Charging station site selection method and system

Abstract

The invention provides a charging station site selection method and system, and the method comprises the steps: receiving a target region inputted by a user in real time, and detecting a region map corresponding to the target region in a preset map database in real time; scanning the whole area map to correspondingly detect a plurality of original streets contained in the target area, and adding a corresponding target identifier to each original street; performing primary screening on the plurality of original streets according to the target identifier based on a first preset rule so as to correspondingly screen out a plurality of target streets; and performing secondary screening on the plurality of target streets based on a second preset rule to correspondingly screen out an optimal street, and setting a corresponding charging station in the optimal street, each target identifier having uniqueness. According to the invention, the optimal location can be objectively and accurately selected, and the use efficiency of the charging station is correspondingly improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a charging station site selection method and system. Background Art

[0002] With the advancement of science and technology and the rapid development of the times, the production technology of new energy vehicles has become increasingly mature, so that new energy vehicles have been recognized by people and have been popularized in people’s daily lives, greatly facilitating people’s work and life.

[0003] In order to facilitate users to charge their new energy electric vehicles, a large number of charging stations need to be set up. Specifically, in order to improve the utilization efficiency of the charging stations, each charging station needs to be set at a reasonable location.

[0004] Furthermore, in the prior art, in the process of selecting a site for a charging station, most of the time, staff conduct on-site inspections and decide the installation location of the charging station based on their subjective judgment. However, although this site selection method can complete the site selection of the charging station to a certain extent, the factors considered by the staff in the site selection process are relatively single and not comprehensive, and are easily affected by human subjective factors, which leads to certain errors. Summary of the invention

[0005] Based on this, the purpose of the present invention is to provide a charging station site selection method and system to solve the problem that the factors considered in the site selection process in the prior art are relatively single and not comprehensive, and are easily affected by human subjective factors, resulting in easy errors.

[0006] The first aspect of the embodiment of the present invention proposes:

[0007] A method for selecting a charging station site, wherein the method comprises:

[0008] Receiving a target area input by a user in real time, and detecting a regional map corresponding to the target area in a preset map database in real time;

[0009] Performing a full scan on the regional map to detect a number of original streets contained in the target area, and adding a corresponding target mark to each of the original streets;

[0010] Based on the first preset rule, a plurality of the original streets are screened according to the target identifier to select a plurality of target streets accordingly;

[0011] Based on the second preset rule, a second screening is performed on the target streets to select the optimal street, and a corresponding charging station is set inside the optimal street, and each target identifier is unique.

[0012] The beneficial effect of the present invention is that by receiving the target area input by the user in real time, the required regional map can be obtained accordingly, so that a deeper analysis can be performed. Specifically, it is only necessary to scan in real time a number of original streets corresponding to the current regional map, wherein corresponding target identifiers can be added respectively for easy distinction. Based on this, subsequent primary screening and secondary screening can be further performed, and the optimal streets suitable can be finally screened out, so that a location that meets the requirements can be selected objectively and accurately, thereby correspondingly improving the utilization efficiency of the charging station and improving the user experience.

[0013] Furthermore, the step of screening the plurality of original streets according to the target identifier based on the first preset rule to correspondingly screen out a plurality of target streets includes:

[0014] When a number of the original streets are detected in real time, the geographical center corresponding to the target area is detected in real time;

[0015] Detecting the target distance between each original street and the geographic center in real time, and matching the geographic coefficient corresponding to each original street in a preset database in real time according to the size of each target distance;

[0016] A plurality of the original streets are screened based on the target distance and the geographic coefficient to correspondingly screen out a plurality of the target streets.

[0017] Furthermore, the step of screening the plurality of original streets based on the target distance and the geographic coefficient to screen out the plurality of target streets includes:

[0018] The number of vehicles passing through each of the original streets is obtained by a collection device within a preset time period, and the vehicle flow coefficient corresponding to each of the original streets is matched in real time in the preset database according to the size of each of the number of vehicles;

[0019] The traffic flow coefficient and the geographic coefficient are cumulatively processed to generate a corresponding target coefficient in real time, and the target distance of each original street and the target coefficient corresponding thereto are cumulatively processed to calculate a primary score value corresponding to each original street;

[0020] In real time, a number of target streets are correspondingly selected from the number of original streets according to the primary scoring value.

[0021] Furthermore, the step of selecting a plurality of target streets from a plurality of original streets in real time according to the primary scoring value includes:

[0022] When the primary score value of each of the original streets is obtained respectively, it is determined in real time whether the primary score value of each of the original streets is greater than a preset score threshold;

[0023] If it is determined in real time that there is an original street whose score value is greater than the preset score threshold, the original street corresponding to the current score value greater than the preset score threshold is set as the target street, and there are multiple target streets.

[0024] Furthermore, the step of performing secondary screening on the target streets based on the second preset rule to select the optimal street includes:

[0025] When a number of target streets are acquired in real time, a sorting is performed according to the size of the primary score value of each target street to generate a corresponding first sequence table;

[0026] The number of fuel vehicles and electric vehicles passing through each of the target streets is detected in real time by the collection device within the preset time period;

[0027] The optimal street is selected based on the first sequence table according to the number of fuel vehicles and the number of electric vehicles.

[0028] Furthermore, the step of selecting the optimal street according to the number of fuel vehicles and the number of electric vehicles based on the first sequence table includes:

[0029] When the number of fuel vehicles and the number of electric vehicles corresponding to each of the target streets are obtained in real time, a target ratio between the number of fuel vehicles and the number of electric vehicles is calculated in real time;

[0030] The target ratio is set to a vehicle type coefficient that matches the target street, and the optimal street is selected based on the vehicle type coefficient and the first sequence table.

[0031] Furthermore, the step of selecting the optimal street according to the vehicle type coefficient and the first sequence table includes:

[0032] When the vehicle type coefficient corresponding to each of the target streets is obtained respectively, the vehicle type coefficient of each target street in the first sequence table and the corresponding primary score value are cumulatively multiplied to calculate the secondary score value corresponding to each of the target streets in real time;

[0033] A plurality of target streets are secondary sorted according to the size of each secondary scoring value to generate a corresponding second sequence list in real time, and the first street in the second sequence list is correspondingly set as the optimal street.

[0034] The second aspect of the embodiment of the present invention proposes:

[0035] A charging station site selection system, wherein the system comprises:

[0036] A detection module, used to receive a target area input by a user in real time, and detect a regional map corresponding to the target area in a preset map database in real time;

[0037] A scanning module, used for performing a full scan on the regional map to detect a number of original streets contained in the target area, and adding a corresponding target mark to each of the original streets;

[0038] A first screening module, used for screening the plurality of original streets according to the target identifier based on a first preset rule, so as to screen out a plurality of target streets accordingly;

[0039] The second screening module is used to perform secondary screening on the target streets based on the second preset rule to select the optimal street and set up corresponding charging stations inside the optimal street, and each target identifier is unique.

[0040] Furthermore, the first screening module is specifically used for:

[0041] When a number of the original streets are detected in real time, the geographical center corresponding to the target area is detected in real time;

[0042] Detecting the target distance between each original street and the geographic center in real time, and matching the geographic coefficient corresponding to each original street in a preset database in real time according to the size of each target distance;

[0043] A plurality of the original streets are screened based on the target distance and the geographic coefficient to correspondingly screen out a plurality of the target streets.

[0044] Furthermore, the first screening module is specifically used for:

[0045] The number of vehicles passing through each of the original streets is obtained by a collection device within a preset time period, and the vehicle flow coefficient corresponding to each of the original streets is matched in real time in the preset database according to the size of each of the number of vehicles;

[0046] The traffic flow coefficient and the geographic coefficient are cumulatively processed to generate a corresponding target coefficient in real time, and the target distance of each original street and the target coefficient corresponding thereto are cumulatively processed to calculate a primary score value corresponding to each original street;

[0047] In real time, a number of target streets are correspondingly selected from the number of original streets according to the primary scoring value.

[0048] Furthermore, the first screening module is specifically used for:

[0049] When the primary score value of each of the original streets is obtained respectively, it is determined in real time whether the primary score value of each of the original streets is greater than a preset score threshold;

[0050] If it is determined in real time that there is an original street whose score value is greater than the preset score threshold, the original street corresponding to the current score value greater than the preset score threshold is set as the target street, and there are multiple target streets.

[0051] Furthermore, the second screening module is specifically used for:

[0052] When a number of target streets are acquired in real time, a sorting is performed according to the size of the primary score value of each target street to generate a corresponding first sequence table;

[0053] The number of fuel vehicles and electric vehicles passing through each of the target streets is detected in real time by the collection device within the preset time period;

[0054] The optimal street is selected based on the first sequence table according to the number of fuel vehicles and the number of electric vehicles.

[0055] Furthermore, the second screening module is specifically used for:

[0056] When the number of fuel vehicles and the number of electric vehicles corresponding to each of the target streets are obtained in real time, a target ratio between the number of fuel vehicles and the number of electric vehicles is calculated in real time;

[0057] The target ratio is set to a vehicle type coefficient that matches the target street, and the optimal street is selected based on the vehicle type coefficient and the first sequence table.

[0058] Furthermore, the second screening module is specifically used for:

[0059] When the vehicle type coefficient corresponding to each of the target streets is obtained respectively, the vehicle type coefficient of each target street in the first sequence table and the corresponding primary score value are cumulatively multiplied to calculate the secondary score value corresponding to each of the target streets in real time;

[0060] A plurality of target streets are secondary sorted according to the size of each secondary scoring value to generate a corresponding second sequence list in real time, and the first street in the second sequence list is correspondingly set as the optimal street.

[0061] The third aspect of the embodiment of the present invention proposes:

[0062] A computer comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the charging station site selection method as described above when executing the computer program.

[0063] The fourth aspect of the embodiments of the present invention proposes:

[0064] A readable storage medium stores a computer program, wherein when the program is executed by a processor, the charging station site selection method as described above is implemented.

[0065] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 A flowchart of a charging station site selection method provided by a first embodiment of the present invention;

[0067] Figure 2 This is a structural block diagram of a charging station site selection system provided in the third embodiment of the present invention.

[0068] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0069] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0070] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0071] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0072] See also Figure 1 , which shows the charging station site selection method provided by the first embodiment of the present invention. The charging station site selection method provided by this embodiment can objectively and accurately select a location that meets the requirements, thereby correspondingly improving the utilization efficiency of the charging station and improving the user experience.

[0073] Specifically, this embodiment provides:

[0074] A method for selecting a charging station site comprises the following steps:

[0075] Step S10, receiving a target area input by a user in real time, and detecting a regional map corresponding to the target area in a preset map database in real time;

[0076] Step S20, performing a full scan on the regional map to detect a number of original streets contained in the target area, and adding a corresponding target identifier to each of the original streets;

[0077] Step S30, screening the plurality of original streets according to the target identifier based on the first preset rule to screen out a plurality of target streets;

[0078] Step S40, performing secondary screening on the target streets based on the second preset rule to select the optimal street, and setting up corresponding charging stations inside the optimal street, and each target identifier is unique.

[0079] Specifically, in this embodiment, it should be noted that, in order to objectively and accurately select the deployment location of the charging station that meets the user's requirements, it is necessary to obtain the characteristics of each area and the main driving location of the vehicles in each area. Based on this, when the server set in the background receives the target area sent by the user through the existing user terminal in real time, the present invention will immediately detect the regional map adapted to the current target area in the existing map database in real time. It should be pointed out that the target area can be a town, a county town or an urban area, and the location of the charging station is further selected according to the current regional map.

[0080] Furthermore, in order to further obtain the characteristics of the current target area, it is necessary to further analyze and process the current area map. Preferably, the present invention will first perform a full scan of the current area map. At the same time, it can detect the corresponding original streets contained in the current target area. Based on this, in order to facilitate subsequent identification and processing, the present invention will further add corresponding target identifiers to each current original street. Preferably, the target identifier is marked with a number. Furthermore, the server will immediately call out the pre-set first preset rule inside it, and immediately filter the current original streets once through the current first preset rule, and filter out the required target streets accordingly. Based on this, the pre-set second preset rule is further called out, and the optimal street can be finally filtered out from the current target streets through the second preset rule, that is, the location that can maximize the efficiency of the charging station, and finally the charging station is set inside the current optimal street, so that the optimal location of the charging station can be objectively and accurately selected, which correspondingly improves the user experience.

[0081] Second embodiment

[0082] Furthermore, the step of screening the plurality of original streets according to the target identifier based on the first preset rule to correspondingly screen out a plurality of target streets includes:

[0083] When a number of the original streets are detected in real time, the geographical center corresponding to the target area is detected in real time;

[0084] Detecting the target distance between each original street and the geographic center in real time, and matching the geographic coefficient corresponding to each original street in a preset database in real time according to the size of each target distance;

[0085] A plurality of the original streets are screened based on the target distance and the geographic coefficient to correspondingly screen out a plurality of the target streets.

[0086] Furthermore, the step of screening the plurality of original streets based on the target distance and the geographic coefficient to screen out the plurality of target streets includes:

[0087] The number of vehicles passing through each of the original streets is obtained by a collection device within a preset time period, and the vehicle flow coefficient corresponding to each of the original streets is matched in real time in the preset database according to the size of each of the number of vehicles;

[0088] The traffic flow coefficient and the geographic coefficient are cumulatively processed to generate a corresponding target coefficient in real time, and the target distance of each original street and the target coefficient corresponding thereto are cumulatively processed to calculate a primary score value corresponding to each original street;

[0089] In real time, a number of target streets are correspondingly selected from the number of original streets according to the primary scoring value.

[0090] Furthermore, the step of selecting a plurality of target streets from a plurality of original streets in real time according to the primary scoring value includes:

[0091] When the primary score value of each of the original streets is obtained respectively, it is determined in real time whether the primary score value of each of the original streets is greater than a preset score threshold;

[0092] If it is determined in real time that there is an original street whose score value is greater than the preset score threshold, the original street corresponding to the current score value greater than the preset score threshold is set as the target street, and there are multiple target streets.

[0093] Furthermore, the step of performing secondary screening on the target streets based on the second preset rule to select the optimal street includes:

[0094] When a number of target streets are acquired in real time, a sorting is performed according to the size of the primary score value of each target street to generate a corresponding first sequence table;

[0095] The number of fuel vehicles and electric vehicles passing through each of the target streets is detected in real time by the collection device within the preset time period;

[0096] The optimal street is selected based on the first sequence table according to the number of fuel vehicles and the number of electric vehicles.

[0097] Furthermore, the step of selecting the optimal street according to the number of fuel vehicles and the number of electric vehicles based on the first sequence table includes:

[0098] When the number of fuel vehicles and the number of electric vehicles corresponding to each of the target streets are obtained in real time, a target ratio between the number of fuel vehicles and the number of electric vehicles is calculated in real time;

[0099] The target ratio is set to a vehicle type coefficient that matches the target street, and the optimal street is selected based on the vehicle type coefficient and the first sequence table.

[0100] Furthermore, the step of selecting the optimal street according to the vehicle type coefficient and the first sequence table includes:

[0101] When the vehicle type coefficient corresponding to each of the target streets is obtained respectively, the vehicle type coefficient of each target street in the first sequence table and the corresponding primary score value are cumulatively multiplied to calculate the secondary score value corresponding to each of the target streets in real time;

[0102] A plurality of target streets are secondary sorted according to the size of each secondary scoring value to generate a corresponding second sequence list in real time, and the first street in the second sequence list is correspondingly set as the optimal street.

[0103] In addition, in the present embodiment, it is also necessary to explain that after a number of original streets are acquired in real time through the above steps, it is necessary to immediately perform a deeper level of processing on the current original streets. In order to be able to objectively and accurately judge the importance of each current original street in the current target area, it is necessary to perform corresponding analysis at the geographical level and the vehicle level. Preferably, the present invention will first detect the geographic center of the current target area. Based on this, the current geographic center can be used as the basis for calculation, and the target distance between each current original street and the current geographic center can be further detected. At the same time, the geographic coefficient corresponding to each current original street can be directly matched in real time in a pre-set database according to the size of each current target distance. Based on this, in order to be able to objectively and accurately evaluate a corresponding score for each current original street, so as to facilitate subsequent comparison, preferably, the present invention will further collect the number of vehicles passing through each original street in real time within a week through the camera set on each original street. Similarly, the vehicle flow coefficient corresponding to each current original street can be matched in real time in the above preset database according to the number of vehicles corresponding to each current original street. Based on this, the geographical coefficient and the vehicle flow coefficient of each current original street can be directly accumulated, and the target coefficient corresponding to each current original street can be generated synchronously. Further, the target coefficient of each current original street and the target distance corresponding to it are accumulated, so that the primary score value corresponding to each current original street can be further calculated. On this basis, it is judged in real time whether the primary score value of each current original street is greater than the preset score threshold. Specifically, if yes, it corresponds to the fact that the importance of the current original street is high and needs to be further screened. If not, it corresponds to the fact that the importance is low and the corresponding deletion is performed. In the above manner, a number of required target streets can be screened out accordingly for subsequent processing.

[0104] Furthermore, after obtaining several required target streets through the above steps, since each current target street has a corresponding primary scoring value, based on this, a corresponding primary sorting can be performed directly according to the size of each current primary scoring value relative to each other, and a corresponding first sequence table can be generated. In addition, it should be pointed out that since the existing charging stations are only for the existing new energy electric vehicles, based on this, the number of new energy electric vehicles also determines the location of the charging station. Based on this, the present invention will further collect the number of fuel vehicles and electric vehicles passing through each target street in real time within a week through the camera inside each target street. Further, at this time, the target ratio between the current number of fuel vehicles and the current number of electric vehicles will be further calculated. Correspondingly, the current target ratio can be directly set to the vehicle model coefficient adapted to the current target street. Furthermore, within the above-mentioned first sequence table, the vehicle model coefficient of each target street and the corresponding primary score value are sequentially multiplied, and the secondary score value corresponding to each current target street can be further calculated. On this basis, it is only necessary to perform a corresponding secondary sorting on each current secondary score value to further generate a second sequence table corresponding to several current target streets. Based on this, the first place in the current second sequence table can be directly set as the required optimal street, so that the charging station setting location that meets the requirements can be objectively and accurately selected, which correspondingly improves the user's usage efficiency.

[0105] See also Figure 2 , the third embodiment of the present invention provides:

[0106] A charging station site selection system, wherein the system comprises:

[0107] A detection module, used to receive a target area input by a user in real time, and detect a regional map corresponding to the target area in a preset map database in real time;

[0108] A scanning module, used for performing a full scan on the regional map to detect a number of original streets contained in the target area, and adding a corresponding target mark to each of the original streets;

[0109] A first screening module, used for screening the plurality of original streets according to the target identifier based on a first preset rule, so as to screen out a plurality of target streets accordingly;

[0110] The second screening module is used to perform secondary screening on the target streets based on the second preset rule to select the optimal street and set up corresponding charging stations inside the optimal street, and each target identifier is unique.

[0111] Furthermore, the first screening module is specifically used for:

[0112] When a number of the original streets are detected in real time, the geographical center corresponding to the target area is detected in real time;

[0113] Detecting the target distance between each original street and the geographic center in real time, and matching the geographic coefficient corresponding to each original street in a preset database in real time according to the size of each target distance;

[0114] A plurality of the original streets are screened based on the target distance and the geographic coefficient to correspondingly screen out a plurality of the target streets.

[0115] Furthermore, the first screening module is specifically used for:

[0116] The number of vehicles passing through each of the original streets is obtained by a collection device within a preset time period, and the vehicle flow coefficient corresponding to each of the original streets is matched in real time in the preset database according to the size of each of the number of vehicles;

[0117] The traffic flow coefficient and the geographic coefficient are cumulatively processed to generate a corresponding target coefficient in real time, and the target distance of each original street and the target coefficient corresponding thereto are cumulatively processed to calculate a primary score value corresponding to each original street;

[0118] In real time, a number of target streets are correspondingly selected from the number of original streets according to the primary scoring value.

[0119] Furthermore, the first screening module is specifically used for:

[0120] When the primary score value of each of the original streets is obtained respectively, it is determined in real time whether the primary score value of each of the original streets is greater than a preset score threshold;

[0121] If it is determined in real time that there is an original street whose score value is greater than the preset score threshold, the original street corresponding to the current score value greater than the preset score threshold is set as the target street, and there are multiple target streets.

[0122] Furthermore, the second screening module is specifically used for:

[0123] When a number of target streets are acquired in real time, a sorting is performed according to the size of the primary score value of each target street to generate a corresponding first sequence table;

[0124] The number of fuel vehicles and electric vehicles passing through each of the target streets is detected in real time by the collection device within the preset time period;

[0125] The optimal street is selected based on the first sequence table according to the number of fuel vehicles and the number of electric vehicles.

[0126] Furthermore, the second screening module is specifically used for:

[0127] When the number of fuel vehicles and the number of electric vehicles corresponding to each of the target streets are obtained in real time, a target ratio between the number of fuel vehicles and the number of electric vehicles is calculated in real time;

[0128] The target ratio is set to a vehicle type coefficient that matches the target street, and the optimal street is selected based on the vehicle type coefficient and the first sequence table.

[0129] Furthermore, the second screening module is specifically used for:

[0130] When the vehicle type coefficient corresponding to each of the target streets is obtained respectively, the vehicle type coefficient of each target street in the first sequence table and the corresponding primary score value are cumulatively multiplied to calculate the secondary score value corresponding to each of the target streets in real time;

[0131] A plurality of target streets are secondary sorted according to the size of each secondary scoring value to generate a corresponding second sequence list in real time, and the first street in the second sequence list is correspondingly set as the optimal street.

[0132] A fourth embodiment of the present invention provides a computer, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the charging station site selection method as described above when executing the computer program.

[0133] A fifth embodiment of the present invention provides a readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the charging station site selection method as described above is implemented.

[0134] In summary, the charging station site selection method and system provided in the above embodiments of the present invention can objectively and accurately select a location that meets the requirements, thereby correspondingly improving the utilization efficiency of the charging station and improving the user experience.

[0135] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0136] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0137] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0138] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0139] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0140] The above-described embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the attached claims.

Claims

1. A method for selecting a charging station site, characterized in that: The method comprises: Receiving a target area input by a user in real time, and detecting a regional map corresponding to the target area in a preset map database in real time; Performing a full scan on the regional map to detect a number of original streets contained in the target area, and adding a corresponding target mark to each of the original streets; Based on the first preset rule, a plurality of the original streets are screened according to the target identifier to select a plurality of target streets accordingly; Based on the second preset rule, a second screening is performed on the target streets to select the optimal street, and a corresponding charging station is set inside the optimal street, and each target identifier is unique.

2. The method for selecting a charging station site according to claim 1, characterized in that: The step of screening the plurality of original streets according to the target identifier based on the first preset rule to correspondingly screen out a plurality of target streets comprises: When a number of the original streets are detected in real time, the geographical center corresponding to the target area is detected in real time; Detecting the target distance between each original street and the geographic center in real time, and matching the geographic coefficient corresponding to each original street in a preset database in real time according to the size of each target distance; A plurality of the original streets are screened based on the target distance and the geographic coefficient to correspondingly screen out a plurality of the target streets.

3. The method for selecting a charging station site according to claim 2, characterized in that: The step of screening the plurality of original streets based on the target distance and the geographic coefficient to correspondingly screen out the plurality of target streets comprises: The number of vehicles passing through each of the original streets is obtained by a collection device within a preset time period, and the vehicle flow coefficient corresponding to each of the original streets is matched in real time in the preset database according to the size of each of the number of vehicles; The traffic flow coefficient and the geographic coefficient are cumulatively processed to generate a corresponding target coefficient in real time, and the target distance of each original street and the target coefficient corresponding thereto are cumulatively processed to calculate a primary score value corresponding to each original street; In real time, a number of target streets are correspondingly selected from the number of original streets according to the primary scoring value.

4. The method for selecting a charging station site according to claim 3, characterized in that: The step of selecting a plurality of target streets from the plurality of original streets in real time according to the primary scoring value comprises: When the primary score value of each of the original streets is obtained respectively, it is determined in real time whether the primary score value of each of the original streets is greater than a preset score threshold; If it is determined in real time that there is an original street whose score value is greater than the preset score threshold, the original street corresponding to the current score value greater than the preset score threshold is set as the target street, and there are multiple target streets.

5. The method for selecting a charging station site according to claim 4, characterized in that: The step of performing secondary screening on the target streets based on the second preset rule to select the optimal street comprises: When a number of target streets are acquired in real time, a sorting is performed according to the size of the primary score value of each target street to generate a corresponding first sequence table; The number of fuel vehicles and electric vehicles passing through each of the target streets is detected in real time by the collection device within the preset time period; The optimal street is selected based on the first sequence table according to the number of fuel vehicles and the number of electric vehicles.

6. The method for selecting a charging station site according to claim 5, characterized in that: The step of selecting the optimal street based on the first sequence table according to the number of fuel vehicles and the number of electric vehicles comprises: When the number of fuel vehicles and the number of electric vehicles corresponding to each of the target streets are obtained in real time, a target ratio between the number of fuel vehicles and the number of electric vehicles is calculated in real time; The target ratio is set to a vehicle type coefficient that matches the target street, and the optimal street is selected based on the vehicle type coefficient and the first sequence table.

7. The method for selecting a charging station site according to claim 6, characterized in that: The step of selecting the optimal street according to the vehicle type coefficient and the first sequence table includes: When the vehicle type coefficient corresponding to each of the target streets is obtained respectively, the vehicle type coefficient of each target street in the first sequence table and the corresponding primary score value are cumulatively multiplied to calculate the secondary score value corresponding to each of the target streets in real time; A plurality of target streets are secondary sorted according to the size of each secondary scoring value to generate a corresponding second sequence list in real time, and the first street in the second sequence list is correspondingly set as the optimal street.

8. A charging station site selection system, characterized in that: The system comprises: A detection module, used to receive a target area input by a user in real time, and detect a regional map corresponding to the target area in a preset map database in real time; A scanning module, used for performing a full scan on the regional map to detect a number of original streets contained in the target area, and adding a corresponding target mark to each of the original streets; A first screening module, used for screening the plurality of original streets according to the target identifier based on a first preset rule, so as to screen out a plurality of target streets accordingly; The second screening module is used to perform secondary screening on the target streets based on the second preset rule to select the optimal street and set up corresponding charging stations inside the optimal street, and each target identifier is unique.

9. A computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the charging station site selection method according to any one of claims 1 to 7 is implemented.

10. A readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the charging station site selection method as described in any one of claims 1 to 7 is implemented.

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