CN114954129A - Charging station information recommendation method and device, electronic terminal and storage medium - Google Patents
Charging station information recommendation method and device, electronic terminal and storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a method and a device for recommending charging station information, an electronic terminal and a storage medium, wherein the method comprises the following steps: determining a first time and a first remaining capacity for the current vehicle to travel to each charging station matched with the travel route in response to a recommendation request input by a user; acquiring charging queuing information of each charging station at the first time from a cloud server; and sequencing the charging stations according to the first residual electric quantity and the charging queuing information, and recommending charging station information according to a sequencing result. According to the technical scheme of the embodiment of the invention, a reasonable travel charging suggestion can be provided by integrating various factors, and the charging experience of a user can be improved.
Description
Technical Field
The embodiment of the invention relates to vehicle technologies, in particular to a method and a device for recommending charging station information, an electronic terminal and a storage medium.
Background
A charging station may be considered as a power station that provides a charging service for a power battery of an electric vehicle (may be referred to as an electric car). In the prior art, only the charging station information closest to the trolley bus is recommended and displayed in the process of trolley bus running. This kind of recommendation mode is comparatively single, can not satisfy user's stroke charge demand, leads to the user to charge and experiences relatively poorly.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for recommending charging station information, an electronic terminal, and a storage medium, which can provide a reasonable travel charging suggestion by integrating multiple factors, and can improve charging experience of a user.
In a first aspect, an embodiment of the present invention provides a method for recommending charging station information, which is applied to a vehicle terminal and includes:
determining a first time and a first remaining capacity for the current vehicle to travel to each charging station matched with the travel route in response to a recommendation request input by a user;
the method comprises the steps that charging queuing information of each charging station at the first time is obtained from a cloud server;
and sequencing the charging stations according to the first residual electric quantity and the charging queuing information, and recommending the charging station information according to the sequencing result.
In a second aspect, an embodiment of the present invention further provides a charging station information recommendation device, integrated in a vehicle terminal, including:
the first residual capacity matching module is used for responding to a recommendation request input by a user and determining first time and first residual capacity of the current vehicle when the current vehicle runs to each charging station matched with the travel route;
the charging queuing information acquisition module is used for acquiring charging queuing information of each charging station at the first time from the cloud server;
and the charging station information recommending module is used for sequencing all charging stations according to the first residual electric quantity and the charging queuing information and recommending the charging station information according to the sequencing result.
In a third aspect, an embodiment of the present invention further provides an electronic terminal, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor executes the computer program to implement the method for recommending charging station information according to any embodiment of the present application.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the method for recommending charging station information according to any embodiment of the present application.
The embodiment of the invention provides a method and a device for recommending charging station information, an electronic terminal and a storage medium, wherein the method for recommending the charging station information comprises the following steps: determining a first time and a first remaining capacity for the current vehicle to travel to each charging station matched with the travel route in response to a recommendation request input by a user; the method comprises the steps that charging queuing information of each charging station at the first time is obtained from a cloud server; and sequencing the charging stations according to the first residual electric quantity and the charging queuing information, and recommending the charging station information according to the sequencing result. According to the technical scheme of the embodiment of the invention, more reasonable travel charging suggestions are recommended by combining various factors such as travel routes, vehicle electric quantity consumption, charging station queuing conditions and the like, so that the driving charging requirements of users can be met, and the charging experience of the users is improved.
Drawings
Fig. 1 is a schematic flowchart illustrating a method for recommending charging station information according to an embodiment of the present invention;
fig. 2 is a schematic flowchart of a charging station information recommendation method according to a second embodiment of the present invention;
fig. 3 is a schematic flowchart of an alternative example of a charging station information recommendation method according to a second embodiment of the present invention;
fig. 4 is a schematic structural diagram of a charging station information recommendation device according to a third embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic terminal according to a fourth embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described through embodiments with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention. In the following embodiments, optional features and examples are provided in each embodiment, and various features described in the embodiments may be combined to form a plurality of alternatives, and each numbered embodiment should not be regarded as only one technical solution.
It is understood that before the technical solutions disclosed in the embodiments of the present invention are used, the type, the use range, the use scene, etc. of the personal information related to the present invention should be informed to the user and authorized by the user in a proper manner according to the relevant laws and regulations.
For example, in response to receiving an active request from a user, prompt information is sent to the user to explicitly prompt the user that the requested operation to be performed would require acquisition and use of personal information to the user (e.g., information about the user's electric train). Therefore, the user can select whether to provide personal information to the software or hardware such as electronic equipment, application program, server or storage medium for executing the operation of the technical scheme of the invention according to the prompt information.
It will be appreciated that the data involved in the subject technology, including but not limited to the data itself, the acquisition or use of the data, should comply with the requirements of the corresponding laws and regulations and related regulations.
Before the embodiment of the present invention is described, an application scenario of the embodiment of the present invention is exemplarily described: the tram user is consistently anxious with mileage, worrys about missing the charging station, does not want to queue up at the charging station again. The existing navigation system can only show the information of the nearest charging station to the user, and the user needs to judge whether to charge or not, or needs to plan the charging station in advance, so that if the users who plan the charging station for the user to charge happen are more, the charging stations queue more, the user route planning is disordered, and the route experience is influenced. The charging station information recommendation method provided by this embodiment can provide reasonable charging advice information by starting from the full-grid electric vehicle data and combining the charging station information, the navigation information, the state information of the vehicle itself, and the like, and can fully utilize the charging station resources and alleviate charging anxiety of the user. Specifically, the recommendation method of charging station information can be described with reference to the following embodiments.
Example one
Fig. 1 is a flowchart illustrating a charging station information recommendation method according to an embodiment of the present invention. The present embodiment is applicable to a case where a trip charging advice is dynamically recommended to an electric car. The method can be executed by the recommendation device of the charging station provided by the embodiment of the invention, the recommendation device can be implemented in a software and/or hardware manner, and can be configured in an electronic terminal, for example, a vehicle terminal.
Referring to fig. 1, the method for recommending charging station information provided in this embodiment is applied to a vehicle terminal, and may include:
and S110, responding to a recommendation request input by a user, and determining a first time and a first remaining capacity when the current vehicle runs to each charging station matched with the travel route.
The recommendation request may be understood as a request for indicating recommendation of charging station information. The current vehicle may be understood as a vehicle that the user is currently driving or riding. A trip route may be understood as a route that needs to be traveled between the current vehicle and the intended destination. Each charging station that is matched to a route of travel can be understood as a charging station that is located on or closer to the route of travel of the current vehicle. The first time can be understood as the time corresponding to the current vehicle traveling to each charging station. The first remaining capacity may be understood as a remaining capacity of the current vehicle after the current vehicle travels to each charging station.
The user may input a recommendation request on the vehicle terminal. For example, clicking a recommendation button on a system application in a vehicle terminal; alternatively, the recommendation button is clicked on a navigation application installed in the vehicle terminal. In the embodiment of the present invention, the vehicle terminal to which the user inputs the recommendation request is not limited at all.
The first time may be a time point or a time period. Specifically, the first time may be a specific time point when the current vehicle arrives at each charging station, or may be a time period in which the time when the current vehicle arrives at each charging station may be located.
The first remaining capacity may be an electric quantity value or a range of electric quantities. Specifically, the first remaining capacity may be a specific remaining capacity value of the current vehicle arriving at each charging station, or may be a range value of a capacity in which the remaining capacity of the current vehicle arriving at each charging station may be located.
Specifically, in response to a recommendation request input by a user on the vehicle terminal and requiring recommendation of charging station information, the vehicle terminal may determine a first time corresponding to a time when the current vehicle travels to each charging station located on the route of travel, and a first remaining capacity corresponding to a remaining capacity of the current vehicle after the current vehicle travels to each charging station.
And S120, acquiring charging queuing information of each charging station at the first time from the cloud server.
The cloud server can be understood as a simple, efficient, safe and reliable computing service with elastically stretchable processing capacity, and can be in communication connection with each vehicle terminal. The charging queuing information can be obtained by predicting the charging pile number of each charging station and the residual electric quantity of each vehicle reaching each charging station by the cloud server. Fill electric pile can be understood as being located the stake bolt that can charge current vehicle in the charging station, can have a plurality of electric piles of filling in a charging station. Each vehicle may include the current vehicle as well as other vehicles.
The vehicle terminal can request charging queuing information from the cloud server according to the first time when the vehicle terminal runs to each charging station matched with the travel route, so that the cloud server can predict the charging queuing information. The process of predicting the charging queue information by the cloud server includes, for example: according to the residual electric quantity of each vehicle reaching each charging station, the probability of each vehicle charging at the charging station can be predicted. According to the predicted probability of each vehicle charging at the charging station, the number of vehicles which possibly need to be charged in each charging station and the time length of the vehicles needing to be charged can be predicted. And comparing the number of the charging piles of the charging station with the predicted number of the vehicles which are possibly charged, and combining the time length of the vehicles needing to be charged to obtain charging queuing information. Wherein, the charging queue information may include: the number of the remaining charging piles of each charging station when no vehicle is queued for charging is calculated; the queuing number when the vehicles are queued, the expected queuing time and the like. The cloud server can feed back the charging queuing information of each charging station to the corresponding vehicle terminal after determining the charging queuing information of each charging station at the first time.
S130, sorting all charging stations according to the first residual electric quantity and the charging queuing information, and recommending charging station information according to a sorting result.
The sequencing result can be understood as a result of sequencing the charging stations. The charging station information may be understood as related information corresponding to each charging station, such as a name, address, etc. of the charging station.
Specifically, the vehicle terminal sorts the charging stations according to the first remaining electric quantity and the charging queuing information; and information such as names and addresses of the top N (such as 2, 3 and the like) recommended charging stations in the sequencing result can be recommended.
In addition, when the charging station information is recommended according to the sorting result, the information such as the first time, the first residual capacity and the charging queuing information at the first time of the recommended charging station can be displayed, so that a user can know more comprehensive driving and charging information, and the user experience is improved.
The recommendation method for the charging station information, provided by the embodiment of the invention, is used for responding to a recommendation request input by a user, and determining the first time and the first remaining capacity when a current vehicle runs to each charging station matched with a travel route; the method comprises the steps that charging queuing information of each charging station at the first time is obtained from a cloud server; and sequencing the charging stations according to the first residual electric quantity and the charging queuing information, and recommending the charging station information according to the sequencing result. According to the technical scheme of the embodiment of the invention, more reasonable travel charging suggestions are recommended by combining various factors such as travel routes, vehicle electric quantity consumption and charging station queuing conditions, so that the driving charging requirements of users can be met, and the charging experience of the users is improved.
An optional technical solution, sorting charging stations according to the first remaining power and the charging queue information, includes: and determining first target charging stations from the charging stations according to the first residual electric quantity, and sequencing the first target charging stations according to the charging queuing information of the first target charging stations at the corresponding first time.
The first target charging station may be understood as a charging station at which the current vehicle is more likely to be charged, and the number of the first target charging stations may be at least one. Determining a first target charging station from the charging stations according to the first remaining capacities may include: an electric quantity range may be preset, and if the first remaining electric quantity corresponding to the charging station is within the preset electric quantity range, it may be considered that the charging of the current vehicle at the charging station is more likely, and at this time, the charging station may be determined as the first target charging station. For example, T is the total electric quantity of the current vehicle, and the preset circuit range is [ T × 10%, T × 50% ]; when the first remaining capacity corresponding to the charging station a is within a range of [ T × 10%, T × 50% ], the charging station a may be determined as a first target charging station.
The sorting of the first target charging stations according to the charging queuing information of the first target charging station at the corresponding first time may include: and sequencing the first target charging stations according to the number of the remaining charging piles, the number of queued vehicles and the queuing time of the first target charging stations at the corresponding first time. Optionally, if there are charging stations in the first target charging station whose number of queuing people is less than the number of charging piles, the charging stations whose number of queuing people is less than the number of charging piles are preferentially sorted. And if the number of the queued charging stations is not less than that of the charging piles in the first target charging stations, preferentially sequencing the charging stations with the minimum number of the queued charging stations. This has the advantage that charging stations that save more time for the user can be preferentially recommended.
Another optional technical solution is that determining a first time and a first remaining capacity at which the current vehicle travels to each charging station matched with the travel route includes: and re-determining the first time and the first residual electric quantity when the current vehicle runs to each charging station matched with the travel route at preset time intervals.
The preset time period may be understood as a preset time length, for example, the preset time period may be ten minutes, twenty minutes, or the like. Optionally, the preset time duration may be preset by the vehicle terminal itself, or may be set by the user.
It should be noted that the route of the user is not constant, and other factors such as environment and road conditions may affect the first time and the first remaining capacity at any time. Accordingly, the charging queue information of each charging station at the corresponding first time also changes. Therefore, in the embodiment of the present invention, the first time and the first remaining capacity at which the current vehicle travels to each charging station matching the travel route may be newly determined every preset time period.
Correspondingly, the charging queuing information of each charging station at the new first time can be acquired from the cloud server at preset intervals. The cloud server can obtain at least one of the number of charging piles for the current vehicle to travel to each charging station on the travel route, the number of vehicles currently being charged at each charging station and the required residual charging time of the vehicles, the number of vehicles currently waiting to be charged at each charging station in a queuing mode and the residual electric quantity of each vehicle reaching each charging station, so as to predict and obtain charging queuing information. And feeding back the charging queuing information obtained by prediction to the vehicle terminal.
After receiving the new charging queuing information, the vehicle terminal can sort the charging stations according to the new first remaining capacity and the new charging pairing information. The charging station information is dynamically recommended according to the updated sequencing result of each charging station, so that the recommendation accuracy can be improved, and the user experience is improved.
In another optional technical solution, after recommending the charging station information according to the sorting result, the method may further include: and responding to a selection instruction input by a user, determining a second target charging station from the recommended charging station information, and uploading the first time when the current vehicle reaches the second target charging station and the first residual electric quantity to the cloud server so as to enable the cloud server to determine charging queuing information.
The selection command may be understood as a command for selecting a target charging station. The second target charging station may be understood as a charging station selected by the user in the recommended charging station information.
Specifically, the selection instruction in response to the user input may be, for example, an instruction in response to the user clicking on a recommended charging station. And determining a second target charging station selected by the user from the recommended charging station information, and uploading the first time and the first remaining capacity corresponding to the second target charging station of the current vehicle to the cloud server, so that the cloud server determines the charging queuing information corresponding to the second target charging station again.
The advantage of setting up like this is that can make the server update the queuing information of charging according to the target charging station of user's selection, provides the more accurate queuing information of charging of the charging station that probably wants to arrive for the user, improves user's experience.
Example two
The recommendation method for charging station information provided in this embodiment can be combined with each alternative in the recommendation method for charging station information provided in the above embodiment. The method for recommending charging station information according to this embodiment describes in detail a determination of a first time and a first remaining capacity at which a current vehicle travels to each charging station that matches a travel route. Obtaining travel related data of a current vehicle; the travel related data comprises the current residual capacity and the first distance of each charging station matched with the travel route; acquiring a first corresponding relation of current distance and consumed time and a second corresponding relation of current distance and power consumption; determining the first time when the current vehicle runs to each charging station according to each first distance and the first corresponding relation; and determining the first residual electric quantity of the current vehicle running to each charging station according to the current residual electric quantity, each first distance and the second corresponding relation. The first time and the first remaining capacity of each matched charging station can be more accurate.
Fig. 2 is a flowchart illustrating a charging station information recommendation method according to a second embodiment of the present invention. Referring to fig. 2, the method for recommending charging station information provided in this embodiment is applied to a vehicle terminal, and may include:
s210, responding to a recommendation request input by a user, and acquiring travel related data of the current vehicle; the trip-related data includes a current remaining capacity and a first distance of each charging station currently matching the trip route.
The travel-related data may include, but is not limited to, related data corresponding to the current vehicle state and data related to each charging station matching the travel route. The current remaining capacity may be understood as the capacity of the current vehicle remaining at the current time. The first distance may be understood as the distance of the current vehicle to the respective charging station at the current time.
Specifically, in response to a recommendation request input by a user, the vehicle terminal acquires travel related data such as the current remaining capacity of the current vehicle and distances from each charging station to the current vehicle, which are currently matched with the travel route.
S220, acquiring a first corresponding relation between the current distance and consumed time and a second corresponding relation between the current distance and consumed power.
The first current distance-elapsed time relationship is understood to be the relationship between the current distance of the vehicle from the charging station and the elapsed time required for the vehicle to travel the current distance. The second current distance-power consumption correspondence is understood to be the correspondence between the distance of the current vehicle from the charging station and the amount of power consumed to travel the current distance. It should be noted that the first corresponding relationship and the second corresponding relationship may be a preset mathematical formula or a logic model, or may be a logic formula or a logic model determined in real time, and in the embodiment of the present invention, the corresponding manner of the first corresponding relationship and the second corresponding relationship is not limited at all. Optionally, the vehicle terminal may obtain the first corresponding relationship and the second corresponding relationship from the cloud server, or may determine the first corresponding relationship and the second corresponding relationship by the vehicle terminal itself.
And S230, determining the first time when the current vehicle runs to each charging station according to each first distance and the first corresponding relation.
Specifically, the first corresponding relationship may be a corresponding relationship between a current distance and time consumption, and each first distance may be a current distance from the current vehicle to each charging station, so that time consumption for traveling to each first distance may be determined according to each first distance and the first corresponding relationship, and first time for the current vehicle to travel to each charging station may be determined according to a current time point and the time consumption of each first distance.
S240, determining the first residual electric quantity of the current vehicle running to each charging station according to the current residual electric quantity, each first distance and the second corresponding relation.
Specifically, since the second corresponding relationship may be a corresponding relationship between a current distance and power consumption, and each first distance may be a current distance from a current vehicle to each charging station, power consumption for running each first distance may be determined according to each first distance and the second corresponding relationship. And determining the first residual electric quantity of the current vehicle running to each charging station according to the current residual electric quantity and the electric power consumption amount of each first distance.
And S250, acquiring charging queue information of each charging station at the first time from the cloud server.
And S260, sequencing the charging stations according to the first residual electric quantity and the charging queuing information, and recommending charging station information according to a sequencing result.
According to the method for recommending the charging station information, the travel related data of the current vehicle are obtained, the first corresponding relation of the current distance and the consumed time and the second corresponding relation of the current distance and the consumed power are obtained, the first time when the current vehicle runs to each charging station is determined according to each first distance and each first corresponding relation, and finally the first remaining power when the current vehicle runs to each charging station is determined according to the current remaining power, each first distance and each second corresponding relation. Therefore, the first time and the first residual capacity of each matched charging station can be more accurate.
An optional technical solution is that the trip related data further includes at least one of the following: driving behavior data, road condition data currently matched with the travel route, and environment data currently matched with the travel route; accordingly, a first remaining capacity of the current vehicle to travel to each charging station is determined based on the following steps: and inputting the current residual electric quantity, each first distance, driving behavior data, road condition data and environment data into a machine learning model representing the second corresponding relation, and obtaining the first residual electric quantity of the current vehicle running to each charging station through the machine learning model.
It should be noted that, in practical applications, driving behaviors, road conditions, environments, and other factors of the user may all affect the first remaining power. Therefore, in order to prevent the first remaining capacity from being affected by other factors, so that the determined first remaining capacity is more accurate, the trip-related data may further include at least one of the following: driving behavior data, road condition data currently matched with the travel route, and environment data currently matched with the travel route.
The driving behavior data can be understood as historical driving behavior habits of the user, such as habits of the user on the strength and frequency of stepping on the brake, habits of the user on the strength and frequency of stepping on the accelerator, and the like. The road condition data can be understood as current condition data of the road, such as uphill distance, downhill distance, high speed distance, congestion condition data, road maintenance condition data, and the like. The environmental data may be understood as data corresponding to the environment on the road, such as environmental data corresponding to weather, temperature, wind power.
Specifically, the current remaining capacity, each first distance, driving behavior data, road condition data and environment data are input into a machine learning model representing the second corresponding relationship, and the first remaining capacity of the current vehicle running to each charging station is obtained through the machine learning model obtained through pre-training.
The machine learning model can be obtained by training according to the data sample set in advance. The data sample set is a sample set including a plurality of sample groups composed of the current remaining capacity, each first distance, driving behavior data, road condition data, environment data and corresponding first remaining capacity. The logic relation between the travel related data and the power consumption can be learned through the training process. The trained machine learning model can be used for rapidly outputting the first residual electric quantity of the current vehicle running to each charging station after inputting the current residual electric quantity, each first distance, driving behavior data, road condition data and environment data. The machine learning model may be a neural network model, and the neural network model may be a convolutional neural network model or a non-convolutional neural network, and in this embodiment, network parameters such as the number of layers, the layers, different convolutional kernels and/or weights of the neural network model are not limited.
The advantage of this setting is that the influence of other factors on the first remaining capacity can be prevented, so that the determined first remaining capacity is more accurate.
In order to better understand the above technical solutions as a whole, the following description is made by way of example with reference to specific examples. For example, referring to fig. 3, in response to a recommendation request input by a user, driving behavior data of the user, road condition data currently matching with a travel route, environment data currently matching with the travel route, a remaining capacity of the current vehicle, and distances from charging stations currently matching with the travel route to the current vehicle are acquired as travel related data of the current vehicle. And determining the first time and the first residual electric quantity when the current vehicle runs to each charging station matched with the travel route according to the travel related data of the current vehicle, the current distance-time consumption corresponding relation and the current distance-power consumption corresponding relation. And acquiring the estimated queuing vehicle number of each charging station at the first time and the charging pile number of each charging station from the cloud server to obtain charging queuing information. And sequencing the charging stations according to the first residual electric quantity and the charging queuing information, and recommending the charging station information according to the sequencing result.
In addition, the charging station information recommendation method provided by the present embodiment and the charging station information recommendation method provided by the foregoing embodiment belong to the same technical concept, and the technical details that are not described in detail in the present embodiment can be referred to the foregoing embodiment, and the same technical features have the same beneficial effects in the present embodiment and the foregoing embodiment.
EXAMPLE III
Fig. 4 is a schematic structural diagram of a charging station information recommendation device according to a third embodiment of the present invention. The present embodiment is applicable to a case where a trip charging advice is dynamically recommended to an electric car.
Referring to fig. 4, the charging station information recommendation apparatus provided by the present invention, integrated in a vehicle terminal, may include:
a time electric quantity determination module 310, configured to determine, in response to a recommendation request input by a user, a first time and a first remaining electric quantity at which the current vehicle travels to each charging station that matches the travel route;
the charging queuing information acquiring module 320 is configured to acquire charging queuing information of each charging station at a first time from the cloud server;
and the charging station information recommending module 330 is configured to sort the charging stations according to the first remaining electric quantity and the charging queue information, and recommend the charging station information according to a sorting result.
Optionally, the time electric quantity determining module 310 may include:
the first distance matching unit is used for acquiring travel related data of the current vehicle; the travel related data comprises the current residual capacity and the first distance of each charging station matched with the travel route;
a second corresponding relation obtaining unit, configured to obtain a current distance-time consuming first corresponding relation and a current distance-power consumption second corresponding relation;
the first time determining unit is used for determining first time when the current vehicle runs to each charging station according to each first distance and the first corresponding relation;
and the first residual electric quantity determining unit is used for determining the first residual electric quantity of the current vehicle running to each charging station according to the current residual electric quantity, each first distance and the second corresponding relation.
Optionally, on the basis of the above scheme, the trip related data may further include at least one of the following: driving behavior data, road condition data currently matched with the travel route, and environment data currently matched with the travel route. Correspondingly, the first remaining power determining unit is specifically configured to: and inputting the current residual electric quantity, each first distance, driving behavior data, road condition data and environment data into a machine learning model representing the second corresponding relation, and obtaining the first residual electric quantity of the current vehicle running to each charging station through the machine learning model.
Optionally, on the basis of the technical scheme, the charging queue information is obtained by predicting, by the cloud server, the charging pile number of each charging station and the remaining electric quantity of each vehicle reaching each charging station.
Optionally, the charging station information recommending module 330 may include:
a first target charging station determination unit configured to determine a first target charging station from the charging stations according to each first remaining power amount;
and the first target charging station sequencing unit is used for sequencing the first target charging stations according to the charging queue information of the first target charging stations at the corresponding first time.
Optionally, the time electric quantity determining module 310 may be configured to:
and re-determining the first time and the first remaining capacity of the current vehicle running to each charging station matched with the travel route every preset time.
Optionally, on the basis of the above scheme, the recommendation apparatus for charging station information may further include:
the second target charging station determining module is used for responding to a selection instruction input by a user after the charging station information is recommended according to the sorting result, and determining a second target charging station from the recommended charging station information;
the uploading module is used for uploading the first time when the current vehicle reaches the second target charging station and the first remaining capacity to the cloud server so that the cloud server can determine the charging queuing information.
According to the charging station information recommendation device provided by the third embodiment of the invention, the first time and the first remaining capacity of the current vehicle running to each charging station matched with the travel route are determined by responding to the recommendation request input by the user; the method comprises the steps that charging queuing information of each charging station at the first time is obtained from a cloud server; and sequencing the charging stations according to the first residual electric quantity and the charging queuing information, and recommending the charging station information according to the sequencing result. According to the device provided by the embodiment of the invention, more reasonable travel charging suggestions are recommended by combining various factors such as travel routes, vehicle electric quantity consumption and charging station queuing conditions, so that the driving charging requirements of users can be met, and the charging experience of the users is improved.
The charging station information recommendation device provided by the embodiment of the invention can execute the charging station information recommendation method provided by the embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method. Technical details that are not described in detail can be referred to in the recommendation method of charging station information provided by the embodiment of the present invention.
Example four
Fig. 5 is a schematic structural diagram of an electronic terminal according to a fourth embodiment of the present invention. Fig. 5 illustrates a block diagram of an exemplary electronic terminal 12 suitable for use in implementing embodiments of the present invention. The electronic terminal 12 shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiment of the present invention. The device 12 is typically an electronic terminal that assumes the recommendation function of the charging station information.
As shown in fig. 5, the electronic terminal 12 is embodied in the form of a general purpose computing device. The components of the electronic terminal 12 may include, but are not limited to: one or more processors or processing units 16, a memory 28, and a bus 18 that couples the various components (including the memory 28 and the processing unit 16).
The electronic terminal 12 typically includes a variety of computer readable media. Such media may be any available media that is accessible by electronic terminal 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The electronic terminal 12 may also communicate with one or more external devices 14 (e.g., keyboard, mouse, camera, etc., and display), one or more devices that enable a user to interact with the electronic terminal 12, and/or any device (e.g., network card, modem, etc.) that enables the electronic terminal 12 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 22. Also, the electronic terminal 12 may communicate with one or more networks (e.g., a Local Area Network (LAN), Wide Area Network (WAN), etc.) and/or a public Network (e.g., the internet) via the Network adapter 20. As shown, the network adapter 20 communicates with the other modules of the electronic terminal 12 via the bus 18. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic terminal 12, including but not limited to: microcode, device drivers, Redundant processing units, external disk drive Arrays, disk array (RAID) devices, tape drives, and data backup storage devices, to name a few.
The processor 16 executes various functional applications and data processing by running the program stored in the memory 28, for example, to implement the recommendation method for charging station information provided by the above-described embodiment of the present invention, including:
determining a first time and a first remaining capacity for the current vehicle to travel to each charging station matched with the travel route in response to a recommendation request input by a user;
the method comprises the steps that charging queuing information of each charging station at the first time is obtained from a cloud server;
and sequencing the charging stations according to the first residual electric quantity and the charging queuing information, and recommending the charging station information according to the sequencing result.
Of course, those skilled in the art can understand that the processor may also implement the technical solution of the recommendation method for charging station information provided in the embodiments of the present invention.
EXAMPLE five
Fifth, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements a method for recommending charging station information, where the method includes:
determining a first time and a first remaining capacity for the current vehicle to travel to each charging station matched with the travel route in response to a recommendation request input by a user;
the method comprises the steps that charging queuing information of each charging station at the first time is obtained from a cloud server;
and sequencing the charging stations according to the first residual electric quantity and the charging queuing information, and recommending the charging station information according to the sequencing result.
Of course, the computer-readable storage medium on which the computer program is stored is not limited to the above method operations, and may also execute the recommendation method of the charging station information provided by the embodiment of the present invention.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor device, apparatus, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution apparatus, device, or apparatus.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution apparatus, device, or apparatus.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments illustrated herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A recommendation method of charging station information is applied to a vehicle terminal and comprises the following steps:
determining a first time and a first remaining capacity for the current vehicle to travel to each charging station matched with the travel route in response to a recommendation request input by a user;
acquiring charging queuing information of each charging station at the first time from a cloud server;
and sequencing the charging stations according to the first residual electric quantity and the charging queuing information, and recommending charging station information according to a sequencing result.
2. The method of claim 1, wherein determining a first time and a first remaining capacity for the current vehicle to travel to each charging station matching the travel route comprises:
acquiring travel related data of a current vehicle; the travel related data comprise the current residual capacity and the first distance of each charging station matched with the travel route at present;
acquiring a first corresponding relation of current distance and consumed time and a second corresponding relation of current distance and power consumption;
determining first time when the current vehicle runs to each charging station according to each first distance and the first corresponding relation;
and determining the first residual electric quantity of the current vehicle running to each charging station according to the current residual electric quantity, each first distance and the second corresponding relation.
3. The method of claim 2, wherein the trip-related data further comprises at least one of: driving behavior data, road condition data currently matched with the travel route, and environment data currently matched with the travel route;
accordingly, a first remaining capacity of the current vehicle to travel to each of the charging stations is determined based on the following steps:
inputting the current remaining power, each first distance, the driving behavior data, the road condition data and the environment data into a machine learning model representing the second corresponding relation;
and obtaining a first residual electric quantity of the current vehicle running to each charging station through the machine learning model.
4. The method of claim 1, wherein the charging queue information is obtained by the cloud server according to the charging pile number of each charging station and the remaining power of each vehicle reaching each charging station.
5. The method of claim 1, wherein the sorting the charging stations according to the first remaining capacity and the charging queue information comprises:
determining a first target charging station from the charging stations according to the first residual electric quantity;
and sequencing the first target charging stations according to the charging queue information of the first target charging stations at the corresponding first time.
6. The method of any of claims 1-5, wherein determining a first time and a first remaining amount of power for the current vehicle to travel to each charging station matching the travel route comprises:
and re-determining the first time and the first remaining capacity of the current vehicle when the current vehicle runs to each charging station matched with the travel route every preset time.
7. The method according to any of claims 1-5, further comprising, after said recommending charging station information according to the ranking result:
determining a second target charging station from the recommended charging station information in response to a selection instruction input by the user;
uploading the first time when the current vehicle reaches the second target charging station and the first remaining capacity to the cloud server so that the cloud server determines the charging queue information.
8. A charging station information recommendation device, integrated in a vehicle terminal, comprising:
the time electric quantity determining module is used for responding to a recommendation request input by a user, and determining a first time and a first residual electric quantity when the current vehicle runs to each charging station matched with the travel route;
the charging queuing information acquisition module is used for acquiring charging queuing information of each charging station at the first time from a cloud server;
and the charging station information recommending module is used for sequencing the charging stations according to the first residual electric quantity and the charging queuing information and recommending the charging station information according to a sequencing result.
9. An electronic terminal comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the recommendation method for charging station information according to any of claims 1-7 when executing the program.
10. A computer-readable storage medium on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the recommendation method for charging station information according to any one of claims 1 to 7.
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