Utility optimization method for height-adjustable directional pendant charging

Abstract

The present invention discloses a utility optimization method for height-adjustable directed pendant charging, which specifically includes the following steps: defining a set of height-adjustable directed pendant chargers and a set of rechargeable devices; defining a charging power formula based on height, a charging area radius formula, and a rechargeable device utility formula; defining a utility maximization problem for height-adjustable directed pendant charging; proposing a height discretization method for height-adjustable directed pendant charging and converting the charging utility maximization problem into a discretized problem; converting the discretized problem into an equivalent multidimensional knapsack problem; and obtaining a charging scheduling plan through a utility optimization charging scheduling algorithm based on a height discretization method. The present invention provides a utility optimization method for height-adjustable directed pendant charging, which determines the activation of directed pendant chargers and the height scheduling plan to maximize total utility without exceeding the cost budget constraint.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless charging scheduling, and in particular to a utility optimization method for height-adjustable directional pendant charging. Background Art

[0002] As a wireless energy transmission technology that can achieve one-to-many and long-distance charging, RF wireless charging has received much attention from academia and industry in recent years, and has been widely used in medical monitoring, wireless sensor networks and other fields.

[0003] However, in RF wireless charging, the power received by the RF antenna may be reduced due to the obstruction of obstacles, thus affecting the charging effect. In order to solve this important problem, many researchers have proposed solutions to deal with obstacle obstruction. However, methods such as fixing the charging distance and finding the receiving power enhancement area not only have low space utilization, but also require the equipment to be movable, and have limited practicality. Compared with these methods, a new charging mode in which the charger is suspended can not only greatly improve the space utilization while ensuring that the rechargeable devices do not affect each other, but also can be applied to both static charging and mobile charging scenarios, and has high practical value. Therefore, based on this suspension charging mode, the present invention further performs directional suspension charging scheduling to optimize the total charging utility.

[0004] Although there are studies on suspended charging, in existing work, the height of the charger is fixed. When the charging power of the charger is not adjustable, it is difficult to meet scenarios with different receiving power requirements. For example, some rechargeable devices may want to complete charging as quickly as possible and require a higher receiving power, while in other scenarios, other rechargeable devices are not allowed to receive too much power for safety reasons. In order to better adapt to various demand scenarios, height-adjustable directed suspended charging can be scheduled on the basis of traditional suspended charging, that is, the directed charger is suspended vertically, and the height of the directed suspended charger is adjusted to change the charging area on the ground and the size of the received power, so as to better meet the diverse charging needs and provide a larger optimization space for the optimization of the total charging utility. Summary of the invention

[0005] The purpose of the present invention is to better meet the diversified charging needs, provide a larger optimization space for the optimization of the total charging utility, and provide a utility optimization method for height-adjustable directional suspension charging.

[0006] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0007] A utility optimization method for height-adjustable directional pendant charging, comprising the following steps:

[0008] A set of height-adjustable directional pendant chargers and a set of chargeable devices are defined;

[0009] Define the formula for charging power based on altitude, the formula for the radius of the charging area, and the formula for the utility of the rechargeable device;

[0010] Define the utility maximization problem of height-adjustable directed pendant charging;

[0011] A highly discretized method for height-adjustable directional overhang charging is proposed and the charging utility maximization problem is transformed into a discretized problem.

[0012] Convert the discretized problem into an equivalent multidimensional knapsack problem;

[0013] The charging scheduling scheme is obtained through a utility optimization charging scheduling algorithm based on a highly discretized method.

[0014] Furthermore, a set of height-adjustable directional hanging chargers and a set of chargeable devices are defined, including:

[0015] Set the height adjustable directional hanging charger set to , where each directed pendant charger , , the charging power of each charger is , the maximum charging angle is , the maximum charging distance is ,in ; Set the unit power activation cost of all directional pendant chargers to ; Directed pendant charger Height In the feasible range within, that is ;

[0016] Set the rechargeable device collection to , every rechargeable device , , the utility weight corresponding to the unit power obtained by the rechargeable device is .

[0017] Furthermore, the formula for charging power based on height, the formula for the radius of the charging area, and the formula for the utility of the rechargeable device are defined, including:

[0018] When there is a directed pendant charger The height is When charging the device From the directed pendant charger The calculation formula for the received power obtained at the location is:

[0019] (1)

[0020] in, and Represents two constants determined by the hardware and environment, Indicates rechargeable device and directed pendant chargers The horizontal distance between

[0021] Directed pendant charger The radius of the charging area formed on the ground By height Determine and and There is a relationship, the specific formula is:

[0022] (2)

[0023] Rechargeable devices The utility formula is:

[0024] (3)

[0025] in, A 0-1 variable used to represent a directed pendant charger Whether it is enabled.

[0026] Furthermore, the utility maximization problem of height-adjustable directional overhanging charging is defined, and the specific formula includes:

[0027] (4)

[0028] (4-1)

[0029] (4-2)

[0030] (4-3)

[0031] Among them, formula (4) aims to maximize the total utility of rechargeable devices, constraint (4-1) is used to ensure that the height of all turned-on directional hanging chargers is within the feasible interval, and constraint (4-2) is used to ensure that the total cost of turning on the charger does not exceed the total cost budget, where represents the total cost budget, and constraint (4-3) is used to ensure is a 0-1 variable.

[0032] Furthermore, a highly discretized method for highly adjustable directional overhang charging includes:

[0033] For any directed pendant charger , traverse all rechargeable devices, when the rechargeable device and directed pendant chargers The horizontal distance between When the height interval Discretize, the specific formula is:

[0034] (5)

[0035] Will , , Defined as height intervals The lowest discretization height, the highest discretization height and the High discretization height, where , , , represents a discretization error greater than zero;

[0036] When there is a directed pendant charger The heights are , and When charging the device From the directed pendant charger The calculation formulas for the received power obtained at are given by formula (6), formula (7) and formula (8) respectively:

[0037] (6)

[0038] (7)

[0039] (8)

[0040] The discretized height formula is:

[0041] (9)

[0042] Add all the discretized heights obtained The discretized height set .

[0043] Furthermore, the charging utility maximization problem is transformed into a discretized problem, and the specific formula is:

[0044] (10)

[0045] (10-1)

[0046] (10-2)

[0047] (10-3).

[0048] Furthermore, the discretized problem is transformed into an equivalent multidimensional knapsack problem, which specifically includes the following steps:

[0049] Will All possible discretized heights in are considered as one item, then the item The utility function is: ;

[0050] make Tuple express of dimensions, among which is the number of directed pendant chargers, where , ;

[0051] The discretized problem is transformed into a multidimensional knapsack problem. The specific formula is:

[0052] (11)

[0053] (11-1)

[0054] (11-2)

[0055] (11-3)

[0056] in, A 0-1 variable used to represent items Whether it is selected.

[0057] Furthermore, a charging scheduling scheme is obtained by a utility optimization charging scheduling algorithm based on a highly discretized method, which specifically includes the following steps:

[0058] A1: Input directed pendant charger set , rechargeable device collection , feasible height range , charging power , maximum charging angle , maximum charging distance , utility weight , the unit power start-up cost is , total cost budget ;

[0059] A2: Initialize all directed pendant charger parameters, that is, for all ,make , , and perform a highly discretized method to obtain ;

[0060] A3: For each , calculate the utility, that is ;

[0061] A4: According to The size of Sort in non-increasing order, where ;

[0062] A5: According to the sorting results of step A4, Add solution set , until constraints (11-1) and (11-2) are no longer satisfied;

[0063] A6: For each and ,make , .

[0064] According to one aspect of the present invention, a storage medium is provided, wherein instructions are stored in the storage medium, and when a computer reads the instructions, the computer is caused to execute any one of the above-mentioned utility optimization methods for height-adjustable directional suspension charging.

[0065] According to another aspect of the present invention, there is provided an electronic device, comprising a processor and the above-mentioned storage medium, wherein the processor executes instructions in the storage medium.

[0066] Compared with the prior art, the present invention has the following beneficial effects:

[0067] 1. The utility optimization charging scheduling algorithm based on a highly discretized method of the present invention has low time complexity.

[0068] 2. The utility optimization charging scheduling algorithm based on the highly discretized method of the present invention has a high degree of approximation for the utility maximization problem of highly adjustable directed pendant charging.

[0069] 3. The present invention can determine the activation and height scheduling scheme of the directional suspended charger without exceeding the cost budget constraint to maximize the total utility. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0071] Figure 1 This is a schematic diagram of the process of Example 1 of the present invention;

[0072] Figure 2 This is a schematic diagram of the charging scenario structure of Example 1 of the present invention;

[0073] Figure 3 Schematic diagram of the charging area of ​​a directional suspended charger at different heights in Example 1 of the present invention;

[0074] Figure 4 This is a flow chart of a charging scheduling algorithm according to Embodiment 1 of the present invention;

[0075] Figure 5 It is a horizontal coordinate top view of Example 2 of the present invention;

[0076] Figure 6 A total utility data diagram showing the change in the number of directional pendant chargers in Example 3 of the present invention;

[0077] Figure 7 A total utility data diagram of changing the number of rechargeable devices in Example 3 of the present invention;

[0078] Figure 8 A total utility data diagram of changing the unit power start-up cost in Example 3 of the present invention;

[0079] Fig. 9 This is a total utility data diagram of changing the maximum charging angle of the directional suspended charger in Example 3 of the present invention;

[0080] Fig.10 A total utility data diagram of changing the utility weight of a rechargeable device in Embodiment 3 of the present invention;

[0081] Fig.11 This is a total utility data diagram of changing the charging power of a directed pendant charger in Example 3 of the present invention;

[0082] Fig.12 This is a running time data diagram of changing the number of directed pendant chargers and the number of chargeable devices in Example 3 of the present invention;

[0083] Fig.13 This is a data diagram of the total utility and running time of changing the discretization error in Example 3 of the present invention;

[0084] Fig.14 This is a graph showing the total utility and operating time data of changing the number of directed pendant chargers in Example 3 of the present invention. DETAILED DESCRIPTION

[0085] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0086] Example 1: Figure 1As shown, a utility optimization method for height-adjustable directional pendant charging of the present invention specifically includes the following steps:

[0087] S1: Define a set of height-adjustable directional hanging chargers and a set of rechargeable devices;

[0088] The height adjustable directional hanging charger set is , , belong to different charging providers, so each directed hanging charger , have their own charging power , maximum charging angle , and the maximum charging distance ,in ; The unit power startup cost of all directional pendant chargers is ; Directed pendant charger Height In the feasible range within, that is ; The rechargeable device set is , each rechargeable device may perform different tasks. , , obtain the utility weight corresponding to the unit electricity The scene structure diagram of the present invention is as follows Figure 2 shown.

[0089] S2: Define the charging formula based on height, the charging area radius formula, and the utility formula of the rechargeable device;

[0090] The altitude-based charging formula includes:

[0091] When there is a directed pendant charger The height is When charging the device From the directed pendant charger The received power obtained at is:

[0092] (1)

[0093] in, and are two constants determined by the hardware and environment, For rechargeable devices and directed pendant chargers The horizontal distance between

[0094] The charging area radius formula includes:

[0095] like Figure 3As shown, there is a directional pendant charger The radius of the charging area formed on the ground By height Determine and based on and There are different calculation formulas for the relationship between , which can be expressed as:

[0096] (2)

[0097] The rechargeable device utility formula includes:

[0098] Rechargeable devices The utility formula is:

[0099] (3)

[0100] in, A 0-1 variable used to represent a directed pendant charger Whether it is enabled.

[0101] S3: Formalize the utility maximization problem of height-adjustable directed pendant charging;

[0102] make represents the total cost budget;

[0103] The utility maximization problem of height-adjustable directed pendant charging is defined as:

[0104] (4)

[0105] (4-1)

[0106] (4-2)

[0107] (4-3)

[0108] Among them, formula (4) aims to maximize the total utility, constraint (4-1) ensures that the height of all turned-on directional hanging chargers is within the feasible range, constraint (4-2) ensures that the total cost of turning on the charger does not exceed the total cost budget, and constraint (4-3) ensures is a 0-1 variable.

[0109] S4: Propose a highly discretized method for highly adjustable directed overhang charging;

[0110] For a directed pendant charger and rechargeable devices , if satisfied , then for the height interval Discretize it, where

[0111] (5)

[0112] Will , , Defined as height intervals The lowest discretization height, the highest discretization height and the High discretization height, where , , , is a discretization error greater than zero;

[0113] have

[0114] (6)

[0115] (7)

[0116] (8)

[0117] Therefore, the discretized height formula is:

[0118] (9)

[0119] For any directed pendant charger , traverse all rechargeable devices, when the rechargeable device satisfy When , perform the above operation and add all the discretized heights obtained to The discretized height set ;

[0120] Therefore, the original problem can be transformed into a discretized problem, which can be expressed as follows:

[0121] (10)

[0122] (10-1)

[0123] (10-2)

[0124] (10-3).

[0125] S5: Convert the discretized problem into an equivalent multidimensional knapsack problem;

[0126] Will All possible discretized heights in are considered as one item, then the item The effect ;

[0127] use Tuple express of dimensions, among which is the number of directed pendant chargers, , ;

[0128] The discretized problem can be expressed as an equivalent multidimensional knapsack problem, as follows:

[0129] (11)

[0130] (11-1)

[0131] (11-2)

[0132] (11-3)

[0133] in, A 0-1 variable used to represent items Whether it is selected.

[0134] S6: calling the utility optimization charging scheduling algorithm based on the highly discretized method to obtain a charging scheduling plan;

[0135] like Figure 4 As shown, the scheduling algorithm process includes:

[0136] A1: Input directed pendant charger set , rechargeable device collection , feasible height range , charging power , maximum charging angle , maximum charging distance , utility weight , the unit power start-up cost is , total cost budget ;

[0137] A2: Initialize all directed pendant charger parameters, that is, for all ,make , , and perform a highly discretized method to obtain ;

[0138] A3: For each , calculate its utility, that is, ;

[0139] A4: According to The size of Sort in non-increasing order, where ;

[0140] A5: According to the order described in step A4, Add solution set , until constraints (11-1) and (11-2) are no longer satisfied;

[0141] A6: For each and ,make , .

[0142] The time complexity of the algorithm is determined by the order of step A4, and in the worst case, the total number of discretized heights is To simplify the expression, let . Using quick sort, the time complexity of the algorithm is .

[0143] The utility optimization charging scheduling algorithm based on the highly discretized method has the following advantages for the utility maximization problem of highly adjustable directed overhang charging: The approximation of is the harmonic series.

[0144] Lemma 1: Directed pendant chargers turned on in the optimal solution The height must be between it and a rechargeable device The corresponding height range Inside.

[0145] Lemma 2: After the original problem is transformed into a discretized problem by using a highly discretized method for height-adjustable directed pendant charging, if the optimal total utility of the original problem is , the optimal total utility of the discretized problem is , then .

[0146] Since the discretized problem is equivalent to the multidimensional knapsack problem, we solve the multidimensional knapsack problem according to steps A4 and A5. Therefore, the utility optimization charging scheduling algorithm based on the highly discretized method has a good approximation for the discretized problem. The approximation of .

[0147] Embodiment 2: A utility optimization method for height-adjustable directional pendant charging according to the present invention specifically comprises the following steps:

[0148] In this embodiment, there are height-adjustable directional suspended chargers in S1, S2 and S3. }, the rechargeable device collection is , are distributed in a 5m*5m square area. Table 1 shows the parameters related to the directional hanging charger, and Table 2 shows the parameters related to the rechargeable device. Figure 5 This is a top view of Example 2.

[0149] Table 1 Parameters of directional suspension charger

[0150]

[0151] Table 2 Rechargeable device related parameters

[0152]

[0153] also, , , , , .

[0154] A1: Input directed pendant charger set , rechargeable device collection , and other parameters;

[0155] A2: Initialize all directed pendant charger parameters and perform a high degree of discretization to obtain ,by For example, , ;

[0156] Execute the high discretization method in S4 and obtain ;

[0157] A3: For each , calculate its utility, that is, ;

[0158] by , For example, .

[0159] A4: Based on The size of In non-increasing order;

[0160] Still , For example, ;

[0161] The sorting results are ,in , , .

[0162] A5: Add one by one big , until constraints (11-1) and (11-2) are no longer satisfied, the solution set is obtained ;

[0163] , The four-tuple of , satisfying the constraints, can be directly added ,at this time ;

[0164] ,because The four-tuple of ,and The four-tuple After adding, we get , does not satisfy constraint (11-2), do not join;

[0165] Nor can they join;

[0166] ,because The four-tuple of ,and The four-tuple After adding, we get , satisfying the constraints, can be added, at this time ;

[0167] Not joinable;

[0168] final, .

[0169] A6: For each and ,make , ;

[0170] Therefore, there is , , , ;

[0171] The total utility is 6.8466.

[0172] Example 3: In order to verify and illustrate the technical effects of the present invention, Example 3 involves three solutions for comparative testing with the present invention method:

[0173] 1. Greedy selection algorithm based on minimum height: The optional height of each directed pendant charger is fixed to the minimum height, and the directed pendant charger with the largest utility-cost ratio is greedily selected each time to be added until no more can be added.

[0174] 2. Greedy selection algorithm based on maximum height: The optional height of each directed pendant charger is fixed to the maximum height, and the directed pendant charger with the largest utility-cost ratio is greedily selected each time to be added until no more can be added.

[0175] 3. Greedy selection algorithm based on random height: select a random height in the feasible height range for each directed pendant charger, and greedily select the directed pendant charger with the largest utility-cost ratio each time to add until no more can be added.

[0176] Parameter setting: Set the directional pendant charger and rechargeable equipment in a 20m*20m square area. Set the default parameters as follows: Number of directional pendant chargers , number of rechargeable devices , charging power , maximum charging angle , Environmental parameters , , utility weight , unit power start-up cost , total cost budget , discretization error ; According to formula (1), set , that is, when the received power is less than 0.1 mW When , it is considered as no receiving power; in addition, setting , ,in and are two random numbers and Next we vary the values ​​of key parameters to explore their effect on the algorithm, with each measurement being averaged over 300 random topologies.

[0177] like Figure 6 As shown in the figure, the total utility of all algorithms increases with the number of directed pendant chargers. The utility-optimized charging scheduling algorithm based on the height discretization method always has the highest total utility. Although more rechargeable devices can be covered at the highest height, the received power may be low. Therefore, the total utility of the greedy selection algorithm based on the highest height is always the lowest. However, the total utility of the greedy selection algorithm based on the lowest height is also always lower than that of the utility-optimized charging scheduling algorithm based on the height discretization method. Compared with the other three comparison algorithms, the total utility of the utility-optimized charging scheduling algorithm based on the height discretization method is increased by an average of 26.15%, 67.49% and 40.71%, respectively.

[0178] like Figure 7 As shown in the figure, the total utility of all algorithms increases with the number of rechargeable devices. Compared with the other three comparison algorithms, the total utility of the utility optimization charging scheduling algorithm based on the highly discretized method is increased by 25.15%, 67.38% and 41.03% on average, respectively.

[0179] like Figure 8 As shown in the figure, as the unit power activation cost increases, the number of directed hanging chargers that can be activated decreases, so the total utility of all algorithms decreases. Compared with the other three comparison algorithms, the total utility of the utility optimization charging scheduling algorithm based on the highly discretized method is increased by 22.10%, 66.81% and 39.53% on average, respectively.

[0180] like Fig. 9 As shown in the figure, as the maximum charging angle of the directional pendant charger increases, the total utility of all algorithms increases. This is because at the same height, the directional pendant charger can cover more rechargeable devices. Compared with the other three comparison algorithms, the total utility of the utility optimization charging scheduling algorithm based on the height discretization method is increased by 24.68%, 74.13% and 44.59% on average, respectively.

[0181] like Fig.10 As shown in the figure, as the utility weight of rechargeable devices increases, the total utility of all algorithms increases. Compared with the other three comparison algorithms, the total utility of the utility optimization charging scheduling algorithm based on the highly discretized method is increased by 17.74%, 59.98% and 35.90% respectively on average.

[0182] like Fig.11 As shown in Figure 2, as the charging power of the directed pendant charger increases, the total utility of all algorithms increases. However, the increasing trend slows down in the later stage. This is because although the power received by the rechargeable device increases, the cost of turning on the directed pendant charger also increases. The combination of these two factors leads to Fig.11 Compared with the other three comparison algorithms, the total utility of the utility optimization charging scheduling algorithm based on the highly discretized method is improved by 21.56%, 64.56% and 38.14% on average, respectively.

[0183] In addition, we also tested the running time of the algorithm. Fig.12 As shown in the figure, although the running time of the utility optimization charging scheduling algorithm based on the highly discretized method is higher than that of the other three comparison algorithms, it never exceeds 0.1 seconds. Considering the improvement in total utility, we believe that such a time cost is reasonable.

[0184] Furthermore, we tested the impact of discretization error on the algorithm proposed in this invention. Fig.13 As shown in , as the discretization error increases, the total utility gradually decreases and the running time also gradually decreases. When Compared with the previous case, the total utility is improved by 5.19%. , it is only 0.0111 seconds, so this running time is reasonable.

[0185] Since it is impossible to find the actual optimal solution for the original problem in a continuous interval, we compare it with the optimal solution of the discretized problem. Fig.14 As shown in the figure, the total utility of the utility optimization charging scheduling algorithm based on the highly discretized method is only 6.82% lower than the optimal solution of the discretized problem on average. When the number of directed hanging chargers is 28, it takes 33.84 seconds to find the optimal solution of the discretized problem, which is much slower than the algorithm proposed in the present invention. Therefore, the utility optimization charging scheduling algorithm based on the highly discretized method in the present invention is more practical.

[0186] The above embodiments are only used to illustrate the technical solution 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 solution of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A utility optimization method for height-adjustable directional pendant charging, It is characterized in that The following steps are involved: A height-adjustable directional pendant charger set and a chargeable device set are defined; Define the formula for charging power based on altitude, the formula for the radius of the charging area, and the formula for the utility of the rechargeable device; Define the utility maximization problem of height-adjustable directed pendant charging; A highly discretized method for height-adjustable directional overhang charging is proposed and the charging utility maximization problem is transformed into a discretized problem. Convert the discretized problem into an equivalent multidimensional knapsack problem; The charging scheduling scheme is obtained through the utility optimization charging scheduling algorithm based on the highly discretized method; The definition includes a height-adjustable directional hanging charger set and a chargeable device set, including: Set the height-adjustable directional suspension charger set to M = {s 1 ,s 2 ,…,s m }, where each directed pendant charger s j ∈M, j∈{1,2,…,m}, the charging power of each charger is P j , the maximum charging angle is A j , the maximum charging distance is D j ,in Set the unit power activation cost of all directed pendant chargers to c; directed pendant chargers s j Height h j In the feasible interval [b j ,t j ], that is, h j ∈[b j ,t j ]; Set the rechargeable device set to N = {o 1 ,o 2 ,…,o n }, each rechargeable device o i ∈N, i∈{1,2,…,n}, the utility weight corresponding to the unit power obtained by the rechargeable device is w i ; Define the formula for charging power based on altitude, the formula for the radius of the charging area, and the formula for the utility of the rechargeable device, including: When the directed pendant charger s j The height is h j When charging the device i From directed pendant chargers j The calculation formula for the received power obtained at the location is: Among them, α and β are two constants determined by hardware and environment, r ij Indicates rechargeable device i and directed pendant chargers j The horizontal distance between Directed Pendant Chargers j The radius of the charging area formed on the ground By height h j Determine, and with h j and D j cosA j There is a relationship, the specific formula is: Rechargeable devices i The utility formula is: Among them, x j is a 0-1 variable used to represent the directional pendant charger s j Whether it is turned on; The utility maximization problem of height-adjustable directional pendant charging is defined, and the specific formula includes: Among them, formula (4) aims to maximize the total utility of the rechargeable device, constraint (4-1) is used to ensure that the height of all turned-on directed hanging chargers is within the feasible interval, constraint (4-2) is used to ensure that the total cost of turning on the charger does not exceed the total cost budget, where C represents the total cost budget, and constraint (4-3) is used to ensure that x j is a 0-1 variable.

2. The method according to claim 1, It is characterized in that A highly discretized approach for highly adjustable directed overhang charging, including: For any directed pendant charger s j , traverse all rechargeable devices, when the rechargeable device o i and directed pendant chargers j The horizontal distance between When the height interval Discretize, the specific formula is: Will Defined as height intervals The lowest discretization height, the highest discretization height, and the v+1th highest discretization height in , where ε represents a discretization error greater than zero; When the directed pendant charger s j The heights are and When charging the device i From directed pendant chargers j The calculation formulas for the received power obtained at are given by formula (6), formula (7) and formula (8) respectively: The discretized height formula is: Add all the discretized heights obtained to s j The discretized height set Ω j .

3. The method according to claim 2, It is characterized in that The charging utility maximization problem is transformed into a discretized problem. The specific formula is:

4. The method according to claim 3, It is characterized in that The discretized problem is transformed into an equivalent multidimensional knapsack problem, which includes the following steps: Will All possible discretized heights in are considered as one item, then the item The utility function is: Let m+1 tuple (c k,0 ,c k,1 ,…,c k,m ) means h k m+1 dimensions, where m is the number of directed pendant chargers, and c k,0 =cP j , The discretized problem is transformed into a multidimensional knapsack problem. The specific formula is: Among them, z k It is a 0-1 variable, used to represent item h k Whether it is selected.

5. The method according to claim 4, It is characterized in that The charging scheduling scheme is obtained by the utility optimization charging scheduling algorithm based on a highly discretized method, which specifically includes the following steps: A1: Input the set of directed hanging chargers M, the set of rechargeable devices N, and the feasible height interval [b j ,t j ], charging power P j , maximum charging angle A j , maximum charging distance D j , utility weight w i , the unit power startup cost is c, and the total cost budget is C; A2: Initialize all directed pendant charger parameters, that is, for all s j ∈M, let x j =0,h j =b j , and perform a highly discretized method to obtain Ω j ; A3: For each Compute utility, i.e. A4: According to The size of h k Sort in non-increasing order, where h k ∈Ω j ; A5: According to the sorting results of step A4, h k Add solution set Ω * , until constraints (11-1) and (11-2) are no longer satisfied; A6: For each h k ∈Ω * And h k ∈Ω j , let x j =1,h j =h k .

6. A storage medium, It is characterized in that The storage medium stores instructions, and when a computer reads the instructions, the computer executes the utility optimization method for height-adjustable directional suspension charging as described in any one of claims 1 to 5.

7. An electronic device, It is characterized in that The invention comprises a processor and the storage medium as claimed in claim 6, wherein the processor executes instructions in the storage medium.

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