New energy vehicle charging pile management method and device, equipment and storage medium

Abstract

The invention relates to the technical field of new energy vehicle charging, and discloses a new energy vehicle charging pile management method, device and equipment and a storage medium, and the method comprises the steps: obtaining new energy vehicle type data, driving data and charging pile position data; calculating arrival time data of the charging pile according to the driving data and the charging pile position data; according to the new energy automobile type data, the driving data and the charging pile arrival time data, effective charging pile data are obtained through calculation; according to the effective charging pile data and pre-obtained charging pile use data, obtaining a charging pile priority sequence through a priority model; and obtaining the charging pile with the highest use priority according to the charging pile priority sequence, and sending the charging pile with the highest priority to the new energy automobile user. According to the method, an optimal charging scheme can be provided for a new energy automobile owner according to the idle condition of the charging pile and the number of parking spaces, and the charging experience and the use efficiency are improved.

Description

Technical Field

[0001] The present invention relates to the field of new energy vehicle charging technology, and in particular to a new energy vehicle charging pile management method, device, electronic equipment and storage medium. Background Art

[0002] At present, with the advancement of technology, new energy vehicles play an important role in reducing environmental pollution, promoting energy structure transformation, and promoting the upgrading of the automobile industry. They are of great significance to enhancing the overall competitiveness of the automobile industry, and the speed of their research and development, sales and use has also been further accelerated. With the increase in the number of new energy vehicles, the construction of charging infrastructure has become an important link in supporting the development of new energy vehicles, and the laying of new energy vehicle charging piles has also increased. In order to support this trend, the construction of charging piles has also been rapidly carried out in various places. As the basic supporting facilities for the popularization of new energy vehicles, the importance of charging piles is self-evident. A reasonable layout of charging piles can not only facilitate charging for car owners, but also effectively alleviate mileage anxiety and increase the attractiveness of new energy vehicles.

[0003] The traditional single charging solution is that the owner of a new energy vehicle decides the charging location and time. Generally, the owner drives to the location of the charging pile and chooses the nearest charging pile. However, charging a new energy vehicle is different from refueling an ordinary vehicle. It takes a long time and is time-consuming and laborious. The owner needs to wait a long time before the battery is fully charged. During the long wait, the owner cannot continue to use the car, and it is not convenient to leave the location of the charging pile, which greatly reduces the user's travel experience. At the same time, it is easy to have an emergency, resulting in the phenomenon of driving away before the vehicle is fully charged. The half-charged and half-discharged car battery is most likely to be damaged, which affects the service life of the car battery and the entire vehicle. The traditional single charging solution has great safety hazards.

[0004] In summary, the existing charging solutions result in low efficiency of charging piles, which greatly reduces the owner's experience of using charging piles. Summary of the invention

[0005] The present invention provides a new energy vehicle charging pile management method, device, electronic device and storage medium to realize a method for conveniently, quickly and safely selecting corresponding charging piles, fully considering multiple factors such as the idle situation of charging piles, the number of parking spaces, road congestion, nearby facilities, etc., to provide the best charging solution for new energy vehicle owners, and improve the owners' charging experience and usage efficiency.

[0006] In the first aspect, in order to solve the above technical problems, the present invention provides a new energy vehicle charging pile management method, comprising:

[0007] Obtain new energy vehicle type data, driving data and charging station location data;

[0008] Calculate the charging pile arrival time data according to the driving data and the charging pile position data;

[0009] Obtaining effective charging pile data by calculation according to the new energy vehicle type data, the driving data and the charging pile arrival time data;

[0010] According to the valid charging pile data and the pre-acquired charging pile usage data, a priority ranking of the charging piles is obtained through a priority model;

[0011] According to the priority sorting of the charging piles, the charging pile with the highest priority for use is obtained, and the charging pile with the highest priority is sent to the new energy vehicle user.

[0012] Preferably, the new energy vehicle type data includes new energy vehicle model and cruising range; the driving data includes departure time, driving speed, and departure location.

[0013] In an optional implementation, calculating the charging pile arrival time data according to the driving data and the charging pile position data includes:

[0014] According to the driving data and the charging pile position data, a road condition correction coefficient is obtained through a road condition correction coefficient model;

[0015] The fastest time and the slowest time for the new energy vehicle to reach the charging pile are calculated according to the road condition correction coefficient; wherein the charging pile arrival time data includes the fastest time and the slowest time;

[0016] The fastest time is calculated by the following formula:

[0017]

[0018] where t fastest is the fastest time, d is the distance from the starting position to the charging station, v is the driving speed, and C is the road condition correction coefficient;

[0019] The slowest time is calculated by the following formula:

[0020]

[0021] where t slowest is the slowest time, d is the distance from the starting position to the charging pile, v is the driving speed, and C is the road condition correction coefficient.

[0022] In an optional implementation, obtaining the road condition correction coefficient according to the driving data and the charging pile position data through a road condition correction coefficient model includes:

[0023] The first section road condition correction factor is calculated using the following formula:

[0024] C 1 =k 1 / v 1

[0025] Among them C 1 is the first section road condition correction coefficient, k 1 is the preset first section road condition proportional coefficient, v 1 The average speed of the current road conditions between the starting point and the end point is pre-selected, and the average speed of the time period close to the planned departure time and equal to the average speed of the planned departure time is selected;

[0026] The second section road condition correction factor is calculated using the following formula:

[0027] C 2 =k 2 v 2

[0028] Among them C 2 is the second section road condition correction coefficient, k 2 is the preset second section road condition proportional coefficient, v 2 The average speed of the vehicle under the current road conditions between the starting point and the end point is pre-selected, and the average speed of the vehicle over a time period that is equal to the planned departure time is selected;

[0029] A road condition correction coefficient is calculated based on the first section road condition correction coefficient, the second section road condition correction coefficient and a preset weight.

[0030] In an optional implementation, obtaining the effective charging pile by calculation according to the new energy vehicle type data, the driving data and the charging pile arrival time data includes:

[0031] The valid charging pile is verified by the following time verification conditions:

[0032] t 4 -t 3 >r×(t 2 -t 1 )

[0033] where t 1 is the fastest time for a new energy vehicle to reach the charging pile from its starting position, t 2 is the slowest time for a new energy vehicle to reach the charging pile from its starting position, t 3 is the time required for the charging pile to fully charge the new energy vehicle, t 4 is the time that the new energy vehicle stays at the charging pile, and r is the preset safety time margin;

[0034] For charging piles that meet the time verification conditions, verify whether they are compatible with the new energy vehicle model. If so, they are valid charging piles.

[0035] In an optional implementation, the priority ranking of the charging piles is obtained through a priority model according to the valid charging pile data and the pre-acquired charging pile usage data;

[0036] The charging pile usage data includes the remaining charging time and the number of parking spaces;

[0037] The priority model is:

[0038] S i =w 1 ·(max(R)-R i )+w 2 ·P i

[0039] Among them, R i is the remaining charging time of charging pile i, max(R) is the maximum remaining charging time among the valid charging piles, and w 1 is the weight of the remaining charging time, w 2 is the weight of the number of parking spaces, P i is the number of parking spaces for charging pile i, S i is the comprehensive score of charging pile i;

[0040] The charging piles are prioritized from high to low according to the comprehensive scores.

[0041] In an optional implementation, after obtaining the charging pile with the highest priority according to the priority sorting of the charging piles, the method further includes:

[0042] Charging piles are allocated according to the types of new energy vehicles, which include pure electric vehicles, hybrid vehicles and fuel-electric vehicles.

[0043] In a second aspect, the present invention provides a new energy vehicle charging pile management device, comprising:

[0044] Data acquisition module, used to obtain new energy vehicle type data, driving data and charging pile location data;

[0045] A time calculation module, used to calculate the charging pile arrival time data according to the driving data and the charging pile position data;

[0046] An effective screening module, used to obtain effective charging pile data by calculation according to the new energy vehicle type data, the driving data and the charging pile arrival time data;

[0047] A scoring calculation module, used to obtain a priority ranking of charging piles according to the valid charging pile data and the pre-acquired charging pile usage data through a priority model;

[0048] The result distribution module is used to obtain the charging pile with the highest priority according to the priority of the charging piles, and send the charging pile with the highest priority to the new energy vehicle user.

[0049] In a third aspect, the present invention further provides an electronic device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements any one of the above-mentioned new energy vehicle charging pile management methods when executing the computer program.

[0050] In a fourth aspect, the present invention also provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the above-mentioned new energy vehicle charging pile management methods.

[0051] Compared with the prior art, the present invention has the following beneficial effects: the present invention discloses a new energy vehicle charging pile management method, the method comprising obtaining new energy vehicle type data, driving data and charging pile location data; calculating the charging pile arrival time data according to the driving data and the charging pile location data; obtaining effective charging pile data by calculation according to the new energy vehicle type data, the driving data and the charging pile arrival time data; obtaining the charging pile priority ranking according to the effective charging pile data and the pre-acquired charging pile usage data through the priority model; obtaining the charging pile with the highest priority according to the charging pile priority ranking, and sending the charging pile with the highest priority to the new energy vehicle user. The method can accurately calculate the time when the vehicle arrives at the charging pile by obtaining the new energy vehicle type data, driving data and charging pile location data. In this way, the charging plan can be arranged in advance, the waiting time can be avoided too long, the charging resources can be reasonably allocated, the waste of charging pile resources can be avoided, the charging efficiency can be improved, and the utilization rate of charging facilities and user experience can be effectively improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 This is a schematic diagram of a new energy vehicle charging pile management method provided by the first embodiment of the present invention;

[0053] Figure 2 It is a structural schematic diagram of a new energy vehicle charging pile management device provided by the second embodiment of the present invention. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] At present, with the advancement of technology, new energy vehicles play an important role in reducing environmental pollution, promoting energy structure transformation, and promoting the upgrading of the automobile industry. They are of great significance to enhancing the overall competitiveness of the automobile industry, and the speed of their research and development, sales and use has also been further accelerated. With the increase in the number of new energy vehicles, the construction of charging infrastructure has become an important link in supporting the development of new energy vehicles, and the laying of new energy vehicle charging piles has also increased. In order to support this trend, the construction of charging piles has also been rapidly carried out in various places. As the basic supporting facilities for the popularization of new energy vehicles, the importance of charging piles is self-evident. A reasonable layout of charging piles can not only facilitate charging for car owners, but also effectively alleviate mileage anxiety and increase the attractiveness of new energy vehicles.

[0056] In the traditional single charging solution, the owner of a new energy vehicle decides the charging location and time. Generally, the owner drives to the location of the charging pile and chooses the nearest charging pile. However, charging a new energy vehicle is different from refueling an ordinary vehicle. It takes a long time and is time-consuming and laborious. The owner needs to wait a long time before the battery is fully charged. During the long wait, the owner cannot continue to use the car, and it is not convenient to leave the location of the charging pile, which greatly reduces the user's travel experience. At the same time, it is easy to have an emergency, resulting in the phenomenon of driving away before the vehicle is fully charged. The half-charged and half-discharged car battery is most likely to be damaged, affecting the service life of the car battery and the entire vehicle. The traditional single charging solution has great safety hazards. The existing charging solution causes low efficiency in the use of charging piles, which greatly reduces the owner's experience of using charging piles.

[0057] In order to solve the above technical problems, refer to Figure 1 The first embodiment of the present invention provides a new energy vehicle charging pile management method, comprising the following steps:

[0058] S11, obtaining new energy vehicle type data, driving data and charging pile location data;

[0059] S12, calculating charging pile arrival time data according to the driving data and the charging pile position data;

[0060] S13, obtaining effective charging pile data by calculation according to the new energy vehicle type data, the driving data and the charging pile arrival time data;

[0061] S14, obtaining a priority ranking of charging piles according to the valid charging pile data and the pre-acquired charging pile usage data through a priority model.

[0062] S15, obtaining the charging pile with the highest priority according to the priority sorting of the charging piles, and sending the charging pile with the highest priority to the new energy vehicle user.

[0063] In step S11, new energy vehicle type data, driving data and charging pile location data are obtained.

[0064] It is worth noting that the new energy vehicle type data includes new energy vehicle model and cruising range; the driving data includes departure time, driving speed, and departure location. Vehicle model information helps to understand the charging needs of the car, while cruising range is key information for estimating whether the car can successfully reach the charging pile. Departure time can help estimate when the car may need charging services and is used to calculate the road condition correction factor; driving speed and departure location are used to calculate the time required for the car to reach the charging pile. By collecting this data, it is possible to more accurately predict when the vehicle will arrive at the charging station, thereby better planning the use of charging stations and avoiding waste of resources.

[0065] In one embodiment, the acquisition of the new energy vehicle type data. When the user first registers to use the charging pile service, he or she may be required to enter information such as the vehicle brand, model, and cruising range. This information can be filled in through the vehicle manual or data provided by the manufacturer. For new energy vehicles with Internet of Vehicles functions, the vehicle information, including model, remaining power, cruising range, etc., can be directly read and uploaded through the vehicle's built-in system. This method requires the vehicle to support the corresponding communication protocol and requires the user to authorize the system to access this information. At the same time, some new energy vehicle brands have their own mobile applications, and users can synchronize vehicle information in the application, and this data can also be used for charging pile services.

[0066] In one embodiment, the driving data is obtained. The current location information of the vehicle can be obtained through the vehicle's GPS system or the GPS positioning function on the user's mobile phone; the user can also manually enter the departure time and expected driving speed before using the charging pile service. For networked vehicles, the vehicle's speed information can be obtained through on-board sensors. With the development of big data and artificial intelligence, the user's historical driving data can be used to predict future driving speeds and departure times. By training machine learning models, such as regression models, neural networks, etc., the patterns in historical driving data are learned, and time series analysis techniques are used to predict future driving speeds and departure times. Deep learning techniques, such as long short-term memory networks (LSTMs), are applied to capture long-term dependencies in the data.

[0067] It is worth mentioning that the charging pile location data is one of the important components for realizing the management of new energy vehicle charging piles. It contains the specific geographical location information of the charging pile, including the latitude and longitude coordinates of the charging pile, which is used to accurately locate the location of the charging pile; the detailed address of the charging pile, including the city, street, house number, etc., to facilitate the driver's navigation; fast charging pile or slow charging pile, different types of charging piles are suitable for vehicles with different charging needs.

[0068] In step S12, the charging pile arrival time data is calculated based on the driving data and the charging pile position data.

[0069] In one embodiment, a road condition correction coefficient is obtained according to the driving data and the charging pile position data through a road condition correction coefficient model; the fastest time and the slowest time for the new energy vehicle to reach the charging pile are calculated according to the road condition correction coefficient; wherein the charging pile arrival time data includes the fastest time and the slowest time;

[0070] The fastest time is calculated by the following formula:

[0071]

[0072] where t fastest is the fastest time, d is the distance from the starting position to the charging pile, V is the driving speed, and C is the road condition correction coefficient; this formula means that when the road condition is good (that is, C is larger), new energy vehicles can reach the charging pile faster.

[0073] The slowest time is calculated by the following formula:

[0074]

[0075] where t slowest is the slowest time, d is the distance from the starting position to the charging pile, V is the driving speed, and C is the road condition correction coefficient. This formula means that in the case of poor road conditions (i.e., C is small), the time it takes for new energy vehicles to reach the charging pile will be extended.

[0076] For example: The ideal straight-line distance from the current location of the vehicle to the charging station is 30 kilometers. Under ideal conditions (no traffic jams), the average speed of the vehicle is 60 kilometers per hour, and the road condition correction factor is 1.05.

[0077]

[0078] In this hypothetical scenario, the fastest time for a new energy vehicle to reach a charging station is about 28.56 minutes, and the slowest time is about 31.5 minutes.

[0079] It is worth noting that this calculation method can provide an estimated arrival time range for new energy vehicles, so that users and charging pile managers can better plan charging trips and resource allocation. In actual applications, the road condition correction coefficient may be dynamically adjusted according to real-time traffic information to more accurately predict the arrival time. This calculation method helps: by knowing the fastest arrival time in advance, users can choose the best charging time and improve charging efficiency; charging pile managers can reasonably arrange the use of charging piles and optimize resource allocation based on the estimated arrival time; providing accurate arrival time predictions allows users to better arrange their trips, reduce waiting time, and improve user experience.

[0080] In one implementation, obtaining the road condition correction coefficient according to the driving data and the charging pile location data through a road condition correction coefficient model includes:

[0081] The first section road condition correction factor is calculated using the following formula:

[0082] C 1 =k 1 / v 1

[0083] Among them C 1 is the correction coefficient for the first section of road condition, k1 is the preset proportional coefficient for the first section of road condition, v 1 The average speed of the current road conditions between the starting point and the end point is pre-selected, and the average speed of the time period close to the planned departure time and equal to the average speed of the planned departure time is selected;

[0084] The second section road condition correction factor is calculated using the following formula:

[0085] C 2 =k 2 v 2

[0086] Among them C 2 is the second section road condition correction coefficient, k 2 is the preset second section road condition proportional coefficient, v 2 The average speed of the vehicle under the current road conditions between the starting point and the end point is pre-selected, and the average speed of the vehicle over a time period that is equal to the planned departure time is selected;

[0087] The road condition correction coefficient is calculated based on the first section road condition correction coefficient, the second section road condition correction coefficient and the preset weight. For example, if the first section road condition correction coefficient is 1.3, the second section road condition correction coefficient is 0.8, and the preset weights are 0.5 and 0.5, then the road condition correction coefficient is 1.05.

[0088] It is worth noting that the road condition correction coefficient is calculated based on the current traffic conditions (such as congestion, road construction, etc.) through the road condition correction coefficient model. This model can help us adjust the estimated time for new energy vehicles to reach the charging pile according to different road conditions, so as to more accurately screen out effective charging piles. This coefficient reflects the degree of change of the actual driving speed relative to the ideal driving speed. Among them, the first section of the road condition correction coefficient is calculated based on historical data, the average speed in the vicinity of the planned departure time and in an equal time period, and its characteristic is that the lower the average speed, the higher the correction coefficient. Therefore, the first section of the road condition correction coefficient only needs to be a decreasing function of the average speed. In this embodiment, an inverse proportional function is used, and a negative exponential function or a decreasing logarithmic function can also be used. Among them, the second section of the road condition correction coefficient is calculated based on the current real-time road conditions, the average speed within a period of time after the planned departure time, and its characteristic is that the lower the average speed, the lower the correction coefficient. Therefore, the second section of the road condition correction coefficient only needs to be an increasing function of the average speed. In other embodiments, a direct proportional function can be used, and an exponential function or an increasing logarithmic function can also be used.

[0089] In step S13, effective charging pile data is obtained by calculation according to the new energy vehicle type data, the driving data and the charging pile arrival time data.

[0090] In one embodiment, the valid charging pile is verified by the following time verification conditions:

[0091] t 4 -t 3 >r×(t 2 -t 1 )

[0092] where t 1 is the fastest time for a new energy vehicle to reach the charging pile from its starting position, t 2 is the slowest time for a new energy vehicle to reach the charging pile from its starting position, t 3 is the time required for the charging pile to fully charge the new energy vehicle, t 4 is the time that the new energy vehicle stays at the charging pile, and r is the preset safety time margin; for the charging pile that meets the time verification conditions, verify whether it meets the new energy vehicle model, and if so, it is a valid charging pile.

[0093] It is worth noting that the time verification condition is first used to determine whether the charging pile meets the basic time requirements. If the time verification condition is met, it means that the charging pile has sufficient time for the new energy vehicle to complete charging. Even if there are some unexpected delays, they can be dealt with by the reserved time margin. For charging piles that meet the time verification conditions, it is necessary to further verify whether they support specific new energy vehicle models. The charging pile is considered valid only if it supports the charging interface and protocol of the model.

[0094] Specifically, different new energy vehicles may use different charging interface standards. Before verifying whether the charging pile is valid, it is necessary to ensure that the charging interface of the charging pile matches the interface required by the new energy vehicle. If the interface is incompatible, the charging pile cannot provide charging services for the model. In addition to the physical interface, it is also necessary to verify whether the charging pile supports a specific charging communication protocol. The charging protocol defines the communication method between the vehicle and the charging pile during the charging process to ensure the safety and efficiency of the charging process. If the charging pile supports the charging protocol required by the vehicle, then the charging pile and the vehicle can correctly exchange data to ensure the smooth progress of the charging process. Finally, the output power and current specifications of the charging pile also need to match the requirements of the new energy vehicle. If the vehicle supports fast charging, the charging pile must be able to provide enough power to meet the fast charging requirements. Otherwise, even if the interface and protocol are compatible, charging may not proceed at the expected speed. Through the above steps, the compatibility between the charging pile and the specific new energy vehicle model can be ensured, thereby ensuring the effectiveness of the charging pile. Only when the charging pile supports the charging interface, charging protocol, and power and current specifications required by the specific model can it be considered a valid charging pile. This verification process helps to improve charging efficiency and ensure the safety and reliability of the charging process.

[0095] In step S14, the priority ranking of the charging piles is obtained through a priority model according to the valid charging pile data and the pre-acquired charging pile usage data.

[0096] In one embodiment, the priority ranking of charging piles is obtained through a priority model according to the valid charging pile data and the pre-acquired charging pile usage data; the charging pile usage data includes the remaining charging time and the number of parking spaces; the priority model is:

[0097] S i =w 1 ·(max(R)-R i )+w 2 ·P i

[0098] Among them, R iis the remaining charging time of charging pile i, max(R) is the maximum remaining charging time among the valid charging piles, and w 1 is the weight of the remaining charging time, w 2 is the weight of the number of parking spaces, P i is the number of parking spaces for charging pile i, S i is the comprehensive score of charging pile i; the priority of charging piles is sorted from high to low according to the comprehensive score. This is done to ensure that the charging piles with shorter remaining charging time have higher scores, and the charging piles with more parking spaces have higher scores. For example: Charging pile A has 30 minutes of remaining charging time and 5 parking spaces; Charging pile B has 45 minutes of remaining charging time and 8 parking spaces; assuming the maximum remaining charging time is 60 minutes, the weight w 1 is 0.6, weight w 2 is 0.4; then according to the priority model, the comprehensive score of charging pile A is 20, and the comprehensive score of charging pile B is 12.2. According to the calculation results, the comprehensive score of charging pile A is higher than that of charging pile B, so charging pile A has a higher priority. In actual applications, the weights are adjusted according to specific scenarios to better reflect actual needs. For example, if the remaining charging time is more critical, the weight w can be increased. 1 On the contrary, if the number of parking spaces is more important, the weight w can be increased. 2 The value of .

[0099] It is worth noting that the design principles of the priority model in this embodiment include that the shorter the remaining charging time, the higher the priority; the more parking spaces, the higher the priority. If there is more charging pile data or more complex priority considerations, the comprehensive scoring model can be expanded in a similar way to more comprehensively evaluate the priority of charging piles.

[0100] Preferably, after the charging piles with the highest priority are obtained according to the priority sorting of the charging piles, the method further includes: allocating corresponding charging piles according to new energy vehicle models, and the new energy vehicle models include pure electric, hybrid electric vehicles and fuel electric vehicles. For pure electric vehicles, the charging piles need to have the following characteristics: support common charging standards, such as CCS (Combined Charging System), CHAdeMO or Tesla dedicated interface; provide appropriate charging power according to the charging needs of the vehicle, such as fast charging (DC) or slow charging (AC). Hybrid electric vehicles can be divided into two types according to their design: HEV (Hybrid Electric Vehicle): mainly relying on fuel engines, assisted by electric motors, usually do not require external power supply charging, do not need charging piles to provide charging services for them, but can provide refueling services; PHEV (Plug-in Hybrid E1ectric Vehicle): can rely on both fuel engines and external power supplies to charge batteries, support long-term pure electric mode driving, in addition to providing charging services, should also consider providing refueling services, because PHEV vehicles still need to rely on fuel engines after the battery is exhausted. For fuel cell vehicles, they rely on hydrogen as fuel, so special hydrogen refueling stations are required instead of charging piles.

[0101] For example, suppose there is a list of charging piles, including charging pile A, charging pile B, and charging pile C, with a priority of A>B>C. Verify the validity of charging pile A, including: confirming that charging pile A supports the user's new energy vehicle model; confirming that the charging interface and communication protocol of charging pile A are compatible with the user's vehicle; confirming that charging pile A is currently available, not occupied by other vehicles, and has no faults. Then it can be determined that charging pile A is the charging pile with the highest priority.

[0102] S15, obtaining the charging pile with the highest priority according to the priority sorting of the charging piles, and sending the charging pile with the highest priority to the new energy vehicle user.

[0103] In one embodiment, if the charging pile with the highest priority passes all validity verifications, the information of the charging pile is sent to the user. The information includes: the exact location of the charging pile (such as latitude and longitude coordinates, detailed address); the charging fee standard of the charging pile; the service time of the charging pile (such as opening hours); and specific instructions on how to make an appointment or use the charging pile. The user then receives the charging pile information through the application on the smartphone and navigates to the specified location; for new energy vehicles with Internet of Vehicles functions, the charging pile information can be directly displayed through the vehicle system and navigation services can be provided. In order to further optimize the user experience, the following points can also be considered: ensure the real-time update of the charging pile status to avoid users finding that the charging pile is occupied or malfunctions after arriving; while recommending the highest priority charging pile, provide several alternative charging piles for users to choose from in case there is a problem with the preferred charging pile; establish a user feedback mechanism to allow users to report the status of the charging pile and help the system maintain the latest charging pile information. Through the above steps, the highest priority charging pile can be effectively recommended to users, improving the convenience and efficiency of charging.

[0104] In order to facilitate the understanding of the present invention, some preferred embodiments of the present invention are further described below.

[0105] In one implementation, the charging pile arrival time data is calculated based on the driving data and the charging pile location data. The real-time traffic light conditions of the upstream intersection where the charging pile is located are introduced to predict the driving speed with the best road conditions to generate the fastest time to reach the charging pile. The predicted time to reach the charging pile = the section of road + the total waiting time for the red light of the section of road + the queuing time in front of the charging pile. Considering the estimated time required for the car to be fully charged, different models have different battery types, some are lithium iron phosphate batteries, and some are ternary lithium batteries. Based on the battery parameters such as voltage, capacity, battery nominal capacity and energy consumption parameters, the estimated time for the model to be fully charged is inferred. The estimated time is the average value accumulated under a large amount of previous data. Of course, the predicted value can also be based on the historical charging data near the charging pile to correct the estimated system time.

[0106] In summary, the present invention discloses a new energy vehicle charging pile management method, which estimates the reasonable arrival time by predicting the arrival time and traffic conditions of the vehicle in advance, and provides customers with the best charging pile selection through matching the car and the charging pile, reducing the waiting time, and selecting the fastest charging pile to be fully charged as much as possible, so as to improve the customer experience. At the same time, the type of new energy vehicle, the planned arrival time, the location and the real-time traffic conditions are comprehensively considered to accurately plan the optimal time to arrive at the charging pile; and the current charging state of the charging pile (the number of vehicles, the model, the remaining charging time, the number of parking spaces, etc.) is introduced as a screening condition to improve the rationality and efficiency of the charging pile selection, especially for different models (such as pure electric and extended range) to select the corresponding charging pile, and provide the best charging solution. The algorithm is introduced to calculate and screen out the effective charging piles that meet the conditions, and match and give the best charging solution to solve the user pain points. Different road condition correction coefficients are set according to the road conditions to improve the calculation accuracy of the time when the new energy vehicle arrives at the location of the charging pile from the current location. The management method arranges the charging plan in advance, avoids too long waiting time, reasonably allocates charging resources, avoids the waste of charging pile resources, improves the efficiency of charging, and effectively improves the utilization rate of charging facilities and user experience.

[0107] Reference Figure 2 The second embodiment of the present invention provides a new energy vehicle charging pile management device, including:

[0108] Data acquisition module, used to obtain new energy vehicle type data, driving data and charging pile location data;

[0109] A time calculation module, used to calculate the charging pile arrival time data according to the driving data and the charging pile position data;

[0110] An effective screening module, used to obtain effective charging pile data by calculation according to the new energy vehicle type data, the driving data and the charging pile arrival time data;

[0111] A scoring calculation module, used to obtain a priority ranking of charging piles according to the valid charging pile data and the pre-acquired charging pile usage data through a priority model;

[0112] The result distribution module is used to obtain the charging pile with the highest priority according to the priority of the charging piles, and send the charging pile with the highest priority to the new energy vehicle user.

[0113] Preferably, the data acquisition module is used to:

[0114] Acquire new energy vehicle type data, driving data and charging pile location data; wherein the new energy vehicle type data includes new energy vehicle model and cruising range; the driving data includes departure time, driving speed and departure location.

[0115] Preferably, the time calculation module is used to:

[0116] The charging pile arrival time data is calculated according to the driving data and the charging pile location data, including obtaining a road condition correction coefficient through a road condition correction coefficient model according to the driving data and the charging pile location data; the fastest time and the slowest time for the new energy vehicle to reach the charging pile are calculated according to the road condition correction coefficient; wherein the charging pile arrival time data includes the fastest time and the slowest time;

[0117] The fastest time is calculated by the following formula:

[0118]

[0119] where t fastest is the fastest time, d is the distance from the starting position to the charging station, v is the driving speed, and C is the road condition correction coefficient;

[0120] The slowest time is calculated by the following formula:

[0121]

[0122] where t slowest is the slowest time, d is the distance from the starting position to the charging pile, v is the driving speed, and C is the road condition correction coefficient.

[0123] The road condition correction coefficient obtained by using a road condition correction coefficient model according to the driving data and the charging pile location data includes:

[0124] The first section road condition correction factor is calculated using the following formula:

[0125] C 1 =k 1 / v 1

[0126] Among them C 1 is the first section road condition correction coefficient, k 1 is the preset first section road condition proportional coefficient, v 1 The average speed of the current road conditions between the starting point and the end point is pre-selected, and the average speed of the time period close to the planned departure time and equal to the average speed of the planned departure time is selected;

[0127] The second section road condition correction factor is calculated using the following formula:

[0128] C 2 =k 2 v 2

[0129] Among them C2 is the second section road condition correction coefficient, k 2 is the preset second section road condition proportional coefficient, v 2 The average speed of the vehicle under the current road conditions between the starting point and the end point is pre-selected, and the average speed of the vehicle over a time period that is equal to the planned departure time is selected;

[0130] A road condition correction coefficient is calculated based on the first section road condition correction coefficient, the second section road condition correction coefficient and a preset weight.

[0131] Preferably, the effective screening module is used for:

[0132] According to the new energy vehicle type data, the driving data and the charging pile arrival time data, effective charging pile data is obtained by calculation, including:

[0133] The valid charging pile is verified by the following time verification conditions:

[0134] t 4 -t 3 >r×(t 2 -t 1 )

[0135] where t 1 is the fastest time for a new energy vehicle to reach the charging pile from its starting position, t 2 is the slowest time for a new energy vehicle to reach the charging pile from its starting position, t 3 is the time required for the charging pile to fully charge the new energy vehicle, t 4 is the time that the new energy vehicle stays at the charging pile, and r is the preset safety time margin;

[0136] For charging piles that meet the time verification conditions, verify whether they are compatible with the new energy vehicle model. If so, they are valid charging piles.

[0137] Preferably, the result distribution module is used to:

[0138] After obtaining the charging pile with the highest priority according to the priority sorting of the charging piles, and sending the charging pile with the highest priority to the new energy vehicle user, the method further includes:

[0139] Charging piles are allocated according to the types of new energy vehicles, which include pure electric vehicles, hybrid vehicles and fuel-electric vehicles.

[0140] It should be noted that a new energy vehicle charging pile management device provided in an embodiment of the present invention is used to execute all process steps of a new energy vehicle charging pile management method in the above embodiment. The working principles and beneficial effects of the two correspond one to one, so they will not be repeated here.

[0141] In summary, the present invention discloses a new energy vehicle charging pile management method, which estimates the reasonable arrival time by predicting the arrival time and traffic conditions of the vehicle in advance, and provides customers with the best charging pile selection through matching the car and the charging pile, reducing the waiting time, and selecting the fastest charging pile to be fully charged as much as possible to improve the customer experience. At the same time, the type of new energy vehicle, the planned arrival time, the location and the real-time traffic conditions are comprehensively considered to accurately plan the optimal time to arrive at the charging pile; and the current charging state of the charging pile (the number of vehicles, the model, the remaining charging time, the number of parking spaces, etc.) is introduced as a screening condition to improve the rationality and efficiency of the charging pile selection, especially for different models (such as pure electric and extended range) to select the corresponding charging pile, and provide the best charging solution. The algorithm is introduced to calculate and screen out the effective charging piles that meet the conditions, and match and give the best charging solution to solve the user pain points. Different road condition correction coefficients are set according to the road conditions to improve the calculation accuracy of the time when the new energy vehicle arrives at the location of the charging pile from the current location. The management method arranges the charging plan in advance, avoids too long waiting time, reasonably allocates charging resources, avoids the waste of charging pile resources, improves the efficiency of charging, and effectively improves the utilization rate of charging facilities and user experience.

[0142] The embodiment of the present invention further provides an electronic device. The electronic device includes: a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a priority model program. When the processor executes the computer program, the steps in the above-mentioned various new energy vehicle charging pile management method embodiments are implemented, such as Figure 1 Alternatively, when the processor executes the computer program, the functions of each module / unit in the above-mentioned device embodiments are implemented, such as the data acquisition module.

[0143] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program in the electronic device.

[0144] The electronic device may be a computing device such as a desktop computer, a notebook, a PDA, and a smart tablet. The electronic device may include, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that the above components are merely examples of electronic devices and do not constitute a limitation on the electronic device. The electronic device may include more or fewer components than the above components, or may combine certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0145] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the electronic device, and uses various interfaces and lines to connect various parts of the entire electronic device.

[0146] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the electronic device by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0147] Wherein, if the module / unit integrated in the electronic device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0148] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0149] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A new energy vehicle charging pile management method, characterized in that: include: Obtain new energy vehicle type data, driving data and charging station location data; Calculate the charging pile arrival time data according to the driving data and the charging pile position data; Obtaining effective charging pile data by calculation according to the new energy vehicle type data, the driving data and the charging pile arrival time data; According to the valid charging pile data and the pre-acquired charging pile usage data, a priority ranking of the charging piles is obtained through a priority model; According to the priority sorting of the charging piles, the charging pile with the highest priority for use is obtained, and the charging pile with the highest priority is sent to the new energy vehicle user.

2. The new energy vehicle charging pile management method according to claim 1, characterized in that: The new energy vehicle type data includes the new energy vehicle model and cruising range; the driving data includes the departure time, driving speed, and departure location.

3. The new energy vehicle charging pile management method according to claim 1, characterized in that: The charging pile arrival time data is calculated according to the driving data and the charging pile position data, including: According to the driving data and the charging pile position data, a road condition correction coefficient is obtained through a road condition correction coefficient model; The fastest time and the slowest time for the new energy vehicle to reach the charging pile are calculated according to the road condition correction coefficient; wherein the charging pile arrival time data includes the fastest time and the slowest time; The fastest time is calculated by the following formula: where t fastest is the fastest time, d is the distance from the starting position to the charging station, v is the driving speed, and C is the road condition correction coefficient; The slowest time is calculated by the following formula: where t slowest is the slowest time, d is the distance from the starting position to the charging pile, v is the driving speed, and C is the road condition correction coefficient.

4. The new energy vehicle charging pile management method according to claim 3 is characterized in that: The road condition correction coefficient is obtained according to the driving data and the charging pile position data through a road condition correction coefficient model, including: The first section road condition correction factor is calculated using the following formula: C1=k1 / v1 Where C1 is the correction coefficient for the first section of road conditions, k1 is the preset first section of road condition ratio coefficient, and v1 is the pre-selected average vehicle speed of the current road conditions between the starting point and the end point. The average vehicle speed of the time period close to the planned departure time and equal to the average vehicle speed of the planned departure time is selected; The second section road condition correction factor is calculated using the following formula: C2=k2vv2 Where C2 is the correction coefficient for the second section of road conditions, k2 is the preset second section of road condition ratio coefficient, and v2 is the average vehicle speed of the current road conditions between the starting point and the end point obtained in advance, and the average vehicle speed is selected for the same time period as the planned departure time; A road condition correction coefficient is calculated based on the first section road condition correction coefficient, the second section road condition correction coefficient and a preset weight.

5. The new energy vehicle charging pile management method according to claim 1, characterized in that: The obtaining of the effective charging pile by calculation according to the new energy vehicle type data, the driving data and the charging pile arrival time data comprises: The valid charging pile is verified by the following time verification conditions: t4-t3>r×(t2-t1) Where t1 is the fastest time for the new energy vehicle to reach the charging pile from the starting position, t2 is the slowest time for the new energy vehicle to reach the charging pile from the starting position, t3 is the time required for the charging pile to fully charge the new energy vehicle, t4 is the time the new energy vehicle stays at the charging pile, and r is the preset safety time margin; For charging piles that meet the time verification conditions, verify whether they meet the new energy vehicle type data. If so, it is a valid charging pile.

6. The new energy vehicle charging pile management method according to claim 2, characterized in that: According to the valid charging pile data and the pre-acquired charging pile usage data, a priority ranking of the charging piles is obtained through a priority model; The charging pile usage data includes the remaining charging time and the number of parking spaces; The priority model is: S i =w1·(max(R)-R i )+w2·P i Among them, R i is the remaining charging time of charging pile i, max(R) is the maximum remaining charging time among the valid charging piles, w1 is the weight of the remaining charging time, w2 is the weight of the number of parking spaces, P i is the number of parking spaces for charging pile i, S i is the comprehensive score of charging pile i; The charging piles are prioritized from high to low according to the comprehensive scores.

7. The new energy vehicle charging pile management method according to claim 2, characterized in that: After obtaining the charging pile with the highest priority according to the priority sorting of the charging piles, the method further includes: Charging piles are allocated according to the types of new energy vehicles, which include pure electric vehicles, hybrid vehicles and fuel-electric vehicles.

8. A new energy vehicle charging pile management device, characterized in that: include: Data acquisition module, used to obtain new energy vehicle type data, driving data and charging pile location data; A time calculation module, used to calculate the charging pile arrival time data according to the driving data and the charging pile position data; An effective screening module, used to obtain effective charging pile data by calculation according to the new energy vehicle type data, the driving data and the charging pile arrival time data; A scoring calculation module, used to obtain a priority ranking of charging piles according to the valid charging pile data and the pre-acquired charging pile usage data through a priority model; The result distribution module is used to obtain the charging pile with the highest priority according to the priority of the charging piles, and send the charging pile with the highest priority to the new energy vehicle user.

9. An electronic device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the method for managing a new energy vehicle charging pile as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the new energy vehicle charging pile management method as described in any one of claims 1 to 7.

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