Method for determining optimal water surface stability and underwater motion performance of dual-mode unmanned sailboat

Abstract

The invention discloses a method for determining optimal water surface stability and underwater motion performance of a dual-mode unmanned sailboat. Firstly, based on ship stability specifications, the water surface initial stability height of a sailing ship under different heavy hammer masses is calculated, and the initial stability height range is determined; secondly, ship body recovery torque and wind tilting torque are calculated, static and dynamic heeling angles are determined, and the initial stability high range of the ship body is further narrowed; thirdly, calculating underwater stability, establishing an underwater motion model, and obtaining a hydrodynamic coefficient; then, simulation is carried out based on the underwater motion model, and the limit pitch angle and rising / diving height performance under different parameters are calculated. And finally, constructing a multi-objective optimization model and solving an optimal parameter combination. And selecting an optimal compromise scheme based on an ideal point method, and determining the final weight mass and propeller mounting angle. Unified optimization of the dual-mode performance is achieved, and the design efficiency and the comprehensive performance of the aircraft are remarkably improved.

Description

Technical Field

[0001] This invention belongs to the field of marine unmanned vehicle design technology, and relates to a method for determining the optimal surface stability and underwater motion performance of a dual-mode unmanned sailboat that combines fluid dynamics, ship stability and multi-objective genetic optimization methods. Background Technology

[0002] Dual-mode unmanned sailboats are a new type of marine unmanned vehicle that combines surface navigation and underwater navigation. Because of their dual-mode switching capability, these vehicles can flexibly choose between surface or underwater navigation modes according to actual needs when performing missions, thereby improving mission adaptability and survivability.

[0003] However, the dual-mode navigation characteristics also bring unique technical challenges, especially in terms of stability design. When a sailboat is in surface navigation mode, its stability is mainly manifested in its ability to resist external disturbances such as wind and waves. This requires sufficient initial stability and large-angle stability to ensure navigation safety and attitude stability under strong winds or large waves. In underwater navigation mode, the hull needs to have a certain degree of stability to maintain attitude balance, but excessive stability will limit its underwater maneuverability and affect its pitch, turn, and other motion response capabilities. Therefore, how to achieve the optimal balance between surface stability and underwater maneuverability has become a key issue in the design of dual-mode unmanned sailboats.

[0004] Currently, the methods for analyzing the stability and motion performance of single-mode vehicles (such as surface ships or underwater vehicles) are relatively mature. However, for vehicles operating in both surface and underwater modes, the stability design and performance evaluation still lack systematic and unified theoretical and methodological support. Existing research often focuses on performance optimization in a specific mode or relies on empirical trial-and-error methods for parameter adjustment, lacking a comprehensive consideration of the impact of dual-mode coupling. This results in long design cycles, low efficiency, and difficulty in guaranteeing global optimality.

[0005] Furthermore, during mode switching, the hull structure, buoyancy, and center of gravity of the dual-mode unmanned sailboat undergo significant changes, further increasing the complexity of stability analysis and motion modeling. Traditional single-point optimization or single-objective design methods are insufficient to simultaneously meet the requirements of surface capsizing resistance and underwater maneuverability. Therefore, it is urgent to introduce multi-objective system optimization strategies, combining computational fluid dynamics (CFD) simulation with ship stability theory to establish an integrated design and evaluation system suitable for dual-mode operation scenarios. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide a systematic and automated method for determining the optimal surface stability and underwater motion performance of a dual-mode unmanned sailboat. By integrating fluid dynamics simulation, ship stability calculation and multi-objective genetic optimization, the method scientifically balances the contradiction between surface navigation stability and underwater navigation maneuverability, thereby determining the optimal solution for key design parameters.

[0007] To achieve the above objectives, this invention provides a method for determining the optimal surface stability and underwater motion performance of a dual-mode unmanned sailboat, comprising the following steps:

[0008] Step 1: Based on the ship stability code, calculate the initial metacentric height of the sailboat under different weight masses and determine the range of the initial metacentric height.

[0009] Step 2: Calculate the hull restoring moment and wind heeling moment, and determine the static and dynamic heel angles to further narrow down the range of the hull's initial stability.

[0010] Step 3: Calculate the underwater stability height and establish an underwater motion model to obtain the hydrodynamic coefficients.

[0011] Step 4: Perform simulation based on the underwater motion model to calculate the limit pitch angle and ascent / descent height performance under different parameters.

[0012] Step 5: Construct a multi-objective optimization model and solve for the optimal parameter combination; select the best compromise scheme based on the ideal point method, and determine the final weight of the hammer and the installation angle of the thruster.

[0013] Based on the above technical solution, compared with the prior art, the present invention has the following advantages:

[0014] 1. For the first time, surface stability, underwater maneuverability, and mode switching characteristics are incorporated into a unified framework for overall optimization, solving the problem of performance conflicts in multiple modes in the design of dual-mode vehicles.

[0015] 2. By deeply integrating CFD simulation with classical ship stability theory, high-precision calculations of wind-induced tilting moment, restoring moment, and hydrodynamic coefficients are performed, significantly improving the reliability of the analysis.

[0016] 3. By simplifying the underwater motion degrees of freedom and using alternative dynamic mesh techniques such as UDFs (user-defined functions) to solve for the additional mass, computational efficiency is significantly improved while ensuring accuracy.

[0017] 4. By adopting a multi-objective genetic optimization algorithm to replace traditional manual trial and error, the design process is automated and optimized. It can quickly provide a global Pareto optimal solution, which greatly improves the design quality and efficiency. Attached Figure Description

[0018] Figure 1This is a schematic diagram of the structure of a dual-mode unmanned sailboat according to an embodiment of this application.

[0019] Figure 2 This is an overall flowchart of a method for determining the optimal surface stability and underwater motion performance of a dual-mode unmanned sailboat according to an embodiment of this application.

[0020] Figure 3 This is a schematic diagram illustrating the force exerted on the hull by the wind-induced action of the wing sail in an embodiment of this application.

[0021] Figure 4 This is a graph showing the tilting moment and the recovery moment of the embodiment of this application with respect to the tilt angle.

[0022] Figure 5 This is a schematic diagram of the inertial coordinate system and the three-degree-of-freedom motion coordinate system of the ship hull during underwater navigation according to an embodiment of this application.

[0023] Figure 6 This is a flowchart of the multi-objective genetic optimization algorithm in an embodiment of this application.

[0024] Figure 7 This is an embodiment of the present application. Figure 6 A flowchart for evaluating individuals within a population.

[0025] Figure 8 This is an embodiment of the present application. Figure 6 A flowchart for verifying constraints.

[0026] Figure 9 This is a Pareto front diagram obtained using a multi-objective genetic optimization algorithm in an embodiment of this application. Detailed Implementation

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] like Figure 1 As shown, this application embodiment provides a dual-mode unmanned sailboat ( Figure 1 The left side of the middle section represents the surface mode, and the right side represents the underwater mode. The mode includes: a pair of horizontal rudders 1, which provide torque for the pitching motion of the hull; a propeller 2, which provides forward propulsion for the hull to navigate underwater; a wing sail 3, which provides propulsion for the hull to navigate on the surface; a center plate 4 and a counterweight 5, which provide stability for the hull on the surface and underwater; a butterfly valve, which controls the intake of water into the hull; and a water pump, which controls the drainage of water from the hull.

[0029] The mode switching process is as follows: When switching from surface mode to underwater mode, the wing sail is folded up and the butterfly valve is opened to allow water to enter the hull and sink; when switching back from underwater mode to surface mode, the butterfly valve is closed and the water pump is started to drain water, and the wing sail is unfolded after the hull rises. The mass of the counterweight is a core parameter affecting the overall center of gravity and stability of the hull; the installation angle of the propeller relative to the horizontal plane directly relates to the maximum pitch angle achievable during underwater navigation.

[0030] like Figure 2 As shown, this application provides a method for determining the optimal surface stability and underwater motion performance of a dual-mode unmanned sailboat, applied to the aforementioned dual-mode unmanned sailboat. This method uses the mass of the counterweight and the thruster installation angle as key design variables, employing a multi-objective genetic optimization algorithm to collaboratively optimize the sailboat's surface stability (characterized by high initial stability and large tilt angle stability) and underwater motion performance (characterized by maximum pitch angle), including the following steps:

[0031] Step 1: Based on the ship stability code, calculate the initial metacentric height of the sailboat under different weight masses and determine the range of the initial metacentric height.

[0032] Based on the theory of initial stability of ships, when the hull is tilted at a small angle... At that time, its transverse epicenter radius , This represents the moment of inertia of the waterline surface area about its longitudinal central axis. This indicates the ship's displacement volume.

[0033] Calculate the initial stability of the hull , The vertical coordinates representing the center of buoyancy in the water surface state. The vertical coordinates representing the centroid of the water surface state.

[0034] In 3D modeling software (such as SolidWorks), create a hull model with different weight masses. For each mass configuration, the software can directly provide the required parameters. , , and Substituting into the above formula, the corresponding initial stability height can be quickly calculated. The feasible range of the aforementioned high initial stability is determined by the minimum high initial stability requirement in the ship stability code, and it must ensure that the hull has the ability to resist capsizing under normal navigation conditions.

[0035] Step 2: Calculate the hull restoring moment and wind heel moment, and determine the static and dynamic heel angles to further narrow down the range of initial stability. This includes:

[0036] Step 2-1: Calculation of restoring torque:

[0037] In SolidWorks, by rotating a ship model with a defined waterline around its center of gravity in a heeling motion, the coordinates of the center of buoyancy before and after the heeling can be directly obtained through the software, thus yielding the restoring arm. , and These are the lateral coordinates of the center of buoyancy after upright and tilted positions, respectively.

[0038] Further, calculate the restoring torque. Indicates the density of seawater. It represents the acceleration due to gravity.

[0039] By calculating different yaw angles The curve of the restoring moment as a function of the pitch angle can be obtained by fitting. .

[0040] Step 2-2: Calculation of wind tilting moment:

[0041] An aerodynamic model of the wing sail was built in Ansys Fluent, and the drag generated by it at different angles of attack under maximum wind speed was calculated. and lift ,like Figure 3 As shown ( Figure 3 In Indicates the positive direction of the ship's sway. (This indicates the positive direction of the ship's heave). Through coordinate transformation, the longitudinal force in the ship's coordinate system is obtained. and lateral force , can be represented as:

[0042]

[0043] in, Indicates the sail's angle. Indicates the angle of attack; , representing the relative wind angle. Then, the maximum tilting moment generated by the wing sail... It can be represented as:

[0044]

[0045] in, For the maximum lateral force, The wind-driven tilt arm in a positive buoyancy state can be represented as:

[0046]

[0047] in, This represents the vertical coordinate of the center of the wing sail region. From this, we can plot the wind tilt moment variation curves corresponding to different weight masses, and then fit the curves to obtain... The two moments mentioned above are applied with respect to the heel angle. The curve is as follows Figure 4 As shown.

[0048] Steps 2-3: Determining static and dynamic tilt angles:

[0049] like Figure 4 As shown, when When the forces acting on the hull are in equilibrium, the corresponding heel angle is the static heel angle. Considering the kinetic energy during the heeling process, the hull will overtake... Continue to tilt. According to the law of conservation of energy, the work done by the wind tilting torque... Equal to the work done by the restoring torque At that time, that is When the angle of roll is 1, the corresponding angle of roll is called the dynamic roll angle. According to engineering safety requirements, the static tilt angle... and dynamic tilt angle None should exceed 90 This allows for a further narrowing of the applicable range for the mass of the counterweight and the application scope for products with high initial stability.

[0050] Step 3: Calculate the underwater stability height and establish an underwater motion model, obtaining hydrodynamic coefficients through CFD simulation. This includes:

[0051] Step 3-1: Calculation of underwater stability height and initial pitch angle:

[0052] After folding the wing sail, simulate the underwater state using model density in SolidWorks to directly obtain the underwater center of gravity. and floating heart .

[0053] Calculate underwater stability and initial stable pitch angle :

[0054]

[0055]

[0056] When adjusting the mass of the counterweight, it is necessary to adjust the counterweight to ensure that the total weight of the hull and buoyancy remain unchanged, and the initial pitch angle remains constant. The weight is fixed so that changes in the weight's mass only affect stability.

[0057] Step 3-2: Establish underwater kinematics and dynamics model:

[0058] like Figure 5 As shown, given the ship's symmetry, the underwater motion is simplified to a three-degree-of-freedom problem (swing, heave, pitch) in the longitudinal plane, and the kinematic equations are established:

[0059]

[0060] in, Indicates the velocity in the direction of oscillation. The velocity representing the direction of heave. Indicates the angular velocity in the pitch direction; It indicates the pitch angle; it is positive when the ship is bow-down and negative when the ship is bow-up. This represents the velocity of the ship in the OX direction in the inertial coordinate system. This represents the velocity of the ship in the OY direction in the inertial coordinate system.

[0061] Establish the dynamic equations:

[0062] in, The acceleration in the direction of the ship's pitch is represented. The acceleration in the direction of the ship's heave. Angular acceleration in the direction of ship pitch; Indicates the mass of the ship's hull; The moment of inertia representing the pitch direction of the ship; , These represent the resultant forces acting on the ship's hull in the longitudinal and helical directions, respectively. The resultant moment acting on the hull in the pitch direction can be expressed as:

[0063]

[0064] in, , These represent the thrust of the propeller in the directions of pitch and heave, respectively. This indicates the torque exerted by the propeller on the hull in the pitch direction; , These represent the hydrostatic forces generated by gravity and buoyancy in the directions of the ship's sway and heave, respectively. This represents the hydrostatic moment generated by gravity and buoyancy in the direction of the ship's pitch. , These represent the hydrodynamic forces acting on the ship's hull in the directions of surge and heave during its underwater motion, respectively. This represents the hydrodynamic torque experienced by the ship in the pitch direction during its underwater motion; , These represent the hydrodynamic forces generated by a single horizontal rudder on the hull in the pitch and heave directions, respectively. This represents the hydrodynamic torque generated by a single horizontal rudder on the hull in the pitch direction.

[0065] in, , , It can be represented as:

[0066]

[0067] in, This represents the additional mass coefficient in the direction of the ship's pitch. This represents the secondary damping coefficient for the ship's pitching motion. When indicating the pitching motion of the ship The resulting heave force coefficient, This represents the additional mass coefficient in the direction of hull heave. This represents the heave force coefficient generated by the ship's pitching motion. This represents the linear damping coefficient for the ship's heave motion. This represents the secondary damping coefficient of the ship's heave motion. When indicating the pitching motion of the ship The resulting heave force coefficient; This represents the additional moment of inertia coefficient in the pitch direction of the hull. When indicating the heaving motion of the ship The resulting pitching moment coefficient, This represents the linear damping coefficient for the ship's pitching motion. This represents the pitching moment coefficient generated by the ship's swaying motion. When indicating the heaving motion of the ship The resulting pitching moment coefficient, When indicating the heaving motion of the ship The resulting pitching moment coefficient; , is the coupling coefficient.

[0068] Step 3-3: Solve for hydrodynamic coefficients using CFD:

[0069] The hydrodynamic term can be expressed as a function containing various hydrodynamic coefficients. To solve for these coefficients, the following series of CFD simulations are required:

[0070] Step 3-3-1: Straight-line simulation: By changing the incoming flow velocity, the relationship between drag and the square of the velocity is fitted to obtain the drag coefficient. .

[0071] Step 3-3-2: Inclined Flight Simulation: Perform steady-state calculations at different drift angles, fit the vertical force and pitch moment, and obtain... , , , , .

[0072] Step 3-3-3: Unsteady simulation of pure heave / pure pitch: Defining the oscillating motion of the hull using UDF ( or The system monitors unsteady forces and torques. The monitoring data is then sinusoidally fitted in MatLab to separate the forces and torques related to acceleration (…). , ) and speed ( , The relevant terms are used to solve for the solution. , , and Equal coefficients.

[0073] Step 3-3-4: Additional Mass Coefficient for Swaying Solution: An efficient method to replace the moving mesh is adopted. Steady-state drag is first obtained through uniform motion simulation. Then, using a UDF, the inlet velocity is abruptly changed from uniform velocity to uniform acceleration, and transient simulation is used to obtain the instantaneous drag during acceleration. ,Depend on The sway-additional mass coefficient is obtained by inverse calculation. .

[0074] Step 3-3-5: Horizontal Rudder Force Coefficient: The rudder force and torque coefficient of the horizontal rudder can be obtained by calculating its lift and drag coefficients at different angles of attack, and based on the installation position.

[0075] In particular, determining some coupling coefficients is quite difficult; therefore, approximate relationships for these coupled hydrodynamic coefficients are set as follows: , .

[0076] After solving all the hydrodynamic coefficients, a complete underwater three-degree-of-freedom dynamic model that can be used for simulation and prediction is constructed.

[0077] Step 4: Perform simulation based on the underwater motion model to calculate the limit pitch angle and ascent / descent height performance under different parameters.

[0078] In the MatLab / Simulink simulation environment, based on the underwater three-degree-of-freedom (pitch, heave, and pitch) kinematics and dynamic equations of the hull established in step 3, a corresponding system simulation model is built. This model uses all the hydrodynamic coefficients obtained through CFD simulation in step 3 and the force / moment model of the horizontal rudder as input parameters, thus forming a simulation platform that can accurately reflect the underwater dynamic characteristics of the hull.

[0079] To simulate a typical scenario where a ship accelerates from a stable state and performs surfacing or diving maneuvers, the initial simulation conditions are set as follows: initial sway velocity... The initial velocity of the heave is a constant value. and pitch angular velocity All are zero. Thruster thrust. The rudder angles were set to a fixed operating value to provide forward propulsion. To investigate the pitch limits achievable by the hull under active control, the angles of the left and right horizontal rudders were adjusted. Set to positive and negative full rudder states. These correspond to two extreme maneuvering conditions: the ship diving to its maximum extent (bow-down) and surfacing (bow-up), respectively.

[0080] Under defined initial conditions and control rules, multiple simulation scenarios were generated by combining different counterweight masses with a series of thruster installation angles. For each scenario, a Simulink model was run to simulate and record the ship's pitch angle. A complete history curve over time is required. Additionally, data on the maximum pitch angle and dive height performance achievable by the hull must be recorded and calculated. Dip height performance can be expressed as the dive height per 10 m horizontal distance traveled.

[0081] Through this simulation step, we can obtain a series of mapping relationship data between the combination of design parameters and the underwater motion performance of the hull, providing direct input for the next step of multi-objective optimization.

[0082] Step 5: Construct a multi-objective optimization model and solve for the optimal parameter combination; select the optimal trade-off based on the ideal point method to determine the final weight mass and thruster installation angle. This includes:

[0083] Step 5-1: Establish the fitting objective function:

[0084] Construct a water surface stability fitting function and apply it to different weight masses. The corresponding initial stability is high By performing a linear fit, we obtain:

[0085]

[0086] This model indicates that water surface stability is approximately linearly related to the mass of the counterweight.

[0087] Different weights of hammers and thruster installation angle The ultimate pitch angle obtained from the combined simulation and the height of 10m dive / ascent per horizontal movement By performing quadratic surface fitting, the underwater pitch angle model is obtained:

[0088]

[0089]

[0090] This model describes the nonlinear relationship between the ship's underwater motion performance and two design variables.

[0091] Step 5-2: Define the multi-objective optimization problem:

[0092] Based on step 5-1, the engineering design problem is transformed into a constrained multi-objective optimization problem (MOP) mathematical model.

[0093] Step 5-2-1: Design variables:

[0094] Key adjustable parameters affecting performance are defined as optimization variables. In the embodiments of this application, they are defined as follows: The mass of the hammer is expressed in kilograms (kg). The installation angle of the thruster, in degrees ( The angle between the hull reference line and the reference line is used to indicate the reference line.

[0095] Step 5-2-2: Objective function:

[0096] Define two performance metrics that need to be maximized simultaneously:

[0097] Surface stability. The higher the stability value, the stronger the ship's ability to resist capsizing, and the safer the navigation.

[0098] Maximum pitch angle (absolute value). This value represents the maximum absolute pitch angle that the ship can achieve when moving downwards (pitch) and upwards (raise). Maximizing this value means enhancing the ship's underwater maneuverability.

[0099] Since optimization algorithms typically default to minimizing the objective, the algorithm internally takes the negative of these two objective functions, transforming the maximization problem into a minimization problem, i.e.: .

[0100] Step 5-2-3: Constraints:

[0101] Define the constraints for the multi-objective optimization problem, including:

[0102] Stability constraints: Water surface stability It must be greater than or equal to a set minimum value. ,Right now This constraint ensures that all optimized solutions meet the basic safety requirements.

[0103] Pitch angle symmetry constraint: the absolute value of the maximum downward pitch angle The absolute value of the maximum upward elevation angle The absolute value of the difference must not exceed ,Right now This constraint ensures that the hull has approximately symmetrical maneuverability in the surfacing and diving directions, avoiding loss of controllability.

[0104] Limiting pitch angle constraint: the absolute value of the maximum downward pitch angle The absolute value of the maximum upward elevation angle All must be less than or equal to a set maximum value. ,Right now This constraint ensures that the angle of the hull during pitching is not too large, thus ensuring the safety of the hull during underwater navigation.

[0105] Dive / ascend distance constraint: The hull dives / ascends to a certain height for every 10m of horizontal movement underwater. It needs to be greater than a certain set value This constraint ensures that the hull has a certain degree of ascent and descent capability.

[0106] Step 5-3: Optimize the solution using the NSGA-II algorithm:

[0107] The second-generation non-dominated sorting genetic algorithm (NSGA-II) is adopted. The algorithm flow is as follows: Figure 6 , Figure 7 and Figure 8 As shown, the specific process is as follows:

[0108] Step 5-3-1: Initialization: Within the allowable range of design variables, randomly generate a certain number of initial parameter combinations (individuals) to form the initial population.

[0109] Step 5-3-2: Evaluation: Calculate the two objective function values ​​for each individual in the population. and And check whether the constraints are met.

[0110] Step 5-3-3: Ranking and Selection: Based on Pareto dominance, individuals in the population are divided into different levels of non-dominated fronts. The top-ranked front contains the optimal set of candidate solutions (i.e., a solution cannot improve one objective while harming another). Within the same front, the solution density around each individual is calculated to maintain the diversity of the solution set. Based on ranking and crowding, a new generation of the population is generated through genetic operators such as selection, crossover, and mutation.

[0111] Step 5-3-4: Iteration: Repeat the evaluation, sorting, and selection steps until the algorithm converges. Finally, a set of Pareto optimal solutions is obtained, which forms a Pareto front in the objective function space, such as... Figure 9 As shown, each point on the frontier represents an optimal compromise.

[0112] Step 5-4: Output the optimal compromise solution:

[0113] The NSGA-II algorithm described above ultimately outputs a Pareto optimal solution set. Each solution in this set represents a feasible design scheme, and no single scheme is strictly superior to another in all objectives. Therefore, it is necessary to select the most suitable optimal compromise solution based on the actual task preferences to complete the design. This application's embodiment employs an automated decision-making process based on the ideal point method, which involves finding a point in the objective space closest to the ideal point. The specific steps are as follows:

[0114] Step 5-4-1: Define the ideal point:

[0115] Ideal point Let be a hypothetical point in the target space, where each coordinate component represents the optimal value achievable by a single target without constraints from other targets. For the two minimization objective functions in this application embodiment... Stable component at the ideal point For all solutions in the Pareto front The minimum value, i.e. Pitch component of the ideal point For all corresponding Pareto fronts The minimum value, i.e. Ideal point It is usually impossible to reach, but it represents the theoretical limit.

[0116] Step 5-4-2: Normalization process:

[0117] Because the two objective functions have different physical meanings and dimensions (initial stability is higher than angle), directly calculating the geometric distance will lead to the objective with the larger dimension dominating the selection process. To solve this problem, the objective space needs to be normalized.

[0118] First, find the worst value (Nadir Point) for each target direction in the Pareto solution set, i.e. , .

[0119] Then, for each solution in the Pareto solution set Its normalized target value and Represented as:

[0120]

[0121] After normalization, all target values ​​are scaled to the [0, 1] interval, eliminating the influence of dimensions. The coordinates of the ideal point after normalization are: .

[0122] Step 5-4-3: Calculate the distance and select the best compromise solution:

[0123] Calculate each Pareto solution in the normalized objective space. To the normalized ideal point Euclidean distance ;

[0124] Compare all Choose the solution with the smallest distance as the best compromise solution.

[0125] Based on the same concept as the above method, this test case also provides a method for determining the optimal surface stability and underwater motion performance of a dual-mode unmanned sailboat, with specific implementation details as follows:

[0126] (1) Set the parameters of the dual-mode unmanned sailboat: sailboat mass The weight of the hammer is 475 kg. The range is [12kg, 30kg]. The calculated initial stability is high (in mm). .

[0127] The maximum wind force that the dual-mode sailboat can withstand on the water is level 6. Calculate the wind tilt moment under this wind condition. and restoring torque Calculate the static tilt angle under different weight masses based on the relationship between the two torques. and dynamic tilt angle Based on the static tilt angle and dynamic tilt angle No more than 90 Determine the initial stability of the sailboat is high It needs to be greater than 90mm.

[0128] (2) Solve for the underwater center of gravity coordinates and hydrodynamic coefficients of the sailboat and input them into the hydrodynamic model. Set the initial conditions for the simulation as follows: initial sway velocity The initial velocity of the heave is 0. and pitch angular velocity All are 0, initial pitch angle 2 Total thrust of the propulsion unit Set to 100N, thruster installation angle The range is [-12] 12 ].

[0129] By combining different weights of the counterweights and thruster installation angles, multiple scenarios were simulated in MATLAB Simulink to obtain the maximum pitch angle achievable by the hull underwater. and (Unit is) ) and the height of dive / ascent for every 10m of horizontal movement of the hull. and (Unit: m), and by fitting it, we obtain:

[0130]

[0131]

[0132]

[0133]

[0134] (3) The design variables for multi-objective optimization are , The range is [12kg, 30kg], The range is [-12] 12 The objective function for optimization is high initial stability of the water surface. and the maximum pitch angle that the ship can achieve when sailing up and down. and .

[0135] (4) The constraints of multi-objective optimization design include:

[0136] Stability constraints: High initial surface stability 90mm;

[0137] Pitch angle symmetry constraint: 1 ;

[0138] Limiting pitch angle constraints: 25 ;

[0139] Descent / ascent altitude constraints: 1.5m 1.5m.

[0140] (5) Set the initial parameters of the NSGA-II algorithm as follows: population size 100, maximum number of iterations 50, crossover rate 0.8, mutation rate 0.1.

[0141] After the algorithm iterations are complete, a set of Pareto fronts is obtained. The optimal design parameters, determined through the calculation of the best compromise solution, are the mass of the counterweight. It weighs 24.24 kg, and the thruster installation angle is... It is 4.5 High initial stability of the water surface The diameter is 91.9 mm, which meets the stability constraints; the maximum angle of attack achievable during underwater navigation is... It is 14.7 Maximum elevation angle It is 15.6 It satisfies the pitch angle symmetry constraint and the ultimate pitch angle constraint; the ascent height for every 10m horizontal movement after reaching the maximum pitch angle. The depth is 2.13m, and the diving height is 10m for every horizontal movement. The depth is 1.82m, which meets the diving / ascent height constraints.

[0142] In summary, the optimal compromise solution of the Pareto front obtained by the method described in this invention satisfies all kinds of constraints and optimizes the surface stability and underwater motion performance of the dual-mode unmanned sailboat.

[0143] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. For those skilled in the art, other variations or modifications can be made based on the above description. It is impossible to exhaustively list all the implementation methods here. All obvious variations or modifications derived from the technical solutions of the present invention are still within the protection scope of the present invention.

Claims

1. A method for determining the optimal surface stability and underwater motion performance of a dual-mode unmanned sailboat, characterized in that, Includes the following steps: Step 1: Based on the ship stability code, calculate the initial metacentric height of the sailboat under different weight masses and determine the range of the initial metacentric height; Step 2: Calculate the hull restoring moment and wind heeling moment, and determine the static and dynamic heel angles to further narrow down the range of the hull's initial stability. Step 3: Calculate the underwater stability height and establish an underwater motion model to obtain the hydrodynamic coefficients; Step 4: Perform simulation based on the underwater motion model to calculate the limiting pitch angle and ascent / descent height performance under different parameters; Step 5: Construct a multi-objective optimization model and solve for the optimal parameter combination; select the best compromise scheme based on the ideal point method, and determine the final weight of the hammer and the installation angle of the thruster.

2. The method according to claim 1, characterized in that, Step 2 includes: Step 2-1: Obtain the coordinates of the center of buoyancy of the hull model before and after tilting around the center of gravity, and fit the curve of the change of the restoring moment. Step 2-2: Establish the aerodynamic model of the wing sail and fit it to obtain the wind tilt moment variation curve; Steps 2-3: Based on the two torque change curves mentioned above, obtain the static and dynamic tilt angles. According to engineering safety requirements, further narrow down the applicable range of the counterweight mass and the applicable range of high initial stability.

3. The method according to claim 1, characterized in that, Step 3 includes: Step 3-1: Obtain the underwater center of gravity and center of buoyancy of the hull, and calculate the underwater stability height and initial pitch angle; Step 3-2: Simplify underwater motion into a three-degree-of-freedom problem in the vertical plane and establish kinematic and dynamic equations; Step 3-3: Simulate and solve for the hydrodynamic coefficients.

4. The method according to claim 3, characterized in that, Step 3-3 includes: Step 3-3-1: Obtain the drag coefficient through straight-line simulation; Step 3-3-2: Obtain the correlation coefficients between vertical force and pitch moment through slant flight simulation; Step 3-3-3: Obtain acceleration correlation coefficients through unsteady simulation of pure heave / pure pitch; Step 3-3-4: Obtain the sway-added mass coefficient through transient acceleration simulation; Step 3-3-5: Obtain the rudder force and torque coefficient through horizontal rudder angle of attack simulation.

5. The method according to claim 4, characterized in that, Step 3-3-4 specifically involves: First, a constant velocity simulation is used to obtain the steady-state drag. Then, the inlet velocity is changed from constant velocity to constant acceleration, and the instantaneous drag during acceleration is obtained using transient simulation. The sway-additional mass coefficient is calculated from the instantaneous resistance and steady-state resistance.

6. The method according to any one of claims 3-5, characterized in that, Step 4 specifically involves: A simulation model was built based on the aforementioned kinematic and dynamic equations. To simulate a typical scenario where the ship accelerates from a stable state and performs surfacing or diving maneuvers, the initial conditions for the simulation are set. Simulations were performed to study the hull's motion response under different combinations of hammer mass and thruster installation angle, and the limit pitch angle and ascent / descent height performance under different parameters were calculated.

7. The method according to claim 6, characterized in that, The initial conditions include: The initial sway velocity is set to a constant value, while the initial heave velocity and pitch velocity are zero; the initial pitch angle is set to a constant value; the thruster thrust is set to a fixed operating value; and the horizontal rudder is set to full rudder position to simulate extreme handling conditions.

8. The method according to claim 1, characterized in that, Step 5 includes: Step 5-1: Fit the surface stability function to the initial stability height of the water surface and the mass of the counterweight; fit the underwater limit pitch angle, the mass of the counterweight and the thruster installation angle to obtain the underwater pitch angle model. Step 5-2: Based on Step 5-1, define a mathematical model for a constrained multi-objective optimization problem; Step 5-3: Use the NSGA-II algorithm to optimize the solution and obtain a set of Pareto optimal solutions; Step 5-4: Select the best compromise based on the ideal point method to determine the final weight of the hammer and the installation angle of the thruster.

9. The method according to claim 8, characterized in that, Step 5-2 includes: Step 5-2-1: Define the adjustable parameters that affect performance as optimization variables; Step 5-2-2: Define water surface stability and the absolute value of the maximum pitch angle as performance indicators that need to be optimized simultaneously; Step 5-2-3: Define the constraints for the multi-objective optimization problem, including: The initial stability of the water surface should not be lower than the set minimum value to meet basic safety requirements; The difference between the absolute values ​​of the downward and upward limit pitch angles should not exceed the set value to avoid controllability imbalance; The absolute values ​​of both the downward and upward limit pitch angles do not exceed the set values ​​to ensure the safety of underwater navigation; The ascent / descent height for each horizontal movement should not be lower than the set value.

10. The method according to claim 8 or 9, characterized in that, Step 5-4 includes: Step 5-4-1: Define the ideal point as the point formed by the individual optimal values ​​of each objective; Step 5-4-2: Normalize the Pareto solution set to eliminate the influence of dimensions; Step 5-4-3: Calculate the Euclidean distance from each solution to the ideal point, and select the solution with the smallest distance as the best compromise solution.

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