Charging station intelligent management system

Abstract

The invention relates to the technical field of charging stations, and particularly discloses a charging station intelligent management system, which comprises an information acquisition module used for acquiring vehicle registration information of a parking lot without charging pile installation conditions in a preset range; the entry and exit management module is used for screening out license plate numbers of the fuel vehicles from the vehicle registration information and marking the license plate numbers as potential users; the image recognition module is used for acquiring monitoring image data of the station, acquiring vehicle images of potential customers from the monitoring image data and recognizing vehicle models according to the vehicle images; the identification module is also used for identifying and recording whether the potential customer leaves the vehicle; the entrance and exit identification module is also used for recording the exit time of the potential customers and recording the visiting duration according to the entrance time and the exit time of the charging station; the analysis module is used for analyzing the car changing probability of the potential user according to the visiting duration of the potential user, the car model and the information of whether the potential user leaves the car or not, wherein the car changing probability comprises high, medium or low. By adopting the technical scheme of the invention, potential customers can be effectively identified and the car changing willingness of the customers can be predicted.

Description

Technical Field

[0001] The present invention relates to the technical field of charging stations, and in particular to an intelligent management system for charging stations. Background Art

[0002] With the popularization of new energy vehicles, charging stations, as important supporting infrastructure, have received extensive attention for their construction and operation. However, in some old communities, units and other areas where there are no conditions for installing charging piles, users of fuel vehicles have gradually shown a potential willingness to replace new energy vehicles, but due to the lack of accurate user demand prediction and management, the charging needs in these areas are often difficult to meet in a timely manner. Traditional charging station management systems mainly focus on the services of new energy vehicles, and lack targeted analysis for non-new energy vehicle users, making it difficult for operators to reasonably plan resources, and the construction of basic settings cannot match actual needs, which easily leads to a situation where it is difficult to find a pile, affecting the promotion of new energy vehicles.

[0003] In this context, in order to effectively tap into the replacement needs of fuel vehicle users, improve the operational efficiency of charging stations, and help operators plan and expand charging stations in advance, there is an urgent need for an intelligent management system that can effectively identify potential customers and predict their willingness to replace vehicles. Summary of the invention

[0004] The present invention provides an intelligent management system for charging stations, which can effectively identify potential customers and predict their willingness to change vehicles.

[0005] In order to solve the above technical problems, this application provides the following technical solutions:

[0006] An intelligent management system for a charging station, comprising an information acquisition module, an entry and exit management module, an entry and exit identification module, an inspection module, an image recognition module and an analysis module;

[0007] An information acquisition module is used to obtain vehicle registration information of parking lots within a preset range that do not have charging pile installation conditions; vehicle registration information includes license plate number and vehicle type; vehicle type includes new energy vehicles and fuel vehicles;

[0008] The entry and exit management module is used to filter out the license plate numbers of fuel vehicles from the vehicle registration information and mark them as potential users;

[0009] The entry and exit identification module is used to collect the license plate number of the vehicle entering the venue, compare it with the vehicle registration information, and determine whether it is a potential customer. If it is a potential customer, the access information of the potential user is generated;

[0010] An image recognition module is used to obtain monitoring image data of the station, obtain the vehicle image of the potential customer from the monitoring image data, and identify the vehicle model based on the vehicle image; it is also used to identify whether the potential customer has left the vehicle and record it;

[0011] The entry and exit recognition module is also used to record the exit time of potential customers, and record the duration of the visit based on the entry and exit time of the charging station;

[0012] The analysis module is used to analyze the vehicle-changing probability of potential users based on the information of the potential customers' visit duration, vehicle model, and whether they leave the vehicle. The vehicle-changing probability includes: high, medium, or low.

[0013] Furthermore, the analysis module is also used to classify the interest level of potential customers according to the duration of the visit and assign a score;

[0014] Determine the launch year of fuel vehicles based on vehicle model and assign a score;

[0015] Analyze and assign scores based on whether the customer leaves the vehicle:

[0016] Weights are assigned to the visit duration, vehicle model, and whether the vehicle is left, and the vehicle change probability is calculated based on the weights.

[0017] Furthermore, the analysis module calculates the comprehensive score by the formula:

[0018] Comprehensive score = (visit duration score × weight 1) + (vehicle model score × weight 2) + (whether to leave the vehicle score × weight 3)

[0019] The probability of changing cars is finally divided according to the comprehensive score, where the higher the comprehensive score, the higher the probability of changing cars.

[0020] Furthermore, it also includes a charging parking space management module, which is used to monitor the usage status of the charging pile in real time, including whether the charging pile is idle; if it is idle, determine whether there is a vehicle occupying the charging pile parking space; if it is not idle, obtain the license plate number, vehicle model, current battery power and charging power of the new energy vehicle being charged, and estimate the charging completion time based on the current battery power and charging power.

[0021] Furthermore, it also includes a charging reservation module, which is used to receive the user's charging reservation information, the charging reservation information includes options such as the reserved charging time period and charging power, and is also used to obtain the usage status information of the charging pile and allocate a charging parking space for the user; it is also used to release the allocated charging parking space when the user fails to arrive on time or park in the reserved charging time period.

[0022] Furthermore, the information acquisition module is also used to obtain vehicle entry and exit information of parking lots that do not have charging pile installation conditions within a preset range;

[0023] The analysis module is also used to determine whether the potential customer's visit method is a specific visit based on the potential customer's entry and exit time at the charging station and the vehicle entry and exit information of the corresponding parking lot, and if so, determine the actual journey time;

[0024] The analysis module is also used to estimate the round trip time based on the location of the charging station and the corresponding parking lot; it is also used to determine whether the difference between the real-time travel time of the potential user and the estimated round trip time is within a preset range, and if so, determine it as a single destination;

[0025] The analysis module is also used to analyze the car change cycle of potential users based on information about whether the potential destination is a single destination. If it is a single destination, the car change cycle is less than a preset cycle. If it is not a single destination, the car change cycle is greater than the preset cycle.

[0026] This solution obtains vehicle registration information of parking lots that do not have the conditions for installing charging piles within a preset range, identifies potential customers, and conducts a comprehensive analysis of the potential customers' behavior before and after entering the parking lot to understand the probability and cycle of potential users' vehicle replacement. It can provide reliable data support for the expansion and layout of charging stations, and further promote the marketization of new energy vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 The present invention is a logic block diagram of a first embodiment of an intelligent management system for charging stations. DETAILED DESCRIPTION

[0028] The following is further described in detail through specific implementation methods:

[0029] Embodiment 1

[0030] like Figure 1 As shown, a charging station intelligent management system of this embodiment includes an information acquisition module, an entry and exit management module, an entry and exit identification module, an inspection module, an image recognition module and an analysis module.

[0031] The information acquisition module is used to obtain vehicle registration information of parking lots that do not have charging pile installation conditions within a preset range; vehicle registration information includes license plate number and vehicle type; vehicle types include new energy vehicles and fuel vehicles; for example, if the preset range is 2km, then vehicle registration information of parking lots (community parking lots, unit parking lots) that do not have charging pile installation conditions within 2km is obtained. In this solution, a cooperative relationship is established with the corresponding parking lot, such as the corresponding parking lot vehicles paying commissions to the parking lot management party when they charge at this charging station, etc., to achieve a win-win business.

[0032] The entry and exit management module is used to filter out the license plate numbers of fuel vehicles from the vehicle registration information and mark them as potential users;

[0033] The entry and exit identification module is used to collect the license plate number of the vehicle entering the station, compare it with the vehicle registration information, and determine whether the customer is a potential customer. If so, the access information of the potential user is generated; if not, it is determined whether it is a new energy vehicle. If not, a closed prompt is generated to prevent other fuel vehicles from entering the charging station and occupying parking spaces ineffectively.

[0034] The inspection module is used to receive access information and screen whether there is an inspection personnel at the current station. If there is, send the potential customer's license plate number to the inspection personnel; receive the inspection personnel's feedback on the potential customer; the feedback information includes the potential customer's purpose of entering the charging station, car replacement plan information, car replacement time information, car replacement type information, etc. For example, the customer's purpose of entering the charging station: to investigate the convenience of charging, car replacement plan information: there is a car replacement plan, car replacement time information: plan to replace the car within half a year, and car replacement type information: replace a plug-in hybrid vehicle.

[0035] The image recognition module is also used to obtain the monitoring image data of the station when there is no inspection personnel at the current station, obtain the vehicle image of the potential customer from the monitoring image data, and identify the vehicle model based on the vehicle image; it is also used to identify whether the potential customer has left the vehicle and record it;

[0036] The entry and exit recognition module is also used to record the exit time of potential customers, and record the duration of the visit based on the entry and exit time of the charging station;

[0037] The analysis module is used to determine whether there is feedback information from potential customers. If so, the vehicle replacement probability of the potential user is analyzed based on the feedback information.

[0038] If there is no feedback information, the potential user's probability of changing cars is analyzed based on the potential customer's visit duration, vehicle model, and whether they left the vehicle. The probability of changing cars includes: high, medium, or low;

[0039] Specifically, when analyzing the probability of potential users changing their cars based on feedback information, potential customers who plan to change their cars within six months are identified as having a high probability of changing their cars;

[0040] When there is no feedback information, the analysis module is used to grade the interest level of potential customers according to the duration of the visit and assign scores; for example: short stay (less than 2 minutes): low probability of changing cars, 1 point; medium stay (2 minutes-5 minutes): medium probability of changing cars, 3 points; long stay (more than 5 minutes): high probability of changing cars, 5 points.

[0041] Determine the launch year of fuel vehicles based on vehicle models and assign a score: for example, if launched in 2014 or earlier, the probability of vehicle replacement is high, 5 points; if launched between 2015 and 2020, the probability of vehicle replacement is medium, 3 points; if launched after 2021, the probability of vehicle replacement is low, 1 point;

[0042] Analyze and assign scores based on whether the customer leaves the vehicle: For example, if the customer does not leave the vehicle, the probability of changing the vehicle is low, 1 point; if the customer leaves the vehicle for less than 2 minutes, the probability of changing the vehicle is medium, 2 points; if the customer leaves the vehicle for more than 2 minutes, the probability of changing the vehicle is high, 3 points;

[0043] Assign weights to the duration of the visit, the vehicle model, and whether the person leaves the vehicle, and calculate the vehicle change probability based on the weights. In this embodiment, the weight 1 of the duration of the visit is 50%, the weight 2 of the vehicle model is 30%, and the weight 3 of whether the person leaves the vehicle is 20%.

[0044] The comprehensive score is calculated by the formula:

[0045] Comprehensive score = (visit duration score × 0.5) + (vehicle model score × 0.3) + (whether to leave the vehicle score × 0.2)

[0046] The higher the comprehensive score, the higher the probability of changing the car. In this embodiment, the comprehensive score is finally divided into the following levels:

[0047] 4.0≤Comprehensive score≤5.0, high probability

[0048] 2.5≤Comprehensive score<4.0, medium probability

[0049] Comprehensive score <2.5, low probability.

[0050] The analysis module is also used to count and output the number of users who have a high probability of changing cars at the charging station within a preset time. The preset time is, for example, one month.

[0051] The solution of this embodiment uses intelligent data analysis and management to accurately identify potential customers (fuel vehicle users) in parking lots near charging stations that do not have the conditions for installing charging piles, and uses multi-dimensional data to comprehensively evaluate their willingness to change vehicles, providing a scientific decision-making basis for charging station operators. Through the hierarchical analysis of the probability of changing vehicles, an accurate reference is provided for the early expansion of charging stations, which is particularly suitable for special scenarios such as old communities and units, and solves the problem of predicting charging demand in the process of converting fuel vehicles to new energy vehicles. In addition, this solution combines key data such as vehicle model, residence time, and user behavior to dynamically count potential market trends to ensure that operators can quickly respond to market changes and optimize facility layout.

[0052] In summary, this solution not only improves the intelligent management level of charging stations, but also provides strong support for the promotion and popularization of new energy vehicles. At the same time, through the detailed analysis of customer behavior, it enhances customer experience, further promotes the promotion of green energy, and contributes to the development of a low-carbon society.

[0053] Embodiment 2

[0054] The difference between this embodiment and the first embodiment is that this embodiment includes a charging parking space management module and a charging reservation module.

[0055] The charging management module is used to monitor the usage status of the charging pile in real time, including whether the charging pile is idle; if it is idle, determine whether there is a vehicle occupying the charging pile parking space; if it is not idle, obtain the license plate number, vehicle model, current battery power and charging power of the new energy vehicle being charged, and estimate the charging completion time based on the current battery power and charging power. In this embodiment, vehicle occupation refers to the failure to drive away the vehicle in time after charging is completed.

[0056] The charging reservation module is used to receive the user's charging reservation information, which includes options such as the scheduled charging time period and charging power. It is also used to obtain the usage status information of the charging pile and allocate a charging parking space for the user. It is also used to release the allocated charging parking space when the user fails to arrive or park on time during the scheduled charging period.

[0057] Embodiment 3

[0058] The difference between this embodiment and the first embodiment is that the information acquisition module in this embodiment is also used to obtain vehicle entry and exit information of parking lots that do not have charging pile installation conditions within a preset range;

[0059] The analysis module is also used to determine whether the potential customer's visit method is a specific visit based on the potential customer's entry and exit time at the charging station and the vehicle entry and exit information of the corresponding parking lot. If so, determine the actual journey time. The specific visit method means starting from the parking lot to the charging station, and then charging at the charging station and returning to the parking lot. The actual journey time is the sum of the time for the two round trips.

[0060] The analysis module is also used to estimate the round-trip travel time based on the location of the charging station and the corresponding parking lot; the estimated travel time can be connected to the existing navigation software to obtain the corresponding path planning time. It is also used to determine whether the difference between the potential user's real-time travel time and the estimated round-trip travel time is within a preset range. If so, it is determined as a single destination.

[0061] The analysis module is also used to analyze the car change cycle of the potential user according to the information of whether the potential destination is a single destination. If it is a single destination, the car change cycle is less than the preset cycle, and if it is not a single destination, the car change cycle is greater than the preset cycle. In this embodiment, the preset cycle is set by the management personnel according to the market research results, for example, 3 months.

[0062] This embodiment combines the location data of the charging station and the corresponding parking lot and the actual travel time to accurately determine the visit method and travel time of potential customers, and accurately identify whether the potential customer's visit is driven by a specific purpose (specially visiting the charging station). This analysis method effectively avoids the interference of multi-destination visits on the prediction of the car replacement cycle, making the evaluation of the car replacement cycle more scientific and reasonable.

[0063] Embodiment 4

[0064] The difference between this embodiment and the second embodiment is that, in this embodiment, the analysis module is also used to analyze the visiting time period according to the visiting time of each potential user; in this embodiment, a day is divided into several fixed time periods (for example, every hour), an interval sequence of entry time periods is generated, the number of potential customers in each time period is counted, a mapping relationship between the time period and the number of people is generated, and the time period with the largest number of people is found as the visiting time period.

[0065] The analysis module is also used to detect the entry of potential users during the visiting period, and to determine whether there are new energy vehicles in the same parking lot as potential users according to the license plate number of the new energy vehicles being charged. If there are, they are screened out and marked;

[0066] The analysis module is also used to determine, based on monitoring image data analysis, whether the potential user has communicated with the marked new energy vehicle owner when the potential customer leaves the vehicle. If so, determine whether the communication duration exceeds the set time and record it if it exceeds the set time. The charging management module is also used to reduce or exempt the charging amount when the charging of the new energy vehicle with communication records is completed and a charging order is generated.

[0067] This embodiment analyzes the visiting time and time distribution of potential users, identifies the time periods when potential customers frequently visit, and provides a basis for optimizing service resources at charging stations during key time periods. By marking the communication behavior between potential users and new energy vehicle owners, the factors affecting the decision-making of potential customers' social interaction on vehicle replacement are explored, and the communication duration is included in the analysis scope. Combined with the charging amount reduction mechanism, it encourages new energy vehicle owners to communicate with potential customers and helps potential users understand the actual situation of charging stations.

[0068] The above are only embodiments of the present invention. The invention is not limited to the fields involved in this implementation case. The common sense such as the known specific structures and characteristics in the scheme is not described in detail here. The ordinary technicians in the relevant field know all the common technical knowledge in the technical field to which the invention belongs before the application date or the priority date, can obtain all the existing technologies in the field, and have the ability to apply the conventional experimental means before that date. The ordinary technicians in the relevant field can improve and implement this scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for ordinary technicians in the relevant field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, which will not affect the effect of the implementation of the present invention and the practicality of the patent. The protection scope required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to explain the content of the claims.

Claims

1. An intelligent management system for charging stations, characterized in that: It includes information acquisition module, entry and exit management module, entry and exit identification module, inspection module, image recognition module and analysis module; An information acquisition module is used to obtain vehicle registration information of parking lots that do not have charging pile installation conditions within a preset range; Vehicle registration information includes license plate number and vehicle type; vehicle types include new energy vehicles and fuel vehicles; The entry and exit management module is used to filter out the license plate numbers of fuel vehicles from the vehicle registration information and mark them as potential users; The entry and exit identification module is used to collect the license plate number of the vehicle entering the venue, compare it with the vehicle registration information, and determine whether it is a potential customer. If it is a potential customer, the access information of the potential user is generated; An image recognition module is used to obtain monitoring image data of the station, obtain the vehicle image of the potential customer from the monitoring image data, and identify the vehicle model based on the vehicle image; it is also used to identify whether the potential customer has left the vehicle and record it; The entry and exit recognition module is also used to record the exit time of potential customers, and record the duration of the visit based on the entry and exit time of the charging station; The analysis module is used to analyze the vehicle-changing probability of potential users based on the information of the potential customers' visit duration, vehicle model, and whether they leave the vehicle. The vehicle-changing probability includes: high, medium, or low.

2. The intelligent management system for charging stations according to claim 1, characterized in that: The analysis module is also used to grade the interest level of potential customers and assign a score based on the duration of the visit; Determine the launch year of fuel vehicles based on vehicle model and assign a score; Analyze and assign scores based on whether the customer leaves the vehicle: Weights are assigned to the visit duration, vehicle model, and whether the vehicle is left, and the vehicle change probability is calculated based on the weights.

3. The intelligent management system for charging stations according to claim 2, characterized in that: The analysis module calculates the comprehensive score through the formula: Comprehensive score = (visit duration score × weight 1) + (vehicle model score × weight 2) + (whether to leave the vehicle score × weight 3) The probability of changing cars is finally divided according to the comprehensive score, where the higher the comprehensive score, the higher the probability of changing cars.

4. The intelligent management system for charging stations according to claim 3 is characterized in that: It also includes a charging parking space management module, which is used to monitor the usage status of the charging pile in real time, including whether the charging pile is idle; if it is idle, determine whether there is a vehicle occupying the charging pile parking space; if it is not idle, obtain the license plate number, vehicle model, current battery power and charging power of the new energy vehicle being charged, and estimate the charging completion time based on the current battery power and charging power.

5. The intelligent management system for charging stations according to claim 4, characterized in that: It also includes a charging reservation module, which is used to receive the user's charging reservation information, which includes options such as the reserved charging time period and charging power, and is also used to obtain the usage status information of the charging pile and allocate a charging parking space for the user; it is also used to release the allocated charging parking space when the user fails to arrive on time or park in the reserved charging time period.

6. The intelligent management system for charging stations according to claim 5, characterized in that: The information acquisition module is also used to obtain vehicle entry and exit information of parking lots that do not have charging pile installation conditions within a preset range; The analysis module is also used to determine whether the potential customer's visit method is a specific visit based on the potential customer's entry and exit time at the charging station and the vehicle entry and exit information of the corresponding parking lot, and if so, determine the actual journey time; The analysis module is also used to estimate the round trip time based on the location of the charging station and the corresponding parking lot; it is also used to determine whether the difference between the real-time travel time of the potential user and the estimated round trip time is within a preset range, and if so, determine it as a single destination; The analysis module is also used to analyze the car change cycle of potential users based on information about whether the potential destination is a single destination. If it is a single destination, the car change cycle is less than a preset cycle. If it is not a single destination, the car change cycle is greater than the preset cycle.

Images