device, computer equipment, and storage medium to solve the problems in related technologies such as low matching degree between vehicle charging strategies and actual vehicle needs, lack of rationality in charging location selection, and the need for users to continuously monitor charging status and manually perform migration operations.

[0005] In a first aspect, embodiments of the present invention provide a vehicle charging management method, the method comprising: The system obtains the vehicle's historical charging habits and charging records of the same model from the server, and generates the vehicle's charging strategy based on the historical charging habits and charging records of the same model. When the vehicle is detected to meet the migration conditions, a target charging location is determined within the parking platform according to the vehicle's demand priority, and the vehicle is controlled to migrate from its current parking location to the target charging location. After the vehicle arrives at the target charging location, the charging strategy is executed, and the charging status of the vehicle is synchronized in real time to the user terminal associated with the vehicle.

[0006] This invention generates personalized charging strategies based on a vehicle's historical charging habits and charging records of the same model, ensuring that charging time and power match actual vehicle usage. This solves the problem of low matching between existing charging strategies using fixed parameters and actual vehicle needs. Furthermore, by automatically determining the target charging location and controlling vehicle migration based on demand priority when the vehicle meets migration conditions, users can intelligently select charging locations without manual judgment or operation, balancing charging efficiency and cost. This addresses the issues of users needing to frequently monitor charging status, manually move the vehicle, and struggle to make reasonable choices among multiple charging locations. Moreover, by executing the charging strategy and synchronizing the charging status to the user's terminal in real time after the vehicle arrives at the target charging location, users can promptly learn about the charging progress without actively querying. Additionally, when the user is in a highly focused scenario, only safety reminders are pushed, while routine status notifications are filtered out, thus solving the problem of user distraction due to frequent notifications. In summary, this invention achieves adaptive optimization of charging strategies, intelligent migration of charging locations, and contextualized push notifications of charging status, ultimately improving the overall intelligence level of vehicle charging management and user experience.

[0007] In conjunction with the first aspect, in one implementation, the historical charging habits include at least one of the vehicle's historical charging duration, historical charging power, historical charging start time, and historical charging end time; the same-model charging records include statistical data on the charging behavior of other vehicles of the same model as the vehicle stored on the server. The step of generating the vehicle's charging strategy based on the historical charging habits and the charging records of the same vehicle model includes: The charging duration and charging power of the vehicle are determined based on the historical charging habits and the charging records of the same vehicle model, and the charging strategy is generated based on the charging duration and the charging power.

[0008] The technical solution provided by this invention first acquires at least one of the vehicle's historical charging duration, historical charging power, historical charging start time, and historical charging end time, as well as charging behavior statistics of other vehicles of the same model stored on the server. This provides a dual data foundation for the generation of subsequent charging strategies, combining individual vehicle usage characteristics and group charging patterns. This solves the problem in existing technologies where charging strategies rely solely on factory-fixed parameters, resulting in low matching with actual vehicle needs. Furthermore, by determining the vehicle's charging duration and power based on historical charging habits and charging records of the same model, and generating a charging strategy based on these determined parameters, the charging strategy integrates both the vehicle's own charging behavior patterns and the charging experience of other vehicles of the same model. This solves the problem of charging strategies deviating from actual user habits due to a single data source. Moreover, because the determination process for charging duration and power integrates individual historical data and group statistical data, the generated charging strategy can adapt to the differences in charging behavior among different users. This solves the problem of low charging efficiency or increased battery wear caused by using uniform charging parameters for users with different driving habits. In summary, the embodiments of the present invention inevitably achieve individualized customization of charging strategies, multi-dimensional fusion of data sources, and dynamic adaptation of charging parameters, and ultimately improve the accuracy of matching charging strategies with actual vehicle needs and charging efficiency.

[0009] In conjunction with the first aspect, in one implementation, the demand priority includes charging priority; the step of determining a target charging location within the parking platform based on the vehicle's demand priority and controlling the vehicle to move from its current parking location to the target charging location includes: When the demand priority is charging priority, any available charging location within the parking platform is determined as the target charging location, and the vehicle is controlled to move from its current parking location to the target charging location.

[0010] The technical solution provided by this invention prioritizes charging, ensuring the vehicle understands that the user's primary goal is to charge as quickly as possible, regardless of charging costs. This provides a clear decision-making guide for determining the target charging location, solving the problem in existing technologies where users, even with urgent charging needs, still have to compare and choose among multiple available charging locations, leading to charging delays. Furthermore, when charging is prioritized, any available charging location within the parking platform is designated as the target charging location, eliminating the need for the vehicle to compare costs or wait for a specific location to become available. This solves the problem of users missing the optimal charging opportunity due to hesitation or comparison. Moreover, by controlling the vehicle to move directly from its current parking position to any available charging location, the vehicle can enter charging mode as quickly as possible, thus eliminating the time consumption caused by manual operation and decision-making. In summary, this invention achieves rapid decision-making, instant response in location selection, and efficient vehicle migration in charging-priority scenarios, ultimately improving user charging efficiency and the overall charging experience.

[0011] In conjunction with the first aspect or its corresponding implementation, in one implementation, the demand priority includes cost priority; the step of determining the target charging location within the parking platform according to the vehicle's demand priority and controlling the vehicle to move from its current parking location to the target charging location includes: When the demand priority is cost priority, at least one candidate charging location that meets the cost condition is obtained, and the candidate charging location with the lowest cost is selected as the target charging location. If the target charging location is currently idle, then the vehicle will be moved to the target charging location; or, If the target charging location is currently occupied, perform one of the following operations: The candidate charging location with the second lowest cost and currently idle is identified as the new target charging location, and the vehicle is controlled to move to the new target charging location; or, the vehicle is controlled to continue waiting until the target charging location becomes idle, and then the vehicle is moved to the target charging location.

[0012] The technical solution provided by this invention prioritizes demand based on cost and acquires at least one candidate charging location that meets the cost criteria. This allows the vehicle to clearly understand that the user's primary goal is to control charging costs, thus providing a decision-making guide for selecting the lowest-cost target charging location. This solves the problem in existing technologies where users, when focused on charging costs, find it difficult to quickly identify the lowest-cost location from multiple charging locations. Furthermore, by selecting the lowest-cost candidate charging location as the target charging location and directly migrating to it when it becomes available, the vehicle can automatically lock and execute the selection of the optimal charging location, thereby eliminating the decision-making burden caused by manual price comparison and selection. Moreover, by providing two optional operations—a downgraded selection method and a waiting method—when the target charging location is occupied, users can flexibly choose according to their tolerance for time costs. That is, a second-lowest-cost and available location satisfies the needs of users who do not want to wait, while waiting for the preferred location to become available satisfies the needs of users who insist on the lowest cost. This solves the problem that a single processing method cannot accommodate the different time cost preferences of users. In summary, the embodiments of the present invention will inevitably achieve automatic selection of the most cost-effective location, dual-path adaptation in occupied scenarios, and flexible response to user time cost preferences, and ultimately improve the rationality of charging location selection and user satisfaction in cost-priority scenarios.

[0013] In conjunction with the first aspect, in one implementation, controlling the vehicle to move from its current parking location to the target charging location includes: If multiple vehicles compete for the target charging location at the same time, the timestamp of each vehicle confirming its journey to the target charging location, as recorded by the server, is obtained. The vehicle with the highest priority to migrate to the target charging location is determined based on the order of the timestamps.

[0014] The technical solution provided by this invention obtains the timestamp of each vehicle confirming its arrival at the target charging location, as recorded by the server, when multiple vehicles are competing for the same location simultaneously. This provides a unified and immutable quantitative basis for determining the order of competition among vehicles, thus providing an objective data foundation for determining migration priority. This solves the problem of competition or chaos that may occur when multiple vehicles arrive at the same charging location simultaneously, due to the lack of a fair allocation mechanism in the prior art. Furthermore, by determining the vehicle with the highest priority to migrate to the target charging location based on the order of timestamps, the vehicle with the earliest confirmation time obtains priority migration rights, thereby solving the unfairness problem caused by subjective judgment or random allocation. Moreover, since the timestamp accuracy reaches the millisecond level and is uniformly recorded by the server, the order can still be accurately distinguished when multiple vehicles initiate requests almost simultaneously. Vehicles that confirm first migrate first, while vehicles that confirm later queue or reselect, thereby solving the problems of uncertain waiting time and resource allocation disputes caused by users competing for charging locations. In summary, the embodiments of the present invention inevitably achieve fair quantification of charging location competition, objective determination of migration priority, and orderly management in multi-vehicle scenarios, and ultimately improve the fairness of charging resource allocation and multi-vehicle collaborative efficiency.

[0015] In conjunction with the first aspect, in one embodiment, the method further includes: Obtain the initial charging plan for the vehicle, which includes an initial charge amount and an initial driving route. The initial charge amount indicates the vehicle's current battery level or the battery level to be reached after the charging strategy is completed. When a change is detected in the real-time activity data associated with the vehicle, a target charging plan is generated based on the changed real-time activity data. The target charging plan includes a target charging amount and a target driving route, wherein the target charging amount is used to indicate the amount of electricity the vehicle needs to reach after the change in the real-time activity data. Based on the target charging amount and the target driving route, calculate the estimated additional power consumption of the target charging plan relative to the initial charging plan; If the estimated additional power consumption is greater than the additional power consumption threshold, a power replenishment plan adjustment request is generated and sent to the user terminal associated with the vehicle.

[0016] The technical solution provided by this invention obtains an initial charging plan for the vehicle, including an initial charging amount and an initial driving route. This provides a benchmark for subsequent trip change detection and power demand comparison. Based on this, when changes are detected in real-time activity data associated with the vehicle, a target charging plan is generated based on the changed data. This target charging plan includes a target charging amount and a target driving route, enabling the vehicle to sense changes in the user's trip and re-plan its power demand. This solves the problem of insufficient power or overcharging caused by the vehicle continuing to execute the original plan after a user's trip changes. Furthermore, by calculating the estimated additional power consumption based on the target charging amount and target driving route, and generating an adjustment request and sending it to the user terminal when the estimated additional power consumption exceeds a threshold, the user can know whether additional charging is needed without having to judge the impact of trip changes on power. This solves the problem of trip disruption caused by the user ignoring the impact of power. In summary, this invention inevitably achieves real-time perception of trip changes, dynamic calculation of power demand, and proactive push of adjustment requests, ultimately improving the adaptability of charging management to changes in user travel plans and enhancing driving safety.

[0017] In conjunction with the first aspect or its corresponding implementation, in one implementation, the method further includes: Receive adjustment feedback from the user terminal in response to the energy replenishment plan adjustment request, the adjustment feedback including agreeing to the adjustment or rejecting the adjustment; If the adjustment feedback is "agree to adjustment", then the vehicle is recharged based on the estimated additional power consumption, or the planned charging points in the target driving route are obtained, and the target driving route is adjusted according to the estimated additional power consumption and the charging points. If the feedback is a refusal to adjust, then the number of charging points will be increased along the target driving route.

[0018] The technical solution provided by this invention first receives adjustment feedback from the user terminal regarding the request to adjust the charging plan. This feedback includes either agreement to the adjustment or rejection of the adjustment. This allows the vehicle to determine subsequent operations based on the user's true intentions, thus solving the problem of the vehicle being unable to understand the user's decision-making intent after sensing a change in the route. Furthermore, when the adjustment feedback is "agree to adjust," the vehicle is either recharged based on the estimated additional power consumption, or pre-planned charging points along the target route are obtained and the target route is adjusted based on the estimated additional power consumption and the charging points. This allows the vehicle to choose between returning to charging or optimizing the route, provided the user agrees to the adjustment. This solves the problem that a single processing method cannot adapt to different driving stages and charging conditions. Finally, when the adjustment feedback is "reject," the number of charging points along the target route is increased. This ensures trip safety even if the user refuses to recharge, thus solving the problem of trip interruption due to insufficient battery power after the user refuses to adjust. In summary, the embodiments of the present invention inevitably achieve immediate response to user decisions, dual-path adaptation for charging or route adjustments, and a safety net for travel safety, and ultimately improve the coordination level between user autonomy and vehicle intelligent execution during the adjustment of charging plans.

[0019] Secondly, embodiments of the present invention provide a vehicle charging management device, the device comprising: The strategy generation module is used to obtain the vehicle's historical charging habits and charging records of the same model from the server, and generate the vehicle's charging strategy based on the historical charging habits and the charging records of the same model. The location migration module is used to determine the target charging location within the parking platform according to the vehicle's demand priority when it is detected that the vehicle currently meets the migration conditions, and control the vehicle to migrate from the current parking location to the target charging location; The strategy execution module is used to execute the charging strategy after the vehicle arrives at the target charging location, and to synchronize the charging status of the vehicle with the user terminal associated with the vehicle in real time.

[0020] Thirdly, embodiments of the present invention provide a computer device, including: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the vehicle charging management method of the first aspect or any corresponding embodiment described above.

[0021] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing computer instructions, which are used to cause a computer to execute the vehicle charging management method of the first aspect or any corresponding embodiment described above. Attached Figure Description

[0022] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0023] Figure 1 This is a schematic flowchart of a vehicle charging management method according to some embodiments of the present invention; Figure 2 This is a schematic diagram of the hardware connection of a charging-sharing ground lock platform according to some embodiments of the present invention; Figure 3 This is a structural block diagram of a vehicle charging management device according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] According to an embodiment of the present invention, a method for managing the charging 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.

[0026] This embodiment provides a vehicle charging management method, applied to a time-segment intelligent synchronization system for a shared charging lock platform. Figure 1 This is a flowchart of a vehicle charging management method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps: Step S101: Obtain the vehicle's historical charging habits and charging records of the same model from the server, and generate the vehicle's charging strategy based on the historical charging habits and charging records of the same model.

[0027] Step S102: When it is detected that the vehicle currently meets the migration conditions, the target charging location is determined in the parking platform according to the vehicle's demand priority, and the vehicle is controlled to migrate from the current parking location to the target charging location.

[0028] Step S103: After the vehicle arrives at the target charging location, the charging strategy is executed, and the charging status of the vehicle is synchronized with the user terminal associated with the vehicle in real time.

[0029] The vehicle charging management method provided in this embodiment generates a personalized charging strategy based on the vehicle's historical charging habits and charging records of the same model. This ensures that charging duration and power match the actual usage of the vehicle, solving the problem of low matching degree between the charging strategy and the actual needs of the vehicle due to the use of fixed parameters in the prior art. Furthermore, by automatically determining the target charging location and controlling the vehicle's migration based on demand priority when the vehicle meets the migration conditions, users can intelligently select the charging location without manual judgment or operation, while balancing charging efficiency and cost. This solves the problems of users needing to frequently monitor the charging status, manually move the vehicle, and make reasonable choices among multiple charging locations. Moreover, by executing the charging strategy after the vehicle arrives at the target charging location and synchronizing the charging status to the user's terminal in real time, users can promptly know the charging progress without actively querying. Furthermore, when the user is in a highly focused scenario, only safety reminders are pushed, and regular status notifications are filtered out, thus solving the problem of user distraction due to frequent notifications. In summary, this embodiment of the invention inevitably achieves adaptive optimization of the charging strategy, intelligent migration of the charging location, and scenario-based push notifications of the charging status, ultimately improving the overall intelligence level of vehicle charging management and the user experience.

[0030] Figure 2 This is a hardware connection diagram of a shared charging parking lock platform according to some embodiments of the present invention, used to illustrate the communication connection relationships between various hardware devices within the parking platform and between the parking platform and the server. This hardware connection architecture provides the underlying infrastructure support for the vehicle charging management method provided in this embodiment, enabling vehicles to interact with the parking platform and the server, thereby achieving functions such as self-learning charging strategy generation, automatic migration, and charging status synchronization.

[0031] like Figure 2As shown, the hardware connection architecture includes a smart synchronous charging parking space 01, a vehicle parked in the parking space 02, a charging parking lot entrance 03, a single parking space processor and parking space connection line 04, a single parking space processor 05, a counter-smart parking lock charging platform processor connection line 06, a platform signal aggregation line 07, a charging platform main processor 08, a charging platform local area network processor connection line 09, a charging platform main processor and local area network gateway connection line 10, a local area network gateway processing platform 11, a local area network gateway and server connection line 12, and a server 13.

[0032] The intelligent synchronous charging parking lock platform's charging parking space 01 is a physical location within the parking platform that provides vehicle parking and charging services. This parking space is equipped with a parking lock and is suitable for parking lots consisting of private parking spaces. The vehicle 02 parked in this space is the executing entity of the charging management method of this invention. During parking or charging, the charging status information or parking status information of vehicle 02 is anonymized and then synchronized to the server 13 through this hardware connection architecture, and the server 13 then provides feedback to the vehicle owner. The relationship between vehicle 02 and the various hardware devices within the parking platform is as follows: vehicle 02 acts as the decision-making and execution unit, while the processor and communication lines within the parking platform act as the sensing and transmission units. Vehicle 02 autonomously generates a charging strategy and controls its own migration by receiving charging location status and cost information provided by the parking platform, as well as historical charging habits and charging records of the same vehicle model obtained through the server.

[0033] The charging parking lot entrance 03 is located at the entrance of the parking platform. Before entering the charging parking lot entrance 03, vehicle 02 needs to upload its battery level and status data to the server 13. The battery level and status data include the remaining battery level of vehicle 02 and the average parking time of vehicle 02 on this parking platform in history. After vehicle 02 enters the charging parking lot entrance 03, it is included in the electronic fence range of the parking platform, and the hardware connection architecture begins to monitor vehicle 02 in real time and support data transmission.

[0034] Each charging parking space is equipped with a single parking space processor 05 to collect status signals from the corresponding charging parking space, send control commands, and transmit information, performing comprehensive operational processing. The single parking space processor and the parking space connection cable 04 are used to realize information transmission between the single parking space processor 05 and the corresponding charging parking space. During the execution of the charging strategy by vehicle 02, the single parking space processor 05 collects the occupancy status, idle status, and operating status of the charging space in real time, and transmits this data to vehicle 02 or server 13 via subsequent lines, providing vehicle 02 with the basis for determining the target charging location.

[0035] The opposing smart lock charging platform processor connection line 06 is used to connect two adjacent or opposing charging platform processors to realize the signal aggregation between adjacent processors. The aggregated signal is transmitted to the smart lock charging platform main processor 08 through the platform signal aggregation line 07.

[0036] The charging platform's main processor 08 is used to aggregate information uploaded by processors in each charging parking space, and also to issue execution commands to the individual parking space processors 05 in each charging parking space, as well as to synchronize information sent by the server 13. The main processor 08 is the core data aggregation and distribution unit within the parking platform. After vehicle 02 determines its target charging location, the main processor 08 sends the vehicle 02's migration command to the corresponding individual parking space processor 05, controlling the parking lock to unlock or lock, thus cooperating with vehicle 02 to complete the migration.

[0037] The charging platform LAN processor connection line 09 serves as a backup communication line. When the network connection is interrupted, the hardware connection architecture switches the charging data to the internal LAN communication mode via the charging platform LAN processor connection line 09. The data is directly transmitted to the LAN gateway processing platform 11 for internal network processing and operation, without going through the charging platform main processor 08. This backup mechanism ensures that the basic collaborative functions between charging spaces within the parking platform are not interrupted when the network is interrupted, and vehicle 02 can still obtain the charging location status information within the parking platform.

[0038] The connection line 10 between the charging platform's main processor and the local area network gateway is used to transmit the signals aggregated by the charging platform's main processor 08 to the local area network gateway processing platform 11 when the network connection is normal. The local area network gateway processing platform 11 then interacts with the server 13. Vehicle 02 obtains historical charging habits and charging records of the same vehicle model from the server 13, synchronizes its own charging status to the server 13, and then pushes it to the user terminal.

[0039] The LAN gateway processing platform 11 is used to cache and transmit all charging platform data summarized by the charging platform master processor 08 when the network connection is normal, and to interact with the server 13. When the network connection is interrupted, the LAN gateway processing platform 11 directly collects data from each charging platform for internal exchange processing to ensure that the basic collaborative functions between charging spaces within the parking platform are not interrupted.

[0040] The LAN gateway and server connection line 12 is used to realize information transmission between the LAN gateway processing platform 11 and the server 13 when the network connection is normal.

[0041] Server 13 is used to provide vehicle owners with the function of querying charging platform information data when vehicle 02 has not entered the electronic fence, and to handle information interaction between various mobile terminals. Server 13 stores historical charging habit data, charging record data of the same vehicle model, as well as the structure data and charging rule data of each parking platform, which are downloaded and used by vehicle 02 after entering the electronic fence.

[0042] The steps described above will be explained in detail below.

[0043] In step S101, the historical charging habits and charging records of the same model of the vehicle are obtained from the server, and the charging strategy of the vehicle is generated based on the historical charging habits and charging records of the same model.

[0044] In one implementation, historical charging habits include at least one of the vehicle's historical charging duration, historical charging power, historical charging start time, and historical charging end time; the same model charging record includes statistical data on the charging behavior of other vehicles of the same model stored on the server. The vehicle's charging strategy is generated based on historical charging habits and charging records of the same model, including: Based on historical charging habits and charging records of the same vehicle model, the charging time and charging power of the vehicle are determined, and a charging strategy is generated based on the charging time and charging power.

[0045] In this embodiment, the charging-sharing parking lock platform's time-segment intelligent synchronization system receives historical charging habits and charging records of the same vehicle model from the server. The server refers to a remote platform that provides data storage and computing services. Historical charging habits refer to charging-related behavior patterns formed during the current vehicle's past use, while charging records of the same vehicle model refer to statistical data on the charging behavior of other vehicles of the same model as the current vehicle stored on the server.

[0046] Specifically, historical charging habits can include at least one of the following: historical charging duration, historical charging power, historical charging start time, and historical charging end time. Historical charging duration refers to the time spent on each charging session in the past; historical charging power refers to the power used by the vehicle during past charging sessions; historical charging start time refers to the time when the vehicle started charging in the past; and historical charging end time refers to the time when the vehicle finished charging in the past.

[0047] Before generating a charging strategy, the smart synchronization system of the shared charging lock platform needs to obtain users' charging viewing records and charging-related queries on other charging devices. Charging viewing records include the frequency and timing of users checking the charging status of various charging devices such as mobile phones, smart devices, and electric bicycles. Charging-related queries include charging safety and operation issues searched by users through search engines, such as the risk of the vehicle being scratched by other vehicles during charging, and how to handle water entering the charging port.

[0048] Next, the charging view records and charging-related query content are uploaded to the server. The server summarizes and analyzes the user's viewing frequency and operating habits, and generates user charging habit data through a self-learning algorithm. Specifically, the information push frequency is determined based on the user's viewing frequency, and the information push content is determined based on the user's query content. The server then distributes the generated charging habit data as part of the historical charging habits to the charging shared parking lock platform's time-segment intelligent synchronization system.

[0049] Furthermore, based on the vehicle's own historical data and user charging habit data in the historical charging habits, combined with the charging patterns of the same model reflected in the charging records of the same model, the charging time and charging power for the current vehicle are jointly determined, and a charging strategy is generated based on the determined charging time and charging power, so that the charging strategy takes into account the individual usage characteristics of the vehicle, the user's charging behavior preferences, and the charging experience of other vehicles of the same model.

[0050] The technical solution provided in this embodiment first acquires at least one of the vehicle's historical charging duration, historical charging power, historical charging start time, and historical charging end time, as well as charging behavior statistics of other vehicles of the same model stored on the server. This provides a dual data foundation for the generation of subsequent charging strategies, combining individual vehicle usage characteristics and group charging patterns. This solves the problem in existing technologies where charging strategies rely solely on factory-fixed parameters, resulting in low matching with actual vehicle needs. Furthermore, by determining the vehicle's charging duration and power based on historical charging habits and charging records of the same model, and generating a charging strategy based on these determined parameters, the charging strategy integrates both the vehicle's own charging behavior patterns and the charging experience of other vehicles of the same model. This solves the problem of charging strategies deviating from actual user habits due to a single data source. Moreover, because the determination process for charging duration and power integrates individual historical data and group statistical data, the generated charging strategy can adapt to the differences in charging behavior among different users. This solves the problem of low charging efficiency or increased battery wear caused by using uniform charging parameters for users with different driving habits. In summary, this embodiment inevitably achieves individualized customization of charging strategies, multi-dimensional fusion of data sources, and dynamic adaptation of charging parameters, ultimately improving the accuracy of matching charging strategies with actual vehicle needs and charging efficiency.

[0051] In step S102, when it is detected that the vehicle currently meets the migration conditions, the target charging location is determined within the parking platform according to the vehicle's demand priority, and the vehicle is controlled to migrate from the current parking location to the target charging location.

[0052] In one implementation, demand priority includes charging priority; determining a target charging location within the parking platform based on the vehicle's demand priority, and controlling the vehicle to move from its current parking location to the target charging location, includes: When the demand priority is charging priority, any available charging location within the parking platform is identified as the target charging location, and the vehicle is controlled to move from its current parking location to the target charging location.

[0053] In this embodiment, migration conditions refer to the conditions that trigger the vehicle to move from its current parking location to another location, including at least one of the following: charging is completed, an available charging location appears in the parking platform, the current parking duration is close to the user's preset fee threshold, or a free charging period is about to begin or end.

[0054] When the smart synchronization system of the charging-sharing parking lock platform detects that a vehicle currently meets any of the above migration conditions, it obtains the user's preset demand priority. Demand priority refers to the user's preference order for different goals during the charging process, which can include charging priority and cost priority. Charging priority means that the user's primary goal is to charge as quickly as possible, regardless of the charging cost; cost priority means that the user's primary goal is to control charging costs, and they tend to choose free or low-cost charging locations.

[0055] Next, obtain information on all available charging locations within the parking platform. The parking platform refers to a place that provides vehicle parking and charging services, including parking lots, charging stations, and parking garages. Available charging locations refer to locations that are not currently occupied by other vehicles and can provide charging services normally.

[0056] When the user's preset priority is charging, a location is randomly selected from all available charging locations within the parking platform, or selected in a preset order, as the target charging location. The target charging location refers to the final destination the vehicle needs to reach during this migration. Since the user's primary goal is to charge as quickly as possible, the vehicle does not need to compare the costs of available charging locations or wait for a specific location to become available; any available charging location will meet the user's needs.

[0057] After determining the target charging location, the system obtains the vehicle's current location coordinates and the target charging location coordinates within the current parking platform, plans the optimal driving path from the current location to the target charging location, and controls the vehicle to automatically drive along the planned path, moving from the current parking location to the target charging location to complete the migration process.

[0058] For example, a user drives an electric vehicle into the underground parking lot of a commercial complex. The vehicle has 15% battery remaining. The user needs to travel long distances the next day and wants to recharge the battery as soon as possible while shopping. Therefore, the user selects charging priority in the vehicle settings.

[0059] After receiving historical charging habits and charging records for the same vehicle model from the server, the system generates a charging strategy. It detects that the migration conditions are met, meaning there are available charging locations within the parking platform. Since the user's preset priority is charging, the system scans the status of all charging stations within the parking platform. It finds three available fast-charging stations on the second basement level and two available slow-charging stations on the first basement level, but these are close to the elevator entrance. Therefore, regardless of charging cost differences or distance, the system directly selects one of the fast-charging stations on the second basement level as the target charging location. The system sends a migration command to the vehicle, controlling it to move from the entrance to the fast-charging station. After the migration is complete, the user can directly enter the shopping mall without having to compare and choose between multiple charging locations.

[0060] The technical solution provided in this embodiment prioritizes charging, ensuring the vehicle understands that the user's primary goal is to charge as quickly as possible, regardless of charging costs. This provides a clear decision-making guide for determining the target charging location, solving the problem in existing technologies where users still need to compare and choose among multiple available charging locations when their charging needs are urgent, leading to charging delays. Furthermore, since any available charging location within the parking platform is designated as the target charging location when the priority is charging, the vehicle does not need to compare costs or wait for a specific location to become available, thus preventing users from missing the optimal charging time due to hesitation or comparison. Moreover, by controlling the vehicle to move directly from its current parking location to any available charging location, the vehicle can enter charging mode as quickly as possible, eliminating the time consumption caused by manual operation and decision-making. In summary, this embodiment inevitably achieves rapid decision-making, instant response in location selection, and efficient execution of vehicle migration in charging-priority scenarios, ultimately improving user charging efficiency and the overall charging experience.

[0061] In one implementation, demand priority includes cost priority; determining a target charging location within the parking platform based on the vehicle's demand priority, and controlling the vehicle to move from its current parking location to the target charging location, includes: When the demand priority is cost priority, at least one candidate charging location that meets the cost condition is obtained, and the candidate charging location with the lowest cost is selected as the target charging location. If the target charging location is currently vacant, then move the vehicle to the target charging location; or, If the target charging location is currently occupied, perform one of the following operations: The candidate charging location with the second lowest cost and currently idle is selected as the new target charging location, and the vehicle is moved to the new target charging location; or, the vehicle is controlled to continue waiting until the target charging location becomes idle, and then the vehicle is moved to the target charging location.

[0062] In this embodiment, when the user's preset priority is cost priority, the cost information for all charging locations within the parking platform is first obtained. This cost information includes the unit electricity price for each charging location, whether there are free periods, whether it participates in promotional activities, and the additional occupancy fee charged by the parking platform. Furthermore, the user's pre-set cost conditions also need to be obtained. These conditions can be a specific value, such as the user requiring the charging cost to not exceed 0.8 yuan per kilowatt-hour, or a relative range, such as the user requesting to select the charging location with the lowest cost within the parking platform.

[0063] Next, all charging locations within the parking platform are filtered based on cost criteria, and those meeting the cost criteria are designated as candidate charging locations. If multiple charging locations within the parking platform meet the cost criteria, these candidate charging locations are sorted in ascending order of cost to generate a candidate charging location queue. The candidate charging location with the lowest cost is taken from the head of the queue as the target charging location, which refers to the final destination the vehicle needs to travel to during this migration.

[0064] The system detects whether a target charging location is currently idle by using vehicle-to-infrastructure communication or server-side data queries. Idle status means the charging location is not occupied by any vehicle, the charging equipment is functioning properly, and it can immediately provide charging service. If the target charging location meets all three conditions, it is considered idle; if any condition is not met—for example, if a vehicle is parked at the location but not charging, the charging equipment is malfunctioning, or the location is reserved—it is considered not idle.

[0065] If the target charging location is currently vacant, then the target charging location is determined as the destination for migration. A driving route from the current parking location to the target charging location is planned, and the vehicle is controlled to automatically drive to the target charging location according to the planned route to complete the migration.

[0066] If the target charging location is not currently idle, meaning it is occupied by another vehicle, the system will further retrieve the user's pre-set waiting strategy. The waiting strategy is a behavior pattern selected by the user in the vehicle settings, which can include two types: a downgrade selection mode and a persistent waiting mode.

[0067] In the downgraded selection mode, the lowest-priced charging location that is already occupied is removed from the candidate charging location queue, and the next lowest-priced candidate charging location in the queue that is currently available is selected as the new target charging location. For example, if the candidate charging location queue consists of location A (0.5 yuan per kWh, occupied), location B (0.6 yuan per kWh, available), and location C (0.7 yuan per kWh, available), in downgraded selection mode, location A will be skipped, and location B will be selected as the new target charging location. The vehicle will then be moved from its current parking position to the new target charging location. If there are no other available candidate charging locations in the queue besides the occupied location, the user will be notified that there are currently no available charging locations, and further instructions from the user will be awaited.

[0068] In the persistent waiting mode, without selecting other candidate charging locations, the system first determines whether the current parking location is legal and safe and does not obstruct the passage of other vehicles. If the current parking location is legal and safe, the vehicle remains in its current position, and the status of the target charging location is re-checked at preset time intervals. If the current parking location poses a risk of being towed or obstructs the passage of other vehicles, the vehicle is moved to a designated waiting area within the parking platform, where the status of the target charging location is continuously monitored. When the target charging location changes from a non-idle state to an idle state, the vehicle is moved from the current parking location or the waiting area to the target charging location.

[0069] While the vehicle is waiting, the system can continuously synchronize the current waiting status information with the user terminal associated with the vehicle, including the estimated availability time of the target charging location, the current queue order, and whether a new charging location with a lower cost has become available. If a charging location with a lower cost than the current target charging location becomes available during the waiting period and that location is vacant, a query can be sent to the user terminal, allowing the user to decide whether to abandon the current wait and go to the lower-cost charging location, or to abandon the current wait and go to the lower-cost charging location directly.

[0070] For example, a user drives an electric vehicle into the underground parking lot of a commercial complex. The vehicle has 15% battery remaining and the user plans to use it only for daily commuting, without needing to travel long distances the next day. The user wants to save on charging costs as much as possible. In the vehicle settings, the user selects cost priority and sets the charging fee to no more than 0.8 yuan per kilowatt-hour.

[0071] The system detected that there are five charging locations in the current parking platform that meet the fee conditions. Location A is 0.6 yuan per kWh but is occupied, Location B is 0.7 yuan per kWh and is available, Location C is 0.75 yuan per kWh and is available, Location D is 0.8 yuan per kWh and is available, and Location E is 0.8 yuan per kWh and is available.

[0072] Therefore, location A, which has the lowest cost, can be selected as the target charging location. However, if location A is detected to be occupied, the operation will be performed according to the user's preset waiting strategy. If the user is not willing to wait, location B, which has the second lowest cost and is available, will be selected as the new target charging location, and the vehicle will be moved to location B to start charging. If the user is willing to wait, the vehicle will be driven into the waiting area, and the status of location A will be continuously monitored. Once location A becomes available, the vehicle will be moved to location A to charge.

[0073] The technical solution provided by this invention prioritizes demand based on cost and acquires at least one candidate charging location that meets the cost criteria. This allows the vehicle to clearly understand that the user's primary goal is to control charging costs, thus providing a decision-making guide for selecting the lowest-cost target charging location. This solves the problem in existing technologies where users, when focused on charging costs, find it difficult to quickly identify the lowest-cost location from multiple charging locations. Furthermore, by selecting the lowest-cost candidate charging location as the target charging location and directly migrating to it when it becomes available, the vehicle can automatically lock and execute the selection of the optimal charging location, thereby eliminating the decision-making burden caused by manual price comparison and selection. Moreover, by providing two optional operations—a downgraded selection method and a waiting method—when the target charging location is occupied, users can flexibly choose according to their tolerance for time costs. That is, a second-lowest-cost and available location satisfies the needs of users who do not want to wait, while waiting for the preferred location to become available satisfies the needs of users who insist on the lowest cost. This solves the problem that a single processing method cannot accommodate the different time cost preferences of users. In summary, the embodiments of the present invention will inevitably achieve automatic selection of the most cost-effective location, dual-path adaptation in occupied scenarios, and flexible response to user time cost preferences, and ultimately improve the rationality of charging location selection and user satisfaction in cost-priority scenarios.

[0074] In one implementation, controlling the vehicle to move from its current parking location to a target charging location includes: If multiple vehicles compete for the target charging location at the same time, obtain the timestamp of each vehicle confirming its journey to the target charging location, as recorded by the server. The order of timestamps determines the vehicles that will be migrated to the target charging location with the highest priority.

[0075] In real-world charging scenarios, it's common for multiple vehicles to simultaneously detect the same target charging location and prepare to proceed. For example, in a parking platform, there might be only one available charging spot that meets the fee priority criteria. The smart synchronization system of the charging-sharing parking lock platform on three vehicles might detect the location as available almost simultaneously and generate migration instructions for each. If all three vehicles drive towards the charging spot at the same time, it could lead to congestion, the risk of collisions, or a standoff at the charging spot's entrance.

[0076] In the scenario where multiple vehicles compete for the same target charging location, the following competition detection is performed before controlling the vehicle to move from its current parking position to the target charging position: Specifically, the system sends a target charging location confirmation request to the server. This request includes the identifier of the target charging location the vehicle is currently heading to, as well as the vehicle's unique identification code. Upon receiving this request, the server queries its database for all target charging location confirmation requests for the same location. A target charging location confirmation request is a locking request sent by the vehicle to the server after deciding to go to a charging location, indicating that the vehicle intends to use that charging location.

[0077] When the server detects that multiple vehicles have sent confirmation requests for the same target charging location, the server records the time when each vehicle sends the confirmation request and uses that time as the timestamp for the vehicle confirming its journey to the target charging location. The timestamp has an accuracy of at least milliseconds to ensure that the order of requests can still be distinguished when multiple vehicles send requests almost simultaneously.

[0078] The system receives all confirmation request records for the current target charging location returned by the server, including the unique identifier of each competing vehicle and its corresponding timestamp.

[0079] Next, the competing vehicles are sorted according to the order of their timestamps. The earlier the time corresponding to the timestamp, the earlier the vehicle confirms its journey to the target charging location, and the higher its migration priority. The vehicle with the earliest time corresponding to the timestamp is determined as the vehicle with the highest priority to migrate to the target charging location.

[0080] If the vehicle itself is determined to be the highest priority vehicle for migration, the migration control steps continue, moving the vehicle from its current parking location to the target charging location. Simultaneously, a migration execution confirmation is sent to the server, which updates the status of the target charging location to locked or occupied, preventing other vehicles from competing for the location.

[0081] If the vehicle is not the highest priority vehicle to migrate, the current target charging location is abandoned. The target charging location determination process can be repeated based on the vehicle's demand priority, and another available charging location can be selected from the candidate charging locations as the new target charging location. Alternatively, the vehicle can choose to enter a waiting queue, and the server will notify the vehicle to proceed to the target charging location in sequence according to its timestamp.

[0082] To avoid frequent competition that could degrade system efficiency, the server also sets an expiration time for timestamps. If the vehicle with the highest priority for migration fails to complete the migration or send a migration execution confirmation within a preset time, the server determines that the vehicle has relinquished its priority and passes the priority to the vehicle with the next earlier timestamp. For example, if the first-priority vehicle does not arrive at the target charging location within three minutes, the server will reassign that location to the second-priority vehicle.

[0083] During the competition, the results are synchronized to the user terminal in real time. If the vehicle wins the competition, the user terminal will display that it is heading to the target charging location. If the vehicle fails the competition, the user terminal will display the current queue order, the estimated waiting time, and other available charging locations, allowing the user to decide whether to continue waiting or choose another location.

[0084] The technical solution provided in this embodiment obtains the timestamp of each vehicle confirming its arrival at the target charging location from the server when multiple vehicles are competing for the same location simultaneously. This provides a unified and immutable quantitative basis for determining the competition order of each vehicle, thus providing an objective data foundation for determining migration priority. This solves the problem of competition or chaos that may occur when multiple vehicles arrive at the same charging location at the same time due to the lack of a fair allocation mechanism in the prior art. On this basis, the vehicle with the highest priority to migrate to the target charging location is determined based on the order of timestamps, so that the vehicle with the earliest confirmation time has priority to migrate, thereby solving the problem of unfairness caused by subjective judgment or random allocation. Furthermore, since the timestamp accuracy reaches the millisecond level and is uniformly recorded by the server, the order can still be accurately distinguished when multiple vehicles make requests almost simultaneously. The vehicle that confirms first migrates first, while the vehicle that confirms later queues or reselects, thereby solving the problem of uncertain waiting time and resource allocation disputes caused by users competing for charging locations. In summary, this embodiment will inevitably achieve fair quantification of charging location competition, objective determination of migration priority, and orderly management in multi-vehicle scenarios, and ultimately improve the fairness of charging resource allocation and the efficiency of multi-vehicle collaboration.

[0085] In step S103, after the vehicle arrives at the target charging location, the charging strategy is executed, and the charging status of the vehicle is synchronized in real time with the user terminal associated with the vehicle.

[0086] After the vehicle arrives at the target charging location, it establishes a communication connection with the charging pile and begins charging according to the charging strategy generated in step S101. The charging strategy includes optimized charging time and charging power, and the vehicle monitors its own charging status in real time during the charging process. The charging status includes the current battery percentage, the charging time already elapsed, the remaining estimated charging time, the current charging power, the battery temperature, and whether there are any charging abnormalities.

[0087] In addition, the charging status needs to be synchronized in real time to the user terminal associated with the vehicle. The user terminal refers to the mobile device carried by the user, including mobile phones, smartwatches, or tablets. When the charging status of the vehicle changes while it is charging, the updated status is pushed to the user terminal, rather than waiting for the user to actively query it.

[0088] Since user charging habit data has already been generated in step S101 based on charging view records and charging-related queries, the charging view records can include the frequency with which the user checks the battery level when charging a mobile phone, the times when checking the charging progress of smart devices, and the types of content the user focuses on when charging an electric bicycle.

[0089] Furthermore, the system can aggregate a user's own charging-related queries with the most frequently requested related queries from other users of the same vehicle model to generate dynamic reminders. The frequency of these dynamic reminders is determined by the user's viewing frequency; for example, if a user checks the charging status three times per hour, the vehicle will send a status update every twenty minutes.

[0090] When pushing charging status to the user's terminal, the system can also further obtain the user's current scene information. Scene information refers to the user's current physical environment and activity status. The physical environment can be identified through location data between the vehicle and the server, including shopping malls, offices, and homes. The activity status can be obtained through analysis of data from social media and shopping apps authorized by the user, such as whether the user is watching a movie, in a meeting, driving, or dining.

[0091] Next, filtering rules for information push are determined based on the physical environment and activity status. These filtering rules determine which types of status information can be pushed and which types should be postponed. For example, in addition to safety alerts, when the user is in a preset high-focus scenario, the vehicle blocks non-safety alerts. Safety alerts include charging abnormalities, battery overheating, and charging interruption risks, while non-safety alerts include routine status updates such as charging progress reaching 50% and charging is about to be completed.

[0092] For example, after a user parks their vehicle at an underground charging station in a shopping mall and begins charging, they enter the mall's cinema to watch a movie. Detecting the user's high level of focus while watching the movie, only safety-related alerts such as charging anomalies and battery overheating are sent to the user's device. Regular status updates such as charging progress reaching 50% or 80% are not sent, thus preventing the user from being distracted by frequent charging status notifications during the movie. Once the movie ends and the user leaves the cinema, all status information, including charging completion, is restored.

[0093] For example, a user parks their vehicle in the company's underground parking garage to charge while attending a meeting in the office. The vehicle system recognizes the user's meeting status and reduces the push notification frequency from the default once every fifteen minutes to once per hour, only sending notifications for charging completion and charging error messages, thus avoiding disturbing the user with frequent notifications.

[0094] In performing the aforementioned scene recognition and information filtering, user-defined scenes are also supported. Users can create custom scenes in the vehicle settings; for example, a user can set the driving scene to not receive any charging status notifications, and the home resting scene to only receive charging completion notifications. User-defined scenes can be set to execute automatically, thus automatically applying preset filtering rules after the corresponding scene is recognized, eliminating the need for manual adjustments by the user each time.

[0095] The implementation path of scene recognition includes the integration of multiple data sources. For example, it can identify the current environmental characteristics through vehicle exterior cameras and radar to determine whether the vehicle is located in a parking lot or charging station, or determine whether the user's current location is a shopping mall, office building or residential area through the location data of the user's mobile terminal. It can also identify the user's current activity type through the check-in data of social software authorized by the user and the consumption data of shopping software, such as when the user is watching a movie after purchasing a ticket at a movie theater.

[0096] Furthermore, when a user first uses the feature, sufficient data on their personal charging viewing habits has not yet been accumulated. In this case, based on the user's profile, the system can reference the habit data of other users who have already used the feature and whose similarity to the user profile is higher than a similarity threshold, selecting the most frequently viewed content among these other users as the initial push frequency. If no user habit data is available on the server side, the system will follow the default push scheme preset by the vehicle manufacturer, such as pushing a charging status update every thirty minutes, with immediate push notifications for charging completion and charging abnormalities.

[0097] The technical solution provided in this embodiment first executes a charging strategy after the vehicle arrives at the target charging location, ensuring the vehicle charges according to the optimized charging time and power. This provides a foundation for real-time synchronization of the charging status, solving the problem of disconnect between the charging process and status notifications in existing technologies. Furthermore, by synchronizing the vehicle's charging status to the user terminal associated with the vehicle in real time, users can be informed of the charging progress without actively checking or inquiring, thus solving the problem of user distraction caused by needing to continuously monitor the charging status. Moreover, by determining the push frequency and content based on the user's viewing habits on different charging devices and the current scenario, users in highly focused scenarios such as watching a movie in a shopping mall or attending an office meeting receive only safety-related reminders, while routine status notifications are filtered out, thus solving the problem of frequent notifications interfering with the user's current activity. In summary, this embodiment inevitably achieves proactive synchronization of charging status, personalized adaptation of push frequency and content, and interference filtering in highly focused scenarios, ultimately improving the continuity and comfort of the user experience during the charging process.

[0098] In real-world applications, users may change their travel plans after charging is complete. For example, a user might initially plan to travel alone but decide to travel with two others while charging; or a user might initially plan to go straight home but decide to shop at a mall first; or a user might initially plan to leave in two hours but decide to leave an hour later after finishing some tasks. These changes will affect the actual battery level required by the vehicle. If these changes are not detected and the charging amount is not adjusted accordingly, the vehicle may be undercharged and unable to complete the changed trip, or overcharged, causing unnecessary delays for the user. To address this technical problem, this embodiment also includes the following steps: Obtain the vehicle's initial charging plan, which includes the initial charge amount and the initial driving route. The initial charge amount indicates the vehicle's current battery level or the battery level to be reached after the charging strategy is completed. When a change is detected in the real-time activity data associated with the vehicle, a target charging plan is generated based on the changed real-time activity data. The target charging plan includes a target charging amount and a target driving route. The target charging amount is used to indicate the amount of electricity the vehicle needs to reach after the real-time activity data changes. Based on the target charging amount and the target driving route, calculate the estimated additional power consumption of the target charging plan relative to the initial charging plan; If the estimated additional power consumption exceeds the additional power consumption threshold, a power replenishment plan adjustment request is generated and sent to the user terminal associated with the vehicle.

[0099] Specifically, the vehicle can obtain the user-preset initial charging plan before, during, or after executing a charging strategy. The initial charging plan refers to the user-defined planning information related to vehicle energy replenishment, including the initial charge amount and the initial driving route. The initial charge amount varies depending on whether the vehicle is currently charging. When the vehicle has not yet started charging or does not need charging, the initial charge amount is the vehicle's actual battery level at the current moment; for example, if the vehicle's current battery level is 40%, the initial charge amount is 40%. When the vehicle is executing or has completed a charging strategy, the initial charge amount indicates the battery level the vehicle needs to reach after completing the charging strategy; for example, if the goal of the charging strategy is to charge to 50%, the initial charge amount is 50%. The initial driving route refers to the navigation path planned by the user from the current location to the destination, including the roads along the way, the estimated driving distance, and the planned charging points. Charging points refer to the locations of pre-set charging stations along the driving route for replenishing battery power.

[0100] During the user's driving process, real-time activity data associated with the vehicle can be continuously monitored through wireless communication between the vehicle and the user's mobile terminal, identification of the number of passengers by the vehicle camera and seat sensors, and detection of the load by the vehicle weight sensor. The real-time activity data includes the user's mobile terminal's schedule change information, navigation change information entered by the user through the vehicle system, changes in the number of passengers, and changes in the vehicle's load.

[0101] When changes are detected in real-time activity data, it is determined whether these changes affect the feasibility of the initial charging plan. For example, if a user originally planned to drive to work alone, with an initial route from home to work and an initial charge of 50% sufficient for the round trip, but then receives a call during the drive requiring them to pick someone up from the airport, the real-time activity data changes, adding a stop along the route from the company to the airport. In this case, it is necessary to determine whether the initial charge of 50% can support the user's changed journey.

[0102] A target charging plan is generated based on the changed real-time activity data. This plan refers to a redesigned energy replenishment scheme for the vehicle after changes in user activity, including a target charging amount and a target driving route. The target driving route is the updated navigation path, such as from the current location via the company to the airport and back home. The target charging amount is the battery level the vehicle needs to reach after the real-time activity data changes; it includes the minimum battery level required to complete the changed trip, plus a safety margin.

[0103] Next, based on the target charging amount and the target driving route, the estimated additional power consumption of the target charging plan relative to the initial charging plan is calculated. The estimated additional power consumption is calculated as follows: first, the initial power consumption required to complete the initial driving route is calculated; then, the target power consumption required to complete the target driving route is calculated; finally, the target power consumption is subtracted from the initial power consumption to obtain the estimated additional power consumption. If the initial charging amount in the initial charging plan is the vehicle's current battery level, meaning the vehicle does not currently need charging and is only temporarily parked, then the initial power consumption is the power consumption required to complete the initial driving route. If the initial charging amount in the initial charging plan is the battery level required to complete the charging strategy, then the initial power consumption is the difference between the initial charging amount and the vehicle's actual remaining battery level at the time the charging strategy is completed.

[0104] The following factors are also considered when calculating power consumption: road gradient along the target route, expected driving speed, ambient temperature, current vehicle load, and air conditioning usage. For example, if the initial route is 20 kilometers long and the estimated power consumption is 5 kWh; if the target route is 60 kilometers long and the estimated power consumption is 15 kWh, then the estimated additional power consumption is 10 kWh.

[0105] The additional power consumption threshold is a preset criterion used to determine whether a charging plan adjustment request needs to be sent to the user. The additional power consumption threshold can be a fixed value, such as five kilowatt-hours; or it can be a percentage of the initial charge, such as 30% of the initial charge. Users can also turn off this threshold, in which case the vehicle will generate an adjustment request for all real-time activity changes.

[0106] If the estimated additional power consumption is greater than the additional power consumption threshold, it is determined that it is necessary to confirm with the user whether to adjust the charging plan. A charging plan adjustment request is then generated. This request includes the specific details of the current initial charging plan, the real-time activity data that has changed, the specific details of the target charging plan, and the estimated additional power consumption. The charging plan adjustment request is then sent to the user terminal associated with the vehicle, and the user feedback is awaited.

[0107] For example, a user drives an electric vehicle from home to work. Before setting off, the user sets an initial charging plan: a target charge level of 50% and an initial route of 15 kilometers from home to work. The vehicle has already charged its battery to 50% the previous night according to the charging strategy.

[0108] When the user was halfway through their journey, the system detected a new meeting appointment in the user's mobile calendar. The meeting location was in another city 30 kilometers away from the company. The user also entered a new navigation destination through the in-vehicle system, thus the system recognized the change in real-time activity data.

[0109] Next, the system generates a target energy replenishment plan based on the changed activity data: the target driving route is from the current location, through the company, to the conference city, and back home, a total distance of 120 kilometers; the target charging amount is 65% of the minimum charge required to complete the 120-kilometer journey plus a safety margin of 5%, totaling 70%. The vehicle calculates the initial driving route energy consumption as 4 kWh, the target driving route energy consumption as 16 kWh, and the estimated additional energy consumption as 12 kWh.

[0110] The user's preset threshold for additional power consumption is five kWh. Twelve kWh exceeds five kWh, therefore a power plan adjustment request is generated and sent to the user's terminal associated with the vehicle. The adjustment request displays: "Your itinerary has changed, with a new meeting city destination added. The original plan consumed four kWh, the new plan consumes sixteen kWh, requiring an additional twelve kWh of charging. Do you wish to recharge to 70% upon arrival at the company?"

[0111] The technical solution provided in this embodiment, by acquiring the vehicle's initial charging plan, which includes the initial charging amount and the initial driving route, provides a benchmark for subsequent trip change detection and power demand comparison, solving the problem in existing technologies where charging systems cannot know the user's travel intentions. Furthermore, by generating a target charging plan based on the changed real-time activity data associated with the vehicle when changes are detected, the target charging plan includes the target charging amount and the target driving route. This allows the vehicle to perceive user trip changes and re-plan its power demand, thus solving the problem of insufficient power or overcharging caused by the vehicle continuing to execute the original plan after a user's trip has changed. Moreover, by calculating the estimated additional power consumption based on the target charging amount and the target driving route, and generating an adjustment request and sending it to the user terminal when the estimated additional power consumption exceeds a threshold, the user can know whether additional charging is needed without having to judge the impact of trip changes on power, thus solving the problem of users being unable to travel due to ignoring the impact of power. In summary, this embodiment inevitably achieves real-time perception of trip changes, dynamic calculation of power demand, and proactive push of adjustment requests, ultimately improving the adaptability of charging management to changes in user travel plans and driving safety.

[0112] In a real-time approach, the method further includes: Receive adjustment feedback from user terminals regarding requests to adjust the energy replenishment plan. The adjustment feedback includes whether the user agrees to the adjustment or refuses to adjust. If the feedback indicates agreement to the adjustment, the vehicle will be recharged based on the estimated additional power consumption, or the planned charging points along the target route will be obtained, and the target route will be adjusted based on the estimated additional power consumption and the charging points. If the feedback is "reject adjustment", then increase the number of charging points along the target driving route.

[0113] In this embodiment, after sending a power replenishment plan adjustment request to the user terminal, the system waits for the user terminal to return adjustment feedback. Adjustment feedback refers to the user's confirmation response to the adjustment request, which can include either agreeing to the adjustment or rejecting the adjustment.

[0114] After receiving a power replenishment plan adjustment request, the user terminal displays the request content on its screen. The request content includes details of the current initial power replenishment plan, real-time activity data showing changes, the specific details of the target power replenishment plan, and the estimated additional power consumption. The user terminal also displays two selectable buttons: "Agree to Adjustment" and "Reject Adjustment." The user selects one based on their situation, and the user terminal returns the user's selection as adjustment feedback to the system. Upon receiving the adjustment feedback from the user terminal, the system performs different processing operations based on the feedback type.

[0115] If the feedback indicates agreement to the adjustment, and the vehicle is still within the parking platform and has not yet left, the system will choose to recharge the vehicle based on the estimated additional power consumption. Specifically, the system will obtain the vehicle's current remaining battery level, which refers to the remaining battery level after the aforementioned charging strategy has been executed. The difference between the target charging amount and the remaining battery level will be calculated and determined as the supplementary charging amount. The system will then search for an available charging location within the parking platform and charge the vehicle according to the supplementary charging amount until the battery level reaches the target charging amount.

[0116] For example, a user originally planned to charge to 50% before heading home from work, and the battery reached 50% after completing the charging strategy. While driving, the user decided to go to the airport to pick someone up, changing the target charge to 70%. However, the vehicle currently had 40% battery remaining, so an additional 25% charge was needed. After the user agreed to the adjustment, the system automatically found a charging location for the vehicle upon arrival at the company parking lot and provided the additional 25% charge, bringing the battery to 70%.

[0117] In another implementation, if the feedback indicates agreement to the adjustment, but the vehicle has already left the parking platform and cannot return to charging in the short term, then the planned charging points along the target driving route are selected, and the target driving route is adjusted based on the estimated additional power consumption and the charging points.

[0118] Planned charging points refer to the locations of pre-set charging stations along the user's initial driving route for replenishing battery power. Specifically, the system assesses the maximum charging capacity that each planned charging point can provide, and determines whether the existing charging points are sufficient based on the estimated additional power consumption. If the total charging capacity provided by the existing charging points is greater than or equal to the estimated additional power consumption, the original charging points remain unchanged, and only the navigation target is updated. If the total charging capacity provided by the existing charging points is less than the estimated additional power consumption, a new charging point is added to the target driving route, or the user is advised to increase the charging time at a certain charging point. The adjusted target driving route is then pushed to the user's terminal for confirmation before navigation is executed.

[0119] For example, a charging station with 10 kWh of electricity is already planned along the user's original route. If the user's trip is changed and the estimated additional electricity consumption is 12 kWh, the existing charging station's 10 kWh is insufficient to cover the extra consumption. Therefore, a new charging station can be added along the target route, located midway through the original route, providing 5 kWh of electricity. The two charging stations together provide 15 kWh, meeting the additional 12 kWh demand. The revised route with the added charging station is then pushed to the user's device.

[0120] If the feedback for adjustment is "rejection," it means the user does not agree to return to the charging station for recharging or to adjust the charging plan. In this case, the user's decision is respected, and the current battery level and the set charging goal remain unchanged. However, to ensure the user does not break down due to insufficient battery power, the number of charging stations along the target route can be increased. Specifically, the total mileage of the target route and the current remaining battery power are obtained. The maximum safe driving distance at the current battery level is calculated and compared with the total mileage of the target route. If the maximum mileage is less than the total mileage, the number of charging stations along the target route is increased by adding one charging station at regular intervals. The number of charging stations added is positively correlated with the estimated additional power consumption; the greater the estimated additional power consumption, the more charging stations are added. The target route with the increased charging stations is then pushed to the user's terminal.

[0121] For example, if the user refuses to agree to the adjustment, the vehicle will not return to charging, but the vehicle's current remaining battery is 45%, and the total distance of the target route corresponds to 70% of the battery consumption. The current battery level is insufficient for the entire journey. The vehicle adds three charging points along the target route, such as those located at 30%, 60%, and 90% of the mileage. As the user travels along the new route, the vehicle will remind the user at each charging point whether or not to charge, allowing the user to decide whether to proceed. If the user does not charge during the entire journey, the vehicle will issue another warning when the battery level drops below a safe threshold, advising the user to immediately find a charging station.

[0122] The technical solution provided in this embodiment first receives adjustment feedback from the user terminal regarding the request to adjust the charging plan. This feedback includes either agreeing to the adjustment or rejecting the adjustment. This allows the vehicle to decide on subsequent operations based on the user's true intentions, thus solving the problem that the vehicle cannot know the user's decision-making intent after sensing a change in the route. Furthermore, when the adjustment feedback is "agree to adjust," the vehicle is either recharged based on the estimated additional power consumption, or the planned charging points along the target route are obtained and the target route is adjusted based on the estimated additional power consumption and the charging points. This allows the vehicle to choose between two different execution paths—returning to charging or optimizing the route—provided the user agrees to the adjustment. This solves the problem that a single processing method cannot adapt to different driving stages and charging conditions. Finally, when the adjustment feedback is "rejected," the number of charging points along the target route is increased. This ensures trip safety even if the user refuses to recharge, thus solving the problem of trip interruption due to insufficient battery power after the user refuses to adjust. In summary, this embodiment will inevitably achieve immediate response to user decisions, dual-path adaptation for charging or route adjustments, and a safety net for the trip, and ultimately improve the coordination level between user autonomy and vehicle intelligent execution during the adjustment of the charging plan.

[0123] In real-world scenarios, after connecting their vehicles to charging stations, users typically leave to go shopping, work in the office, or rest at home. Once charging is complete, as described in the aforementioned embodiment, the vehicle automatically moves from the charging location to a legal and safe location within the parking platform, freeing up the charging space for other vehicles. However, users still face several parking challenges when returning to retrieve their vehicles. For example, the distance from their current location to the parking spot may be considerable, especially when carrying heavy items, in inclement weather, or when time is tight. Alternatively, upon arriving at the parking spot, users may find the exit blocked by other vehicles, preventing them from exiting. They then need to find the owner of the blocking vehicle or contact parking lot management, wasting considerable time and effort. Furthermore, the complex internal structure of parking lots and unclear exit signs can easily cause users to get lost in multi-level or large parking lots, making it difficult to quickly find the exit. Regarding parking fees, users may exceed the free period by one or two minutes due to excessive walking time to the exit, requiring them to pay for the next full period, or they may miss the end of the previous time period due to underestimating the queue time at the parking lot exit. If the parking management system cannot coordinate with the charging management solution to provide intelligent parking reminders after charging is complete, users can only rely on their personal experience to deal with the above situations, resulting in a poor parking experience, wasted time, and unnecessary expenses. To solve this technical problem, the system in this embodiment further provides a self-learning intelligent parking status reminder function on the basis of the vehicle completing charging and automatically migrating to a legal and safe location.

[0124] Specifically, the system obtains the current parking platform's structural layout, historical parking traffic data, and floor plan from the server. The server-side data originates from official management information uploaded to the cloud by the parking platform operator when the parking lot was established. The structural layout refers to the parking platform's internal layout information, including parking space distribution, passageway orientation, entrance and exit locations, and the locations of elevators and stairwells. The floor plan refers to a two-dimensional or three-dimensional map of the parking platform, used to display parking space numbers, area divisions, and the relative relationship between the user's current location and the target location.

[0125] Next, the system can learn from the structure and floor plan of the parking platform. Specifically, it can analyze the parking space occupancy rate, average passage speed at each exit, queue length at each entrance, and time statistics required for users to move from different parking spaces to the exit in historical parking traffic data to generate optimized information prompt strategies for the current parking platform.

[0126] For scenarios involving reminders when switching between free and billing periods, the system first obtains the coordinates of the user's current parking location and calculates the estimated travel time from the current location to the parking lot exit. This estimated travel time includes the walking time to the exit and any potential elevator waiting time. It also needs to obtain the current traffic speed at the parking lot exit, such as whether there is a queue and the speed at which the barrier gate opens. The vehicle subtracts the current time and the estimated travel time from the end time of the free period to obtain the dynamic remaining time. When the dynamic remaining time is less than a preset threshold, a reminder is pushed to the user's terminal, informing them of the time they need to leave the parking lot to enjoy the free period or avoid entering the next billing period. For example, if the user's parking location is far from the exit, requiring an eight-minute walk, and the free period ends in ten minutes, the reminder is pushed nine minutes before the end of the free period, rather than a fixed ten minutes in advance.

[0127] For scenarios where the parking location is far away, the system needs to obtain the distance between the user's selected parking location and their actual destination. For example, the user's actual destination could be a shopping mall entrance, an office building elevator, or a movie theater ticket gate. This distance is compared to a preset long-distance threshold. If the distance between the parking location and the destination exceeds the long-distance threshold, the system determines that the current parking location is too far, and therefore activates the vehicle's autonomous driving function. The vehicle then automatically travels from the parking location to the user's real-time location for pickup. The autonomous driving function relies on a large-scale VLA (Visual Language) model or end-to-end model configured on the vehicle. These models are capable of locating the user in open-air spaces and even internal longitudinal parking lots. If the vehicle is not equipped with autonomous driving, the system optimizes the route based on the distance between the user's terminal and the vehicle, and activates the automatic parking function when the user is five meters away from the vehicle, automatically driving the vehicle out of the parking space for the user to get in directly.

[0128] To address scenarios where exits are blocked by other vehicles after parking, the system uses external cameras to identify the license plate information of surrounding vehicles. When a vehicle is detected parked in front or to the side, preventing the vehicle from exiting, a request is automatically uploaded to the server. The server then uses the license plate information to retrieve the contact information of the vehicle owner blocking the exit and sends a request to move the vehicle. Simultaneously, the system can synchronize the obstruction status and processing progress to the user's device in real time, informing the user that a request to move the vehicle has been sent and the estimated response time for the blocking vehicle. Users do not need to get out of their cars to check or make phone calls to move the vehicle.

[0129] Furthermore, this embodiment also allows users to flexibly pick up their vehicles based on their desired return location, without having to go to a fixed parking spot. Specifically, users can select their desired pick-up location on their user terminal, such as an exit of a shopping mall or a lobby of an office building. The system plans the vehicle's route from the parking spot to the pick-up location and controls the vehicle to automatically drive to that location to pick up the user.

[0130] For example, a user drives into the underground parking garage of a large shopping mall. The garage has four levels, each with 200 parking spaces. The user parks on the third basement level near section B and then takes the elevator to the mall entrance on the first floor. The user takes three minutes to walk from the parking spot to the elevator, one minute to reach the first floor, and two minutes to walk from the elevator to the mall entrance, totaling six minutes and a walking distance of 350 meters. The user's preset distance threshold is 300 meters; 350 meters is greater than 300 meters, therefore the user determines the current parking spot is too far.

[0131] After shopping for two hours, a user prepares to leave the mall and selects the North Gate on the first floor as their pick-up point on their mobile device, instead of returning to Area B on the third basement level. Upon receiving the user's instruction, the system automatically starts from Area B on the third basement level, travels along the internal parking lot passage to the North Gate exit on the first floor, and waits for the user. The user's walk from inside the mall to the North Gate takes only two minutes, eliminating the need to spend an extra six minutes returning to their original parking location.

[0132] If, during a user's shopping period, the system detects that the free parking period is nearing its end (e.g., one hour and fifty-five minutes of parking within a two-hour free period), and the estimated walking time from the current location to the exit is five minutes, assuming the exit's current traffic speed is three vehicles per minute with no congestion, and the calculation indicates the user needs to start moving two minutes before the free period ends (one hour and fifty-eight minutes) to ensure a free exit, the system will send a reminder to the user's device: "Your free parking period will end in five minutes. We recommend you proceed to the parking lot exit now." Upon receiving this reminder, the user can end their shopping early and leave promptly, avoiding extra charges beyond the free period.

[0133] The technical solution provided in this embodiment first acquires the current parking platform's structural configuration, historical parking flow data, and floor plan, and then uses this data to generate optimized information prompt strategies through self-learning. This provides a calculation basis that matches the specific characteristics of the parking lot for subsequent parking reminders, solving the problem of existing technologies using fixed times or templates that lead to a disconnect from the actual scenario. Furthermore, by dynamically calculating the remaining free time reminder based on the parking lot exit traffic speed and the user's estimated travel time to the exit, users can receive accurate exit suggestions before the free period ends, thus solving the problem of users paying extra due to walking distance or queues exceeding the free period by one or two minutes. Moreover, by activating an autonomous vehicle to pick up the user when the distance between the parking location and the destination exceeds a threshold, and by automatically identifying and sending a vehicle relocation request when a vehicle is detected as being blocked, users do not need to walk long distances or search for the owner of the blocked vehicle, thus solving the problem of wasted time and energy during vehicle retrieval. In summary, this embodiment inevitably achieves personalized parking reminders, dynamic and accurate calculation of free periods, and automated assistance in the vehicle retrieval process, ultimately improving the user's parking experience and vehicle retrieval efficiency.

[0134] This embodiment also provides a vehicle charging management device for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0135] This embodiment provides a vehicle charging management device, such as... Figure 3 As shown, it includes: The strategy generation module 301 is used to obtain the vehicle's historical charging habits and charging records of the same model from the server, and generate the vehicle's charging strategy based on the historical charging habits and charging records of the same model.

[0136] The location migration module 302 is used to determine the target charging location within the parking platform according to the vehicle's demand priority when the vehicle is detected to meet the migration conditions, and control the vehicle to migrate from the current parking location to the target charging location.

[0137] The strategy execution module 303 is used to execute the charging strategy after the vehicle arrives at the target charging location and to synchronize the vehicle's charging status with the user terminal associated with the vehicle in real time.

[0138] In one implementation, historical charging habits include at least one of the vehicle's historical charging duration, historical charging power, historical charging start time, and historical charging end time; the same-model charging record includes statistical data on the charging behavior of other vehicles of the same model stored on the server; the strategy generation module 301 includes: The strategy generation unit is used to determine the charging time and charging power of the vehicle based on historical charging habits and charging records of the same model, and to generate a charging strategy based on the charging time and charging power.

[0139] In one implementation, demand priority includes charging priority; the location migration module 302 includes: The first location migration unit is used to determine any available charging location within the parking platform as the target charging location when the demand priority is charging priority, and to control the vehicle to migrate from the current parking location to the target charging location.

[0140] In one implementation, demand priority includes cost priority; the location migration module 302 further includes: The location selection unit is used to obtain at least one candidate charging location that meets the cost condition when the demand priority is cost priority, and select the candidate charging location with the lowest cost as the target charging location.

[0141] The second location migration unit is used to migrate the vehicle to the target charging location if the target charging location is currently idle; or, The third location migration unit is used to perform one of the following operations if the target charging location is currently occupied: determine the candidate charging location with the second lowest cost and currently in an idle state as the new target charging location, and control the vehicle to migrate to the new target charging location; or control the vehicle to continue waiting until the target charging location is in an idle state, and then migrate the vehicle to the target charging location.

[0142] In one embodiment, the location migration module 302 further includes: The location migration subunit is used to obtain the timestamp of each vehicle confirming its journey to the target charging location, which is recorded by the server, if multiple vehicles are competing for the target charging location at the same time; and to determine the vehicle that migrates to the target charging location with the highest priority based on the order of the timestamps.

[0143] In one embodiment, the apparatus further includes: The initial plan acquisition unit is used to acquire the vehicle's initial charging plan, which includes the initial charging amount and the initial driving route. The initial charging amount indicates the vehicle's current battery level or the battery level to be reached after the charging strategy is completed.

[0144] The target plan generation unit is used to generate a target charging plan based on the changed real-time activity data when changes are detected in the real-time activity data associated with the vehicle. The target charging plan includes a target charging amount and a target driving route. The target charging amount is used to indicate the amount of electricity the vehicle needs to reach after the real-time activity data changes.

[0145] The additional power consumption calculation unit is used to calculate the estimated additional power consumption of the target charging plan relative to the initial charging plan, based on the target charging amount and the target driving route.

[0146] The request generation unit is used to generate a charging plan adjustment request and send the charging plan adjustment request to the user terminal associated with the vehicle if the estimated additional power consumption is greater than the additional power consumption threshold.

[0147] In one embodiment, the apparatus further includes: The feedback receiving unit is used to receive adjustment feedback returned by the user terminal in response to the energy replenishment plan adjustment request. The adjustment feedback includes agreeing to the adjustment or rejecting the adjustment.

[0148] The first adjustment unit is used to either recharge the vehicle based on the estimated additional power consumption if the adjustment feedback indicates agreement, or to obtain the planned charging points along the target driving route and adjust the target driving route based on the estimated additional power consumption and the charging points.

[0149] The second adjustment unit is used to increase the number of charging points along the target driving route if the feedback is a rejection of adjustment.

[0150] In this embodiment, the vehicle charging management device is presented in the form of functional units. Here, a unit refers to an ASIC circuit, a processor and memory executing one or more software or fixed programs, and / or other devices that can provide the aforementioned functions. Further functional descriptions of the various modules and units are the same as in the corresponding embodiments described above, and will not be repeated here.

[0151] This invention also provides a computer device having the above-described features. Figure 3 The vehicle's charging management device is shown below. See below for details. Figure 4The diagram illustrates a structural schematic suitable for implementing a computer device according to embodiments of the present invention. The computer device may include a processor (e.g., a central processing unit, a graphics processing unit, etc.) 401, which can perform various appropriate actions and processes based on a program stored in a read-only memory (i.e., ROM 402) or a program loaded from memory 408 into random access memory (i.e., RAM 403). The RAM 403 also stores various programs and data required for the operation of the computer device. The processor 401, ROM 402, and RAM 403 are interconnected via a bus 404. Input / output (i.e., I / O interface 405) is also connected to the bus 404.

[0152] Typically, the following devices can be connected to I / O interface 405: input devices 406 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 407 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 408 including, for example, magnetic tapes, hard disks, etc.; and communication devices 409. Communication device 409 allows the computer device to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 4 Computer equipment with various devices is shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0153] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 409, or installed from a memory 408, or installed from a ROM 402. When the computer program is executed by the processor 401, it performs the functions defined in the vehicle charging management method of the embodiments of the present invention.

[0154] Figure 4 The computer device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of the present invention.

[0155] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the vehicle charging management method shown in the above embodiments is implemented.

[0156] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0157] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for managing vehicle charging, characterized in that, The method includes: The system obtains the vehicle's historical charging habits and charging records of the same model from the server, and generates the vehicle's charging strategy based on the historical charging habits and charging records of the same model. When the vehicle is detected to meet the migration conditions, a target charging location is determined within the parking platform according to the vehicle's demand priority, and the vehicle is controlled to migrate from its current parking location to the target charging location. After the vehicle arrives at the target charging location, the charging strategy is executed, and the charging status of the vehicle is synchronized in real time to the user terminal associated with the vehicle.

2. The method according to claim 1, characterized in that, The historical charging habits include at least one of the vehicle's historical charging duration, historical charging power, historical charging start time, and historical charging end time; the same model charging records include statistical data on the charging behavior of other vehicles of the same model as the vehicle stored on the server. The step of generating the vehicle's charging strategy based on the historical charging habits and the charging records of the same vehicle model includes: The charging duration and charging power of the vehicle are determined based on the historical charging habits and the charging records of the same vehicle model, and the charging strategy is generated based on the charging duration and the charging power.

3. The method according to claim 1, characterized in that, The demand priority includes charging priority; determining the target charging location within the parking platform based on the vehicle's demand priority, and controlling the vehicle to move from its current parking location to the target charging location, includes: When the demand priority is charging priority, any available charging location within the parking platform is determined as the target charging location, and the vehicle is controlled to move from its current parking location to the target charging location.

4. The method according to claim 1 or 3, characterized in that, The demand priority includes cost priority; determining the target charging location within the parking platform based on the vehicle's demand priority and controlling the vehicle to move from its current parking location to the target charging location includes: When the demand priority is cost priority, at least one candidate charging location that meets the cost condition is obtained, and the candidate charging location with the lowest cost is selected as the target charging location. If the target charging location is currently idle, then the vehicle will be moved to the target charging location; or, If the target charging location is currently occupied, perform one of the following operations: The candidate charging location with the second lowest cost and currently idle is identified as the new target charging location, and the vehicle is controlled to move to the new target charging location; or, the vehicle is controlled to continue waiting until the target charging location becomes idle, and then the vehicle is moved to the target charging location.

5. The method according to claim 1, characterized in that, The control of the vehicle to move from its current parking location to the target charging location includes: If multiple vehicles compete for the target charging location at the same time, the timestamp of each vehicle confirming its journey to the target charging location, as recorded by the server, is obtained. The vehicle with the highest priority to migrate to the target charging location is determined based on the order of the timestamps.

6. The method according to claim 1, characterized in that, The method further includes: Obtain the initial charging plan for the vehicle, which includes an initial charge amount and an initial driving route. The initial charge amount indicates the vehicle's current battery level or the battery level to be reached after the charging strategy is completed. When a change is detected in the real-time activity data associated with the vehicle, a target charging plan is generated based on the changed real-time activity data. The target charging plan includes a target charging amount and a target driving route, wherein the target charging amount is used to indicate the amount of electricity the vehicle needs to reach after the change in the real-time activity data. Based on the target charging amount and the target driving route, calculate the estimated additional power consumption of the target charging plan relative to the initial charging plan; If the estimated additional power consumption is greater than the additional power consumption threshold, a power replenishment plan adjustment request is generated and sent to the user terminal associated with the vehicle.

7. The method according to claim 6, characterized in that, The method further includes: Receive adjustment feedback from the user terminal in response to the energy replenishment plan adjustment request, the adjustment feedback including agreeing to the adjustment or rejecting the adjustment; If the adjustment feedback is "agree to adjustment", then the vehicle is recharged based on the estimated additional power consumption, or the planned charging points in the target driving route are obtained, and the target driving route is adjusted according to the estimated additional power consumption and the charging points. If the feedback is a refusal to adjust, then the number of charging points will be increased along the target driving route.

8. A vehicle charging management device, characterized in that, The device includes: The strategy generation module is used to obtain the vehicle's historical charging habits and charging records of the same model from the server, and generate the vehicle's charging strategy based on the historical charging habits and the charging records of the same model. The location migration module is used to determine the target charging location within the parking platform according to the vehicle's demand priority when it is detected that the vehicle currently meets the migration conditions, and control the vehicle to migrate from the current parking location to the target charging location; The strategy execution module is used to execute the charging strategy after the vehicle arrives at the target charging location, and to synchronize the charging status of the vehicle with the user terminal associated with the vehicle in real time.

9. A computer device, characterized in that, include: A memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, the processor executing the computer instructions to perform the method of any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the method of any one of claims 1 to 7.

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