CN111209493A - Charging station recommendation method, device, equipment and medium - Google Patents
Charging station recommendation method, device, equipment and medium Download PDFInfo
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- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/12—Electric charging stations
Abstract
The invention discloses a charging station recommendation method, relates to the technical field of electric vehicle charging, and aims to solve the problem that the user experience is poor due to the fact that the charging station is recommended in a single dimension mode in the prior art, and the method comprises the following steps: acquiring current position information of a user; screening charging stations in a preset geographical range according to the current position information of a user, and screening the use states of the charging stations in the preset geographical range to obtain an optional charging station list; carrying out multi-dimensional scoring on the charging stations in the selectable charging station list according to preset conditions; and recommending the charging station with the highest score to the user according to the scoring result. The invention also discloses a charging station recommendation device, electronic equipment and a computer storage medium. According to the invention, the charging station is subjected to multi-dimensional scoring, so that the most suitable charging station is recommended for the user.
Description
Technical Field
The invention relates to the technical field of electric vehicle charging, in particular to a charging station recommendation method, device, equipment and medium.
Background
More and more people recently select the electric new energy automobile as a travel tool; even for environmental protection purposes, fuel vehicle sale prohibition schedules have been introduced by some countries. With more and more electric new energy automobiles, charging stations for charging the electric new energy automobiles are increased.
At present, a plurality of APPs for helping car owners to search charging piles or charging stations are provided, the APP recommended charging piles are recommended to the charging stations based on single dimensionality, for example, the charging stations with the shortest distance are recommended based on linear distance, however, the user experience is poor in the recommendation mode of the single dimensionality, and after the user arrives at the charging stations according to the recommendation, the problems that the charging stations are closed, the cost is too high, or the user needs to queue up and the like are often encountered.
Disclosure of Invention
In order to overcome the defects of the prior art, one of the objectives of the present invention is to provide a charging station recommendation method, which performs multidimensional scoring on charging stations, so as to recommend the most suitable charging station to the user.
One of the purposes of the invention is realized by adopting the following technical scheme:
a charging station recommendation method comprises the following steps:
acquiring current position information of a user;
screening charging stations in a preset geographical range according to the current position information of a user, and screening the use states of the charging stations in the preset geographical range to obtain an optional charging station list;
carrying out multi-dimensional scoring on the charging stations in the selectable charging station list according to preset conditions;
and recommending the charging station with the highest score to the user according to the scoring result.
Further, the preset geographic range is a geographic area with the current position of the user as a center of a circle and a radius of 30 kilometers.
Further, the method for screening the use states of the charging stations in the preset geographic range to obtain an optional charging station list comprises the following steps:
and filtering the charging stations meeting the filtering conditions according to the use states of the charging stations in the preset geographic range to obtain the optional charging station list, wherein the filtering conditions comprise suspended service, no available charging pile and no available parking space.
Further, the preset conditions comprise a linear distance from the current position of the user to the charging station, an available charging pile density, a parking fee of the charging station, charging information and a path.
Further, according to preset conditions, performing multidimensional scoring on the charging stations in the selectable charging station list, and adding the scores of each dimension to obtain a scoring result, wherein the multidimensional scoring comprises the following steps:
sequentially calculating the linear distances between the charging stations in the selectable charging station list and the current position of the user, sequencing the linear distances in an ascending order, and adding the top N charging stations;
sorting the available charging pile densities of the charging stations in the selectable charging station list in a descending order, and adding scores to the top N charging stations;
sorting the parking fees of the charging stations in the selectable charging station list in an ascending order, and adding points to 5 charging stations with the lowest parking fee and no parking fee;
sorting the charging fees of the charging stations in the selectable charging station list in an ascending order, and adding points to the 5 charging stations with the lowest charging fees;
and obtaining a path plan from the current position of the user to the charging station and the license plate number of the user, and subtracting the charging station of which the path plan passes through the congestion area or the restricted area.
Further, according to the scoring result, recommending the charging station with the highest score to the user, and further comprising the following steps:
judging whether the charging station with the highest score in the same time period is a recommended charging station of other users;
when the charging station with the highest score is not the recommended charging station of other users, or when the charging station with the highest score is the recommended charging station of other users and the number of the idle charging piles is larger than the number of the recommended users, directly recommending the charging station with the highest score to the users;
when the charging station with the highest score is a recommended charging station of other users and the number of the idle charging piles is smaller than the number of the recommended users, the scores of the charging station with the highest score for all the recommended users are arranged in a descending order, and the idle charging piles are matched for all the recommended users in sequence from high to low according to the scores until all the idle charging piles are successfully matched; and when the user does not match the idle charging pile of the charging station with the highest score, recommending the charging station with the second score to the user.
Further, after recommending the charging station with the highest score to the user, the method further comprises the following steps:
receiving the charging station selected by the user;
locking an idle charging pile in the charging station for the user;
and when the user starts charging or is locked for more than preset time, unlocking.
Another object of the present invention is to provide a charging station recommendation apparatus, which can recommend an optimal charging station to a user by performing multidimensional scoring on the charging stations.
The second purpose of the invention is realized by adopting the following technical scheme:
a charging station recommendation device, comprising:
the acquisition module is used for acquiring the current position information of the user;
the filtering module is used for screening the charging stations in a preset geographic range according to the current position information of the user, and screening the use states of the charging stations in the preset geographic range to obtain an optional charging station list;
the scoring module is used for carrying out multi-dimensional scoring on the charging stations in the selectable charging station list according to preset conditions;
and the pushing module is used for recommending the charging station with the highest score to the user according to the scoring result.
It is a further object of the present invention to provide an electronic device for performing one of the above objects, comprising a processor, a storage medium, and a computer program stored in the storage medium, wherein the computer program, when executed by the processor, implements the above-mentioned charging station recommendation method.
It is a fourth object of the present invention to provide a computer-readable storage medium storing one of the objects of the invention, having a computer program stored thereon, which when executed by a processor, implements the above-described charging station recommendation method.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, the charging stations are screened according to the use states of the charging stations, the charging stations are subjected to multi-dimensional grading, the charging station with the highest grading is recommended to the user, the most suitable charging station is provided for the user through the multi-dimensional grading, the user experience is improved, and the operation cost of the charging station is reduced.
Drawings
Fig. 1 is a flowchart of a charging station recommendation method according to a first embodiment;
fig. 2 is a flowchart of a charging station scoring method according to the first embodiment;
fig. 3 is a flowchart of a charging station recommendation method according to the second embodiment;
FIG. 4 is a flowchart of a locking method of a charging station according to the second embodiment;
fig. 5 is a block diagram showing a configuration of a charging station recommendation device according to a third embodiment;
fig. 6 is a block diagram of the electronic apparatus according to the fourth embodiment.
Detailed Description
The present invention will now be described in more detail with reference to the accompanying drawings, in which the description of the invention is given by way of illustration and not of limitation. The various embodiments may be combined with each other to form other embodiments not shown in the following description.
Example one
The embodiment I provides a charging station recommendation method, which aims to screen charging stations within a certain range and evaluate the charging stations through a plurality of conditions so as to provide the most appropriate charging stations for users.
In the embodiment, the charging station recommendation service is mainly provided for the user through the mobile phone Web webpage or the mobile phone APP, the information of the charging station is stored in the server executing the method in advance, and the use conditions of the charging station, such as the condition of an idle charging pile, the condition of an idle parking space and the like, are updated in real time.
Referring to fig. 1, a method for recommending a charging station is characterized by comprising the following steps:
s110, acquiring current position information of a user;
the current location information of the user in S110 is obtained by calling an API interface of the third-party map, such as a Baidu map, a Gade map, and the like.
S120, screening charging stations in a preset geographic range according to the current position information of the user, and screening the use states of the charging stations in the preset geographic range to obtain an optional charging station list;
the preset geographic range in this embodiment is a circular range formed by taking the current position of the user as a circle center and a radius of 30 kilometers, and the charging stations included in the circle form a selectable charging station list. Of course, the preset geographical range may also be set according to the actual situation of the urban charging station, and when there are fewer charging stations, the preset geographical range may be appropriately increased, otherwise the preset geographical range may be appropriately decreased.
In S120, the charging stations in the preset geographic range are screened for use states to obtain a selectable charging station list, and the method further includes the following steps:
and filtering the charging stations meeting the filtering conditions according to the use states of the charging stations in the preset geographic range to obtain the optional charging station list, wherein the filtering conditions comprise suspended service, no available charging pile and no available parking space.
The filtering described above is performed according to the usage status of the charging station, in order to filter out unusable charging stations. The suspended service comprises charging stations which are not in business hours and are temporarily closed, the unavailable charging piles comprise charging stations which are not available or have faults, and the available parking spaces refer to parking spaces of the charging stations.
S130, carrying out multi-dimensional scoring on the charging stations in the selectable charging station list according to preset conditions;
in this embodiment, the preset conditions include a linear distance from the current location of the user to the charging station, an available charging pile density, a parking fee of the charging station, charging charge information, and a path. Of course, the preset conditions can be increased according to actual conditions.
Referring to fig. 2, according to a preset condition, performing multidimensional scoring on charging stations in the selectable charging station list, and adding the scores of each dimension to obtain the scoring result, where the multidimensional scoring includes the following steps:
s1301, calculating the linear distances between the charging stations in the optional charging station list and the current position of the user in sequence, sequencing the linear distances in an ascending order, and adding the charging stations sequenced in the first N times;
in this embodiment, N is 10, and 10 stations closest to the charging station in a straight line distance from the current position of the user are added with a score of 2. The purpose of S1301 is to preferentially recommend a charging station with a short distance. The straight-line distance calculation method in S1301 may be acquired by calling a third-party map API, or may directly calculate the straight-line distance thereof through longitude and latitude, and the specific calculation method is not limited in this embodiment.
S1302, sorting the available charging pile densities of the charging stations in the selectable charging station list in descending order, and adding the top N charging stations in the sorting order;
the scoring score of the step S1302 is 2 points, and the density refers to the number of available charging piles of the current station. The purpose of S1302 is to preferentially select a station that currently has a plurality of available charging piles.
S1303, sequencing the parking fees of the charging stations in the selectable charging station list in an ascending order, and adding points to 5 charging stations with the lowest parking fees and no parking fees;
the server for scoring stores the parking fee price of the charging station in advance, and the parking fee bonus rule in this embodiment is as follows: and adding 1 point to the free stations, sequencing the paid stations in a descending order according to the parking cost, and adding 1 point to the paid stations ranked in the top five. The purpose of S1303 is to preferentially select a parking-free charging station or a charging station with a low parking fee.
S1304, sorting the charging fees of the charging stations in the selectable charging station list in an ascending order, and adding points to the 5 charging stations with the lowest charging fees;
the server that performs the scoring process stores the charging fee price of the charging station in advance. The charging fee adding rule in the embodiment is as follows: and (4) sequencing the charging stations in an ascending order according to the charging cost, and adding 1 to the charging station 5 at the top. The purpose of S1304 is to preferentially select a charging station with a low charging fee.
S1305, obtaining a path plan from the current position of the user to a charging station and the license plate number of the user, and subtracting the charging station of which the path plan passes through a congestion area or a restricted area;
in S1305, the path planning is obtained by calling an API of a third-party map, where the third-party map is an application program having functions of path planning and real-time traffic detection, such as a Baidu map and a Gaode map. The license plate number of the user is usually the license plate number input by the user during registration, and can also send a license plate number request to the user side and receive the license plate number information returned by the user. The division reduction rule is that 1 division is reduced for charging stations which pass through a congested area in the path planning, and 1 division is reduced for charging stations which pass through a restricted area. The purpose of S1305 is to reduce the length of time for traveling on the road and improve efficiency.
And S140, recommending the charging station with the highest score to the user according to the scoring result.
It should be noted that, when actually scoring, the scoring rule described in this embodiment is not limited, and different scoring rules may be set, for example, different points are added according to the ranking, and one more point is added to the charging station in the first ranking.
Example two
The second embodiment is performed on the basis of the first embodiment, and mainly explains and explains the situation when the same charging station is recommended to a plurality of users at the same time.
Referring to fig. 3, recommending the charging station with the highest score to the user according to the scoring result, further includes the following steps:
s210, judging whether the charging station with the highest score in the same time period is a recommended charging station of other users;
the same time period of S210 may be set according to actual conditions, and this embodiment is not particularly limited.
S220, when the charging station with the highest score is not a recommended charging station of other users, or when the charging station with the highest score is a recommended charging station of other users and the number of idle charging piles is larger than the number of recommended users, directly recommending the charging station with the highest score to the users;
when the number of the recommended idle charging piles at the charging station is large, the charging station can be continuously used as the recommended charging piles of other users without the determination step of the step S230.
S230, when the charging station with the highest score is a recommended charging station of other users and the number of the idle charging piles is smaller than the number of recommended users, the scores of the charging station with the highest score on all the recommended users are arranged in a descending order, and the idle charging piles are matched for all the recommended users in sequence from high to low according to the scores until all the idle charging piles are successfully matched; and when the user does not match the idle charging pile of the charging station with the highest score, recommending the charging station with the second score to the user.
The charging station in S230 is recommended to a plurality of users at the same time, but since information of each user, such as a number plate, a location where the user is located, and the like, is different, scores of different users by the same charging station are also different, and therefore, by comparing scores of the charging station for the users, it is preferable to match an idle charging pile to a user with a high score.
For the unmatched users, the charging station with the second score is recommended to the corresponding user, and of course, the related steps from S210 to S230 need to be executed before recommendation, so as to prevent the problem that the charging station with the second score is also recommended to multiple people at the same time to cause queuing.
In order to prevent the charging pile from being occupied, the charging pile is further locked in this embodiment, specifically, referring to fig. 4, the method includes the following steps:
s310, receiving the charging station selected by the user;
s320, locking an idle charging pile in the charging station for the user;
and S330, when the user starts charging or locks for more than preset time, unlocking.
After receiving an instruction of selecting a charging station by a user, the server sends a locking message to the charging station, and the charging station completes locking of a charging pile. The preset time in S330 is 15 minutes in this embodiment, and may be set according to actual conditions in actual operation.
EXAMPLE III
An embodiment three discloses a device corresponding to the charging station recommendation method in the foregoing embodiment, which is a virtual device structure in the foregoing embodiment, and as shown in fig. 5, the device includes:
an obtaining module 410, configured to obtain current location information of a user;
the filtering module 420 is configured to screen charging stations within a preset geographic range according to the current location information of the user, and screen the use states of the charging stations within the preset geographic range to obtain an optional charging station list;
the scoring module 430 is configured to perform multidimensional scoring on the charging stations in the selectable charging station list according to a preset condition;
and the pushing module 440 is configured to recommend the charging station with the highest score to the user according to the scoring result.
Preferably, the preset conditions include a linear distance from the current position of the user to the charging station, an available charging pile density, a parking fee of the charging station, charging information and a path.
Example four
Fig. 6 is a schematic structural diagram of an electronic apparatus according to a fourth embodiment of the present invention, as shown in fig. 6, the electronic apparatus includes a processor 510, a memory 520, an input device 530, and an output device 540; the number of the processors 510 in the computer device may be one or more, and one processor 510 is taken as an example in fig. 6; the processor 510, the memory 520, the input device 530 and the output device 540 in the electronic apparatus may be connected by a bus or other means, and the connection by the bus is exemplified in fig. 6.
The memory 520 is a computer-readable storage medium, and can be used to store software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the charging station recommendation method in the embodiment of the present invention (for example, the obtaining module 410, the filtering module 420, the scoring module 430, and the pushing module 430 in the charging station recommendation method apparatus). The processor 510 executes various functional applications and data processing of the electronic device by running the software programs, instructions and modules stored in the memory 520, so as to implement the charging station recommendation methods of the first and second embodiments.
The memory 520 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the memory 520 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, memory 520 may further include memory located remotely from processor 510, which may be connected to an electronic device through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 530 may be used to receive input of user identity information, user location information, and the like. The output device 540 may include a display device such as a display screen.
EXAMPLE five
An embodiment of the present invention further provides a storage medium containing computer-executable instructions, where the storage medium may be used for a computer to execute a charging station recommendation method, where the method includes:
acquiring current position information of a user;
screening charging stations in a preset geographical range according to the current position information of a user, and screening the use states of the charging stations in the preset geographical range to obtain an optional charging station list;
carrying out multi-dimensional scoring on the charging stations in the selectable charging station list according to preset conditions;
and recommending the charging station with the highest score to the user according to the scoring result.
Of course, the storage medium containing the computer-executable instructions provided by the embodiments of the present invention is not limited to the method operations described above, and may also perform related operations in the charging station recommendation method provided by any embodiments of the present invention.
From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes instructions for enabling an electronic device (which may be a mobile phone, a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.
It should be noted that, in the embodiment of the charging station recommendation method-based device, the included units and modules are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
Various other modifications and changes may be made by those skilled in the art based on the above-described technical solutions and concepts, and all such modifications and changes should fall within the scope of the claims of the present invention.
Claims (10)
1. A charging station recommendation method is characterized by comprising the following steps:
acquiring current position information of a user;
screening charging stations in a preset geographical range according to the current position information of a user, and screening the use states of the charging stations in the preset geographical range to obtain an optional charging station list;
carrying out multi-dimensional scoring on the charging stations in the selectable charging station list according to preset conditions;
and recommending the charging station with the highest score to the user according to the scoring result.
2. The charging station recommendation method according to claim 1, wherein the preset geographic range is a geographic area with a radius of 30 km and a current position of a user as a center.
3. The charging station recommendation method according to claim 1 or 2, wherein the step of screening the use states of the charging stations within the preset geographic range to obtain the selectable charging station list comprises the following steps:
and filtering the charging stations meeting the filtering conditions according to the use states of the charging stations in the preset geographic range to obtain the optional charging station list, wherein the filtering conditions comprise suspended service, no available charging pile and no available parking space.
4. The charging station recommendation method according to claim 1, wherein the preset conditions include a linear distance from a current location of a user to a charging station, an available charging pile density, a parking fee of the charging station, charging charge information and a path.
5. The charging station recommendation method according to claim 4, wherein the charging stations in the selectable charging station list are subjected to multi-dimensional scoring according to preset conditions, and the scoring of each dimension is added to obtain the scoring result, and the multi-dimensional scoring comprises the following steps:
sequentially calculating the linear distances between the charging stations in the selectable charging station list and the current position of the user, sequencing the linear distances in an ascending order, and adding the top N charging stations;
sorting the available charging pile densities of the charging stations in the selectable charging station list in a descending order, and adding scores to the top N charging stations;
sorting the parking fees of the charging stations in the selectable charging station list in an ascending order, and adding points to 5 charging stations with the lowest parking fee and no parking fee;
sorting the charging fees of the charging stations in the selectable charging station list in an ascending order, and adding points to the 5 charging stations with the lowest charging fees;
and obtaining a path plan from the current position of the user to the charging station and the license plate number of the user, and subtracting the charging station of which the path plan passes through the congestion area or the restricted area.
6. The charging station recommendation method according to claim 1 or 5, wherein the charging station with the highest score is recommended to the user according to the scoring result, further comprising the steps of:
judging whether the charging station with the highest score in the same time period is a recommended charging station of other users;
when the charging station with the highest score is not the recommended charging station of other users, or when the charging station with the highest score is the recommended charging station of other users and the number of the idle charging piles is larger than the number of the recommended users, directly recommending the charging station with the highest score to the users;
when the charging station with the highest score is a recommended charging station of other users and the number of the idle charging piles is smaller than the number of the recommended users, the scores of the charging station with the highest score for all the recommended users are arranged in a descending order, and the idle charging piles are matched for all the recommended users in sequence from high to low according to the scores until all the idle charging piles are successfully matched; and when the user does not match the idle charging pile of the charging station with the highest score, recommending the charging station with the second score to the user.
7. The charging station recommendation method according to claim 6, wherein after recommending the highest scoring charging station to the user, further comprising the steps of:
receiving the charging station selected by the user;
locking an idle charging pile in the charging station for the user;
and when the user starts charging or is locked for more than preset time, unlocking.
8. A charging station recommendation device, comprising:
the acquisition module is used for acquiring the current position information of the user;
the filtering module is used for screening the charging stations in a preset geographic range according to the current position information of the user, and screening the use states of the charging stations in the preset geographic range to obtain an optional charging station list;
the scoring module is used for carrying out multi-dimensional scoring on the charging stations in the selectable charging station list according to preset conditions;
and the pushing module is used for recommending the charging station with the highest score to the user according to the scoring result.
9. An electronic device comprising a processor, a storage medium, and a computer program stored in the storage medium, wherein the computer program, when executed by the processor, implements the charging station recommendation method of any of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out a charging station recommendation method according to any one of claims 1 to 7.
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| CN112749343A (en) * | 2021-01-22 | 2021-05-04 | 武汉蔚来能源有限公司 | Resource recommendation method and device and computer storage medium |
| CN114516278A (en) * | 2020-11-18 | 2022-05-20 | 比亚迪股份有限公司 | Charging pile recommendation method, device, system and storage medium |
| CN115374236A (en) * | 2022-10-26 | 2022-11-22 | 北京宾理信息科技有限公司 | Method, device, equipment and medium for generating intelligent public charging service network |
| CN115482681A (en) * | 2021-05-31 | 2022-12-16 | 博泰车联网科技(上海)股份有限公司 | Method for assisting in planning a route for a vehicle, and computer storage medium |
| CN117556971A (en) * | 2023-11-02 | 2024-02-13 | 江苏智融能源科技有限公司 | Ordered charging recommendation system and method based on artificial intelligence |
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