Charging pile and electric vehicle distribution method and system

Abstract

The invention discloses a charging pile and electric vehicle distribution method and system, and relates to the technical field of intelligent traffic and energy management, and the method comprises the steps: building a distribution model for charging piles in a distribution range according to the idle condition of the charging piles and the equipment degradation degree; establishing an electric vehicle user preferential function according to the economical efficiency of the electric vehicle user and the distance between the charging pile and the starting position of the user; and after calculation of the charging pile distribution function and the electric vehicle user preferential function, information reported by the electric vehicle users and the numbers of the charging piles to be selected are matched. According to the distribution method of the charging piles and the electric vehicles, by considering the idle condition of the charging piles, the equipment degradation degree, the economical efficiency and convenience of the users and the bearing capacity of the power grid, the benefits between the charging platform and the users are balanced, the peak-valley difference of the power grid is reduced, the utilization rate of the charging piles is increased, the waiting time of the users is shortened, and the user experience is improved. The charging pile has better effects in the aspects of economy, the utilization rate of the charging pile and convenience.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent transportation and energy management, and in particular to a method and system for allocating charging piles and electric vehicles. Background Art

[0002] Charging piles play a key role in solving the range anxiety problem of new energy vehicles. With the rapid growth of new energy vehicle ownership, the charging pile industry has attracted the participation and investment of many companies. Although the ratio of cars to charging piles is gradually approaching a balance, the uneven distribution of charging piles is still prominent. Charging pile resources are tight in the central area of ​​the city, while charging piles are relatively abundant in the suburbs.

[0003] In order to effectively alleviate this contradiction, the charging platform is actively playing a hub role, integrating the charging facility resources in the region to provide users with unified charging scheduling services. They have established an intelligent charging pile allocation function, providing real-time information on available charging piles, and reasonably arranging charging plans based on user needs and power grid conditions to help electric vehicle users find the most suitable charging piles.

[0004] The charging platform not only connects electric vehicle users and power grid companies, but also provides users with convenient charging services through the purchase and sale of electricity, and obtains reasonable profits from it. However, current research on electric vehicle and charging pile allocation methods mostly focuses on maximizing the benefits of charging platforms, and cannot take into account the comprehensive optimization method of user charging costs and power grid economic benefits;

[0005] Looking ahead, as electric vehicles become more popular, charging demand will continue to grow. Without effective charging guidance and control methods, users may concentrate on charging during peak hours, resulting in increased grid load fluctuations, which will not only affect user experience, but may also damage the stability and economic benefits of the grid.

[0006] Therefore, it is necessary to develop a method for allocating charging piles and electric vehicles to balance the interests between the charging platform and users. It is also necessary to fully consider the carrying capacity of the power grid, guide users to charge reasonably through intelligent scheduling and orderly control, reduce the peak-to-valley difference of the power grid, improve the operation efficiency of the power grid, and achieve a win-win situation for all parties. Summary of the invention

[0007] In view of the above-mentioned problems, the present invention is proposed.

[0008] Therefore, the technical problem solved by the present invention is that the existing method for matching electric vehicle users with charging piles has the problems of poor economy, poor convenience, low utilization rate of charging piles, and imbalance of interests between charging platforms and users.

[0009] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for allocating charging piles and electric vehicles, comprising establishing an allocation model for charging piles within an allocation range according to the idle status of the charging piles and the degree of equipment degradation; establishing an electric vehicle user optimization function according to the economic efficiency of the electric vehicle user and the distance of the charging pile relative to the user's starting position; after calculating the charging pile allocation function and the electric vehicle user optimization function, matching the information reported by the electric vehicle user and the number of the charging pile to be selected.

[0010] As a preferred solution of the method for allocating charging piles and electric vehicles described in the present invention, wherein: the establishment of an allocation function for charging piles within the allocation range according to the idle status of the charging piles and the degree of equipment degradation includes evaluating the idle status of the charging piles, determining the availability of the idle status for the current charging demand, constructing an allocation model a1, including the idle time and idle times of the charging piles, inputting the charging pile number ID and the current time t c ;

[0011] Perform data processing to obtain the idle time record of the charging pile, including the start idle time and the end idle time;

[0012] Find out at the current time t c The last record before the end of idle time, denoted as t l ;

[0013] Output current time and t l The time difference between the two is used to count the number of idle times of the charging pile N. i ;

[0014] Free time is proportional to the rating;

[0015] The number of idle times is proportional to the score;

[0016] Combine the current time with t l The time difference between the two and the number of idle times of the charging piles are counted to construct the allocation model a1, which is expressed as:

[0017]

[0018] Among them, w1 and w2 represent weight coefficients, N max Indicates the maximum idle times threshold, T m Indicates the maximum idle time threshold.

[0019] As a preferred solution of the method for allocating charging piles and electric vehicles of the present invention, wherein: the establishment of an allocation model for charging piles within the allocation range according to the idle status of the charging piles and the degree of equipment degradation includes constructing a charging pile allocation function a2 for evaluating the degree of equipment degradation of the charging piles, including the service life and failure rate of the charging piles;

[0020] The charging pile allocation function a2 is designed to evaluate the equipment degradation of the charging piles and reflect the reliability and maintenance requirements;

[0021] Enter the charging pile number;

[0022] Get the service life Y of the charging pile usage , obtain the fault record of the charging pile and count the number of faults N failure ;

[0023] The age is inversely proportional to the score;

[0024] The number of failures is inversely proportional to the score;

[0025] Combined with Y usage and N failure , the charging pile allocation function a2 is constructed as:

[0026]

[0027] Among them, w3 and w4 represent weight coefficients, Y max Indicates the maximum service life, N failure Indicates the number of failures of the charging pile, N max_failure Indicates the maximum fault count threshold.

[0028] As a preferred solution of the method for allocating charging piles and electric vehicles of the present invention, wherein: the establishment of an allocation model for charging piles within the allocation range according to the idle status of the charging piles and the degree of equipment degradation includes adjusting and optimizing a1a2 according to actual conditions to meet needs and scenarios;

[0029] Further refine the allocation strategy based on the geographical location and charging power of the charging piles;

[0030] Taking geographical location factors into consideration, the distance score is output, including:

[0031] According to the departure location reported by the electric vehicle user, output the distance to each charging pile;

[0032] Set a distance scoring function based on the distance, and use an inverse proportional function or exponential function to make the distance proportional to the score;

[0033] Considering the geographical location weight, the distance score is combined with the results of the charging pile allocation functions a1 and a2, and the distance score is weighted and added to the final score, which is expressed as:

[0034] S final =w1×a1+w2×a2+w3×S distance

[0035] Among them, S distance represents the distance score, Sfinal Indicates the final rating.

[0036] As a preferred solution of the method for allocating charging piles and electric vehicles of the present invention, the allocation model for charging piles within the allocation range according to the idle status of the charging piles and the degree of equipment degradation includes considering the charging power factor. Regarding the charging power score:

[0037] Different electric vehicles require charging piles of different powers for charging. The required charging power range is determined based on the user's vehicle model or battery requirements;

[0038] Set a score for the charging power of each charging pile, and increase the score within the power range that meets user needs.

[0039] About power weights:

[0040] Combine the charging power score with the results of the charging pile allocation functions a1 and a2, give the charging power score a weight, and add it to the final score;

[0041] Regarding charging time considerations:

[0042] Taking into account the charging time requirements of electric vehicle users, the estimated charging time is output by combining the charging power and battery capacity, and will be used as part of the score.

[0043] As a preferred solution of the method for allocating charging piles and electric vehicles of the present invention, wherein: the establishment of an electric vehicle user selection function according to the economy of the electric vehicle user and the distance of the charging pile relative to the user's starting position includes the electric vehicle user selection function comprehensively considering the economy and convenience of the user to provide the user with the best charging option;

[0044] Establish the charging unit price of the charging pile and the distance from the user's starting location to the charging pile;

[0045] Combine these two variables into one function and assign different weights to reflect the importance users place on economy and convenience;

[0046] w price and w distance Represent the weights of price and distance respectively, the values ​​are between 0 and 1, and the sum of the two is 1;

[0047] The optimal function definition of electric vehicle users is expressed as:

[0048]

[0049] Among them, S optimality represents the optimal rating of electric vehicle users, w price represents the price weight coefficient, w distancerepresents the distance weight coefficient, price_per_kWh represents the charging price of the charging pile, d charger represents the distance from the current location of the electric vehicle user to the charging station, ∈ = 0.01, to avoid the denominator being zero;

[0050] The user selects the optimal charging pile based on the score of the optimal function of the optimal electric vehicle user.

[0051] As a preferred solution of the method for allocating charging piles and electric vehicles of the present invention, wherein: after the calculation of the charging pile allocation function and the electric vehicle user optimization function, the information reported by the electric vehicle user and the number of the charging pile to be selected are matched, including matching the information reported by the electric vehicle user and the number of the charging pile to be selected after the output of the charging pile allocation function and the electric vehicle user optimization function;

[0052] The matching results are divided into three cases:

[0053] If only one of the numbers reported by the electric vehicle user and the operator number overlaps, it means that the reservation is valid. At this time, the user will receive a text message notification to confirm the location of the charging station and related information;

[0054] If the number reported by the electric vehicle user and the operator number overlap in more than one item, it means that the reservation is valid, but the system will reallocate it according to the result of the user's selection function and send a message to the user's mobile phone, waiting for the user's confirmation;

[0055] There is no overlap between the number reported by the electric vehicle user and the operator number, which means that the user's reservation is invalid, but the system allows the user to enter the next round of reservations.

[0056] Another object of the present invention is to provide a charging pile and electric vehicle allocation system, which can solve the problem that the current electric vehicle user and charging pile matching method cannot take into account both the user charging cost and the economic benefit of the power grid by establishing a charging pile allocation function and an electric vehicle user optimization function.

[0057] As a preferred solution of the charging pile and electric vehicle allocation system described in the present invention, it includes: a charging pile allocation function construction module, an electric vehicle user selection function construction module, and an electric vehicle user and charging pile allocation module; the charging pile allocation function construction module establishes an allocation function; the electric vehicle user selection function construction module is used to establish an electric vehicle user selection function; the electric vehicle user and charging pile allocation module is used to match the information reported by the electric vehicle user and the number of the charging pile to be selected.

[0058] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of a method for allocating charging piles and electric vehicles.

[0059] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a method for allocating charging piles and electric vehicles.

[0060] Beneficial effects of the present invention: The method for allocating charging piles and electric vehicles provided by the present invention balances the interests of the charging platform and users by considering the idle status of the charging piles, the degree of equipment degradation, the economy and convenience of users, and the carrying capacity of the power grid, thereby realizing intelligent matching and allocation between electric vehicle users and charging piles, guiding users to charge reasonably, reducing the peak-to-valley difference of the power grid, improving the utilization rate of charging piles, reducing user waiting time, improving user experience, and achieving a win-win situation for all parties. The present invention achieves better results in terms of economy, utilization rate of charging piles, and convenience. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0062] Figure 1 An overall flow chart of a method for allocating charging piles and electric vehicles provided in the first embodiment of the present invention.

[0063] Figure 2 An overall flow chart of a charging pile and electric vehicle allocation system provided in accordance with the third embodiment of the present invention. DETAILED DESCRIPTION

[0064] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0065] Example 1, reference Figure 1 , as an embodiment of the present invention, provides a method for allocating charging piles and electric vehicles, comprising:

[0066] S1: Establish an allocation model for charging piles within the allocation range based on the idle status of charging piles and the degree of equipment degradation.

[0067] Furthermore, a charging pile allocation function is established.

[0068] According to the idle status of charging piles and the degree of equipment degradation, allocation functions a1 and a2 are established for the charging piles within the allocation range.

[0069] Allocation function a1 is used to evaluate the idleness of charging piles, including the idle time and number of idle times of charging piles, etc. Charging pile allocation function a2 is used to evaluate the equipment degradation of charging piles, including the service life and failure rate of charging piles, etc. Through these two functions, it is possible to reasonably allocate charging piles to electric vehicle users with charging needs.

[0070] 1. Function a1 is designed to evaluate the idleness of charging piles to determine their availability for current charging needs. The following is a specific implementation example:

[0071] a1 (charging station number, current time) → idleness score

[0072] 1) Input:

[0073] Charging pile number: a number that uniquely identifies the charging pile.

[0074] Current time: The current timestamp of the system.

[0075] 2) Data processing:

[0076] Get the idle time record of the charging pile (including the start idle time and the end idle time).

[0077] Traverse the idle time records and find the last record that ends the idle time before the current time, recorded as t l .

[0078] At the same time, count the number of idle times N of the charging pile i , which is the number of idle time records.

[0079] 3) Rating calculation:

[0080] The longer the idle time, the higher the score should be (indicating that the charging station is more idle).

[0081] The more idle times, the higher the score should be (indicating that the charging station is frequently idle).

[0082] Combine the current time with t l The time difference between the charging stations and the number of idle times of the charging stations are counted to design a weighted scoring formula:

[0083]

[0084] Among them, w1 and w2 represent weight coefficients, N max Indicates the maximum idle times threshold, T m Indicates the maximum idle time threshold;

[0085] w1 and w2 can be adjusted according to actual conditions;

[0086] The maximum idle time threshold and the maximum idle number threshold are used to normalize the score.

[0087] 4) Output:

[0088] Returns the idleness score a1 of the charging pile.

[0089] It should be noted that function a2 is intended to evaluate the degree of equipment degradation of the charging pile to reflect its reliability and maintenance requirements. The following is a specific implementation example:

[0090] a2 (charging station number) → degradation score

[0091] 1) Input:

[0092] Charging pile number: a number that uniquely identifies the charging pile.

[0093] 2) Data processing:

[0094] Get the service life Y of the charging pile usage .

[0095] Get the fault records of the charging pile and count the number of faults N failure .

[0096] If detailed fault data (such as fault type, fault duration, etc.) is available, it can also be considered for inclusion in the assessment.

[0097] 3) Rating calculation:

[0098] The older the device, the lower the score should be (indicating that the device is older).

[0099] The greater the number of failures, the lower the score should be (indicating poorer equipment reliability).

[0100] Combined with Y usage and N failure , design a weighted scoring formula to combine the service life and the number of failures. The formula is as follows:

[0101]

[0102] Among them, w3 and w4 represent weight coefficients, Y max Indicates the maximum service life, N failure Indicates the number of failures of the charging pile, N max_failure Indicates the maximum fault count threshold;

[0103] The maximum age and maximum number of failures thresholds are used to normalize the scores.

[0104] 4) Output:

[0105] Returns the degradation score a2 of the charging pile. Note that the lower the score, the better, which is the opposite of the score direction of a1.

[0106] It should also be noted that in actual applications, these two functions can be adjusted and optimized according to specific circumstances to meet specific needs and scenarios. At the same time, other factors (such as charging piles) can be combined geographical location, charging power, etc.) Further refine the allocation strategy. The following is the specific strategy refinement method:

[0107] 1. Consider location

[0108] 1) Calculate the distance score:

[0109] Based on the departure location reported by the electric vehicle user, the distance to each charging station is calculated.

[0110] A distance scoring function is set according to the distance, and an inverse proportional function or an exponential function is used so that the closer the distance, the higher the score.

[0111] 2) Geographical location weight:

[0112] Combine the distance score with the results of the charging pile allocation functions a1 and a2, give the distance score an appropriate weight, and add it to the final score. The formula is as follows:

[0113] S final =w1×a1+w2×a2+w3×S distance

[0114] Among them, S distance represents the distance score, S final Indicates the final rating.

[0115] Furthermore, 2. Consider the charging power factor

[0116] 1) Charging power rating:

[0117] Different electric vehicles may require charging piles of different powers for charging. Determine the required charging power range based on the user's vehicle model or battery requirements.

[0118] A score is set for the charging power of each charging pile so that it scores higher within the power range that meets user needs.

[0119] 2) Power weight:

[0120] Combine the charging power score with the results of the charging pile allocation functions a1 and a2, give the charging power score an appropriate weight, and add it to the final score.

[0121] 3) Charging time considerations:

[0122] Taking into account the charging time needs of electric vehicle users, the estimated charging time is calculated by combining the charging power and battery capacity and used as part of the score.

[0123] S2: Establish an optimal selection function for electric vehicle users based on the economic factors of electric vehicle users and the distance of the charging pile relative to the user's starting location.

[0124] Furthermore, a selection function for electric vehicle users is established.

[0125] The optimal selection function for electric vehicle users is established based on the economics of electric vehicle users and the distance of charging piles relative to the user's starting location. This function comprehensively considers the economics and convenience of users and provides users with the best charging options.

[0126] The following is an example of a specific electric vehicle user selection function:

[0127] Create two key variables:

[0128] price_per_kWh: charging price per kWh of the charging station (yuan / kWh).

[0129] d charger : The distance from the user's starting location to the charging station (the unit can be kilometers or other distance units).

[0130] Combine these two variables into a function and assign different weights to them to reflect the importance users place on economy and convenience. Assume that w price and w distance They represent the weights of price and distance respectively, their values ​​are between 0 and 1, and their sum is 1.

[0131] The optimal function is defined as:

[0132]

[0133] Among them, S optimality represents the optimal rating of electric vehicle users, w price represents the price weight coefficient, w distance represents the distance weight coefficient, price_per_kWh represents the charging price of the charging pile, d charger Indicates the distance from the electric vehicle user's current location to the charging station;

[0134] Here, we take the inverse of price and distance because we hope that the score increases with decreasing price and shortening distance. If a factor is not the focus of the user's consideration, its weight can be set to 0.

[0135] In addition, in order to avoid the situation where the denominator is zero (that is, the price is zero or the distance is zero), a small positive number epsilon is added as the base:

[0136]

[0137] Here, ∈ is a small positive number, such as 0.01.

[0138] Finally, users can choose the best charging pile based on the score of this optimization function. The higher the score of the charging pile, the better it is for the user.

[0139] S3: After the calculation of the charging pile allocation function and the electric vehicle user optimization function, the information reported by the electric vehicle user and the number of the charging pile to be selected are matched.

[0140] Going further, the allocation of electric vehicle users and charging stations.

[0141] After the calculation of the charging pile allocation function and the electric vehicle user selection function, the information reported by the electric vehicle user and the number of the charging pile to be selected are matched. The matching results are divided into the following three cases:

[0142] 1) If only one of the numbers reported by the electric vehicle user and the operator number coincides, it means that the reservation is valid. At this time, the user will receive a text message notification to confirm the location of the charging station and related information.

[0143] 2) If more than one of the numbers reported by the electric vehicle user and the operator number overlap, it means that the reservation is valid, but the system will reallocate it based on the result of the user's optimization function and send a message to the user's mobile phone, waiting for the user's confirmation.

[0144] 3) The number reported by the electric vehicle user and the operator number do not overlap, which means that the user's reservation is invalid, but the system allows the user to enter the next round of reservations.

[0145] Example 2, an embodiment of the present invention, provides a method for allocating charging piles and electric vehicles. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0146] First, before the experiment began, basic information of 10 charging piles was collected, including the age of each charging pile, failure rate, idle time record, etc. User data includes the user's departure location, charging demand (required charging amount), and economic indicators of electric vehicles (such as battery capacity and power consumption).

[0147] Record the service life and failure times of 10 charging piles as the basis for evaluating the degradation of charging piles. Record the idle time and idle times of charging piles as the evaluation data of idle conditions. Monitor the user's departure location, arrival time at the charging pile, charging cost and other data.

[0148] The experimental group adopted the charging pile allocation model proposed in the present invention, and dynamically adjusted the allocation strategy of the charging piles according to the idleness score and the degradation score of the charging piles.

[0149] Combining the economic efficiency of users (i.e., each user's charging demand and price sensitivity) and the optimization function of the distance to the charging pile, the most suitable charging pile is allocated to each user, with priority given to charging piles with low failure rates and high idle rates.

[0150] The control group uses the existing charging pile allocation method based on simple distance matching, which does not consider the idleness and degradation of the charging piles, and is allocated based solely on the distance between the user and the charging pile. The charging time, charging cost, idle time and other data of the control group are recorded.

[0151] After the experiment, the usage of charging piles in the experimental group and the control group was recorded, including the charging pile number, charging fee, idle time of the charging pile and number of failures for each charging.

[0152] The data was collated and a comparison table of the experimental group and the control group was generated in order to further analyze the effects of the invention on economy and charging pile utilization.

[0153] Table 1 Experimental data table

[0154]

[0155]

[0156] From the table, we can see that the experimental group has obvious advantages in terms of charging costs, idle time of charging piles, and number of failures.

[0157] The average charging cost of the experimental group was 15.17 yuan, while the average charging cost of the control group was 25.25 yuan. The experimental group saved about 40% of the charging cost compared with the control group.

[0158] The average idle time of charging piles in the experimental group was 115 minutes, while the average idle time of charging piles in the control group was 55 minutes.

[0159] The number of failures in the experimental group was significantly lower than that in the control group. The experimental group recorded 2 failures in total, while the control group recorded 11 failures. The higher failure rate of charging piles in the control group increased the waiting and repair time for users, affecting the overall utilization rate of charging piles.

[0160] The average idle times of the experimental group was 5.83 times, while the average idle times of the control group was 3.25 times. The idle times of the experimental group were significantly higher, which shows that the allocation strategy of the present invention can effectively utilize those charging piles that are idle for a long time, reducing the waste of idle resources.

[0161] In summary, the present invention achieves better results in terms of economy, utilization rate of charging piles and convenience.

[0162] Example 3, reference Figure 2 , which is an embodiment of the present invention, provides a charging pile and electric vehicle allocation system, including a charging pile allocation function construction module, an electric vehicle user selection function construction module, and an electric vehicle user and charging pile allocation module.

[0163] The charging pile allocation function construction module establishes an allocation function, the electric vehicle user selection function construction module is used to establish an electric vehicle user selection function, and the electric vehicle user and charging pile allocation module is used to match the information reported by the electric vehicle user and the number of the charging pile to be selected.

[0164] If the function 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 this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0165] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0166] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0167] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. It should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and are not limited. Although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

[0168] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for allocating charging piles and electric vehicles, characterized in that: include: Establish an allocation model for charging piles within the allocation range based on the idle status of charging piles and the degree of equipment degradation; Establish an optimal selection function for electric vehicle users based on the economics of electric vehicle users and the distance of the charging pile relative to the user's starting location; After the calculation of the charging pile allocation function and the electric vehicle user optimization function, the information reported by the electric vehicle user and the number of the charging pile to be selected are matched.

2. The method for allocating charging piles and electric vehicles according to claim 1, characterized in that: The method of establishing an allocation function for charging piles within the allocation range according to the idleness of the charging piles and the degree of equipment degradation includes evaluating the idleness of the charging piles, determining the availability of the idleness for the current charging demand, and constructing an allocation model a1, including the idle time and the number of idle times of the charging piles, and inputting the charging pile ID and the current time t c ; Perform data processing to obtain the idle time record of the charging pile, including the start idle time and the end idle time; Find out at the current time t c The last record before the idle period ends, denoted as t l ; Output current time and t l The time difference between the two is used to count the number of idle times of the charging pile N. i ; Free time is proportional to the rating; The number of idle times is proportional to the rating; Combine the current time with t l The time difference between the two and the number of idle times of the charging piles are counted to construct the allocation model a1, which is expressed as: Among them, w1 and w2 represent weight coefficients, N max Indicates the maximum idle times threshold, T m Indicates the maximum idle time threshold.

3. The method for allocating charging piles and electric vehicles according to claim 2, characterized in that: The establishment of an allocation model for charging piles within the allocation range according to the idle status of the charging piles and the degree of equipment degradation includes constructing a charging pile allocation function a2 for evaluating the degree of equipment degradation of the charging piles, including the service life and failure rate of the charging piles; The charging pile allocation function a2 is designed to evaluate the equipment degradation of the charging piles and reflect the reliability and maintenance requirements; Enter the charging pile number; Get the service life Y of the charging pile usage , obtain the fault record of the charging pile and count the number of faults N failure ; The age is inversely proportional to the score; The number of failures is inversely proportional to the score; Combined with Y usage and N failure , the charging pile allocation function a2 is constructed as: Among them, w3 and w4 represent weight coefficients, Y max Indicates the maximum service life, N failure Indicates the number of failures of the charging pile, N max_failure Indicates the maximum fault count threshold.

4. The method for allocating charging piles and electric vehicles according to claim 3, characterized in that: The establishment of an allocation model for charging piles within the allocation range according to the idleness of charging piles and the degree of equipment degradation includes adjusting and optimizing a1a2 according to actual conditions to meet needs and scenarios; Further refine the allocation strategy based on the geographical location and charging power of the charging piles; Taking geographical location factors into consideration, the distance score is output, including: According to the departure location reported by the electric vehicle user, output the distance to each charging pile; Set a distance scoring function based on the distance, and use an inverse proportional function or exponential function to make the distance proportional to the score; Considering the geographical location weight, the distance score is combined with the results of the charging pile allocation functions a1 and a2, and the distance score is weighted and added to the final score, which is expressed as: S final =w1×a1+w2×a2+w3×S distance Among them, S distance represents the distance score, S final Indicates the final rating.

5. The method for allocating charging piles and electric vehicles according to claim 4, characterized in that: The establishment of an allocation model for charging piles within the allocation range according to the idleness of charging piles and the degree of equipment degradation includes considering the charging power factor. Regarding the charging power score: Different electric vehicles require charging piles of different powers for charging. The required charging power range is determined based on the user's vehicle model or battery requirements; Set a score for the charging power of each charging pile, and increase the score within the power range that meets user needs. About power weights: Combine the charging power score with the results of the charging pile allocation functions a1 and a2, give the charging power score a weight, and add it to the final score; Regarding charging time considerations: Taking into account the charging time requirements of electric vehicle users, the estimated charging time is output by combining the charging power and battery capacity, and will be used as part of the score.

6. The method for allocating charging piles and electric vehicles according to claim 5, characterized in that: The establishing of the electric vehicle user optimization function according to the economic efficiency of the electric vehicle user and the distance of the charging pile relative to the user's starting position includes the electric vehicle user optimization function comprehensively considering the economic efficiency and convenience of the user to provide the user with the best charging option; Establish the charging unit price of the charging pile and the distance from the user's starting location to the charging pile; Combine these two variables into one function and assign different weights to reflect the importance users place on economy and convenience; w price and w distance Represent the weights of price and distance respectively, the values ​​are between 0 and 1, and the sum of the two is 1; The optimal function definition of electric vehicle users is expressed as: Among them, S optimality represents the optimal rating of electric vehicle users, w price represents the price weight coefficient, w distance represents the distance weight coefficient, price_per_kWh represents the charging price of the charging pile, d charger represents the distance from the current location of the electric vehicle user to the charging station, ∈ = 0.01, to avoid the denominator being zero; The user selects the optimal charging pile based on the score of the optimal function of the optimal electric vehicle user.

7. The method for allocating charging piles and electric vehicles according to claim 6, characterized in that: The matching of the information reported by the electric vehicle user and the number of the charging pile to be selected after the calculation of the charging pile allocation function and the electric vehicle user optimization function includes matching the information reported by the electric vehicle user and the number of the charging pile to be selected after the output of the charging pile allocation function and the electric vehicle user optimization function; The matching results are divided into three cases: If only one of the numbers reported by the electric vehicle user and the operator number coincides, it means that the reservation is valid. At this time, the user will receive a text message notification to confirm the location of the charging station and related information; If the number reported by the electric vehicle user and the operator number overlap in more than one item, it means that the reservation is valid, but the system will reallocate it according to the result of the user's selection function and send a message to the user's mobile phone, waiting for the user's confirmation; There is no overlap between the number reported by the electric vehicle user and the operator number, which means that the user's reservation is invalid, but the system allows the user to enter the next round of reservations.

8. A system using the method for allocating charging piles and electric vehicles as claimed in any one of claims 1 to 7, characterized in that: It includes a charging pile allocation function construction module, an electric vehicle user selection function construction module, and an electric vehicle user and charging pile allocation module; The charging pile allocation function construction module establishes an allocation function; The electric vehicle user optimization function construction module is used to establish an electric vehicle user optimization function; The electric vehicle user and charging pile allocation module is used to match the information reported by the electric vehicle user with the number of the charging pile to be selected.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for allocating charging piles and electric vehicles according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for allocating charging piles and electric vehicles according to any one of claims 1 to 7 are implemented.

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