Multi-vehicle cooperative charging management system suitable for underground parking lot

Abstract

The invention relates to the technical field of new energy vehicle charging equipment, and discloses a multi-vehicle cooperative charging management system suitable for an underground parking lot, and the system comprises a plurality of adaptive mechanical arms which are disposed on a movable guide rail, each adaptive mechanical arm is provided with a monocular camera positioning module, and the adaptive mechanical arms carry out the visual recognition of a charging port of a target electric vehicle, the charging port type and the three-dimensional space position are automatically identified; the power grid load monitoring module monitors and collects electric vehicle charging data in real time; the scheduling algorithm module receives a user charging request, analyzes the current electric quantity and the charging time of the vehicle according to the charging data, determines the specific charging priority and sequence of a plurality of to-be-charged vehicles, and calls the automatic charging device meeting the condition; the movable guide rail drives the mechanical arm to move and guides the mechanical arm to move according to the position of the charging port, so that the charging plug moves to a target position; through the synergistic effect of the self-adaptive mechanical arm and the self-adaptive moving guide rail, efficient, accurate and automatic charging management of multiple vehicles is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy vehicle charging equipment, and more particularly to a multi-vehicle collaborative charging management system suitable for underground parking lots. Background Art

[0002] The market share of new energy vehicles (NEVs) is increasing year by year, and their operation relies on charging stations. However, current charging stations on the market require user operation, which is not only cumbersome but also extremely inconvenient when used in underground parking lots. This not only reduces the user experience but also poses certain safety risks. Surveys show that only 1%-8% of all parking spaces in parking lots are equipped with charging stations. The difficulty of parking and even greater difficulty of charging have become a major problem in the use of NEVs. In addition, existing charging stations can only charge one NEV at a time, making it impossible to charge multiple vehicles in a coordinated manner.

[0003] In view of this, realizing automatic charging of new energy electric vehicles through corresponding devices will bring a more humane experience to users, further eliminate safety hazards, and effectively solve the problem of charging multiple vehicles in underground parking lots.

[0004] However, existing charging systems for new energy electric vehicles are mostly fixed, which have certain limitations. For example, in underground parking lots, it is impossible to charge multiple new energy electric vehicles simultaneously, and users are required to wait at charging stations, which is labor-intensive and takes up space in underground parking lots. Furthermore, existing charging systems use a single robotic arm, which limits charging efficiency and lacks the ability to dynamically respond to grid loads. Summary of the Invention

[0005] The purpose of the present invention is to provide a multi-vehicle collaborative charging management system suitable for underground parking lots, which realizes efficient and accurate automatic charging management of multiple vehicles through the synergy of visual positioning of adaptive robotic arms and adaptive mobile guide rails.

[0006] To achieve the above object, the present invention provides the following technical solutions: A multi-vehicle collaborative charging management system suitable for underground parking lots, comprising: Adaptive robotic arms, including a plurality of adaptive robotic arms, each of which is mounted on a movable guide rail, and each of which is equipped with a visual recognition device; wherein the visual recognition device is configured to visually recognize the charging port of the target electric vehicle, automatically identify the type of the charging port using a built-in Canny edge detection algorithm, and determine the three-dimensional spatial position of the charging port; The grid load monitoring module is used to monitor and collect charging data of target electric vehicles in real time; The scheduling algorithm module is used to receive the charging requests of users, analyze the current battery power of the target electric vehicle and the time required for charging based on the collected charging data, select the specific charging priorities and sequences of multiple electric vehicles to be charged, and dispatch eligible adaptive robotic arms to perform the charging tasks; The movable guide rail is installed on the ceiling of the parking lot and is used to provide moving tracks for multiple adaptive robotic arms in the underground parking lot; The scheduling algorithm module directly guides the movement of the adaptive robotic arm through the information of the three-dimensional spatial position output by the monocular camera positioning module, so that the charging plug at the end of the adaptive robotic arm accurately moves to the target position and completes the plugging and unplugging operations according to the preset program.

[0007] Furthermore, a monocular camera and a monocular camera positioning module are mounted on the visual recognition device: The monocular camera is used for visual recognition of the charging port of the target electric vehicle; The monocular camera positioning module automatically identifies the type of the charging port and determines the three-dimensional spatial position of the charging port through the built-in Canny edge detection algorithm.

[0008] Furthermore, the adaptive robotic arm is also provided with: The charging plug accurately moves and inserts into the charging port by using the three-dimensional spatial position of the charging port identified by the monocular camera positioning module; The charging unit is connected to the charging plug. After the charging plug is inserted into the charging port, electric energy is connected to charge the target electric vehicle.

[0009] Furthermore, the grid load monitoring module includes: The charging regulation unit is used to intelligently regulate the high-power charging mode or low-power charging mode of the electric vehicle according to the charging demand of the target electric vehicle and the grid load situation; The safety protection unit is used to monitor and collect the charging data during the charging process of the target electric vehicle in real time; when the charging data is abnormal, it automatically disconnects the charging unit and controls the charging plug to disconnect from the charging port of the target electric vehicle.

[0010] Furthermore, the charging data includes: voltage, current and power factor data.

[0011] Furthermore, the scheduling algorithm module includes: The control unit is used to receive the order information of the user-side APP, generate corresponding charging tasks, and feedback them to the user-side APP; A scheduling unit is used to analyze the current battery power and the charging time required for the target electric vehicle based on the collected charging data, select the specific charging priorities and sequences of multiple vehicles to be charged, and retrieve an adaptive robotic arm that meets the conditions to perform the charging task.

[0012] Further, the charging task includes: the charging vehicle type, charging time, charging waiting time, charging parameters, and assigns the charging task to an adaptive robotic arm that meets the conditions.

[0013] Further, the charging plug at the end of the adaptive robotic arm is a replaceable charging plug.

[0014] Further, the adaptive robotic arm has a telescopic function, moves to the position of the electric vehicle to be charged on the ceiling using a movable guide rail, then extends the adaptive robotic arm, and completes the charging by identifying with a monocular camera; After the charging is completed, shorten the adaptive robotic arm, and then move the adaptive robotic arm to the position of the next electric vehicle that needs to be charged through the movable guide rail.

[0015] According to the specific embodiments provided by the present invention, the following technical effects are disclosed by the present invention: This application uses a monocular camera to identify the position of the charging port of a new energy electric vehicle and controls the adaptive robotic arm to drive the charging plug to move, insert the charging plug into the charging port of the new energy vehicle, and charge the new energy vehicle; the power grid load monitoring module monitors the electrical energy parameters such as current and voltage during the charging of the new energy vehicle in real time, adjusts the charging power according to the power grid load and the electrical energy parameters during the charging process, and forcibly disconnects the charging when the charging parameters during the charging process show obvious abnormalities to ensure the safety during the charging process of the new energy electric vehicle; there is a control unit and a scheduling unit in the scheduling algorithm module; through the control unit, information interaction can be carried out with the user-side APP, a charging task is generated, and the information of the completed charging is fed back to the user-side APP after the charging is completed; through the scheduling unit, according to the charging task generated by the control unit, among the multiple adaptive robotic arms in the intelligent new energy vehicle automatic charging device, an automatic charging device that meets the conditions is retrieved to perform the charging task. When receiving the charging task, the movable guide rail drives the robotic arm to the charging location and goes to the next charging location after the charging task is completed. Description of the Drawings

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only the embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained according to the provided drawings without creative efforts.

[0017] The multi-vehicle collaborative charging management system applicable to underground parking lots of the present invention will be further described below in conjunction with the accompanying drawings; Figure 1 It is a schematic diagram of the overall module of the underground parking lot in the multi-vehicle collaborative charging management system of the present invention; Figure 2 It is a schematic diagram of the structure of the adaptive robotic arm disposed on the movable guide rail in the multi-vehicle collaborative charging management system of the present invention.

[0018] Description of the drawings: 1. Movable guide rail; 2. Sliding device; 3. Adaptive robotic arm; 4. Telescopic device; 5. User mobile terminal; 6. Control unit. Specific embodiments

[0019] The specific embodiments of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following embodiments are used to illustrate the present invention, but are not used to limit the scope of the present invention.

[0020] In order to better understand the purpose, structure and function of the present invention, the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0021] As Figure 1 and Figure 2 shown, the present invention provides a multi-vehicle collaborative charging management system applicable to underground parking lots, including: There are multiple adaptive robotic arms 3, and each adaptive robotic arm 3 is disposed on the movable guide rail 1. Each adaptive robotic arm 3 is configured with a monocular camera positioning module; wherein the monocular camera positioning module is used for visual recognition of the charging port of the target electric vehicle, automatically identifying the type of the charging port through the built-in Canny edge detection algorithm, and determining the three-dimensional spatial position of the charging port; The grid load monitoring module is used for real-time monitoring and collecting the charging data of the target electric vehicle; The scheduling algorithm module is used for receiving the charging request of the user, analyzing the current battery power and the charging time required of the target electric vehicle according to the collected charging data, selecting the specific charging priorities and sequences of multiple electric vehicles to be charged, and calling the eligible adaptive robotic arms 3 to execute the charging tasks; wherein the priority is calculated through a multi-factor weighted scoring model (with a full score of 100 points), and the charging sequence of the charging vehicles is selected according to the priority.

[0022] The movable guide rail 1 is disposed on the ceiling of the parking lot and is used for providing a moving track for multiple adaptive robotic arms 3 in the underground parking lot; The information on the three-dimensional spatial position output by the monocular camera positioning module directly guides the movement of the adaptive robotic arm 3, enabling the charging plug at the end of the adaptive robotic arm 3 to accurately move to the target position and complete the plugging and unplugging operations according to the preset program.

[0023] The movable guide rail 1 is installed on the ceiling of the parking lot and is used to provide moving tracks for multiple adaptive robotic arms in the underground parking lot; The information on the three-dimensional spatial position output by the monocular camera positioning module directly guides the movement of the adaptive robotic arm 3, enabling the charging plug at the end of the adaptive robotic arm 3 to accurately move to the target position and complete the plugging and unplugging operations according to the preset program.

[0024] The adaptive robotic arm 3 includes: A monocular camera for visually identifying the charging port of the target electric vehicle; A monocular camera positioning module that automatically identifies the type of the charging port and determines the three-dimensional spatial position of the charging port through the built-in Canny edge detection algorithm.

[0025] The adaptive robotic arm 3 further includes: A charging plug that accurately moves and inserts into the charging port by using the three-dimensional spatial position of the charging port identified by the monocular camera positioning module; A charging unit is connected to the charging plug of the electric vehicle. When the charging plug is inserted into the charging port, the electric energy is connected to charge the target electric vehicle.

[0026] The power grid load monitoring module includes: A charging regulation unit for intelligently regulating the high-power charging mode or low-power charging mode of the electric vehicle according to the charging demand of the target electric vehicle and the power grid load situation; In this embodiment, intelligently regulating the high-power charging mode or low-power charging mode of the electric vehicle according to the charging demand of the target electric vehicle and the power grid load situation is specifically as follows: When the grid capacity is 500kW, the basic load is 200kW (lighting / air conditioning, etc.), the maximum power of charging vehicle A is 150kW, the required power is 80%→100%, and the priority score P = 85; the maximum power of charging vehicle b is 120kW, the required power is 50%→80%, and the priority score P = 45; the maximum power of charging vehicle A is 100kW, the required power is 30%→90%, and the priority score P = 65.

[0027] Grid load = Base 200kW + A(150kW) + C(40kW) = 390kW (load factor 78% < 85%). A operates at high power, and C starts at low power. When B joins for charging, the total demand power: 200 + A(150kW) + B(120kW) + C(40kW) = 510kW > 500kW → load factor 102%. The control algorithm is triggered: A: P = 150×0.4×(1 - 1.02 / 0.85) = 60kW. B: P = 120×0.4×(1 - 1.02 / 0.85) = 48kW. C: Remains at 40kW. When A finishes charging and exits, the grid load drops to: 200 + 48 + 40 = 288kW (load factor 57.6%) → B resumes high power of 120kW, and C resumes high power of 100kW. The safety protection unit is used to monitor and collect the charging data of the target electric vehicle in real time during the charging process; when the charging data is abnormal, it automatically disconnects the charging unit and controls the charging plug to disconnect from the charging port of the target electric vehicle.

[0028] The charging data includes: voltage, current, and power factor data.

[0029] The scheduling algorithm module includes: The control unit is used to receive the order information from the user-side APP, generate the corresponding charging task, and feedback it to the user-side APP; The scheduling unit 6 is used to analyze the current battery power and the charging time required for the target electric vehicle based on the collected charging data, select the specific charging priorities and sequences of multiple vehicles to be charged, and retrieve the eligible automatic charging devices to execute the charging task.

[0030] The strategy for selecting the specific charging priorities and sequences of multiple vehicles to be charged is specifically as follows: The priority is calculated through a multi-factor weighted scoring model (with a full score of 100 points). The score P = 30%*a + 25%*b + 20%c + 15%d + 10%e; the higher the P, the higher the priority. a is the urgency of the battery level, a = (1 - current battery level / 15%) × 100 (when the battery level is below 15%, the urgency of the battery level increases linearly, and it is 0 points when the battery level is 15%; when the battery level drops to 0%, the urgency of the battery level reaches the maximum value of 100 points). b is the urgency of time, b = (remaining time / charging time) × 25 (triggered when the remaining time < 2 times the charging time). c is the user level, c = (emergency vehicle: 20 / VIP: 15 / ordinary: 10 / low activity: 5), d is the grid load factor, d = (valley electricity period (+10) / flat electricity period (0) / peak electricity period (-5)). e is the charging efficiency, e = (actual charging power / maximum power) × 10 (to avoid inefficient resource occupation). The charging sequence of the charging vehicles is selected according to the priority.

[0031] Specifically in this embodiment, the user parks the new energy electric vehicle in the underground parking lot and turns on the user mobile terminal 5, and inputs the basic information of the vehicle and the location of the vehicle in the user mobile terminal 5. The control unit receives the information in the user mobile terminal 5, feeds back the estimated charging completion time to the user, and generates a charging task. The control unit transmits the charging task to the scheduling unit. The scheduling unit retrieves the eligible adaptive robotic arm 3 according to the charging task to execute the charging task. If all the adaptive robotic arms do not meet the conditions, the scheduling unit will retain the charging task until there is an eligible adaptive robotic arm 3.

[0032] According to the parking position of the new energy electric vehicle, the charging task is assigned to the eligible adaptive robotic arm 3, and it is determined by the monocular camera that the adaptive robotic arm 3 has reached the new energy vehicle that meets the vehicle type information, and then stops moving.

[0033] After the monocular camera identifies the charging port of the new energy vehicle, it controls the charging plug on the adaptive robotic arm 3 to insert into the charging port of the new energy vehicle. The charging plug on the robotic arm is connected to a charging unit, which can charge the new energy vehicle after being inserted into the charging port of the new energy vehicle. The grid load monitoring module monitors the electrical energy parameters during the charging process, judges whether the new energy electric vehicle has completed charging through the charging parameters, and feeds back to the user mobile terminal 5 through the control unit.

[0034] After the charging is completed, the charging plug on the adaptive robotic arm 3 disconnects from the charging port, and the adaptive robotic arm 3 retracts to the ceiling of the underground parking lot. The control unit feeds back the information of charging completion to the user mobile terminal 5. The movable guide rail 1 moves the robotic arm to the next parking position when receiving the next charging task.

[0035] The charging task includes: charging vehicle type, charging time, charging waiting time, charging parameters, and the charging task is assigned to the eligible adaptive robotic arm 3, and the charging information is fed back to the user mobile terminal.

[0036] In this embodiment, the strategy of assigning the charging task to the eligible adaptive robotic arm 3 is illustrated by the following examples: For example, a certain charging station is equipped with two adaptive charging devices, robotic arm A (in area 2-04) and robotic arm B (in area 4-11), and there are vehicle 1 (current battery level 15%, target battery level 90%, battery capacity 75 kWh, maximum power 150 kW, in area 3-07) and vehicle 2 (current battery level 50%, target battery level 80%, battery capacity 60 kWh, maximum power 50 kW, in area 1-12).

[0037] Charging time of vehicle 1: (0.9 - 0.15) × 75 / 150 = 37.5 minutes → actually 40 minutes (including the positioning time of the monocular camera); Charging time of vehicle 2: (0.8 - 0.5) × 60 / 50 = 21.6 minutes → actually 24 minutes (including the positioning time of the monocular camera); The time required for robotic arm A to reach vehicle 1 is 8 minutes, and the time required for robotic arm A to reach vehicle 2 is 4 minutes. The time required for robotic arm B to reach vehicle 1 is 10 minutes, and the time required for robotic arm B to reach vehicle 2 is 7 minutes. Therefore, let robotic arm A go to area 3 - 07 to charge vehicle 1, and the total time is 48 minutes. Let robotic arm B go to area 1 - 12 to charge vehicle 2, and the total time is 31 minutes. (The priority score P of vehicle 1 is higher, and the robotic arm with the least time to reach vehicle 1 is preferentially selected).

[0038] The charging plug at the end of the adaptive robotic arm ́3 is a replaceable charging plug.

[0039] In this embodiment, the new - energy vehicle charging plug at the end of the adaptive robotic arm 3 can replace the charging gun head, supports the national standard fast - charging (GB / T 20234) and European standard (IEC 62196) protocols, and is adapted to more than 20 mainstream vehicle models.

[0040] The movable guide rail 1 is connected to the adaptive robotic arm 3. The movement of the movable guide rail 1 is controlled according to the control unit, and the movement of the adaptive robotic arm 3 is driven by the movement of the movable guide rail 1 to realize the movement of the adaptive robotic arm 3 in the parking lot.

[0041] The movable guide rail 1 can be installed on the ceiling of the underground parking lot. The robotic arm is hung upside - down on the movable guide rail 1, and the movement of the robotic arm is driven by the movable guide rail 1.

[0042] The adaptive robotic arm 3 has a telescopic function. The sliding device 2 on the movable guide rail 1 drives the adaptive robotic arm 3 to move on the ceiling to the position of the new - energy electric vehicle to be charged. Then, the telescopic device 4 is used to extend the adaptive robotic arm 3, and charging is completed through monocular camera recognition. After charging, the adaptive robotic arm is shortened using the telescopic function, and then the adaptive robotic arm 3 is moved to the position of the next new - energy vehicle to be charged through the guide rail.

[0043] As Figure 2 shown, after the scheduling unit assigns the charging task to the automatic charging device, the movable guide rail hanging on the ceiling of the underground parking lot starts to move, and drives the adaptive robotic arm 3 connected to the movable guide rail 1 to move to the position of the vehicle.

[0044] Subsequently, the adaptive robotic arm 3 starts to extend and the monocular camera connected to the adaptive robotic arm 3 starts to identify the charging port of the new energy vehicle.

[0045] The foregoing description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A multi-vehicle collaborative charging management system applicable to underground parking lots, characterized in that, Including: There are multiple adaptive robotic arms, and each adaptive robotic arm is installed on a movable guide rail. Each adaptive robotic arm is equipped with a visual recognition device; The visual recognition device is used to perform visual recognition on the charging port of the target electric vehicle, automatically identify the type of the charging port through the built-in Canny edge detection algorithm, and determine the three-dimensional spatial position of the charging port; The grid load monitoring module is used to monitor and collect the charging data of the target electric vehicle in real time; The scheduling algorithm module is used to receive the charging request of the user, analyze the current battery power and the charging time required of the target electric vehicle according to the collected charging data, select the specific charging priorities and sequences of multiple electric vehicles to be charged, and dispatch the eligible adaptive robotic arms to perform the charging task; The movable guide rail is installed on the ceiling of the parking lot and is used to provide a moving track for multiple adaptive robotic arms in the underground parking lot; The scheduling algorithm module directly guides the movement of the adaptive robotic arm through the information of the three-dimensional spatial position output by the monocular camera positioning module, so that the charging plug at the end of the adaptive robotic arm accurately moves to the target position and completes the plugging and unplugging operations according to the preset program.

2. The multi-vehicle collaborative charging management system applicable to an underground parking lot according to claim 1, wherein The visual recognition device is equipped with a monocular camera and a monocular camera positioning module: The monocular camera is used to perform visual recognition on the charging port of the target electric vehicle; The monocular camera positioning module automatically identifies the type of the charging port and determines the three-dimensional spatial position of the charging port through the built-in Canny edge detection algorithm.

3. The multi-vehicle collaborative charging management system applicable to an underground parking lot according to claim 1, characterized in that, The adaptive robotic arm is further provided with: A charging plug, which accurately moves and inserts into the charging port by using the three-dimensional spatial position of the charging port identified by the monocular camera positioning module; A charging unit, which is connected to the charging plug. When the charging plug is inserted into the charging port, electric energy is connected to charge the target electric vehicle.

4. The multi-vehicle collaborative charging management system applicable to an underground parking lot according to claim 3, wherein, The grid load monitoring module includes: A charging regulation unit, which is used to intelligently regulate the high-power charging mode or low-power charging mode of the electric vehicle according to the charging demand of the target electric vehicle and the grid load situation; A safety protection unit, which is used to monitor and collect the charging data during the charging process of the target electric vehicle in real time; when the charging data is abnormal, it automatically disconnects the charging unit and controls the charging plug to disconnect from the charging port of the target electric vehicle.

5. The multi-vehicle collaborative charging management system applicable to an underground parking lot according to claim 1, wherein The charging data includes: voltage, current and power factor data.

6. The multi-vehicle collaborative charging management system applicable to an underground parking lot according to claim 1, characterized in that The scheduling algorithm module includes: A control unit, which is used to receive the order information of the user-side APP, generate a corresponding charging task, and feedback it to the user-side APP; A scheduling unit, which is used to analyze the current battery power and the charging time required of the target electric vehicle according to the collected charging data, select the specific charging priorities and sequences of multiple vehicles to be charged, and dispatch the eligible adaptive robotic arms to perform the charging task.

7. The multi-vehicle collaborative charging management system applicable to an underground parking lot according to claim 6, characterized in that, The charging task includes: charging vehicle type, charging time, charging waiting time, charging parameters, and assigns the charging task to the eligible adaptive robotic arms.

8. The multi-vehicle collaborative charging management system applicable to an underground parking lot according to claim 1, characterized in that The charging plug at the end of the adaptive robotic arm is a replaceable charging plug.

9. The multi-vehicle collaborative charging management system applicable to an underground parking lot according to claim 1, characterized in that, The described adaptive robotic arm has a telescopic function. It uses a movable guide rail to move on the ceiling to the position of the electric vehicle to be charged, then extends the adaptive robotic arm, and completes the charging through monocular camera recognition. After the charging is completed, the adaptive robotic arm is shortened, and then the adaptive robotic arm is moved to the position of the next electric vehicle to be charged through the movable guide rail.

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