A charging gun distribution method of a charging station, an electronic device, and a storage medium

Abstract

The application relates to the technical field of electric vehicle charging, and discloses a charging gun distribution method of a charging station, an electronic device and a storage medium, the method comprising the following steps: in the case that vehicle node parameters uploaded by a to-be-charged vehicle are received, collecting real-time state information of each charging gun, wherein the vehicle node parameters represent the current battery condition, charging demand condition and charging adaptation condition of the to-be-charged vehicle; for each charging gun, performing weight matching of the charging gun relative to the to-be-charged vehicle according to the vehicle node parameters and the real-time state information of the charging gun, so as to obtain an adaptation score of the charging gun; and selecting the charging gun with the highest adaptation score to charge the to-be-charged vehicle. In the application, the charging demand of the vehicle can be accurately matched with the real-time performance of the charging gun, the intelligent optimal distribution of the charging gun can be realized, the service life of the charging equipment is prolonged, and the charging efficiency of the to-be-charged vehicle is improved.

Description

Technical Field

[0001] This invention relates to the field of electric vehicle charging technology, and in particular to a charging gun distribution method, electronic device, and storage medium for a charging station. Background Technology

[0002] With the increasing popularity of electric vehicles, the demand for charging stations has surged, leading to problems such as long vehicle waiting times, uneven load on charging guns, and rapid wear and tear on charging equipment. In practice, when multiple electric vehicles are charging, it is necessary to allocate multiple charging guns within the charging station. Existing allocation methods often rely on user selection on-site or a simple first-come, first-served rule, failing to fully consider the differences in vehicle charging needs and the real-time performance of the charging guns, resulting in low charging efficiency and shortened lifespan of charging equipment. Summary of the Invention

[0003] This invention aims to at least partially solve one of the technical problems in related technologies. To this end, this invention proposes a charging gun distribution method, electronic device, and storage medium for charging stations, which can achieve intelligent distribution of charging guns and improve vehicle charging efficiency.

[0004] In a first aspect, embodiments of the present invention provide a charging gun allocation method for a charging station, applied to a charging management platform in the charging station, the method comprising: Upon receiving the vehicle node parameters uploaded by the vehicle to be charged, the real-time status information of each of the charging guns is collected. The vehicle node parameters represent the current battery status, charging demand, and charging compatibility of the vehicle to be charged. For each charging gun, a weighted matching process is performed on the charging gun relative to the vehicle to be charged based on the vehicle node parameters and the real-time status information of the charging gun, to obtain the matching score of the charging gun. The charging gun with the highest adaptation score is selected to charge the vehicle to be charged.

[0005] Optionally, in one embodiment of the present invention, the real-time status information includes at least one of the following: Basic status information, representing the idle / occupied status of the charging gun, the current output power, and the estimated end time of charging for the electric vehicle currently occupying the charging gun; Performance status information, which represents the number of power modules that the charging gun can call up and the current utilization rate of the power modules; Charging configuration information indicates the charging interface type and compatible charging protocols of the charging gun; Historical status information represents the failure rate of the charging gun within a preset historical time period.

[0006] Optionally, in one embodiment of the present invention, when the real-time status information includes the basic status information, the performance status information, the charging configuration information, and the historical status information, and the vehicle node parameters include demand parameters and adaptation parameters, the step of performing weighted matching of the charging gun relative to the vehicle to be charged based on the vehicle node parameters and the real-time status information of the charging gun to obtain the adaptation score of the charging gun includes: The charging time factor corresponding to the vehicle to be charged is determined based on the basic status information and the demand parameters, and the compatibility factor corresponding to the vehicle to be charged is determined based on the charging configuration information and the adaptation parameters. The load balancing factor corresponding to the vehicle to be charged is determined based on the performance status information, and the risk avoidance factor corresponding to the vehicle to be charged is determined based on the historical status information. The charging time factor, the compatibility factor, the load balancing factor, and the risk avoidance factor are weighted and calculated to obtain the compatibility score of the charging gun.

[0007] Optionally, in one embodiment of the present invention, the method further includes: When it is determined that the adaptation scores of at least two of the charging guns are the same and both are the highest, the historical average charging efficiency of the corresponding at least two of the charging guns is obtained. The charging gun with the highest historical average charging efficiency is selected to charge the vehicle to be charged.

[0008] Optionally, in one embodiment of the present invention, the step of weighting the charging time factor, the compatibility factor, the load balancing factor, and the risk avoidance factor to obtain the adaptation score of the charging gun includes: The charging time factor, the compatibility factor, the load balancing factor, and the risk aversion factor are substituted into the weight matching calculation formula to calculate the adaptation score of the charging gun. The weight matching calculation formula is as follows: ; The compatibility score for the charging gun. The charging time factor is... The load balancing factor is... For the compatibility factor, For the aforementioned risk aversion factor, As the weight of the charging time factor, For load balancing factor weights, For compatibility factor weights, Weighting of risk aversion factors .

[0009] Alternatively, in one embodiment of the present invention, .

[0010] Optionally, in one embodiment of the present invention, determining the charging time factor corresponding to the vehicle to be charged based on the basic state information and the demand parameters includes: The maximum charging power that the charging gun can provide is determined based on the basic status information, and the charging power demand of the vehicle to be charged is determined based on the demand parameters. If the maximum charging power is not less than the charging demand power, the charging time factor corresponding to the vehicle to be charged is determined to be 1; otherwise, the charging time factor corresponding to the vehicle to be charged is determined to be the ratio of the maximum charging power to the charging demand power.

[0011] Optionally, in one embodiment of the present invention, determining the compatibility factor corresponding to the vehicle to be charged based on the charging configuration information and the adaptation parameters includes: If, based on the charging configuration information and the adaptation parameters, it is determined that the charging gun matches the charging interface type and charging protocol of the vehicle to be charged, the compatibility factor corresponding to the vehicle to be charged is determined to be 1; otherwise, the compatibility factor corresponding to the vehicle to be charged is determined to be 0.

[0012] In a second aspect, embodiments of the present invention provide an electronic device, comprising: At least one processor; At least one memory for storing at least one program; When at least one of the programs is executed by at least one of the processors, the charging gun distribution method for the charging station as described in the first aspect is implemented.

[0013] Thirdly, embodiments of the present invention provide a computer-readable storage medium storing a processor-executable program, which, when executed by a processor, is used to implement the charging gun distribution method for a charging station as described in the first aspect.

[0014] This invention proposes a charging gun allocation method, electronic device, and storage medium for charging stations. By virtually accessing the vehicle node parameters of the vehicle to be charged, the current battery status, charging demand, and charging compatibility of the vehicle are determined. Real-time status information of each charging gun is also acquired. Based on the vehicle node parameters and the real-time status information of the charging guns, multi-dimensional weighted matching is performed to obtain a compatibility score for different charging guns relative to the vehicle node parameters. Adaptive allocation of charging guns is then achieved based on the compatibility score. The entire process accurately matches the vehicle's charging needs with the real-time performance of the charging guns, enabling intelligent and optimal allocation of charging guns, extending the lifespan of charging equipment, and improving the charging efficiency of the vehicle to be charged. Attached Figure Description

[0015] Figure 1 This is a flowchart of a charging gun distribution method for a charging station provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the principle of a virtual vehicle node provided in an embodiment of the present invention; Figure 3 yes Figure 1 The flowchart of step S2 in the process; Figure 4 yes Figure 3 A partial flowchart of step S21, "Determine the charging time factor corresponding to the vehicle to be charged based on the basic status information and demand parameters". Figure 5 yes Figure 3 A partial flowchart of step S21, "Determine the compatibility factor corresponding to the vehicle to be charged based on the charging configuration information and adaptation parameters". Figure 6 This is a flowchart of a charging gun distribution method for a charging station provided in another embodiment of the present invention; Figure 7 This is a schematic diagram of weight allocation for a multi-objective optimization algorithm provided in an embodiment of the present invention; Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0017] It should be noted that although functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart.

[0018] Figure 1 This is a flowchart of a charging gun allocation method for a charging station according to an embodiment of the present invention. This charging gun allocation method can be applied to, but is not limited to, a charging management platform within the charging station. The charging management platform can be integrated into the charging station itself, or it can be externally configured within the charging station. Its specific type, parameters, etc., can be set by those skilled in the art according to different application scenarios, and are not limited here. For example, it can include, but is not limited to, IoT sensors, a charging pile interaction unit, and a backend computing unit. The IoT sensors are used for data communication, the charging pile interaction unit is used for real-time interaction with the charging vehicle, and the backend computing unit is used for weight matching calculations. Figure 1 As shown, the charging gun distribution method of the charging station may include, but is not limited to, steps S1 to S3.

[0019] Step S1: Upon receiving the vehicle node parameters uploaded by the vehicle to be charged, collect the real-time status information of each charging gun. The vehicle node parameters represent the current battery status, charging demand, and charging compatibility of the vehicle to be charged. Step S2: For each charging gun, based on the vehicle node parameters and the real-time status information of the charging gun, perform weight matching of the charging gun relative to the vehicle to be charged to obtain the matching score of the charging gun. Step S3: Select the charging gun with the highest compatibility score to charge the vehicle to be charged.

[0020] In this step, the vehicle node parameters of the vehicle to be charged are virtually accessed to clarify the current battery status, charging demand, and charging compatibility of the vehicle. Real-time status information of each charging gun is also obtained. Based on the vehicle node parameters and the real-time status information of the charging guns, multi-dimensional weighted matching is performed to obtain a compatibility score for different charging guns relative to the vehicle node parameters. The appropriate charging guns are then allocated based on their compatibility scores. This process accurately matches the vehicle's charging needs with the real-time performance of the charging guns, enabling intelligent and optimal allocation of charging guns, extending the lifespan of the charging equipment, and improving the charging efficiency of the vehicle to be charged.

[0021] It should be noted that the charging management platform collects real-time status information of all charging guns in the charging station to build a dynamic status database. During the sampling process, the dynamic status database can be continuously updated at preset intervals (e.g., 30 seconds). In other words, if a used charging gun is released or a new vehicle is connected, the matching score can be recalculated in real time to dynamically adjust the allocation results. This embodiment is also applicable to the case of multiple vehicles connected, where only the matching score of the charging gun corresponding to each vehicle needs to be calculated separately. The principle is the same. To avoid redundancy, the following embodiments are mainly based on the case of a single vehicle.

[0022] In one embodiment, once the charging gun with the highest compatibility score is determined, the user terminal can be pushed with the charging gun number, estimated charging time, and charging gun location navigation information, and the charging gun can be locked. The locking time can be preset, for example, 10 minutes. If the charging gun is not used within the time limit, it will be automatically released.

[0023] In one embodiment, such as Figure 2 As shown, vehicle node parameters can be presented, but are not limited to, in the form of virtual vehicle nodes. That is, the vehicle to be charged can upload vehicle node parameters to the charging management platform through the vehicle terminal, mobile APP, or charging pile interaction module (such as NFC, RFID, etc.) to generate a virtual vehicle node. The virtual vehicle node is specifically used to store the battery parameters, demand parameters, and adaptation parameters of the corresponding vehicle to be charged. These parameters respectively represent the current battery status, charging demand status, and charging adaptation status of the vehicle to be charged. Among them, battery parameters can include, but are not limited to, the current battery level (such as SOC, etc.), total battery capacity, maximum supported charging power, and battery type (such as ternary lithium / lithium iron phosphate, etc.). Demand parameters can include, but are not limited to, the target battery level, the expected dwell time, and whether V2G function is supported. Adaptation parameters can include, but are not limited to, the charging interface type (such as DC fast charging interface, AC slow charging interface, etc.) and compatible charging protocols (GB / T, CCS, or CHAdeMO, etc.).

[0024] In one embodiment, the real-time status information may include, but is not limited to, at least one of the following: Basic status information, representing the idle / occupied status of the charging gun, the current output power, and the estimated end time of charging for the electric vehicle currently occupying the charging gun; Performance status information indicates the number of power modules that the charging gun can call upon and the current utilization rate of the power modules. It can also indicate, but is not limited to, the current operating status of the charging gun's heat dissipation system (such as the speed of the cooling fan in the heat dissipation system, internal temperature, etc.). The current utilization rate of the power modules refers to the ratio of the number of power modules currently being called upon for charging to the total number of power modules. Charging configuration information indicates the charging interface type and compatible charging protocols of the charging gun; Historical status information represents the failure rate of the charging gun within a preset historical time period. The preset historical time period can be set by the user, for example, it can be set to the most recent N hours. The failure rate can be evaluated by average charging efficiency, number of voltage fluctuations, and interface failure records.

[0025] like Figure 3 As shown in one embodiment of the present invention, when the real-time status information includes basic status information, performance status information, charging configuration information, and historical status information, and the vehicle node parameters include demand parameters and adaptation parameters, step S2 may include, but is not limited to, the following steps: Step S21: Determine the charging time factor corresponding to the vehicle to be charged based on the basic status information and demand parameters, and determine the compatibility factor corresponding to the vehicle to be charged based on the charging configuration information and adaptation parameters. Step S22: Determine the load balancing factor corresponding to the vehicle to be charged based on the performance status information, and determine the risk avoidance factor corresponding to the vehicle to be charged based on the historical status information. Step S23: Calculate the weights of the charging time factor, compatibility factor, load balancing factor, and risk avoidance factor to obtain the charging gun's compatibility score.

[0026] In this step, the charging time factor represents the degree to which the charging time can be shortened, the compatibility factor is used to ensure the compatibility between the vehicle to be charged and the charging gun, the load balancing factor is used to balance the overall load of the charging station, and the risk avoidance factor is used to assess the risk of charging failure. By combining the charging time factor, compatibility factor, load balancing factor and risk avoidance factor for weight calculation, the degree of fit between the charging gun and the vehicle to be charged can be better evaluated, and the corresponding fit score can be obtained.

[0027] In one embodiment of the present invention, step S23 may include, but is not limited to, the following steps: Step S231: Substitute the charging time factor, compatibility factor, load balancing factor and risk avoidance factor into the weight matching calculation formula to calculate the weight and obtain the charging gun's compatibility score. The formula for weight matching is as follows: ; The compatibility score for the charging gun. For charging time factor, As a load balancing factor, For compatibility factors, As a risk aversion factor, As the weight of the charging time factor, For load balancing factor weights, For compatibility factor weights, Weighting of risk aversion factors .

[0028] In one embodiment, , , and The specific value can be set according to the actual charging needs. Preferably, it can be set to... This reflects the control level from high to low as follows: shortening charging time, balancing load, ensuring compatibility, and avoiding fault risks.

[0029] In one embodiment, Calculations can be made based on the current utilization rate of the power module in the charging gun, for example... The value can be 1 minus the current power module utilization rate of the charging gun. Of course, it can also be multiplied by the corresponding fixed coefficient for easier calculation. For example, the fixed coefficient can be 100. The same applies below.

[0030] In one embodiment, The selection can be based on different scenarios. For example, if there are no fault records in the last 72 hours, then the value is 1; for each fault that occurs, then... Reduce by 0.2.

[0031] like Figure 4 As shown, in one embodiment of the present invention, step S21, which determines the charging time factor corresponding to the vehicle to be charged based on the basic state information and demand parameters, may include, but is not limited to, the following steps: Step S211: Determine the maximum charging power that the charging gun can provide based on the basic status information, and determine the charging power demand of the vehicle to be charged based on the demand parameters. Step S212: When the maximum charging power is not less than the charging demand power, determine the charging time factor corresponding to the vehicle to be charged as 1; otherwise, determine the charging time factor corresponding to the vehicle to be charged as the ratio of the maximum charging power to the charging demand power.

[0032] In this step, the charging time factor is set by determining the difference between the maximum charging power that the charging gun can provide and the charging power required by the vehicle to be charged. That is, when the charging gun can provide the maximum power required by the vehicle to be charged, the charging time factor is set to 1; otherwise, the charging time factor is set to a value less than 1, which is the ratio of the maximum charging power to the charging power required.

[0033] like Figure 5As shown, in one embodiment of the present invention, step S21, determining the compatibility factor corresponding to the vehicle to be charged based on the charging configuration information and adaptation parameters, may include, but is not limited to, the following steps: Step S213: If the charging gun and the charging interface type and charging protocol of the vehicle to be charged are matched according to the charging configuration information and adaptation parameters, the compatibility factor corresponding to the vehicle to be charged is determined to be 1; otherwise, the compatibility factor corresponding to the vehicle to be charged is determined to be 0.

[0034] In this step, if it is determined that the charging gun and the charging interface type and charging protocol of the vehicle to be charged are compatible, it means that the charging gun and the vehicle to be charged are fully compatible. Therefore, the compatibility factor is set to the maximum and the value is 1. Otherwise, it means that the two cannot be matched, and the corresponding compatibility factor should not provide an actual calculation component, that is, the value is 0.

[0035] like Figure 6 As shown in one embodiment of the present invention, the charging gun distribution method of the charging station may further include, but is not limited to, the following steps: Step S4: When it is determined that at least two charging guns have the same and the highest adaptation scores, obtain the historical average charging efficiency of the corresponding at least two charging guns. Step S5: Select the charging gun with the highest historical average charging efficiency to charge the vehicle to be charged.

[0036] In this step, if at least two charging guns have the same and the highest matching score, it means that these charging guns are compatible with the vehicle to be charged. Considering the standardized operation process of the charging station, the charging gun with the highest historical average charging efficiency is selected to charge the vehicle. This is beneficial to further improve the equipment operating efficiency of the charging station and enhance the user charging experience. The historical period corresponding to the historical average charging efficiency can be selected according to the actual situation and is not restricted.

[0037] To better illustrate the working principle of the above embodiments, the following description is provided in conjunction with specific examples.

[0038] like Figure 7 , Figure 7 The weight coefficient allocation of the multi-objective optimization algorithm used in this embodiment is shown, and two cases are explained.

[0039] Scenario 1: Single vehicle access scenario Vehicle Q parameters: SOC 30%, battery capacity 70kWh, maximum power demand 60kW, DC fast charging interface, charging protocol GB / T, target battery level 80%; Charging gun 1: Idle, can provide 60kW of power, power module utilization rate 30%, no fault record; Charging gun 2: Idle, can provide 40kW of power, power module utilization rate 20%, no fault record; Calculate the fit score (with a fixed coefficient of 100, the same below): Charging gun 1: =100 (60kW≥60kW) =100-30=70、 =100、 =100; =0.4*100+0.3*70+0.2*100+0.1*100=81; Charging gun 2: =100*(40 / 60)=66.7 =100-20=80、 =100、 =100; =0.4*66.7+0.3*80+0.2*100+0.1*100=72.68; Allocation result: The optimal charging gun is charging gun 1, and the estimated charging time is approximately 29 minutes (70 × (80% - 30%)) / 60.

[0040] Scenario 2: Multiple vehicles queuing Vehicle M (connected first): Maximum power requirement 50kW; Vehicle N (rear access): Maximum power required 30kW; Charging gun 3 (provides a maximum power of 50kW and a power module utilization rate of 40%), charging gun 4 (provides a maximum power of 30kW and a power module utilization rate of 30%). Initial allocation: Vehicle M is matched with charging gun 3 ( For 85), vehicle N is matched with charging gun 4 ( (82) 3 minutes later: Vehicle M finishes charging, and charging gun 3 is released; at this time, the charging management platform recalculates the compatibility score of vehicle N with charging gun 3. =0.4*100+0.3*60+0.2*100+0.1*100=88, which is higher than the 82 of charging gun 4; Dynamic adjustment: Update the optimal charging gun for vehicle N to charging gun 3 to shorten its charging time.

[0041] It can be seen that by accurately matching vehicle needs with charging gun performance, charging efficiency can be significantly improved, and statistics show that it can shorten the average waiting time for users by 20%-30%. It can also balance the load on the equipment, avoid a single charging gun from running at high load for a long time, and extend the life of its power module. In particular, it can enhance the user experience, support advance reservation, and allow users to connect directly to the optimal charging gun through navigation without having to queue on-site. It has a wide range of adaptability and is compatible with vehicles of different brands and charging protocols, and is suitable for various scenarios such as public charging stations and community charging stations.

[0042] Figure 8 This is a schematic diagram of the structure of an electronic device 1000 provided in an embodiment of the present invention. For example... Figure 8 As shown, the electronic device 1000 includes a memory 1100 and a processor 1200. The number of memories 1100 and processors 1200 can be one or more. Figure 8 Taking a memory 1100 and a processor 1200 as an example; the memory 1100 and the processor 1200 in the device can be connected via a bus or other means. Figure 8 Taking the example of a connection between China and Israel via a bus.

[0043] The memory 1100, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the charging gun allocation method of the charging station provided in any embodiment of the present invention. The processor 1200 implements the above-described charging gun allocation method of the charging station by running the software programs, instructions, and modules stored in the memory 1100.

[0044] The memory 1100 may primarily include a program storage area and a data storage area, wherein the program storage area may store the operating system and application programs required for at least one function. Furthermore, the memory 1100 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 1100 may further include memory remotely located relative to the processor 1200, and these remote memories can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0045] An embodiment of the present invention also provides a computer-readable storage medium storing computer-executable instructions for performing a charging gun distribution method for a charging station as provided in any embodiment of the present invention.

[0046] An embodiment of the present invention also provides a computer program product, including a computer program or computer instructions, which are stored in a computer-readable storage medium. A processor of a computer device reads the computer program or computer instructions from the computer-readable storage medium and executes the computer program or computer instructions, causing the computer device to perform the charging gun distribution method of a charging station as provided in any embodiment of the present invention.

[0047] The electronic devices and application scenarios described in the embodiments of this invention are for the purpose of more clearly illustrating the technical solutions of the embodiments of this invention, and do not constitute a limitation on the technical solutions provided by the embodiments of this invention. As those skilled in the art will know, with the evolution of electronic devices and the emergence of new application scenarios, the technical solutions provided by the embodiments of this invention are also applicable to similar technical problems.

[0048] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0049] In hardware implementations, the division between functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0050] The terms “component,” “module,” “system,” etc., used in this specification are used to refer to computer-related entities, hardware, firmware, combinations of hardware and software, software, or software in execution. For example, a component can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a program, or a computer. As illustrated, applications running on computing devices and computing devices can both be components. One or more components may reside in a process or execution thread, and components may be located on a single computer or distributed among two or more computers. Furthermore, these components can be executed from various computer-readable media on which various data structures are stored. Components can communicate, for example, via local or remote processes based on signals having one or more data packets (e.g., data from two components interacting with another component between a local system, a distributed system, or a network, such as the Internet interacting with other systems via signals).

Claims

1. A method for distributing charging guns in a charging station, characterized in that, The method, applied to the charging management platform in the charging station, includes: Upon receiving the vehicle node parameters uploaded by the vehicle to be charged, the real-time status information of each of the charging guns is collected. The vehicle node parameters represent the current battery status, charging demand, and charging compatibility of the vehicle to be charged. For each charging gun, a weighted matching process is performed on the charging gun relative to the vehicle to be charged based on the vehicle node parameters and the real-time status information of the charging gun, to obtain the matching score of the charging gun. The charging gun with the highest adaptation score is selected to charge the vehicle to be charged.

2. The charging gun distribution method for a charging station according to claim 1, characterized in that, The real-time status information includes at least one of the following: Basic status information, representing the idle / occupied status of the charging gun, the current output power, and the estimated end time of charging for the electric vehicle currently occupying the charging gun; Performance status information, which represents the number of power modules that the charging gun can call up and the current utilization rate of the power modules; Charging configuration information indicates the charging interface type and compatible charging protocols of the charging gun; Historical status information represents the failure rate of the charging gun within a preset historical time period.

3. The charging gun distribution method for a charging station according to claim 2, characterized in that, When the real-time status information includes the basic status information, the performance status information, the charging configuration information, and the historical status information, and the vehicle node parameters include demand parameters and adaptation parameters, the step of performing weighted matching of the charging gun relative to the vehicle to be charged based on the vehicle node parameters and the real-time status information of the charging gun to obtain the adaptation score of the charging gun includes: The charging time factor corresponding to the vehicle to be charged is determined based on the basic status information and the demand parameters, and the compatibility factor corresponding to the vehicle to be charged is determined based on the charging configuration information and the adaptation parameters. The load balancing factor corresponding to the vehicle to be charged is determined based on the performance status information, and the risk avoidance factor corresponding to the vehicle to be charged is determined based on the historical status information. The charging time factor, the compatibility factor, the load balancing factor, and the risk avoidance factor are weighted and calculated to obtain the compatibility score of the charging gun.

4. The charging gun distribution method for a charging station according to claim 1, characterized in that, The method further includes: When it is determined that the adaptation scores of at least two of the charging guns are the same and both are the highest, the historical average charging efficiency of the corresponding at least two of the charging guns is obtained. The charging gun with the highest historical average charging efficiency is selected to charge the vehicle to be charged.

5. The charging gun distribution method for a charging station according to claim 3, characterized in that, The process of weighting the charging time factor, the compatibility factor, the load balancing factor, and the risk aversion factor to obtain the compatibility score of the charging gun includes: The charging time factor, the compatibility factor, the load balancing factor, and the risk aversion factor are substituted into the weight matching calculation formula to calculate the adaptation score of the charging gun. The weight matching calculation formula is as follows: ； The compatibility score for the charging gun. The charging time factor is... The load balancing factor is... For the compatibility factor, For the aforementioned risk aversion factor, As the weight of the charging time factor, For load balancing factor weights, For compatibility factor weights, Weighting of risk aversion factors .

6. The charging gun distribution method for a charging station according to claim 5, characterized in that, 。 7. The charging gun distribution method for a charging station according to claim 3, characterized in that, The step of determining the charging time factor corresponding to the vehicle to be charged based on the basic state information and the demand parameters includes: The maximum charging power that the charging gun can provide is determined based on the basic status information, and the charging power demand of the vehicle to be charged is determined based on the demand parameters. If the maximum charging power is not less than the charging demand power, the charging time factor corresponding to the vehicle to be charged is determined to be 1; otherwise, the charging time factor corresponding to the vehicle to be charged is determined to be the ratio of the maximum charging power to the charging demand power.

8. The charging gun distribution method for a charging station according to claim 3, characterized in that, The step of determining the compatibility factor corresponding to the vehicle to be charged based on the charging configuration information and the adaptation parameters includes: If, based on the charging configuration information and the adaptation parameters, it is determined that the charging gun matches the charging interface type and charging protocol of the vehicle to be charged, the compatibility factor corresponding to the vehicle to be charged is determined to be 1; otherwise, the compatibility factor corresponding to the vehicle to be charged is determined to be 0.

9. An electronic device, characterized in that, include: At least one processor; At least one memory for storing at least one program; When at least one of the programs is executed by at least one of the processors, the charging gun distribution method for a charging station as described in any one of claims 1 to 8 is implemented.

10. A computer-readable storage medium, characterized in that, It stores a processor-executable program, which, when executed by the processor, is used to implement the charging gun distribution method of the charging station as described in any one of claims 1 to 8.

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