Intelligent allocation method and system for charging stations in residential areas

Abstract

This application relates to a method and system for intelligently allocating charging spots in a residential area. The method comprises: obtaining basic information about an electric vehicle, including the remaining power of the electric vehicle; generating a charging instruction for the electric vehicle based on the basic information; generating charging spot allocation information based on the charging instruction, and feeding back the allocation information to a user terminal corresponding to the electric vehicle. In this application, vehicle owners can reach an allocated charging spot for charging based on the allocation information from the user terminal, thereby reducing the time the vehicle owner spends searching for a charging spot and improving the convenience of charging the electric vehicle.

Description

Technical Field

[0001] The present application relates to the field of electric vehicle charging, and in particular to a method and system for intelligently allocating charging stations in a residential area. Background Art

[0002] As global warming and other issues continue to intensify, people are increasingly aware of the environmental hazards of fossil fuels, prompting a search for new, clean energy alternatives. As a major source of fossil fuel consumption, the automotive industry faces significant challenges and pressure. As a response, new energy vehicles (NEVs), powered by electricity, are seen as the future of the automotive industry. Clearly, the environmental impact of NEV emissions is negligible, and due to the renewable nature of electricity, NEVs pose no risk to energy crises. Consequently, promoting NEVs has become a priority for governments worldwide.

[0003] However, as the number of electric vehicles in residential communities increases, charging facilities in the communities are becoming increasingly scarce. When electric vehicles need to be charged, owners often have to spend a long time looking for an idle potential, which is very inconvenient. Summary of the Invention

[0004] In order to improve the convenience of charging electric vehicles, the present application provides a method and system for intelligently allocating charging spaces in a residential area.

[0005] In a first aspect, the present application provides a method for intelligently allocating charging stations in a cell, which adopts the following technical solutions:

[0006] A method for intelligently allocating charging stations in a residential area, comprising:

[0007] Acquiring basic information of the electric vehicle, wherein the basic information includes the remaining power of the electric vehicle;

[0008] Generate a charging instruction for the electric vehicle based on the basic information;

[0009] The allocation information of the charging position is generated based on the charging instruction, and the allocation information is fed back to the user terminal corresponding to the electric vehicle.

[0010] By adopting the above technical solution, the car owner can reach the assigned charging position for charging according to the allocation information of the user terminal, thereby reducing the time spent by the car owner in searching for the charging position and improving the convenience of charging the electric vehicle.

[0011] Optionally, generating the charging position allocation information includes:

[0012] Scoring each of the charging positions, and obtaining an optimal charging position based on the scoring results;

[0013] The allocation information is generated based on the optimal charging position.

[0014] By adopting the above technical solution, each charging position is scored based on a combination of multiple inspection parameters, and the optimal charging position is allocated according to the scoring results, making the allocation of charging positions more reasonable.

[0015] Optionally, the basic information includes vehicle parameters, and the vehicle parameters include charging power;

[0016] Scoring each charging position includes:

[0017] Calculating a required charging period for the electric vehicle based on the remaining power and the charging power;

[0018] If the charging period is staggered with the peak charging period of the charging position, a first score is obtained;

[0019] If the charging period does not stagger with the peak charging period of the charging position, a second score is obtained;

[0020] Obtaining distance information between the charging position and a pre-stored address in the user terminal;

[0021] Obtaining a first estimated time for the electric vehicle to leave the charging position after charging is completed based on the charging habit information;

[0022] A weighted calculation is performed on the distance information of the charging position and the first estimated departure time, and the sum of the two scores is calculated to obtain a third score, and a sum of the third score and the first score or the second score is calculated.

[0023] Optionally, the basic information also includes the current location of the electric vehicle;

[0024] The generating of a charging instruction for the electric vehicle based on the basic information includes:

[0025] Determining whether the current position of the electric vehicle is at a preset position;

[0026] If so, determining whether the remaining power is not greater than a preset power threshold;

[0027] If so, a charging instruction is generated for charging the electric vehicle.

[0028] By adopting the above technical solution, charging instructions are automatically generated according to the basic information of electric vehicles, thereby improving the automation level of charging space allocation in the community.

[0029] Optionally, determining whether the remaining power is not greater than a preset power threshold includes:

[0030] Obtaining the preset power threshold corresponding to the electric vehicle;

[0031] Comparing the remaining power with the preset power threshold to determine whether the remaining power is not greater than the preset power threshold;

[0032] Wherein, obtaining the preset power threshold corresponding to the electric vehicle includes:

[0033] If the number of times the electric vehicle is charged is less than the number threshold, the initial power threshold is used as the preset power threshold;

[0034] If the number of times the electric vehicle has been charged is not less than the number threshold, obtaining charging habit information of the electric vehicle, the charging habit information including historical remaining power of the electric vehicle during historical charging operations;

[0035] The initial power threshold is revised based on the historical remaining power, and the revised power threshold is used as the preset power threshold.

[0036] By adopting the above technical solution, if the number of times an electric vehicle has been charged within a statistical period is less than the number threshold, the electric vehicle may be newly purchased by the owner, and the initial power threshold can be used as the preset power threshold. If the electric vehicle is frequently charged in the community, the preset power threshold can be set based on the owner's charging habits, improving the rationality of the preset power threshold setting.

[0037] Optionally, after determining whether the remaining power is not greater than a preset power threshold, the method further includes:

[0038] If the remaining power is greater than the preset power threshold, obtaining a subsequent travel plan of the electric vehicle and historical power consumption information of the electric vehicle;

[0039] calculating the power consumption of the trip plan based on the trip plan and the historical power consumption information;

[0040] If the difference between the remaining power and the power consumption of the trip plan is less than a prompt threshold, a prompt message indicating that the electric vehicle has insufficient power is generated and the prompt message is sent to a user terminal.

[0041] By adopting the above technical solution, the possibility that the remaining power of the electric vehicle is greater than the preset power threshold but the remaining power of the electric vehicle is insufficient to support the entire planned trip when going out is reduced.

[0042] Optionally, before using the initial power threshold as the preset power threshold, the method further includes:

[0043] Determining whether the owner of the electric vehicle is associated with other electric vehicles whose charging times are not less than the threshold number;

[0044] If so, obtaining the charging habit information of other associated electric vehicles and executing the step of correcting the initial power threshold based on the historical remaining power;

[0045] If not, the step of using the initial power threshold as the preset power threshold is executed.

[0046] By adopting the above technical solution, in a community, there are situations where the same owner is associated with multiple electric vehicles. When the owners of multiple electric vehicles are the same, the charging habits of the electric vehicles are also the same. Therefore, the preset power threshold of a newly purchased electric vehicle whose charging times are less than the times threshold can be corrected according to the charging habit information of other associated electric vehicles.

[0047] In a second aspect, the present application provides a device for intelligently allocating charging spaces in a residential area, which adopts the following technical solution:

[0048] A device for intelligently allocating charging stations in a residential area, comprising:

[0049] A first acquisition module is used to acquire basic information of the electric vehicle, wherein the basic information includes the remaining power of the electric vehicle;

[0050] A generating calculation module is used to generate a charging instruction required for charging the electric vehicle based on the basic information;

[0051] A feedback generation module is used to generate allocation information of charging positions based on the charging instruction, and feed back the allocation information to a user terminal corresponding to the electric vehicle.

[0052] In a third aspect, the present application provides a system for intelligently allocating charging stations in a residential area, which adopts the following technical solutions:

[0053] A community charging station intelligent allocation system includes electronic equipment, user terminals and charging station terminals;

[0054] The electronic device is communicatively connected with the user terminal and the charging terminal;

[0055] The electronic device is used to execute the method described in any one of the first aspects

[0056] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0057] A computer-readable storage medium stores a computer program that can be loaded by a processor and execute the method according to the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a flowchart of a method for intelligently allocating charging spaces in a cell according to an embodiment of the present application.

[0059] Figure 2 It is a flowchart of step S102 of an embodiment of the present application.

[0060] Figure 3 It is a flowchart of step S103 of an embodiment of the present application.

[0061] Figure 4 This is a structural block diagram of a cell charging space intelligent allocation device according to an embodiment of the present application.

[0062] Figure 5 This is a structural block diagram of an electronic device according to an embodiment of the present application.

[0063] Figure 6 This is a structural block diagram of a community charging station intelligent allocation system according to an embodiment of the present application. Implementation Method

[0064] The present application is further described in detail below with reference to the accompanying drawings.

[0065] The present invention provides a method for intelligently allocating charging spots in a residential area. This method can be executed by a device, which can be a server or a terminal device. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be, but is not limited to, a desktop computer.

[0066] like Figure 1 As shown, a method for intelligently allocating charging stations in a cell is implemented by a server. The main process of the method is described as follows (steps S101 to S103):

[0067] Step S101: acquiring basic information of the electric vehicle, including the remaining power of the electric vehicle.

[0068] The electric vehicle communicates wirelessly with a user terminal, which can be a mobile phone. The electric vehicle sends the remaining power to the user terminal, which then communicates wirelessly with a server, which then forwards the remaining power to the server.

[0069] Vehicle parameters can be input by the user on the user terminal. Vehicle parameters include battery capacity, on-board charger power and electric vehicle charging power. It is easy to understand that the larger the battery capacity, the longer the cruising range, and the longer the time required to charge; the greater the charging power of the electric vehicle, the faster the charging speed, and the shorter the charging time; when the charging position used by the electric vehicle is AC charging, the AC charging power depends on the on-board charger power.

[0070] In this embodiment, the basic information also includes the current location of the electric vehicle, and the current location of the electric vehicle can be collected through a GPS device on the electric vehicle.

[0071] Step S102: Generate a charging instruction for the electric vehicle based on the basic information.

[0072] like Figure 2 As shown, generating a charging instruction for the electric vehicle based on the basic information in step S102 includes the following processing:

[0073] Step S1021: Determine whether the current position of the electric vehicle is at a preset position. If so, proceed to step S1022.

[0074] The owner of an electric vehicle can enter a preset location through a user terminal. The preset location can be the community entrance or a distance ikm from the charging station. If the preset location is the community entrance, the electric vehicle's current location can also be determined by the community access control system. If the community access control system recognizes the electric vehicle's license plate, the electric vehicle's current location is the community entrance. ikm is the preset distance value, exemplarily 2km from the charging station.

[0075] Step S1022: Determine whether the remaining power is not greater than a preset power threshold. If so, proceed to step S1023.

[0076] In this embodiment, step S1022 includes the following processing: obtaining a preset power threshold corresponding to the electric vehicle; comparing the remaining power with the preset power threshold to determine whether the remaining power is not greater than the preset power threshold.

[0077] The process of obtaining the preset power threshold corresponding to the electric vehicle includes the following steps:

[0078] If the number of times the electric vehicle is charged is less than the number threshold, the initial power threshold is used as the preset power threshold.

[0079] The server has preset count thresholds and initial charge thresholds for the statistical period. If the number of times an electric vehicle has been charged within the statistical period is less than the count threshold, the electric vehicle may be newly purchased by the owner, and the initial charge threshold can be used as the preset charge threshold. For example, the statistical period is 5 days, the count threshold is 3 times, and the initial charge threshold is 30%.

[0080] If the number of times the electric vehicle is charged is not less than the number threshold, the charging habit information of the electric vehicle is obtained, where the charging habit information includes the historical remaining power of the electric vehicle during historical charging operations.

[0081] When an electric vehicle is frequently charged in a community, a preset power threshold can be set according to the owner's charging habits. For example, the owner's historical remaining power during the statistical period is 40%.

[0082] The initial power threshold is revised based on the historical remaining power, and the revised power threshold is used as the preset power threshold.

[0083] The initial power threshold is corrected to the historical remaining power. For example, 40% of the historical remaining power is used as the preset power threshold. The preset power threshold is set according to the owner's personalized charging habit information, which improves the rationality of the preset power threshold setting.

[0084] In this embodiment, before the initial power threshold is used as the preset power threshold, the following processing is also included: determining whether the owner of the electric vehicle is associated with other electric vehicles whose charging times are not less than the times threshold; if so, obtaining the charging habit information of other associated electric vehicles, and executing the step of correcting the initial power threshold based on the historical remaining power; if not, executing the step of using the initial power threshold as the preset power threshold.

[0085] In a community, there are cases where the same owner is associated with multiple electric vehicles. When the owners of multiple electric vehicles are the same, the charging habits of the electric vehicles are also the same. Therefore, the preset power threshold of a newly purchased electric vehicle whose charging times are less than the times threshold can be corrected according to the charging habit information of other associated electric vehicles.

[0086] In this embodiment, after step S1022, the following processing is further included:

[0087] If the remaining power is greater than a preset power threshold, the subsequent travel plan of the electric vehicle and the historical power consumption information of the electric vehicle are obtained.

[0088] The driver can input their subsequent travel plan after returning to the community through the input unit; the user terminal can also automatically identify the work schedule in the work software and automatically obtain the subsequent travel plan. The travel plan includes the starting point of the departure, the return destination, and the distance between the starting and end points.

[0089] When the remaining power of the electric vehicle is greater than a preset power threshold but the electric vehicle needs to go out later, the remaining power of the electric vehicle may not be sufficient to support the entire planned trip.

[0090] The power consumption of the planned trip is calculated based on the planned trip and historical power consumption information.

[0091] Historical power consumption information includes power consumption per unit mileage, where power consumption = distance between the starting point and the end point / power consumption per unit mileage.

[0092] If the difference between the remaining power and the power consumption of the trip plan is less than the prompt threshold, a prompt message indicating that the electric vehicle has insufficient power is generated and sent to the user terminal.

[0093] The difference is the remaining power minus the power consumption. The server has a preset prompt threshold, which can be 0. The user terminal feeds back the prompt information to the car owner in the form of a pop-up message or vibration reminder.

[0094] Step S1023: Generate a charging instruction for the electric vehicle to be charged.

[0095] The server automatically generates charging instructions based on the basic information of electric vehicles, thereby improving the automation level of charging space allocation in the community.

[0096] Step S103: generating allocation information of charging positions based on the charging instruction, and feeding back the allocation information to the user terminal corresponding to the electric vehicle.

[0097] The charging position can be an idle charging position in the community or all charging positions. Car owners can reach the assigned charging position for charging according to the allocation information of the user terminal, thereby reducing the time spent by car owners in finding charging positions and improving the convenience of charging electric vehicles.

[0098] The allocation information includes charging position number information and location guidance information. The server can draw a guidance route based on the current location of the electric vehicle and the location information of the charging position, so as to facilitate the owner to reach the allocated charging position for charging.

[0099] like Figure 3 As shown, in this embodiment, generating the charging position allocation information in step S103 further includes the following processing:

[0100] Step S1031: Score each charging position and obtain the optimal charging position based on the scoring results.

[0101] In this embodiment, the charging position with the smallest score among the multiple charging positions is the optimal charging position.

[0102] Step S1032: Generate allocation information based on the optimal charging position.

[0103] Each charging position is scored based on a number of inspection parameters, and the optimal charging position is allocated according to the scoring results, making the allocation of charging positions more reasonable.

[0104] The parameters considered when scoring the charging station include the charging period being staggered with the peak charging period of the charging station, the distance information between the charging station and the address pre-stored in the user terminal, and the first estimated time for the electric vehicle to leave the charging station after charging is completed.

[0105] Among them, the charging period is the time period between the start of charging and the completion of charging. The charging start time can be the current time or the preferred time selected or input by the car owner; the car owner can input the pre-stored address through the input unit connected to the user terminal. The pre-stored address can be the car owner's home address.

[0106] In this embodiment, step S1031 further includes the following processing:

[0107] Step a1: Calculate the required charging period for the electric vehicle based on the remaining power and the charging power.

[0108] The time required to charge the electric vehicle is calculated based on the remaining power and charging function, and then the required charging period is calculated based on the time when charging starts.

[0109] Step b1: Determine whether the charging period is staggered with the peak charging period of the charging station. If so, proceed to step c1; if not, proceed to step d1.

[0110] The peak charging period of each charging position is obtained based on the statistical data of the charging position occupancy data statistical unit electrically connected to the server for counting the occupancy time information of each charging position. When the inspection parameters of other items are the same, the charging positions with charging periods staggered from the peak charging periods are selected for allocation, thereby improving the utilization efficiency of the charging positions.

[0111] Step c1: Get a first score.

[0112] Step d1: Obtain a second score.

[0113] The first score and the second score are preset values ​​in the server. The first score is smaller than the second score. For example, the first score is 0.5 and the second score is 1.5.

[0114] Step e1: Obtain the distance information between the charging position and the address pre-stored in the user terminal.

[0115] Step f1: obtaining a first estimated time for the electric vehicle to leave the charging station after charging is completed based on the charging habit information.

[0116] Charging habit information includes the multiple times the owner takes to drive the electric vehicle away from the charging station after a reminder message indicating that charging of the electric vehicle is complete is sent to the owner during a statistical period. Since the distance from the owner's pre-stored address to the charging station is known, the owner's habitual travel speed can be calculated based on the time and distance.

[0117] The first estimated departure time is t=s / v, where s is the distance between the pre-stored address and the charging location of the electric vehicle, and v is the owner's usual driving speed.

[0118] Step g1: Perform weighted calculation on the distance information of the charging position and the first estimated departure time, respectively, and sum them to obtain a third score, and calculate the sum of the third score and the first score or the second score.

[0119] In this embodiment, to ensure scoring accuracy, the units of the assessment parameters need to be standardized. The distance information is measured in kilometers, and the first estimated time to depart is measured in minutes. The server has preset weights for the distance information and the first estimated time to depart for each charging station. For example, the weight for the distance information is 0.4, and the weight for the first estimated time to depart is 0.6.

[0120] If there are four charging stations, including two charging stations whose charging periods are staggered with the charging peak period and two charging stations whose charging periods are not staggered with the charging peak period, the specific scoring situation is:

[0121] The evaluation parameters for a charging station that is staggered from the peak charging period include: distance information of 1 km, first estimated departure time of 30 minutes, and the score of the charging station is 1*0.4+30*0.6+0.5=18.9.

[0122] The evaluation parameters for a charging station that is staggered from the peak charging period include: distance information of 2 km, first estimated departure time of 20 minutes, and the score of this charging station is 2*0.4+20*0.6+0.5=13.3.

[0123] For another charging station whose charging period does not coincide with the peak charging period, the assessment parameters include: distance information of 1 km, and first estimated departure time of 30 minutes. In this case, the score of this charging station is 1*0.4+30*0.6+1.5=19.9.

[0124] The assessment parameters for another charging station whose charging period does not coincide with the peak charging period include: distance information of 2 km and first estimated departure time of 20 minutes. The score of this charging station is 2*0.4+20*0.6+1.5=14.3.

[0125] Since 19.9>18.9>14.3>13.3, the optimal charging position is the charging position with a score of 13.3.

[0126] If the charging positions are all the charging positions in the community, as another optional implementation of this embodiment, if there are other electric vehicles parked at the charging positions that are charging, the examination parameters for scoring the charging positions also include the second estimated departure time of other electric vehicles from the charging positions. The second estimated departure time can be calculated based on the charging habit information of the owner of the electric vehicle. The calculation method is consistent with the calculation method of the first estimated departure time, and will not be repeated here.

[0127] The difference from the above embodiment is that if there are other electric vehicles being charged parked at the charging station, step g1 includes the following processing:

[0128] The distance information of the charging position, the first estimated time to leave, and the second estimated time to leave are weightedly calculated and summed to obtain a fourth score, and the sum of the fourth score and the first score or the second score is calculated.

[0129] For example, the weight corresponding to distance information is 0.2, the weight corresponding to the first estimated time to depart is 0.4, and the weight corresponding to the second estimated time to depart is 0.4. If the distance information is x km, the first estimated time to depart is y min, and the second estimated time to depart is z min, the charging spot score is x*0.2+y*0.4+z*0.4+0.5 or x*0.2+y*0.4+z*0.4+1.5.

[0130] Based on the same technical concept, the present application also provides a cell charging position intelligent allocation device, such as Figure 4 As shown, the intelligent charging space allocation device 200 for a residential area mainly includes:

[0131] The first acquisition module 201 is configured to acquire basic information of the electric vehicle, where the basic information includes the remaining power of the electric vehicle.

[0132] The generation calculation module 202 is used to generate a charging instruction required for charging the electric vehicle based on the basic information.

[0133] The feedback generation module 203 is configured to generate allocation information of charging positions based on the charging instruction, and feed back the allocation information to the user terminal corresponding to the electric vehicle.

[0134] Optionally, the feedback generation module 203 includes:

[0135] The scoring submodule is used to score each charging position and obtain the optimal charging position based on the scoring results;

[0136] The first generating submodule is configured to generate allocation information based on the optimal charging position.

[0137] Optionally, the scoring submodules include:

[0138] A first calculation submodule is used to calculate the charging period required for the electric vehicle based on the remaining power and the charging power;

[0139] A first obtaining submodule is configured to obtain a first score when the charging period is staggered with the charging peak period of the charging position;

[0140] A second obtaining submodule is used to obtain a second score when the charging period does not stagger the charging peak period of the charging position;

[0141] The first acquisition submodule is used to obtain distance information between the charging position and the address pre-stored in the user terminal;

[0142] The second acquisition submodule is used to obtain a first estimated time for the electric vehicle to leave the charging position after charging is completed based on the charging habit information;

[0143] The second calculation submodule is configured to perform weighted calculations on the distance information of the charging position and the first estimated departure time, respectively, and sum the sums to obtain a third score, and calculate the sum of the third score and the first score or the second score.

[0144] Optionally, the generating calculation module 202 includes:

[0145] A first judgment submodule is used to judge whether the current position of the electric vehicle is at a preset position;

[0146] The second judgment submodule is used to judge whether the remaining power is not greater than a preset power threshold;

[0147] The second generating submodule is used to generate a charging instruction required for charging the electric vehicle.

[0148] Optionally, the second judgment submodule includes:

[0149] The third acquisition submodule is used to obtain a preset power threshold corresponding to the electric vehicle;

[0150] The third judgment submodule is used to compare the remaining power with a preset power threshold to determine whether the remaining power is not greater than the preset power threshold;

[0151] Optionally, the third acquisition submodule includes:

[0152] As a submodule, it is used to use the initial power threshold as the preset power threshold when the number of times the electric vehicle is charged is less than the number threshold;

[0153] a fourth acquisition submodule, configured to acquire charging habit information of the electric vehicle when the number of times the electric vehicle has been charged is not less than a number threshold, the charging habit information including historical remaining power of the electric vehicle during historical charging operations;

[0154] The correction submodule is used to correct the initial power threshold based on the historical remaining power, and use the corrected power threshold as the preset power threshold.

[0155] Optionally, also include:

[0156] A second acquisition module is used to acquire a subsequent travel plan of the electric vehicle and historical power consumption information of the electric vehicle when the remaining power is greater than a preset power threshold;

[0157] A calculation module, configured to calculate the power consumption of the planned trip based on the planned trip and historical power consumption information;

[0158] The generating and sending module is used to generate a prompt message indicating that the electric vehicle has insufficient power when the difference between the remaining power and the power consumption of the trip plan is less than a prompt threshold, and send the prompt message to the user terminal.

[0159] Optionally, also include:

[0160] A judgment module, used to judge whether the owner of the electric vehicle is associated with other electric vehicles whose charging times are not less than a threshold number;

[0161] An acquisition execution module, configured to obtain charging habit information of other associated electric vehicles and execute a step of correcting the initial power threshold based on historical remaining power;

[0162] The module is executed to execute the step of using the initial power threshold as the preset power threshold.

[0163] In one example, the module in any of the above devices can be one or more integrated circuits configured to implement the above methods, such as: one or more application specific integrated circuits (ASICs), or one or more digital signal processors (DSPs), or one or more field programmable gate arrays (FPGAs), or a combination of at least two of these integrated circuit forms.

[0164] For another example, when the modules in the device can be implemented in the form of a processing element scheduling program, the processing element can be a general-purpose processor, such as a central processing unit (CPU) or other processor capable of calling programs. For another example, these modules can be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0165] Various objects such as various messages / information / equipment / network elements / systems / devices / actions / operations / processes / concepts that may appear in this application are named. It can be understood that these specific names do not constitute a limitation on the relevant objects. The names assigned may change with factors such as scenarios, contexts or usage habits. The understanding of the technical meaning of the technical terms in this application should be mainly determined from the functions and technical effects embodied / executed in the technical solutions.

[0166] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and modules described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0167] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0168] Based on the same technical concept, the present application also provides an electronic device, such as Figure 5 As shown, the electronic device 300 includes a processor 301 and a memory 302 , and may further include an information input / information output (I / O) interface 303 , one or more communication components 304 , and a communication bus 305 .

[0169] The processor 301 is used to control the overall operation of the electronic device 300 to complete all or part of the steps in the above-mentioned method for intelligently allocating charging spots in a cell. The memory 302 is used to store various types of data to support the operation of the electronic device 300. Such data may include, for example, instructions for any application or method operating on the electronic device 300, as well as application-related data. The memory 302 may be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as one or more of static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0170] The I / O interface 303 provides an interface between the processor 301 and other interface modules, which may be a keyboard, a mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 304 is used to test wired or wireless communication between the electronic device 300 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more thereof, therefore, the corresponding communication component 104 may include: Wi-Fi components, Bluetooth components, NFC components.

[0171] Communication bus 305 may include a path for transmitting information between the aforementioned components. Communication bus 305 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, for example. Communication bus 305 may be divided into an address bus, a data bus, a control bus, and the like.

[0172] The electronic device 300 can be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to execute the method for intelligently allocating charging positions in a cell provided in the above embodiment.

[0173] The electronic device 300 may include, but is not limited to, mobile terminals such as digital broadcast receivers, PDAs (Personal Digital Assistants), and PMPs (Portable Multimedia Players), and fixed terminals such as digital TVs and desktop computers, and may also be servers.

[0174] Based on the same technical concept, this application also provides a community charging station intelligent allocation system, such as Figure 6 As shown, the community charging position intelligent allocation system 400 includes the above-mentioned electronic device 300. In this embodiment, the electronic device 300 is a server 401. The community charging position intelligent allocation system 400 also includes a user terminal 402 and a charging position terminal 403. The server 401 is communicatively connected with the user terminal 402 and the charging position terminal 403. The server 401 is used to execute the above-mentioned community charging position intelligent allocation method.

[0175] The electric vehicle is provided with a power monitoring unit, which is in communication with the user terminal 402 . The power monitoring unit acquires the remaining power of the electric vehicle and outputs it to the user terminal 402 .

[0176] The user terminal 402 is electrically connected to an input unit, and the owner of the electric vehicle can input information such as vehicle parameters, pre-stored addresses, and travel plans through the input unit.

[0177] The charging terminal 403 is electrically connected to a status monitoring unit for monitoring the usage status of each charging position in the community. The status monitoring unit can update and calculate the remaining charging time of the electric vehicle currently being charged in real time and output it to the charging terminal 403.

[0178] The server 401 is electrically connected to a vehicle information storage unit for storing vehicle information of each electric vehicle. The vehicle information is information input by the vehicle owner through an input unit.

[0179] The charging terminal 403 is electrically connected to a charging status prompt unit for obtaining the charging status of the electric vehicle in real time. The charging terminal 403 sends the charging status of the electric vehicle to the server 401, and the server 401 forwards the charging status of the electric vehicle to the user terminal 402. When the electric vehicle battery is fully charged, the owner is prompted to drive the electric vehicle away from the charging position in time.

[0180] The server 401 is electrically connected to a charging position occupancy data statistics unit for counting the occupancy time information of each charging position. The charging position occupancy data statistics unit can collect statistics on the charging occupancy status of each charging position in each time period.

[0181] The server 401 is electrically connected to a car owner's charging habit statistics unit, which is used to count the charging habit information of the car owner, such as the time between the time when the car owner receives the reminder that the electric car battery is fully charged and the time when the car is driven away.

[0182] Based on the same technical concept, the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned method for intelligent allocation of charging positions in a cell are implemented.

[0183] The computer-readable storage medium may include: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc., which can store program codes.

[0184] The terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0185] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of application involved in this application is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the aforementioned application concept. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions applied for in this application.

Claims

1. A method for intelligently allocating charging stations in a residential area, characterized in that: include: Acquiring basic information of the electric vehicle, wherein the basic information includes the remaining power of the electric vehicle; Generate a charging instruction for the electric vehicle based on the basic information; generating allocation information of the charging position based on the charging instruction, and feeding back the allocation information to a user terminal corresponding to the electric vehicle; The generating of the charging position allocation information includes: Scoring each of the charging positions, and obtaining an optimal charging position based on the scoring results; generating the allocation information based on the optimal charging position; The basic information includes vehicle parameters, and the vehicle parameters include charging power; Scoring each charging position includes: Calculating a required charging period for the electric vehicle based on the remaining power and the charging power; If the charging period is staggered with the peak charging period of the charging position, a first score is obtained; If the charging period does not stagger with the peak charging period of the charging position, a second score is obtained; Obtaining distance information between the charging position and a pre-stored address in the user terminal; Obtaining a first estimated time for the electric vehicle to leave the charging position after charging is completed based on the charging habit information; A weighted calculation is performed on the distance information of the charging position and the first estimated departure time, and the sum of the two scores is calculated to obtain a third score, and a sum of the third score and the first score or the second score is calculated.

2. The method according to claim 1, characterized in that The basic information also includes the current location of the electric vehicle; The generating of a charging instruction for the electric vehicle based on the basic information includes: Determining whether the current position of the electric vehicle is at a preset position; If so, determining whether the remaining power is not greater than a preset power threshold; If so, a charging instruction is generated for charging the electric vehicle.

3. The method according to claim 2, characterized in that Determining whether the remaining power is not greater than a preset power threshold includes: Obtaining the preset power threshold corresponding to the electric vehicle; Comparing the remaining power with the preset power threshold to determine whether the remaining power is not greater than the preset power threshold; Wherein, obtaining the preset power threshold corresponding to the electric vehicle includes: If the number of times the electric vehicle is charged is less than the number threshold, the initial power threshold is used as the preset power threshold; If the number of times the electric vehicle has been charged is not less than the number threshold, obtaining charging habit information of the electric vehicle, the charging habit information including historical remaining power of the electric vehicle during historical charging operations; The initial power threshold is revised based on the historical remaining power, and the revised power threshold is used as the preset power threshold.

4. The method according to claim 2, characterized in that After determining whether the remaining power is not greater than a preset power threshold, the method further includes: If the remaining power is greater than the preset power threshold, obtaining a subsequent travel plan of the electric vehicle and historical power consumption information of the electric vehicle; calculating the power consumption of the trip plan based on the trip plan and the historical power consumption information; If the difference between the remaining power and the power consumption of the trip plan is less than a prompt threshold, a prompt message indicating that the electric vehicle has insufficient power is generated and the prompt message is sent to a user terminal.

5. The method according to claim 3, characterized in that Before using the initial power threshold as the preset power threshold, the method further includes: Determining whether the owner of the electric vehicle is associated with other electric vehicles whose charging times are not less than the threshold number; If so, obtaining the charging habit information of other associated electric vehicles and executing the step of correcting the initial power threshold based on the historical remaining power; If not, the step of using the initial power threshold as the preset power threshold is executed.

6. A smart charging station allocation device for a residential area, characterized in that: include: A first acquisition module is used to acquire basic information of the electric vehicle, wherein the basic information includes the remaining power of the electric vehicle; A generating calculation module is used to generate a charging instruction required for charging the electric vehicle based on the basic information; A feedback generation module is used to generate allocation information of charging positions based on the charging instruction, and feed back the allocation information to a user terminal corresponding to the electric vehicle; The feedback generation module includes: The scoring submodule is used to score each charging position and obtain the optimal charging position based on the scoring results; A first generating submodule, configured to generate allocation information based on an optimal charging position; The scoring submodule includes: A first calculation submodule is used to calculate the charging period required for the electric vehicle based on the remaining power and the charging power; A first obtaining submodule is configured to obtain a first score when the charging period is staggered with the charging peak period of the charging position; A second obtaining submodule is used to obtain a second score when the charging period does not stagger the charging peak period of the charging position; The first acquisition submodule is used to obtain distance information between the charging position and the address pre-stored in the user terminal; The second acquisition submodule is used to obtain a first estimated time for the electric vehicle to leave the charging position after charging is completed based on the charging habit information; The second calculation submodule is configured to perform weighted calculations on the distance information of the charging position and the first estimated departure time, respectively, and sum the sums to obtain a third score, and calculate the sum of the third score and the first score or the second score.

7. A community charging station intelligent allocation system, characterized by: including electronic equipment, user terminals and charging station terminals; The electronic device is communicatively connected with the user terminal and the charging terminal; The electronic device is configured to execute the method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 5.

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