A generalized multi-oil-capsule underwater vehicle dynamics modeling method

Abstract

The application discloses a kind of generalization multi-oil-bag underwater vehicle dynamics modeling method.The method first determines the number of oil tank and oil bag in buoyancy system by parameterization definition and determines its decision variable space;Subsequently, the position matrix of each unit is determined using the optimization algorithm based on Gaussian distribution;Then, the mass and volume redistribution model is established, and the dynamic gravity and dynamic buoyancy of the whole machine are accurately calculated according to the oil transfer amount;Based on the relative position of dynamic center of gravity and floating center, the restoring torque model is established;Finally, the six-degree-of-freedom kinematics and dynamics equations are constructed by integrating the attitude adjustment mechanism driving torque and hydrodynamic load.The application breaks the limitation of traditional model only adapting single configuration, has strong generalization, can accurately describe the dynamic drift effect of center of gravity and floating center under the coordinated control of multiple units, and significantly improves the motion prediction accuracy of complex configuration underwater vehicle in deep sea environment.

Description

Technical Field

[0001] This invention belongs to the field of underwater vehicle design and automatic control technology, and particularly relates to a generalized multi-fuel bladder underwater vehicle dynamics modeling method. Background Technology

[0002] Underwater vehicles are key equipment for ocean exploration, resource development, and deep-sea operations, playing an irreplaceable role in marine scientific research and military defense. With the continuous increase in exploration depth, extending from shallow-sea observation to exploration of the deep sea at depths of tens of thousands of meters, underwater vehicles are developing towards higher payload capacity, longer endurance, and greater maneuverability. To achieve precise depth control and attitude adjustment in complex underwater environments, buoyancy control systems have become the core actuators of underwater vehicles. Especially in gliding underwater vehicles, the transfer of oil between internal fuel tanks and external fuel bladders via pump units, changing the displacement volume to generate net buoyancy, is the foundation for their low-energy reciprocating motion. As platform size increases, to improve adjustment efficiency and trim capabilities, modern underwater vehicles are increasingly adopting complex configurations with multiple fuel bladders and tanks, which places higher demands on the generalization and accuracy of dynamic modeling.

[0003] However, existing underwater vehicle dynamics modeling methods primarily focus on single buoyancy adjustment units, resulting in relatively fixed model configurations that are difficult to adapt to diverse fuel bladder layouts. Current technologies typically treat the center of gravity and center of buoyancy during buoyancy adjustment as constant or simplified, neglecting the dynamic eccentric torque generated by the migration of fuel at different locations within the hull. For ton-class or heavy-load vehicles, the redistribution of fuel between multiple fuel bladders and tanks causes significant drift in the overall center of gravity and center of buoyancy, a nonlinear coupling relationship that traditional simplified models cannot accurately describe. Furthermore, existing models lack in-depth analysis of the evolution of restoring torque under multi-unit coordinated control, leading to insufficient attitude prediction accuracy in complex configurations. Therefore, constructing a generalized dynamic model capable of uniformly describing multiple buoyancy units and accurately capturing the dynamic evolution of the center of gravity / center of buoyancy has become a pressing technical challenge in the design and control of deep-sea operational platforms. Summary of the Invention

[0004] To address the problem that existing technologies suffer from insufficient accuracy and poor generalization in dynamic modeling of complex underwater vehicles due to the single configuration and fixed modeling rules of the buoyancy system, which makes it difficult to accurately describe the dynamic weight / buoyancy center drift effect caused by oil mass migration and displacement volume changes when dealing with the coordinated control of multiple buoyancy units, this invention provides a generalized multi-oil bladder underwater vehicle dynamic modeling method.

[0005] This invention provides a generalized multi-fuel-bag underwater vehicle dynamics modeling method, characterized by the following steps:

[0006] S1. Parameterized Definition of Buoyancy System Configuration: Determine the number of fuel tanks in the buoyancy system based on the mission requirements of the underwater vehicle. and the number of oil sacs And define the decision space of each unit in the body coordinate system; S2. Optimized Layout: Within the decision space, the layout is determined through an optimization algorithm. One fuel tank and The position coordinates of each oil sac are used to form a position matrix; S3. Mass redistribution modeling: Based on the amount of oil transferred between the oil tank and the oil bladder, calculate the mass change of each equivalent mass point, and obtain the dynamic gravity and center of gravity of the whole machine through gravity superposition. S4. Multi-buoyancy unit superposition modeling: The total buoyancy is decomposed into static buoyancy of the fuselage and dynamic buoyancy components generated by multiple oil bladders. The total buoyancy of the whole machine and the position of the center of buoyancy are obtained by superimposing the components. S5. Restoring torque modeling: Based on the relative positional relationship between the dynamic center of gravity and the dynamic center of buoyancy, a restoring torque model of gravity and buoyancy in the body coordinate system is established; S6. Construction of Six-Degree-of-Freedom Dynamic Equations: Combining the dynamic gravity, total buoyancy, restoring torque, and external loads, construct the six-degree-of-freedom kinematic and dynamic equations of the underwater vehicle.

[0007] In the above technical solution, preferably, the process of determining the position matrix in step S2 includes: defining the coordinates of the fuel bladder and fuel tank in the longitudinal, lateral, and vertical directions of the engine body as variables, introducing a Gaussian distribution-based allocation algorithm, and optimizing the solution with torque balance efficiency as the objective function to determine the position coordinates of each fuel tank. and the coordinates of each oil sac position .

[0008] In the above technical solution, preferably, the dynamic gravity of the whole machine mentioned in step S3... The matrix representation in the geodetic coordinate system is as follows:

[0009] in, For the weight of the spacecraft itself, For the first The gravitational component caused by changes in the oil level in each fuel tank For the first The gravitational component caused by changes in the oil content within each oil sac.

[0010] In the above technical solution, preferably, the total buoyancy mentioned in step S4... Represented in the geodetic coordinate system as:

[0011] in, For the static buoyancy of the body, For the first The dynamic buoyancy generated by the change in the volume of water discharged from each oil bladder.

[0012] In the above technical solution, preferably, step S4 further includes establishing the force matrix of each oil bladder's buoyancy in the body coordinate system. :

[0013] in, The pitch angle, This refers to the roll angle.

[0014] In the above technical solution, preferably, the external load in step S6 includes the driving torque generated by the attitude adjustment mechanism and the hydrodynamic load; the driving torque is generated by a movable mass block that moves along the longitudinal axis of the body and an eccentric mass block that rotates around the axis of the body.

[0015] In the above technical solution, preferably, the modeling process of the hydrodynamic load includes: calculating viscous hydrodynamics using a linear hydrodynamic model, describing inertial hydrodynamics using an additional mass term, and uniformly representing it through a hydrodynamic coefficient matrix with respect to the pose state variables.

[0016] In the above technical solution, preferably, after the six-degree-of-freedom dynamic equations are constructed, the motion model solution step is also included: introducing initial values ​​of state variables, using the Runge-Kutta integral algorithm to numerically solve the dynamic equations, and outputting the motion state information of the vehicle.

[0017] The generalized multi-fuel bladder underwater vehicle dynamics modeling method provided in this invention has the following beneficial effects: This invention has strong generalizability and versatility. By parametrically defining the number and location of fuel tanks and fuel bladders in the buoyancy system, it breaks the limitation of existing modeling methods that can only target a single buoyancy adjustment unit or a fixed configuration. It can achieve unified modeling of multiple buoyancy adjustment units introduced at different locations on the body, effectively adapting to the diverse configurations and application scenarios of gliding underwater vehicles, ranging from hundreds of kilograms to tons and from shallow seas to deep abysses.

[0018] This invention significantly improves the accuracy and descriptive capability of the dynamic model. By establishing a mass redistribution model and a multi-buoyancy unit superposition model, it deeply analyzes the dynamic changes in mass caused by the transfer of oil between multiple oil tanks and oil bladders, and accurately captures the total buoyancy and the real-time displacement of the center of buoyancy by combining the changes in the drainage volume of each oil bladder. This modular modeling approach overcomes the shortcomings of existing technologies that ignore the dynamic influence of the center of gravity and the center of buoyancy, and can realistically and accurately reflect the complex influence of the coordinated control of multiple buoyancy units on the overall attitude and motion characteristics of the aircraft.

[0019] This invention, by introducing an optimization layout algorithm based on Gaussian distribution, enables the scientific allocation of the spatial positions of multiple fuel tanks and fuel bladders under the constraints of the aircraft structure, greatly enhancing the rationality of the buoyancy system design. Combined with the established six-degree-of-freedom dynamic equations, this invention provides reliable theoretical support for the performance analysis, control theory research, and engineering design of multi-fuel bladder underwater vehicles, filling a research gap both domestically and internationally in the dynamic description of coordinated control of multiple buoyancy units, and possesses significant engineering application value. Attached Figure Description

[0020] Figure 1 This is the flowchart described in this invention; Figure 2 This is a comparison diagram of different arrangements of fuel tanks and fuel bladders as described in this invention; Figure 3 This is a schematic diagram of the fuel tank bladder described in this invention; Figure 4 These are schematic diagrams of the mass redistribution model and the buoyancy model; Figure 5 This is a schematic diagram of the coordinate axes described in this invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0022] This invention provides a generalized dynamics modeling method for underwater vehicles with multiple fuel bladders. To further illustrate the structure of this invention, a detailed description is provided below with reference to the accompanying drawings: Please see Figure 1 This embodiment discloses a generalized multi-fuel bladder underwater vehicle dynamics modeling method, which is mainly applied to gliding or long-range autonomous underwater vehicles, especially for work platforms that need to perform high-load, high-precision buoyancy adjustment in extreme environments such as 10,000-meter deep abysses.

[0023] The first step in this embodiment of the invention is to perform parameterized definition of the buoyancy system configuration. In the preliminary design phase of an underwater vehicle, the number of fuel tanks in the buoyancy system must be predetermined based on specific mission requirements (such as pressure resistance requirements due to operating depth, buoyancy reserve requirements due to total displacement, etc.) and the extremely limited space constraints within the vehicle. and the number of oil sacs Here and All are positive integers. Please refer to [link / reference]. Figure 2 and Figure 3 This illustrates the arrangement of fuel tanks and fuel bladders. Through this parametric definition, this method overcomes the limitations of traditional models that can only adapt to a single fuel bladder or fixed structure, achieving generalized support for complex heterogeneous configurations such as "front-mounted and rear-mounted fuel bladders" and "multi-tank cooperative drive." In this process, this embodiment also needs to define the decision space of each unit in the airframe coordinate system, that is, to clarify the physical boundary constraints that allow for the arrangement of fuel tanks and fuel bladders within the aircraft's sealed compartment.

[0024] After defining the parametric configuration, this embodiment performs a position optimization layout step. This step aims to accurately locate the installation positions of each fuel tank and fuel bladder within a predefined decision space using an optimization algorithm, thereby forming the core position matrix. First, the body coordinate system is established. Please see Figure 5 The origin Located at the center of gravity of the aircraft design, The axis points towards the bow along the longitudinal axis of the aircraft. The axis points to the starboard side. The axis is vertically downwards. [The following is likely a separate, unrelated sentence:] [Will...] One fuel tank and The position coordinates of each oil bladder in the longitudinal, lateral, and vertical directions are defined as the decision variables to be solved. To achieve the highest attitude control sensitivity while ensuring static stability, this embodiment introduces a Gaussian distribution-based allocation algorithm. This algorithm uses torque balance efficiency as the objective function to simulate the contribution rate of oil to the pitch and roll moments of the aircraft when it is transferred at different positions.

[0025] In the specific algorithm implementation, the layable space is sampled using a Gaussian probability density function, and the optimal position combination is searched through iterative calculation. The final determined position matrix contains the position coordinates of each fuel tank. (in ) and the position coordinates of each oil sac (in ).

[0026] In the specific implementation of the algorithm, to balance the globality of the search and the convergence speed, this embodiment presets the maximum number of iterations for the Gaussian distribution-based allocation algorithm to 1000 to 2000 steps. The convergence criterion of the algorithm is monitored in real time using a dual standard: first, the relative rate of change of the objective function value in 100 consecutive iterations is less than a preset threshold of 10. -6 Secondly, the eigenvalues ​​of the covariance matrix of the Gaussian probability density distribution decrease to less than 5% of the initial weights, which indicates that the algorithm has successfully locked the location region of the global optimal solution from the global search.

[0027] Next, this embodiment enters the mass redistribution modeling stage. Please refer to... Figure 4 This step transforms the physical fluid motion within the buoyancy system into the dynamic changes of mass points in the mechanical model. In this modeling process, the oil in each tank and each oil bladder is considered as an equivalent mass point with variable mass. When the buoyancy adjustment system operates, the pump unit drives the oil to transfer in a controlled manner between the internal tank and the external oil bladder, causing the mass of each equivalent mass point to change continuously. This embodiment calculates the amount of oil transferred in real time based on the oil transfer amount estimated by the flow sensor or pump speed. Change in the mass of oil in each tank and the Change in the mass of oil in each oil sac Based on the law of conservation of mass, the total mass of the internal system remains constant when minor losses are ignored, but changes in its distribution can cause a drastic or slight shift in the center of gravity of the entire machine.

[0028] Based on the above equivalent mass model, this embodiment calculates the dynamic gravity of the entire machine in the geodetic coordinate system using the principle of gravity superposition. Geodetic coordinate system Taking a point at sea level as the origin, its The axis points vertically downwards. The total weight of the entire aircraft is fixed by the gravity of the aircraft itself. Real-time gravity components in each fuel tank and the real-time gravity components within each oil bladder Together they constitute, and their mathematical expression is:

[0029] This superimposed modeling method allows the model to reflect in real time the center of gravity shift effect caused by the transfer of oil between units with large longitudinal or lateral spans. Simultaneously, this embodiment calculates the real-time center of gravity coordinates of the entire machine in the machine coordinate system. This coordinate is the sum of the products of the mass of each part and its corresponding position coordinate, divided by the total mass of the entire machine. Due to the center of gravity coordinate... It is updated in real time as the oil is transferred, and it will serve as an important input parameter for subsequent calculation of the restoring torque.

[0030] After completing the mass redistribution modeling and obtaining the dynamic center of gravity position, this embodiment further executes the multi-buoyancy element superposition modeling step (S4). The core logic of this step lies in decomposing the total buoyancy of the underwater vehicle into the sum of a constant static buoyancy force and multiple controlled dynamic buoyancy components. In specific implementation, for a predefined... Each oil bladder has a corresponding volume, and the system monitors the change in drainage volume of each bladder in real time. This volume change is typically measured by pump stroke, pressure balance, or a dedicated displacement sensor. This is combined with the water density at the vehicle's depth. and local gravitational acceleration In this embodiment, the first... The dynamic buoyancy component generated by each oil bladder .

[0031] Specifically, the change in drainage volume of each oil bladder was obtained. In this embodiment, a dual verification method of "sensor measurement and actuator kinematic inverse calculation" is employed. Specifically, for the hydraulic control unit, a high-precision magnetostrictive displacement sensor or a Hall effect-based magnetic induction encoder is embedded in the hydraulic actuator (such as a bidirectional hydraulic piston pump or electric push rod) that drives the oil transfer, thereby monitoring the displacement of the piston or plunger in real time. Combined with the known plunger cross-sectional area Using the formula The nominal drainage volume is calculated directly. Simultaneously, the control system collects the real-time rotational speed of the hydraulic pump motor. With running time Using the flow integral algorithm (in For unit displacement, To cross-check the volumetric efficiency as it changes with pressure, so as to eliminate errors caused by mechanical backlash.

[0032] Considering the significant impact of the extreme high-pressure environment (e.g., 110 MPa) in deep-sea areas on fluid compressibility and structural deformation, this embodiment further introduces a functional correction model of volume change and hydraulic system pressure:

[0033] In this model, Due to the current deep environmental pressure, Standard atmospheric pressure; The effective bulk modulus of hydraulic oil with respect to pressure and temperature is used to correct for the increase in oil density and the reduction in volume caused by high pressure. This is the structural deformation compensation coefficient of the flexible reinforcement material of the oil bladder under hydrostatic pressure, used to correct the slight deformation of the oil bladder wall thickness under compression. Through this function correction model, this embodiment can accurately compensate for the "true drainage contribution" of the oil bladder in the deep-sea environment, effectively solving the technical problem of the inconsistency between nominal displacement and actual buoyancy increment under high pressure, thereby ensuring that the dynamic model has extremely high analytical accuracy across the entire ocean depth range.

[0034] Geodetic coordinate system Below, total buoyancy The vector direction is always with The axes are opposite. The total buoyancy mathematical model constructed in this embodiment is expressed as follows: , in This refers to the static buoyancy force generated by the water displaced by the pressure hull, functional loads, and uncompensated structures of the aircraft. To meet the computational requirements of the six-degree-of-freedom dynamic equations in the body coordinate system, this embodiment also includes converting the total buoyancy force defined in the geodetic coordinate system to the force matrix in the body coordinate system. The coordinate transformation process. This force matrix. It integrates the real-time attitude angle information of the vehicle, and its specific expression is as follows:

[0035] In this formula, Represents pitch angle, Represents the roll angle.

[0036] This model not only quantifies the vertical driving effect of buoyancy, but also accurately describes the projection of the buoyancy component onto the longitudinal and lateral axes of the aircraft when the vehicle is tilted. This is crucial for predicting the horizontal propulsion efficiency and sideslip characteristics of deep-sea gliders.

[0037] After determining the dynamic gravity and total buoyancy of the entire aircraft, this embodiment enters the restoring moment modeling stage (S5). In underwater dynamic equilibrium, the restoring moment is a core element in maintaining the static stability of the vehicle and controlling attitude return. This embodiment constructs this model by establishing the relative geometric relationship between the dynamically changing center of gravity and center of buoyancy. The flow of oil between the internal fuel tank and the external fuel bladder (causing the center of gravity to...) Migration) and controlled expansion and contraction of the oil bladder (leading to total buoyancy) The migration occurs simultaneously, and the traditional assumption that the center of gravity or center of buoyancy is a fixed point is no longer applicable. In this embodiment, the total center of buoyancy position... The value is obtained by weighting the position of the static center of buoyancy of the fuselage and the geometric center positions of each dynamic oil bladder according to their displacement volume. In the fuselage coordinate system, gravity acts on the dynamic center of gravity. Buoyancy acts on the dynamic center of buoyancy When the projections of the two objects in the horizontal plane do not coincide, a restoring torque is generated.

[0038] Specifically, the restoring torque model established in this embodiment is implemented in the body coordinate system via the gravity vector. With buoyancy vector The torques are represented by a superposition. Since the directions of gravity and buoyancy change in real time with the aircraft's attitude in the body coordinate system, the model needs to calculate the torque components that restore the aircraft to equilibrium using cross product operations based on the current three-dimensional coordinates of the center of gravity and center of buoyancy. Through this dynamic coupling modeling, this method can accurately capture the physical essence of the nonlinear change in "center of gravity height" due to oil transfer during high-load adjustment, thus providing a complete static foundation for the subsequent construction of high-precision six-degree-of-freedom dynamic equations.

[0039] To address the roll-pitch coupling caused by center-of-gravity shift in an asymmetrical layout, this embodiment addresses the restoring moment. A detailed matrix expansion analysis is performed. In the body coordinate system, the restoring torque vector is formed by the superposition of the gravitational torque and the buoyancy torque vector, and its analytical expression is expanded as follows:

[0040] In this analytical expression, , ,, and , ,, These are the real-time coordinates of the dynamic center of gravity and the dynamic center of buoyancy in the body coordinate system, respectively. For asymmetric layouts (such as oil bladders along the lateral direction)... Asymmetric arrangement of axes leads to or When the result is not zero, a significant coupling characteristic can be observed from the above equations: roll moment. The pitch angle was introduced in Related items This means that the roll balance of the aircraft will be directly affected by the pitch attitude; more importantly, the yaw moment A term arising from the coupling of lateral offset and pitch motion appeared in the text. This coupling mechanism indicates that when the aircraft experiences a lateral center of gravity deviation, a simple pitch adjustment will induce unexpected yaw motion. Through this precise matrix expansion, this embodiment can quantify this nonlinear coupling disturbance caused by the asymmetric layout, introducing decoupling compensation terms (such as offsetting it through the cooperative rotation of the eccentric mass block) in subsequent control law design. The generated parasitic torque provides a direct mathematical analytical basis, thereby ensuring the attitude robustness of the vehicle during multi-unit coordinated control.

[0041] Building upon the restoration moment modeling, this embodiment further executes the six-degree-of-freedom dynamic equation construction step (S6). This step aims to vector synthesize the aforementioned static and dynamic mechanical components, and by establishing a set of differential equations describing the evolution of the vehicle's attitude and motion state, achieve accurate prediction of the generalized multi-fuel bladder vehicle's trajectory. Specifically, the dynamic model constructed in this embodiment comprehensively considers the driving torque, hydrodynamic loads, and the variable mass effect caused by oil migration.

[0042] First, a detailed model is performed on the driving torque generated by the aircraft's attitude adjustment mechanism. In this embodiment, the driving torque is generated jointly by a longitudinal control mechanism and a lateral control mechanism. The longitudinal control is achieved through the longitudinal axis of the aircraft (…). The attitude control is achieved through a movable mass block that moves along the axis, which changes the longitudinal position of the aircraft's center of gravity, thereby generating a pitch driving torque. Lateral control is achieved through an eccentric mass block that rotates around the aircraft's axis, generating a roll driving torque by changing the angular position of the eccentric mass block. These changes in internal loads are decoupled from the adjustments of the external buoyancy unit, yet they are superimposed in the torque space, together constituting the active attitude control terms of the aircraft.

[0043] This embodiment uses a deep-sea autonomous underwater vehicle with a total displacement of approximately 2000 kg as an example to illustrate the physical parameters and torque mapping relationship of the attitude adjustment mechanism inside the vehicle.

[0044] The internal longitudinal control mechanism uses a movable mass block made of high-density tungsten alloy, whose mass... Set within the range of 25kg to 4kg (preferably 35kg), and installed along the longitudinal axis of the machine body ( On the precision lead screw guide rail arranged on the axis, its maximum effective stroke is ±450 mm. The lateral adjustment mechanism adopts an asymmetrically arranged eccentric mass block, whose mass... Set within the range of 8kg to 15kg (preferably 12kg), the eccentricity (i.e., the radial distance of the center of gravity from the axis of rotation) is... The setting is 80mm to 150mm, and its rotation angle range is ±180°.

[0045] To provide underlying support for the control law, this embodiment establishes an analytical mapping function between displacement / angle and driving torque. When the longitudinal mass block moves relative to the equilibrium position... At that time, the generated pitch driving torque for:

[0046] When the rotation angle position of the lateral eccentric mass block is When (with vertical upward as 0), the resulting roll driving torque and parasitic pitching moment They are respectively:

[0047] Using the aforementioned mapping function, the control system can accurately calculate the distance the stepper motor should drive the mass block to move or the angle of rotation based on the balancing torque required by the six-degree-of-freedom dynamic equations. Specifically, this model introduces... The project successfully captured the minute eccentric disturbances to the pitch angle caused by the rotation of the eccentric block, thereby achieving deep decoupling and coordinated compensation of roll and pitch motions at the control level.

[0048] Secondly, this embodiment provides a refined characterization of the hydrodynamic loads experienced by the underwater vehicle during its motion in the fluid. Since underwater vehicles typically maintain a low-speed cruising state when operating at great depths, this embodiment employs a linear hydrodynamic model to describe the viscous hydrodynamics under conditions of small angles of attack and small sideslip angles. An additional mass term is introduced to describe the inertial hydrodynamics during acceleration. Specifically, the hydrodynamic forces and moments are uniformly represented by a hydrodynamic coefficient matrix relating velocity, angular velocity, angle of attack, and drift angle. This matrix includes key parameters such as the position derivative and velocity derivative. These coefficients accurately capture the hindering and coupling effects of the fluid on the multi-degree-of-freedom motion of the underwater vehicle.

[0049] Regarding the acquisition method and core parameter setting of hydrodynamic coefficients, this embodiment adopts a comprehensive determination method that combines numerical simulation prediction as the main approach and physical experiment verification as a supplement.

[0050] First, this embodiment utilizes CFD (Computational Fluid Dynamics) numerical simulation based on high-precision Reynolds-averaged Navier-Stokes equations to construct a full-scale 3D model of the vehicle on the ANSYS Fluent or Star-CCM+ platform. By dividing the boundary layer mesh into fine details, the flow field distribution of the vehicle at different angles of attack (-10° to 10°) and sideslip angles is simulated, thereby initially calculating the position derivative and velocity derivative. Subsequently, combined with a scaled-down model tank towing test, actual measurements are conducted using a self-made or standard six-component underwater balance at different flow velocities ranging from 0.5 m / s to 2.0 m / s. The CFD data is then corrected using nonlinear regression through the least squares method to eliminate the idealization bias in the turbulence model treatment during numerical simulation.

[0051] To ensure the high reliability of the dynamic equations during the simulation, this embodiment uses typical sailing speeds. A series of core hydrodynamic parameters were set. Regarding drag characteristics, a zero-lift drag coefficient was set. The value ranges from 0.085 to 0.120, used to accurately describe the basic friction and pressure drag of an aircraft during longitudinal straight flight; in terms of lift and stability, the lift line slope... The pitch moment derivative is set between 1.85 and 2.15 rad. The value is set between -0.45 and -0.62 rad to ensure the model can sensitively capture lift fluctuations and longitudinal static stability caused by changes in angle of attack. Simultaneously, to characterize the virtual inertia caused by fluid-body motion, this embodiment adds an axial mass coefficient. The vertical additional mass factor is set to 0.05 to 0.08. Set to 0.85 to 0.95.

[0052] Furthermore, to address complex motions under varying operating conditions, this embodiment also introduces a rotational additional moment of inertia coefficient calculated based on semi-empirical formulas (such as the Hoerner formula). This coefficient is integrated into the hydrodynamic damping matrix of the dynamic equations. Through this multi-method cross-verification approach, the model can not only capture stable cruise characteristics but also accurately characterize the unsteady fluid response of the vehicle at the moment of buoyancy adjustment triggering. This provides high-fidelity dynamic input for subsequent high-precision operation of the control system in complex flow field environments such as deep abysses.

[0053] Finally, in this embodiment, all the force and torque components mentioned above are substituted into Newton-Euler's laws of motion to construct the complete six-degree-of-freedom kinematic and dynamic equations for the underwater vehicle. The general form of the equations is as follows:

[0054] in, It is a generalized mass matrix that includes the system's own mass and the hydrodynamically added mass; The matrix represents the Coriolis force and centripetal force. The hydrodynamic damping matrix; The restoring force vector is composed of the aforementioned dynamic gravity, total buoyancy, and restoring torque; This is the driving torque vector generated by the attitude adjustment mechanism. The equations constructed in this embodiment not only mathematically guarantee the generalized description of the multi-oil bladder and multi-oil tank system, but also fully present the complex coupling process of "mass redistribution - volume redistribution - real-time torque evolution" in terms of physical mechanism.

[0055] After constructing the six-degree-of-freedom kinematics and dynamics equations of the underwater vehicle, this embodiment further executes the motion model solution step (S8). This step aims to transform the abstract mathematical equations into quantifiable vehicle motion trajectories and state parameters through numerical calculation.

[0056] In practice, it is first necessary to introduce initial values ​​for the state variables. These state variables typically constitute a high-dimensional vector, including the vehicle's position coordinates in the geodetic coordinate system. Attitude angle and linear velocity in the body coordinate system and angular velocity This embodiment utilizes a fourth-order Runge-Kutta integral algorithm to iteratively solve a system of nonlinear differential equations. Within each calculation step, the algorithm calculates the acceleration vector based on the current rate of change of oil volume, the mass block's moving speed, and the real-time hydrodynamic load, and then integrates it to obtain the velocity and attitude information for the next moment. Through iterative iteration, the model can continuously output the vehicle's attitude, velocity, and angular velocity curves throughout the entire mission cycle, providing high-fidelity simulation data support for the design of control laws and stability assessment of the control system.

[0057] This invention defines a generalized configuration of multiple fuel tanks and multiple fuel bladders through parameterization and introduces a Gaussian distribution-based position optimization layout. This scheme not only improves modeling accuracy but also, through redundant spatial design, enables the vehicle to achieve asymmetric torque compensation using the remaining healthy buoyancy units even in single-point failure scenarios such as mechanical failures or hydraulic blockages in some fuel bladders or tanks. This is achieved through the pre-set torque coupling relationship in the position matrix, resulting in a leap in system-level fault-tolerant control and survivability, which has extremely high engineering reliability value in the extreme environment of the deep sea. Secondly, the Gaussian distribution-based optimized layout constrains the evolution trajectory of the dynamic center of gravity and buoyancy within a smaller envelope during the full-range adjustment process, greatly suppressing the violent attitude oscillations caused by large-scale oil migration. This physical "pre-smoothing" effect significantly reduces the decoupling pressure of the airborne control algorithm, enabling the vehicle to maintain a more stable gliding trajectory when transitioning through variable density layers in the deep sea. Thus, without increasing control energy consumption, the optimized structural layout indirectly improves the detection environment quality of the acoustic payload. Finally, due to the adoption of generalized superposition modeling, the sensitivity of the model to the nonlinear viscosity-temperature characteristics of oil is statistically smoothed through the spatial superposition of multiple units. This makes the dynamic adaptability of the vehicle to large-span depth / temperature changes show a significant nonlinear gain compared with the single configuration model, providing a robust guarantee that traditional models cannot match for the fine attitude control of the 10,000-meter-class full-ocean-depth vehicle.

[0058] In summary, the embodiments of this invention construct a universal dynamic model adaptable to various heterogeneous configurations through parameterized definition, optimized position layout, and modular gravity and buoyancy superposition logic. This model not only accurately describes the dynamic coupling evolution of the center of gravity and center of buoyancy in a multi-oil bladder system during adjustment, but also significantly improves the motion prediction accuracy of large, deep-sea, multi-buoyancy unit collaborative control vehicles in complex marine environments by introducing attitude adjustment mechanism torque and refined hydrodynamic loads.

[0059] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A generalized multi-fuel bladder underwater vehicle dynamics modeling method, characterized in that, The method includes the following steps: S1. Parameterized Definition of Buoyancy System Configuration: Determine the number of fuel tanks in the buoyancy system based on the mission requirements of the underwater vehicle. and the number of oil sacs And define the decision space of each unit in the body coordinate system; S2. Optimized Layout: Within the decision space, the layout is determined through an optimization algorithm. One fuel tank and The position coordinates of each oil sac are used to form a position matrix; S3. Mass redistribution modeling: Based on the amount of oil transferred between the oil tank and the oil bladder, calculate the mass change of each equivalent mass point, and obtain the dynamic gravity and center of gravity of the whole machine through gravity superposition. S4. Multi-buoyancy unit superposition modeling: The total buoyancy is decomposed into static buoyancy of the fuselage and dynamic buoyancy components generated by multiple oil bladders. The total buoyancy of the whole machine and the position of the center of buoyancy are obtained by superimposing the components. S5. Restoring torque modeling: Based on the relative positional relationship between the dynamic center of gravity and the dynamic center of buoyancy, a restoring torque model of gravity and buoyancy in the body coordinate system is established; S6. Construction of Six-Degree-of-Freedom Dynamic Equations: Combining the dynamic gravity, total buoyancy, restoring torque, and external loads, construct the six-degree-of-freedom kinematic and dynamic equations of the underwater vehicle.

2. The generalized multi-fuel bladder underwater vehicle dynamics modeling method according to claim 1, characterized in that, The process of determining the position matrix in step S2 includes: defining the coordinates of the fuel bladders and fuel tanks in the longitudinal, lateral, and vertical directions of the fuselage as variables; introducing a Gaussian distribution-based allocation algorithm; and optimizing the solution with torque balance efficiency as the objective function to determine the position coordinates of each fuel tank. and the coordinates of each oil sac position .

3. The generalized multi-fuel bladder underwater vehicle dynamics modeling method according to claim 1, characterized in that, The dynamic gravity of the whole machine mentioned in step S3 The matrix representation in the geodetic coordinate system is as follows: in, For the weight of the spacecraft itself, For the first The gravitational component caused by changes in the oil level in each fuel tank For the first The gravitational component caused by changes in the oil content within each oil sac.

4. The generalized multi-fuel bladder underwater vehicle dynamics modeling method according to claim 1, characterized in that, The total buoyancy mentioned in step S4 Represented in the geodetic coordinate system as: in, For the static buoyancy of the body, For the first The dynamic buoyancy generated by the change in the volume of water discharged from each oil bladder.

5. The generalized multi-fuel bladder underwater vehicle dynamics modeling method according to claim 4, characterized in that, Step S4 also includes establishing the force matrix of each oil bladder's buoyancy in the body coordinate system. : in, The pitch angle, This refers to the roll angle.

6. The generalized multi-fuel bladder underwater vehicle dynamics modeling method according to claim 1, characterized in that, The external loads mentioned in step S6 include the driving torque generated by the attitude adjustment mechanism and the hydrodynamic load; the driving torque is generated by a movable mass block that moves along the longitudinal axis of the machine body and an eccentric mass block that rotates around the axis of the machine body.

7. The generalized multi-fuel bladder underwater vehicle dynamics modeling method according to claim 6, characterized in that, The modeling process of the hydrodynamic load includes: calculating viscous hydrodynamics using a linear hydrodynamic model, describing inertial hydrodynamics using an additional mass term, and uniformly representing it using a hydrodynamic coefficient matrix with respect to the pose state variables.

8. The generalized multi-fuel bladder underwater vehicle dynamics modeling method according to claim 1, characterized in that, After constructing the six-degree-of-freedom dynamic equations, the process also includes solving the motion model: introducing initial values ​​for state variables, using the Runge-Kutta integral algorithm to numerically solve the dynamic equations, and outputting the motion state information of the vehicle.

Images