Guiding vehicle charging scheduling method and device, guiding vehicle and storage medium

Abstract

The invention discloses a guide vehicle charging scheduling method and device, a guide vehicle and a storage medium. Vehicle information of at least one to-be-charged guide vehicle and charging pile information of at least one to-be-distributed charging pile in a target area are acquired; according to the vehicle information and the charging pile information, determining a target function related to the earliest completion of charging of the at least one to-be-charged guide vehicle; processing the target function according to a preset solution algorithm to determine target charging scheduling information under the condition that at least one charging constraint condition is met; and according to the target charging scheduling information, at least one to-be-charged guide vehicle is controlled to move to a corresponding target charging pile at the target charging starting moment for charging processing, and the target charging pile is a to-be-distributed charging pile determined according to the target distribution relation. According to the invention, reasonable charging scheduling of the charging guide vehicle is realized, so that the overall charging duration of the to-be-charged guide vehicle in the target area is shortest, and the charging cost of the guide vehicle is saved.

Description

Technical Field

[0001] This invention relates to the field of information processing technology, and in particular to a method, apparatus, guide vehicle, and storage medium for scheduling charging of a guide vehicle. Background Technology

[0002] Automated Guided Vehicles (AGVs), as core equipment for automated material handling, possess a high degree of automation and flexible path planning capabilities, and are widely used in various logistics and transportation scenarios. In practical applications, an area typically includes one or more AGVs. To ensure the normal operation of AGVs in that area, charging and scheduling of at least one AGV is usually performed.

[0003] Currently, the main approach relies on a timed charging strategy, controlling the automated guided vehicles (AGVs) to travel to available charging stations according to preset schedules. However, when multiple AGVs need charging, this method results in some AGVs being overcharged while others cannot be charged in time. This leads to issues such as unreasonable allocation of charging resources, excessively long overall charging time for AGVs in a given area, and wasted charging resources. Summary of the Invention

[0004] This invention provides a method, device, guide vehicle, and storage medium for scheduling charging of guide vehicles, which enables reasonable scheduling of charging guide vehicles, minimizing the overall charging time of guide vehicles waiting to be charged within the target area and saving charging costs for guide vehicles.

[0005] According to one aspect of the present invention, a method for scheduling the charging of a guided vehicle is provided, the method comprising:

[0006] Obtain vehicle information of at least one guide vehicle to be charged and charging pile information of at least one charging pile to be allocated within the target area; wherein, the vehicle information includes at least: vehicle quantity information, initial power information and target power information of each guide vehicle to be charged, and the charging pile information includes at least: charging pile quantity information;

[0007] Based on the vehicle information and the charging pile information, a target function is determined that is related to the earliest completion of charging of the at least one guide vehicle to be charged; wherein, completion of charging is related to the battery level of the guide vehicle to be charged reaching the target battery level.

[0008] The objective function is processed according to a preset solution algorithm to determine target charging scheduling information under the condition that at least one charging constraint is satisfied. The at least one charging constraint includes at least one of the following: a first constraint to control that each guide vehicle to be charged corresponds to one charging pile to be allocated at the same charging time; a second constraint to control that no task is assigned to guide vehicles whose power information has not reached the target power information; a third constraint to control that the charging start time and charging end time of the guide vehicle to be charged belong to a preset time range; a fourth constraint to control that each charging pile to be allocated corresponds to at most one guide vehicle to be charged at the same charging time; and a fifth constraint to control that the power information of the guide vehicle to be charged at the charging end time is not less than the target power information. The target charging scheduling information includes at least: the target allocation relationship between the guide vehicle to be charged and the charging pile to be allocated, and the target charging start time of each guide vehicle to be charged.

[0009] Based on the target charging scheduling information, the at least one guide vehicle to be charged is controlled to move to the corresponding target charging pile at the target charging start time for charging processing, wherein the target charging pile is the charging pile to be allocated determined according to the target allocation relationship.

[0010] According to another aspect of the present invention, a vehicle charging scheduling device is provided, the device comprising:

[0011] The information acquisition module is used to acquire vehicle information of at least one guide vehicle to be charged and charging pile information of at least one charging pile to be allocated within the target area; wherein, the vehicle information includes at least: vehicle quantity information, initial power information and target power information of each guide vehicle to be charged, and the charging pile information includes at least: charging pile quantity information.

[0012] The objective function determination module is used to determine an objective function related to the earliest completion of charging of the at least one guide vehicle to be charged, based on the vehicle information and the charging pile information; wherein, completing charging is related to the battery level of the guide vehicle to be charged reaching the target battery level information;

[0013] The scheduling information determination module is used to process the objective function according to a preset solution algorithm to determine target charging scheduling information under the condition that at least one charging constraint is satisfied. The at least one charging constraint includes at least one of the following: a first constraint to control that each guide vehicle to be charged corresponds to one charging pile to be allocated at the same charging time; a second constraint to control that no task is assigned to guide vehicles whose power information has not reached the target power information; a third constraint to control that the charging start time and charging end time of the guide vehicle to be charged belong to a preset time range; a fourth constraint to control that each charging pile to be allocated corresponds to at most one guide vehicle to be charged at the same charging time; and a fifth constraint to control that the power information of the guide vehicle to be charged at the charging end time is not less than the target power information. The target charging scheduling information includes at least: the target allocation relationship between the guide vehicle to be charged and the charging pile to be allocated, and the target charging start time of each guide vehicle to be charged.

[0014] The vehicle charging scheduling module is used to control at least one guide vehicle to move to the corresponding target charging pile for charging at the target charging start time, based on the target charging scheduling information, wherein the target charging pile is a charging pile to be allocated determined according to the target allocation relationship.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] At least one processor; and

[0017] A memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the vehicle charging scheduling method according to any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the guided vehicle charging scheduling method according to any embodiment of the present invention.

[0020] According to another aspect of the present invention, a computer program product is provided, comprising a computer program, characterized in that the computer program, when executed by a processor, implements the guided vehicle charging scheduling method as described in any embodiment of the present invention.

[0021] The technical solution of this invention involves acquiring vehicle information of at least one guide vehicle to be charged and charging pile information of at least one charging pile to be allocated within a target area. Based on the vehicle and charging pile information, an objective function is determined that is associated with the earliest completion of charging for at least one guide vehicle to be charged. The objective function is processed according to a preset solution algorithm to determine target charging scheduling information while satisfying at least one charging constraint condition. Based on the target charging scheduling information, at least one guide vehicle to be charged is controlled to move to the corresponding target charging pile at the target charging start time specified in the target charging scheduling information for charging processing. This invention solves the problems of unreasonable allocation of charging resources, excessively long overall charging time for automated guided vehicles in the area, and wasted charging resources caused by charging scheduling based on existing technologies. It achieves reasonable charging scheduling for guide vehicles, minimizing the overall charging time for guide vehicles in the target area and saving charging costs for guide vehicles.

[0022] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a flowchart of a vehicle charging scheduling method provided in an embodiment of the present invention;

[0025] Figure 2 This is an example diagram corresponding to the target charging scheduling information provided in an embodiment of the present invention;

[0026] Figure 3 This is an example diagram corresponding to the target charging scheduling information provided in an embodiment of the present invention;

[0027] Figure 4 This is an example diagram showing the charging cost corresponding to the target charging scheduling information provided in an embodiment of the present invention;

[0028] Figure 5 This is a flowchart of a vehicle charging scheduling method provided in an embodiment of the present invention;

[0029] Figure 6 This is a schematic diagram of the structure of a guide vehicle charging scheduling device provided in an embodiment of the present invention;

[0030] Figure 7 This is a schematic diagram of the structure of an electronic device that implements the guide vehicle charging scheduling method of the present invention. Detailed Implementation

[0031] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0032] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0033] Example 1

[0034] Figure 1 This is a flowchart of a guide vehicle charging scheduling method provided in Embodiment 1 of the present invention. This embodiment is applicable to the allocation of charging piles for at least one guide vehicle to be charged within a target area, so as to minimize the overall charging time. This method can be executed by a guide vehicle charging scheduling device, which can be implemented in hardware and / or software. The guide vehicle charging scheduling device can be configured in electronic devices such as mobile phones, computers, or servers. Figure 1 As shown, the method includes:

[0035] S110. Obtain vehicle information of at least one guide vehicle to be charged and charging pile information of at least one charging pile to be assigned within the target area.

[0036] The target area can be a pre-defined logistics transportation area. In actual material transportation scenarios, the target area typically includes multiple guided vehicles (AGVs) and multiple charging stations. The guided vehicles, or Automated Guided Vehicles (AGVs), are used for material handling within the target area. For example, if the target area is a tobacco material transportation area, then the AGVs are used to transport tobacco materials. The charging stations are used to charge the guided vehicles.

[0037] For multiple guide vehicles, there may be guide vehicles that need charging and guide vehicles that do not need charging. This embodiment of the invention only addresses guide vehicles that need charging. That is, guide vehicles within the target area that need charging can be called guide vehicles awaiting charging. Optionally, the current guide vehicle can be determined as a guide vehicle awaiting charging based on at least one of the following charging triggering conditions: Specifically, when the initial battery level of the current guide vehicle is detected to be lower than a preset battery threshold, the current guide vehicle is determined to be a guide vehicle awaiting charging; and / or, when the current guide vehicle is detected to be in an idle state, the current guide vehicle is determined to be a guide vehicle awaiting charging; and / or, when the current time is detected to be within a preset charging time period, the guide vehicles within the target area are designated as guide vehicles awaiting charging. The preset battery threshold can be any value between 20% and 30%. The currently idle guide vehicle can be a guide vehicle that has completed tasks such as material handling and sorting. The preset charging time period can be a pre-set non-peak operating time period, such as 11:00 AM to 1:00 PM. It should be noted that in this embodiment of the invention, the battery information can be a battery percentage, that is, the percentage of battery capacity relative to the total battery capacity of the guide vehicle.

[0038] Accordingly, the target area may contain charging stations that are currently available for charging, as well as those that are not. Therefore, the charging stations within the target area that are currently available for charging can be designated as the charging stations to be assigned.

[0039] The vehicle information for the guide vehicles to be charged includes at least: vehicle quantity information, initial battery level information for each guide vehicle, and target battery level information. The vehicle quantity information refers to the total number of guide vehicles in the target area. The initial battery level information can be understood as the initial battery level of the guide vehicle before charging. The target battery level information can be pre-set, representing the desired battery level of the guide vehicle after charging. Optionally, the target battery level information can be 100%. The charging pile information includes at least: the number of charging piles. The number of charging piles can be understood as the total number of all charging piles to be allocated in the target area.

[0040] Specifically, for at least one guide vehicle within the target area at the current time, the initial battery level information corresponding to each guide vehicle is determined. When a guide vehicle is detected to meet at least one of the aforementioned charging trigger conditions, that guide vehicle is designated as a guide vehicle to be charged. Based on this, at least one guide vehicle to be charged within the target area is determined, along with its initial battery level information and vehicle quantity information. The vehicle quantity information, along with the initial battery level information and preset target battery level information for each guide vehicle to be charged, are used as vehicle information.

[0041] Accordingly, at least one charging pile within the target area at the current time is detected and processed to identify idle charging piles within the target area as waiting-to-be-assigned charging piles. The number of charging piles waiting to be assigned is then determined.

[0042] S120. Based on vehicle information and charging pile information, determine the objective function related to the earliest completion of charging of at least one guide vehicle to be charged.

[0043] The completion of charging is related to the target battery level of the guide vehicles to be charged. The objective function can be related to the earliest time when all guide vehicles in the target area have completed charging. In other words, the time when the last guide vehicle in the target area completes charging can be taken as the maximum charging completion time. The objective function is to minimize the maximum charging completion time.

[0044] Specifically, based on vehicle information and charging pile information, an objective function is constructed that relates to the earliest completion of charging for all vehicles waiting to be charged.

[0045] In this embodiment of the invention, the objective function can be determined in the following manner: For at least one guide vehicle to be charged, based on the initial power information of the guide vehicle to be charged and the charging pile information of the charging pile to be allocated, a current power determination function related to the charging status of the guide vehicle to be charged is determined; based on the correspondence between the current power and the charging rate, a charging rate determination function corresponding to the current power determination function is determined; based on the initial power information and the target power information, a target charging duration determination function corresponding to the charging rate determination function is determined; based on the vehicle quantity information of the guide vehicles to be charged and the target charging duration determination function corresponding to the guide vehicles to be charged, an objective function associated with the charging start time of each guide vehicle to be charged is determined.

[0046] Here, the charging status indicates whether the guide vehicle to be charged is charging at the corresponding time. The current battery level determination function can be used to represent the battery level of the guide vehicle to be charged at the corresponding time. Optionally, the current battery level determination function can be expressed as:

[0047] ;

[0048] in, Indicates the guide vehicle to be charged The charging status, ,in, , This indicates the number of vehicles. In other words, there are vehicles within the target area. A guide vehicle awaiting charging. This is a pre-set charging time range for the guide vehicles waiting to be charged within the target area. This indicates the preset latest charging time. It can represent Current charging guide vehicle The corresponding charging rate, Indicates the guide vehicle to be charged The total amount of electricity charged. Indicates the guide vehicle to be charged The initial battery level information. Indicates the guide vehicle to be charged exist Battery level information corresponding to a given moment.

[0049] The relationship between current battery level and charging rate can be as follows: when the current battery level of the vehicle to be charged is lower than the first battery level, the vehicle to be charged can be fast-charged, i.e., the charging rate is relatively fast; when the current battery level of the vehicle to be charged is higher than the first battery level, the vehicle to be charged can be trickle-charged, i.e., the charging rate is relatively slow. Here, the first battery level can be 80%.

[0050] Accordingly, the charging rate determination function can be used to determine the charging rate corresponding to the current battery level. Optionally, the charging rate determination function can be expressed as:

[0051] ;

[0052] in, Indicates the guide vehicle to be charged exist Battery level information corresponding to a given moment. Indicates the guide vehicle to be charged exist The charging rate corresponding to a given moment.

[0053] The target charging time determination function can be used to determine the time required for the battery level of the pilot vehicle to reach the target battery level. That is, the target charging time is the time required for the battery level of the pilot vehicle to reach the target battery level. Optionally, the target charging time determination function can be expressed as:

[0054] ;

[0055] in, Indicates the guide vehicle to be charged Initial battery level information, Indicates the guide vehicle to be charged exist The charging rate corresponding to a given moment. Indicates the guide vehicle to be charged The charging status, ,in, , This represents the set of vehicle numbers of the guide vehicles to be charged. This indicates the number of vehicles. Indicates in The information shows the cumulative charge level of the vehicle currently waiting to be charged. This indicates the target battery level. Indicates the guide vehicle to be charged The target charging time. It should be noted that the above... It is an unknown quantity.

[0056] Accordingly, based on the above functions, the objective function can be expressed as:

[0057] ;

[0058] in, Indicates the guide vehicle to be charged Target charging time, Indicates the guide vehicle to be charged The charging start time. This indicates the moment when all the guide vehicles to be charged have completed charging.

[0059] Specifically, for at least one vehicle to be charged, the current energy level determination function related to the charging status of the vehicle is determined based on its initial energy level information and the charging pile information of the assigned charging piles. Since the charging rate is related to the current energy level, the corresponding charging rate determination function can be determined based on the correspondence between the charging rate and the current energy level. Based on the initial energy level information and the target energy level information, and according to the charging rate determination function, the target charging time determination function corresponding to the vehicle reaching the target energy level is determined. Based on the target charging time determination function for each vehicle and the number of vehicles to be charged, an objective function corresponding to the charging start time of each vehicle is determined. By solving the objective function, the allocation relationship between the vehicles and the assigned charging piles is rationally determined to minimize the time required for all vehicles to complete charging, thereby reducing charging costs and conserving electricity resources.

[0060] S130. The objective function is processed according to the preset solution algorithm to determine the target charging scheduling information under the condition that at least one charging constraint condition is met.

[0061] The preset solution algorithm can be used to solve the objective function to determine the target charging scheduling information corresponding to the earliest completion of charging for all the guide vehicles to be charged. Optionally, the preset solution algorithm can be an evolutionary repair algorithm. The target charging scheduling information includes at least: the target allocation relationship between the guide vehicles to be charged and the charging piles to be allocated, and the target charging start time for each guide vehicle to be charged.

[0062] The target allocation relationship can be used to characterize the corresponding allocation relationship between the guide vehicles to be charged and the charging piles to be assigned. For example, if there are guide vehicles AGV-1, AGV-2, AGV-3, and AGV-4 to be charged in the target area, and there are charging piles to be assigned: charging pile 0, charging pile 1, and charging pile 2, then the target allocation relationship can be used to characterize which charging pile AGV-1, AGV-2, AGV-3, and AGV-4 are assigned to. Correspondingly, the target charging start time can be understood as the start time of charging for the guide vehicles to be charged. As can be seen from the above example, in practical application scenarios, the relationship between guide vehicles to be charged and charging piles to be assigned is not one-to-one; there may be at least two guide vehicles to be charged assigned to the same charging pile. Therefore, it is necessary to determine the start time of charging for each guide vehicle by using the target charging start time. Optionally, the target charging scheduling information may also include target charging status information. Among them, the target charging state information is used to characterize the charging state of each guide vehicle to be charged at different times. For example, in At any given moment, is the guide vehicle being charged?

[0063] Accordingly, to ensure that the charging process for the guided vehicles based on the assigned charging piles better meets actual needs, at least one charging constraint can be set. Specifically:

[0064] The first constraint condition is used to control that each guide vehicle to be charged corresponds to one charging pile to be assigned at the same charging time. This first constraint condition can be understood as follows: each guide vehicle to be charged can be assigned one charging pile to be assigned, and at the same time, each charging pile to be assigned can only charge one guide vehicle to be charged.

[0065] Optionally, the first constraint can be characterized by the following formula.

[0066] ;

[0067] in, Indicates the guide vehicle to be charged Should it be assigned to a charging station to be allocated? ;when This indicates the guide vehicle to be charged. Assigned to charging piles to be assigned ,when Indicates the guide vehicle to be charged Unassigned charging stations . , , This represents the set of vehicle numbers of the guide vehicles to be charged. This indicates the number of vehicles. , , This represents the set of charging pile numbers to be assigned. This indicates the number of charging stations to be allocated. It should be noted that... These are the unknowns that need to be solved subsequently. That is, the target charging allocation relationship is determined by solving the objective function under at least one charging constraint condition.

[0068] A second constraint is used to prevent the assignment of tasks to the guide vehicle waiting to be charged if its battery level information has not reached the target level. This second constraint can be understood as follows: when the battery level information of the guide vehicle waiting to be charged has not reached the target level, the charging process of the guide vehicle must not be interrupted and must be fully charged in one go. In other words, during the charging process, no task can be assigned to the guide vehicle waiting to be charged if its battery level information has not reached the target level.

[0069] Optionally, the second constraint can be characterized by the following formula:

[0070] ;

[0071] in, This indicates the guide vehicle to be charged. exist Is it charging at any time? Indicates the guide vehicle to be charged exist Charge anytime, anywhere Indicates the guide vehicle to be charged exist It is not currently charged. , , This represents the set of vehicle numbers of the guide vehicles to be charged. This indicates the number of vehicles. , This is a pre-set charging time range for the guide vehicles waiting to be charged within the target area. This indicates the preset latest charging time.

[0072] A third constraint is used to control the charging start and end times of the guide vehicle to be charged to fall within a preset time range. The preset time range can be a pre-set range for the charging time of the guide vehicle within a target area. The third constraint includes two aspects: first, if the guide vehicle is charging at the current moment, then the current moment is later than the charging start time of the guide vehicle. Optionally, it can be expressed by the following formula:

[0073] ;

[0074] in, Indicates the guide vehicle to be charged At the present moment Down-charging, Indicates the guide vehicle to be charged The charging start time, Indicates the current moment. , , This represents the set of vehicle numbers of the guide vehicles to be charged. This indicates the number of vehicles. , This is a pre-set charging time range for the guide vehicles to be charged within the target area, i.e., a preset time range. This indicates the preset latest charging time.

[0075] Secondly, the charging completion time for the guide vehicle to be charged shall not be later than the preset latest charging time. Optionally, this can be expressed by the following formula:

[0076] ;

[0077] in, Indicates the guide vehicle to be charged The charging start time. Indicates the guide vehicle to be charged Target charging time, Indicates the guide vehicle to be charged The moment when charging ends, This indicates the preset latest charging time. , , This represents the set of vehicle numbers of the guide vehicles to be charged. This indicates the number of vehicles.

[0078] The fourth constraint condition controls that each assigned charging station corresponds to at most one guide vehicle at the same charging time. This can be understood as ensuring that at any given moment, each assigned charging station charges only one guide vehicle. This can be expressed by the following formula:

[0079] ;

[0080] in, Indicates the guide vehicle to be charged Should it be assigned to a charging station to be allocated? ;when This indicates the guide vehicle to be charged. Assigned to charging piles to be assigned ,when This indicates that the guide vehicle for charging has not been assigned to a charging station. . , , This represents the set of vehicle numbers of the guide vehicles to be charged. This indicates the number of vehicles. , , This represents the set of charging pile numbers to be assigned. This indicates the number of charging stations to be allocated. This indicates the guide vehicle to be charged. exist Is it charging at any time? Indicates the guide vehicle to be charged exist Charge anytime, anywhere Indicates the guide vehicle to be charged exist It is not currently charged. This is a preset time range. This indicates the preset latest charging time.

[0081] The fifth constraint is used to ensure that the charge level of the guide vehicle at the end of charging is not less than the target charge level. Optionally, the fifth constraint can be determined by the following formula.

[0082] ;

[0083] in, Indicates the guide vehicle to be charged Initial battery level information, Indicates the guide vehicle to be charged exist The charging rate at that moment, Indicates the guide vehicle to be charged The charging status, This indicates the guide vehicle to be charged. exist Is it charging at any time? Indicates the guide vehicle to be charged exist Charge anytime, anywhere Indicates the guide vehicle to be charged exist It is not currently charged. Indicates in The information shows the cumulative charge level of the vehicle currently waiting to be charged. This indicates the target battery level. , This represents the set of vehicle numbers of the guide vehicles to be charged. This indicates the number of vehicles.

[0084] Specifically, the objective function is processed according to a preset solution algorithm to solve for the target allocation relationship, the target charging start time of each vehicle, and the target charging status information of the vehicle, under the condition that the above constraints are met.

[0085] Optionally, the method further includes: after determining the target charging scheduling information, determining the total charging cost corresponding to the target area based on the target charging scheduling information. Optionally, this can be determined using the following formula.

[0086] ;

[0087] in, This represents the total cost of charging. This indicates the preset latest charging time. Indicates the target region at time... The corresponding unit charging cost. It should be noted that because the unit charging cost varies over time, the exact timeframe is not specified. The corresponding unit charging cost can be determined based on the time-of-use charging cost table for the target area. This table includes the unit charging cost for different time periods within the target area. For example, the unit charging cost is A yuan / kWh from 8:00 to 11:00, and B yuan / kWh from 11:00 to 12:00.

[0088] The above, This indicates the number of vehicles. Indicates the guide vehicle to be charged At any moment The corresponding target charging status information, Indicates the guide vehicle to be charged exist Charge anytime, anywhere Indicates the guide vehicle to be charged exist It is not currently charged. Indicates the guide vehicle to be charged At any moment The charging information below; It can be determined by the following formula,

[0089] ;

[0090] in, Indicates the guide vehicle to be charged exist The charging rate corresponding to a given moment can be determined using a charging rate determination function after obtaining the target charging schedule information. The charging rate at which it is applied. Indicates the guide vehicle to be charged The total battery capacity. For example, the total battery capacity could be 5 kilowatt-hours.

[0091] It should be noted that since the target charging scheduling information is the scheduling allocation information corresponding to the earliest completion of charging for all the guide vehicles waiting to be charged, the total charging cost corresponding to the target charging scheduling information is also the minimum.

[0092] S140. Based on the target charging scheduling information, control at least one waiting-to-charge guide vehicle to move to the corresponding target charging pile at the target charging start time for charging.

[0093] The target charging start time can be understood as the charging start time in the target charging scheduling information. The target charging pile is the charging pile to be allocated, determined according to the target allocation relationship.

[0094] Specifically, based on the target charging scheduling information, at least one guide vehicle to be charged is controlled to move to the corresponding target charging pile at the corresponding target charging start time for charging.

[0095] In this embodiment of the invention, after obtaining the target charging schedule information, the method further includes: generating at least one visual chart corresponding to the target charging schedule information, and displaying the at least one visual chart on the display page of the target terminal.

[0096] The visualization charts are used to visualize the target allocation relationships and the target charging start time of each guide vehicle to be charged, which are included in the target charging scheduling information. For example, the graph in the visualization chart can be a Gantt chart, and the table can be an Excel spreadsheet. The target terminal can be the terminal electronic device of the corresponding user. The display page can be the terminal interface used to display the visualization charts.

[0097] Specifically, at least one visual chart corresponding to the target charging scheduling information is generated based on the target charging scheduling information, and the visual chart is displayed on the display page of the target terminal so that relevant personnel can intuitively determine the various types of information corresponding to the target charging scheduling information.

[0098] For example, the number of vehicles to be charged is 30, the number of charging piles to be allocated is 3, and the preset time range includes 96 time steps, each time step corresponding to one hour. This can be understood as taking the charging start time corresponding to the first vehicle to start charging as the time step from the charging start time to one hour of charging as a time step.

[0099] Taking the above as an example, the example diagram corresponding to the target charging scheduling information can be as follows: Figure 2 As shown, through Figure 2 Multiple guide vehicles to be charged can be identified for each assigned charging station, as well as the charging sequence for each guide vehicle. The charging sequence can be determined based on the target charging start time of the guide vehicle. Figure 2 It can also determine the target charging status information of the guide vehicle to be charged at each time step, and the total charging time of all guide vehicles to be charged in the target area is 84 hours.

[0100] Example tables corresponding to the target charging scheduling information can be found as follows: Figure 3 As shown. (Through) Figure 3 The initial battery level information for each AGV to be charged can be determined. Figure 3 The initial charge level and the target charging time corresponding to the vehicle to be charged. Figure 3 The charging time in the middle), and the charging pile to be assigned to each guide vehicle to be charged ( Figure 3 The charging pile in the middle), the charging start time of the guide vehicle waiting to be charged ( Figure 3 (start time) and charging end time ( Figure 3 (The end time in the text). Since the information displayed for each AGV to be charged is similar, the following explanation uses AGV1 as an example. Figure 3 The initial battery level of the AGV1 to be charged is 21%, the target charging time is 11 hours, and it will be charged by the charging pile to be assigned: charging pile 2. The charging start time is the 24th time step, and the charging end time is the 35th time step.

[0101] Correspondingly, a visual chart can also be generated corresponding to the charging cost associated with the target charging scheduling information, such as... Figure 4 As shown. Figure 4 This includes the charging cost corresponding to each time step.

[0102] The technical solution of this embodiment obtains vehicle information of at least one guide vehicle to be charged and charging pile information of at least one charging pile to be allocated within a target area. Based on the vehicle information and charging pile information, it determines an objective function associated with the earliest completion of charging for at least one guide vehicle to be charged. The objective function is processed according to a preset solution algorithm to determine target charging scheduling information while satisfying at least one charging constraint condition. Based on the target charging scheduling information, at least one guide vehicle to be charged is controlled to move to the corresponding target charging pile at the target charging start time specified in the target charging scheduling information for charging processing. This invention solves the problems of unreasonable allocation of charging resources, excessively long overall charging time for automated guided vehicles in the area, and waste of charging resources caused by charging scheduling based on existing technologies. It achieves reasonable charging scheduling for guide vehicles, minimizing the overall charging time for guide vehicles in the target area and saving charging costs for guide vehicles.

[0103] Example 2

[0104] Figure 5 This is a flowchart of a guided vehicle charging scheduling method provided in Embodiment 2 of the present invention. This embodiment refines the step of "processing the objective function according to a preset solution algorithm to determine the target charging scheduling information while satisfying at least one charging constraint condition" based on the above embodiment. For specific implementation details, please refer to the technical solution of this embodiment. Technical terms that are the same as or corresponding to those in the above embodiments will not be repeated here. Figure 5 As shown, the method includes:

[0105] S210. Obtain vehicle information of at least one guide vehicle to be charged and charging pile information of at least one charging pile to be assigned within the target area.

[0106] The vehicle information includes at least the following: vehicle quantity information, initial battery level information and target battery level information for each vehicle to be charged; the charging pile information includes at least the following: number of charging piles.

[0107] S220. Based on vehicle information and charging pile information, determine the objective function related to the earliest completion of charging of at least one guide vehicle to be charged.

[0108] Among them, the completion of charging is related to the battery level of the guide vehicle to be charged reaching the target battery level.

[0109] S230. Based on at least one guide vehicle to be charged and at least one charging pile to be allocated, determine at least one initial charging schedule information, and use the initial charging schedule information as the initial individual to obtain the population to be processed.

[0110] The initial charging scheduling information can be determined based on the vehicle information of the guide vehicle to be charged and the charging pile information of the charging pile to be allocated, and is subject to adjustment. The population to be processed includes at least one initial individual.

[0111] Specifically, based on the vehicle data of each guide vehicle and the number of charging piles to be assigned, a charging pile is randomly assigned to each guide vehicle. The initial charging start time for each guide vehicle is determined according to a preset time range. This initial allocation relationship between the guide vehicles and the charging piles, along with the initial charging start time for each vehicle, is used as initial charging scheduling information. To improve the accuracy of subsequent determination of target charging scheduling information, the above process can be repeated to obtain at least one initial charging scheduling piece of information. For each initial charging scheduling piece of information, it is treated as an initial individual, and a population to be processed, including all initial individuals, is determined.

[0112] In this embodiment of the invention, the method for determining the initial charging scheduling information may be as follows: based on at least one guide vehicle to be charged and at least one charging pile to be allocated, a charging pile allocation list is determined, wherein the charging pile allocation list includes at least one allocation identifier, which is used to characterize the initial allocation relationship between the guide vehicle to be charged and the charging pile to be allocated; an initial charging start time list corresponding to at least one guide vehicle to be charged is determined, wherein the initial charging start time list includes the initial charging start time of each guide vehicle to be charged; and the initial charging scheduling information is determined based on the charging pile allocation list and the initial charging start time list.

[0113] The charging pile allocation list represents the initial allocation relationship between the guide vehicle to be charged and the charging pile to be assigned. The charging pile allocation list includes at least one allocation identifier, which corresponds to the initial allocation relationship between a guide vehicle to be charged and a charging pile to be assigned. The initial charging start time list includes the initial charging start time for each guide vehicle to be charged. The initial charging start time is set according to a preset time range, indicating the time when the guide vehicle to be charged begins charging.

[0114] Specifically, based on at least one guide vehicle to be charged and at least one charging pile to be assigned, a charging pile to be assigned is randomly assigned to each guide vehicle to be charged, thus obtaining an initial allocation relationship between each guide vehicle to be charged and each charging pile to be assigned. An allocation identifier corresponding to each initial allocation relationship is determined, and a charging pile allocation list is constructed based on at least one allocation identifier.

[0115] Based on a preset time range, an initial charging start time is set for each guide vehicle to be charged, and an initial charging start time list is determined according to the initial charging start times of at least one guide vehicle. Initial charging scheduling information is determined based on the initial charging start times in the initial charging start time list and the initial allocation relationship with the charging pile allocation list. Optionally, the process of determining the charging pile allocation list and the initial charging start time list is repeated to determine at least one piece of initial charging scheduling information.

[0116] For example, taking the evolutionary repair algorithm as the preset solution algorithm, in this embodiment of the invention, the evolutionary repair algorithm is used to solve the charging scheduling optimization problem between charging piles and guide vehicles. This algorithm integrates the global search capability of evolutionary computation and the local optimization capability of conflict repair, ensuring the feasibility of the solution through a unique repair operator, effectively solving the problem of chromosome infeasibility in traditional algorithms. The steps of this evolutionary repair algorithm are as follows:

[0117] During the initialization phase, the starting power level, target power level (100%), number of vehicles to be charged, and number of charging piles to be allocated for each vehicle to be charged are determined.

[0118] A task-assignment-based real-number encoding method is employed. The key feature of this encoding method is that each chromosome in the structure consists of two lists: Pile_assignment (charging pile allocation list) and Start_times (initial charging start time list). The Pile_assignment list includes the charging pile number corresponding to each guide vehicle to be charged. This charging pile number represents the initial allocation relationship between the guide vehicle and the assigned charging pile. The Start_times list includes the initial charging start time for each guide vehicle.

[0119] Gene representation: Each vehicle to be charged corresponds to two genes. The first gene is the charging pile number corresponding to the vehicle to be charged, and the second gene is the initial charging start time corresponding to the vehicle to be charged. That is, chromosome length = vehicle quantity information × 2.

[0120] S240. Determine the initial fitness corresponding to each initial individual based on the objective function and at least one charging constraint.

[0121] The initial fitness is used to characterize the charging completion time corresponding to each initial charging scheduling information, and the charging completion time is used to characterize the time when at least one guide vehicle to be charged has completed charging. In other words, the charging completion time can be the time when all guide vehicles to be charged in the target area have completed charging according to the initial charging scheduling information.

[0122] Specifically, based on the initial allocation relationship and initial charging start time in the initial charging scheduling information corresponding to each initial individual, and based on the objective function, the charging completion time corresponding to each initial charging scheduling information is calculated, provided that at least one charging constraint condition is met. The charging completion time corresponding to each initial charging scheduling information is then used as the initial fitness for each initial individual.

[0123] S250. Based on the initial fitness of each initial individual, and according to the preset individual retention ratio information, determine at least one first individual, and according to the preset individual selection strategy, determine at least one second individual.

[0124] In this context, the first individual and the second individual are both initial individuals in the population to be processed. The preset individual retention ratio can be pre-set, representing the proportion of initial individuals to be retained out of the total number of initial individuals. For example, if there are 10 initial individuals in the population to be processed, and the preset individual retention ratio is 10%, then the desired initial individual to be retained is 1. It should be noted that the desired initial individual to be retained is the first individual.

[0125] The preset individual selection strategy can be based on initial fitness and a preset number of comparisons to select the second individual. Optionally, the preset individual selection strategy can be a tournament selection strategy. The second individual can be the initial individual that needs to undergo crossover and mutation operations.

[0126] Specifically, for all initial individuals in the population to be processed, at least one first individual is determined from the population based on the initial fitness of each initial individual and according to the preset individual retention ratio information. Following a preset individual selection strategy, a preset number of initial individuals are determined from the population to be processed each time, and their initial fitness is compared. At least one second individual is selected according to a preset probability distribution. This process of determining at least one second individual according to the preset individual selection strategy is repeated until at least one second individual consistent with the preset number determined by the preset individual selection strategy is identified.

[0127] In this embodiment of the invention, the method for determining the first individual and the second individual may be as follows: determining at least one first individual based on the preset individual retention ratio information and the initial fitness of each initial individual; wherein the first individual is an initial individual in the population to be processed; determining at least one individual to be processed in the population to be processed; wherein the individual to be processed is an initial individual in the population to be processed that is not the first individual; determining a preset number of second individuals based on the probability distribution information corresponding to the preset individual selection strategy and the initial fitness of at least one individual to be processed.

[0128] The number of individuals in the first group is determined by the product of the preset individual retention ratio and the total number of initial individuals. Individuals to be processed can be initial individuals selected from the population to be processed, and are not necessarily the first group. The number of individuals to be processed is related to the preset comparison number in the preset individual selection strategy. Probability distribution information is used to characterize the probability that at least one individual to be processed will be selected as the second group.

[0129] For example, let's explain the above using a pre-defined individual selection strategy as the tournament selection strategy. When conducting a tournament selection, based on the tournament size k=3 (pre-defined number of comparisons), three initial individuals that are not the first individual are randomly selected from the population to be processed, resulting in three individuals to be processed. These three individuals are then sorted from highest to lowest initial fitness (higher fitness, higher ranking). At this point, based on probability distribution information... The three values ​​in the table correspond to the probabilities of these three sorted individuals being selected as the second individual. Specifically, the individual with the highest initial fitness has a probability of 0.6 being selected as the second individual; the individual with the middle initial fitness has a probability of 0.3; and the individual with the lowest initial fitness has a probability of 0.1. Accordingly, the individual with the highest initial fitness is the second individual. To improve the accuracy of the target charging scheduling information, the above process can be repeated to determine a preset number of second individuals, which will then be used as the basis for subsequent crossover and mutation operations.

[0130] Specifically, based on the preset individual retention ratio and the total number of initial individuals, the number of individuals to be selected as the first individual is determined. Based on this number, at least one first individual is selected from the population to be processed, in descending order of initial fitness. It should be noted that the initial fitness of the selected first individuals is always higher than the initial fitness of the unselected initial individuals.

[0131] For initial individuals in the population not selected as the first individual, a preset number of individuals are selected from these initial individuals according to a preset comparison number in the preset individual selection strategy. Then, based on the probability distribution information in the preset individual selection strategy and the initial fitness of the individuals, the probability of each individual being selected as the second individual is determined. The individual with the highest probability (highest initial fitness) is selected as the second individual. This process of determining the second individual from the initial individuals not selected as the first individual is repeated until a preset number of second individuals are obtained.

[0132] For example, in conjunction with the above example, an elite retention tournament selection strategy is adopted. Based on the elite retention ratio (preset individual retention ratio information) of 10%, three initial individuals with higher initial fitness are selected as the first individuals from the 30 initial individuals in the population to be processed.

[0133] For the remaining 27 initial individuals, based on the tournament size k=3 in the tournament selection strategy, 3 individuals are randomly selected from the 27 initial individuals to be processed. This is based on probability distribution information. The initial fitness of these three individuals to be processed is determined, and the individual with the highest probability (highest initial fitness) is selected as the second individual. The process of determining the second individual is repeated until five (preset number) second individuals are obtained, and crossover and / or mutation operations are performed on these five second individuals.

[0134] S260. Perform crossover and / or mutation operations on at least one second individual to obtain at least one third individual.

[0135] Both crossover and mutation operations involve adjusting a second entity to obtain a new entity. Crossover can involve swapping the initial allocation relationships or initial charging start times of two or more second entities. Mutation can involve adjusting the initial allocation relationships or initial charging start times of the second entity. The resulting new entity is then designated as the third entity. This third entity corresponds to the updated initial charging schedule information.

[0136] Specifically, a crossover operation is performed on at least one second body based on a crossover operator, and / or, a mutation operator is performed on at least one second body to obtain at least one third body.

[0137] For example, combining the above examples, the crossover operation can be a two-point crossover. Its core is: by randomly setting two cut points in the chromosome corresponding to the second individual (corresponding to the charging station allocation list and the initial charging start time list), the chromosome is divided into three segments, and then the middle segments are exchanged to generate the third individual. Compared to single-point crossover (only one cut point), two-point crossover allows for more flexible gene recombination, retaining more high-quality segment combinations from the second individual.

[0138] Among them, for the first step of two-point crossover, two different integers c1 and c2 (1 < c1 < c2 < L) are randomly selected from the chromosome as two cut points. For example, if the chromosome length L = 8, c1 = 3 and c2 = 6 may be randomly selected. Then the chromosome is divided into three segments: Segment 1: positions 1 to c1 - 1 (i.e., positions 1 to 2); Segment 2: positions c1 to c2 (i.e., positions 3 to 6, the core segment to be crossed); Segment 3: positions c2 + 1 to L (i.e., positions 7 to 8). The significance of randomness: to avoid a single gene recombination pattern caused by fixed cut points and ensure population diversity. After determining the two cut points, the cut segments of the two chromosomes are exchanged to generate two offspring chromosomes.

[0139] Combined with the above, it can be understood that for the charging pile allocation list corresponding to the second individual A, two charging pile numbers corresponding to two to-be-charged guiding vehicles are selected from the charging pile allocation list, so as to divide the charging pile allocation list into three parts of charging pile allocation sub-lists based on these two charging pile numbers. Correspondingly, in the same way, the charging pile allocation list corresponding to the second individual B is cut to obtain three parts of charging pile allocation sub-lists. The charging pile allocation sub-lists of the second individual A are exchanged with the charging pile allocation sub-lists of the second individual B to obtain two new charging pile allocation lists. Correspondingly, based on the two new charging pile allocation lists and the corresponding initial charging start time lists, two updated initial charging scheduling information is determined, that is, the third individual is obtained.

[0140] Combined with the above example, the mutation operation can be implemented based on a third-order mutation strategy. The third-order mutation strategy includes: charging pile mutation (probability ), time offset mutation (probability ), and local optimization mutation (performing neighborhood search on the optimal solution). Among them, the charging pile mutation can be to adjust the initial allocation relationship in the initial charging scheduling information corresponding to the second individual, and the time offset mutation can be to adjust the initial charging start time in the initial charging scheduling information corresponding to the second individual.

[0141] In the embodiment of the present invention, after obtaining at least one third individual, the method further includes: if it is detected that there is a third individual that does not satisfy at least one charging constraint condition, then the third individual is adjusted according to the repair operator to obtain an adjusted third individual, so as to update the to-be-processed population based on the adjusted third individual.

[0142] Among them, the repair operator is used to adjust the updated initial charging scheduling information that does not satisfy the charging constraint condition.

[0143] Specifically, if the updated initial charging schedule information corresponding to the third body obtained by the crossover operation and / or mutation operation does not meet the charging constraint conditions, the updated initial charging schedule information corresponding to the third body can be adjusted based on the repair operator to obtain the adjusted third body. The population to be processed can then be updated based on the adjusted third body and at least one first body.

[0144] For example, in conjunction with the above examples, crossover operations can cause the updated initial charging schedule information corresponding to a third entity to fail to meet charging constraints. For instance, two guide vehicles may be charging at the same assigned charging pile simultaneously, or the charging start time of the guide vehicles may not fall within a preset time range. Similarly, mutation operations may also cause the updated initial charging schedule information corresponding to a third entity to fail to meet charging constraints. For example, the charging order of multiple guide vehicles corresponding to a given charging pile may be disrupted, or there may be charging time conflicts among the guide vehicles.

[0145] If the updated initial charging schedule information corresponding to the third entity is found to not satisfy any charging constraint, it can be corrected based on the repair operator to ensure the validity of the updated initial charging schedule information.

[0146] This involves identifying factors in the updated initial charging schedule information that do not meet charging constraints through a repair operator. For example, it might detect that a guide vehicle is charging at two different charging stations. Correction rules are determined based on these factors, and the updated initial charging schedule information is adjusted accordingly. For instance, if duplicate charging occurs (i.e., the guide vehicle corresponds to two charging stations), one of the correspondences is deleted.

[0147] It should be noted that if the updated initial charging schedule information corresponding to the third entity all meet the charging constraints, then there is no need to adjust the third entity using the repair operator.

[0148] Optionally, for multiple guide vehicles corresponding to the same charging pile experiencing overlapping charging times, the repair operator can adjust the updated initial charging schedule information corresponding to the third entity in the following way: Retain the allocation relationship in the updated initial charging schedule information; initialize the charging start time of each guide vehicle in the updated initial charging schedule information to 0; estimate the charging duration of each guide vehicle based on its initial and target battery levels; sort at least one guide vehicle corresponding to each charging pile in ascending order of charging duration; determine the charging start time of each guide vehicle based on the sorting result and charging time; and obtain the charging schedule information corresponding to the adjusted third entity based on the charging start time of each guide vehicle and its corresponding allocation relationship. Based on the above, it can be understood that by forcing sequential execution and prioritizing shortest tasks, the charging time of guide vehicles on the same charging pile does not overlap.

[0149] S270. Based on at least one first individual and at least one third individual, update the population to be processed to obtain an updated population to be processed. Use the updated population to be processed as the population to be processed, and repeat the update process for the population to be processed. When the number of repeated executions reaches a preset threshold or the fitness change rate is lower than a preset value, use the charging scheduling information with the lowest fitness of the individual in the population to be processed as the target charging scheduling information.

[0150] The preset threshold number of times can be pre-set, representing the standard number of times the individuals in the population to be processed are updated. For example, the preset threshold number of times could be 100. The fitness change rate can be understood as the degree of change between the fitness values ​​of the updated population to be processed after multiple consecutive determinations. The preset value can be a pre-set standard value for the fitness change rate. The charging schedule information with the lowest fitness of individuals in the population to be processed is the earliest charging schedule information that ensures all the guide vehicles to be charged are fully charged.

[0151] Specifically, based on at least one first individual and at least one third individual, the population to be processed is updated to obtain an updated population to be processed. That is, the individuals included in the updated population to be processed are the first individual and the third individual. Using the individuals in the updated population to be processed as initial individuals, the updated population to be processed is used again as the population to be processed, and the process of determining the first individual and the third individual and updating the population to be processed is repeated until the number of repetitions reaches a preset threshold or the fitness change rate is lower than a preset value. The charging schedule information with the lowest fitness among the individuals in the population to be processed at this point is taken as the target charging schedule information.

[0152] For example, based on at least one first individual and at least one third individual, an updated population to be processed is determined; that is, the individuals included in the updated population to be processed are the first individual and the third individual. The individuals in the updated population to be processed are used as initial individuals, and the updated population to be processed is used again as the population to be processed. The process of determining the first individual and the third individual, and updating the population to be processed, is repeated until any of the following conditions are met, at which point the process terminates:

[0153] The execution count reaches a preset threshold of 100 times, or...

[0154] The rate of change of fitness of the population to be treated after 10 consecutive iterations 1% lower than the preset value.

[0155] in, ;

[0156] Indicates the current iteration (the... The global optimal fitness value (times); Indicates the previous iteration (the first iteration) The global optimal fitness value is the minimum fitness value among the fitness values ​​of each individual in the population to be processed.

[0157] S280. Based on the target charging scheduling information, control at least one waiting-to-charge guide vehicle to move to the corresponding target charging pile at the target charging start time for charging.

[0158] Among them, the target charging pile is the charging pile to be allocated determined according to the target allocation relationship.

[0159] The technical solution of this embodiment obtains vehicle information of at least one guide vehicle to be charged and charging pile information of at least one charging pile to be allocated within a target area. Based on the vehicle information and charging pile information, an objective function associated with the earliest completion of charging of at least one guide vehicle to be charged is determined. Based on at least one guide vehicle to be charged and at least one charging pile to be allocated, at least one initial charging schedule is determined, and this initial charging schedule is used as an initial individual to obtain a population to be processed. Based on the objective function and at least one charging constraint, the initial fitness corresponding to each initial individual is determined. Based on the initial fitness corresponding to each initial individual, at least one first individual is determined according to a preset individual retention ratio, and at least one second individual is determined according to a preset individual selection strategy. Crossover and / or mutation operations are performed on the at least one second individual to obtain at least one third individual. Based on at least one first individual and at least one third individual, the population to be processed is updated to obtain an updated population. This updated population is then used as the target population, and the update process is repeated until the number of repetitions reaches a preset threshold or the fitness change rate falls below a preset value. At this point, the charging schedule information with the lowest fitness among the individuals in the target population is selected as the target charging schedule information. This heuristic algorithm solves the objective function, achieving a near-optimal solution while maintaining speed, thus improving the speed and accuracy of determining the target charging schedule information. Based on the target charging schedule information, at least one guide vehicle is controlled to move to the corresponding target charging pile at the target charging start time specified in the target charging schedule information. This invention solves the problems of unreasonable charging resource allocation, excessively long overall charging time for automated guided vehicles in the area, and wasted charging resources caused by existing charging scheduling techniques. It achieves reasonable charging scheduling for guide vehicles, minimizing the overall charging time for guide vehicles in the target area and saving charging costs.

[0160] Example 3

[0161] Figure 6 This is a schematic diagram of the structure of a guiding vehicle charging scheduling device provided in Embodiment 3 of the present invention. Figure 6 As shown, the device includes: an information acquisition module 310, an objective function determination module 320, a scheduling information determination module 330, and a vehicle charging scheduling module 340.

[0162] Information acquisition module 310 is used to acquire vehicle information of at least one guide vehicle to be charged and charging pile information of at least one charging pile to be allocated within a target area; wherein, the vehicle information includes at least: vehicle quantity information, initial power information and target power information of each guide vehicle to be charged, and the charging pile information includes at least: charging pile quantity information; objective function determination module 320 is used to determine an objective function related to the earliest completion of charging of the at least one guide vehicle to be charged based on the vehicle information and the charging pile information; wherein, completion of charging is related to the power of the guide vehicle to be charged reaching the target power information; scheduling information determination module 330 is used to process the objective function according to a preset solution algorithm to determine target charging scheduling information under the condition of satisfying at least one charging constraint condition; wherein, the at least one charging constraint condition includes: a first constraint condition for controlling each guide vehicle to be charged to correspond to one charging pile to be allocated at the same charging time, and a second constraint condition for controlling each guide vehicle to be charged to correspond to one charging pile to be allocated at the same charging time. The system includes at least one of the following constraints: a second constraint preventing the allocation of tasks to guide vehicles whose power information does not reach the target power information; a third constraint ensuring that the charging start and end times of the guide vehicles fall within a preset time range; a fourth constraint ensuring that each assigned charging pile corresponds to at most one guide vehicle at the same charging time; and a fifth constraint ensuring that the power information of the guide vehicles at the end of charging is not less than the target power information. The target charging scheduling information includes at least the target allocation relationship between the guide vehicles and the assigned charging piles, and the target charging start time for each guide vehicle. The vehicle charging scheduling module 340 is configured to control at least one guide vehicle to move to the corresponding target charging pile at the target charging start time for charging, based on the target charging scheduling information. The target charging pile is the assigned charging pile determined based on the target allocation relationship.

[0163] The technical solution of this embodiment obtains vehicle information of at least one guide vehicle to be charged and charging pile information of at least one charging pile to be allocated within a target area. Based on the vehicle information and charging pile information, it determines an objective function associated with the earliest completion of charging for at least one guide vehicle to be charged. The objective function is processed according to a preset solution algorithm to determine target charging scheduling information while satisfying at least one charging constraint condition. Based on the target charging scheduling information, at least one guide vehicle to be charged is controlled to move to the corresponding target charging pile at the target charging start time specified in the target charging scheduling information for charging processing. This invention solves the problems of unreasonable allocation of charging resources, excessively long overall charging time for automated guided vehicles in the area, and waste of charging resources caused by charging scheduling based on existing technologies. It achieves reasonable charging scheduling for guide vehicles, minimizing the overall charging time for guide vehicles in the target area and saving charging costs for guide vehicles.

[0164] Based on the above embodiments, optionally, the objective function determination module is used to, for at least one guide vehicle to be charged, determine a current power determination function related to the charging status of the guide vehicle to be charged, based on the initial power information of the guide vehicle to be charged and the charging pile information of the charging pile to be allocated; determine a charging rate determination function corresponding to the current power determination function based on the correspondence between the current power and the charging rate; determine a target charging duration determination function corresponding to the charging rate determination function based on the initial power information and the target power information; and determine an objective function associated with the charging start time of each guide vehicle to be charged, based on the vehicle quantity information of the guide vehicles to be charged and the target charging duration determination function corresponding to the guide vehicles to be charged.

[0165] Optionally, the scheduling information determination module includes: a population to be processed determination unit, used to determine at least one initial charging scheduling information based on at least one guide vehicle to be charged and at least one charging pile to be allocated, and to use the initial charging scheduling information as initial individuals to obtain a population to be processed; wherein the population to be processed includes at least one initial individual; an initial fitness determination unit, used to determine the initial fitness corresponding to each initial individual based on the objective function and the at least one charging constraint; wherein the initial fitness is used to characterize the charging completion time corresponding to each initial charging scheduling information, and the charging completion time is used to characterize the time when all at least one guide vehicle to be charged is fully charged; and an individual selection unit, used to determine at least one first individual based on the initial fitness corresponding to each initial individual and according to preset individual retention ratio information, to obtain a population to be processed. Based on a preset individual selection strategy, at least one second individual is determined; wherein the first individual and the second individual are both initial individuals in the population to be processed; an individual crossover and mutation unit is used to perform crossover and / or mutation operations on the at least one second individual to obtain at least one third individual, wherein the third individual corresponds to the updated initial charging schedule information; a target charging schedule information determination unit is used to update the population to be processed based on at least one first individual and at least one third individual to obtain an updated population to be processed, and to use the updated population to be processed as the population to be processed, and to repeat the update process of the population to be processed, so that when the number of repetitions reaches a preset threshold or the fitness change rate is lower than a preset value, the charging schedule information with the lowest individual fitness in the population to be processed is used as the target charging schedule information.

[0166] Optionally, the population determination unit includes: an initial charging scheduling information determination subunit, configured to determine a charging pile allocation list based on at least one guide vehicle to be charged and at least one charging pile to be allocated, wherein the charging pile allocation list includes at least one allocation identifier, the allocation identifier being used to characterize the initial allocation relationship between the guide vehicle to be charged and the charging pile to be allocated; determine an initial charging start time list corresponding to at least one guide vehicle to be charged; wherein the initial charging start time list includes the initial charging start time of each guide vehicle to be charged; and determine initial charging scheduling information based on the charging pile allocation list and the initial charging start time list.

[0167] Optionally, an individual selection unit is configured to determine at least one first individual based on a preset individual retention ratio and the initial fitness of each initial individual; wherein the first individual is an initial individual in the population to be processed; determine at least one individual to be processed in the population to be processed; wherein the individual to be processed is an initial individual in the population to be processed that is not the first individual; and determine a preset number of second individuals based on probability distribution information corresponding to a preset individual selection strategy and the initial fitness of at least one individual to be processed.

[0168] Optionally, the scheduling information determination module further includes: an individual adjustment unit, used to adjust the third individual according to the repair operator if it is detected that there is a third individual that does not meet at least one of the charging constraints, so as to obtain an adjusted third individual, and to update the population to be processed based on the adjusted third individual.

[0169] Optionally, the device further includes: an information display module, used to generate at least one visual chart corresponding to the target charging scheduling information, and display at least one of the visual charts on the display page of the target terminal.

[0170] The vehicle charging scheduling device provided in this embodiment of the invention can execute the vehicle charging scheduling method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0171] Example 4

[0172] Figure 7This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0173] like Figure 7 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0174] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0175] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the guided vehicle charging scheduling method.

[0176] In some embodiments, the guided vehicle charging scheduling method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the guided vehicle charging scheduling method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to execute the guided vehicle charging scheduling method by any other suitable means (e.g., by means of firmware).

[0177] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0178] Computer programs used to implement the guided vehicle charging scheduling method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer programs can be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0179] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication unit 19, or installed from storage unit 18, or installed from ROM 12. When the computer program is executed by processor 11, it performs the functions defined in the methods of the embodiments of the present invention.

[0180] Example 5

[0181] Embodiment 5 of the present invention also provides a computer-readable storage medium storing computer instructions for causing a processor to execute a guided vehicle charging scheduling method, the method comprising:

[0182] Acquire vehicle information for at least one guide vehicle to be charged and charging pile information for at least one charging pile to be allocated within a target area; wherein, the vehicle information includes at least: vehicle quantity information, initial battery level information for each guide vehicle to be charged, and target battery level information, and the charging pile information includes at least: charging pile quantity information; based on the vehicle information and the charging pile information, determine an objective function related to the earliest completion of charging for the at least one guide vehicle to be charged; wherein, completion of charging is related to the battery level of the guide vehicle to be charged reaching the target battery level information; process the objective function according to a preset solution algorithm to determine target charging scheduling information under the condition of satisfying at least one charging constraint condition; wherein, the at least one charging constraint condition includes: a first constraint condition for controlling each guide vehicle to be charged to correspond to one charging pile to be allocated at the same charging time, and a second constraint condition for controlling the battery level not reaching the target battery level information. The system includes at least one of the following constraints: a second constraint on the allocation of the charging guide vehicle with target power information; a third constraint on ensuring that the charging start and end times of the charging guide vehicle are within a preset time range; a fourth constraint on ensuring that each charging pile to be allocated corresponds to at most one charging guide vehicle at the same charging time; and a fifth constraint on ensuring that the power information of the charging guide vehicle at the end of charging is not less than the target power information. The target charging scheduling information includes at least the target allocation relationship between the charging guide vehicle and the charging pile to be allocated, and the target charging start time of each charging guide vehicle. Based on the target charging scheduling information, the system controls at least one charging guide vehicle to move to the corresponding target charging pile at the target charging start time for charging processing, wherein the target charging pile is the charging pile to be allocated determined based on the target allocation relationship.

[0183] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on 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 fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0184] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0185] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0186] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0187] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0188] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for scheduling the charging of a guided vehicle, characterized in that, include: Obtain vehicle information of at least one guide vehicle to be charged and charging pile information of at least one charging pile to be allocated within the target area; wherein, the vehicle information includes at least: vehicle quantity information, initial power information and target power information of each guide vehicle to be charged, and the charging pile information includes at least: charging pile quantity information; Based on the vehicle information and the charging pile information, a target function is determined that is related to the earliest completion of charging of the at least one guide vehicle to be charged; wherein, completion of charging is related to the battery level of the guide vehicle to be charged reaching the target battery level. The objective function is processed according to a preset solution algorithm to determine target charging scheduling information under the condition that at least one charging constraint is satisfied. The at least one charging constraint includes at least one of the following: a first constraint to control that each guide vehicle to be charged corresponds to one charging pile to be allocated at the same charging time; a second constraint to control that no task is assigned to guide vehicles whose power information has not reached the target power information; a third constraint to control that the charging start time and charging end time of the guide vehicle to be charged belong to a preset time range; a fourth constraint to control that each charging pile to be allocated corresponds to at most one guide vehicle to be charged at the same charging time; and a fifth constraint to control that the power information of the guide vehicle to be charged at the charging end time is not less than the target power information. The target charging scheduling information includes at least: the target allocation relationship between the guide vehicle to be charged and the charging pile to be allocated, and the target charging start time of each guide vehicle to be charged. Based on the target charging scheduling information, the at least one guide vehicle to be charged is controlled to move to the corresponding target charging pile at the target charging start time for charging processing, wherein the target charging pile is the charging pile to be allocated determined according to the target allocation relationship.

2. The method according to claim 1, characterized in that, The objective function can be determined in the following way: For at least one guide vehicle to be charged, a current power determination function related to the charging status of the guide vehicle to be charged is determined based on the initial power information of the guide vehicle to be charged and the charging pile information of the charging pile to be allocated. Based on the correspondence between the current battery level and the charging rate, determine the charging rate determination function corresponding to the current battery level determination function; Based on the initial power information and the target power information, a target charging duration determination function corresponding to the charging rate determination function is determined; Based on the vehicle quantity information of the guide vehicles to be charged and the target charging duration determination function corresponding to the guide vehicles to be charged, a target function associated with the charging start time of each guide vehicle to be charged is determined.

3. The method according to claim 1, characterized in that, The step of processing the objective function according to a preset solution algorithm to determine the target charging scheduling information under the condition of satisfying at least one charging constraint includes: Based on at least one guide vehicle to be charged and at least one charging pile to be allocated, at least one initial charging schedule information is determined, and the initial charging schedule information is used as an initial individual to obtain a population to be processed; wherein, the population to be processed includes at least one initial individual; Based on the objective function and the at least one charging constraint, an initial fitness corresponding to each initial individual is determined; wherein, the initial fitness is used to characterize the charging completion time corresponding to each initial charging scheduling information, and the charging completion time is used to characterize the time when all at least one guide vehicle to be charged is fully charged; Based on the initial fitness of each initial individual, at least one first individual is determined according to the preset individual retention ratio information, and at least one second individual is determined according to the preset individual selection strategy; wherein, the first individual and the second individual are both initial individuals in the population to be processed; Perform crossover and / or mutation operations on the at least one second body to obtain at least one third body, wherein the third body corresponds to the updated initial charging schedule information; Based on at least one first individual and at least one third individual, the population to be processed is updated to obtain an updated population to be processed. The updated population to be processed is used as the population to be processed, and the update process of the population to be processed is repeated. When the number of repeated executions reaches a preset threshold or the fitness change rate is lower than a preset value, the charging scheduling information with the lowest fitness of individuals in the population to be processed is used as the target charging scheduling information.

4. The method according to claim 3, characterized in that, The initial charging scheduling information is determined in the following manner: Based on at least one guide vehicle to be charged and at least one charging pile to be assigned, a charging pile allocation list is determined, wherein the charging pile allocation list includes at least one allocation identifier, which is used to characterize the initial allocation relationship between the guide vehicle to be charged and the charging pile to be assigned; Determine an initial charging start time list corresponding to at least one guide vehicle to be charged; wherein the initial charging start time list includes the initial charging start time of each guide vehicle to be charged; The initial charging schedule information is determined based on the charging pile allocation list and the initial charging start time list.

5. The method according to claim 3, characterized in that, The process of determining at least one first individual based on the initial fitness of each initial individual, according to preset individual retention ratio information, and determining at least one second individual based on a preset individual selection strategy, includes: Based on the preset individual retention ratio information and the initial fitness of each initial individual, at least one first individual is determined; wherein, the first individual is the initial individual in the population to be processed; Identify at least one individual to be processed in the population to be processed; wherein, the individual to be processed is an initial individual in the population to be processed that is not the first individual; Based on the probability distribution information corresponding to the preset individual selection strategy and the initial fitness of at least one of the individuals to be processed, a preset number of second individuals are determined.

6. The method according to claim 3, characterized in that, After obtaining at least one third body, the method further includes: If it is detected that the third body does not satisfy at least one of the charging constraints, the third body is adjusted according to the repair operator to obtain the adjusted third body, and the population to be processed is updated based on the adjusted third body.

7. The method according to claim 1, characterized in that, After determining the target charging scheduling information, the method further includes: Generate at least one visualization chart corresponding to the target charging scheduling information, and display at least one of the visualization charts on the display page of the target terminal.

8. A vehicle charging scheduling device, characterized in that, include: The information acquisition module is used to acquire vehicle information of at least one guide vehicle to be charged and charging pile information of at least one charging pile to be allocated within the target area; wherein, the vehicle information includes at least: vehicle quantity information, initial power information and target power information of each guide vehicle to be charged, and the charging pile information includes at least: charging pile quantity information. The objective function determination module is used to determine an objective function related to the earliest completion of charging of the at least one guide vehicle to be charged, based on the vehicle information and the charging pile information; wherein, completing charging is related to the battery level of the guide vehicle to be charged reaching the target battery level information; The scheduling information determination module is used to process the objective function according to a preset solution algorithm to determine target charging scheduling information under the condition that at least one charging constraint is satisfied. The at least one charging constraint includes at least one of the following: a first constraint to control that each guide vehicle to be charged corresponds to one charging pile to be allocated at the same charging time; a second constraint to control that no task is assigned to guide vehicles whose power information has not reached the target power information; a third constraint to control that the charging start time and charging end time of the guide vehicle to be charged belong to a preset time range; a fourth constraint to control that each charging pile to be allocated corresponds to at most one guide vehicle to be charged at the same charging time; and a fifth constraint to control that the power information of the guide vehicle to be charged at the charging end time is not less than the target power information. The target charging scheduling information includes at least: the target allocation relationship between the guide vehicle to be charged and the charging pile to be allocated, and the target charging start time of each guide vehicle to be charged. The vehicle charging scheduling module is used to control at least one guide vehicle to move to the corresponding target charging pile for charging at the target charging start time, based on the target charging scheduling information, wherein the target charging pile is a charging pile to be allocated determined according to the target allocation relationship.

9. A guide vehicle, characterized in that, The guide vehicle includes: At least one processor; and A controller communicatively connected to the at least one processor; wherein, The at least one processor is used to receive target charging scheduling information and send a control signal to the controller when it detects that the current time is consistent with the target charging start time in the target charging scheduling information; The controller is used to receive the control signal and control the guide vehicle to move to the target charging pile corresponding to the target charging scheduling information for charging.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the guiding vehicle charging scheduling method according to any one of claims 1-7.

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