Charging queuing method and device of charging station and charging station

Abstract

The invention discloses a charging queuing method and device for a charging station and the charging station, and aims to realize objective sorting according to the time of vehicles entering a geo-fence, realize intelligent queuing and improve the operation efficiency of the charging station. The charging queuing method of the charging station comprises the following steps: determining a virtual boundary of a geofence according to position information of the charging station; wherein the virtual boundary of the geofence comprises the physical boundary of the charging station; acquiring position information of a target vehicle in a preset range; the preset range is larger than the virtual boundary of the geo-fence; based on the position relationship between the position information of the target vehicle and the virtual boundary, determining the entering time of the target vehicle entering the geo-fence for the first time on the day; generating a charging queue based on the sequence of the entering time; and based on the charging queue, charging prompt information is sent to the target vehicles in the charging queue in sequence.

Description

Technical Field

[0001] This application relates to the field of charging scheduling technology, specifically to a charging queuing method, apparatus, and charging station for a charging station. Background Technology

[0002] With the large-scale application of new energy vehicles, especially electric heavy-duty trucks, in logistics, mining, and ports, the demand for charging is increasing daily. Currently, most electric heavy-duty truck charging stations still rely on experience-based manual dispatching to manage vehicle charging queues. Dispatchers must manually arrange the charging sequence and allocate charging piles based on information such as vehicle arrivals, charging demand, and the status of charging equipment. However, with the rapid increase in the number of vehicles and the increasing complexity of charging tasks, the shortcomings of traditional manual dispatching methods in terms of efficiency, fairness, and response speed are becoming increasingly apparent. This easily leads to problems such as charging station congestion, uneven resource utilization, and excessively long waiting times for drivers, hindering the improvement of the overall operational efficiency and service capabilities of charging stations. Summary of the Invention

[0003] To address the aforementioned technical problems, this application is proposed. Embodiments of this application provide a charging queuing method, apparatus, and charging station, which can objectively sort vehicles according to the time they enter the geofence, achieving intelligent queuing and improving the operational efficiency of the charging station.

[0004] According to a first aspect of this application, a charging queuing method for a charging station is provided, comprising: determining a virtual boundary of a geofence based on the location information of the charging station; wherein the virtual boundary of the geofence includes the physical boundary of the charging station; acquiring location information of target vehicles within a preset range; the preset range being larger than the virtual boundary of the geofence; determining the entry time of the target vehicle's first entry into the geofence on a given day based on the positional relationship between the target vehicle's location information and the virtual boundary; generating a charging queue based on the order of the entry times; and sequentially sending charging reminder information to the target vehicles in the charging queue based on the charging queue.

[0005] As one possible implementation, after generating the charging queue based on the order of entry time, the method further includes: determining whether the target vehicle meets the removal conditions, wherein the removal conditions are: the dwell time of the target vehicle since entering the geofence is less than a first preset time, and the charging status of the target vehicle is not charging; when the removal conditions are met, the target vehicle is removed from the charging queue.

[0006] As one possible implementation, after generating the charging queue based on the order of entry times, the method further includes: determining whether the target vehicle meets the skip condition, wherein the skip condition is: the target vehicle is not charging within a second preset time period starting from the date of receiving the charging prompt information; when the skip condition is met, the target vehicle is marked as skipped and a charging prompt information is sent to the next target vehicle.

[0007] As one possible implementation, the charging queuing method for the charging station further includes: when the target vehicle is not entering the geofence for the first time on the same day, and the target vehicle is marked as having missed its turn, generating priority charging information for the target vehicle.

[0008] As one possible implementation, the charging queuing method for the charging station further includes: receiving priority charging information; based on the priority of the priority charging information, placing the target vehicle corresponding to the priority charging information at the top of the charging queuing queue to obtain a first charging queuing queue; wherein the priority of the priority charging information is positively correlated with the top position of the target vehicle in the first charging queuing queue.

[0009] As one possible implementation, based on the charging queue, charging reminder information is sent sequentially to target vehicles in the charging queue, including: obtaining the charging status of the target vehicles in the charging queue based on the charging queue; when the charging status of the target vehicle is charging and the real-time battery level of the target vehicle is greater than a preset battery level, sending charging reminder information to the next target vehicle in the charging queue.

[0010] As one possible implementation, the charging queuing method at the charging station further includes: obtaining the route between the target vehicle and the virtual boundary based on the location information of the target vehicle and the positional relationship between the virtual boundary and the virtual boundary; calculating the charging waiting time of the target vehicle based on the route distance; sorting the target vehicles based on the charging waiting time to generate an initial charging queue; wherein, generating the charging queue based on the order of entry time includes: adjusting the initial charging queue based on the order of entry time to generate the charging queue.

[0011] As one possible implementation, the location information of the target vehicle includes the real-time coordinates of the target vehicle; wherein, determining the entry time of the target vehicle's first entry into the geofence based on the positional relationship between the target vehicle's location information and the virtual boundary includes: comparing the real-time coordinates of the target vehicle with the boundary coordinates of the virtual boundary; when the real-time coordinates of the target vehicle coincide with the boundary coordinates, and the trajectory of the target vehicle within a preset time indicates that the target vehicle enters the geofence from outside the virtual boundary of the geofence, the moment when the coordinates coincide is determined as the entry time of the target vehicle's first entry into the geofence.

[0012] According to a second aspect of this application, a charging queuing device for a charging station is provided, comprising: a setting module, configured to determine a virtual boundary of a geofence based on the location information of the charging station; wherein the virtual boundary of the geofence includes the physical boundary of the charging station; an acquisition module, configured to acquire location information of target vehicles within a preset range; the preset range being larger than the virtual boundary of the geofence; a determination module, configured to determine the entry time of the target vehicle's first entry into the geofence on a given day based on the positional relationship between the target vehicle's location information and the virtual boundary; a generation module, configured to generate a charging queue based on the order of the entry times; and a notification module, configured to sequentially send charging notification information to the target vehicles in the charging queue based on the charging queue.

[0013] According to a third aspect of this application, a charging station is provided, comprising: a geofence, the virtual boundary of which includes the physical boundary of the charging station; and a charging queuing device for the charging station as described in the second aspect or any implementation thereof, the charging queuing device for the charging station being used to perform a charging queuing method for the charging station.

[0014] The charging queuing method, apparatus, and charging station provided in this application, by defining a geofence around the charging station and automatically identifying the entry time of the target vehicle's first entry into the geofence on the same day based on the target vehicle's location information, uses the entry time as the basis for queuing. This eliminates subjective judgment errors and ensures the uniqueness, traceability, and immutability of the queuing basis, laying a precise data foundation for subsequent queue management. By generating a charging queue based on the order of all vehicle entry times, a unified queuing standard is applied to all vehicles. Furthermore, through charging prompts, vehicles can clearly know their queue position and charging time, reducing disputes and anxiety caused by unfair queuing or unclear progress, and improving the service capacity of the charging station. Attached Figure Description

[0015] The above and other objects, features, and advantages of this application will become more apparent from the more detailed description of the embodiments of this application in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the embodiments of this application to explain this application and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0016] Figure 1 This is a schematic flowchart of a charging queuing method for a charging station provided in an exemplary embodiment of this application.

[0017] Figure 2 This is a schematic diagram of the structure of a charging queuing device for a charging station provided in an exemplary embodiment of this application.

[0018] Figure 3 This is a structural diagram of an electronic device provided in an exemplary embodiment of this application. Detailed Implementation

[0019] Hereinafter, exemplary embodiments according to this application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein.

[0020] Driven by the global goal of energy transition, electric heavy-duty trucks, with their outstanding advantages such as zero emissions, low noise, and low operating costs, are being widely used in logistics, mining, and ports, leading to an explosive growth in charging demand. However, current charging stations face numerous challenges in managing electric heavy-duty truck charging. Traditional manual dispatching methods are no longer adequate for the new situation, resulting in low operational efficiency, significant resource waste, and high management costs at charging stations, thus hindering the further promotion and sustainable development of electric heavy-duty trucks.

[0021] With the widespread adoption of electric heavy-duty trucks in various application scenarios, the number of vehicles at charging stations has surged. Existing electric heavy-duty truck charging station management faces the following major technical bottlenecks: First, the contradiction between concentrated vehicle arrivals and long charging times is prominent. Manual registration is slow and prone to errors. During peak arrival times, the workload of management personnel increases dramatically, easily leading to scheduling chaos due to information recording errors, omissions, or poor communication. This model is not only time-consuming and labor-intensive but also struggles to cope with dynamically changing on-site situations, resulting in low overall operational efficiency. Second, existing check-in methods (such as card swiping) cannot accurately capture the physical arrival time of vehicles, leading to a lack of objective basis for the first-come, first-served principle and frequent disputes. For example, the check-in or operation time recorded by existing technologies (manual registration, card swiping / scanning) is not the physical arrival time. Vehicles may arrive early, but drivers may get off late to check in, or move their vehicles within the station and wait. This leaves significant room for dispute regarding who arrived first, and management personnel lack irrefutable objective data as arbitration evidence. Finally, there are significant breakpoints in the critical process from queuing to charging. For example, when a vehicle finishes charging and vacates a charging station, there is a lack of an automatic and timely notification mechanism to inform the next vehicle in line, resulting in valuable charging facilities being left idle and waiting, causing waste of resources and delays for subsequent vehicles.

[0022] Therefore, to solve the above problems and overcome technical bottlenecks, this application proposes a charging queuing method, device, and charging station. By objectively recording the arrival time of vehicles entering the geofence, human error can be eliminated. Charging information allows drivers to monitor their queue position and estimated waiting time in real time, reducing anxiety; vehicles within the station move in an orderly manner according to the charging queue, avoiding congestion and safety hazards.

[0023] Figure 1 This is a schematic flowchart of a charging queuing method for a charging station provided in an exemplary embodiment of this application. Figure 1 For example, firstly, based on the location information of the charging stations, the virtual boundaries of the geofence are determined (see...). Figure 1 (S110). The virtual boundary of the geofence includes the physical boundary of the charging station. Next, the location information of the target vehicle within a preset range is obtained (see S110). Figure 1 (S120); a virtual boundary with a preset range larger than the geofence. Next, based on the location information of the target vehicle and the positional relationship between the virtual boundary and the target vehicle's location, the entry time of the target vehicle's first entry into the geofence on that day is determined (see S120). Figure 1 (S130). Then, based on the order of entry time, a charging queue is generated (see S130). Figure 1 (S140). Finally, based on the charging queue, charging reminder information is sent sequentially to the target vehicles in the charging queue (see S140). Figure 1(S150). By objectively recording vehicle arrival times through virtual boundaries of geofencing, human disputes are eliminated. By sequentially sending charging reminder information to target vehicles in the charging queue, drivers can clearly understand their queue position and estimated waiting time, making charging station management more intelligent and rational.

[0024] The following text combines Figure 1 This application provides a more detailed description of the charging queuing method for charging stations provided in its embodiments.

[0025] In S110, the virtual boundary of the geofence is determined based on the location information of the charging station.

[0026] The geofence mentioned above is a location-based virtual boundary technology. It dynamically delineates a virtual, closed polygonal area within a geographic information system using positioning methods such as Global Positioning System (GNSS), Radio Frequency Identification (RFID), Wi-Fi, or cellular networks, thus forming a geofence. When a geofence is set up around a charging station, it forms a virtual boundary that encloses the charging station; that is, the virtual boundary of the geofence includes the physical boundary of the charging station.

[0027] In some embodiments, the charging station may be a new type of charging station designed and built specifically to meet the large-scale, high-efficiency power replenishment needs of heavy trucks. Combined with geofencing technology, it can automatically sense the range of target vehicles entering the charging station, prepare charging resources in advance, and accurately record the entry and exit times for subsequent queuing and operation analysis.

[0028] In S120, the location information of the target vehicle within the preset range is obtained.

[0029] In some embodiments, the preset range is larger than the virtual boundary of the geofence. Real-time location data uploaded by the vehicle terminal or vehicle communication module can be used in advance to determine the vehicle's location information. When the vehicle's location information indicates that the vehicle is within a preset range outside the virtual boundary, this vehicle is designated as the target vehicle. For example, a vehicle with a radius of 3 kilometers from the virtual boundary can be designated as the target vehicle. In other words, the target vehicle is one that is relatively close to the charging station and may become a target customer entering the charging station.

[0030] For example, based on the location information of the target vehicle and its positional relationship with the virtual boundary, the route between the target vehicle and the virtual boundary is obtained; the charging waiting time of the target vehicle is calculated based on the route distance. Based on the charging waiting time, the target vehicles are sorted to generate an initial charging queue. The initial charging queue is then adjusted based on the order of entry time to generate a new charging queue. In other words, when this charging queuing method is applied to large heavy trucks, it can only receive the location information of large heavy trucks entering the charging station, thereby analyzing the possible entry time of large heavy trucks into the charging station and queuing them in advance. Once the large heavy trucks enter the geofence, the entry time is determined, and the charging queue is readjusted based on the entry time.

[0031] By calculating arrival times and initially queuing in advance, charging resources can be planned more precisely. For example, knowing the estimated arrival time of vehicles in advance allows for the rational allocation of parking spaces, avoiding parking shortages or vacancy caused by concentrated vehicle arrivals, and improving the overall utilization rate of parking lots. Furthermore, advance queuing and dynamic queue adjustment can rationally allocate the number of charging stations open and staff deployment based on vehicle arrival data. Preparing in advance before peak arrival times ensures the efficient operation of charging facilities, reduces vehicle waiting time, and improves the utilization efficiency of charging infrastructure. Moreover, calculating queuing and arrival times for vehicles within a preset range in advance can prevent a surge of vehicles entering the charging station. When charging resources are insufficient at the station, vehicles are notified in advance of the estimated waiting time, allowing for rational scheduling of charging trips and ensuring the rational allocation of resources for large heavy trucks.

[0032] In S130, based on the location information of the target vehicle and the location relationship between the virtual boundary, the entry time of the target vehicle's first entry into the geofence on that day is determined.

[0033] In some embodiments, for a geofence to implement the logic triggered when a vehicle enters the area, the geofence region must first be defined in the digital world. This definition process can involve drawing a polygon on a map using a sequence of coordinate points, creating a virtual, invisible boundary that can be precisely identified by a computational program. The virtual boundary serves as the reference point for the geofence to determine positional relationships. Therefore, by creating a virtual boundary, geofencing technology maps and enhances the rules for managing physical space within the digital twin space. Furthermore, the core algorithm for the geofence triggering mechanism (such as entry, exit, or stay) can continuously calculate the spatial relationship between the moving object and the virtual boundary by inputting the real-time coordinates of the moving object and the set of coordinates of the virtual boundary. Here, the moving object is the target vehicle.

[0034] As a method for determining the positional relationship between a target vehicle's location information and a virtual boundary, the target vehicle's location information can include its real-time coordinates. These real-time coordinates are compared with the boundary coordinates of the virtual boundary. When the real-time coordinates coincide with the boundary coordinates, and the target vehicle's trajectory within a preset time indicates that it has entered the geofence from outside the virtual boundary, the moment of coordinate coincidence is determined as the target vehicle's first entry time into the geofence. For example, maintenance personnel manually draw or configure a virtual boundary around the charging station's electronic map on the management platform. This boundary is saved as a series of latitude and longitude coordinates and bound to the corresponding charging station's identifier. The system continuously receives vehicle location information and calculates it in real-time against the virtual boundary coordinate set. By determining the coincidence of coordinates, a timestamp is assigned to the target vehicle, forming a fixed and immutable entry time.

[0035] In S140, a charging queue is generated based on the order of entry time.

[0036] Since the entry time is obtained by marking the overlap between the target vehicle and the virtual boundary, this fixed and unalterable entry time fundamentally eliminates subjective judgment errors, provides a fair queuing basis, reduces disputes and anxiety caused by unfair queuing or unclear progress, and lays a precise data foundation for subsequent queue management.

[0037] In S150, charging reminder information is sent sequentially to the target vehicles in the charging queue based on the charging queue.

[0038] In some embodiments, charging reminder information may be sent via app push notifications, SMS messages, voice broadcasts, etc.

[0039] In some embodiments, after generating a charging queue, a charging sequence number for a vehicle can be generated based on this queue, and the charging status of the target vehicle in the queue can be obtained. Based on the real-time charging status and current battery level of each vehicle, the estimated waiting time for vehicles in the queue is calculated, and a charging sequence number and estimated waiting time are sent to each vehicle. This ensures transparency, fairness in the queuing process, and provides clear expectations.

[0040] For example, when a target vehicle is charging and its real-time battery level is greater than a preset level (which can be set to 100% or 95%), a charging notification message is sent to the next target vehicle in the charging queue. This notification message alerts the vehicle to proceed to charging, preventing charging delays caused by information asymmetry. Furthermore, the estimated charging time can be calculated based on the vehicle's real-time battery level and used as the estimated waiting time for the next vehicle in the queue. If the estimated charging time is less than five minutes (which can be set manually), the next vehicle is alerted to prepare to charge, improving overall operational efficiency.

[0041] In some embodiments, to further improve the operational efficiency of charging stations and ensure the feasibility and rationality of charging queues, invalid vehicles in the charging queue can be removed. For example, it can be determined whether a target vehicle meets the removal criteria. The removal criteria are: the target vehicle's dwell time since entering the geofence is less than a first preset time, and the target vehicle's charging status is not charging. When the removal criteria are met, the target vehicle is removed from the charging queue. In other words, if a vehicle does not start charging within a set time after entering the geofence, it is automatically removed from the queue. Timely removal of invalid queue vehicles can obtain more accurate queuing progress estimates, allowing the driver of the target vehicle to know more accurate queuing information.

[0042] In some embodiments, if a notified vehicle does not start charging within a preset time, a skip mechanism can be set to avoid resource waste caused by long waiting times. For example, it can be determined whether the target vehicle meets the skip condition, which is: the target vehicle is not charging within a second preset time period starting from the date of receiving the charging prompt message; when the skip condition is met, the target vehicle is marked as skipped and a charging prompt message is sent to the next target vehicle.

[0043] For vehicles that have missed their assigned number, a priority mechanism can be set up. These vehicles typically still have charging needs, and providing compensation for their return to the queue avoids long waits or leaving to find other charging stations due to late re-queueing, thus reducing unnecessary vehicle movement and traffic congestion around the stations. Furthermore, clear priority rules guide drivers to act more responsibly, as they know that even if they miss their number due to a temporary absence, their charging needs can still be met. This reduces unnecessary and premature entry into the geofence to reserve a spot, making the queue more reflective of real-time charging demand and optimizing charging station allocation efficiency. As a mechanism for prioritizing charging after a missed number, when a target vehicle has entered the geofence for the first time that day and is marked as having missed its assigned number, priority charging information is generated for that vehicle.

[0044] In some embodiments, priority charging information may be generated automatically based on conditions, or it may be generated by administrators based on driver registration, or it may be generated by the driver registering themselves in an electronic program while located within a geofence.

[0045] In some embodiments, after receiving priority charging information, based on the priority of the priority charging information, the target vehicle corresponding to the priority charging information is placed at the top of the charging queue to obtain a first charging queue; wherein, the priority of the priority charging information is positively correlated with the top position of the target vehicle in the first charging queue. That is, a designated vehicle can be placed at the top of the queue to deal with special circumstances.

[0046] Setting priorities for charging information here allows for the construction of a hierarchical, fair, and operable priority system. For example, when a vehicle that has missed its turn requests charging again, its queue position will receive compensatory priority, but its final ranking must be after all the highest-priority vehicles. High-priority vehicles are those with urgent tasks requiring charging; these vehicles can be assigned to the first position in the waiting queue or have their current queue order interrupted and directly assigned to the next available charging station. Basic priority refers to vehicles that have entered the geofence for the first time and are in the queue without triggering any priority or removal rules. By establishing priorities for charging information, the operational efficiency of large heavy trucks can be guaranteed. Furthermore, providing a remedial channel for vehicles that have missed their turn demonstrates the flexibility and humanization of the service. Finally, basic rules ensure fundamental fairness for the vast majority of drivers in the queue, clearly defining the queue based on first-come, first-served.

[0047] By prioritizing charging information, removing vehicles, and handling vehicle overbooking, and incorporating real-time vehicle battery levels and task urgency, the queue is dynamically rearranged. This improves operational efficiency and resource utilization, enhances dispatch fairness and rationality, and allows drivers to see their queue position changes in real time, providing predictable waiting times and reducing anxiety. This not only resolves the inherent conflict between fairness and efficiency but also significantly improves the charging stations' ability to handle complex scenarios, thereby enhancing their overall operational efficiency and service capabilities.

[0048] Figure 2 This is a schematic diagram of the structure of a charging queuing device for a charging station provided in an exemplary embodiment of this application, as shown below. Figure 2As shown, the charging queuing device 2 at the charging station includes: a setting module 21, used to determine the virtual boundary of the geofence based on the location information of the charging station; wherein the virtual boundary of the geofence includes the physical boundary of the charging station; an acquisition module 22, used to acquire the location information of target vehicles within a preset range; the preset range is larger than the virtual boundary of the geofence; a determination module 23, used to determine the entry time of the target vehicle's first entry into the geofence on the same day based on the positional relationship between the target vehicle's location information and the virtual boundary; a generation module 24, used to generate a charging queue based on the order of entry times; and a prompting module 25, used to send charging prompt information to the target vehicles in the charging queue in sequence.

[0049] As one possible implementation, the charging queuing device 2 of the charging station may include: determining whether the target vehicle meets the removal conditions, wherein the removal conditions are: the dwell time of the target vehicle since entering the geofence is less than a first preset time, and the charging status of the target vehicle is not charging; when the removal conditions are met, the target vehicle is removed from the charging queue.

[0050] As one possible implementation, the charging queuing device 2 of the charging station may include: determining whether the target vehicle meets the skip condition, wherein the skip condition is: the target vehicle is not charging within a second preset time period starting from the date of receiving the charging prompt information; when the skip condition is met, the target vehicle is marked as skipped and a charging prompt information is sent to the next target vehicle.

[0051] As one possible implementation, the charging queuing device 2 at the charging station may also include: generating priority charging information for the target vehicle when the target vehicle is not entering the geofence for the first time on the same day and the target vehicle is marked as having missed its turn.

[0052] As one possible implementation, the charging queuing device 2 of the charging station may further include: receiving priority charging information; based on the priority of the priority charging information, placing the target vehicle corresponding to the priority charging information at the top of the charging queuing queue to obtain a first charging queuing queue; wherein the priority of the priority charging information is positively correlated with the top position of the target vehicle in the first charging queuing queue.

[0053] As one possible implementation, the prompting module 25 can be configured to: obtain the charging status of the target vehicle in the charging queue based on the charging queue; when the target vehicle is charging and its real-time battery level is greater than a preset battery level, send a charging prompt message to the next target vehicle in the charging queue.

[0054] As one possible implementation, the charging queuing device 2 of the charging station may include: obtaining the route between the target vehicle and the virtual boundary based on the location information of the target vehicle and the positional relationship between the virtual boundary and the virtual boundary; calculating the charging waiting time of the target vehicle based on the route distance; sorting the target vehicles based on the charging waiting time to generate an initial charging queue; wherein, the generation module 24 may be configured to: adjust the initial charging queue based on the order of entry time to generate a charging queue.

[0055] As one possible implementation, the location information of the target vehicle includes the real-time coordinates of the target vehicle; wherein, the determination module 23 can be configured to: compare the real-time coordinates of the target vehicle with the boundary coordinates of the virtual boundary, and when the real-time coordinates of the target vehicle coincide with the boundary coordinates, and the running trajectory of the target vehicle within a preset time indicates that the target vehicle enters the geofence from outside the virtual boundary of the geofence, the moment when the coordinates coincide is determined as the entry time of the target vehicle entering the geofence for the first time.

[0056] An electronic device includes: a processor; a memory for storing processor-executable instructions; and a processor for executing a charging queuing method for a charging station according to embodiments of this application.

[0057] Below, for reference Figure 3 This application describes an electronic device according to embodiments thereof. The electronic device may be either or both of a first device and a second device, or a standalone device independent of them, which may communicate with the first device and the second device to receive acquired input signals from them.

[0058] Figure 3 A block diagram of an electronic device according to an embodiment of this application is illustrated.

[0059] like Figure 3 As shown, the electronic device 30 includes one or more processors 31 and memory 32.

[0060] The processor 31 may be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and may control other components in the electronic device 30 to perform desired functions.

[0061] The memory 32 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 31 may execute the program instructions to implement the charging queuing method of the charging station in the various embodiments of this application described above, and / or other desired functions. Various contents such as input signals, signal components, and noise components may also be stored in the computer-readable storage medium.

[0062] In one example, the electronic device 30 may also include an input device 33 and an output device 34, which are interconnected via a bus system and / or other forms of connection mechanism (not shown).

[0063] When the electronic device is a standalone device, the input device 33 can be a communication network connector for receiving the collected input signals from the first device and the second device.

[0064] In addition, the input device 33 may also include, for example, a keyboard, a mouse, etc.

[0065] The output device 34 can output various information to the outside, including determined distance information, direction information, etc. The output device 34 may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0066] Of course, for the sake of simplicity, Figure 3 Only some of the components of the electronic device 30 relevant to this application are shown in this illustration; components such as buses, input / output interfaces, etc., are omitted. In addition, the electronic device 30 may include any other suitable components depending on the specific application.

[0067] Computer program products can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0068] A computer-readable storage medium stores a computer program for executing a charging queuing method for a charging station according to embodiments provided in this application.

[0069] Computer-readable storage media may take the form of any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may, for example, include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0070] The above description has been given for illustrative and descriptive purposes. Furthermore, this description is not intended to limit the embodiments of this application to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A charging queuing method for a charging station, characterized in that, include: Based on the location information of the charging stations, the virtual boundary of the geofence is determined; wherein the virtual boundary of the geofence includes the physical boundary of the charging stations; Obtain the location information of target vehicles within a preset range; the preset range is larger than the virtual boundary of the geofence; Based on the location information of the target vehicle and the location relationship between the virtual boundary, the entry time of the target vehicle when it first enters the geofence on that day is determined; A charging queue is generated based on the order of entry times; Based on the charging queue, charging reminder information is sent sequentially to the target vehicles in the charging queue.

2. The charging queuing method for charging stations according to claim 1, characterized in that, After generating the charging queue based on the order of entry times, the process further includes: Determine whether the target vehicle meets the removal conditions, wherein the removal conditions are: the dwell time of the target vehicle since entering the geofence is less than a first preset time, and the charging status of the target vehicle is not charging; When the removal conditions are met, the target vehicle is removed from the charging queue.

3. The charging queuing method for charging stations according to claim 1, characterized in that, After generating the charging queue based on the order of entry times, the process further includes: Determine whether the target vehicle meets the skip condition, wherein the skip condition is: the target vehicle is not charging within a second preset time period starting from the date of receiving the charging prompt information; When the skip condition is met, the target vehicle is marked as skipped and a charging reminder message is sent to the next target vehicle.

4. The charging queuing method for charging stations according to claim 3, characterized in that, The charging queuing method at the charging station also includes: When the target vehicle enters the geofence for the first time on a given day, and the target vehicle is marked as having passed through, priority charging information for the target vehicle is generated.

5. The charging queuing method for charging stations according to claim 1, characterized in that, The charging queuing method at the charging station also includes: Receive priority charging information; Based on the priority of the priority charging information, the target vehicle corresponding to the priority charging information is placed at the top of the charging queue to obtain a first charging queue; wherein, the priority of the priority charging information is positively correlated with the top position of the target vehicle in the first charging queue.

6. The charging queuing method for charging stations according to claim 1, characterized in that, Based on the charging queue, charging reminder information is sent sequentially to the target vehicles in the charging queue, including: Based on the charging queue, obtain the charging status of the target vehicle in the charging queue; When the target vehicle is charging and its real-time battery level is greater than a preset battery level, a charging notification message is sent to the next target vehicle in the charging queue.

7. The charging queuing method for charging stations according to claim 1, characterized in that, The charging queuing method at the charging station also includes: Based on the positional relationship between the target vehicle's location information and the virtual boundary, obtain the route between the target vehicle and the virtual boundary; Calculate the charging waiting time of the target vehicle based on the route distance; Based on the charging waiting time, the target vehicles are sorted to generate an initial charging queue. The process of generating a charging queue based on the order of entry times includes: The initial charging queue is adjusted based on the order of entry time to generate the charging queue.

8. The charging queuing method for charging stations according to claim 1, characterized in that, The target vehicle's location information includes its real-time coordinates; The determination of the entry time of the target vehicle's first entry into the geofence, based on the positional relationship between the target vehicle's location information and the virtual boundary, includes: The real-time coordinates of the target vehicle are compared with the boundary coordinates of the virtual boundary. When the real-time coordinates of the target vehicle coincide with the boundary coordinates, and the trajectory of the target vehicle within a preset time indicates that the target vehicle enters the geofence from outside the virtual boundary of the geofence, the moment when the coordinates coincide is determined as the entry time of the target vehicle when it first enters the geofence.

9. A charging queuing device for a charging station, characterized in that, include: A setting module is used to determine the virtual boundary of a geofence based on the location information of the charging station; wherein the virtual boundary of the geofence includes the physical boundary of the charging station; The acquisition module is used to acquire the location information of target vehicles within a preset range; the preset range is larger than the virtual boundary of the geofence; The determination module is used to determine the entry time of the target vehicle's first entry into the geofence on that day based on the positional relationship between the target vehicle's location information and the virtual boundary; The generation module is used to generate a charging queue based on the order of the entry times; The notification module is used to send charging notification information to the target vehicles in the charging queue in sequence, based on the charging queue.

10. A charging station, characterized in that, include: A geofence, wherein the virtual boundary of the geofence includes the physical boundary of the charging station; The charging queuing device for a charging station as described in claim 9, wherein the charging queuing device for the charging station is used to execute the charging queuing method for the charging station.

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