Method and system for energy capture of a deformable dual float wave energy autonomous underwater vehicle

Abstract

This application relates to the field of wave energy capture technology and discloses a method and system for capturing wave energy in a deformable dual-buoy autonomous underwater vehicle (AUV). The method includes: establishing a mapping table between the deployment angle and the natural frequency of the dual-buoy based on the structural parameters of the deformable buoy; using the deployment angle as a continuous decision variable; calculating the optimal deployment angle and optimal damping coefficient by subtracting the power generation gain component from the additional drag energy consumption component and the attitude maintenance energy consumption component; applying this to the folding mechanism and power output device to form a hybrid operating state; and continuously updating the mapping table based on the deviation between the measured and predicted power generation. This application improves the net wave energy capture efficiency and adaptive operational robustness of the DFWEC-AUV under real irregular sea conditions.

Description

Technical Field

[0001] This application relates to the field of wave energy capture technology, and in particular to a method and system for energy capture of a deformable dual-buoy wave energy autonomous underwater vehicle. Background Technology

[0002] Autonomous underwater vehicles (AUVs) face severe energy bottlenecks in long-endurance deep-sea operations. Traditional AUVs rely on internal batteries with limited capacity, severely restricting their operational range. To overcome this constraint, researchers have deeply integrated an oscillating wave energy converter with the AUV, proposing a deformable dual-buoy wave-powered autonomous underwater vehicle (AUV). The core idea is to design deployable deformable buoys and additional damping plates on the exterior of the AUV. A folding and unfolding mechanism allows the AUV to switch between navigation mode and wave power generation mode. In power generation mode, the AUV body and the deployed deformable buoys together form an oscillating dual-buoy system. Wave excitation on the sea surface causes relative motion between the two buoys, and a power output device converts the mechanical vibration energy into electrical energy, thereby providing autonomous energy replenishment for the AUV.

[0003] However, existing technologies have fundamental flaws in achieving the aforementioned wave energy capture: the deployment angle of the deformable buoy is fixed at full deployment, the PTO damping coefficient is determined offline based on a specific wave period, and the analysis of the two parameters is independent, neither being incorporated into a unified real-time control framework. This fixed fully deployed operating mode completely ignores the energy consumption corresponding to the additional hydrodynamic drag and attitude maintenance torque introduced after the deformable buoy is deployed. The power generation benefits are largely consumed by the additional propulsion energy consumption and attitude maintenance energy consumption. Furthermore, under real irregular sea conditions, the dominant wave frequency continuously drifts, and the natural frequency of the dual-buoy system under fixed parameters is detuned to the actual wave frequency for a long time, resulting in a significant decrease in energy capture efficiency. Existing technologies do not have any adaptive correction mechanism for this. Summary of the Invention

[0004] This application provides a method and system for energy harvesting of wave energy by a deformable dual-buoy wave energy autonomous underwater vehicle. It solves the problems in the prior art where the net power generation is largely consumed by additional energy consumption due to the fixed and fully deployed deformable buoy, and the lack of online correction of the natural frequency prediction model, which leads to continuous detuning under changing sea states. It improves the net wave energy harvesting efficiency and adaptive operation robustness of DFWEC-AUV under real irregular sea states.

[0005] In a first aspect, this application provides an energy harvesting method for a deformable dual-buoy wave-energy autonomous underwater vehicle, the energy harvesting method comprising: Step S1: Based on the structural parameters of the deformable buoy, establish the mapping relationship between the unfolding angle and the natural frequency of the dual-buoy body to obtain the natural frequency mapping table; Step S2: Determine the current natural frequency based on the real-time acquired wave dominant frequency using the natural frequency mapping table. This includes: performing Fourier analysis on the output signal of the airborne pressure sensor array within a 60-second acquisition window to obtain the current wave dominant frequency and significant wave height; inputting the current wave dominant frequency into the natural frequency mapping table and performing a lookup calculation on the continuous interpolation function in the natural frequency mapping table to obtain the current natural frequency; calculating the capture width ratio of the dual-floating body system based on the difference between the current natural frequency and the current wave dominant frequency to obtain the power generation gain component; subtracting the power generation gain component from the additional drag energy consumption component introduced by the increased deployment angle and the attitude maintenance energy consumption component, and using the deployment angle as the only continuous decision variable, solving for the optimal deployment angle and optimal damping coefficient corresponding to the maximum value of the difference among the three components within the continuous interval from fully folded to fully deployed, wherein the optimal deployment angle is less than the fully deployed angle; Step S3: Apply the optimal deployment angle and the optimal damping coefficient to the folding mechanism and the power output device respectively to form a hybrid operating state in which the vehicle drifts along the mission course and captures wave energy simultaneously. Step S4: Continuously update the inherent frequency mapping table based on the deviation between the measured power generation and the predicted power generation under the hybrid operating state, and trigger the re-solution of the optimal expansion angle when the change in the wave dominant frequency exceeds a preset threshold.

[0006] Secondly, this application provides a deformable dual-buoy wave-energy autonomous underwater vehicle energy harvesting system, the deformable dual-buoy wave-energy autonomous underwater vehicle energy harvesting system comprising: The mapping module is used to establish a mapping relationship between the unfolding angle and the natural frequency of the dual-body float based on the structural parameters of the deformable buoy, and to obtain a natural frequency mapping table. The difference module is used to determine the current natural frequency based on the real-time acquired wave dominant frequency and the natural frequency mapping table. This includes: performing Fourier analysis on the output signal of the airborne pressure sensor array within a 60-second acquisition window to obtain the current wave dominant frequency and significant wave height; inputting the current wave dominant frequency into the natural frequency mapping table and performing a lookup calculation on the continuous interpolation function in the natural frequency mapping table to obtain the current natural frequency; calculating the capture width ratio of the dual-floating body system based on the difference between the current natural frequency and the current wave dominant frequency to obtain the power generation gain component; and subtracting the power generation gain component from the additional drag energy consumption component introduced by the increased deployment angle and the attitude maintenance energy consumption component. Using the deployment angle as the only continuous decision variable, the module calculates the optimal deployment angle and optimal damping coefficient corresponding to the maximum value of the difference among the three components within the continuous interval from fully folded to fully deployed. The optimal deployment angle is less than the fully deployed angle. The synchronization module is used to apply the optimal deployment angle and the optimal damping coefficient to the folding mechanism and the power output device respectively, forming a hybrid operating state in which the vehicle drifts along the mission course and captures wave energy synchronously. The triggering module is used to continuously update the inherent frequency mapping table based on the deviation between the measured power generation and the predicted power generation under the hybrid operating state, and to trigger the re-solution of the optimal expansion angle when the change in the wave dominant frequency exceeds a preset threshold.

[0007] Thirdly, a deformable dual-buoy wave-energy autonomous underwater vehicle (AUV) energy harvesting device is provided, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor invokes the instructions in the memory to cause the deformable dual-buoy wave-energy autonomous underwater vehicle energy harvesting device to execute the aforementioned deformable dual-buoy wave-energy autonomous underwater vehicle energy harvesting method.

[0008] Fourthly, a computer-readable storage medium is provided, wherein instructions are stored therein, which, when executed on a computer, cause the computer to perform the above-described energy capture method for a deformable dual-buoy wave-energy autonomous underwater vehicle.

[0009] The technical solution provided in this application establishes a natural frequency mapping table between the deployment angle and the natural frequency of the dual-buoy system, incorporating the continuous deployment angle of the deformable buoy into a unified hydrodynamic quantification framework. This transforms the deployment angle, originally a binary structural parameter used only for mode switching, into a control variable that can be continuously optimized. Based on this, the power generation gain component, the additional drag energy consumption component, and the attitude maintenance energy consumption component are uniformly incorporated into the net power generation objective function. Using the deployment angle as the sole continuous decision variable, the optimal deployment angle and optimal damping coefficient are calculated across the entire range from fully folded to fully deployed, at which the maximum difference among the three components is reached. This breaks the inherent assumption in existing technologies that treat power generation mode and navigation mode as mutually exclusive binary states. It fundamentally eliminates the problem of excessive encroachment of power generation benefits by additional drag energy consumption and attitude maintenance energy consumption due to a fixed full deployment angle, ensuring that the dual-buoy system always operates in the intermediate deployment state with optimal net power generation under different sea conditions. The golden section method has a global convergence guarantee on the single-peak net power generation sequence determined by the inherent frequency mapping table. Its iterative interval reduction calculation logic for the continuous interval of the expansion angle matches the cubic spline interpolation structure of the inherent frequency mapping table. Under the condition of limited airborne computing resources, it can accurately locate the optimal expansion angle with a limited number of iterations, so that the algorithm characteristics are effectively adapted to the engineering constraints of the airborne platform of the aircraft.

[0010] By simultaneously applying the optimal deployment angle and optimal damping coefficient to the folding mechanism and power output device, the vehicle enters a hybrid operating state where wave energy capture and mission heading drift occur simultaneously. The thrusters maintain the set drift speed with minimum compensation power, and power generation and propulsion are completely parallel in time, reducing the cost of mission interruption to zero. This is an operational characteristic not found in existing fully deployed static levitation power generation methods. Furthermore, the radiation damping coefficient in the natural frequency mapping table is continuously updated based on the deviation between the measured and predicted power generation in the hybrid operating state. This continuously improves the prediction accuracy of the mapping table as missions accumulate. When the change in the dominant wave frequency exceeds a preset threshold, the optimal deployment angle is automatically recalculated, forming a complete closed loop of sensing wave condition changes, updating mapping parameters, re-optimizing, and adjusting attitude. This allows the dual-floating-body system to continuously track the optimal net power generation state under irregularly changing real sea conditions, overcoming the fundamental defect in existing technologies where fixed parameters result in a significant decrease in energy capture efficiency under changing sea conditions. Attached Figure Description

[0011] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a schematic diagram of an embodiment of the energy harvesting method for a deformable dual-buoy wave-energy autonomous underwater vehicle in this application. Figure 2 This is a schematic diagram illustrating the mapping relationship between the deployment angle and the natural frequency of the dual-buoy body in an embodiment of this application. Detailed Implementation

[0013] This application provides an energy harvesting method and system for a deformable dual-buoy wave-energy autonomous underwater vehicle. The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" or "having" and any variations thereof are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0014] For ease of understanding, the specific process of the embodiments of this application is described below. Please refer to [link / reference]. Figure 1 One embodiment of the energy harvesting method for a deformable dual-buoy wave-energy autonomous underwater vehicle in this application includes: Step S1: Based on the structural parameters of the deformable buoy, establish the mapping relationship between the unfolding angle and the natural frequency of the dual-buoy body to obtain the natural frequency mapping table; Specifically, the natural frequency mapping table is a discrete correspondence table indexed by the development angle and using the natural heave frequency of the dual-buoy system as the value. After being fitted into a continuous function by cubic spline interpolation, it is stored in the airborne controller. The structural parameters of the deformable buoy include the number of blades, the area of ​​a single blade, the length of the articulated arm, and the diameter of the damping plate. These parameters are all known during the design phase and do not require online measurement. The discrete step length of the development angle is set to 1°, a value that, while meeting interpolation accuracy requirements, keeps the amount of mapping table data within the limits of airborne storage resources. After the natural frequency mapping table is calculated offline on shore, it is written to the airborne read-only storage area. During maritime operations, the vehicle only performs table lookup and interpolation calculations and does not re-establish the mapping relationship.

[0015] Step S2: Based on the real-time collected wave main frequency, determine the current natural frequency using the natural frequency mapping table. Subtract the power generation gain component from the additional drag energy consumption component and attitude maintenance energy consumption component introduced by the increased deployment angle. Using the deployment angle as the only continuous decision variable, solve for the optimal deployment angle and optimal damping coefficient corresponding to the maximum value of the difference among the three components in the continuous interval from fully folded to fully deployed. The optimal deployment angle is less than the fully deployed angle. Specifically, the power generation gain component, the additional drag energy consumption component, and the attitude maintenance energy consumption component together constitute the complete energy balance of net power generation. The power generation gain component is determined by the difference between the current wave dominant frequency and the natural frequency obtained from the natural frequency mapping table. The smaller the difference, the closer the dual-buoy system is to resonance, and the higher the power generation. The additional drag energy consumption component is determined by the increase in hydrodynamic drag caused by the expansion of the blade's frontal projected area after the deployment angle increases. This increase monotonically increases with the deployment angle. The attitude maintenance energy consumption component is determined by the buoyancy eccentric torque formed by the product of the blade's submerged volume and the articulated arm length after deployment. This torque needs to be balanced by the continuous output torque of the side thrusters. All three components are continuous functions of the deployment angle, and their differences exhibit a single-peak distribution within the continuous interval from fully folded to fully deployed. The optimal deployment angle is the deployment angle value corresponding to this single peak. This value is necessarily smaller than the fully deployed angle. This is an inevitable result determined by the physical properties of the three components, rather than an artificial limitation.

[0016] Step S3: Apply the optimal deployment angle and the optimal damping coefficient to the folding mechanism and the power output device respectively to form a hybrid operating state in which the vehicle drifts along the mission course and captures wave energy simultaneously. Specifically, the hybrid operating state refers to the spacecraft's operational state after three states are simultaneously established: the folding mechanism is locked at the optimal unfolding angle, the power output device's damping coefficient is adjusted to the optimal damping coefficient, and the thrusters continuously output compensating thrust along the mission heading at a set drift speed. The set drift speed is the spacecraft's lowest stable propulsion speed, a value determined by the thrusters' factory calibration parameters and maintained constant during the hybrid operating state. In the hybrid operating state, wave energy capture and mission heading propulsion are synchronized, which is fundamentally different in physical state from the existing technology's static hovering power generation mode where the spacecraft waits to be charged.

[0017] Step S4: Continuously update the inherent frequency mapping table based on the deviation between the measured power generation and the predicted power generation under the mixed operation state, and trigger the re-solution of the optimal unfolding angle when the change in the wave dominant frequency exceeds the preset threshold.

[0018] Specifically, the predicted power generation is given by the calculation results of the natural frequency mapping table under the current wave dominant frequency and the actual development angle, while the measured power generation is given by the average value collected by the sensor at the output end of the power output device. The difference between the two reflects the degree of deviation between the radiation damping coefficient in the mapping table and the actual sea state. The radiation damping coefficient is a parameter in the linear wave force model that characterizes the rate of outward energy radiation. Its initial value is calibrated by hydrodynamic simulation, but it has a systematic deviation under real irregular sea states and needs to be continuously corrected by measured data. The preset threshold is set to a wave dominant frequency difference of 0.05 rad / s between two adjacent 60-second detection cycles. This value corresponds to a detuning amount in the natural frequency mapping table where the capture width ratio decreases by more than 15%. When this threshold is exceeded, the current optimal development angle is no longer at the position of maximum net power generation, and it must be solved again.

[0019] In one specific embodiment, step S1 includes: Based on the number of blades, the area of ​​a single blade, and the length of the articulated arm of the deformable buoy, the projected area of ​​the blades on the waterline at each deployment angle is calculated to obtain the waterline area sequence. Based on the waterline area sequence, the hydrodynamic restoring stiffness is calculated by multiplying the sum of the waterline area and the waterline area sequence of the vehicle body by the seawater density and gravitational acceleration, and the stiffness sequence is obtained. Based on the stiffness sequence and the equivalent mass of the system at each deployment angle, the square root of the ratio of stiffness to mass is calculated. The equivalent mass of the system is the sum of the mass of the vehicle body and the mass of the deformable buoy, plus the additional mass at that deployment angle. The natural frequency values ​​corresponding to each deployment angle are obtained. The correspondence between the deployment angle and the natural frequency values ​​is fitted as a continuous function by cubic spline interpolation to obtain the natural frequency mapping table.

[0020] Specifically, the waterline area sequence is a discrete sequence indexed by the deployment angle and defined as the sum of the projected areas of each blade of the deformable buoy on the still water surface at the corresponding deployment angle. The projected area of ​​each blade on the waterline is equal to the product of the area of ​​a single blade and the cosine of the deployment angle. Multiplying the number of blades by this product yields the buoy's waterline area at a single deployment angle. The sequence is calculated point-by-point across the entire range from fully folded to fully deployed, with a step size of 1° for the deployment angle, to obtain the complete waterline area sequence. The stiffness sequence is a discrete sequence indexed by the deployment angle and defined as the hydrodynamic restoring stiffness of the dual-buoy system at the corresponding deployment angle. It is calculated by adding the waterline area of ​​the vehicle body to the waterline area of ​​the buoy at the corresponding deployment angle in the waterline area sequence, and then multiplying by the seawater density of 1025 kg / m³. 3 With gravitational acceleration of 9.81 m / s² 2 The seawater density is taken as the standard seawater density, and the gravitational acceleration is taken as the standard gravitational acceleration. Both are physical constants and do not require on-site measurement.

[0021] The natural frequency values ​​are obtained by dividing the hydrodynamic restoring stiffness of the corresponding development angle in the stiffness sequence by the square root of the equivalent mass of the system at that development angle. The equivalent mass of the system is the sum of the mass of the vehicle body and the mass of the deformable buoy, plus the additional mass at that development angle. The additional mass is stored in the form of a table after hydrodynamic simulation is performed offline on shore. The vehicle directly looks up the value in the table during operation at sea. The discrete node set consisting of each development angle and the corresponding natural frequency value is input into a cubic spline interpolation operation. Adjacent nodes are connected by cubic polynomials. The resulting continuous function is the natural frequency mapping table. The cubic spline interpolation ensures the continuity of function values, first derivatives, and second derivatives at the nodes. Under the condition of a 1° node spacing, the interpolation error meets the accuracy requirements for subsequent table lookup. The natural frequency mapping table is written into the read-only memory area of ​​the airborne controller in the form of an interpolation coefficient array for real-time table lookup after subsequent wave frequency acquisition.

[0022] Figure 2 This is a schematic diagram illustrating the mapping relationship between the deployment angle and the natural frequency of the dual-buoy system in this embodiment. The horizontal axis represents the deployment angle θ of the deformable buoy, ranging from 0° to 90°, and the vertical axis represents the natural frequency of the dual-buoy system, in rad / s. The solid line is the mapping curve showing the continuous change of the natural frequency with the deployment angle. This curve is obtained by cubic spline interpolation and shows a monotonically decreasing trend as the deployment angle increases, reflecting the physical law that the rate of increase in added mass exceeds the rate of increase in hydrodynamic restoring stiffness due to the increase in deployment angle. The horizontal dashed line indicates the typical wave dominant frequency of 0.8 rad / s. The horizontal dashed line intersects the mapping curve at the point where the natural frequency is equal to the wave dominant frequency. A vertical dotted line is drawn from this intersection point towards the horizontal axis. The intersection of the vertical dotted line and the horizontal axis is the resonant deployment angle of 61° at the current wave dominant frequency. At this deployment angle, the natural frequency of the dual-buoy system is equal to the wave dominant frequency, the capture width ratio reaches its maximum value, and the power generation gain component reaches its peak value within this deployment angle range.

[0023] In one specific embodiment, step S2, determining the current natural frequency based on the real-time acquired wave dominant frequency using a natural frequency mapping table, includes: Based on the output signal of the airborne pressure sensor array within a 60-second acquisition window, Fourier analysis is performed on the output signal to obtain the current wave dominant frequency and significant wave height. Input the current wave dominant frequency into the natural frequency mapping table, and perform a lookup calculation on the continuous interpolation function in the natural frequency mapping table to obtain the current natural frequency; Based on the difference between the current natural frequency and the current dominant wave frequency, the capture width ratio of the dual-floating body system is calculated to obtain the power generation gain component.

[0024] Specifically, the airborne pressure sensor array consists of four pressure sensors evenly distributed at the bow and stern of the vehicle. Each sensor continuously acquires water pressure signals at a sampling rate of 100 Hz, with a acquisition window set to 60 seconds. This duration corresponds to the data volume of at least three complete wave cycles within the typical deep-sea wave cycle range of 5 to 20 seconds, meeting the minimum signal length requirement for Fourier analysis. A Fast Fourier Transform (FFT) is performed on the pressure time series within the 60-second window, converting the time-domain signal into a frequency-domain power spectrum. The frequency component with the largest amplitude in the power spectrum is taken as the current wave dominant frequency, and the effective wave height of the corresponding time-domain signal is taken as the root mean square statistic of the difference between the wave crest and trough. Substituting the current wave dominant frequency into the cubic spline interpolation continuous function of the natural frequency mapping table, the natural frequency corresponding to the current unfolding angle is obtained, which is the current natural frequency.

[0025] The capture width ratio is a dimensionless coefficient describing the ratio of the actual wave energy power captured by a dual-floating-body system to the incident wave energy power under the current wave condition. Its value is determined by the difference between the current natural frequency and the current dominant wave frequency: when the difference is zero, the dual-floating-body system is in a resonant state, and the damped energy dissipation power ratio of the single-degree-of-freedom forced vibration system reaches its maximum value; as the difference increases, the damped energy dissipation power ratio monotonically decreases according to the linear wave force frequency domain response model. Since the mechanical vibration energy captured by the dual-floating-body system from wave excitation must be converted into electrical energy by a power output device, the capture width ratio is calculated by multiplying the aforementioned damped energy dissipation power ratio by the overall efficiency coefficient of the power output device. This coefficient, encompassing generator electromagnetic conversion efficiency, rectification loss, and transmission friction loss, was calibrated using a shore-based test bench and is set to 0.78. The specific formula for calculating the capture width ratio (CWR) is as follows:

[0026] This formula is equivalent to:

[0027] in, The natural frequency corresponding to the current expansion angle, in units of ; The current wave frequency, in units of ; The system damping ratio is taken as the measured calibration value of 0.15. The overall efficiency coefficient of the power output device, encompassing generator electromagnetic conversion efficiency, rectification loss, and transmission friction loss, is taken as 0.78 from the shore-based test calibration value. hour, Capture width ratio is taken as the maximum value The dual-buoy system is in a resonant state; when Deviation , As it increases, the capture width decreases monotonically.

[0028] The system damping ratio is taken as the measured calibration value of 0.15. The power generation gain component is given by the product of the capture width ratio, the square of the current effective wave height, and the wave excitation force coefficient. The wave excitation force coefficient is stored in the airborne data table after being calibrated offline on shore by hydrodynamic simulation. The unit of the power generation gain component is watts, which serves as the first input for the subsequent subtraction calculation of the three components of net power generation.

[0029] In one specific embodiment, step S2 involves subtracting the power generation gain component from the additional drag energy consumption component introduced by the increased deployment angle and the attitude maintenance energy consumption component, including: Based on the frontal projected area of ​​the blades at each deployment angle, seawater density, drag coefficient, and set drift speed, the additional drag energy consumption component is calculated by dividing the product of the additional hydrodynamic drag increment and the set drift speed by the thruster efficiency. Based on the buoyancy eccentricity moment determined by the product of the blade submerged volume, seawater density, gravitational acceleration and the horizontal component of the blade submerged section in the articulated arm length at each deployment angle, the energy consumption component for attitude maintenance is calculated by dividing the product of the buoyancy eccentricity moment and the attitude control angular velocity by the side thruster efficiency. The net power generation sequence corresponding to each expansion angle is obtained by subtracting the power generation gain component from the additional drag energy consumption component and the attitude maintenance energy consumption component.

[0030] Specifically, the additional drag energy consumption component is the extra power consumption of the propeller caused by the increase in the frontal projected area of ​​the blades after the deformable buoy deploys. The frontal projected area of ​​the blades at each deployment angle is equal to the product of the area of ​​a single blade and the sine of the deployment angle, multiplied by the number of blades; this area increases monotonically with the deployment angle. The increment of additional hydrodynamic drag is given by multiplying the product of the frontal projected area of ​​the blades, seawater density, drag coefficient, and the square of the set drift velocity by half. The drag coefficient is taken as 1.2, a value obtained from the calibration of the deformable buoy physical model through a tank towing experiment. The set drift velocity is taken as 0.3 m / s, which is the minimum propulsion speed that the propeller can stably output, determined by the propeller's factory calibration parameters. The additional drag energy consumption component is obtained by dividing the product of the additional hydrodynamic drag increment and the set drift velocity by the propeller efficiency. The propeller efficiency is taken as the measured calibration value of 0.65, a value determined under the rated operating conditions of the vehicle by the ratio of the propeller output shaft power to the input electrical power. The buoyancy eccentricity moment is the roll moment formed by the lateral shift of the outer float's buoyancy center relative to the vehicle's center of gravity after the deformable buoy is deployed. It is given by the product of the blade's submerged volume, seawater density, gravitational acceleration, and the horizontal component of the blade's submerged section in the articulated arm length at each deployment angle. This moment increases first with the deployment angle and then slows down after the deployment angle exceeds 45°.

[0031] The formula for calculating the buoyancy eccentricity moment is as follows:

[0032] in, For the development angle The water volume of each leaf blade. Let the density of seawater be taken as... , Let be the acceleration due to gravity, and take . , This is the horizontal component of the blade submerged section in the length of the articulated arm, which is the horizontal offset distance of the buoyancy point relative to the center of gravity of the aircraft.

[0033] The attitude maintenance energy consumption component is the power consumed by the side thrusters to continuously counteract the buoyancy eccentricity moment and maintain the vehicle's vertical attitude. The side thruster output torque is equal to the buoyancy eccentricity moment. The attitude control angular velocity is given by the steady-state output value of the attitude controller's proportional-integral-derivative control law when the roll angle deviation does not exceed 2°. This value is calibrated through attitude controller parameter tuning experiments. The attitude maintenance energy consumption component is obtained by dividing the product of the buoyancy eccentricity moment and the attitude control angular velocity by the side thruster efficiency, which is taken as the measured calibration value of 0.60. The net generated power sequence is a discrete sequence indexed by the deployment angle, with the value being the difference between the generated power gain component at the corresponding deployment angle and the additional drag energy consumption component, and then the attitude maintenance energy consumption component. The deployment angle step size is consistent with the natural frequency mapping table, both being taken as 1°. The net power generation function exhibits a single-peak distribution across the continuous range from fully folded to fully deployed. At the fully folded angle, the blades are not deployed, the deformable buoy does not contribute to an effective increase in waterline area, the dual-buoy system cannot form effective oscillations, the power generation gain component is zero, the blade frontal projection area is zero, the submerged volume is zero, and the additional drag energy consumption component and attitude maintenance energy consumption component are also zero, resulting in zero net power generation. As the deployment angle increases from the fully folded angle, the increased waterline area causes the natural frequency of the dual-buoy system to gradually approach the dominant wave frequency, and the power generation gain component rises rapidly. The additional drag energy consumption component is proportional to the increase in the blade frontal projection area with the sine of the deployment angle, and the attitude maintenance energy consumption component is proportional to the product of the submerged volume and the horizontal component of the articulated arm. In the small deployment angle range, the growth rates of both are lower than the rise rate of the power generation gain component, resulting in a positive and continuously increasing net power generation. At the resonant deployment angle, the natural frequency equals the dominant wave frequency, and the power generation gain component reaches its maximum value. Beyond the resonant unfolding angle, the natural frequency continues to decrease, deviating from the dominant wave frequency. The capture width ratio decreases monotonically according to the aforementioned formula, and the power generation gain component decreases accordingly. Simultaneously, the additional drag energy consumption component and the attitude maintenance energy consumption component continue to increase monotonically, and the net power generation begins to decrease. At the fully unfolded angle, the power generation gain component decays significantly to near zero due to the severe detuning between the natural frequency and the dominant wave frequency, while the additional drag energy consumption component and the attitude maintenance energy consumption component both reach their maximum values, and the net power generation drops to a negative value. In summary, the net power generation is zero at the left end of the interval, positive inside the interval, and negative at the right end of the interval. Furthermore, the power generation gain component is uniquely determined by the monotonically decreasing characteristic of the natural frequency mapping curve, and there is only one maximum point at the resonant unfolding angle without any local rebound. The additional drag energy consumption component and the attitude maintenance energy consumption component are both monotonically increasing functions of the unfolding angle without any local decline. Therefore, the difference between the three components has only one maximum point in the continuous interval from fully folded to fully unfolded, exhibiting a single-peak distribution. This single-peak characteristic ensures the global convergence of the golden section method, and the peak point of the net power generation sequence is the location of the target interval for subsequent golden section method search.

[0034] In one specific embodiment, step S2 uses the unfolding angle as the only continuous decision variable, and calculates the optimal unfolding angle and optimal damping coefficient corresponding to the maximum difference among the three factors within the continuous interval from fully folded to fully unfolded. This includes: The net power generation sequence is input into the golden section method. The initial search interval boundaries are the full folding angle and the full unfolding angle. With a convergence accuracy of 0.5°, the net power generation sequence is iteratively narrowed to obtain the optimal unfolding angle. Based on the natural frequency value corresponding to the optimal expansion angle in the natural frequency mapping table and the equivalent mass of the system, the square root of the product of the square of the natural frequency value and the equivalent mass of the system is taken, and then the radiation damping coefficient is subtracted to obtain the optimal damping coefficient. Using the non-zero difference between the optimal unfolding angle and the fully unfolded angle as a criterion, the optimal unfolding angle is confirmed to be in the intermediate unfolding state, and the optimal unfolding angle and the optimal damping coefficient are output to step S3.

[0035] Specifically, the golden section method is a single-variable, derivative-free optimization method for unimodal functions. Its iterative logic is as follows: using the full fold angle 0° and the full unfolding angle θmax as the initial search interval boundaries, two interior points are symmetrically selected within the current interval according to the golden ratio of 0.618. The net power generation values ​​at these two interior points are obtained by consulting the cubic spline interpolation function of the net power generation sequence. The sub-interval with the larger net power generation is retained as the new search interval, while the other side is discarded. This process is repeated iteratively until the interval width narrows to within 0.5°. The midpoint of the interval is then taken as the optimal unfolding angle output. The convergence accuracy is set to 0.5°, which matches the unfolding angle step size of 1° in the natural frequency mapping table. This ensures no additional computational bias is introduced within the interpolation error range, while keeping the maximum number of iterations below 20 to meet the response time requirements of airborne real-time computing. The net power generation sequence inevitably exhibits a unimodal distribution due to the physical monotonicity of the three components. The golden section method provides global convergence guarantees for unimodal functions, eliminating the risk of getting trapped in local extrema.

[0036] The optimal damping coefficient is the damping coefficient required for the power output device to achieve the theoretical maximum output power of the dual-floating body system at the optimal deployment angle. It is calculated by taking the square root of the product of the square of the natural frequency value corresponding to the optimal deployment angle in the natural frequency mapping table and the equivalent mass of the system at that deployment angle, and then subtracting the radiation damping coefficient. The radiation damping coefficient is a damping parameter in the linear wave force model that characterizes the outward radiation of wave energy by the dual-floating body system due to oscillating motion. It is stored in the airborne data table after being calibrated offline on shore by hydrodynamic simulation, and its initial value is continuously updated in the online correction mechanism of step S4. The intermediate deployment state refers to the deployment state where the optimal deployment angle is strictly greater than the full folding angle 0° and strictly less than the full deployment angle θmax. The criterion is that the difference between the optimal deployment angle and the full deployment angle is not zero. When the difference is zero, it indicates that full deployment is the optimal strategy under the current sea state. When the difference is not zero, it confirms that the optimal deployment angle is in the intermediate deployment state. This determination result, along with the optimal deployment angle and the optimal damping coefficient, is output to drive the folding mechanism and the power output device to perform subsequent adjustment actions.

[0037] In one specific embodiment, step S3 includes: Based on the optimal unfolding angle, an angle command is sent to the stepper motor of the folding mechanism to drive each blade of the deformable buoy to rotate synchronously to the optimal unfolding angle at a set angular velocity, thereby obtaining the actual unfolding angle after locking. Based on the optimal damping coefficient, the load resistance of the power output device is adjusted. The target load resistance value is obtained by dividing the optimal damping coefficient by the square of the generator speed coefficient. The target load resistance value is applied to the solid-state relay array to obtain the load resistance state corresponding to the optimal damping coefficient. Based on the additional drag increment introduced by the actual deployment angle, the output power of the thruster is compensated and calculated to drive the vehicle to continue to propel along the mission heading at a set drift speed, thus obtaining the drift propulsion state. The actual deployment angle, load resistance state, and drift propulsion state after locking are combined and applied to the vehicle to obtain a hybrid operating state in which wave energy capture and mission heading drift are synchronized.

[0038] Specifically, the stepper motor of the folding mechanism receives the optimal deployment angle as an angle command and drives the blades of the deformable buoy to rotate synchronously at a set angular velocity of 5° / s. This angular velocity is determined by the upper limit of the mechanical strength of the hinge shaft of the folding mechanism and the hydrodynamic impact load on the blades during rotation. At this angular velocity, the transient hydrodynamic impact torque on the blades does not exceed 80% of the rated torque of the mechanism. During rotation, the encoder of the mechanism continuously feeds back the actual deployment angle at a frequency of 10 Hz. When the difference between the feedback value and the optimal deployment angle does not exceed 0.5°, the stepper motor stops outputting and triggers mechanical locking. The actual deployment angle after locking is the feedback value of the encoder at this time, which is used as the input for subsequent calculation of additional resistance increment. The target load resistance value is obtained by dividing the optimal damping coefficient by the square of the generator speed coefficient. The generator speed coefficient is the ratio of the linear generator output force to the oscillation speed, given by the generator's factory calibration parameters, and the unit is Newtons per meter per second. The solid-state relay array is composed of several fixed resistors connected in parallel. The controller selects the corresponding combination of resistors according to the target load resistance value, so that the error between the actual load resistance and the target load resistance does not exceed 2% of the rated value, and the load resistance adjustment is completed in no more than 0.1 seconds.

[0039] Drift propulsion mode is the motion state in which the vehicle continuously propels itself along the mission heading at a set drift speed of 0.3 m / s under mixed operating conditions. The thruster output power is determined by the actual deployment angle after locking. Substituting into the following formula for calculating the additional hydrodynamic resistance increment yields the additional resistance increment. :

[0040] in, The drag coefficient is taken as 1.2, the calibration value for the water tank drag test. For the density of seawater, take 1025 kg / m³. 3 ; Number of leaves; This refers to the area of ​​a single blade. This is the actual unfolding angle after locking; To set the drift velocity, we take 0.3 m / s. The required compensation power for the thruster... for:

[0041] in, For thruster efficiency, a measured calibration value of 0.65 is used. The thruster adjusts its rotational speed and outputs corresponding thrust based on this compensated power. The hybrid operating state is the overall operating state of the vehicle after the actual deployment angle, load resistance state, and drift propulsion state are synchronously established after locking. In this state, the deformable buoy maintains an intermediate deployment state to continuously capture wave energy, the power output device continuously converts mechanical vibration energy into electrical energy with the load resistance corresponding to the optimal damping coefficient, and the thruster synchronously outputs compensated thrust to maintain the vehicle's drift along the mission course. The three are completely parallel in time, and the vehicle does not need to interrupt the mission to hover and wait for charging. This is fundamentally different in physical state from the existing operating mode of static levitation power generation after full deployment.

[0042] In one specific embodiment, step S4 includes: Based on the instantaneous power collected within a 1-second acquisition window by the current sensor and voltage sensor at the output end of the power output device, the arithmetic average of the instantaneous power is calculated to obtain the measured power generation. The measured power generation is compared with the predicted power generation based on the inherent frequency mapping table under the current wave main frequency and actual development angle. The average value of the difference within a 300-second sliding window is calculated to obtain the average power deviation. The ratio of the average power deviation to the predicted power generation exceeds 5% as the trigger condition. The ratio of the average power deviation to the predicted power generation is applied to the radiation damping coefficient, and the radiation damping coefficient in the natural frequency mapping table is proportionally corrected to obtain the updated natural frequency mapping table. Based on the difference between the current wave frequency and the wave frequency of the previous detection period, and taking the difference exceeding a preset threshold as the judgment condition, the updated natural frequency mapping table is input into step S2 to trigger the re-solution of the optimal expansion angle.

[0043] Specifically, the current and voltage sensors at the output of the power output device collect instantaneous current and voltage at a sampling rate of 100 Hz. The product of these two values ​​is the instantaneous power. The arithmetic mean of 100 instantaneous power values ​​within a 1-second sampling window is used to obtain the measured power output. The 1-second window duration is much shorter than the minimum wave cycle of 5 seconds, thus including enough sampling points within a single sampling window to eliminate the influence of instantaneous power fluctuations. The predicted power output is calculated by looking up the natural frequency mapping table at the current wave dominant frequency and actual development angle, combined with the wave excitation force coefficient and the square of the current effective wave height. The difference between this and the measured power output is used to obtain the single difference value. The average power deviation is the arithmetic mean of all single differences within a 300-second sliding window. The 300-second sliding window duration corresponds to 15 to 60 wave cycles of data under typical deep-sea conditions. Taking the average within this duration effectively filters out random fluctuations within a single wave cycle, ensuring that the average power deviation stably reflects the systematic deviation between the natural frequency mapping table radiation damping coefficient and the actual sea conditions. The 5% trigger threshold is set based on engineering experience regarding the initial calibration error of the inherent frequency mapping table. Deviations below this threshold are considered normal fluctuations caused by sensor noise and wave randomness, and do not require correction.

[0044] The calculation method for the proportional correction of the radiation damping coefficient is to multiply the current radiation damping coefficient by the ratio of the predicted power generation to the measured power generation. This proportional relationship originates from the physical relationship in the linear wave force model where power generation and the radiation damping coefficient are inversely proportional: when the average power deviation within a 300-second sliding window indicates that the measured power generation is consistently lower than the predicted value, and the ratio of the average power deviation to the predicted power generation exceeds 5%, it indicates that the actual radiation damping is higher than the value stored in the mapping table. Adjusting the radiation damping coefficient upwards according to the ratio of prediction to measurement can eliminate this persistent deviation; conversely, it should be adjusted downwards. Each correction is limited to within 10% of the current value to prevent abnormal sensor readings from causing severe fluctuations in the radiation damping coefficient. The corrected radiation damping coefficient is written to the corresponding storage location in the natural frequency mapping table, resulting in an updated natural frequency mapping table. The preset threshold for the difference in wave dominant frequency is set to 0.05 rad / s. This value corresponds to the detuning amount in the natural frequency mapping table where the capture width ratio decreases by more than 15%. It is calculated from the frequency domain response curve of the natural frequency mapping table under typical sea state parameters. The difference between the current wave dominant frequency and the wave dominant frequency of the previous cycle is read in a detection cycle of 60 seconds. When the difference exceeds 0.05 rad / s, the updated natural frequency mapping table is used as input to trigger the re-solution of the optimal unfolding angle. When the difference does not exceed the threshold, the natural frequency mapping table only completes the correction of the radiation damping coefficient without triggering the re-solution.

[0045] The energy harvesting method for the deformable dual-buoy wave-energy autonomous underwater vehicle (AUV) in this application has been described above. The energy harvesting system for the deformable dual-buoy wave-energy autonomous underwater vehicle (AUV) in this application is described below. One embodiment of the energy harvesting system for the deformable dual-buoy wave-energy autonomous underwater vehicle (AUV) in this application includes: The mapping module is used to establish a mapping relationship between the unfolding angle and the natural frequency of the dual-body float based on the structural parameters of the deformable buoy, and to obtain a natural frequency mapping table. The difference module is used to determine the current natural frequency based on the real-time collected wave main frequency and the natural frequency mapping table. It calculates the difference between the power generation gain component and the additional drag energy consumption component and attitude maintenance energy consumption component introduced by the increase in the spread angle. Using the spread angle as the only continuous decision variable, it solves the optimal spread angle and the optimal damping coefficient corresponding to the maximum value of the difference among the three components in the continuous interval from fully folded to fully spread. The optimal spread angle is less than the fully spread angle. The synchronization module is used to apply the optimal deployment angle and the optimal damping coefficient to the folding mechanism and the power output device respectively, forming a hybrid operating state in which the vehicle drifts along the mission course and captures wave energy synchronously. The triggering module is used to continuously update the inherent frequency mapping table based on the deviation between the measured power generation and the predicted power generation under the hybrid operating state, and to trigger the re-solution of the optimal expansion angle when the change in the wave dominant frequency exceeds a preset threshold.

[0046] This invention also provides an energy harvesting device for a deformable dual-buoy wave-powered autonomous underwater vehicle (AUV), which can be a server. The device includes a processor, memory, display screen, input device, network interface, and database connected via a system bus. The processor, designed as a computer, provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores the data corresponding to this embodiment. The network interface communicates with external terminals via a network connection. The computer program, when executed by the processor, implements the above-described method.

[0047] The present invention also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium, wherein the computer-readable storage medium stores instructions that, when the instructions are executed on a computer, cause the computer to perform the steps of the energy capture method for the deformable dual-buoy wave-energy autonomous underwater vehicle.

[0048] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0049] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a deformable dual-buoyancy wave-powered autonomous underwater vehicle energy harvesting device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0050] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A deformable dual float wave energy autonomous underwater vehicle energy capture method, characterized in that, The method includes: Step S1: Based on the structural parameters of the deformable buoy, establish the mapping relationship between the unfolding angle and the natural frequency of the dual-buoy body to obtain the natural frequency mapping table; Step S2: Determine the current natural frequency based on the real-time acquired wave dominant frequency using the natural frequency mapping table. This includes: performing Fourier analysis on the output signal of the airborne pressure sensor array within a 60-second acquisition window to obtain the current wave dominant frequency and significant wave height; inputting the current wave dominant frequency into the natural frequency mapping table and performing a lookup calculation on the continuous interpolation function in the natural frequency mapping table to obtain the current natural frequency; calculating the capture width ratio of the dual-floating body system based on the difference between the current natural frequency and the current wave dominant frequency to obtain the power generation gain component; subtracting the power generation gain component from the additional drag energy consumption component introduced by the increased deployment angle and the attitude maintenance energy consumption component, and using the deployment angle as the only continuous decision variable, solving for the optimal deployment angle and optimal damping coefficient corresponding to the maximum value of the difference among the three components within the continuous interval from fully folded to fully deployed, wherein the optimal deployment angle is less than the fully deployed angle; Step S3: Apply the optimal deployment angle and the optimal damping coefficient to the folding mechanism and the power output device respectively to form a hybrid operating state in which the vehicle drifts along the mission course and captures wave energy simultaneously. Step S4: Continuously update the inherent frequency mapping table based on the deviation between the measured power generation and the predicted power generation under the hybrid operating state, and trigger the re-solution of the optimal expansion angle when the change in the wave dominant frequency exceeds a preset threshold.

2. The energy harvesting method for a deformable dual-buoy wave-energy autonomous underwater vehicle according to claim 1, characterized in that, Step S1 includes: Based on the number of blades, the area of ​​a single blade, and the length of the articulated arm of the deformable buoy, the projected area of ​​the blades on the waterline at each deployment angle is calculated to obtain the waterline area sequence. Based on the waterline area sequence, the hydrodynamic restoring stiffness is calculated by multiplying the sum of the waterline area of ​​the vehicle body and the waterline area sequence by the seawater density and gravitational acceleration, and a stiffness sequence is obtained. Based on the stiffness sequence and the equivalent mass of the system at each deployment angle, the square root of the ratio of stiffness to mass is performed to obtain the natural frequency value corresponding to each deployment angle. The equivalent mass of the system is the sum of the mass of the vehicle body and the mass of the deformable buoy plus the additional mass at that deployment angle. The natural frequency value corresponding to each deployment angle is obtained by fitting the correspondence between the deployment angle and the natural frequency value as a continuous function using cubic spline interpolation to obtain the natural frequency mapping table.

3. The energy harvesting method for a deformable dual-buoy wave-energy autonomous underwater vehicle according to claim 2, characterized in that, Step S2 involves subtracting the power generation gain component from the additional drag energy consumption component introduced by the increased deployment angle and the attitude maintenance energy consumption component, including: Based on the frontal projected area of ​​the blades at each deployment angle, seawater density, drag coefficient, and set drift speed, the additional drag energy consumption component is calculated by dividing the product of the additional hydrodynamic drag increment and the set drift speed by the thruster efficiency. Based on the buoyancy eccentricity moment determined by the product of the blade submerged volume, seawater density, gravitational acceleration and the horizontal component of the blade submerged section in the articulated arm length at each deployment angle, the buoyancy eccentricity moment and the attitude control angular velocity are divided by the side thruster efficiency to calculate the attitude maintenance energy consumption component. The net power generation sequence corresponding to each deployment angle is obtained by subtracting the power generation gain component from the additional drag energy consumption component and the attitude maintenance energy consumption component.

4. The energy harvesting method for a deformable dual-buoy wave-energy autonomous underwater vehicle according to claim 3, characterized in that, In step S2, the unfolding angle is used as the only continuous decision variable. The optimal unfolding angle and optimal damping coefficient are calculated within the continuous interval from fully folded to fully unfolded, at which the difference between the three factors reaches its maximum value. This includes: The net power generation sequence is input into the golden section method. The initial search interval boundaries are the full folding angle and the full unfolding angle. The convergence accuracy is 0.5°. The net power generation sequence is iteratively narrowed to obtain the optimal unfolding angle. Based on the natural frequency value corresponding to the optimal expansion angle in the natural frequency mapping table and the equivalent mass of the system, the square root of the product of the square of the natural frequency value and the equivalent mass of the system is taken, and then the radiation damping coefficient is subtracted to obtain the optimal damping coefficient. Using the non-zero difference between the optimal unfolding angle and the fully unfolded angle as a criterion, the optimal unfolding angle is confirmed to be in an intermediate unfolding state, and the optimal unfolding angle and the optimal damping coefficient are output to step S3.

5. The energy harvesting method for a deformable dual-buoy wave-energy autonomous underwater vehicle according to claim 1, characterized in that, Step S3 includes: Based on the optimal unfolding angle, an angle command is sent to the stepper motor of the folding mechanism to drive each blade of the deformable buoy to rotate synchronously to the optimal unfolding angle at a set angular velocity, thereby obtaining the actual unfolding angle after locking. According to the optimal damping coefficient, the load resistance of the power output device is adjusted, and the target load resistance value is obtained by dividing the optimal damping coefficient by the square of the generator speed coefficient. The target load resistance value is applied to the solid-state relay array to obtain the load resistance state corresponding to the optimal damping coefficient. Based on the additional drag increment introduced by the actual deployment angle after locking, the output power of the thruster is compensated and calculated to drive the vehicle to continue to propel along the mission heading at a set drift speed, thus obtaining a drift propulsion state. The actual deployment angle after locking, the load resistance state, and the drift propulsion state are combined and applied to the vehicle to obtain a hybrid operating state in which wave energy capture and mission heading drift are synchronized.

6. The energy harvesting method for a deformable dual-buoy wave-energy autonomous underwater vehicle according to claim 5, characterized in that, Step S4 includes: Based on the instantaneous power of the current sensor and voltage sensor at the output end of the power output device within a 1-second acquisition window, the instantaneous power is calculated by arithmetic average to obtain the measured power generation. The measured power generation is subtracted from the predicted power generation based on the inherent frequency mapping table at the current wave main frequency and the actual unfolding angle after locking. The average value of the difference within a 300-second sliding window is calculated to obtain the average power deviation. Using the ratio of the average power deviation to the predicted power generation exceeding 5% as a trigger condition, the ratio of the average power deviation to the predicted power generation is applied to the radiation damping coefficient, and the radiation damping coefficient in the natural frequency mapping table is proportionally corrected to obtain an updated natural frequency mapping table. Based on the difference between the current wave frequency and the wave frequency of the previous detection period, and taking the difference exceeding a preset threshold as a judgment condition, the updated natural frequency mapping table is input into step S2 to trigger the re-solution of the optimal expansion angle.

7. An energy harvesting system for a deformable dual-buoyancy wave-energy autonomous underwater vehicle, characterized in that, For implementing the energy harvesting method of the deformable dual-buoy wave-energy autonomous underwater vehicle as described in any one of claims 1-6, the deformable dual-buoy wave-energy autonomous underwater vehicle energy harvesting system comprises: The mapping module is used to establish a mapping relationship between the unfolding angle and the natural frequency of the dual-body float based on the structural parameters of the deformable buoy, and to obtain a natural frequency mapping table. The difference module is used to determine the current natural frequency based on the real-time acquired wave dominant frequency and the natural frequency mapping table. This includes: performing Fourier analysis on the output signal of the airborne pressure sensor array within a 60-second acquisition window to obtain the current wave dominant frequency and significant wave height; inputting the current wave dominant frequency into the natural frequency mapping table and performing a lookup calculation on the continuous interpolation function in the natural frequency mapping table to obtain the current natural frequency; calculating the capture width ratio of the dual-floating body system based on the difference between the current natural frequency and the current wave dominant frequency to obtain the power generation gain component; and subtracting the power generation gain component from the additional drag energy consumption component introduced by the increased deployment angle and the attitude maintenance energy consumption component. Using the deployment angle as the only continuous decision variable, the module calculates the optimal deployment angle and optimal damping coefficient corresponding to the maximum value of the difference among the three components within the continuous interval from fully folded to fully deployed. The optimal deployment angle is less than the fully deployed angle. The synchronization module is used to apply the optimal deployment angle and the optimal damping coefficient to the folding mechanism and the power output device respectively, forming a hybrid operating state in which the vehicle drifts along the mission course and captures wave energy synchronously. The triggering module is used to continuously update the inherent frequency mapping table based on the deviation between the measured power generation and the predicted power generation under the hybrid operating state, and to trigger the re-solution of the optimal expansion angle when the change in the wave dominant frequency exceeds a preset threshold.

8. An energy harvesting device for a deformable dual-buoyancy wave-energy autonomous underwater vehicle, characterized in that, The device includes a memory and a processor, the memory storing a computer program that can run on the processor, and the processor executing the computer program to implement the energy capture method for the deformable dual-buoy wave-energy autonomous underwater vehicle according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is run by the processor, it causes the processor to execute the energy capture method for a deformable dual-buoy wave-energy autonomous underwater vehicle as described in any one of claims 1 to 6.

Images