Unmanned automatic control system

Abstract

This invention provides an unmanned automatic control system, comprising: a sensor system, a PLC control system, a host computer control system, an onboard environmental perception system, and an energy optimization control system. The sensor system primarily collects and filters system status data. The PLC system, as the main control unit, receives information from the central control system, processes instructions, and controls the vehicle. The host computer system primarily processes positioning information and determines safety strategies. The perception system analyzes the video and point cloud data received from the sensor system to identify potential risks during vehicle operation. The energy optimization system primarily manages energy consumption, rationally allocating energy based on the vehicle's operating status to conserve energy.

Description

Technical Field

[0001] This invention relates to the technical field of self-driving unmanned torpedo tanker systems, specifically to unmanned automatic control systems. Background Technology

[0002] Torpedo ladle cars are widely used in the transportation of molten iron between steel mills. The utilization efficiency and transportation method of torpedo ladle cars have an important impact on the temperature drop of molten iron during transportation and the energy consumption and product quality of steel production.

[0003] The torpedo ladle car, also known as a torpedo-type molten iron mixing car, is a large-scale molten iron transport device. It boasts advantages such as low heat loss, long heat retention time, and energy savings. It can also store molten iron to balance temporary imbalances between ironmaking and steelmaking processes. Furthermore, it can replace the mixing furnace and ordinary molten iron ladle cars in steelmaking, and can perform desulfurization and dephosphorization operations during molten iron transport. In addition to the ladle body, the torpedo ladle car has a tipping mechanism, typically driven by a hydraulic system or a motor-driven reducer. It also includes the car body as the transport carrier and a covering mechanism. For long transport distances, an auxiliary heating system is added. In the production process, the use of torpedo ladle cars simplifies the steelmaking process, reduces heat loss, and saves on per-trip transport costs due to its large storage capacity.

[0004] Patent document CN110058585A discloses an automatic driving control system for an unmanned vehicle. Specifically, the control system for the unmanned vehicle includes a first processing unit configured to run a primary automatic driving process for controlling the unmanned vehicle. The control system also includes a programmable logic array operatively communicating with the first processing unit. The control system further includes a state machine configured in the programmable logic array. The state machine is configured to allow control of the unmanned vehicle according to a backup automatic driving process in response to an invalid output from the first processing unit.

[0005] Regarding the aforementioned technologies, the inventors believe that there are problems with the low turnover rate of torpedo tank cars due to insufficient locomotive capacity and the low turnover rate of torpedo tanks due to limitations in the number of locomotives. Therefore, a technical solution is needed to improve these technical problems. Summary of the Invention

[0006] In view of the deficiencies in the prior art, the purpose of this invention is to provide an unmanned automatic control system.

[0007] An unmanned automatic control system according to the present invention includes a sensor system, a PLC control system, a host computer control system, an on-board environmental perception system, and an energy optimization control system; the sensor system is connected to the PLC control system, the host computer control system, and the on-board environmental perception system respectively; the PLC control system and the host computer control system are connected.

[0008] The sensor system collects the vehicle's actual location through a positioning device and collects the vehicle's operating status information through an electronic control system.

[0009] The PLC control system receives some high-speed sensor information, filters and verifies the sensor information, and sends the preprocessed sensor data to the host computer control system. The PLC control system converts the control rate into a control quantity that the motor and its drive system can recognize according to the control command, and issues the corresponding control quantity.

[0010] The host computer control system receives the status of some sensors, and communicates with the PLC control system in real time. Using the current vehicle sensor system data as the initial state, it performs vehicle sensor information fusion, vehicle positioning, and driving strategy control calculation and implementation.

[0011] The vehicle environment perception system receives signals from vehicle perception sensors, designs environment perception algorithms, and sends the perception results to the vehicle central control unit to provide vehicle environment perception-related information.

[0012] The energy optimization control system combines the characteristics of the vehicle's transmission system, the power supply and on-board control rate of the vehicle's energy system, and the characteristics of the vehicle's process requirements. By correcting the control rate, it saves system energy consumption.

[0013] Preferably, the positioning device includes a Gray bus, RFID, and satellite positioning.

[0014] Preferably, the vehicle operating status information includes vehicle speed, master and slave wheel side speeds, and the battery control system.

[0015] Preferably, the sensor system includes a positioning sensor and an environmental sensing sensor;

[0016] The positioning sensor employs a method of mutual verification among multiple positioning sensors.

[0017] The environmental perception sensor uses image acquisition equipment and point cloud acquisition equipment to collect real-time information about the vehicle's surroundings and transmits the relevant information to the perception processing system for related operations.

[0018] Preferably, the central control system includes a sensor preprocessing system, a sensor data preliminary fusion system, a central communication system, a vehicle speed control system, and a vehicle speed planning system.

[0019] The sensor preprocessing system receives the data collected by the sensor according to the relevant communication protocol;

[0020] The sensor data preliminary fusion system organically combines sensor signals of the same type of physical quantity detection from different types of sensors through information fusion related methods.

[0021] The central communication system supports communication with various vehicle subsystems;

[0022] The vehicle speed control system receives the operation command from the ground center and adopts a feedback and feedforward control system. Based on the different requirements of vehicle operation status under various working conditions, it uses the target value and feedback sensor as input and the actual control quantity of the system as output to design different control methods.

[0023] The on-board speed planning system designs and plans operating speeds based on actual production process requirements.

[0024] Preferably, the subsystem includes various sensors, a vehicle ground central control system, a sensing system, and a host computer processing system.

[0025] Preferably, the host computer system includes a sensor information fusion system and a high-precision positioning system;

[0026] The sensor information fusion system collects sensor information directly connected to the host computer, receives sensor information from the central control system through communication, and fuses the sensor information based on the signal fusion method to obtain sensor data.

[0027] The high-precision positioning system matches the fused data from the positioning sensor system with high-precision map data to obtain the positioning of SmartTPC on the railway.

[0028] Preferably, the vehicle-mounted environmental perception system collects information from perception sensors to identify whether there are obstacles on the SmartTPC's operating track surface and within its field of vision. After identifying the type and location of the obstacles, the perception system determines the type of emergency measures that the vehicle needs to take based on the vehicle's current operating status and the process instructions being executed by the vehicle. The system then sends the judgment to the central processing unit, which further processes the judgment result to generate an emergency action.

[0029] Preferably, the sensing system includes a visual sensing system and a laser sensing system;

[0030] The visual perception system collects relevant image and video information to judge and identify obstacles within the field of vision;

[0031] The laser sensing system uses point clouds as input to identify obstacle information within the field of view and obtain environmental information.

[0032] Preferably, the energy optimization system combines the vehicle's working characteristics and process requirements under different operating conditions to rationally allocate energy and adopt an energy-saving operation mode during operation.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] 1. This invention relates to a self-driving unmanned torpedo tanker system in the field of autonomous driving. It mainly addresses the problem of low turnover rate of torpedo tankers in factory areas due to insufficient locomotive capacity. The invention designs a self-driving unmanned torpedo tanker to enable the torpedo tanker to move autonomously, thereby solving the problem of low turnover rate of torpedo tankers caused by the limited number of locomotives.

[0035] 2. This invention utilizes a Smart PTC control system to achieve automatic control and operation of the self-driving torpedo tanker, enabling unmanned operation of the torpedo tanker. Attached Figure Description

[0036] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0037] Figure 1 This is a structural diagram of the SmartTPC control system of the present invention. Detailed Implementation

[0038] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0039] This invention mainly involves designing an unmanned intelligent torpedo tank car (SmartTPC) automatic control system to realize the automatic transportation of molten iron by unmanned torpedo tank cars on industrial railways.

[0040] Reference Figure 1 In this implementation, a SmartTPC control system is established, which comprises: a sensor system, a PLC control system, a host computer control system, an on-board environmental perception system, and an energy optimization control system.

[0041] Sensor system: The sensor system collects the vehicle's actual location through positioning devices such as Gray bus, RFID, and satellite positioning; and collects vehicle operating status information, such as vehicle speed, master and slave wheel speeds, and battery control system information, through the electronic control system.

[0042] PLC Control System: The PLC control system receives information from some high-speed sensors, filters and verifies the sensor information using filtering algorithms, and sends the pre-processed sensor data to the host computer control system. Simultaneously, based on control commands, the PLC control system calculates the vehicle control rate in real time using advanced control algorithms, converting the control rate into control quantities recognizable by the motor and its drive system. Based on the corresponding system's communication protocol, it issues the appropriate control quantities. Besides serving as a communication and data acquisition module for the vehicle's automatic control system, the PLC control system is also a control system for high-reality-controlled technological actions in the vehicle; therefore, it is the core control system of the vehicle system.

[0043] Upper computer control system: The upper computer system directly receives the status of some sensors and communicates with the PLC control system in real time. Using the current data of the vehicle sensor system as the initial state, it performs complex calculations and controls such as vehicle sensor information fusion, high-precision vehicle positioning, and driving strategy control.

[0044] Vehicle-mounted environmental perception system: The vehicle-mounted environmental perception system receives signals from vehicle-mounted perception sensors, combines the characteristics of the sensors and perception algorithms, designs environmental perception algorithms, and sends the perception results to the vehicle's central control unit, providing relevant information on vehicle environmental perception for the vehicle's central control unit to use in decision-making.

[0045] Energy optimization control system: Combining the characteristics of the vehicle's transmission system, the power supply and on-board control rate of the vehicle's energy system, and the characteristics of the vehicle's process requirements, the system saves energy consumption by correcting the control rate.

[0046] The sensor system includes positioning sensors and environmental perception sensors. The positioning sensors use a method of cross-verification among multiple positioning sensors to ensure that the vehicle meets the accuracy requirements for actual operation under different working conditions. The environmental perception sensors use image acquisition equipment and point cloud acquisition equipment to collect real-time information about the vehicle's surroundings and transmit the relevant information to the perception processing system for related operations.

[0047] The PLC control system includes a sensor preprocessing system, a sensor data preliminary fusion system, a central communication system, an on-board speed control system, and an on-board speed planning system.

[0048] The sensor preprocessing system receives the data collected by the sensor according to the relevant communication protocol.

[0049] The preliminary sensor data fusion system uses information fusion methods to organically combine sensor signals of the same type of physical quantity from different types of sensors to obtain more accurate data.

[0050] The central communication system is the core system of vehicle automation, and the PLC control system is the central system for vehicle information aggregation. Its communication system supports communication with various vehicle subsystems while ensuring real-time performance and stability. These subsystems mainly include, but are not limited to, various sensors, the vehicle ground PLC control system, the sensing system, and the host computer processing system.

[0051] Onboard speed control system: The onboard speed control system receives operating commands from the ground center and adopts a feedback and feedforward control system. Based on the different requirements of vehicle operation under various working conditions, it uses target values ​​and feedback sensors as inputs and the actual control quantity of the system as output. Different control methods are designed to meet the actual operating speed requirements of SmartTPC. In the driving control process, a dynamic tracking control method is used to control the motor to follow the set speed curve and prevent overshoot during operation. In the precise positioning control process, pulse control and overshoot suppression control methods are used to accurately follow the positioning speed curve. At the same time, a position loop closure is used to ensure the final positioning accuracy of ±50mm.

[0052] Onboard speed planning system: Due to the influence of actual working conditions and road conditions during operation, relevant constraints are imposed on the speed of SmartTPC during actual operation. For example, in special areas such as switches and level crossings, advanced deceleration curves are set to ensure that the speed does not overshoot when the vehicle passes through speed-limited areas such as switches and level crossings. At the same time, under different environmental systems, safety rules and production operation safety requirements will also impose requirements on the operating speed of SmartTPC. Based on these constraints and combined with actual process production needs, the speed planning system designs the operating speed. In response to the efficiency requirements during the operation, a ramp acceleration curve is designed to meet the acceleration characteristics requirements during operation. At the same time, through the design of a stepped deceleration curve, smooth and stable deceleration is ensured during the deceleration process, ensuring the smooth and safe operation of the train.

[0053] The host computer system includes a sensor information fusion system and a high-precision positioning system. The sensor information fusion system collects sensor information directly connected to the host computer, receives sensor information from the PLC control system via communication, and then fuses the sensor information based on signal fusion methods to obtain more accurate sensor data. The high-precision positioning system matches the fused data from the positioning sensor system with high-precision map data to obtain the precise positioning of the SmartTPC on the railway, providing stable and reliable information for subsequent control and other functions.

[0054] The onboard environmental perception system collects information from sensing sensors to identify whether there are obstacles on the SmartTPC's operating track surface and within its field of view. Simultaneously, it detects obstacles, pedestrians, and vehicles that threaten driving safety in real time in complex operating areas such as switches and intersections. After identifying the type and location of obstacles, the perception system determines the type of emergency measure required based on the vehicle's current operating status and the process commands it is executing. This determination is then sent to the central processing unit, which further processes the results and generates emergency actions to ensure driving safety.

[0055] The perception system includes visual perception systems and laser perception systems.

[0056] Visual perception system: The visual system is based on optical components such as cameras and video cameras to collect relevant image and video information. Because the image information has obvious edges and high resolution, it provides more descriptive information for small and irregular obstacles and can better distinguish the boundaries of obstacles. Based on this, a visual perception system is designed to judge and identify obstacles within the field of view.

[0057] Laser Sensing System: The laser sensing system uses point clouds as input to identify obstacle information within the field of view. Since point cloud information can accurately describe the spatial position of the measured object in the system, and reflectivity can classify the properties of the measured object, a laser sensing system is designed based on the characteristics of laser sensors and organically combined with a visual sensing system to obtain more comprehensive environmental information.

[0058] The energy optimization system mainly combines the vehicle's working characteristics and process requirements under different working conditions to rationally allocate energy and adopt energy-saving operation mode during operation to avoid energy waste.

[0059] This invention relates to a self-driving unmanned torpedo tanker system in the field of autonomous driving. It primarily addresses the low turnover rate of torpedo tankers within a factory area due to insufficient locomotive capacity. The invention designs a self-driving unmanned torpedo tanker to achieve autonomous movement, thereby solving the problem of low turnover rate caused by the limited number of locomotives. This invention utilizes a Smart PTC control system to achieve automatic control and operation of the self-driving torpedo tanker, realizing unmanned driving of the torpedo tanker.

[0060] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. An unmanned automatic control system applied to a torpedo tanker, characterized in that, It includes a sensor system, a PLC control system, a host computer control system, an on-board environmental perception system, and an energy optimization control system; the sensor system is connected to the PLC control system, the host computer control system, and the on-board environmental perception system, respectively; the PLC control system and the host computer control system are connected. The sensor system collects the vehicle's actual location through a positioning device; Vehicle operating status information is collected through the electronic control system; The PLC control system receives some high-speed sensor information, filters and verifies the sensor information, and sends the preprocessed sensor data to the host computer control system. The PLC control system converts the control rate into a control quantity that the motor and its drive system can recognize according to the control command, and issues the corresponding control quantity. The host computer control system receives the status of some sensors, and communicates with the PLC control system in real time. Using the current vehicle sensor system data as the initial state, it performs vehicle sensor information fusion, vehicle positioning, and driving strategy control calculation and implementation. The vehicle environment perception system receives signals from vehicle perception sensors, designs environment perception algorithms, and sends the perception results to the vehicle central control unit to provide vehicle environment perception-related information. The energy optimization control system combines the characteristics of the vehicle's transmission system, the power supply and on-board control rate of the vehicle's energy system, and the characteristics of the vehicle's process requirements. By correcting the control rate, it saves system energy consumption. The central control system includes a sensor preprocessing system, a sensor data preliminary fusion system, a central communication system, an on-board speed control system, and an on-board speed planning system. The sensor preprocessing system receives the data collected by the sensor according to the relevant communication protocol; The sensor data preliminary fusion system organically combines sensor signals of the same type of physical quantity detection from different types of sensors through information fusion related methods. The central communication system supports communication with various vehicle subsystems; The vehicle speed control system receives the operation command from the ground center and adopts a feedback and feedforward control system. Based on the different requirements of vehicle operation status under various working conditions, it uses the target value and feedback sensor as input and the actual control quantity of the system as output to design different control methods. The vehicle-mounted speed planning system combines actual process production needs to plan and design operating speeds. The PLC control system includes an onboard speed control system and an onboard speed planning system. The onboard speed control system uses a dynamic tracking control method to control the motor to follow the set speed curve. During the precise positioning control process, pulse control and overshoot suppression control methods are used. Through a closed-loop position loop, the final positioning accuracy is ensured to be ±50mm. The onboard speed planning system uses a pre-deceleration curve setting in the turnout and level crossing areas, and designs a ramp acceleration curve and a stepped deceleration curve.

2. The unmanned automatic control system according to claim 1, characterized in that, The positioning equipment includes Gray busbars, RFID, and satellite positioning.

3. The unmanned automatic control system according to claim 1, characterized in that, The vehicle operating status information includes vehicle speed, master and slave wheel side speeds, and the battery control system.

4. The unmanned automatic control system according to claim 1, characterized in that, The sensor system includes positioning sensors and environmental sensing sensors; The positioning sensor employs a method of mutual verification among multiple positioning sensors. The environmental perception sensor uses image acquisition equipment and point cloud acquisition equipment to collect real-time information about the vehicle's surroundings and transmits the relevant information to the perception processing system for related operations.

5. The unmanned automatic control system according to claim 1, characterized in that, The subsystem includes various sensors, a vehicle ground central control system, a perception system, and a host computer processing system.

6. The unmanned automatic control system according to claim 1, characterized in that, The host computer control system includes a sensor information fusion system and a high-precision positioning system; The sensor information fusion system collects sensor information directly connected to the host computer, receives sensor information from the central control system through communication, and fuses the sensor information based on the signal fusion method to obtain sensor data. The high-precision positioning system matches the fused data from the positioning sensor system with high-precision map data to obtain the location of the torpedo tank car on the railway.

7. The unmanned automatic control system according to claim 1, characterized in that, The vehicle-mounted environmental perception system collects information from perception sensors to identify whether there are obstacles on the torpedo tanker's running track and within its field of vision. After identifying the type and location of the obstacles, the perception system determines the type of emergency measures that the vehicle needs to take based on the vehicle's current operating status and the process instructions being executed. The system then sends the judgment to the central processing unit, which further processes the judgment results to generate emergency actions.

8. The unmanned automatic control system according to claim 1, characterized in that, The sensing system includes a visual sensing system and a laser sensing system; The visual perception system collects relevant image and video information to judge and identify obstacles within the field of vision; The laser sensing system uses point clouds as input to identify obstacle information within the field of view and obtain environmental information.

9. The unmanned automatic control system according to claim 1, characterized in that, The energy optimization system combines the vehicle's working characteristics and process requirements under different operating conditions to rationally allocate energy and adopt an energy-saving operation mode during operation.

Images