Foldable wind power hybrid drive three-body unmanned ship and control method thereof

Abstract

The invention belongs to the technical field of unmanned ships, and discloses a foldable wind power hybrid driven three-body unmanned ship and a control method thereof, the unmanned ship comprises a ship body, a wind energy and light energy system, a driving system, a control system and a self-propulsion system; the ship body comprises an outer ship body, a middle ship body and a connecting bridge structure, the outer ship body and the middle ship body are arranged on the two sides of the connecting bridge structure at intervals, the connecting bridge is of a telescopic and folding structure, and a sliding rail and a folding device are adopted as telescopic and folding devices respectively; the wind energy and light energy system realizes multi-source power generation by fusing solar energy and wind energy; the driving system comprises a main propeller and an auxiliary propeller and is used for steering and propelling the ship body; the control system comprises a Jetson Orin Nano main control board, a sensor, a damper and a speed regulator and is used for controlling the unmanned ship; and the self-propulsion system is used for realizing ship positioning and navigation path planning. Green energy is adopted for driving, carbon emission of the ship is greatly reduced, and the energy efficiency of the ship is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of unmanned vessels, and in particular relates to a foldable wind-electric hybrid-driven trimaran unmanned vessel and a control method thereof. Background Art

[0002] With advancements in the design and construction of unmanned vessels, their application scenarios are expanding. However, modern unmanned vessels are generally electrically powered, which limits battery space and weight, severely hindering the development of large unmanned vessels. The industry is focusing on green unmanned vessels powered by renewable energy (solar and wind), offering low cost, minimal pollution, low noise, and long endurance. Some large unmanned vessels rely solely on green energy sources. Solar-powered unmanned vessels offer advantages such as low carbon emissions, environmental friendliness, high efficiency, and safety. However, solar energy is an intermittent and unstable energy source, significantly affected by factors such as location, season, and time of day. These uncertainties can lead to numerous problems in actual vessel operation, and therefore solar panels are generally not considered the primary propulsion source. While wind energy is an emerging clean energy source with promising applications in marine applications, it suffers from excessive randomness and uneven energy density distribution, leading to unmanned vessels becoming stationary in calm wind zones. To maximize wind energy, sails are typically large, which impacts the weight and size of unmanned boats. Furthermore, in harsh sea conditions, the heeling moment generated by the large sails can cause instability. Current wind-driven propulsion systems suffer from poor endurance, difficulty selecting appropriate equipment, and potential instability in adverse conditions.

[0003] Therefore, the current strategy of large unmanned boats using a simple green energy drive is not advisable. They cannot respond well and in a timely manner to complex external conditions. Moreover, due to the randomness and vastness of natural resources, a single green energy drive is difficult to achieve continuous navigation of ships. Therefore, new unmanned boats should be driven mainly by green energy and realize multiple energy supply modes.

[0004] Existing patent CN 114954881 A discloses a wind-electric hybrid-driven clean energy unmanned boat, comprising an unmanned boat body equipped with a wind-electric hybrid drive device. The wind-electric hybrid drive device comprises a wind energy collection unit and a wind energy utilization unit. The wind energy collection unit and the wind energy utilization unit cooperate to realize five control modes: charging mode only, wind-driven driving mode only, driving and charging mode simultaneously, electric-driven driving mode only, and headwind driving mode. The boat can be driven by wind and solar energy, achieving ultra-long endurance with zero carbon emissions. However, the invention's fin-shaped keel reduces the maneuverability of the unmanned boat; the horizontal-axis wind turbine has high requirements for wind direction and starting wind speed, and has a significant impact on the stability of the boat; and the redundant shutdown mechanism imposes unnecessary load on the boat.

[0005] Patent CN 108357638 A discloses a remote-controlled unmanned boat with a wind-driven straight-wing propeller. The two boat segments are spaced apart at the lower ends of a frame structure. The main axis of the lift-type vertical-axis wind rotor is vertically mounted at the upper middle end of the longitudinal girders. Multiple lift-type blades are spaced vertically around the main axis. Each lift-type blade is connected to the outer end of a connecting plate at its inner end, which is connected to the main axis. The main axis extends downward through a wind turbine to the input of a gearbox. The output of the gearbox is connected to the front end of a drive shaft, which in turn is connected to the input of the straight-wing propeller. This invention utilizes wind power to directly drive the propellers of the unmanned boat, propelling the boat forward. Solar panels and wind turbines mounted on the boat's hull charge the onboard battery pack, which then serves as a reserve energy source, theoretically providing the boat with unlimited endurance. However, the single vertical axis wind turbine of this invention has low wind energy utilization efficiency and low power supply per unit time; the unmanned ship is small in size and cannot carry cargo; the straight wing propeller has low propulsion efficiency and small thrust; it requires human remote control and has low self-propulsion capability.

[0006] Existing patent CN 108438138 A discloses a wind- and solar-powered hybrid-driven trimaran unmanned vessel, primarily consisting of a hull, a power system, and a control system. The hull comprises outer hulls, a middle hull, and a frame structure. An outer hull is located on either side of the middle hull. A propeller is mounted at the rear end of the middle hull, and a brushless electric motor propeller is mounted at the lower end of each outer hull's tail. The wind turbine's main shaft is longitudinally connected to a right-angle gearbox, which is laterally connected to an electromagnetic clutch via an input shaft. The other end of the electromagnetic clutch is connected to the propeller via an output shaft. This invention utilizes a hybrid system of wind and solar power to circumvent the limitations of a single natural energy source, resulting in excellent endurance and maneuverability. However, a single vertical-axis wind turbine has low wind energy utilization efficiency and low power per unit time. The unmanned vessel is small, making it incapable of carrying cargo. Drag-type vertical-axis wind turbines have low wind energy utilization. The hull spacing cannot be adjusted, resulting in poor waterway adaptability.

[0007] In summary, currently available unmanned boats are primarily small, powered by lithium batteries or diesel internal combustion engines. They carry limited energy, have limited endurance and transport capabilities, and exhibit poor stability. Wind-powered unmanned boats often utilize a single resistance-type wind turbine, which has low wind energy utilization and energy supply rates. Furthermore, failure of a single wind turbine can shut down the wind power system. Therefore, multiple arrays of lift-type wind turbines should be used to capture wind energy and improve endurance.

[0008] The power density of a single green energy source (solar or wind) is low, so it's necessary to combine different renewable energy sources to increase total output power. However, due to the intermittent nature of renewable energy, introducing it into ships can raise issues related to system stability, grid reliability, and power quality. Because the hull and sides of multihulls are close together, using multiple propellers can lead to interference between them, making the propulsion system susceptible to safety incidents.

[0009] In view of the demand for large-scale green unmanned boats to transport large loads, most researchers adopt the method of increasing the volume of the ship, which has a great impact on the stability and resistance of the hull. Therefore, it is necessary to design a model to achieve the purpose of safe passage of ships in restricted lanes.

[0010] Through the above analysis, the problems and defects of the existing technology are as follows:

[0011] (1) Existing unmanned vessels have limited energy carrying capacity and endurance. Most existing unmanned vessels are small in size and are typically equipped with lithium batteries or diesel internal combustion engines. The limited capacity of these energy systems severely restricts the endurance and transportation capacity of unmanned vessels. In addition, small unmanned vessels have limited weight margins, which affects their stability and load-carrying capacity.

[0012] (2) The current energy supply rate of wind-powered unmanned boats is low; most wind-powered unmanned boats currently use a single resistance-type wind turbine, resulting in a low wind energy utilization rate. The energy supply rate of a single wind turbine is insufficient, and once the wind turbine fails, the entire wind power system will not work properly, resulting in an interruption in the energy supply of the unmanned boat, affecting its endurance and mission execution.

[0013] (3) The power density of a single green energy source is insufficient to support large unmanned ships. The power density of a single green energy source (such as solar or wind energy) is low and cannot meet the high energy output requirements of large unmanned ships. When a single green energy source is introduced into a ship, it is easy to cause problems such as system stability, grid reliability, and power quality, affecting the normal operation and control of the unmanned ship.

[0014] (4) Propulsion system interference and safety hazards: In the design of multi-hull ships, the distance between the main body and the side hull is relatively close. When using a multi-propeller propulsion system, interference between the propellers is likely to occur, increasing the risk of propulsion system failure. This not only reduces propulsion efficiency, but may also cause safety accidents and threaten the stable navigation of the unmanned ship.

[0015] (5) Stability and resistance issues caused by the increase in hull size: To meet the large-load transportation needs of large green unmanned ships, existing technologies usually increase the load capacity by increasing the hull size. However, increasing the hull size will significantly affect the stability and hydrodynamic resistance of the hull, increase energy consumption, reduce navigation efficiency, and limit the adaptability of unmanned ships in complex sea conditions. Summary of the Invention

[0016] To overcome the problems existing in the related art, the present invention discloses a foldable wind-electric hybrid-driven trimaran unmanned vessel and a control method thereof. The technical solution is as follows:

[0017] The present invention is achieved as follows: a foldable wind-electric hybrid driven three-body unmanned boat, comprising: a hull, a wind and light energy system, a driving system, a control system and a self-propulsion system;

[0018] The hull includes an outer hull, a middle hull and a connecting bridge structure; the outer hull and the middle hull are arranged on both sides of the connecting bridge structure, and an outer hull is provided on the left and right sides of the middle hull respectively; the connecting bridge structure adopts a telescopic slide rail and a folding device;

[0019] The wind and solar energy system includes solar panels and multi-array vertical axis wind turbines, battery packs, right-angle gearboxes, generator sets and distribution boxes, achieving multi-source power generation by integrating solar and wind energy;

[0020] The drive system includes a main propeller and two auxiliary propellers. The main propeller achieves hull steering by controlling the direction of rotation of the vector propeller, and provides propulsion through power and speed matching of the ship, engine and propeller. The auxiliary propulsion is assisted by the vector propellers on both sides of the unmanned boat.

[0021] The control system includes: Jetson Orin Nano main control board, sensors, dampers and speed regulators. The embedded neural network of the Jetson Orin Nano main control board predicts the swaying motion of the unmanned boat in the next period of time based on the environmental information returned by the sensors, and changes the control state of the unmanned boat based on the amplitude of the swaying motion. The speed regulator and dampers realize the operation and switching of various modes of the unmanned boat, control the deployment and extension of the unmanned boat and the rotation and shutdown of the fan, and realize the automatic operation of the drive system through power transistors, power supply and electric motors.

[0022] The autonomous navigation system includes: satellite communication host, Beidou host, AIS, Beidou terminal, accelerometer and gyroscope to achieve ship positioning and navigation path planning.

[0023] Furthermore, the neural network adopts a hybrid model architecture, which consists of an input layer, a convolutional neural network (CNN), a long short-term memory (LSTM) network, a fully connected layer, and an output layer.

[0024] Time series data from accelerometers, gyroscopes, GPS, and anemometer sensors are used as input and enter the input layer after data preprocessing. Subsequently, the data is sent to the convolutional neural network (CNN) part, where multiple convolutional layers and pooling layers are used to extract spatial features from the sensor data and capture the correlation between different sensors. The extracted spatial features are then passed to the long short-term memory (LSTM) network, which captures temporal dependencies and dynamic change trends through a cyclic structure to process the ship's swaying motion. The fully connected layer integrates the time series features from the long short-term memory (LSTM) network and optimizes the feature representation. Finally, the output layer generates predictions for the ship's six-degree-of-freedom attitude and sway amplitude in the future. The CNN-LSTM architecture simultaneously processes the spatial and temporal features of sensor data, improving the accuracy of predictions and the response speed of the system, thereby achieving stable and efficient control of the unmanned ship in complex environments.

[0025] Furthermore, the main propeller and the two auxiliary propellers all adopt a vector ducted propeller design and are equipped with universal joints to achieve multi-angle rotation of the propeller; the main propeller and the two auxiliary propellers all use an electromagnetic clutch and output shaft to achieve continuous conversion of electrical energy into propeller mechanical energy.

[0026] Another object of the present invention is to provide a control method for a foldable wind-electric hybrid-driven three-hull unmanned vessel, the method being used to regulate the foldable wind-electric hybrid-driven three-hull unmanned vessel, the method comprising:

[0027] S1, the wind and solar energy system of the unmanned ship uses solar panels and vertical axis wind turbines to convert ambient energy into electrical energy and store it in the battery pack on board;

[0028] In step S2, the autonomous propulsion system controls the BeiDou main engine, accelerometer, and gyroscope to obtain the initial position, direction, speed, and attitude data of the unmanned vessel. The satellite communication system begins to receive satellite signals and connects with the navigation system to complete the positioning of the vessel's current position and navigation path planning.

[0029] S3, the control system uses sensors to obtain information about the ship's attitude and external environment, and loads the preset self-propulsion algorithm and sensor data processing module. It receives real-time data from the navigation system and sensors, analyzes the current environment and hull status, and predicts the ship's movement trend based on a neural network.

[0030] S4, the drive system controls the main and auxiliary propellers, adjusting the propeller's operating state through electromagnetic clutches; the system sets the initial speed and direction of the propellers to achieve ship propulsion operation;

[0031] S5, the control system controls the expansion and contraction and folding state of the bridge structure through the electronic control unit, and the damper realizes the wind machine braking of the unmanned ship based on the decision-making of the intelligent control algorithm; the working condition and operation mode of the unmanned ship are changed, and the sensor system continuously monitors the movement state of the hull, changes in the surrounding environment and power consumption.

[0032] In step S1, the wind and solar energy system of the unmanned vessel uses solar panels and vertical axis wind turbines to convert ambient energy into electrical energy and stores it in the onboard battery pack, including:

[0033] Solar panels in wind and solar energy systems utilize the photovoltaic effect. Semiconductor materials absorb photons from sunlight, stimulating electrons to generate current, converting light energy into electrical energy. This electrical energy is then output to the wind and solar energy systems in the form of direct current through internal wires and connectors.

[0034] A vertical axis wind turbine captures wind energy through its lift-type blades under the action of wind. The vertical axis wind turbine's rotational mechanical motion is converted into rotation on a horizontal axis through a right-angle gearbox. A generator set is connected to the axis to convert the mechanical energy into electrical energy.

[0035] The relative movement of the magnetic field and the wires inside the generator set generates electric current, which is then converted into mechanical energy on the rotating shaft through the transmission system. The generator set connected to the shaft converts the mechanical energy into electrical energy and outputs it in the form of direct current.

[0036] The electricity generated by the solar panels and vertical-axis wind turbine is converted into AC power by an inverter and supplied to the battery pack inside the unmanned boat for storage. The bridge electric system is controlled based on the battery pack's power sensing, enabling the unmanned boat to fold and unfold. This control of the bridge electric system is relatively accurate. The battery pack uses an embedded power sensing module to monitor the battery's charge and discharge status in real time and feeds this power information back to the control system. Based on the power sensing results, the control system precisely controls the bridge electric system through the speed regulator and damper, enabling the unmanned boat to automatically fold and unfold. Combining environmental data and hull posture information returned by sensors, the neural network algorithm embedded in the Jetson Orin Nano main control board dynamically adjusts the operating mode of the bridge electric system to optimize energy efficiency and hull stability.

[0037] The electromagnetic clutch is connected to the output shaft and propeller to control the working state of the transmission device.

[0038] In step S2, the self-propelled system obtains the initial position, direction, speed and attitude data of the unmanned vessel and realizes the positioning of the current position of the vessel and the navigation path planning, including:

[0039] The self-propulsion system uses the BeiDou mainframe, accelerometers, and gyroscopes to obtain information on the vessel’s position, direction, and speed, while the wind and solar energy systems power the system by converting solar and wind energy into electricity;

[0040] The control system has an embedded self-propulsion algorithm that analyzes navigation data, makes decisions, and makes real-time adjustments to navigation and sailing based on data sent back by sensors.

[0041] Satellite communication host transmits ship information in real time;

[0042] The AIS is received through the ground terminal host and connected to the Beidou host.

[0043] In step S3, the control system of the unmanned vessel implements various functions through the neural network and decision-making unit, sensors, dampers and speed regulator embedded in the main control board, including:

[0044] The sensor senses the surrounding environment, detects the key parameters of the unmanned ship, and transmits the key parameters to the JetsonOrin Nano main control board in real time;

[0045] Based on sensor input data, the CNN-LSTM hybrid neural network algorithm, with the Jetson Orin Nano main control board as its core, uses a fully trained neural network to predict the amplitude of the unmanned vessel's swaying motion in the next time period.

[0046] Based on the prediction results of the neural network, the main control board decides whether to adjust the control state of the unmanned boat and sends control signals to each actuator based on the decision;

[0047] The speed governor controls the propulsion speed of the boat, the damper adjusts the movement of the fan, and the power transistor manages the on-off of the power supply and the start and stop of the electric motor, allowing the unmanned boat to switch between different modes.

[0048] System sensors monitor the status of each actuator and return information to the main control board; the Jetson Orin Nano main control board analyzes the feedback data in real time and adjusts the control strategy.

[0049] Further, key parameters include the position, velocity, and wind speed of the UAV;

[0050] Actuators include speed regulators, dampers, power transistors, and electric motors;

[0051] The modes of the unmanned boat include deployment, retraction, rotation of the wind turbine or shutdown.

[0052] In step S4, the drive system controls the main propeller and the auxiliary propeller, and adjusts the operating state of the propeller through the electromagnetic clutch to achieve the ship propulsion operation including:

[0053] The main propeller of the drive system realizes the steering of the hull by rotating the direction of the vector ducted propeller; the main propeller adjusts the transmission of electric energy and the rotation angle and direction of the propeller through the control of the electromagnetic clutch;

[0054] The auxiliary propulsion system is assisted by the vector propellers located behind the two sides of the unmanned boat; the auxiliary propulsion system is combined with the output shaft through the electromagnetic clutch to realize the continuous conversion of electrical energy into mechanical energy of the propeller.

[0055] Furthermore, the main thruster and auxiliary thruster are based on the prediction results of the swaying motion of the neural network, and the working status of the main and auxiliary thrusters under the motion state is determined by the intelligent control algorithm; the control output linkage based on the electromagnetic clutch realizes the conversion of electrical energy into mechanical energy and the regulation of propulsion force.

[0056] Combining all the above technical solutions, the advantages and positive effects of the present invention are as follows:

[0057] First, the purpose of the present invention is to obtain wind energy through vertical axis wind turbines and light energy through solar panels, thereby driving the navigation of unmanned boats and meeting the needs of efficient energy utilization; on the other hand, the wind energy and light energy are converted into electrical energy, and the electrical energy drives the propeller to propel the unmanned boat forward, realizing energy storage and replenishment, achieving the long-term endurance requirements of the unmanned boat, and realizing the safe navigation of the unmanned boat in various waterways through the extension and retraction of the connecting bridge.

[0058] The present invention adopts a trimaran design to give the unmanned ship better stability. Through the overall design of the unmanned ship and the connecting bridge mechanism, it solves the problem of limited weight margin of modern unmanned ships and promotes the development of large unmanned ships. It adopts an innovative connecting bridge telescopic structure design to achieve the purpose of safe navigation in narrow waterways while obtaining high natural energy supplement. It adopts an intelligent control algorithm based on neural networks to further adjust the control state of the unmanned ship and change the actuator state while predicting the ship's posture to achieve safe and intelligent navigation.

[0059] The present invention adopts a multi-array vertical axis wind turbine as the main wind energy capture device. The vertical axis wind turbine has some advantages, such as low starting wind speed, low height requirement, small air resistance, easier maintenance, no requirement for natural wind direction, and more economical; and the multi-array vertical axis wind turbine design has the advantage of modularity, and the maintenance or failure of individual wind turbines will not significantly affect the operation of the entire system.

[0060] The present invention uses vector propellers as propulsion devices, which offer advantages such as good responsiveness and excellent maneuverability. Because the telescopic bridge structure avoids the propeller interference between the hull and side hulls of conventional trimarans, the present invention uses propellers as propulsion devices, ensuring the vessel's maneuverability and stability. Furthermore, the vector propellers' omnidirectional nature enhances the unmanned vessel's maneuverability.

[0061] The present invention uses green energy to drive unmanned ship transportation, greatly reducing the carbon emissions of ships, reducing the impact on the environment, and improving the energy efficiency of ships; at the same time, it significantly reduces the cost of manpower, fuel, etc., increases freight or passenger capacity, improves transportation efficiency and benefits, thereby expanding profit margins and enabling enterprises and employees to obtain greater benefits.

[0062] Second, the foldable wind-solar green large unmanned boat of the present invention is equipped with a vertical-axis wind turbine and solar panels to achieve efficient energy utilization; a retractable connecting bridge design is adopted to achieve the purpose of safe navigation in narrow waterways; an intelligent control algorithm based on a neural network is adopted to achieve rapid adjustment of the ship's attitude to ensure safe navigation; a trimaran design is adopted and equipped with a vector propeller to achieve high stability and high maneuverability.

[0063] The green energy unmanned vessel provided by this invention has multiple functions, such as being a mobile offshore energy station, a vessel for marine environmental surveys, defense monitoring, personnel and cargo transport, or a luxury yacht. These designs are designed to meet diverse maritime service scenarios and needs, demonstrating that this invention not only achieves multifunctionality but also continues to promote innovation and development in green energy unmanned vessel technology.

[0064] Third, the foldable wind-electric hybrid-driven trimaran unmanned boat and its control method of the present invention achieve efficient utilization and stable supply of multiple energy sources by efficiently integrating solar energy and multi-array vertical axis wind turbines, significantly improving the unmanned boat's endurance and energy efficiency. Expected benefits include, but are not limited to, the following aspects:

[0065] (1) Reduced energy costs: The use of renewable energy to drive the system reduces dependence on traditional fossil fuels, significantly reduces operating costs, and improves economic benefits.

[0066] (2) Multifunctional application: The unmanned boat has high stability and large load capacity, and is suitable for various application scenarios such as marine environment monitoring, energy collection, cargo transportation, and maritime rescue, expanding the scope of market application.

[0067] (3) Commercial expansion potential: The unmanned vessel can be used as a mobile charging platform at sea, an ocean survey vessel, a defense monitoring device, or a luxury yacht. It has broad commercial expansion potential, attracting diverse market demands and creating considerable commercial value. In addition, the green energy drive significantly reduces carbon emissions and environmental pollution, conforming to the trend of global sustainable development and enhancing the corporate social responsibility image.

[0068] Fourth, while some existing unmanned vessels have attempted to utilize a single green energy source (such as solar or wind power), these vessels generally suffer from issues such as insufficient endurance, low energy efficiency, and poor stability in complex sea conditions. Furthermore, existing trimaran unmanned vessels often utilize fixed hull spacing, making them difficult to safely navigate narrow waterways. Furthermore, interference between propellers in the propulsion system is a serious issue, impacting both maneuverability and safety.

[0069] The present invention realizes the dynamic adjustment of the spacing between the trimarans by introducing a foldable and retractable connecting bridge structure, significantly improving the adaptability and flexibility of the hull, and enabling safe passage in different waterway environments. At the same time, the use of a multi-array vertical axis wind turbine and a vector ducted propeller design optimizes the capture and utilization efficiency of wind energy, avoids interference between propellers, and improves the safety and control performance of the propulsion system. In addition, combined with intelligent control algorithms and neural network prediction models, intelligent regulation of hull posture and energy management is achieved, filling the technical gap in the combination of efficient utilization of multi-source energy and intelligent control. Therefore, the present invention fills the gap in domestic and foreign industry technology in terms of energy management, structural design and intelligent control of large green unmanned ships, and has significant innovation and advancement.

[0070] For a long time, industry technicians have faced numerous challenges in developing large unmanned vessels, including unstable energy supply, limited endurance, hull instability in complex sea conditions, and poor propulsion system safety. In particular, single-source green energy propulsion systems have struggled to meet the high energy output and long-duration continuous navigation requirements of large unmanned vessels. Furthermore, the low efficiency and high failure rate of single-source wind turbines further limit the application and reliability of unmanned vessels.

[0071] The present invention achieves multi-source efficient power generation by integrating solar energy and multi-array vertical axis wind turbines, solving the problems of instability and insufficient power density of a single energy supply. The foldable and retractable connecting bridge structure design enhances the adaptability of the hull in different sea conditions and waterway environments, ensuring the safe passage of unmanned ships in complex and narrow waterways. The vector ducted propeller design effectively avoids the problem of propeller interference in the propulsion system, improving the control performance and safety. At the same time, the intelligent control algorithm based on neural networks realizes intelligent regulation of the hull posture and energy management, significantly improving the stability and endurance of unmanned ships in complex sea conditions. Through these technological innovations, the performance and application potential of large unmanned ships have been significantly improved.

[0072] Fifth, existing technologies, such as fixed hull spacing and propeller design, make it difficult for unmanned vessels to achieve efficient maneuverability and safe navigation in complex waterway environments. These technical biases limit the adaptability and reliability of unmanned vessels in a wider range of application scenarios.

[0073] The present invention successfully overcomes many technical biases in the existing technology through innovative multi-source energy fusion, foldable and retractable connecting bridge structure and vector ducted propeller design. The application of multi-array vertical axis wind turbines breaks the limitation of a single wind energy capture mode and improves the efficiency of wind energy utilization and the reliability of the system. The foldable and retractable connecting bridge structure design breaks through the traditional design concept of fixed hull spacing and enhances the adaptability and flexibility of unmanned ships in different waterway environments. The introduction of vector ducted propellers solves the problem of propeller interference in the propulsion system and improves the control performance and safety. In addition, the intelligent control algorithm based on neural networks realizes the intelligent regulation of hull posture and energy management, further overcoming the technical bias of slow response and poor adaptability of traditional control systems in complex environments. Therefore, the present invention has successfully overcome many technical biases in the existing technology in terms of multi-source energy utilization, structural design and intelligent control, and has created a new situation in large-scale green unmanned ship technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure;

[0075] Figure 1 This is a schematic diagram of a folded state of a trimaran unmanned boat provided by an embodiment of the present invention;

[0076] Figure 2 This is a schematic diagram of the unfolded state of the trimaran unmanned boat provided by an embodiment of the present invention;

[0077] Figure 3 This is a top view of the unfolded state of the trimaran unmanned boat provided by an embodiment of the present invention;

[0078] Figure 4 This is a side view of the unfolded state of the trimaran unmanned boat provided by an embodiment of the present invention;

[0079] Figure 5 This is a front view of the unfolded state of the trimaran unmanned boat provided by an embodiment of the present invention;

[0080] Figure 6 This is a top view of the trimaran unmanned boat in a folded state provided by an embodiment of the present invention;

[0081] Figure 7 This is a side view of the folded trimaran unmanned boat provided by an embodiment of the present invention;

[0082] Figure 8 This is a front view of the folded trimaran unmanned boat provided by an embodiment of the present invention;

[0083] Figure 9 This is a schematic diagram of a connecting bridge mechanism for a trimaran unmanned ship provided by an embodiment of the present invention;

[0084] Figure 10 This is a schematic diagram of the wind and solar energy system of a trimaran unmanned vessel provided by an embodiment of the present invention;

[0085] Figure 11 Schematic diagram of the driving system of the trimaran unmanned ship provided by an embodiment of the present invention;

[0086] Figure 12 1 is a schematic diagram of a control system for a trimaran unmanned vessel according to an embodiment of the present invention;

[0087] Figure 13 This is a schematic diagram of a trimaran unmanned boat self-propelled system provided by an embodiment of the present invention;

[0088] Figure 14 This is a schematic diagram of an accelerometer and a gyroscope for a trimaran unmanned vessel provided by an embodiment of the present invention;

[0089] Figure 15 This is a flowchart of the operation of the trimaran unmanned ship provided by an embodiment of the present invention;

[0090] Figure 16 This is a block diagram of a neural network for intelligent control of a trimaran unmanned ship provided by an embodiment of the present invention;

[0091] Figure 17 This is a flow chart of a control method for a trimaran unmanned vessel provided by an embodiment of the present invention;

[0092] In the figure: 1. Vertical axis wind turbine; 2. Solar panel; 3. Hull; 4. Folding device; 5. Connecting rod; 6. Electronic control unit; 7. Telescopic slide; 8. Damper; 9. Battery pack; 10. Solar panel power output interface; 11. Right-angle gearbox; 12. Generator set; 13. Support mechanism; 14. Electric motor; 15. Electromagnetic clutch; 16. Main propulsion; 17. Universal joint; 18. Infrared sensor; 19. Beidou host; 20. Satellite communication system; 21. Accelerometer and gyroscope. DETAILED DESCRIPTION

[0093] To make the above-mentioned objects, features, and advantages of the present invention more readily apparent, specific embodiments of the present invention are described in detail below with reference to the accompanying drawings. The following description sets forth numerous specific details to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways than those described herein, and those skilled in the art may make similar modifications without departing from the scope of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0094] The innovation of the present invention is:

[0095] 1. A telescopic bridge structure design enables adjustable spacing between the three hulls of the trimaran. This telescopic structure is controlled by an intelligent control algorithm, which uses predicted ship attitude information to determine the next direction of the telescopic structure. Specifically, when natural energy is abundant or the unmanned vessel is operating efficiently, the intelligent control algorithm determines that the vessel is at a safe level based on the predicted ship attitude information and deploys the telescopic structure of the trimaran bridge, increasing the unmanned vessel's energy efficiency. In harsh natural environments (such as excessive wind speeds and high waves) that threaten the safety of the unmanned vessel or in narrow lanes, the intelligent control algorithm retracts the telescopic structure to ensure the safety of the unmanned vessel.

[0096] 2. A neural network intelligent control algorithm is used to ensure safe navigation and efficient energy utilization. The system uses environmental data transmitted by the ship's sensors and the ship's attitude data from the previous period to predict the ship's attitude in the short term. Based on the predicted ship attitude, the ship's control strategy is adjusted in advance to ensure safe navigation.

[0097] 3. The design employs a multi-array vertical-axis wind turbine 1 to achieve efficient wind energy capture and utilization, optimizing load distribution. Multiple vertical-axis wind turbines 1 are arrayed in different areas of the hull 3, helping to evenly distribute the load generated by the wind turbines across the hull 3. Through proper layout and structural design, the torque and lateral forces generated by the wind turbines can offset each other, reducing structural stress on the hull 3 and improving overall stability. Current unmanned vessels, due to their small size and limited space, often utilize a single horizontal-axis or vertical-axis wind turbine 1, resulting in low wind energy utilization. The large unmanned vessel designed in this invention can be equipped with multiple vertical-axis wind turbines 1 to capture wind energy from all directions, achieving efficient wind energy capture and utilization. Furthermore, the array of multiple vertical-axis wind turbines 1, distributed in different areas of the hull 3, helps evenly distribute the load generated by the wind turbines across the hull 3. Through proper layout and structural design, the torque and lateral forces generated by the wind turbines can offset each other, reducing structural stress on the hull 3 and improving overall stability. Because the wind turbine array utilizes a modular design, maintenance or failure of individual wind turbines will not significantly impact the operation of the entire system. The modular design also makes it easy to adjust the number and distribution of wind turbines according to different mission requirements and adapt to different environmental conditions and energy needs.

[0098] 4. The vector propeller design is adopted to achieve efficient maneuverability and stable navigation of the unmanned ship. Due to the emergence of the telescopic structure, the propulsion of the explosive vector propeller is free of interference between the propeller and the rudder. The interference range of the propeller is within four to eight times the diameter. When the ship is in the deployed posture, the propeller spacing can reach 10 times, and there is no interference. Specifically, since the distance between the side body and the main body of an ordinary trimaran is relatively close, the use of propellers is prone to cause propulsion interference, and a pump-push design is mostly adopted. The present invention has a telescopic connecting bridge design to ensure that the distance between the side body and the main body is relatively far, which can avoid interference between propellers. In addition, due to the full-rotation characteristic of the vector propeller, it can provide thrust in all directions for the ship, making it easier to achieve efficient maneuverability and stable navigation of the unmanned ship.

[0099] This invention realizes: energy collection and environmental monitoring in open sea areas

[0100] In open seas, unmanned ships usually need to sail for a long time to complete energy collection or environmental monitoring tasks. The unmanned ship of the present invention can efficiently capture solar energy and wind energy by integrating solar panels 2 and multi-array vertical axis wind turbines 1, and realize efficient conversion and storage of multi-source energy. The modular design of the multi-vertical axis wind turbine 1 enables it to maintain a high energy conversion efficiency even when the wind speed varies greatly. Through the intelligent control system, the swaying trend of the ship in the future is predicted, and the rotation state of the wind turbine and the posture of the hull 3 are dynamically adjusted to ensure that the unmanned ship can still maintain stable navigation under strong wind and wave conditions. In addition, combined with the foldable connecting bridge structure, the hull 3 can be expanded or retracted as needed to optimize wind energy capture and the hydrodynamic performance of the hull 3.

[0101] Positive effects: ① The multi-source energy system significantly extends the unmanned vessel's endurance, reducing its reliance on traditional energy sources. ② The intelligent control system ensures the vessel's stability in harsh sea conditions, improving mission reliability. ③ The unmanned vessel can conduct long-term and efficient environmental monitoring, meeting the needs of remote monitoring and data collection.

[0102] The present invention realizes: flexible passage in narrow waterways

[0103] In narrow waterways or complex waters, traditional multi-hull unmanned boats have difficulty flexibly adjusting their navigation width due to the fixed spacing between the three hulls, which affects the safety and efficiency of passage. The present invention uses a retractable and foldable connecting bridge structure to dynamically adjust the spacing between the three hulls according to the width of the waterway. In narrow waterways, the connecting bridge structure contracts, reducing the space occupied by the unmanned boat and improving navigation flexibility and safety. In wide sea areas or energy collection areas, the connecting bridge structure unfolds, increasing the spacing between the three hulls and improving stability and energy capture efficiency. The intelligent control system automatically adjusts the state of the connecting bridge structure based on real-time navigation data and environmental sensor information, ensuring that the unmanned boat can achieve optimal operating conditions in different waterway environments.

[0104] Positive Effects: ① Dynamically adjust the distance between the hulls 3, enabling the unmanned vessel to safely and efficiently navigate various narrow waterways. ② Adjust the hull 3 structure according to different waterway conditions, optimizing the unmanned vessel's hydrodynamic performance and energy capture efficiency. ③ The unmanned vessel can maintain efficient operation in various waterways and sea conditions, enhancing its wide range of applications and flexibility.

[0105] Example 1, as Figure 1 As shown, the foldable wind-electric hybrid driven trimaran unmanned boat of the present invention comprises: a hull 3, a wind and light energy system, a driving system, a control system and a self-propulsion system;

[0106] The hull 3 includes an outer hull, an intermediate hull and a connecting bridge structure; the outer hull and the intermediate hull are arranged on both sides of the connecting bridge structure, and an outer hull is provided on the left and right sides of the intermediate hull respectively; the connecting bridge structure adopts a telescopic slide rail and a folding device 4;

[0107] The wind and solar energy system includes: solar panels 2 and multi-array vertical axis wind turbines 1, battery packs 9, right-angle gearboxes 11, generator sets 12 and distribution boxes, which achieve multi-source power generation by integrating solar and wind energy;

[0108] The drive system includes: a main propeller 16 and two auxiliary propellers. The main propeller 16 realizes the steering of the hull 3 by controlling the direction of rotation of the vector propeller, and provides propulsion function through the power and speed matching of the ship, engine and propeller; the auxiliary propulsion is assisted by the vector propellers on both sides of the unmanned boat.

[0109] The control system includes: a Jetson Orin Nano main control board, sensors, a damper 8, and a speed regulator. The neural network embedded in the Jetson Orin Nano main control board predicts the swaying motion of the unmanned boat in the next period of time based on the environmental information returned by the sensors, and changes the control state of the unmanned boat based on the amplitude of the swaying motion. The speed regulator and damper 8 enable the operation and switching of various modes of the unmanned boat, controlling the deployment and extension of the unmanned boat and the rotation and shutdown of the fan. The power transistor, power supply, and electric motor realize the automatic operation of the drive system.

[0110] The self-propelled system includes: a satellite communication host, a Beidou host 19, an AIS, a Beidou terminal, an accelerometer and a gyroscope 21 to achieve ship positioning and navigation path planning.

[0111] The neural network adopts a hybrid model architecture, which consists of an input layer, a convolutional neural network (CNN), a long short-term memory (LSTM) network, a fully connected layer, and an output layer.

[0112] Time series data from accelerometers, gyroscopes, GPS, and anemometer sensors are used as input and enter the input layer after data preprocessing. Subsequently, the data is sent to the convolutional neural network (CNN) part, where multiple convolutional layers and pooling layers are used to extract spatial features from the sensor data and capture the correlation between different sensors. The extracted spatial features are then passed to the long short-term memory (LSTM) network, which captures temporal dependencies and dynamic change trends through a cyclic structure to process the ship's swaying motion. The fully connected layer integrates the time series features from the long short-term memory (LSTM) network and optimizes the feature representation. Finally, the output layer generates predictions for the ship's six-degree-of-freedom attitude and sway amplitude in the future. The CNN-LSTM architecture simultaneously processes the spatial and temporal features of sensor data, improving the accuracy of predictions and the response speed of the system, thereby achieving stable and efficient control of the unmanned ship in complex environments.

[0113] In the autonomous propulsion system, various components work together to form an orderly operational process. First, the navigation system (including the Beidou mainframe 19, accelerometers, and gyroscopes 21) obtains the vessel's accurate position, direction, and speed in real time. The power system (consisting of solar panels 2 and vertical-axis wind turbines 1) continuously supplies the entire system by converting solar and wind energy into electricity. Next, the autonomous propulsion algorithm embedded in the control system utilizes the Jetson Orin Nano mainboard. Using convolutional neural networks (CNNs) and long-short-term memory networks (LSTMs), it extracts and fuses features from preprocessed navigation data and data from environmental sensors (such as infrared sensors 18 and anemometers), predicting the amplitude and trend of the unmanned vessel's swaying motion over the next time period. Based on the predictions, the autonomous propulsion algorithm assesses the risk level of the current navigation state and formulates appropriate control strategies, including adjusting heading, speed, hull 3 attitude, deployment or retraction of the connecting bridge, and rotation and shutdown of the wind turbines. Control commands are transmitted to actuators (such as power transistors, power supplies, and electric motors) via the speed regulator and damper 8, enabling the unmanned vessel to operate and switch between different modes. Throughout this process, a feedback loop continuously monitors the actuator status and hull 3 motion, adjusting the control strategy in real time to ensure stable and efficient navigation in various environments. Simultaneously, the satellite communication host transmits real-time vessel information, which is received by the ground terminal host. The AIS connects to the Beidou host 19, enabling efficient information transmission and remote monitoring.

[0114] like Figure 2 As shown, the hull 3 of the present invention includes an outer hull, an intermediate hull and a connecting bridge structure to form a composite hull system. In this design, the outer hull and the intermediate hull are connected by a connecting bridge structure (see Figure 9) connection, and the connecting bridge structure has the characteristics of telescopic and folding to enhance the flexibility and adaptability of the hull 3. The slide rail system allows the connecting bridge to be flexibly telescopic in the horizontal direction, while the folding device 4 enables it to be folded in the vertical direction. The synergistic effect of these two mechanisms enables the connecting bridge to achieve multi-directional movement and adjustment in different situations. The electronic control unit 6 is the key to this process. Based on the coordinated control of the movement of the electronic control unit 6 by the intelligent control system, the slide rails and folding device 4 can be operated accurately and smoothly, ensuring that the telescopic and folding movements of the connecting bridge can be achieved during the operation of the hull 3. The electric unit consists of an electric motor, a transmission device and a control unit, and is driven by a small battery. The electric motor is precisely controlled by the control unit to achieve the movement of the slide rails and folding device 4. The overall material adopts high-strength and lightweight materials such as stainless steel, which can reduce the weight of the entire hull 3 while ensuring the stability and reliability of the structure, and improve the maneuverability and fuel efficiency of the hull 3. This structural design allows the connecting bridge to be telescopic and folded as needed to adapt to different navigation environments and passage spaces, increasing the flexibility and versatility of the hull 3.

[0115] The top view, side view and front view of the unfolded state of the three-body unmanned boat of the present invention are as follows: Figure 3-Figure 5 As shown, the top view, side view and front view of the folded state of the trimaran unmanned ship are as follows Figure 6-Figure 8 shown.

[0116] like Figure 10 As shown, the wind and solar energy system of the present invention integrates solar and wind energy, achieving multi-source power generation, energy storage, and intelligent control of the movement of the hull 3. First, solar panels 2 utilize the photovoltaic effect to convert photons in sunlight into electrical energy. The semiconductor materials used in solar panels 2 excite electrons in response to photons, generating an electric current. This direct current is transmitted via internal wires and connectors to the panel's power output interface 10, where it is output to the battery pack 9, supplying the invention's power needs. Next, the vertical-axis wind turbine 1 captures wind energy through its lift-type blades. A right-angle gearbox 11 converts the vertical-axis wind turbine's rotational motion into horizontal rotation. The shaft, connected to a generator set 12 secured by a support mechanism 13, converts the mechanical energy into electrical energy. The relative motion between the magnetic field within the generator set 12 and the wires generates an electric current. This generated electrical energy is then stored in the battery pack 9 within the unmanned vessel. The battery pack 9, through its built-in power sensor, controls the control bridge's electrical system, enabling the unmanned vessel to fold and unfold. Finally, the battery pack 9 supplies power to the entire system.

[0117] like Figure 11As shown, the present invention realizes a highly efficient power conversion drive system through the coordinated action of the battery pack 9, the motor 14, and the electromagnetic clutch 15. First, the battery pack 9 acts as an energy storage device, storing the electricity generated by the solar panels 2 and the vertical axis wind turbine 1, ensuring that the system can continue to supply the required electricity to the motor 14 in the event of insufficient sunlight or unstable wind. Second, the motor 14 is the core of the drive system and operates with the electricity supplied by the battery pack 9. During startup, the motor 14 first receives the electricity stored in the battery pack 9 and converts it into mechanical energy to drive the propellers of the main propeller 16 and the auxiliary propeller to rotate, ensuring the immediate start of the system and the normal operation of the motor 14. During the propulsion process, the electromagnetic clutch 15 plays a key role, achieving precise control of the propeller by adjusting the power transmission. The combined output shaft control of the electromagnetic clutch 15 allows the operating state of the main propeller 16 to be intelligently adjusted according to system requirements, achieving smooth power transmission to the propeller, and enabling the system to maintain efficient and flexible propulsion performance under different navigation conditions. The main propeller 16 is the core of the system, which realizes the steering of the hull 3 by controlling the universal rotation 17 of the vector propeller. The design of the main propeller 16 is based on the power and speed matching principle of ship-engine-propeller to provide low-vibration and high-efficiency propulsion. The main propeller 16 adopts a ducted propeller design and is equipped with a universal joint 17, which enables the propeller to rotate at multiple angles to adapt to different navigation requirements. This structure ensures that the main propeller 16 can provide stable and flexible propulsion under different hull 3 motion states. The auxiliary propeller is the same as the main propeller 16.

[0118] like Figure 12As shown, the control system of the present invention consists of a main control board, sensors, a damper 8, and a speed regulator. These components work together to enable the operation and switching of the unmanned vessel's various modes, as well as control of key functions. First, the main control board's embedded program serves as the core control. Through pre-programmed programming, the main control board receives information transmitted by sensors and makes corresponding control decisions. This intelligent control system enables the unmanned vessel to respond in real time to the environment and mission requirements. Sensors monitor and sense the environment. They detect the vessel's status, position, surroundings, and other information, and transmit this information to the main control board. Common sensors include position sensors, tilt sensors, and temperature sensors, which are used to obtain various parameters to support the main control board's decision-making. The damper 8 and speed regulator are key devices for controlling the operation and switching of the unmanned vessel's various modes. The damper 8 adjusts the damping of the unmanned vessel's vertical axis fan, ensuring smooth operation under varying environmental conditions. The speed regulator adjusts the speed and direction of the unmanned vessel, enabling flexible navigation control. These devices are implemented using motors and mechanical structures to ensure accurate control of the unmanned vessel's motion. During operation, the drive system's automatic operation is controlled by a clutch. The clutch connects and disconnects the power supply and motor drive as needed, enabling precise control of the drive system. The power supply provides energy for the entire system, while the motor drives the various components, such as deployment, retraction, fan rotation, and shutdown. Through ingenious structural design and collaborative operation, the control system achieves intelligent control of various unmanned vessel operations, ensuring safe, stable, and efficient operation under diverse circumstances.

[0119] like Figure 13 As shown, in the self-navigation system of the present invention, the order in which each component plays a role is closely coordinated to form a set of orderly operation processes. First, the navigation system (including the Beidou host 19, accelerometer and gyroscope 21 (see Figure 14 )) plays a starting role, receiving satellite signals through the satellite communication system 20 to obtain the unmanned vessel's accurate position, direction, and speed information. Subsequently, the power system comes into play, with the solar panels 2 and vertical-axis wind turbine 1 converting solar and wind energy into electricity, providing the necessary power support for the entire system. The control system then intervenes. The embedded self-propulsion algorithm analyzes data provided by the navigation system and makes intelligent decisions, including heading adjustment and speed control, to achieve real-time adjustments to the unmanned vessel. Simultaneously, data transmitted back by sensors is fully utilized during this stage, providing timely environmental feedback to the self-propulsion algorithm.

[0120] With sufficient information in place, the satellite communication system 20 becomes a crucial component. The satellite communication host transmits the unmanned vessel's information to the ground terminal host via a satellite link, enabling real-time monitoring of the vessel's position and status. Simultaneously, the AIS system interfaces with the Beidou host 19, providing diverse information inputs to the entire system. Overall, the navigation system provides basic data, the power system ensures energy supply, the control system implements real-time adjustments based on self-propulsion algorithms and sensor data, and ultimately, the communication system ensures efficient information transmission. This orderly, coordinated process enables the unmanned vessel to maintain efficient and intelligent navigation during autonomous navigation.

[0121] Preferably, the drive system of the present invention ensures the adaptability and flexibility of the unmanned boat in different water conditions. The main propeller 16 provides basic driving force, enabling the unmanned boat to start and move in a specific direction. The introduction of the auxiliary propeller provides additional propulsion for the unmanned boat, assisting the main propeller 16 to achieve more flexible movement and steering. It is worth noting that when the ship is in the folded state, the auxiliary propeller does not work. Through the intelligent control of the electromagnetic clutch 15, the entire drive system can be adjusted in real time according to different mission requirements and environmental conditions to achieve efficient and low-vibration propulsion effects. This orderly workflow ensures that the unmanned boat can operate stably and controllably in various navigation scenarios.

[0122] Preferably, in the control system, the control system of the unmanned boat mainly realizes various functions through key components such as the neural network and decision-making program, sensors, damper 8 and speed regulator embedded in the main control board. The first is environmental data collection and input. The sensors include position sensors, speed sensors, wind speed sensors, etc. These sensors perceive the surrounding environment in real time and detect key parameters such as the position, speed, and wind speed of the unmanned boat. The data collected by these sensors (such as position, speed, wind speed, etc.) are transmitted to the Jetson Orin Nano main control board via the data bus to form an environmental data input stream. On this basis, the main control board implements intelligent control decisions. The board first cleans and standardizes the sensor input data, eliminating noise and outliers to ensure data quality. The processed data is then fed into a neural network model embedded in the Jetson Orin Nano board. The neural network model uses historical data and current input to predict the amplitude and trend of the unmanned vessel's swaying motion in the next time period. Combined with mechanical models (such as ship swaying models and ship maneuvering models), the neural network's predictions are further verified and calibrated to ensure the physical rationality and accuracy of the predictions. Based on the swaying motion predictions, the board uses pre-set control logic to determine whether the control state of the unmanned vessel needs to be adjusted. Based on this control logic, the board generates specific control instructions and sends them to each actuator. Subsequently, the speed regulator adjusts the propulsion speed of the unmanned vessel according to the board's instructions to cope with the upcoming swaying motion and ensure the stability of the hull 3. Simultaneously, the damper 8 adjusts the rotation speed and direction of the fan according to the predicted swaying amplitude to control the stability of the unmanned vessel. Following the board's instructions, the power transistors and electric motors work in coordination to ensure the automated operation of the unmanned vessel's various systems. The power transistor controls the on / off power supply, starting or stopping the electric motor, and enabling the unmanned boat to deploy and retract, and rotate or stop the wind turbines. Finally, the main control board receives sensor feedback and adjusts the control strategy in real time to optimize the boat's stability and efficiency. Based on sway predictions and the current sailing environment, it automatically switches between various operating modes (such as sailing, wind turbine operation, and hull deployment / retraction) to ensure optimal sailing conditions.

[0123] Preferably, in the self-propelled system, each component works together to form an orderly operating process. First, the Beidou host 19, accelerometer and gyroscope 21 obtain the accurate position, direction and speed information of the ship. At the same time, the power system (solar panels 2 and vertical axis wind turbines 1) convert solar energy and wind energy into electrical energy to supply the power required by the entire system. Afterwards, the control system's built-in self-propelled algorithm analyzes navigation data, makes decisions, and realizes real-time adjustments to navigation and navigation based on the data sent back by the sensors. The satellite communication host transmits ship information in real time. The AIS is received by the ground terminal host and docked with the Beidou host 19.

[0124] The unmanned ship drive system works under the following three working conditions:

[0125] Working condition 1: The unmanned boat is deployed, wind energy and light energy are converted into electrical energy for storage, and the propeller of the unmanned boat is not working.

[0126] The battery pack 9 uses its built-in power sensing control system to detect insufficient energy, control the bridge's electrical system, and send commands to the main control board. The electronic control unit 6 pushes the telescopic slide 7, causing the connecting rod 5 to deploy, placing the unmanned boat in its deployed state. The blades of the vertical-axis wind turbine 1 rotate in response to the wind, converting wind energy into rotational mechanical energy. The right-angle gearbox 11 converts the vertical-axis wind turbine 1's rotational motion into rotation about the horizontal axis, which is then connected to the shaft of the generator set 12, converting the mechanical energy into electrical energy. The relative motion between the magnetic field within the generator set 12 and the conductors generates an electric current. This generated electrical energy is then supplied to the battery pack 9 within the unmanned boat for storage. The solar panel 2 excites electrons, sending electrical energy to the battery pack 9 via the panel's power output interface 10.

[0127] The unmanned boat is in the deployed state, and the wind turbine and solar panel 2 work simultaneously, efficiently converting natural wind energy and light energy into electrical energy, which is stored in the battery pack 9 and can be used as a mobile charging platform at sea. Efficient energy utilization: This process does not require the propeller to work, which means that the unmanned boat can remain stationary or rely solely on natural drifting, thereby saving energy and maximizing charging efficiency. The unmanned boat in this mode can be used as a mobile charging station at sea, providing power supply for other unmanned boats or offshore equipment nearby, and is particularly suitable for sea areas far away from land power sources. Energy reserve optimization: When propulsion is not required, excess energy is stored to provide guarantees for subsequent propulsion and equipment operation, extending the endurance of the unmanned boat.

[0128] Compared to traditional fixed charging platforms, the mobility of unmanned boats allows for flexible deployment across vast ocean areas, providing charging services for dispersed equipment. Leveraging the efficient conversion of wind and solar energy, this system offers significant environmental and economic advantages, making it particularly suitable for offshore environments far from land or with limited energy supply. This technical solution offers greater energy efficiency and operational flexibility than existing technologies, bringing significant practical value to offshore operations.

[0129] Working condition 2: The unmanned boat is in folded state, wind energy is converted into electrical energy for storage, and the propeller drives the unmanned boat to move.

[0130] Infrared sensor 18 detects the surrounding environment, and Beidou host 19 determines that the channel ahead requires the unmanned boat to narrow its width. Battery pack 9, using its built-in power sensor, controls the bridge's electrical system. The main control board sends a command, and electronic control unit 6 pushes telescopic slide 7, retracting connecting rod 5, placing the unmanned boat in a folded state. The blades of vertical-axis wind turbine 1 rotate in response to the wind, converting wind energy into rotational mechanical energy. The right-angle gearbox 11 converts the vertical-axis wind turbine's rotational motion into rotation about the horizontal axis. The shaft connected to generator set 12 converts the mechanical energy into electrical energy. Electric motor 14 first receives the electrical energy stored in battery pack 9 and converts it into mechanical energy. The electromagnetic clutch 15 regulates the electrical energy transmission to ensure smooth transmission of electrical energy to the propeller. The main propeller 16 receives the transmission and begins operation, while the auxiliary propellers begin assisting.

[0131] In this operating condition, the unmanned boat's folding structure retracts, reducing its navigation width to facilitate navigation through narrow waterways. Meanwhile, wind energy continues to be converted into electricity and stored in the battery pack 9. Navigational Flexibility: The propellers operate, propelling the unmanned boat forward. The folding structure enables the unmanned boat to navigate narrow waterways, enhancing its environmental adaptability and operational flexibility. Efficient Energy Utilization: Even during propulsion, wind energy is effectively converted into electricity, providing stable energy support for the electric motor 14 and propellers, ensuring propulsion efficiency and endurance.

[0132] Traditional technologies usually adopt fixed structures and are difficult to adapt to complex navigation environments. The folding design of this technology enables the unmanned boat to maintain stable and efficient operation in various water conditions, and is especially suitable for harsh or narrow sea conditions.

[0133] Working condition three: The unmanned boat is deployed, wind energy and light energy are converted into electrical energy for storage, and the propeller drives the unmanned boat to move.

[0134] Infrared sensors 18 detect the surrounding environment, and Beidou host 19 determines that the channel ahead does not require the unmanned boat to narrow its width. The battery pack 9, using its built-in power sensor, controls the bridge's electrical system. The main control board sends a command, and the electronic control unit 6 pushes the telescopic slide 7, retracting the connecting rod 5, placing the unmanned boat in a folded state. The blades of the vertical-axis wind turbine 1 rotate in response to the wind, converting wind energy into rotational mechanical energy. The right-angle gearbox 11 converts the vertical-axis wind turbine 1's rotational motion into rotation about the horizontal axis. The shaft connected to the generator set 12 converts the mechanical energy into electrical energy. Simultaneously, the solar panel 2 excites electrons, sending electrical energy to the battery pack 9 through the panel's power output port 10. The electric motor 14 first receives the electrical energy stored in the battery pack 9 and converts it into mechanical energy. The electromagnetic clutch 15 regulates the electrical energy transmission to ensure smooth transmission of electrical energy to the propeller. The main propeller 16 receives the transmission and begins operation, while the auxiliary propellers begin assisting.

[0135] In this operating condition, the unmanned boat is deployed, with the wind turbine and solar panels 2 operating simultaneously, converting wind and solar energy into electrical energy, which is stored in the battery pack 9. Simultaneously, the propeller propels the unmanned boat forward. Maximizing Energy Capture and Utilization: The simultaneous conversion of wind and solar energy enables the unmanned boat to maintain efficient energy capture during extended voyages, while energy storage ensures continuous and stable propulsion. Improved Navigation Efficiency: The energy in the battery pack 9 provides stable power support for the propeller, enhancing the unmanned boat's navigation efficiency and ensuring smooth operation in varying sea conditions.

[0136] Traditional single energy systems are difficult to maintain long-term efficient operation under complex sea conditions. The multi-energy coordinated conversion and energy storage system of this technical solution not only improves energy utilization efficiency, but also significantly enhances the navigation endurance and stability of unmanned boats.

[0137] Example 2: The ship type in the present invention can be changed to other trimarans or catamarans. The changed cabin layout and equipment arrangement can continue to be used after the center of gravity is checked, and the original functions remain unchanged.

[0138] In Example 3, the blades of the vertical axis wind turbine 1 in the present invention are replaced with H-shaped ones, which does not affect the functionality.

[0139] In Example 4, the ducted propeller in the present invention is replaced with an azimuth counter-rotating propeller.

[0140] In the fifth embodiment, the electromagnetic clutch 15 in the present invention is replaced by a magnetic powder clutch.

[0141] Example 6, as Figure 15 As shown, the operation process of the unmanned ship provided by the embodiment of the present invention includes:

[0142] ① Turn on the main power supply to activate the power system. The solar panels 2 and vertical axis wind turbine 1 start working, converting ambient energy into electricity and storing it in the onboard battery bank 9, ensuring sufficient power supply for the entire system.

[0143] ② The autonomous propulsion system activates the BeiDou main unit 19, accelerometer, and gyroscope 21 to obtain the UAV's initial position, direction, speed, and attitude data. The satellite communication system 20 begins receiving satellite signals and connects with the navigation system to accurately determine the vessel's current position and plan its navigation path.

[0144] ③The sensor system is started to obtain ship attitude information and external environment information.

[0145] ④ The control system starts up, loading the preset self-propulsion algorithm and sensor data processing module. The control system begins receiving real-time data from the navigation system and sensors, analyzes the current environment and hull state, and predicts the ship's motion trends based on a neural network.

[0146] ⑤ The electric motor 14 starts, connecting the main thruster 16 and the auxiliary thruster, and adjusting the thruster's operating state through the electromagnetic clutch 15. The system sets the initial speed and direction of the thruster based on the mission requirements and environmental conditions, and prepares for propulsion operation.

[0147] ⑥ Based on current navigation conditions and mission requirements, the control system, through the electronic control unit 6, controls the bridge structure's expansion and contraction. If energy is harvested in open waters, the bridge structure deploys, increasing the UAV's stability and energy harvesting efficiency. In harsh environments, the bridge structure retracts, ensuring the safety of the hull 3.

[0148] ⑦ The damper 8 actuator starts working and performs wind turbine braking and other tasks based on the intelligent control algorithm decision.

[0149] ⑧ Based on the above operations, the working conditions and operation modes of the unmanned boat are changed. The sensor system continuously monitors the motion state of the hull 3, changes in the surrounding environment, and power consumption. If an abnormal situation or insufficient power is detected, the intelligent control system will automatically adjust the navigation parameters, such as reducing the speed, optimizing energy distribution, or adjusting the route.

[0150] like Figure 16 As shown in the figure, the neural network of the unmanned vessel of the present invention is used to input the vessel's motion posture information of the previous ten seconds, such as the six-degree-of-freedom attitude information of the vessel (roll, pitch, heave, etc.) collected by the gyroscope, and the external environmental information returned by the sensor, such as wind speed, wind direction, and current direction. The deep fully connected feedforward neural network (DNN) predicts the six-degree-of-freedom attitude information of the vessel for the next period and then provides it to the decision-making unit for judgment.

[0151] Through its foldable and retractable bridge structure, the present invention dynamically adjusts the distance between the hulls 3 according to the navigation environment, optimizing hydrodynamic performance and hull stability. In the deployed state, increasing the distance between the hulls 3 improves energy capture efficiency and load capacity; in the folded state, decreasing the distance between the hulls 3 enhances navigational flexibility and maneuverability, ensuring safe passage of the unmanned boat in narrow waterways.

[0152] In this foldable wind-electric hybrid-powered trimaran unmanned vessel, the design of the hulls 3 offers remarkable flexibility. A retractable and foldable bridge structure allows for dynamic adjustment under varying operating conditions. When the unmanned vessel is in its deployed state, the bridge structure is fully extended, and the trimaran's total width reaches 15 meters. In this state, the spacing between the hulls 3 is increased, enhancing the vessel's stability and wind energy capture efficiency, making it suitable for long-term navigation and energy collection missions in open waters.

[0153] When the unmanned boat is folded, the connecting bridge structure shrinks and the trimaran's total width is reduced to 8 meters. This width allows the unmanned boat to flexibly navigate narrow channels and complex water environments, ensuring safe passage in restricted waterways.

[0154] The present invention has the technical advantage of being adaptable to narrow waterways. For example, the standard waterway width of many urban rivers and ports is approximately 10 to 12 meters. When folded, the unmanned boat of the present invention has a width of 8 meters, significantly less than the minimum width of these waterways. This ensures that the unmanned boat can safely and efficiently navigate narrow waterways without being restricted by the fixed width of the hull 3.

[0155] The above description is only a preferred specific implementation method of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with this technical field within the technical scope disclosed by the present invention and within the spirit and principles of the present invention should be covered by the scope of protection of the present invention.

Claims

1. A foldable wind power hybrid driven trimaran unmanned boat, characterized in that: The unmanned ship comprises: a hull (3), a wind energy and light energy system, a driving system, a control system and a self-propulsion system; The hull (3) comprises an outer hull, a middle hull and a connecting bridge structure; the outer hull and the middle hull are arranged on both sides of the connecting bridge structure, and an outer hull is respectively arranged on the left and right sides of the middle hull; the connecting bridge structure adopts a telescopic slide rail (7) and a folding device (4); The wind and light energy system comprises: a solar panel (2) and a multi-array vertical axis wind turbine (1), a battery pack (9), a right-angle gear box (11), a generator set (12) and a distribution box, and realizes multi-source power generation by integrating solar energy and wind energy; The driving system comprises: a main propeller (16) and two auxiliary propellers. The main propeller (16) realizes the steering of the hull (3) by controlling the rotation direction of the vector propeller, and provides a propulsion function through the power and speed matching of the ship, the engine and the propeller; the auxiliary propulsion is assisted by the vector propellers behind the two sides of the unmanned boat; The control system includes: a Jetson Orin Nano main control board, a sensor, a damper (8) and a speed regulator; the Jetson Orin Nano main control board is embedded with a neural network to predict the swaying motion of the unmanned boat in the next period of time according to the environmental information sent back by the sensor, and the control state of the unmanned boat is changed based on the amplitude of the swaying motion; the speed regulator and the damper (8) are used to realize the operation and switching of various modes of the unmanned boat, control the deployment, extension and rotation of the unmanned boat and the rotation and stop of the fan, and realize the automatic operation of the drive system through the power transistor, the power supply and the electric motor; The self-propelled system includes: a satellite communication host, a Beidou host (19), an AIS, a Beidou terminal, an accelerometer and a gyroscope (21), which realizes ship positioning and navigation path planning.

2. The foldable wind power hybrid driven trimaran unmanned boat according to claim 1, characterized in that: The neural network adopts a hybrid model architecture, which consists of an input layer, a convolutional neural network CNN, a long short-term memory network LSTM, a fully connected layer and an output layer; Time series data from accelerometer, gyroscope, GPS, and anemometer sensors are used as input and enter the input layer after data preprocessing; Subsequently, the data is fed into the convolutional neural network (CNN) part, where multiple convolutional and pooling layers are used to extract spatial features from the sensor data and capture the correlation between different sensors. The extracted spatial features are then passed to the LSTM network, which captures temporal dependencies and dynamic trends through a cyclic structure to process the ship's rolling motion. The fully connected layer integrates the temporal features from the LSTM network to optimize the feature representation. Finally, the output layer generates prediction results for the six-degree-of-freedom attitude and sway amplitude of the ship in the future; the CNN-LSTM architecture simultaneously processes the spatial and temporal characteristics of sensor data, improves the accuracy of prediction and the response speed of the system, and realizes stable and efficient control of unmanned ships in complex environments.

3. The foldable wind power hybrid driven trimaran unmanned boat according to claim 1 is characterized in that: The main propeller (16) and the two auxiliary propellers are both designed with vector ducted propellers and are equipped with universal joints (17) to achieve multi-angle rotation of the propellers; the main propeller (16) and the two auxiliary propellers are both connected by an electromagnetic clutch (15) and an output shaft to achieve continuous conversion of electrical energy into propeller mechanical energy.

4. A control method for a foldable wind power hybrid driven trimaran unmanned boat, characterized in that: The method is used to control the foldable wind power hybrid driven trimaran unmanned boat according to any one of claims 1 to 3, and the method comprises: S1, the wind and light energy system of the unmanned ship uses solar panels (2) and vertical axis wind turbines (1) to convert environmental energy into electrical energy and store it in a battery pack (9) on board the ship; S2, the self-propelled system controls the Beidou host (19), accelerometer and gyroscope (21) to obtain the initial position, direction, speed and attitude data of the unmanned ship; the satellite communication system (20) starts to receive satellite signals and connects with the navigation system to complete the positioning of the current position of the ship and the navigation path planning; S3, the control system uses sensors to obtain ship attitude information and external environment information, and loads the preset self-propulsion algorithm and sensor data processing module; receives real-time data provided by the navigation system and sensors, analyzes the current environment and hull (3) status, and predicts the movement trend of the ship based on the neural network; S4, the drive system controls the main propeller (16) and the auxiliary propeller, and adjusts the operating state of the propeller through the electromagnetic clutch (15); the system sets the initial speed and direction of the propeller to realize the ship propulsion operation; S5, the control system controls the extension and folding state of the bridge structure through the electronic control unit (6), and the damper (8) realizes the wind machine braking of the unmanned ship based on the decision of the intelligent control algorithm; the working condition and operation mode of the unmanned ship are changed, and the sensor system continuously monitors the movement state of the hull (3), changes in the surrounding environment and power consumption.

5. The control method of the foldable wind power hybrid driven trimaran unmanned boat according to claim 4 is characterized in that: In step S1, the wind and light energy system of the unmanned ship uses solar panels (2) and vertical axis wind turbines (1) to convert environmental energy into electrical energy and stores it in a battery pack (9) on board the ship, including: The solar panels of wind and solar energy systems use the photovoltaic effect to absorb photons in sunlight through semiconductor materials, stimulate electrons to generate current, and convert light energy into electrical energy; the electrical energy is output to the wind and solar energy system in the form of direct current through internal wires and connectors; The vertical axis wind turbine (1) captures wind energy through lift-type blades under the action of wind, and converts the mechanical motion of the vertical axis wind turbine (1) into rotation on a horizontal axis through a right-angle gearbox (11). A generator set (12) is connected to the axis to convert the mechanical energy into electrical energy. The relative movement of the magnetic field and the wire inside the generator set (12) causes the generation of electric current, which is then converted into mechanical energy on the rotating shaft through the transmission system; the mechanical energy is converted into electrical energy through the generator set (12) connected to the shaft and output in the form of direct current; The electric energy generated by the solar panel (2) and the vertical axis wind turbine (1) is converted into alternating current through an inverter and supplied to the battery pack (9) in the unmanned boat for storage; the bridge electric system is controlled based on the power sensing control of the battery pack (9) to realize the folding and unfolding of the unmanned boat; the bridge electric system is controlled relatively accurately based on the power sensing control of the battery pack (9), and the battery pack (9) monitors the charging and discharging status of the battery in real time through the embedded power sensing module, and feeds back the power information to the control system; based on the power sensing result, the control system accurately controls the bridge electric system through the speed regulator and the damper (8) to realize the automatic folding and unfolding of the unmanned boat; combined with the environmental data and the posture information of the hull (3) sent back by the sensor, the operation mode of the bridge electric system is dynamically adjusted through the neural network algorithm embedded in the Jetson Orin Nano main control board to optimize the energy utilization efficiency and the stability of the hull (3); The electromagnetic clutch (15) is connected to the output shaft and the propeller to control the working state of the transmission device.

6. The control method of the foldable wind power hybrid driven trimaran unmanned boat according to claim 4, characterized in that: In step S2, the self-propelled system obtains the initial position, direction, speed and attitude data of the unmanned ship and realizes the positioning and navigation path planning of the current position of the ship, including: The self-propelled system uses the Beidou main engine (19), accelerometer and gyroscope (21) to obtain the position, direction and speed information of the vessel, while the wind and solar energy systems power the system by converting solar energy and wind energy into electrical energy; The control system has an embedded self-propelled algorithm that analyzes navigation data, makes decisions, and makes real-time adjustments to navigation and navigation based on the data sent back by the sensors; The satellite communication host transmits ship information in real time; The AIS is received by the ground terminal host and connected to the Beidou host (19).

7. The control method of the foldable wind power hybrid driven trimaran unmanned boat according to claim 4, characterized in that: In step S3, the control system of the unmanned ship implements various functions through the neural network and decision-making unit, sensor, damper (8) and speed regulator embedded in the main control board, including: The sensor senses the surrounding environment, detects the key parameters of the unmanned ship, and transmits the key parameters to the Jetson OrinNano main control board in real time; Based on the data input by the sensors, the CNN-LSTM hybrid neural network algorithm with the Jetson Orin Nano main control board as the core predicts the amplitude of the unmanned ship's swaying motion in the next time period through a well-trained neural network; Based on the prediction results of the neural network, the main control board decides whether to adjust the control state of the unmanned ship and sends control signals to each actuator based on the decision; The speed governor controls the propulsion speed of the boat, the damper (8) regulates the movement of the fan, and the power transistor manages the on and off of the power supply and the start and stop of the electric motor, so that the unmanned boat can switch between different modes; System sensors monitor the status of each actuator and return information to the main control board; the Jetson Orin Nano main control board analyzes the feedback data in real time and adjusts the control strategy.

8. The control method of the foldable wind power hybrid driven trimaran unmanned boat according to claim 7, characterized in that: Key parameters include the drone’s position, speed, and wind speed; The actuator includes a speed regulator, a damper (8), a power transistor and an electric motor; The modes of the unmanned boat include deployment, retraction, rotation of the wind turbine or shutdown.

9. The control method of the foldable wind power hybrid driven trimaran unmanned boat according to claim 4, characterized in that: In step S4, the driving system controls the main propeller (16) and the auxiliary propeller, and adjusts the operating state of the propeller through the electromagnetic clutch (15), so as to realize the ship propulsion operation including: The main propeller (16) of the driving system realizes the steering of the hull (3) by rotating the direction of the vector duct propeller; the main propeller (16) adjusts the transmission of electric energy and the rotation angle and direction of the propeller through the control of the electromagnetic clutch (15); The auxiliary propeller assists propulsion through the vector propellers located behind the two sides of the unmanned boat; the auxiliary propeller is combined with the output shaft through the electromagnetic clutch (15) to realize the continuous conversion of electrical energy into mechanical energy of the propeller.

10. The control method of the foldable wind power hybrid driven trimaran unmanned boat according to claim 9, characterized in that: The main propeller (16) and the auxiliary propeller are based on the prediction results of the swaying motion of the neural network, and the working state of the main and auxiliary propellers under the motion state is determined by an intelligent control algorithm; based on the control output linkage of the electromagnetic clutch (15), the conversion of electrical energy into mechanical energy and the regulation of propulsion force are realized.

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