Intelligent scheduling control method of new energy automobile ordered charging guide rail type robot

Abstract

The invention discloses an intelligent scheduling control method for a new energy automobile ordered charging guide rail type robot, and the method comprises the following steps: S1, providing an annular charging track which is provided with a guide rail type robot; s2, two rows of parking spaces are provided, the number of one row of parking spaces is from the minimum parking space to the minimum parking space + m, the number of the other row of parking spaces is from the maximum parking space to the maximum parking space-n, and m and n are natural numbers larger than 1; s3, the position of the guide rail type robot is set as the current parking position of the robot, the idle pile position and the target position are set, the target position is the current idle charging position, and the idle pile position is the position where a charging pile capable of being used for charging is located; and S4, the idle piles are transmitted to a target position through the optimal path by an intelligent scheduling system, a scene recognition module and a path planning algorithm.

Description

Technical Field

[0001] The present invention relates to the field of new energy vehicle charging technology, specifically to an intelligent dispatching control method of a rail-type robot for orderly charging of new energy vehicles, in particular to an intelligent dispatching control technology and implementation method (O-type rail) of a rail-type robot for new energy vehicle charging stations. Background Art

[0002] With the popularity of new energy vehicles, the demand for charging is growing, and the operational efficiency and charging order of charging stations have become key issues. Traditional fixed charging piles are often occupied by oil trucks and overtime during use, which seriously affects the use of charging piles and causes waste of charging resources. In order to solve these pain points, rail-type robots are introduced into charging stations to achieve automated and orderly shared charging. In the prior art, robot scheduling systems mostly use fixed paths or simple algorithms, lack flexibility and intelligent decision-making capabilities, and cannot effectively respond to complex and changing charging needs. Summary of the invention

[0003] In view of the shortcomings of the prior art, the present invention provides an intelligent scheduling control method for a rail-type robot for orderly charging of new energy vehicles. The purpose of the present invention is to propose an intelligent scheduling control technology and implementation method, and to improve the operating efficiency and charging order of the charging station by optimizing the robot's operating path and scheduling strategy.

[0004] To achieve the above object, the present invention provides the following technical solutions: The intelligent dispatching control method of the rail-type robot for orderly charging of new energy vehicles comprises the following steps: Step S1: providing a ring-shaped charging track, on which a rail-type robot is arranged; Step S2: providing two rows of parking spaces, wherein one row of parking spaces is numbered from the smallest parking space to the smallest parking space+m, and the other row of parking spaces is numbered from the largest parking space to the largest parking space-n, wherein m and n are natural numbers greater than 1; Step S3: setting the position of the rail-type robot as the current docking position of the robot, and setting the idle pile position and the target position, wherein the target position is the current idle charging position, and the idle pile position is the position of the charging pile that can be used for charging; Step S4: The idle piles are transported to the target location via the optimal path through the intelligent scheduling system, scene recognition module, and path planning algorithm.

[0005] As a further solution of the present invention, the intelligent scheduling system is used to monitor the status of the charging station in real time, including the current position of the rail robot, the number and position of the idle piles, and the position of the vehicle to be charged; the scene recognition module intelligently identifies different charging scenarios based on the robot's current docking position, target position and the position of the idle piles; the path planning algorithm designs different path planning algorithms for the charging scheduling scenario of the circular track and calculates the optimal path to minimize the robot's moving distance and time.

[0006] As a further solution of the present invention, scenario 1: when the distance of the target position ≥ the distance of the docking position, and the idle pile is between the rail robot and the target position, there are two paths: path A1=(idle pile position-current docking position)+(target position-idle pile position) and path B1=(idle pile position-current docking position)+(idle pile position-minimum parking space)+(maximum parking space-target position).

[0007] As a further solution of the present invention, scenario 2: when the distance of the target position is greater than the distance of the docking position, and the free pile is between the rail robot and the minimum parking space, there are two paths: path A2 = (current docking position - free pile position) + (target position - free pile position) and path B2 = (current docking position - free pile position) + (free pile position - minimum parking space) + (maximum parking space - target position).

[0008] As a further solution of the present invention, scenario 3: when the distance of the target position ≥ the distance of the parking position, and the free pile is between the target position and the maximum parking space, there are two paths: path A3 = (free pile position - current parking position) + (free pile position - target position) and path B3 = (current parking position - minimum parking space) + (maximum parking space - free pile position) + (free pile position - target position).

[0009] As a further solution of the present invention, scenario 4: when the distance to the target position is less than the distance to the docking position, and the idle pile is between the rail robot and the target position, there are two paths: path A4 = (current docking position - idle pile position) + (idle pile position - target position) and path B4 = (current docking position - idle pile position) + (maximum parking space - current docking position) + (target position - minimum parking space).

[0010] As a further solution of the present invention, scenario 5: when the distance to the target position is less than the distance to the docking position, and the idle pile is between the rail robot and the maximum parking space, there are two paths: path A5 = (idle pile position - current docking position) + (idle pile position - target position) and path B5 = (idle pile position - current docking position) + (maximum parking space - idle pile position) + (target position - minimum parking space).

[0011] As a further solution of the present invention, scenario 6: when the distance to the target position is less than the distance to the parking position, and the free pile is between the target position and the minimum parking space, there are two paths: path A6 = (current parking position - free pile position) + (target position - free pile position) and path B6 = (maximum parking space - current parking position) + (free pile position - minimum parking space) + (target position - free pile position).

[0012] As a further solution of the present invention, it is first determined that the target position is ≥ the current docking position, then the length of path A1 and the length of path B1 corresponding to the nth idle pile in scene 1, the length of path A2 and the length of path B2 corresponding to the nth idle pile in scene 2, and the length of path A3 and the length of path B3 corresponding to the nth idle pile in scene 3 are calculated respectively; if it is determined that the target position is < the current docking position, the length of path A4 and the length of path B4 corresponding to the nth idle pile in scene 4, the length of path A5 and the length of path B5 corresponding to the nth idle pile in scene 5, and the length of path A6 and the length of path B6 corresponding to the nth idle pile in scene 6 are calculated respectively.

[0013] As a further solution of the present invention, after all valid paths are calculated and summarized, an optimal path is locked, and scheduling parameters are sent to the rail robot, the parameters are the idle pile position and the target position, and the rail robot executes according to the instructions and sends the results to the scheduling system.

[0014] The present invention has the following beneficial effects: The present invention proposes an intelligent scheduling control technology and implementation method, which improves the operating efficiency and charging order of charging stations by optimizing the robot's running path and scheduling strategy. Specifically, high efficiency, through intelligent scheduling, significantly improves the operating efficiency of charging stations and reduces charging waiting time. Flexibility, can adapt to different charging scenarios and needs, and provide flexible scheduling strategies. Intelligent decision-making, using advanced algorithms and decision support systems to achieve the selection of the optimal path and the issuance of scheduling instructions. Automation, no human intervention is required, to achieve automated robot scheduling and control.

[0015] In order to more clearly illustrate the structural features and effects of the present invention, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1-Figure 6 Schematic diagram of different application scenarios mentioned in the present invention.

[0017] Figure 7 This is a schematic diagram of the intelligent scheduling control method of the rail-type robot for orderly charging of new energy vehicles mentioned in the present invention. DETAILED DESCRIPTION

[0018] The present invention will be further explained below in conjunction with the accompanying drawings and related knowledge, and described clearly and completely. Obviously, the described application is only a part of the embodiments of the present invention, rather than all the embodiments.

[0019] The intelligent scheduling control method of the rail-type robot for orderly charging of new energy vehicles of the present invention solves the problem that the robot scheduling system in the prior art mostly adopts fixed paths or simple algorithms, lacks flexibility and intelligent decision-making ability, and cannot effectively respond to complex and changeable charging needs.

[0020] Reference Figure 1-Figure 7 As shown, the present invention provides an intelligent scheduling control method for a rail-type robot for orderly charging of new energy vehicles, comprising the following steps: Step S1: providing a circular charging track, on which a rail-type robot is arranged; providing the circular charging track allows the rail-type robot to move in a circular manner and reach parking spaces at various locations for charging services. Compared with straight tracks and other forms, it has a wider coverage and more flexible scheduling.

[0021] Step S2: Provide two rows of parking spaces, one row of which is numbered from the smallest parking space to the smallest parking space + m, and the other row of which is numbered from the largest parking space to the largest parking space - n, where m and n are natural numbers greater than 1; provide two rows of parking spaces and number them, so that the system can accurately locate and manage the parking spaces. The numbering can quickly determine the location of the vehicle, facilitate matching with the robot and charging pile, and improve the accuracy and efficiency of scheduling.

[0022] Step S3: Set the position of the rail robot as the current docking position of the robot, set the idle pile position, and the target position, where the target position is the current idle charging position, and the idle pile position is the location of the charging pile that can be used for charging; set the current docking position, idle pile position, and target position of the robot to provide basic data for intelligent scheduling. After the system has clarified these position information, it can perform subsequent path planning and scheduling operations to ensure that the robot can accurately find the idle pile and send it to the target position.

[0023] Step S4: The idle pile is transmitted to the target position through the optimal path through the intelligent scheduling system, the scene recognition module, and the path planning algorithm. Further preferably, the intelligent scheduling system is used to monitor the status of the charging station in real time, including the current position of the rail robot, the number and position of the idle piles, and the position of the vehicle to be charged; the scene recognition module intelligently identifies different charging scenes according to the current docking position, target position, and position of the idle piles of the robot; the path planning algorithm designs different path planning algorithms for the charging scheduling scene of the ring track, and calculates the optimal path to minimize the robot's moving distance and time. The present invention provides an efficient, flexible, and intelligent robot scheduling solution for new energy vehicle charging stations, which has broad application prospects and market potential. The intelligent scheduling system of the present invention: can monitor the status of the charging station in real time, like a "brain", and fully grasp various information in the station in order to make reasonable scheduling decisions. For example, when a large number of vehicles enter the charging station at the same time, the charging sequence and the robot's tasks can be reasonably arranged according to the distribution of robots and idle piles. Scene recognition module: It can intelligently identify different charging scenarios, such as multiple vehicles needing to charge at the same time, the robot is far away from the idle pile, etc., thereby providing a more accurate basis for path planning and making scheduling more targeted. Path planning algorithm: Designing the optimal path based on the characteristics of the ring track can reduce the robot's moving distance and time, improve charging efficiency, reduce energy consumption, and improve the operating efficiency and service quality of the entire charging system.

[0024] Reference Figure 1 As shown, scenario 1: when the distance to the target position ≥ the distance to the parking position, and the idle pile is between the rail robot and the target position, there are two paths: path A1 = (idle pile position - current parking position) + (target position - idle pile position) and path B1 = (idle pile position - current parking position) + (idle pile position - minimum parking space) + (maximum parking space - target position).

[0025] Reference Figure 2 As shown, scenario 2: when the distance to the target position is greater than the distance to the docking position, and the idle pile is between the rail robot and the minimum parking space, there are two paths: path A2 = (current docking position - idle pile position) + (target position - idle pile position) and path B2 = (current docking position - idle pile position) + (idle pile position - minimum parking space) + (maximum parking space - target position).

[0026] Reference Figure 3As shown, scenario 3: when the distance to the target position ≥ the distance to the parking position, and the free pile is between the target position and the maximum parking space, there are two paths: path A3 = (free pile position - current parking position) + (free pile position - target position) and path B3 = (current parking position - minimum parking space) + (maximum parking space - free pile position) + (free pile position - target position).

[0027] Reference Figure 4 As shown, scenario 4: when the distance to the target position is less than the distance to the docking position, and the idle pile is between the rail robot and the target position, there are two paths: path A4 = (current docking position - idle pile position) + (idle pile position - target position) and path B4 = (current docking position - idle pile position) + (maximum parking space - current docking position) + (target position - minimum parking space).

[0028] Reference Figure 5 As shown, scenario 5: when the distance to the target position is less than the distance to the parking position, and the idle pile is between the rail robot and the maximum parking space, there are two paths: path A5 = (idle pile position - current parking position) + (idle pile position - target position) and path B5 = (idle pile position - current parking position) + (maximum parking space - idle pile position) + (target position - minimum parking space).

[0029] Reference Figure 6 As shown, scenario 6: when the distance to the target position is less than the distance to the parking position, and the free pile is between the target position and the minimum parking space, there are two paths: path A6 = (current parking position - free pile position) + (target position - free pile position) and path B6 = (maximum parking space - current parking position) + (free pile position - minimum parking space) + (target position - free pile position).

[0030] In the present invention, the numbers in the paths A1 to A6 and the paths B1 to B6 in the scene are only for the convenience of description and there is no other specific difference. Figure 1-Figure 6 Path A and Path B are used in both.

[0031] Reference Figure 7 As shown, the specific working process of the present invention is: through calculation, all valid paths are summarized to lock an optimal path, and the scheduling parameters are sent to the rail robot, the parameters are the idle pile position and the target position, and the rail robot executes according to the instructions and sends the results to the scheduling system.

[0032] The intelligent scheduling system of the present invention monitors the status of the charging station in real time, including the current position of the robot, the number and position of the idle piles, the position of the vehicle to be charged, etc.; the scene recognition module intelligently identifies different charging scenes (scenes 1 to 6) according to the current docking position, target position and position of the idle piles of the robot; the path planning algorithm (O-type track) designs different path planning algorithms for the six charging scheduling scenarios of the ring track and calculates the optimal path to minimize the robot's moving distance and time.

[0033] That is to say, the intelligent dispatching system of the present invention monitors the status of the charging station in real time and provides data support for the overall dispatching. The scene recognition module identifies 6 different charging scenarios based on the robot's current docking position, target position and idle pile position. The path planning algorithm calculates the optimal path for these 6 scenarios, and finally sends the dispatching parameters such as the idle pile position and target position to the rail-type robot. After the robot performs the task, it feeds back the results to the dispatching system.

[0034] The technical principle of the present invention is described above in combination with the specific embodiments, which are only preferred implementations of the present invention. The protection scope of the present invention is not limited to the above embodiments, and all technical solutions under the idea of ​​the present invention belong to the protection scope of the present invention. Those skilled in the art can think of other specific implementations of the present invention without creative work, and these methods will fall within the protection scope of the present invention.

Claims

1. An intelligent dispatching and control method for a rail-type robot for orderly charging of new energy vehicles, characterized in that: The following steps are involved: Step S1: providing a ring-shaped charging track, on which a rail-type robot is arranged; Step S2: providing two rows of parking spaces, wherein one row of parking spaces is numbered from the smallest parking space to the smallest parking space+m, and the other row of parking spaces is numbered from the largest parking space to the largest parking space-n, wherein m and n are natural numbers greater than 1; Step S3: setting the position of the rail-type robot as the current docking position of the robot, and setting the idle pile position and the target position, wherein the target position is the current idle charging position, and the idle pile position is the position of the charging pile that can be used for charging; Step S4: The idle piles are transported to the target location via the optimal path through the intelligent scheduling system, scene recognition module, and path planning algorithm.

2. The intelligent dispatching control method of the rail-type robot for orderly charging of new energy vehicles as claimed in claim 1 is characterized in that: The intelligent dispatching system is used to monitor the status of the charging station in real time, including the current position of the rail-mounted robot, the number and position of the idle piles, and the position of the vehicle to be charged; the scene recognition module intelligently identifies different charging scenes according to the current docking position of the robot, the target position, and the position of the idle piles; Path planning algorithm, for the charging scheduling scenario of the ring track, different path planning algorithms are designed to calculate the optimal path to minimize the robot's moving distance and time.

3. The intelligent dispatching control method of the rail-type robot for orderly charging of new energy vehicles as claimed in claim 2 is characterized in that: Scenario 1: When the distance to the target position is ≥ the distance to the parking position, and the idle pile is between the rail robot and the target position, there are two paths: path A1 = (idle pile position - current parking position) + (target position - idle pile position) and path B1 = (idle pile position - current parking position) + (idle pile position - minimum parking space) + (maximum parking space - target position).

4. The intelligent dispatching control method of the rail-type robot for orderly charging of new energy vehicles as claimed in claim 3 is characterized in that: Scenario 2: When the distance to the target position is greater than the distance to the docking position, and the idle pile is between the rail robot and the minimum parking space, there are two paths: path A2 = (current docking position - idle pile position) + (target position - idle pile position) and path B2 = (current docking position - idle pile position) + (idle pile position - minimum parking space) + (maximum parking space - target position).

5. The intelligent dispatching control method of the rail-type robot for orderly charging of new energy vehicles as claimed in claim 4 is characterized in that: Scenario 3: When the distance to the target position ≥ the distance to the parking position, and the free pile is between the target position and the maximum parking space, there are two paths: Path A3 = (free pile position - current parking position) + (free pile position - target position) and Path B3 = (current parking position - minimum parking space) + (maximum parking space - free pile position) + (free pile position - target position).

6. The intelligent dispatching control method of the rail-type robot for orderly charging of new energy vehicles as claimed in claim 5 is characterized in that: Scenario 4: When the distance to the target position is less than the distance to the docking position, and the idle pile is between the rail robot and the target position, there are two paths: path A4 = (current docking position - idle pile position) + (idle pile position - target position) and path B4 = (current docking position - idle pile position) + (maximum parking space - current docking position) + (target position - minimum parking space).

7. The intelligent dispatching control method of the rail-type robot for orderly charging of new energy vehicles as claimed in claim 6 is characterized in that: Scenario 5: When the distance to the target position is less than the distance to the parking position, and the idle pile is between the rail robot and the maximum parking space, there are two paths: path A5 = (idle pile position - current parking position) + (idle pile position - target position) and path B5 = (idle pile position - current parking position) + (maximum parking space - idle pile position) + (target position - minimum parking space).

8. The intelligent dispatching control method of the rail-type robot for orderly charging of new energy vehicles as claimed in claim 7 is characterized in that: Scenario 6: When the distance to the target position is less than the distance to the parking position, and the free pile is between the target position and the minimum parking space, there are two paths: path A6 = (current parking position - free pile position) + (target position - free pile position) and path B6 = (maximum parking space - current parking position) + (free pile position - minimum parking space) + (target position - free pile position).

9. The intelligent dispatching control method of the rail-type robot for orderly charging of new energy vehicles as claimed in claim 8 is characterized in that: First, it is determined that the target position is ≥ the current docking position, and then the length of path A1 and path B1 corresponding to the nth idle pile in scene 1, the length of path A2 and path B2 corresponding to the nth idle pile in scene 2, and the length of path A3 and path B3 corresponding to the nth idle pile in scene 3 are calculated respectively; if it is determined that the target position is < the current docking position, the length of path A4 and path B4 corresponding to the nth idle pile in scene 4, the length of path A5 and path B5 corresponding to the nth idle pile in scene 5, and the length of path A6 and path B6 corresponding to the nth idle pile in scene 6 are calculated respectively.

10. The intelligent dispatching control method of the rail-type robot for orderly charging of new energy vehicles as claimed in claim 9 is characterized in that: After the calculation is completed, all valid paths are summarized and locked into an optimal path. The scheduling parameters are sent to the rail robot, which are the idle pile position and the target position. The rail robot executes according to the instructions and sends the results to the scheduling system.

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