Automatic charging method for unmanned logistics vehicle

Abstract

The invention relates to an unmanned logistics vehicle automatic charging method, and belongs to the technical field of unmanned vehicle automatic charging, and the method comprises the steps: obtaining a first electric quantity loss according to a task movement route, obtaining a charging operation route according to an end point coordinate and a preset charging station coordinate, obtaining a second electric quantity loss according to the charging operation route, the first electric quantity loss and the second electric quantity loss are added to obtain total electric quantity loss, if the remaining electric quantity of the unmanned logistics vehicle is larger than or equal to the total electric quantity loss, a logistics task is executed, and if the remaining electric quantity of the unmanned logistics vehicle is smaller than the total electric quantity loss, the unmanned logistics vehicle is controlled to go to a charging station for charging operation; according to the method, when whether automatic charging is carried out or not is determined, key influence factors such as the transportation task path, the charging operation path and extra electric quantity loss on the operation path are combined, it is ensured that automatic charging can be completed, meanwhile, the electric quantity of the unmanned logistics vehicle can be utilized to the maximum degree, and the transportation efficiency of the unmanned logistics vehicle is effectively improved.

Description

Technical Field

[0001] This invention belongs to the field of unmanned vehicle automatic charging technology, specifically relating to an automatic charging method for unmanned logistics vehicles. Background Technology

[0002] Existing automatic charging solutions for unmanned logistics vehicles determine whether to charge by setting a threshold. If the vehicle's remaining battery power is greater than the threshold, charging is not required; if the remaining battery power is less than the threshold, the vehicle automatically searches for a charging station. This solution relies solely on the threshold battery power to determine whether to charge. Sometimes, the vehicle may have enough battery power to complete the next logistics task before charging, but the remaining battery power is less than the threshold, leading to the vehicle not operating at full capacity. Other times, the vehicle may have enough battery power to complete a long-distance logistics task, but the battery power is insufficient to continue operating, requiring manual intervention to recharge. Therefore, existing automatic charging solutions are prone to unexpected situations due to their simplistic consideration of factors, resulting in low logistics efficiency. Summary of the Invention

[0003] To address this issue, the present invention provides an automatic charging method for unmanned logistics vehicles, thereby solving the problem of low logistics and transportation efficiency caused by the simplistic consideration of factors in existing automatic charging solutions, which are prone to unexpected situations.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] In a first aspect, the present invention provides an automatic charging method for unmanned logistics vehicles, comprising:

[0006] Acquire the travel data of the unmanned logistics vehicle for the current logistics task; the travel data includes the starting point coordinates, the ending point coordinates, and the task movement route;

[0007] The first power loss is obtained based on the described task movement route;

[0008] The charging route is obtained based on the endpoint coordinates and the preset charging station coordinates;

[0009] The second power loss is obtained based on the charging operation route;

[0010] The total power loss is obtained by adding the first power loss and the second power loss.

[0011] If the remaining battery power of the unmanned logistics vehicle is greater than or equal to the total battery loss, then the logistics task is executed;

[0012] If the remaining battery power of the unmanned logistics vehicle is less than the total battery loss, then the unmanned logistics vehicle is controlled to go to the charging station for charging.

[0013] Further, obtaining the first power loss based on the task movement route includes:

[0014] The percentage of the breaching path is obtained based on the described mission movement route;

[0015] The temperature correction factor is obtained based on the current temperature;

[0016] The load correction factor is obtained based on the task load of the unmanned logistics vehicle;

[0017] The power loss coefficient is obtained based on the proportion of the broken path, the temperature correction coefficient, and the load correction coefficient.

[0018] The power loss is obtained based on the power loss coefficient and the nominal power, and is taken as the first power loss.

[0019] Furthermore, obtaining the second power loss based on the charging operation route includes:

[0020] The percentage of the road breaking path is obtained based on the charging operation route.

[0021] The temperature correction factor is obtained based on the current temperature;

[0022] The load correction factor is obtained based on the task load of the unmanned logistics vehicle;

[0023] The power loss coefficient is obtained based on the proportion of the broken path, the temperature correction coefficient, and the load correction coefficient.

[0024] The power loss is obtained based on the power loss coefficient and the nominal power as the second power loss.

[0025] Furthermore, the step of obtaining the power loss coefficient based on the breakdown path ratio, temperature correction coefficient, and load correction coefficient includes:

[0026] The power loss coefficient is obtained by using the loss coefficient formula based on the breakdown path ratio, temperature correction coefficient, and load correction coefficient. The loss coefficient formula is as follows:

[0027] K loss =R path ×K temp ×K load ;

[0028] Among them, K loss R is the power loss coefficient. path K represents the percentage of breakthrough paths. temp K is the temperature correction factor. load This is the load correction factor.

[0029] Further, the step of obtaining the power loss based on the power loss coefficient and the nominal power capacity includes:

[0030] The power loss is obtained through a power loss formula, which is:

[0031] Q1 = Q 标称 ×(1-K loss );

[0032] Where Q1 represents power loss; Q 标称 The nominal power consumption refers to the power consumed when running the mission route on a smooth, level road, K. loss This represents the power loss coefficient.

[0033] Furthermore, the formula for calculating the proportion of the road breaking path is as follows:

[0034]

[0035] Among them, R path The percentage of breakthrough paths; L path This refers to the total length of the damaged road, including bumpy sections and uphill sections; L total This represents the total length of the route.

[0036] Furthermore, the formula for calculating the temperature correction coefficient is as follows:

[0037]

[0038] Among them, K temp This is the temperature correction factor, where T is the current temperature and 25 is the baseline value, representing the optimal operating temperature of the battery.

[0039] Furthermore, the formula for calculating the load correction factor is as follows:

[0040] K load =1 + 0.02 × (MM) empty ) / M empty ;

[0041] Among them, K load M is the load correction factor; M is the current total vehicle mass; M empty This refers to the vehicle's unloaded weight.

[0042] Further, obtaining the charging route based on the endpoint coordinates and the preset charging station coordinates includes:

[0043] Obtain the coordinates of all the preset charging stations;

[0044] Multiple travel paths are obtained based on the destination coordinates and the coordinates of each preset charging station.

[0045] Select the longest path from the travel paths as the charging route.

[0046] Furthermore, the control of the unmanned logistics vehicle to proceed to the charging station for charging includes:

[0047] Obtain the coordinates of all the preset charging stations;

[0048] Multiple travel paths are obtained based on the starting point coordinates and the coordinates of each preset charging station.

[0049] Select the shortest path from the travel paths as the automatic charging route;

[0050] The unmanned logistics vehicle runs to the charging station for automatic charging according to the automatic charging path.

[0051] The present invention, by adopting the above technical solution, has at least the following beneficial effects:

[0052] An automatic charging method for unmanned logistics vehicles is provided. When a logistics task is assigned to the unmanned logistics vehicle by the scheduling system, the unmanned logistics vehicle obtains the travel data of the logistics task, calculates the first power loss based on the task's movement route, calculates the charging route based on the destination coordinates and the coordinates of a preset charging station, and calculates the second power loss based on the charging route. The first and second power losses are added together to obtain the total power loss. If the remaining power of the unmanned logistics vehicle is greater than or equal to the total power loss, the logistics task is executed. If the remaining power of the unmanned logistics vehicle is less than the total power loss, the unmanned logistics vehicle is controlled to proceed to the charging station for charging. This method combines key influencing factors such as the transportation task path, the charging route, and additional power losses along the route when determining whether to automatically charge. While ensuring automatic charging, it also maximizes the utilization of the unmanned logistics vehicle's power, effectively improving the transportation efficiency of the unmanned logistics vehicle.

[0053] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Attached Figure Description

[0054] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the 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.

[0055] Figure 1 This is a flowchart illustrating an exemplary embodiment of the present invention of an automatic charging method for an unmanned logistics vehicle;

[0056] Figure 2 This is a schematic block diagram illustrating an automatic charging device for an unmanned logistics vehicle according to an exemplary embodiment of the present invention;

[0057] Figure 3 This is a schematic diagram of an electronic device illustrated in an exemplary embodiment of the present invention.

[0058] The present invention will be further described below with reference to the accompanying drawings and specific embodiments. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be described in detail below. Obviously, the described embodiments are merely some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other implementation methods obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0060] Currently, the unmanned logistics vehicles in the factory rely on manual judgment to determine whether they need charging. Vehicles with low battery levels need to be driven to charging stations by humans. Since there are many unmanned logistics vehicles in the factory, if vehicles that need charging are not monitored in time and charged in time, vehicles may run out of power in non-charging areas, requiring forklifts to move them to the charging area, wasting manpower and resources, and potentially affecting production. The unmanned transport vehicles can be IGVs or AGVs; namely, Intelligent Guided Vehicles (IGVs) and Automated Guided Vehicles (AGVs).

[0061] This invention provides an automatic charging method for unmanned logistics vehicles. When determining whether to automatically charge, the method considers key influencing factors such as the transportation task path, the charging operation path, and additional power loss along the operation path. This ensures that automatic charging can be completed while maximizing the utilization of the unmanned logistics vehicle's power, effectively improving the transportation efficiency of the unmanned logistics vehicle.

[0062] The method of the present invention will be described below through specific embodiments.

[0063] Please see Figure 1 , Figure 1 This is a flowchart illustrating an exemplary embodiment of the present invention of an automatic charging method for an unmanned logistics vehicle. See also: Figure 1 The method includes:

[0064] Step S11: Obtain the travel data of the unmanned logistics vehicle for the current logistics task; the travel data includes the starting point coordinates, the ending point coordinates, and the task movement route;

[0065] Step S12: Obtain the first power loss based on the task movement route;

[0066] Step S13: Obtain the charging route based on the destination coordinates and the preset charging station coordinates;

[0067] Step S14: Obtain the second power loss based on the charging operation route;

[0068] Step S15: Add the first power loss and the second power loss to obtain the total power loss;

[0069] Step S16: If the remaining battery power of the unmanned logistics vehicle is greater than or equal to the total battery loss, then execute the logistics task.

[0070] Step S17: If the remaining battery power of the unmanned logistics vehicle is less than the total battery loss, then control the unmanned logistics vehicle to go to the charging station for charging.

[0071] It should be noted that the technical solution provided in this embodiment can be used in practice as a mini-program or a plugin within existing logistics systems or applications, or as a standalone application that implements automatic charging functionality through external interfaces. Applicable scenarios include, but are not limited to, automatic charging of unmanned logistics vehicles within factory areas.

[0072] Specifically, total power loss can also include reserved power, which can be set according to business needs, with a default setting of 0.

[0073] It should be noted that the preset charging station coordinates are set based on the actual charging station locations within the factory area. That is, the unmanned logistics vehicle can automatically charge by moving to any preset charging station coordinate.

[0074] It is understood that, in the method provided in this embodiment, when the scheduling system issues a logistics task to the unmanned logistics vehicle, the unmanned logistics vehicle obtains the travel data of the logistics task, obtains the first power loss based on the task's movement route, obtains the charging route based on the destination coordinates and the coordinates of the preset charging station, obtains the second power loss based on the charging route, and adds the first power loss and the second power loss to obtain the total power loss. If the remaining power of the unmanned logistics vehicle is greater than or equal to the total power loss, the logistics task is executed; if the remaining power of the unmanned logistics vehicle is less than the total power loss, the unmanned logistics vehicle is controlled to go to the charging station for charging. This method combines key influencing factors such as the transportation task path, the charging route, and the additional power loss on the route when determining whether to automatically charge. While ensuring that automatic charging can be completed, it can also maximize the utilization of the unmanned logistics vehicle's power, effectively improving the transportation efficiency of the unmanned logistics vehicle.

[0075] In practice, the "travel data" in step S11 includes the starting point coordinates, the ending point coordinates, and the mission movement route.

[0076] It should be noted that when the scheduling system issues a logistics task to the unmanned logistics vehicle, it automatically generates the starting point coordinates, the ending point coordinates, and the task movement route, which is a mature existing technology. The starting point coordinates are the current coordinates of the unmanned logistics vehicle, and the ending point coordinates are the coordinates of the unmanned logistics vehicle's resting position after the transportation task is completed. The task movement route is obtained by using existing technology to plan the route based on the starting point coordinates and the ending point coordinates.

[0077] In practice, steps S12 and S14, "obtaining power loss based on the task movement route," includes: obtaining the path clearing ratio based on the task movement route; obtaining a temperature correction coefficient based on the current temperature; obtaining a load correction coefficient based on the task load of the unmanned logistics vehicle; and obtaining the power loss coefficient using the loss coefficient formula based on the path clearing ratio, temperature correction coefficient, and load correction coefficient. The loss coefficient formula is: K loss =R path ×K temp ×K load Among them, K loss R is the power loss coefficient. path K represents the percentage of breakthrough paths. temp K is the temperature correction factor. load This is the load correction factor; the first power loss is obtained based on the power loss factor and the nominal power, and the calculation formula is: Q1 = Q 标称 ×(1-K loss ); where Q1 is the first power loss; Q 标称 The nominal power consumption refers to the power consumed when running the mission route on a smooth, level road.

[0078] It should be noted that the energy consumption differences under different road conditions (such as smooth road surface, damaged road surface, and slope), the battery efficiency correction under different ambient temperatures (-20℃ to 45℃), and the dynamic energy consumption calculation under different load conditions (no load, half load, and full load) are taken into account in the first power loss.

[0079] It should be noted that, at a temperature of 25℃, when the vehicle is unloaded on a flat road surface, the one-to-one correspondence between the driving distance and power consumption was obtained through experiments. Knowing the distance of the route, the corresponding nominal power consumption can be obtained.

[0080] Specifically, the formula for calculating the proportion of road breaking paths is as follows: Among them, R path The percentage of breakthrough paths; L path This refers to the total length of the damaged road, including bumpy sections and uphill sections; L total This represents the total length of the route.

[0081] It should be noted that the length of broken roads can be calculated by using the navigation system and the road condition marking on the internal map of the factory area. Bumpy road sections and uphill sections have been marked in advance on the internal map of the factory area.

[0082] Specifically, the formula for calculating the temperature correction factor is as follows:

[0083] Among them, K temp This is the temperature correction factor, where T is the current temperature and 25 is the baseline value, representing the optimal operating temperature of the battery.

[0084] It should be noted that the current temperature is collected in real time through an onboard temperature sensor.

[0085] Specifically, the formula for calculating the load correction factor is as follows:

[0086] K load =1 + 0.02 × (MM) empty ) / M empty Among them, K load M is the load correction factor; M is the current total vehicle mass; M empty This refers to the vehicle's unloaded weight.

[0087] It should be noted that load data can be calculated through weighing sensors, and the current total mass of the vehicle can generally be set to the calibrated full load mass by default.

[0088] It is understood that the technical solution provided in this embodiment takes into account key influencing factors such as the transportation task path, the charging operation path, and the additional power loss on the operation path when determining whether to automatically charge. While ensuring that automatic charging can be completed, it can also maximize the utilization of the unmanned logistics vehicle's power, effectively improving the transportation efficiency of the unmanned logistics vehicle.

[0089] In practice, the charging route is obtained based on the destination coordinates and the coordinates of the preset charging stations, including: obtaining the coordinates of all preset charging stations; obtaining multiple travel paths based on the destination coordinates and the coordinates of each preset charging station; and selecting the longest path from the travel paths as the charging route.

[0090] It should be noted that after the unmanned logistics vehicle completes the task, it will stop at the destination coordinates. Existing technology can be used to plan the travel path from the destination coordinates to each preset charging station coordinates, and the longest path can be selected as the charging route. This can ensure that the unmanned logistics vehicle can reach any charging station to charge when it reaches the end of the logistics task.

[0091] In practice, controlling the unmanned logistics vehicle to go to the charging station for charging includes: obtaining the coordinates of all preset charging stations; obtaining multiple travel paths based on the starting point coordinates and the coordinates of each preset charging station; selecting the shortest path from the travel paths as the automatic charging route; and the unmanned logistics vehicle running to the charging station according to the automatic charging path for automatic charging.

[0092] It should be noted that the current coordinates of the unmanned logistics vehicle are the starting coordinates. Existing technology can be used to plan the travel path from the starting coordinates to each preset charging station coordinates, and the shortest path can be selected as the charging route. Since it has been determined that charging will be carried out, it is necessary to ensure that the unmanned logistics vehicle can reach the charging station as soon as possible. When considering the shortest path as the charging route, it is possible to first check the charging system to see if there are any available charging slots.

[0093] In one specific embodiment, the power loss coefficient of a certain route is calculated. The total length of the route is 10km, with 2km of broken road sections (including 1km of slope); the ambient temperature is 35℃; and the vehicle is fully loaded (the load is 1.5 times that of the unloaded vehicle).

[0094] The calculation process is as follows:

[0095] 1.R path =2 / 10 = 0.2;

[0096] 2.K temp =1 + 0.005 × (35 - 25) = 1.05;

[0097] 3.K load =1 + 0.02 × (1.5 - 1) = 1.01;

[0098] 4.K loss =0.2×1.05×1.01≈0.212.

[0099] The power loss coefficient for this section of the road is 21.2%.

[0100] Please see Figure 2 , Figure 2 This is a schematic block diagram illustrating an automatic charging device for an unmanned logistics vehicle according to an exemplary embodiment of the present invention. See also: Figure 2 The automatic charging device 100 for unmanned logistics vehicles includes:

[0101] The acquisition module 101 is used to acquire the travel data of the unmanned logistics vehicle for the current logistics task; the travel data includes the starting point coordinates, the ending point coordinates, and the task movement route;

[0102] The power loss module 102 is used to obtain the first power loss based on the task movement route; obtain the charging operation route based on the endpoint coordinates and the preset charging station coordinates; obtain the second power loss based on the charging operation route; and add the first power loss and the second power loss to obtain the total power loss.

[0103] The execution module 103 is used to execute a logistics task if the remaining power of the unmanned logistics vehicle is greater than or equal to the total power loss; and to control the unmanned logistics vehicle to go to the charging station for charging if the remaining power of the unmanned logistics vehicle is less than the total power loss.

[0104] It should be noted that the device provided in this embodiment is applicable to scenarios including but not limited to: automatic charging of unmanned logistics vehicles within a factory area.

[0105] It is understood that the device provided in this embodiment, when the scheduling system issues a logistics task to the unmanned logistics vehicle, obtains a first power loss based on the task movement route, obtains a charging operation route based on the destination coordinates and the preset charging station coordinates, obtains a second power loss based on the charging operation route, and adds the first power loss and the second power loss to obtain the total power loss. If the remaining power of the unmanned logistics vehicle is greater than or equal to the total power loss, the logistics task is executed; if the remaining power of the unmanned logistics vehicle is less than the total power loss, the unmanned logistics vehicle is controlled to go to the charging station for charging. This method combines key influencing factors such as the transportation task path, the charging operation path, and the additional power loss on the operation path when determining whether to automatically charge. While ensuring that automatic charging can be completed, it can also maximize the utilization of the unmanned logistics vehicle's power, effectively improving the transportation efficiency of the unmanned logistics vehicle.

[0106] Please see Figure 3 , Figure 3 This is a schematic diagram of an electronic device illustrated in an exemplary embodiment of the present invention. See also: Figure 3 The electronic device 200 includes: at least one processor 202; and

[0107] Memory 201 is communicatively connected to at least one processor 202; wherein,

[0108] The memory 201 stores instructions that can be executed by at least one processor 202, which enables the at least one processor 202 to perform any of the above-described automatic charging methods for unmanned logistics vehicles.

[0109] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0110] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0111] It should also be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for display, data used for analysis, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0112] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0113] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0114] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. An unmanned automatic charging method for a flow vehicle, characterized by, The method comprises the following steps: obtaining the travel data of the current logistics task of the unmanned logistics vehicle; the travel data comprises the starting point coordinates, the end point coordinates and the task motion route; obtaining the first power loss according to the task motion route; obtaining the charging operation route according to the end point coordinates and the preset charging station coordinates; obtaining the second power loss according to the charging operation route; adding the first power loss and the second power loss to obtain the total power loss; if the remaining power of the unmanned logistics vehicle is greater than or equal to the total power loss, the logistics task is executed; if the remaining power of the unmanned logistics vehicle is less than the total power loss, the unmanned logistics vehicle is controlled to go to the charging station for charging operation.

2. The automatic charging method according to claim 1, characterized by, The step of obtaining the first power loss according to the task motion route comprises the following steps: obtaining the broken path proportion according to the task motion route; obtaining the temperature correction coefficient according to the current temperature; obtaining the load correction coefficient according to the task load of the unmanned logistics vehicle; obtaining the power loss coefficient according to the broken path proportion, the temperature correction coefficient and the load correction coefficient; obtaining the power loss as the first power loss according to the power loss coefficient and the nominal power.

3. The automatic charging method according to claim 1, characterized by, The step of obtaining the second power loss according to the charging operation route comprises the following steps: obtaining the broken path proportion according to the charging operation route; obtaining the temperature correction coefficient according to the current temperature; obtaining the load correction coefficient according to the task load of the unmanned logistics vehicle; obtaining the power loss coefficient according to the broken path proportion, the temperature correction coefficient and the load correction coefficient; obtaining the power loss as the second power loss according to the power loss coefficient and the nominal power.

4. The automatic charging method according to any one of claims 2 or 3, characterized in that, The step of obtaining the power loss coefficient according to the broken path proportion, the temperature correction coefficient and the load correction coefficient comprises the following steps: obtaining the power loss coefficient according to the broken path proportion, the temperature correction coefficient and the load correction coefficient through the loss coefficient formula, wherein the loss coefficient formula is: K loss = R path x K temp x K load : Wherein, K loss is the electric quantity loss coefficient, R path is the breaking path proportion, K temp is the temperature correction coefficient, K load is the load correction coefficient.

5. The automatic charging method according to any one of claims 2 or 3, characterized in that, The step of obtaining the power loss according to the power loss coefficient and the nominal power comprises the following steps: obtaining the power loss through the power loss formula, wherein the power loss formula is: Q1 = Q 标称 x (1 - K loss ); Wherein, Q1 is the electric quantity loss; Q 标称 is the nominal electric quantity, i.e. the electric quantity consumed for running the task movement route on a perfect flat road, K loss is the electric quantity loss coefficient.

6. The automatic charging method according to any one of claims 2 or 3, wherein The calculation formula of the broken path proportion is: wherein R path is the broken path ratio; L path is the total broken path length, including the bump road section and the uphill road section; L total is the total length of the running route.

7. The automatic charging method according to any one of claims 2 or 3, characterized by, The calculation formula of the temperature correction coefficient is: where K temp is a temperature correction factor, T is the current temperature, and 25 is the reference value, which is the optimal operating temperature of the battery.

8. The automatic charging method according to any one of claims 2 or 3, characterized by, The calculation formula of the load correction coefficient is: K load = 1 + 0.02 x (M - M empty ) / M empty ; wherein K load is a load correction factor; M is the current vehicle mass; M empty is the vehicle unladen mass.

9. The automatic charging method according to claim 1, characterized by, The step of obtaining the charging operation route according to the end point coordinates and the preset charging station coordinates comprises the following steps: obtaining all the preset charging station coordinates; obtaining multiple travel paths according to the end point coordinates and each preset charging station coordinate; selecting the longest path from the travel paths as the charging operation route.

10. The automatic charging method according to claim 1, characterized by, The step of controlling the unmanned logistics vehicle to go to the charging station for charging operation comprises the following steps: obtaining all the preset charging station coordinates; obtaining multiple travel paths according to the starting point coordinates and each preset charging station coordinate; selecting the shortest path from the travel paths as the automatic charging route; the unmanned logistics vehicle runs to the charging station according to the automatic charging route for automatic charging.

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