Charging device setting method and apparatus, device, and storage medium

Abstract

This disclosure provides a method, apparatus, device, and storage medium for setting up a charging device, relating to the field of computer technology. The method includes acquiring the number of electric vehicles and the location information of delivery stations; determining the path corresponding to each electric vehicle based on the number of electric vehicles, the location information of delivery stations, and a preset algorithm; determining the electrical energy consumed by each electric vehicle based on its path; and, if any electric vehicle's required electrical energy exceeds the energy that the current electric vehicle can store, setting up a charging device on the path corresponding to that electric vehicle. This allows electric vehicles to be located close to the charging device, making charging more convenient.

Description

Technical Field

[0001] This disclosure relates to the field of computer technology, and in particular to a charging device setting method, apparatus, device and storage medium. Background Technology

[0002] With societal development, electric vehicles are becoming increasingly common. Because they are powered by electricity, electric vehicles offer advantages such as clean energy and high efficiency.

[0003] However, the energy storage of current electric vehicles is limited, and charging devices are needed to ensure their normal operation. However, current charging device installations suffer from problems such as unreasonable placement, making electric vehicle charging rather cumbersome. Summary of the Invention

[0004] This disclosure provides a charging device setting method, apparatus, equipment, and storage medium, which at least to some extent overcomes the current problem of the cumbersome charging of electric vehicles.

[0005] Other features and advantages of this disclosure will become apparent from the following detailed description, or may be learned in part from practice of this disclosure.

[0006] According to one aspect of this disclosure, a method for setting up a charging device is provided, comprising: acquiring the number of electric vehicles and the location information of the delivery stations to be delivered;

[0007] The route for each electric vehicle is determined based on the number of electric vehicles, the location information of the delivery stations, and a preset algorithm.

[0008] The electrical energy required for each electric vehicle is determined based on the path corresponding to each electric vehicle.

[0009] If any electric vehicle needs to consume more electrical energy than it can store, a charging device will be installed on the path corresponding to that electric vehicle.

[0010] In one embodiment of this disclosure, the path corresponding to each electric vehicle is determined based on the number of electric vehicles, the location information of the delivery stations, and a preset algorithm, including:

[0011] The path length for each preset route is determined based on the number of electric vehicles and the location information of the delivery stations.

[0012] The sum of the time variances of each electric vehicle's operation is determined based on the path length corresponding to each preset path scheme and the number of electric vehicles.

[0013] The fitness function value for each preset path scheme is determined by the sum of the path length corresponding to each preset path scheme and the time variance of each electric vehicle running in each preset path scheme, according to the preset fitness function formula.

[0014] The target preset path scheme is determined based on the fitness function value corresponding to each preset path scheme.

[0015] Determine the path for each electric vehicle based on the target preset path plan;

[0016] The fitness function formula is as follows:

[0017]

[0018] Where F is the fitness function value, ω1 and ω2 are coefficients, e is the number of electric vehicles, and L i Let t be the path length corresponding to any path in the preset path scheme. var The variance of the running time of each electric vehicle in each preset route scheme.

[0019] In one embodiment of this disclosure, determining the path length corresponding to each preset route scheme based on the number of electric vehicles and the location information of the delivery stations includes:

[0020] The path length for each preset route is determined based on the number of electric vehicles, the location information of the delivery stations, and a first preset formula; wherein the first preset formula is:

[0021]

[0022] Among them, L i Let d(E) be the path length corresponding to any path in the preset path scheme. j E j+1 () represents the distance between the j-th delivery point and the (j+1)-th delivery point. From the first delivery point to the nth i The distance between n delivery points i This represents the number of delivery points on any one of the preset routes.

[0023] In one embodiment of this disclosure, determining the sum of the time variances of each electric vehicle's operation based on the path length corresponding to each preset path scheme and the number of electric vehicles includes:

[0024] The sum of the time variances for each electric vehicle's operation is determined based on the path length corresponding to each preset path scheme, the number of electric vehicles, and the second preset formula; wherein, the second preset formula is:

[0025]

[0026] Among them, t var The sum of the time variances of operation for each electric vehicle, t i Let t be the running time of any path in the preset path scheme. ave Let be the average running time of all electric vehicles, and e be the number of electric vehicles.

[0027] In one embodiment of this disclosure, determining a target preset path scheme based on the fitness function value corresponding to each preset path scheme includes:

[0028] The fitness function value corresponding to each preset path scheme is iterated according to the fireworks algorithm. When the number of iterations reaches a preset threshold, the optimal fitness function value corresponding to each preset path scheme is obtained.

[0029] The preset path scheme corresponding to the smallest optimal fitness function value is determined as the target preset path scheme.

[0030] In one embodiment of this disclosure, the fitness function value corresponding to each preset path scheme is iterated according to the fireworks algorithm. When the number of iterations reaches a preset threshold, the optimal fitness function value corresponding to each preset path scheme is obtained, including:

[0031] The explosion radius and number of explosions of the fireworks are determined according to the third and fourth preset formulas, respectively.

[0032] Based on the determined fireworks explosion radius and number of explosions, each preset path is mutated to obtain multiple fitness function values ​​after the mutation is completed;

[0033] Among the multiple fitness function values ​​after mutation, the optimal fitness function value is determined as the optimal fitness function value corresponding to the current preset path scheme;

[0034] The third preset formula is:

[0035]

[0036] The fourth preset formula is:

[0037]

[0038] Among them, A i S is the radius of the fireworks explosion. i Let F be the number of fireworks explosions, and F be the fitness function value corresponding to any preset path scheme. min F is the minimum fitness function value among multiple preset path schemes. max F represents the maximum fitness function value among multiple preset path schemes.ave is the average fitness function value among multiple preset path schemes, where M is a constant and UL is the search boundary constant.

[0039] In one embodiment of this disclosure, determining the electrical energy consumed by each electric vehicle based on the path corresponding to each electric vehicle includes:

[0040] The electrical energy consumed by each electric vehicle is determined based on the path corresponding to each electric vehicle and the fifth preset formula; wherein, the fifth preset formula is:

[0041]

[0042] Where EC is the electrical energy required for any electric vehicle, a, b, c, and d are regression coefficients, v is the current average operating speed of the electric vehicle, and L is the current operating path length of the electric vehicle.

[0043] In one embodiment of this disclosure, a charging device is installed on the path corresponding to the current electric vehicle, including:

[0044] The location for setting up the charging device is determined based on the preset optimization model and the path corresponding to the current electric vehicle.

[0045] Install the charging device according to the determined location.

[0046] According to another aspect of this disclosure, a charging device setting apparatus is provided, comprising:

[0047] The acquisition module is used to acquire the number of electric vehicles and the location information of the delivery stations.

[0048] The first determining module is used to determine the path corresponding to each electric vehicle based on the number of electric vehicles, the location information of the delivery stations, and a preset algorithm.

[0049] The second determining module is used to determine the electrical energy required for each electric vehicle based on the path corresponding to each electric vehicle.

[0050] The setting module is used to set up a charging device on the path corresponding to the current electric vehicle when any electric vehicle needs to consume more electrical energy than the electric vehicle can store.

[0051] In one embodiment of this disclosure, the first determining module includes:

[0052] The first determining unit is used to determine the path length corresponding to each preset path scheme based on the number of electric vehicles and the location information of the delivery stations.

[0053] The second determining unit is used to determine the sum of the time variances of each electric vehicle's operation based on the path length corresponding to each preset path scheme and the number of electric vehicles.

[0054] The third determining unit is used to determine the fitness function value corresponding to each preset path scheme based on the preset fitness function formula, the path length corresponding to each preset path scheme and the sum of the time variances of each electric vehicle running in each preset path scheme.

[0055] The fourth determining unit is used to determine the target preset path scheme based on the fitness function value corresponding to each preset path scheme;

[0056] The fifth determining unit is used to determine the path corresponding to each electric vehicle based on the target preset path scheme;

[0057] The fitness function formula is as follows:

[0058]

[0059] Where F is the fitness function value, ω1 and ω2 are coefficients, e is the number of electric vehicles, and L i Let t be the path length corresponding to any path in the preset path scheme. var The variance of the running time of each electric vehicle in each preset route scheme.

[0060] In one embodiment of this disclosure, the first determining unit includes:

[0061] The first determining subunit is used to determine the path length corresponding to each preset path scheme based on the number of electric vehicles, the location information of the delivery stations, and the first preset formula.

[0062] The first preset formula is:

[0063]

[0064] Among them, L i Let d(E) be the path length corresponding to any path in the preset path scheme. j E j+1 () represents the distance between the j-th delivery point and the (j+1)-th delivery point. From the first delivery point to the nth i The distance between n delivery points i This represents the number of delivery points on any one of the preset routes.

[0065] In one embodiment of this disclosure, the second determining unit includes:

[0066] The second determining subunit is used to determine the sum of the time variances of each electric vehicle's operation based on the path length corresponding to each preset path scheme, the number of electric vehicles, and a second preset formula; wherein the second preset formula is:

[0067]

[0068] Among them, t var The sum of the time variances of operation for each electric vehicle, t i Let t be the running time of any path in the preset path scheme. ave Let be the average running time of all electric vehicles, and e be the number of electric vehicles.

[0069] In one embodiment of this disclosure, the fourth determining unit includes:

[0070] The iterative subunit is used to iterate the fitness function value corresponding to each preset path scheme according to the fireworks algorithm. When the number of iterations reaches a preset threshold, the optimal fitness function value corresponding to each preset path scheme is obtained.

[0071] The third determining subunit is used to determine the preset path scheme corresponding to the smallest optimal fitness function value as the target preset path scheme.

[0072] In one embodiment of this disclosure, the iterative subunit includes

[0073] The first determining element is used to determine the explosion radius and the number of explosions of the fireworks according to the third preset formula and the fourth preset formula, respectively.

[0074] The mutation element is used to mutate each preset path according to the determined firework explosion radius and number of explosions, and obtain multiple fitness function values ​​after mutation;

[0075] The second determining element is used to determine the optimal fitness function value among the multiple fitness function values ​​after mutation as the optimal fitness function value corresponding to the current preset path scheme;

[0076] The third preset formula is:

[0077]

[0078] The fourth preset formula is:

[0079]

[0080] Among them, A i S is the radius of the fireworks explosion. i Let F be the number of fireworks explosions, and F be the fitness function value corresponding to any preset path scheme. minF is the minimum fitness function value among multiple preset path schemes. max F represents the maximum fitness function value among multiple preset path schemes. ave is the average fitness function value among multiple preset path schemes, where M is a constant and UL is the search boundary constant.

[0081] In one embodiment of this disclosure, the second determining module includes:

[0082] The sixth determining unit is used to determine the electrical energy required by each electric vehicle based on the path corresponding to each electric vehicle and the fifth preset formula; wherein, the fifth preset formula is:

[0083]

[0084] Where EC is the electrical energy required for any electric vehicle, a, b, c, and d are regression coefficients, v is the current average operating speed of the electric vehicle, and L is the current operating path length of the electric vehicle.

[0085] In one embodiment of this disclosure, the setting module includes:

[0086] The seventh determining unit is used to determine the location of the charging device based on the preset optimization model and the path corresponding to the current electric vehicle.

[0087] The setting unit is used to set the charging device according to the determined location of the charging device.

[0088] According to another aspect of this disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the above-described charging device setting method by executing the executable instructions.

[0089] According to another aspect of this disclosure, a computer-readable storage medium is provided that stores a computer program thereon, which, when executed by a processor, implements the above-described charging device setting method.

[0090] The charging device setting method provided in the embodiments of this disclosure obtains the number of electric vehicles and the location information of the delivery stations, then determines the path corresponding to each electric vehicle based on the number of electric vehicles, the location information of the delivery stations, and a preset algorithm, and then determines the electrical energy required by each electric vehicle based on the path corresponding to each electric vehicle. If the electrical energy required by any electric vehicle is greater than the electrical energy that the current electric vehicle can store, a charging device is set on the path corresponding to the current electric vehicle. Since the path of the electric vehicle is determined first, and then the charging device is determined based on the determined path of the electric vehicle, the electric vehicle can be closer to the charging device, making the charging of the electric vehicle more convenient.

[0091] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0092] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. It is obvious that the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0093] Figure 1 This diagram illustrates a flowchart of a charging device setting method according to an embodiment of the present disclosure;

[0094] Figure 2 This diagram illustrates another charging device setting method according to an embodiment of the present disclosure;

[0095] Figure 3 This diagram illustrates a flowchart of another charging device setting method according to an embodiment of the present disclosure;

[0096] Figure 4 This diagram illustrates a flowchart of another charging device setting method according to an embodiment of the present disclosure;

[0097] Figure 5 This diagram illustrates a flowchart of another charging device setting method according to an embodiment of the present disclosure;

[0098] Figure 6 This diagram illustrates a flowchart of another charging device setting method according to an embodiment of the present disclosure;

[0099] Figure 7 A schematic diagram of a charging device setting apparatus is shown in an embodiment of this disclosure; and

[0100] Figure 8 A structural block diagram of an electronic device according to an embodiment of the present disclosure is shown. Detailed Implementation

[0101] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that this disclosure will be more comprehensive and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0102] Furthermore, the accompanying drawings are merely illustrative of this disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0103] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0104] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0105] To address the aforementioned issues, this disclosure provides a charging device setting method, apparatus, device, and storage medium.

[0106] The following describes a charging device setting method according to an embodiment of the present disclosure.

[0107] Figure 1 A schematic diagram of a charging device setting method according to an embodiment of the present disclosure is shown.

[0108] like Figure 1 As shown, the method may include:

[0109] S102, obtain the number of electric vehicles and the location information of the delivery stations.

[0110] It should be noted that electric vehicles can include vehicles powered by electricity.

[0111] For example, electric vehicles may include new energy vehicles and range-extended electric vehicles.

[0112] Users can input the number of electric vehicles and the location information of the delivery stations.

[0113] S104 determines the path for each electric vehicle based on the number of electric vehicles, the location information of the delivery stations, and a preset algorithm.

[0114] It should be noted that when determining the route for electric vehicles, different stations require different electric vehicles for delivery. The same electric vehicle can deliver to different stations, but the same station cannot be delivered by different electric vehicles.

[0115] S106, determine the electrical energy required for each electric vehicle based on the path corresponding to each electric vehicle.

[0116] S108: If any electric vehicle needs to consume more electrical energy than the electric vehicle can store, a charging device shall be installed on the path corresponding to the electric vehicle.

[0117] The charging device setting method provided in the embodiments of this disclosure obtains the number of electric vehicles and the location information of the delivery stations, then determines the path corresponding to each electric vehicle based on the number of electric vehicles, the location information of the delivery stations, and a preset algorithm, and then determines the electrical energy required by each electric vehicle based on the path corresponding to each electric vehicle. If the electrical energy required by any electric vehicle is greater than the electrical energy that the current electric vehicle can store, a charging device is set on the path corresponding to the current electric vehicle. Since the path of the electric vehicle is determined first, and then the charging device is determined based on the determined path of the electric vehicle, the electric vehicle can be close to the charging device, making the charging of electric vehicles more convenient.

[0118] Based on the same inventive concept, this disclosure provides another method for setting up a charging device, which can be executed by any electronic device with computing power.

[0119] Figure 2 A flowchart of another charging device setting method according to an embodiment of this disclosure is shown.

[0120] like Figure 2 As shown, the difference between this charging device setting method and the charging device setting method in the above embodiments is that S106 may include:

[0121] S202 determines the path length corresponding to each preset route plan based on the number of electric vehicles and the location information of the delivery stations.

[0122] It should be noted that the path length for each preset route is determined based on the number of electric vehicles and the location information of the delivery stations, including:

[0123] The path length for each preset route is determined based on the number of electric vehicles, the location information of the delivery stations, and a first preset formula; wherein the first preset formula is:

[0124]

[0125] Among them, L i Let d(E) be the path length corresponding to any path in the preset path scheme. j E j+1 () represents the distance between the j-th delivery point and the (j+1)-th delivery point. From the first delivery point to the nth i The distance between n delivery points i This represents the number of delivery points on any one of the preset routes.

[0126] The distance between two delivery points can be calculated based on their coordinates.

[0127] S204, determine the sum of the time variances of each electric vehicle's operation based on the path length corresponding to each preset path scheme and the number of electric vehicles.

[0128] It should be noted that the sum of the time variances for each electric vehicle's operation is determined based on the path length and the number of electric vehicles corresponding to each preset route plan, including:

[0129] The sum of the time variances for each electric vehicle's operation is determined based on the path length corresponding to each preset path scheme, the number of electric vehicles, and the second preset formula; wherein, the second preset formula is:

[0130]

[0131] Among them, t var The sum of the time variances of operation for each electric vehicle, t i Let t be the running time of any path in the preset path scheme. ave Let be the average running time of all electric vehicles, and e be the number of electric vehicles.

[0132] It can be understood that the smaller the sum of the time variances of each electric vehicle's operation, the smaller the time difference between each electric vehicle's operation will be.

[0133] S206, determine the fitness function value corresponding to each preset path scheme according to the preset fitness function formula, the path length corresponding to each preset path scheme and the sum of the time variance of each electric vehicle running in each preset path scheme.

[0134] It should be noted that the above embodiments have already provided a method for determining the fitness function value corresponding to each preset path scheme based on the fitness function formula, the path length corresponding to each preset path scheme, and the sum of the time variances of each electric vehicle running in each preset path scheme, which will not be repeated here.

[0135] S208, Determine the target preset path scheme based on the fitness function value corresponding to each preset path scheme;

[0136] S210, determine the path corresponding to each electric vehicle according to the target preset path plan.

[0137] It should be noted that each preset route can correspond to multiple electric vehicles, and each electric vehicle corresponds to one route.

[0138] In this embodiment, the fitness function value corresponding to each preset path scheme is calculated using a fitness function formula, and then the target preset path scheme is determined based on the fitness function value corresponding to each preset path scheme. Since the fitness function formula imposes restrictions on the running time of each electric vehicle and the path length corresponding to each electric vehicle, the target preset path scheme determined based on the fitness function is more practical.

[0139] Based on the same inventive concept, this disclosure provides another method for setting up a charging device, which can be executed by any electronic device with computing power.

[0140] Figure 3 A flowchart of another charging device setting method according to an embodiment of the present disclosure is shown.

[0141] like Figure 3 As shown, the difference between this charging device setting method and the charging device setting method in the above embodiments is that S208 may include:

[0142] S302, iterate the fitness function value corresponding to each preset path scheme according to the fireworks algorithm, and obtain the optimal fitness function value corresponding to each preset path scheme when the number of iterations reaches a preset threshold.

[0143] It should be noted that the preset threshold can be determined by the user.

[0144] S304, determine the preset path scheme corresponding to the smallest optimal fitness function value as the target preset path scheme.

[0145] It should be noted that after multiple iterations, each preset path scheme may obtain multiple corresponding fitness function values. The smallest fitness function value among the multiple corresponding fitness function values ​​can be used as the fitness function value of the current preset path scheme.

[0146] In this embodiment, the fireworks algorithm is used to mutate each preset path scheme, resulting in multiple fitness function values ​​corresponding to each preset path scheme. Then, the smallest fitness function value among these multiple fitness function values ​​is determined as the fitness function value corresponding to the current preset path scheme. This avoids the problem of being unable to determine the optimal fitness function value when multiple preset path schemes have the same fitness function value.

[0147] Based on the same inventive concept, this disclosure provides yet another method for setting up a charging device, which can be executed by any electronic device with computing power.

[0148] Figure 4 A flowchart of another charging device setting method according to an embodiment of this disclosure is shown.

[0149] like Figure 4 As shown, the difference between this charging device setting method and the charging device setting method in the above embodiments is that S304 may include:

[0150] S402, determine the explosion radius and number of explosions of the fireworks according to the third preset formula and the fourth preset formula respectively.

[0151] It should be noted that the third preset formula is:

[0152]

[0153] The fourth preset formula is:

[0154]

[0155] Among them, A i S is the radius of the fireworks explosion. i Let F be the number of fireworks explosions, and F be the fitness function value corresponding to any preset path scheme. min F is the minimum fitness function value among multiple preset path schemes. max F represents the maximum fitness function value among multiple preset path schemes. ave is the average fitness function value among multiple preset path schemes, where M is a constant and UL is the search boundary constant.

[0156] S404, based on the determined fireworks explosion radius and number of explosions, mutate each preset path scheme to obtain multiple fitness function values ​​after mutation.

[0157] It should be noted that among the multiple fitness function values ​​obtained from each fireworks explosion, the smallest fitness function value can be retained. Then, the roulette wheel algorithm is used to randomly select any number of fitness function values ​​corresponding to the path schemes for the next fireworks explosion. The above operation is repeated until the number of iterations meets the preset threshold.

[0158] S406, determine the optimal fitness function value from the multiple fitness function values ​​after mutation as the optimal fitness function value corresponding to the current preset path scheme.

[0159] It should be noted that multiple fitness function values ​​can be obtained through multiple fireworks explosions. The smallest fitness function value can be determined among these multiple fitness function values, and then the preset path scheme corresponding to the smallest fitness function value is used as the target path scheme.

[0160] Based on the same inventive concept, this disclosure provides yet another method for setting up a charging device, which can be executed by any electronic device with computing power.

[0161] Figure 5 A flowchart of another charging device setting method according to an embodiment of this disclosure is shown.

[0162] like Figure 5 As shown, the difference between this charging device setting method and the charging device setting method in the above embodiments is that S106 may include:

[0163] S502, determine the electrical energy required for each electric vehicle based on the path corresponding to each electric vehicle and the fifth preset formula;

[0164] It should be noted that the fifth preset formula is:

[0165]

[0166] Where EC is the electrical energy required for any electric vehicle, a, b, c, and d are regression coefficients, v is the current average operating speed of the electric vehicle, and L is the current operating path length of the electric vehicle.

[0167] Based on the same inventive concept, this disclosure provides yet another method for setting up a charging device, which can be executed by any electronic device with computing power.

[0168] Figure 6 A flowchart of another charging device setting method according to an embodiment of this disclosure is shown.

[0169] like Figure 6 As shown, the difference between this charging device setting method and the charging device setting method in the above embodiments is that S108 may include:

[0170] S602 determines the location of the charging device based on the preset optimization model and the path corresponding to the current electric vehicle.

[0171] It should be noted that the optimization model can be:

[0172]

[0173] in, For the i-th vehicle to run to CV i The running time of the point For the i-th vehicle to run to CV i The energy consumption of the point is k, where k is the number of electric vehicles that need to be charged.

[0174] S604, Install the charging device according to the determined location of the charging device.

[0175] Based on the same inventive concept, this disclosure also provides a charging device setting apparatus, as shown in the following embodiment. Since the principle by which this apparatus solves the problem is similar to that of the method embodiments described above, the implementation of this apparatus embodiment can refer to the implementation of the method embodiments described above, and repeated details will not be elaborated further.

[0176] Figure 7 This diagram illustrates a charging device setting apparatus according to an embodiment of the present disclosure, such as... Figure 7 As shown, the device 700 includes:

[0177] The acquisition module 702 is used to acquire the number of electric vehicles and the location information of the delivery stations;

[0178] The first determining module 704 is used to determine the path corresponding to each electric vehicle based on the number of electric vehicles, the location information of the delivery stations, and a preset algorithm.

[0179] The second determining module 706 is used to determine the electrical energy required for each electric vehicle based on the path corresponding to each electric vehicle.

[0180] The setting module 708 is used to set up a charging device on the path corresponding to the current electric vehicle when there is an electric vehicle that needs to consume more electrical energy than the electric vehicle can store.

[0181] The charging device setting device provided in the embodiments of this disclosure obtains the number of electric vehicles and the location information of the delivery stations, then determines the path corresponding to each electric vehicle based on the number of electric vehicles, the location information of the delivery stations, and a preset algorithm. Then, it determines the electrical energy required by each electric vehicle based on the path corresponding to each electric vehicle. If the electrical energy required by any electric vehicle is greater than the electrical energy that the current electric vehicle can store, a charging device is set on the path corresponding to the current electric vehicle. Since the path of the electric vehicle is determined first, and then the charging device is determined based on the determined path of the electric vehicle, the electric vehicle can be close to the charging device, making the charging of electric vehicles more convenient.

[0182] In one embodiment of this disclosure, the first determining module 704 includes:

[0183] The first determining unit is used to determine the path length corresponding to each preset path scheme based on the number of electric vehicles and the location information of the delivery stations.

[0184] The second determining unit is used to determine the sum of the time variances of each electric vehicle's operation based on the path length corresponding to each preset path scheme and the number of electric vehicles.

[0185] The third determining unit is used to determine the fitness function value corresponding to each preset path scheme based on the preset fitness function formula, the path length corresponding to each preset path scheme and the sum of the time variances of each electric vehicle running in each preset path scheme.

[0186] The fourth determining unit is used to determine the target preset path scheme based on the fitness function value corresponding to each preset path scheme;

[0187] The fifth determining unit is used to determine the path corresponding to each electric vehicle based on the target preset path scheme;

[0188] The fitness function formula is as follows:

[0189]

[0190] Where F is the fitness function value, ω1 and ω2 are coefficients, e is the number of electric vehicles, and L i Let t be the path length corresponding to any path in the preset path scheme. var The variance of the running time of each electric vehicle in each preset route scheme.

[0191] In one embodiment of this disclosure, the first determining unit includes:

[0192] The first determining subunit is used to determine the path length corresponding to each preset path scheme based on the number of electric vehicles, the location information of the delivery stations, and the first preset formula.

[0193] The first preset formula is:

[0194]

[0195] Among them, L i Let d(E) be the path length corresponding to any path in the preset path scheme. j E j+1 () represents the distance between the j-th delivery point and the (j+1)-th delivery point. From the first delivery point to the nth i The distance between n delivery points i This represents the number of delivery points on any one of the preset routes.

[0196] In one embodiment of this disclosure, the second determining unit includes:

[0197] The second determining subunit is used to determine the sum of the time variances of each electric vehicle's operation based on the path length corresponding to each preset path scheme, the number of electric vehicles, and a second preset formula; wherein the second preset formula is:

[0198]

[0199] Among them, t var The sum of the time variances of operation for each electric vehicle, t i Let t be the running time of any path in the preset path scheme. ave Let be the average running time of all electric vehicles, and e be the number of electric vehicles.

[0200] In one embodiment of this disclosure, the fourth determining unit includes:

[0201] The iterative subunit is used to iterate the fitness function value corresponding to each preset path scheme according to the fireworks algorithm. When the number of iterations reaches a preset threshold, the optimal fitness function value corresponding to each preset path scheme is obtained.

[0202] The third determining subunit is used to determine the preset path scheme corresponding to the smallest optimal fitness function value as the target preset path scheme.

[0203] In one embodiment of this disclosure, the iterative subunit includes

[0204] The first determining element is used to determine the explosion radius and the number of explosions of the fireworks according to the third preset formula and the fourth preset formula, respectively.

[0205] The mutation element is used to mutate each preset path according to the determined firework explosion radius and number of explosions, and obtain multiple fitness function values ​​after mutation;

[0206] The second determining element is used to determine the optimal fitness function value among the multiple fitness function values ​​after mutation as the optimal fitness function value corresponding to the current preset path scheme;

[0207] The third preset formula is:

[0208]

[0209] The fourth preset formula is:

[0210]

[0211] Among them, A i S is the radius of the fireworks explosion. i Let F be the number of fireworks explosions, and F be the fitness function value corresponding to any preset path scheme. min F is the minimum fitness function value among multiple preset path schemes. max F represents the maximum fitness function value among multiple preset path schemes. ave is the average fitness function value among multiple preset path schemes, where M is a constant and UL is the search boundary constant.

[0212] In one embodiment of this disclosure, the second determining module 706 includes:

[0213] The sixth determining unit is used to determine the electrical energy required by each electric vehicle based on the path corresponding to each electric vehicle and the fifth preset formula; wherein, the fifth preset formula is:

[0214]

[0215] Where EC represents the electrical energy consumed by any electric vehicle, a, v, c, and d are regression coefficients, v is the current average operating speed of the electric vehicle, and L is the current operating path length of the electric vehicle.

[0216] In one embodiment of this disclosure, the setting module 708 includes:

[0217] The seventh determining unit is used to determine the location of the charging device based on the preset optimization model and the path corresponding to the current electric vehicle.

[0218] The setting unit is used to set the charging device according to the determined location of the charging device.

[0219] Those skilled in the art will understand that various aspects of this disclosure can be implemented as a system, method, or program product. Therefore, various aspects of this disclosure can be specifically implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or a combination of hardware and software aspects, collectively referred to herein as a "circuit," "module," or "system."

[0220] The following reference Figure 8 To describe an electronic device 800 according to such an embodiment of the present disclosure. Figure 8 The electronic device 800 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments disclosed herein.

[0221] like Figure 8 As shown, the electronic device 800 is manifested in the form of a general-purpose computing device. The components of the electronic device 800 may include, but are not limited to: at least one processing unit 810, at least one storage unit 820, and a bus 830 connecting different system components (including storage unit 820 and processing unit 810).

[0222] The storage unit stores program code, which can be executed by the processing unit 810, causing the processing unit 810 to perform the steps described in the "Exemplary Methods" section of this specification according to various exemplary embodiments of this disclosure. For example, the processing unit 810 can perform the following steps of the above method embodiments:

[0223] Obtain the number of electric vehicles and the location information of the delivery stations;

[0224] The route for each electric vehicle is determined based on the number of electric vehicles, the location information of the delivery stations, and a preset algorithm.

[0225] The electrical energy required for each electric vehicle is determined based on the path corresponding to each electric vehicle.

[0226] If any electric vehicle needs to consume more electrical energy than it can store, a charging device will be installed on the path corresponding to that electric vehicle.

[0227] Storage unit 820 may include a readable medium in the form of a volatile storage unit, such as random access memory (RAM) 8201 and / or cache memory 8202, and may further include a read-only memory (ROM) 8203.

[0228] The storage unit 820 may also include a program / utility 8204 having a set (at least one) of program modules 8205, including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0229] Bus 830 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0230] Electronic device 800 can also communicate with one or more external devices 840 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 800, and / or with any device that enables electronic device 800 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 850. Furthermore, electronic device 800 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 860. As shown, network adapter 860 communicates with other modules of electronic device 800 via bus 830. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 800, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0231] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0232] In exemplary embodiments of this disclosure, a computer-readable storage medium is also provided, which may be a readable signal medium or a readable storage medium. A program product capable of implementing the methods described above is stored thereon. In some possible implementations, various aspects of this disclosure may also be implemented as a program product including program code, which, when run on a terminal device, causes the terminal device to perform the steps described in the "Exemplary Methods" section of this specification according to various exemplary embodiments of this disclosure.

[0233] More specific examples of computer-readable storage media in this disclosure may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0234] In this disclosure, a computer-readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of transmitting, propagating, or transmitting a program for use by or in connection with an instruction execution system, apparatus, or device.

[0235] Optionally, the program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0236] In practical implementation, program code for performing the operations of this disclosure can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0237] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0238] Furthermore, although the steps of the method in this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.

[0239] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, mobile terminal, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0240] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the appended claims.

Claims

1. A charging device setting method characterized by comprising: The method comprises: acquiring the number of electric vehicles and position information of sites requiring distribution; determining a path corresponding to each electric vehicle according to the number of electric vehicles, the position information of sites requiring distribution and a preset algorithm, the preset algorithm comprising a fitness function; determining electric energy required to be consumed by each electric vehicle according to the path corresponding to each electric vehicle; in a case where the electric energy required to be consumed by any one of the electric vehicles is greater than the electric energy capable of being stored by the current electric vehicle, setting a charging device on the path corresponding to the current electric vehicle; the determination of the path corresponding to each electric vehicle according to the number of electric vehicles, the position information of sites requiring distribution and the preset algorithm comprises: determining a path length corresponding to each preset path scheme according to the number of electric vehicles and the position information of sites requiring distribution; determining a sum of time variance of each electric vehicle according to the path length corresponding to each preset path scheme and the number of electric vehicles; determining a fitness function value corresponding to each preset path scheme according to a preset fitness function formula, the path length corresponding to each preset path scheme and the sum of time variance of each electric vehicle in each preset path scheme; determining a target preset path scheme according to the fitness function value corresponding to each preset path scheme; determining the path corresponding to each electric vehicle according to the target preset path scheme; wherein the fitness function formula is: Wherein, F is the fitness function value, ω1 and ω2 are coefficients, e is the number of electric vehicles, L i is the path length corresponding to any path in the preset path scheme, t var is the sum of the time variance of each electric vehicle.

2. The charging device setting method according to claim 1, characterized by, the determination of the path length corresponding to each preset path scheme according to the number of electric vehicles and the position information of sites requiring distribution comprises: determining the path length corresponding to each preset path scheme according to the number of electric vehicles, the position information of sites requiring distribution and a first preset formula; wherein the first preset formula is: wherein L i is a path length corresponding to any one path in the preset path scheme, d(E j , E j+1 ) is a distance between the jth delivery point and the j+1th delivery point, is a distance between the 1st delivery point and the nth i delivery point, and n i is a number of delivery points on any one path in the preset path scheme.

3. The method of claim 2, wherein the determination of the sum of time variance of each electric vehicle according to the path length corresponding to each preset path scheme and the number of electric vehicles comprises: determining the sum of time variance of each electric vehicle according to the path length corresponding to each preset path scheme, the number of electric vehicles and a second preset formula; wherein the second preset formula is: where t var is the sum of the variance of the running time of each electric vehicle, t i is the running time of any path in the preset path scheme, t ave is the mean of the running time of all electric vehicles, and e is the number of electric vehicles.

4. The method of claim 1, wherein the determination of the target preset path scheme according to the fitness function value corresponding to each preset path scheme comprises: iterating the fitness function value corresponding to each preset path scheme according to a firework algorithm, and in a case where the number of iterations reaches a preset threshold, acquiring an optimal fitness function value corresponding to each preset path scheme; determining the preset path scheme corresponding to the smallest optimal fitness function value as the target preset path scheme.

5. The method of claim 1, wherein the iteration of the fitness function value corresponding to each preset path scheme according to the firework algorithm, in a case where the number of iterations reaches a preset threshold, acquiring an optimal fitness function value corresponding to each preset path scheme, comprises: determining a firework explosion radius and a number of explosions according to a third preset formula and a fourth preset formula respectively; carrying out mutation on each preset path scheme according to the determined firework explosion radius and the number of explosions, to obtain a plurality of fitness function values after mutation; determining an optimal fitness function value in the plurality of fitness function values after mutation as the optimal fitness function value corresponding to the current preset path scheme; The third preset formula is: The fourth preset formula is: wherein A i is the radius of the fireworks explosion, S i is the number of fireworks explosions, F is the fitness function value corresponding to any preset path scheme, F min is the minimum fitness function value among the fitness function values corresponding to the plurality of preset path schemes, F max is the maximum fitness function value among the fitness function values corresponding to the plurality of preset path schemes, F ave is the average of the fitness function values among the fitness function values corresponding to the plurality of preset path schemes, and M is a constant, and UL is a search boundary constant.

6. The method of claim 1, wherein The electric energy consumed by each electric vehicle is determined according to the path corresponding to each electric vehicle, including: The electric energy consumed by each electric vehicle is determined according to the path corresponding to each electric vehicle and the fifth preset formula; the fifth preset formula is: Wherein, EC is the electric energy consumed by any one electric vehicle, a, b, c, d are all regression coefficients, v is the average running speed of the current electric vehicle, and L is the length of the running path of the current electric vehicle.

7. The method of claim 1, wherein The charging device is set on the path corresponding to the current electric vehicle, including: The position of the charging device is determined according to the preset optimization model and the path corresponding to the current electric vehicle; The charging device is set according to the position of the charging device determined.

8. A charging device setting apparatus characterized by comprising: The device comprises: An acquisition module for acquiring the number of electric vehicles and the position information of the sites needing to be distributed; A first determination module for determining the path corresponding to each electric vehicle according to the number of electric vehicles, the position information of the sites needing to be distributed and a preset algorithm, wherein the preset algorithm includes a fitness function; A second determination module for determining the electric energy consumed by each electric vehicle according to the path corresponding to each electric vehicle; A setting module for setting a charging device on the path corresponding to the current electric vehicle in the case that the electric energy consumed by any one electric vehicle is greater than the electric energy that can be stored by the current electric vehicle; the first determination module comprises: A first determination unit for determining the path length corresponding to each preset path scheme according to the number of electric vehicles and the position information of the sites needing to be distributed; A second determination unit for determining the sum of the time variance of each electric vehicle according to the path length corresponding to each preset path scheme and the number of electric vehicles; A third determination unit for determining the fitness function value corresponding to each preset path scheme according to the path length corresponding to each preset path scheme and the sum of the time variance of each electric vehicle in each preset path scheme according to a preset fitness function formula; A fourth determination unit for determining a target preset path scheme according to the fitness function value corresponding to each preset path scheme; A fifth determination unit for determining the path corresponding to each electric vehicle according to the target preset path scheme; The fitness function formula is: Wherein, F is the fitness function value, ω1 and ω2 are coefficients, e is the number of electric vehicles, L i is the path length corresponding to any path in the preset path scheme, t var is the variance of the time of each electric vehicle running in each preset path scheme.

9. An electronic device, comprising: It comprises: A processor; And A memory for storing executable instructions of the processor; The processor is configured to execute the executable instructions to perform the charging device setting method of any one of claims 1-7.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the charging device setting method of any one of claims 1-7. The computer program is executed by the processor to implement the charging device setting method of any one of claims 1-7.

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