Method, system and computer program product for smart allocation of charging stations

Abstract

The present invention relates to a method for smart allocation of charging stations, which includes the steps of: acquiring vehicle charging information (S1); selecting a vehicle with regular charging behavior based on the acquired vehicle charging information (S2); and acquiring navigation information of the target vehicle and allocating a charging station to the target vehicle based on the navigation information of the target vehicle and the charging information of the vehicle with regular charging behavior (S3). The present invention also relates to a system for smart allocation of charging stations and a computer program product for implementing the method. According to the present invention, the navigation route of the target vehicle can be more rationally planned, thereby effectively shortening the waiting time at the charging station and improving the user's driving experience.

Description

[Technical Field]

[0001] The present invention relates to the technical field of charging electric vehicles, and in particular to a method for smart allocation of charging stations, a system for smart allocation of charging stations, and a computer program product for implementing the method. [Background technology]

[0002] Currently, with the ever-increasing number of electric vehicles on public roads, the demand for charging infrastructure for electric vehicles is ever-increasing. Charging stations can provide parking spaces and charging piles for electric vehicles. However, only a limited number of charging stations can be provided in urban areas. When charging stations are recommended to users, the occupancy or queue status of the charging station is particularly important, and long queue times degrade the user experience. However, existing charging station recommendation schemes only consider the current status of the charging station. Because there is a delay in the information exchange between the user side and the charging side, the user cannot accurately predict the status of the charging station when driving to it. For example, a charging station may have available charging piles when a vehicle starts driving, but all of the charging piles at the charging station may be occupied when the vehicle arrives at the charging station.

[0003] Therefore, how to smartly allocate charging stations to electric vehicles is currently a technical challenge to be solved. Summary of the Invention

[0004] To address the problems in the prior art, the present invention provides a method for smart allocation of charging stations, a system for smart allocation of charging stations, and a computer program product for implementing the method. The core idea of ​​the present invention is as follows: from acquired vehicle charging information, vehicles with regular charging behaviors are selected, and status information of charging stations can be predicted based on the charging information of the vehicles with regular charging behaviors. When a navigation route for a target vehicle is planned, charging stations are allocated to the target vehicle based on the charging habits of the target vehicle and the predicted status information of the charging stations. According to the present invention, the navigation route for the target vehicle can be planned more rationally, thereby effectively shortening queuing time at charging stations and improving the user's driving experience.

[0005] According to a first aspect of the present invention, there is provided a method for smart allocation of charging stations, the method comprising: Step S1: Obtaining vehicle charging information; Step S2: selecting a vehicle whose charging behavior is regular based on the acquired vehicle charging information; Step S3: Obtaining navigation information of the target vehicle, and allocating a charging station to the target vehicle based on the navigation information of the target vehicle and the charging information of vehicles with regular charging behaviors.

[0006] According to an optional embodiment of the present invention, the method comprises: The method may further include step S21: estimating and storing a departure time at which a vehicle with regular charging behavior departs from a charging station based on the acquired vehicle charging information.

[0007] Optionally, in step S3, a charging station is assigned to the target vehicle based on the navigation information of the target vehicle and the stored departure time, and the stored departure time is used to predict the status of the charging station. In this way, the status information of the charging station can be accurately predicted, thereby improving the efficiency and accuracy of smart assignment of charging stations.

[0008] According to an optional embodiment of the present invention, in step S2, the selection is performed at preset time intervals, and the vehicle charging information on which the selection is based changes over time during acquisition. By re-performing the selection at preset time intervals, the accuracy of the selection can be improved.

[0009] According to an optional embodiment of the present invention, step S3 comprises: Step S301: Obtaining navigation information for a target vehicle, including a navigation destination; Step S302: predicting status information of charging stations within a preset area range of a navigation destination according to the stored departure times of vehicles with regular charging behaviors; Step S303: Allocating a charging station to the target vehicle based on the navigation information of the target vehicle and the predicted state information of the charging station; Step S304: Presenting the location information of the assigned charging station and a navigation route to the assigned charging station to the user of the target vehicle.

[0010] Here, in a simple manner, the efficiency and accuracy of smart allocation of charging stations is improved, and the user's driving experience is improved.

[0011] According to an optional embodiment of the present invention, in step S303, based on the navigation information of the target vehicle and the predicted status information of the charging station, it is determined whether there is an available charging station within the preset area range of the navigation destination at the predicted time when the target vehicle is expected to arrive at the navigation destination. If there is an available charging station within the preset area range of the navigation destination at the predicted time, the charging station closest to the navigation destination is assigned to the target vehicle; or if there is no available charging station within the preset area range of the navigation destination at the predicted time, based on preset recommendation criteria, prioritization is performed for the charging stations within the preset area range of the navigation destination. Based on the prioritization of the charging stations, the charging stations are assigned to the target vehicle. Different influence factors are set for factors such as the distance to the navigation destination and the length of the waiting time according to the preset recommendation criteria, and prioritization of the charging stations is performed.

[0012] According to an optional embodiment of the present invention, step S3 comprises: Step S311: obtaining navigation information of the target vehicle, and determining whether the charging behavior of the target vehicle is regular based on the obtained vehicle charging information; Step S312: if the charging behavior of the target vehicle is regular, estimate the charging start time of the target vehicle based on the acquired charging information of the target vehicle, and predict the predicted charging location of the target vehicle based on the navigation information and the charging start time of the target vehicle; Step S313: predicting status information of charging stations within a preset area range of the predicted charging location according to the stored departure times of vehicles whose charging behaviors are regular; Step S314: Allocating a charging station to the target vehicle based on the navigation information of the target vehicle and the predicted state information of the charging station; Step S315: Presenting the location information of the assigned charging station and a navigation route to the assigned charging station to the user of the target vehicle.

[0013] Here, the planned navigation route of the target vehicle is more adapted to the charging habits of the target vehicle, thereby improving the user's driving experience.

[0014] According to an optional embodiment of the present invention, in step S314, based on the charging start time of the target vehicle and the status information of charging stations within a preset area range of the predicted charging location, it is determined whether there is an available charging station within the preset area range of the predicted charging location at the charging start time. If there is an available charging station within the preset area range of the predicted charging location at the charging start time, the available charging station closest to the predicted charging location is assigned to the target vehicle. Alternatively, if there is no available charging station within the preset area range of the predicted charging location at the charging start time, prioritization of charging stations within the preset area range of the predicted charging location is performed based on preset recommendation criteria. Based on the prioritization of charging stations, charging stations are assigned to the target vehicle. Different influence factors are set for factors such as the distance to the predicted charging location and the length of the waiting time according to the preset recommendation criteria, and prioritization of charging stations is performed.

[0015] According to an optional embodiment of the present invention, step S3 comprises: Step S321: Obtaining navigation information of the target vehicle, including a navigation destination, and current charge level information; Step S322: determining whether the current charge level of the target vehicle is sufficient to allow the target vehicle to reach the navigation destination based on the current charge level information of the target vehicle and the navigation information; Step S323: if the current charge level of the target vehicle is not sufficient to allow the target vehicle to reach the navigation destination, determining a predicted charging location and a predicted charging time of the target vehicle based on the navigation information and the current charge level information of the target vehicle; Step S324: predicting status information of charging stations within a preset area range of the predicted charging location based on the stored departure times of vehicles whose charging behaviors are regular; Step S325: Allocating a charging station to the target vehicle based on the navigation information of the target vehicle and the predicted state information of the charging station; Step S326: Presenting the location information of the assigned charging station and a navigation route to the assigned charging station to the user of the target vehicle.

[0016] Here, when the navigation route of the vehicle is planned, the vehicle's charge level information may be fully taken into consideration, thereby avoiding accidents in which the vehicle runs out of electricity before reaching the navigation destination, thereby improving the user's driving experience.

[0017] According to an optional embodiment of the present invention, in step S325, based on the predicted charging time of the target vehicle and the status information of charging stations within a preset area range of the predicted charging location, it is determined whether there is an available charging station within the preset area range of the predicted charging location at the predicted charging time. If there is an available charging station within the preset area range of the predicted charging location at the predicted charging time, the available charging station closest to the predicted charging location is assigned to the target vehicle. Alternatively, if there is no available charging station within the preset area range of the predicted charging location at the predicted charging time, prioritization is performed on the charging stations within the preset area range of the predicted charging location based on preset recommendation criteria. Based on the prioritization of the charging stations, the charging stations are assigned to the target vehicle. Different influence factors are set for factors such as the distance to the predicted charging location and the length of the waiting time according to the preset recommendation criteria, and prioritization of the charging stations is performed.

[0018] According to an optional embodiment of the present invention, the acquired vehicle charging information includes, for example, a vehicle identifier, charging station basic information, an on / off signal of a charging pile, a charging current signal of a charging pile, vehicle start information, vehicle speed information, and / or vehicle location information, and the charging station basic information includes, for example, a charging station identifier, charging station location information, the number of charging piles of the charging station, and / or a charging pile type.

[0019] According to a second aspect of the present invention, there is provided a system for smart allocation of charging stations, which is used to implement a method according to the present invention. The system includes one or more of the following components: a charging information acquisition module configured to acquire vehicle charging information; a charging information processing module configured to select a vehicle with regular charging behavior based on the acquired vehicle charging information; a storage module configured to store charging information of the vehicle with regular charging behavior; a navigation module configured to acquire navigation information input by a user of the target vehicle, wherein high-definition map information labeled with basic charging station information is stored in the navigation module; an allocation module configured to assign a charging station to the target vehicle according to the navigation information and the stored charging information of the vehicle with regular charging behavior; and an information notification module configured to notify a user of location information of the assigned charging station and a navigation route to the assigned charging station.

[0020] According to a third aspect of the present invention there is provided a computer program product, such as a computer readable program carrier, comprising computer program instructions which, when executed by a processor, perform the steps of the method according to the present invention. [Brief explanation of the drawings]

[0021] The principles, features, and advantages of the present invention may be better understood through a more detailed description of the invention provided with reference to the accompanying drawings, in which: [Figure 1] 1 illustrates a flowchart of a method for smart allocation of charging stations, according to an exemplary embodiment of the present invention. [Figure 2] 10 illustrates a flowchart of a method for smart allocation of charging stations according to another exemplary embodiment of the present invention. [Figure 3]10 illustrates a flowchart of a method for smart allocation of charging stations according to another exemplary embodiment of the present invention. [Figure 4] 10 illustrates a flowchart of a method for smart allocation of charging stations according to another exemplary embodiment of the present invention. [Figure 5] 10 illustrates a flowchart of a method for smart allocation of charging stations according to another exemplary embodiment of the present invention. [Figure 6] 1 illustrates a block diagram of a system for smart allocation of charging stations in accordance with an exemplary embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0022] In order to make the technical problems to be solved by the present invention, the technical solutions, and the beneficial technical effects clearer, the present invention will be described in more detail below with reference to the accompanying drawings and several exemplary embodiments. It should be understood that the specific embodiments described in this specification are only used to explain the present invention, and are not used to limit the protection scope of the present invention.

[0023] 1 shows a flowchart of a method for smart allocation of charging stations according to an exemplary embodiment of the present invention. The following exemplary embodiments will explain the method according to the present invention in more detail.

[0024] The method includes steps S1 to S3. In step S1, vehicle charging information is acquired. In this embodiment of the present invention, the acquired vehicle charging information includes, for example, a vehicle identifier (e.g., license plate number), charging station basic information, a charging pile on / off signal, a charging pile charging current signal, vehicle start information, vehicle speed information, and / or vehicle location information. The charging station basic information includes, for example, a charging station identifier, charging station location information, the number of charging piles in the charging station, and / or a charging pile type. Here, it is possible to determine whether vehicle charging is complete based on the charging pile on / off signal and / or the charging pile charging current signal. The charging station includes one or more charging piles, and the charging station, particularly a smart charging station, can upload the on / off signal and / or the charging current signal of each of its charging piles to a back-end server. Based on this, in combination with the vehicle start information, vehicle speed information, and / or vehicle location information, it is possible to determine whether the vehicle has left the charging station after charging is complete. The vehicle start information, vehicle speed information, and / or vehicle position information may be acquired, for example, via the charging information acquisition module 11, in particular, via a real-time monitoring system. For example, if a vehicle start signal is detected and / or if it is detected that the vehicle speed has increased from 0 within a preset period after the detection of an off signal of the charging pile, it is determined that the vehicle has departed from the charging station after the completion of charging.

[0025] It should be noted that when vehicle charging information is obtained, a vehicle identifier (e.g., license plate number) may be associated with the remaining vehicle charging information belonging to that vehicle, and a charging information archive may be established for each vehicle identifier.

[0026] In step S2, a vehicle with regular charging behavior is selected based on the acquired vehicle charging information. In the present invention, "regular charging behavior" may be understood to mean that the vehicle is periodically charged at a certain frequency in a certain period and repeatedly charged at a certain charging station, as follows: The certain period (e.g., a certain period each day or a certain period each week) and / or the certain frequency (e.g., several times a day or once every few days) may be set based on preset criteria. The selection may be performed, for example, via an artificial neural network model trained through big data.

[0027] Optionally, the selection may be performed at preset time intervals (e.g., once a week). It is understood that the vehicle charging information on which the selection is based changes over time during acquisition. The vehicle charging habits (e.g., time of departure from a charging station) reflected by the vehicle charging information are likely to change. Therefore, the accuracy of the selection can be improved by re-performing the selection at preset time intervals.

[0028] In step S3, navigation information of the target vehicle is acquired, and a charging station is assigned to the target vehicle based on the navigation information of the target vehicle and the charging information of vehicles with regular charging behavior. Here, the navigation information input by the user of the target vehicle is acquired via the navigation module 14, and the navigation information includes, among other things, a navigation destination. The navigation module 14 stores high-definition map information. The high-definition map information may include not only basic map information for vehicle navigation but also basic charging station information (e.g., charging station identifiers, charging station location information, the number of charging piles at the charging station, and / or charging pile types), and may optionally further include real-time traffic information used to predict the speed of the target vehicle traveling along the navigation route. For example, based on the navigation information of the target vehicle, the time at which the target vehicle will arrive at the navigation destination can be predicted. Furthermore, based on the charging information of vehicles with regular charging behavior, status information of charging stations within a predetermined area range (e.g., a range of 1 kilometer) of the navigation destination at that time is further predicted. The status information may include, for example, an empty or occupied status, and may further include the length of the waiting time. Therefore, a charging station, such as an available charging station closest to the navigation destination, is assigned to the target vehicle based on predicted status information of the charging station, as will be described in more detail in an optional embodiment of the present invention.

[0029] According to this embodiment of the present invention, the acquired vehicle charging information is analyzed and processed to predict the status information of charging stations on the navigation route of the target vehicle, and appropriate charging stations are allocated to the target vehicle with reference to the navigation information of the target vehicle, so that the navigation route of the target vehicle can be planned more reasonably, thereby effectively shortening the queuing time at charging stations and improving the user's driving experience.

[0030] 2 shows a flowchart of a method for smart allocation of charging stations according to another exemplary embodiment of the present invention. In the following, only the differences from the embodiment shown in FIG. 1 will be described, and for the sake of brevity, the same steps will not be described again.

[0031] The method may further include step S21. In step S21, a departure time at which a vehicle with regular charging behavior departs from the charging station is estimated and stored based on the acquired vehicle charging information. In an optional embodiment of the present invention, after a vehicle with regular charging behavior is selected, the departure time at which the vehicle departs from the charging station may be estimated based on the acquired vehicle charging information, for example, according to the following method. It may be determined whether charging of the vehicle is completed based on the on / off signal of the charging pile and / or the charging current signal of the charging pile. After it is determined that charging of the vehicle is completed, the departure time at which the vehicle departs from the charging station after charging is completed may be estimated based on the vehicle start information, vehicle speed information, and / or vehicle position information. The estimated departure time may be stored in the storage module 13, and in particular, may be stored together with the vehicle identifier in a charging information archive established for each vehicle identifier.

[0032] In step S3, a charging station may be assigned to the target vehicle based on the navigation information of the target vehicle and the stored departure time, and the stored departure time at which a vehicle with regular charging behavior departs from the charging station may be used to predict status information of the charging station.

[0033] According to an optional embodiment of the present invention, the departure times at which vehicles with regular charging behavior leave charging stations are estimated and stored, so that the status information of charging stations can be accurately predicted in a simple manner, thereby improving the efficiency and accuracy of smart allocation of charging stations.

[0034] 3 shows a flowchart of a method for smart allocation of charging stations according to another exemplary embodiment of the present invention. In the following, only the differences from the embodiment shown in FIG. 1 will be described, and for the sake of brevity, the same steps will not be described again.

[0035] Step S3 may include steps S301 to S304. In step S301, navigation information of the target vehicle, including the navigation destination, is acquired. In step S302, status information of charging stations within a preset area range of the navigation destination is predicted based on the stored departure times of vehicles with regular charging behavior. Here, the status information of the charging stations may include, for example, an empty state or an occupied state, and may even include the length of the queue time. The status information may be predicted based on the departure times of vehicles that are regularly charged at the charging stations. Note that this embodiment of the present invention is premised on the fact that the charge level of the target vehicle is sufficient to enable the target vehicle to travel to the navigation destination input by the user. That is, after the target vehicle arrives at the navigation destination, charging is performed near the navigation destination. The time at which the target vehicle will arrive at the navigation destination can be predicted based on the navigation information of the target vehicle.

[0036] In step S303, a charging station is assigned to the target vehicle based on the navigation information of the target vehicle and the predicted status information of the charging station. Here, for example, whether an available charging station exists may be determined according to the predicted time when the target vehicle will arrive at the navigation destination and the status information of the charging station within a preset area range (e.g., 1 kilometer) of the navigation destination at the predicted time. If an available charging station exists within the preset area range of the navigation destination at the predicted time, the available charging station closest to the navigation destination is assigned to the target vehicle. If an available charging station does not exist within the preset area range of the navigation destination at the predicted time, prioritization is performed on the charging stations within the preset area range of the navigation destination based on preset recommendation criteria. Different influence factors may be set for factors such as the distance to the navigation destination and the length of the queue time according to the preset recommendation criteria, and prioritization is performed on the charging stations. Based on the prioritization of the charging stations, charging stations, especially charging stations with short queue times and close distances, are assigned to the target vehicle.

[0037] In step S304, the location information of the assigned charging station and the navigation route to the assigned charging station are notified to the user of the target vehicle. Here, the notification may be performed via the information notification module 16. The information notification module 16 includes, for example, a head-up display screen and / or a central control display screen.

[0038] According to an optional embodiment of the present invention, status information of charging stations within a preset area range of a navigation destination is predicted based on the departure time of a vehicle with regular charging behavior, and appropriate charging stations are assigned to the target vehicle by referring to the navigation information of the target vehicle, thereby improving the efficiency and accuracy of smart assignment of charging stations in a simple manner and improving the user's driving experience.

[0039] 4 shows a flowchart of a method for smart allocation of charging stations according to another exemplary embodiment of the present invention. In the following, only the differences from the embodiment shown in FIG. 1 will be described, and for the sake of brevity, the same steps will not be described again.

[0040] Step S3 may further include steps S311 to S315. In step S311, navigation information of the target vehicle is obtained, and based on the obtained vehicle charging information, it is determined whether the charging behavior of the target vehicle is regular. If the charging behavior of the target vehicle is regular, in step S312, a charging start time of the target vehicle is estimated based on the obtained charging information of the target vehicle, and a predicted charging location of the target vehicle is predicted based on the navigation information and the charging start time of the target vehicle. It should be understood that if the target vehicle has a habit of charging within a certain period of time, planning a navigation route for the target vehicle may take into account guiding the target vehicle to a charging station within the certain period of time.

[0041] In step S313, status information of charging stations within a preset area range of the predicted charging location is predicted based on the stored departure times of vehicles with regular charging behavior. In step S314, charging stations are assigned to the target vehicle based on the navigation information of the target vehicle and the predicted status information of the charging stations. As in the above-described embodiment, it may also be determined whether an available charging station exists within the preset area range of the predicted charging location at the charging start time based on the charging start time of the target vehicle and the status information of charging stations within a preset area range (e.g., 1 kilometer) of the predicted charging location. If an available charging station exists within the preset area range of the predicted charging location at the charging start time, the available charging station closest to the predicted charging location is assigned to the target vehicle. If an available charging station does not exist within the preset area range of the predicted charging location at the charging start time, prioritization is performed on charging stations within the preset area range of the predicted charging location based on preset recommendation criteria. According to a preset recommendation criterion, different influence factors are set for factors such as the distance to the predicted charging location and the length of the queue time, and prioritization is performed for the charging stations. Based on the prioritization of the charging stations, charging stations, especially those with short queue times and close distances, are allocated to the target vehicle.

[0042] In step S315, the location information of the assigned charging station and the navigation route to the assigned charging station are notified to the user of the target vehicle. Here, the notification may be performed via the information notification module 16. The information notification module 16 includes, for example, a head-up display screen and / or a central control display screen.

[0043] According to an optional embodiment of the present invention, the planned navigation route of the target vehicle is more adapted to the charging habits of the target vehicle, thereby improving the user's driving experience.

[0044] 5 shows a flowchart of a method for smart allocation of charging stations according to another exemplary embodiment of the present invention. In the following, only the differences from the embodiment shown in FIG. 1 will be described, and for the sake of brevity, the same steps will not be described again.

[0045] Step S3 may further include steps S321 to S326. In step S321, navigation information of the target vehicle, including a navigation destination, and current charge level information are obtained. Here, the current charge level information of the target vehicle may be obtained through the charge information acquisition module 11, particularly a real-time monitoring system.

[0046] In step S322, based on the current charge level information of the target vehicle and the navigation information, it is determined whether the current charge level of the target vehicle is sufficient to allow the target vehicle to reach the navigation destination. If the current charge level of the target vehicle is not sufficient to allow the target vehicle to reach the navigation destination, in step S323, based on the navigation information and current charge level information of the target vehicle, a predicted charging location and a predicted charging time for the target vehicle are determined. Here, based on the current charge level information of the target vehicle, a maximum driving distance supported by the charge level of the target vehicle may be calculated, and based on the navigation route from the navigation module 14 and the calculated maximum driving distance, a predicted charging location along the navigation route and a predicted charging time for the target vehicle to arrive at the predicted charging location may further be determined.

[0047] In step S324, status information of charging stations within a preset range of the predicted charging location is predicted based on the stored departure times of vehicles with regular charging behavior. In step S325, a charging station is assigned to the target vehicle based on the navigation information of the target vehicle and the predicted status information of the charging station. As in the above-mentioned embodiment, it may also be determined whether an available charging station exists within the preset range of the predicted charging location at the predicted charging time based on the predicted charging time of the target vehicle and the status information of the charging station within the preset range of the predicted charging location. If an available charging station exists within the preset range of the predicted charging location at the predicted charging time, the available charging station closest to the predicted charging location is assigned to the target vehicle. Alternatively, if an available charging station does not exist within the preset range of the predicted charging location at the predicted charging time, prioritization of charging stations within the preset range of the predicted charging location is performed based on preset recommendation criteria. According to the preset recommendation criteria, different influence factors are set for factors such as the distance to the predicted charging location and the length of the queue time, and prioritization of charging stations is performed. Based on the prioritization of the charging stations, charging stations are assigned to target vehicles.

[0048] In step S326, the location information of the assigned charging station and a navigation route to the assigned charging station are presented to the user of the target vehicle.

[0049] According to an optional embodiment of the present invention, the vehicle's charge level information may be fully taken into consideration when the vehicle's navigation route is planned, thereby avoiding accidents in which the vehicle runs out of electricity before reaching the navigation destination, thereby improving the user's driving experience.

[0050] Furthermore, please note that the step numbers described in this specification do not necessarily represent a sequence but are merely reference numbers, and this sequence can be changed according to specific circumstances as long as the technical object of the present invention can be achieved.

[0051] FIG. 6 illustrates a block diagram of a system for smart allocation of charging stations according to an exemplary embodiment of the present invention.

[0052] As shown in FIG. 6 , the system 1 includes one or more of the following components: a charging information acquisition module 11 configured to acquire vehicle charging information and including, for example, a real-time monitoring system; a charging information processing module 12 configured to select vehicles with regular charging behavior based on the acquired vehicle charging information; a storage module 13 configured to store charging information of the vehicles with regular charging behavior; a navigation module 14 configured to acquire navigation information input by a user of the target vehicle, wherein high-definition map information labeled with basic charging station information is stored in the navigation module 14; an assignment module 15 configured to assign a charging station to the target vehicle according to the navigation information of the vehicle with regular charging behavior and the stored charging information; and an information notification module 16 configured to notify the user of location information of the assigned charging station and a navigation route to the assigned charging station, wherein the information notification module 16 includes, for example, a head-up display screen and / or a central control display screen.

[0053] Although specific embodiments of the present invention have been described in detail herein, the specific embodiments are for illustrative purposes only and should not be considered as limiting the scope of the present invention. Various substitutions and modifications can be made without departing from the spirit and scope of the present invention.

Claims

1. 1. A method for smart allocation of charging stations, comprising: Step S1: Acquiring vehicle charging information; Step S2: selecting a vehicle whose charging behavior is regular based on the acquired vehicle charging information; Step S3: acquiring navigation information of a target vehicle, and allocating a charging station to the target vehicle based on the navigation information of the target vehicle and the charging information of the vehicle whose charging behavior is regular; The method comprising:

2. Step S21: A step of estimating and storing a departure time at which the vehicle, whose charging behavior is regular, departs from the charging station based on the acquired vehicle charging information. The method of claim 1 further comprising:

3. 3. The method of claim 2, wherein in step S3, the charging station is assigned to the target vehicle based on the navigation information of the target vehicle and the stored departure time, and the stored departure time is used to predict a state of the charging station.

4. Step S3: Step S301: Obtaining the navigation information of the target vehicle, including a navigation destination; Step S302: predicting status information of charging stations within a preset area range of the navigation destination based on the stored departure time of the vehicle whose charging behavior is regular; Step S303: Allocating a charging station to the target vehicle based on the navigation information of the target vehicle and the predicted status information of the charging station; Step S304: presenting location information of the assigned charging station and a navigation route to the assigned charging station to a user of the target vehicle; The method according to any one of claims 1 to 3, comprising:

5. 5. The method of claim 4, wherein in step S303, based on the navigation information of the target vehicle and the predicted status information of the charging station, it is determined whether an available charging station exists within the preset area range of the navigation destination at the predicted time when the target vehicle is expected to arrive at the navigation destination; if an available charging station exists within the preset area range of the navigation destination at the predicted time, a charging station closest to the navigation destination is assigned to the target vehicle; or if an available charging station does not exist within the preset area range of the navigation destination at the predicted time, prioritization is performed on charging stations within the preset area range of the navigation destination based on preset recommendation criteria; and based on the prioritization of the charging stations, a charging station is assigned to the target vehicle; different influence factors are set for factors such as a distance to the navigation destination and a length of a waiting time according to the preset recommendation criteria, and the prioritization is performed on the charging stations.

6. Step S3: Step S311: obtaining the navigation information of the target vehicle, and determining whether the charging behavior of the target vehicle is regular based on the obtained vehicle charging information; Step S312: if the charging behavior of the target vehicle is regular, estimating a charging start time of the target vehicle based on the acquired charging information of the target vehicle, and predicting a predicted charging location of the target vehicle based on the navigation information and the charging start time of the target vehicle; Step S313: predicting status information of charging stations within a preset area range of the predicted charging location based on the stored departure times of the vehicles whose charging behaviors are regular; Step S314: Allocating a charging station to the target vehicle based on the navigation information of the target vehicle and the predicted status information of the charging station; Step S315: presenting location information of the assigned charging station and a navigation route to the assigned charging station to a user of the target vehicle; The method according to any one of claims 1 to 3, comprising:

7. The method according to any one of claims 1 to 6, wherein in step S2, the selection is performed at preset time intervals, and the vehicle charging information on which the selection is based changes over time during acquisition.

8. 7. The method of claim 6, wherein in step S314, based on the charging start time of the target vehicle and the status information of the charging stations within the preset area range of the predicted charging location, it is determined whether an available charging station exists within the preset area range of the predicted charging location at the charging start time, and if an available charging station exists within the preset area range of the predicted charging location at the charging start time, an available charging station closest to the predicted charging location is assigned to the target vehicle, or if an available charging station does not exist within the preset area range of the predicted charging location at the charging start time, prioritization of charging stations within the preset area range of the predicted charging location is performed based on preset recommendation criteria, and a charging station is assigned to the target vehicle based on the prioritization of the charging stations, and different influence factors are set for factors such as a distance to the predicted charging location and a length of a waiting time according to the preset recommendation criteria, and the prioritization of the charging stations is performed.

9. Step S3: Step S321: Obtaining the navigation information of the target vehicle, including a navigation destination, and current charge level information; Step S322: determining whether the current charge level of the target vehicle is sufficient to allow the target vehicle to arrive at the navigation destination based on the current charge level information of the target vehicle and the navigation information; Step S323: if the current charge level of the target vehicle is not sufficient to allow the target vehicle to reach the navigation destination, determining a predicted charging location and a predicted charging time of the target vehicle based on the navigation information and the current charge level information of the target vehicle; Step S324: Predicting status information of charging stations within a preset area range of the predicted charging location based on the stored departure times of the vehicles whose charging behaviors are regular; Step S325: Allocating a charging station to the target vehicle based on the navigation information of the target vehicle and the predicted status information of the charging station; Step S326: presenting location information of the assigned charging station and a navigation route to the assigned charging station to a user of the target vehicle; The method according to any one of claims 1 to 3, comprising:

10. 10. The method of claim 9, wherein in step S325, based on the predicted charging time of the target vehicle and the status information of the charging stations within the preset area range of the predicted charging location, it is determined whether an available charging station exists within the preset area range of the predicted charging location at the predicted charging time, and if an available charging station exists within the preset area range of the predicted charging location at the predicted charging time, an available charging station closest to the predicted charging location is assigned to the target vehicle, or if an available charging station does not exist within the preset area range of the predicted charging location at the predicted charging time, prioritization is performed on charging stations within the preset area range of the predicted charging location based on preset recommendation criteria, and a charging station is assigned to the target vehicle based on the prioritization of the charging stations, and different influence factors are set for factors such as a distance to the predicted charging location and a length of a waiting time according to the preset recommendation criteria, and the prioritization is performed on the charging stations.

11. The method according to any one of claims 1 to 10, wherein the acquired vehicle charging information includes a vehicle identifier, charging station basic information, an on / off signal of a charging pile, a charging current signal of the charging pile, vehicle start information, vehicle speed information, and / or vehicle position information, and the charging station basic information includes a charging station identifier, charging station position information, the number of charging piles at the charging station, and / or a charging pile type.

12. A system (1) for smart allocation of charging stations, said system (1) being used to implement the method according to any one of claims 1 to 11, said system (1) comprising the following components: a charging information acquisition module (11) configured to acquire vehicle charging information; a charging information processing module (12) configured to select a vehicle whose charging behavior is regular based on the acquired vehicle charging information; a storage module (13) configured to store the charging information of the vehicle whose charging behavior is regular; a navigation module (14) configured to acquire navigation information input by a user of a target vehicle, the navigation module (14) storing high-definition map information labeled with basic charging station information; an allocation module (15) configured to allocate a charging station to the target vehicle according to the navigation information and the stored charging information of the vehicle whose charging behavior is regular; and an information notification module (16) configured to notify the user of location information of the assigned charging station and a navigation route to the assigned charging station; The system (1) includes one or more of:

13. A computer program product, such as a computer readable program carrier, comprising computer program instructions for performing the steps of the method according to any one of claims 1 to 11 when said computer program product is executed by a processor.

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