A method, system and storage medium for controlling a karman vortex street energy harvester

Abstract

This application relates to a control method, system, and storage medium for a Karman vortex street energy harvester, belonging to the technical field of energy harvesting. The method includes acquiring historical wind speed and direction data; analyzing the historical wind speed and direction data to determine the harvester's fixed direction, minimum cantilever length, cantilever length setting, and initial cantilever setting; deploying a preset energy harvester according to the harvester's fixed direction, preset maximum cantilever length, minimum cantilever length, and initial cantilever setting; acquiring a preceding stable waveform, a sliding energy waveform, and an average energy amplitude; analyzing the preceding stable waveform, sliding energy waveform, average energy amplitude, and cantilever length setting to determine the dynamic cantilever setting; and adjusting the length of a preset vibrating cantilever beam on the energy harvester according to the dynamic cantilever setting to control the energy harvester's energy collection. This application improves energy harvesting efficiency.

Description

Technical Field

[0001] This application relates to the technical field of energy harvesting, and in particular to a control method, system and storage medium for a Karman vortex street energy harvester. Background Technology

[0002] The Karman vortex street energy harvester control method refers to the process of maximizing energy harvesting by controlling the magnitude of the natural frequency of the Karman vortex street energy harvester so that the Karman vortex street energy harvester resonates with the Karman vortex street frequency.

[0003] In related technologies, when controlling a Karman vortex street energy harvester, a Karman vortex street energy harvester with a fixed cantilever beam length is usually adopted. A fixed blunt body is installed at the free end of the cantilever beam of the energy harvester to reduce the natural frequency of the energy harvester. During operation, the alternating force generated by the Karman vortex street falling off the airflow behind the energy harvester drives the cantilever beam to vibrate. Then, the mechanical energy is converted into electrical energy through the transducer unit to realize energy harvesting.

[0004] Regarding the aforementioned technologies, when using an energy harvester with a fixed cantilever beam length, due to variations in wind force, the harvester's frequency may not match the Karman vortex street frequency, resulting in a failure to achieve resonance and thus lower energy harvesting efficiency. There is still room for improvement. Summary of the Invention

[0005] To improve energy harvesting efficiency, this application provides a control method, system, and storage medium for a Karman vortex street energy harvester.

[0006] Firstly, this application provides a control method for a Karman vortex street energy harvester, employing the following technical solution: A control method for a Karman vortex street energy harvester includes: Obtain historical wind speed and historical wind direction data; Historical wind speed and direction data are analyzed to determine the fixed direction of the data logger, the minimum cantilever length, the cantilever length setting, and the initial cantilever setting. The preset energy collectors are deployed according to the fixed direction of the collectors, the preset maximum cantilever length, the preset minimum cantilever length, and the initial cantilever position. Obtain the preceding stable waveform, the sliding energy waveform, and the average energy amplitude; The dynamic suspension beam position is determined by analyzing the preceding stable waveform, sliding energy waveform, average energy amplitude, and suspension beam length position. Adjust the length of the pre-set vibrating cantilever beam on the energy harvester according to the dynamic cantilever beam setting to control the energy harvester's energy collection.

[0007] Optionally, the steps of analyzing historical wind speed and direction data to determine the fixed direction of the data logger, the minimum cantilever length, the cantilever length setting, and the initial cantilever setting include: Historical wind direction data corresponding to historical wind speed data are filtered according to a preset effective collection threshold to determine effective wind direction data; Analyze the effective wind direction data to determine the probability of effective wind direction and the effective wind direction for data collection; Data analysis is performed on the effective wind direction probability to determine the maximum wind direction probability; The effective wind direction corresponding to the maximum wind direction probability is determined as the fixed direction of the data collector. Historical wind speed data is extracted based on the fixed direction of the data collector to determine the effective wind speed; The effective wind speed is analyzed to determine the minimum cantilever length; The effective wind speed is analyzed to determine the suspension beam length setting and the initial suspension beam setting.

[0008] Optionally, the step of analyzing the effective wind speed to determine the minimum cantilever length includes: Numerical analysis of effective wind speed is performed to determine the maximum effective wind speed; Input the maximum effective wind speed and the preset mass block diameter into the preset vortex shedding frequency model to determine the maximum vortex shedding frequency; Input the maximum vortex shedding frequency, the preset cantilever section constant, the preset cantilever elastic modulus, and the preset mass weight into the preset cantilever frequency model to determine the minimum cantilever length.

[0009] Optionally, the steps of analyzing the effective wind speed to determine the cantilever length setting and the initial cantilever setting include: Cluster analysis was performed on the effective wind speed to determine the interval wind speed data and the amount of data in each interval. Data processing is performed on the interval data volume to determine the decreasing data volume; Based on the preset number of gear settings, the interval wind speed data corresponding to the decreasing data volume is extracted to determine the gear wind speed data. Data analysis is performed on the gear wind speed data to determine the gear wind range, gear wind speed probability, and gear wind speed. The decreasing data volume, wind speed range, wind speed probability, and wind speed at each gear are analyzed to determine the beam length gear and the initial beam gear.

[0010] Optionally, the steps to analyze the decreasing data volume, wind speed range, wind speed probability, and wind speed at each gear to determine the cantilever length gear and the initial cantilever gear include: The expected value of the wind speed at each gear is calculated based on the probability of wind speed at each gear, in order to determine the base wind speed at each gear. Input the gear reference wind speed into the preset vortex shedding frequency model to determine the gear vortex shedding frequency. Input the vortex shedding frequency of the gear, the preset cantilever section constant, the preset cantilever elastic modulus, and the preset mass weight into the preset cantilever frequency model to determine the cantilever length gear. Extract data from the decreasing data volume to determine the maximum data volume; Data is extracted from the cantilever length range corresponding to the maximum data volume to determine the initial cantilever range.

[0011] Optionally, the steps to determine the dynamic suspension beam position by analyzing the preceding stable waveform, sliding energy waveform, average energy amplitude, and suspension beam length range include: Determine whether the average energy amplitude is greater than the preset effective power generation threshold; If it is not greater than, the average energy amplitude will be continuously obtained for iterative judgment; If it is greater than 1, then perform Fourier transform on the preceding stable waveform and the sliding energy waveform to determine the preceding vortex street main frequency and the real-time vortex street main frequency. Calculate the relative deviation between the preceding vortex street frequency and the real-time vortex street frequency to determine the real-time vortex street deviation; The dynamic suspension beam setting is determined by analyzing the real-time vortex street main frequency, real-time vortex street deviation, and suspension beam length setting.

[0012] Optionally, the steps to analyze the real-time vortex street main frequency, real-time vortex street deviation, and cantilever length setting to determine the dynamic cantilever setting include: Determine whether the real-time vortex shear deviation is greater than the preset gear shift deviation threshold; If it is not greater than, then continuously acquire the preceding stable waveform, sliding energy waveform and average energy amplitude, calculate the real-time vortex shedding deviation and perform cyclic judgment; If it is greater than, then obtain the frequency of the cantilever beam corresponding to the cantilever beam length position; Calculate the absolute deviation between the cantilever beam gear frequency and the real-time vortex street main frequency to determine the gear vortex street deviation; Numerical analysis was performed on the gear shift vortex deviation to determine the minimum vortex deviation. The cantilever length range corresponding to the minimum vortex shedding deviation is determined as the dynamic cantilever range.

[0013] Secondly, this application provides a control system for a Karman vortex street energy harvester, which adopts the following technical solution: A Karman vortex street energy harvester control system includes: The acquisition module is used to acquire historical wind speed data, historical wind direction data, preceding stable waveform, sliding energy waveform, average energy amplitude, and cantilever beam frequency. A memory for storing a program for a Karman vortex street energy harvester control method as described in any of the preceding claims; The processor and the program in the memory can be loaded and executed by the processor to implement a Karman vortex street energy harvester control method as described in any of the above.

[0014] Thirdly, this application provides a computer storage medium capable of storing corresponding programs, which facilitates improving energy harvesting efficiency, and adopts the following technical solution: A computer-readable storage medium storing a computer program that can be loaded by a processor and executed any of the above-described Karman vortex street energy harvester control methods.

[0015] In summary, this application includes at least one of the following beneficial technical effects: By analyzing historical wind speed and direction data, the fixed direction, minimum cantilever length, cantilever length setting, and initial cantilever setting of the energy harvester are determined. The energy harvester is then deployed based on the fixed direction, maximum cantilever length, minimum cantilever length, and initial cantilever setting. After deployment, the preceding stable waveform, sliding energy waveform, and average energy amplitude are acquired. The preceding stable waveform, sliding energy waveform, average energy amplitude, and cantilever length setting are analyzed to determine the dynamic cantilever setting that is closest to the Karman vortex street frequency corresponding to the current wind speed. The length of the vibrating cantilever beam on the energy harvester is then adjusted according to the cantilever setting to control the energy harvester's energy collection and thus improve energy collection efficiency. By clustering analysis of effective wind speeds, interval wind speed data and interval data volume are determined. The interval data volume is sorted to determine the decreasing data volume. According to the number of gear settings, the interval wind speed data corresponding to the decreasing data volume is extracted in sequence to determine the gear wind speed data. Data analysis of the gear wind speed data is performed to determine the gear wind speed interval corresponding to each gear, the probability of the gear wind speed appearing in the interval, and the gear wind speed that has appeared in the gear. The decreasing data volume, gear wind interval, gear wind speed probability, and gear wind speed are analyzed to determine the suspension beam length gear and the initial suspension beam gear. Thus, the suspension beam length gear is determined based on historical wind speed division. Then, the natural frequency of the energy harvester is dynamically adjusted based on wind speed to improve the adaptability of the natural frequency of the energy harvester to the Karman vortex street frequency. By analyzing the real-time vortex street deviation, when the real-time vortex street deviation exceeds the adjustment deviation threshold, it indicates that the wind speed has changed, and the length of the vibrating cantilever beam of the energy harvester needs to be adjusted. Therefore, the absolute deviation between the frequency of the cantilever beam corresponding to all cantilever beam length positions and the real-time vortex street main frequency is calculated to determine the minimum vortex street deviation. The cantilever beam length position corresponding to the minimum vortex street deviation is then determined as the dynamic cantilever beam position, thereby minimizing the difference between the energy harvester's natural frequency and the Karman vortex street frequency to maximize the energy harvesting. Attached Figure Description

[0016] Figure 1 This is a flowchart of a Karman vortex street energy harvester control method according to an embodiment of this application.

[0017] Figure 2 This is a flowchart illustrating the analysis of historical wind speed and direction data in this application embodiment to determine the fixed direction of the data collector, the minimum cantilever length, the cantilever length setting, and the initial cantilever setting.

[0018] Figure 3 This is a flowchart illustrating the analysis of effective wind speed in this application embodiment to determine the minimum cantilever length.

[0019] Figure 4 This is a flowchart in this application embodiment of analyzing the effective wind speed to determine the suspension beam length setting and the initial suspension beam setting.

[0020] Figure 5 This is a flowchart in this application embodiment that analyzes the decreasing data volume, gear wind range, gear wind speed probability, and gear wind speed to determine the suspension beam length gear and the initial suspension beam gear.

[0021] Figure 6 This is a flowchart in this application embodiment that analyzes the preceding stable waveform, sliding energy waveform, average energy amplitude, and cantilever length increments to determine the dynamic cantilever increments.

[0022] Figure 7 This is a flowchart illustrating the analysis of real-time vortex street main frequency, real-time vortex street deviation, and cantilever beam length increments in this embodiment of the application to determine the dynamic cantilever beam increments. Detailed Implementation

[0023] To make the purpose, technical solution, and advantages of this application clearer, the following description is provided in conjunction with the appendix. Figures 1 to 7 The present application will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the application.

[0024] This application discloses a control method, system, and storage medium for a Karman vortex street energy harvester. Specifically, it discloses a processing terminal and an energy harvester, which are communicatively connected to achieve information interaction and control. The processing terminal acquires historical wind speed and direction data, analyzes the historical wind speed and direction data to determine the harvester's fixed direction, minimum cantilever length, cantilever length setting, and initial cantilever setting. The energy harvester is deployed according to the harvester's fixed direction, maximum cantilever length, minimum cantilever length, and initial cantilever setting. After deployment, the preceding stable waveform, sliding energy waveform, and average energy amplitude are acquired. The preceding stable waveform, sliding energy waveform, average energy amplitude, and cantilever length setting are analyzed to determine the dynamic cantilever setting closest to the Karman vortex street frequency corresponding to the current wind speed. The length of the vibrating cantilever beam on the energy harvester is then adjusted according to the cantilever setting to control the energy harvester's energy collection, thereby improving energy collection efficiency.

[0025] Reference Figure 1 This application discloses a control method for a Karman vortex street energy harvester, comprising the following steps: Step S100: Obtain historical wind speed data and historical wind direction data.

[0026] Historical wind speed data refers to the historical wind speed data of the area where the energy harvester is deployed within one year, including historical wind speeds arranged in chronological order. The data is determined by the processing terminal by retrieving wind speed data from the database and integrating the wind speed data in chronological order.

[0027] Historical wind direction data refers to the historical wind direction data within one year in the area where the energy harvester is deployed. This includes historical wind directions arranged in chronological order. The processing terminal determines the wind direction data by retrieving wind direction data from the database and integrating the wind direction data in chronological order.

[0028] Step S101: Analyze historical wind speed data and historical wind direction data to determine the fixed direction of the data collector, the minimum cantilever length, the cantilever length setting, and the initial cantilever setting.

[0029] Here, "fixed direction of the energy harvester" refers to the orientation in which the energy harvester is deployed. "Minimum cantilever beam length" refers to the minimum limit length of the vibrating cantilever beam of the energy harvester. "Cantilever beam length adjustment range" refers to the adjustment range of the cantilever beam length corresponding to different natural frequencies. "Initial cantilever beam adjustment range" refers to the cantilever beam length range at which the energy harvester is initially deployed. All of the above data are determined by the processing terminal through analysis of historical wind speed and direction data. Specific analysis steps are detailed in [reference needed]. Figure 2 The steps in the process.

[0030] Step S102: Deploy the preset energy collector according to the fixed direction of the collector, the preset maximum cantilever length, the preset minimum cantilever length, and the initial cantilever position.

[0031] The maximum cantilever beam length refers to the maximum limit length of the vibrating cantilever beam of the energy harvester. The operator first measures the maximum allowable size of the vibrating cantilever beam on the energy harvester mounting base to ensure that the vibrating cantilever beam will not collide with other structures during vibration. Then, based on the material of the vibrating cantilever beam wall, the root bending stress caused by the maximum wind speed in the area and the fatigue limit of the vibrating cantilever beam are determined to adjust the maximum size of the vibrating cantilever beam.

[0032] An energy harvester is a miniature energy harvester that harvests energy based on the Karman vortex street. This energy harvester acts the alternating aerodynamic force generated by the alternating shedding of the Karman vortex street onto a variable cross-section conical vibrating cantilever beam with adjustable length, causing the vibrating cantilever beam to vibrate. Then, the mechanical stress is converted into electrical energy by the pressure-sensitive material arranged on the wall of the vibrating cantilever beam, thereby providing power to low-energy electronic devices.

[0033] After determining the fixed direction of the collector, the minimum cantilever beam length, and the initial cantilever beam position, a bidirectional limit is set for the length of the vibrating cantilever beam, with the maximum and minimum cantilever beam lengths as boundaries. The energy collector is then deployed according to its deployment direction, and the vibrating cantilever beam is set at the initial cantilever beam position, thereby improving the energy collection efficiency of the energy collector.

[0034] Step S103: Obtain the preceding stable waveform, the sliding energy waveform, and the average energy amplitude.

[0035] Among them, the preceding stable waveform refers to the power generation waveform in the previous stable operating cycle of the currently acquired data. It is used to determine whether the Karman vortex street frequency has changed significantly. The processing terminal extracts and stores the data by setting a sliding window. After filtering the data, the sliding window data is analyzed to determine the preceding adjacent data at the current data time. The dominant frequency of the preceding adjacent data is extracted and compared with the dominant frequency of the previous data. It is determined whether the difference between the two dominant frequencies is within the deviation threshold. If it is within the deviation threshold, the preceding adjacent data is determined to be the preceding stable waveform. If it is not within the deviation threshold, the search continues until the dominant frequency of the preceding data is stable.

[0036] The sliding energy waveform refers to the power generation waveform data extracted in real time by the sliding window. The processing terminal first controls the sliding window to extract two consecutive sets of waveform data, filters the data, calculates the main frequency of the waveform data, and then determines whether the difference between the two main frequencies is within the deviation threshold. If it is within the deviation threshold, the set of data with the later time point is determined as the sliding energy waveform. If it is not within the deviation threshold, it indicates that the current data waveform is unstable. Therefore, the sliding time window continues to extract real-time waveform data until the deviation of adjacent time window data is within the threshold range. This avoids invalid gear adjustment caused by instantaneous changes in wind force and avoids frequent switching of cantilever beam length gears.

[0037] The average energy amplitude refers to the average value of the amplitude of the sliding energy waveform. It is determined by the processing terminal after determining the sliding energy waveform by calculating the average value of the corresponding amplitude of the sliding energy waveform.

[0038] Step S104: Analyze the preceding stable waveform, sliding energy waveform, average energy amplitude, and cantilever length position to determine the dynamic cantilever position.

[0039] The dynamic cantilever beam setting refers to the fixed length setting of the cantilever beam in the energy harvester. Different length settings correspond to different cantilever beam lengths. By adjusting the dynamic cantilever beam setting, the length of the cantilever beam is changed, thereby altering the natural frequency of the energy harvester and improving the resonance efficiency between the energy harvester and the Karman vortex street frequency. This is determined by the processing terminal through analysis of the preceding stable waveform, the sliding energy waveform, the average energy amplitude, and the cantilever beam length setting. Specific analysis steps are detailed below. Figure 6 The steps in the process.

[0040] Step S105: Adjust the length of the preset vibrating cantilever beam on the energy harvester according to the dynamic cantilever beam setting to control the energy harvester to collect energy.

[0041] Among them, the vibrating cantilever beam refers to the main vibrating power generation unit in the energy harvester. The vibrating cantilever beam is a tapered variable cross-section elastic beam with a fixed root and a mass block fixed at the top. When the wind blows towards the energy harvester, the Karman vortex street effect is generated at the mass block at the top of the cantilever beam, thereby causing the cantilever beam to vibrate left and right. The mechanical energy is converted into electrical energy through the pressure-transformer material. The effective length of the cantilever beam is controlled by a micro actuator such as a micro stepper motor or mechanical positioning pin embedded in the base of the energy harvester to realize the fixed length adjustment of the vibrating cantilever beam.

[0042] After determining the dynamic suspension beam setting, adjust the vibrating suspension beam wall on the energy harvester to the dynamic suspension beam setting to control the energy harvester to collect energy and improve energy collection efficiency.

[0043] Reference Figure 2 The steps for analyzing historical wind speed and direction data to determine the fixed direction of the data logger, the minimum cantilever length, the cantilever length setting, and the initial cantilever setting include: Step S200: Filter the historical wind direction data corresponding to the historical wind speed data according to the preset effective acquisition threshold to determine the effective wind direction data.

[0044] Among them, the effective acquisition threshold refers to the wind speed threshold of the effective wind, which is determined by the operator based on the wind speed requirements corresponding to the acquisition accuracy of the energy harvester.

[0045] Valid wind direction data refers to the historical wind direction data corresponding to the historical wind speed data after being filtered by the valid acquisition threshold. The processing terminal first filters the historical wind speed data based on the valid acquisition threshold, and then determines the valid wind direction data based on the wind direction corresponding to the valid wind.

[0046] Step S201: Analyze the effective wind direction data to determine the effective wind direction probability and the effective wind direction for data collection.

[0047] Among them, the probability of effective wind direction refers to the probability of each wind direction appearing in the effective wind, which is determined by the processing terminal by calculating the probability of each wind direction appearing in the effective wind direction data after determining the effective wind direction data.

[0048] Effective wind direction refers to the wind direction corresponding to each effective wind direction probability. It is determined by the processing terminal by integrating the effective wind direction corresponding to each effective wind direction probability after determining the effective wind direction probability.

[0049] Step S202: Perform data analysis on the effective wind direction probability to determine the maximum wind direction probability.

[0050] Among them, the maximum wind direction probability refers to the maximum effective wind direction probability. The processing terminal determines the maximum value among the effective wind direction probabilities by analyzing the data.

[0051] Step S203: Determine the effective wind direction corresponding to the maximum wind direction probability as the fixed direction of the data collector.

[0052] The fixed direction of the data collector is consistent with the fixed direction of the data collector in step S101, and is determined by the processing terminal based on the effective wind direction corresponding to the maximum wind direction probability.

[0053] Step S204: Extract historical wind speed data according to the fixed direction of the data collector to determine the effective wind speed.

[0054] Among them, the effective wind speed refers to the historical wind speed data corresponding to the fixed direction of the data collector. After the processing terminal determines the fixed direction of the data collector, since the orientation of the data collector corresponding to the fixed direction of the data collector is the wind direction, the historical wind speed data is extracted according to the fixed direction of the data collector to determine the wind speed data corresponding to the fixed direction of the data collector, which is the effective wind speed.

[0055] Step S205: Analyze the effective wind speed to determine the minimum cantilever length.

[0056] The minimum cantilever beam length is consistent with the minimum cantilever beam length in step S101, and is determined by the processing terminal through analysis of the effective wind speed. The specific analysis steps are as follows: Figure 3The steps in the process.

[0057] Step S206: Analyze the effective wind speed to determine the cantilever length setting and the initial cantilever setting.

[0058] The cantilever length setting is consistent with the cantilever length setting in step S101. The initial cantilever setting is consistent with the initial cantilever setting in step S101. Both are determined by the processing terminal through analysis of effective wind speed data; the specific analysis steps are as follows. Figure 4 The steps in the process.

[0059] Reference Figure 3 The steps for analyzing the effective wind speed to determine the minimum cantilever length include: Step S300: Perform numerical analysis on the effective wind speed to determine the maximum effective wind speed.

[0060] Among them, the maximum effective wind speed refers to the maximum effective wind speed. The processing terminal determines the maximum value of the effective wind speed by performing numerical analysis on the effective wind speed, which is the maximum effective wind speed.

[0061] Step S301: Input the maximum effective wind speed and the preset mass block diameter into the preset vortex shedding frequency model to determine the maximum vortex shedding frequency.

[0062] The mass block diameter refers to the diameter of the energy block at the top of the cantilever beam in the windward direction, which is calibrated by the operator in the system.

[0063] The vortex shedding frequency model is a formulaic model for calculating the frequency of the KAMAN vortex shedding based on the Strauhal formula. The specific model formula is as follows: .

[0064] In the formula, The maximum vortex shedding frequency, To achieve the maximum effective wind speed, The diameter of the mass block, is the Strouhal coefficient, and is a fixed physical constant.

[0065] The maximum vortex street frequency refers to the Karman vortex street frequency corresponding to the maximum effective wind speed. It is calculated and determined by the processing terminal by inputting the maximum effective wind speed and the diameter of the mass block into the vortex street frequency model, providing data support for the subsequent determination of the minimum cantilever length.

[0066] Step S302: Input the maximum vortex shedding frequency, the preset cantilever section constant, the preset cantilever elastic modulus, and the preset mass weight into the preset cantilever frequency model to determine the minimum cantilever length.

[0067] Among them, the constant of the cantilever section refers to the characteristic parameter of the change of the moment of inertia of the tapered vibrating cantilever beam section along the length of the cantilever beam. It characterizes the distribution characteristics of the bending stiffness of the vibrating cantilever beam. The operator first determines the expression of the linear change of the cantilever diameter with the length of the cantilever wall based on the cantilever diameter corresponding to the maximum and minimum cantilever lengths. Then, the moment of inertia that changes with the length of the vibrating cantilever beam is determined according to the formula of the moment of inertia of the circular section. The moment of inertia is determined by integrating the moment of inertia and dividing the integrated moment of inertia by the length of the cantilever beam.

[0068] The elastic modulus of a cantilever beam is a measure of the compressive deformation capacity of the cantilever beam material. It is the ratio between the stress on the vibrating cantilever beam and the corresponding strain generated by the vibrating cantilever beam, and is calibrated by the operator in the system.

[0069] The mass weight refers to the weight of the mass block at the top of the vibrating cantilever beam. The operator determines the mass weight by back-calculating the target that the natural vibration frequency corresponding to the maximum cantilever beam length is consistent with the Karman vortex street frequency corresponding to the lower limit of the wind speed for energy harvesting by the energy harvester after determining the maximum cantilever beam length.

[0070] The cantilever beam frequency model is a formula model based on the natural frequency formula of a cantilever beam. It matches the natural frequency of the cantilever beam to the Karman vortex street frequency, thereby inversely determining the beam length. The specific model formula is as follows: .

[0071] In the formula, Minimum cantilever length, The elastic modulus of the cantilever beam. For the constant cross-section of the cantilever beam, The maximum vortex shedding frequency, The mass is the weight of the block.

[0072] The minimum cantilever length is consistent with the minimum cantilever length in step S205, and is determined by the processing terminal by inputting the maximum vortex shedding frequency, cantilever cross-sectional constant, cantilever elastic modulus, and mass block weight into the cantilever frequency model.

[0073] Reference Figure 4 The steps for analyzing the effective wind speed to determine the cantilever length setting and the initial cantilever setting include: Step S400: Perform cluster analysis on the effective wind speed to determine the interval wind speed data and the amount of interval data.

[0074] Among them, the interval wind speed data refers to the effective wind speed data divided into wind speed intervals obtained by clustering. The processing terminal inputs the effective wind speed data into a clustering model such as k-means clustering algorithm or Gaussian mixture model. The algorithm clusters the wind speed data based on the set number of groups, determines the effective wind speed interval, and integrates the effective wind speed data according to the effective wind speed interval.

[0075] The interval data volume refers to the total amount of wind speed data in each interval wind speed data corresponding to the wind speed interval. It is determined by the processing terminal by calculating the total amount of wind speed data in each wind speed interval after determining the interval wind speed data.

[0076] Step S401: Perform data processing on the interval data volume to determine the decreasing data volume.

[0077] The decreasing data volume refers to the range of data obtained after descending sorting, which is determined by the processing terminal by descending sorting the range of data volume according to the size of the data volume.

[0078] Step S402: Extract the interval wind speed data corresponding to the decreasing data volume according to the preset number of gear settings to determine the gear wind speed data.

[0079] The number of gear settings refers to the number of gears that cantilever beam length can be set. For example, if the cantilever beam length is divided into three gears, the number of gear settings is 3, which is calibrated by the operator in the system.

[0080] The gear wind speed data refers to the wind speed data corresponding to each gear position of the cantilever beam, which is determined by the processing terminal extracting the interval wind speed data corresponding to the decreasing data volume based on the number of gear positions set.

[0081] Step S403: Perform data analysis on the gear wind speed data to determine the gear wind range, gear wind speed probability, and gear wind speed.

[0082] Among them, the gear wind range refers to the wind speed range corresponding to the gear wind speed data, such as the wind speed range of 12-16m / s, which is determined by the processing terminal by extracting the wind speed range corresponding to each gear wind speed data.

[0083] The gear wind speed probability refers to the probability of each wind speed appearing in the corresponding data of each gear wind speed range. It is determined by the processing terminal by statistically analyzing the wind speeds that have appeared in each wind speed range and the duration of each wind speed, and then calculating the quotient of the duration of the wind speed appearance and the total duration of the wind speed in the range.

[0084] The gear wind speed refers to the wind speed corresponding to each gear wind speed data, which is determined by the processing terminal by extracting the wind speed data contained in each gear range in the gear wind speed data.

[0085] Step S404: Analyze the decreasing data volume, wind speed range, wind speed probability, and wind speed to determine the beam length range and the initial beam range.

[0086] The cantilever length setting is consistent with the cantilever length setting in step S206. The initial cantilever setting is consistent with the initial cantilever setting in step S206. Both are determined by the processing terminal through analysis of the decreasing data volume, the wind range of the setting, the wind speed probability of the setting, and the wind speed of the setting. The specific analysis steps are as follows: Figure 5 The steps in the process.

[0087] Reference Figure 5 The steps for determining the cantilever length setting and the initial cantilever setting include analyzing the decreasing data volume, wind speed range, wind speed probability, and wind speed at each setting. Step S500: Calculate the expected value of the gear wind speed based on the gear wind speed probability to determine the gear reference wind speed.

[0088] Among them, the reference wind speed for each gear refers to the reference wind speed corresponding to each cantilever beam length gear, which is used to determine the Karman vortex street frequency corresponding to each gear, thereby determining the cantilever beam length corresponding to each gear. It is determined by the processing terminal through the mathematical expectation of the gear wind speed calculated based on the gear wind speed probability.

[0089] Step S501: Input the gear reference wind speed into the preset vortex shedding frequency model to determine the gear vortex shedding frequency.

[0090] The vortex shedding frequency model is consistent with the vortex shedding frequency model in step S301.

[0091] The gear vortex frequency refers to the Karman vortex frequency corresponding to each gear of the cantilever beam length, which is determined by the processing terminal by inputting the reference wind speed of each gear into the vortex frequency model.

[0092] Step S502: Input the gear vortex shedding frequency, the preset cantilever cross section constant, the preset cantilever elastic modulus, and the preset mass block weight into the preset cantilever frequency model to determine the cantilever length gear.

[0093] Specifically, the cantilever beam cross-sectional constant is the same as that in step S302. The cantilever beam elastic modulus is the same as that in step S302. The mass weight is the same as that in step S302. The cantilever beam frequency model is the same as that in step S302. The cantilever beam length increments are the same as those in step S404, and are determined by the processing terminal by inputting the vortex shedding frequency, cantilever beam cross-sectional constant, cantilever beam elastic modulus, and mass weight of each increment into the cantilever beam frequency model.

[0094] Step S503: Extract data from the decreasing data volume to determine the maximum data volume.

[0095] The maximum data volume refers to the maximum value among the decreasing data volumes, which is determined by the processing terminal by extracting the first data from the decreasing data volume.

[0096] Step S504: Extract data for the cantilever length gear based on the gear wind range corresponding to the maximum data volume to determine the initial cantilever gear.

[0097] The initial cantilever beam position is consistent with the initial cantilever beam position in step S404. After determining the maximum data volume, the processing terminal first determines the wind range corresponding to the maximum data volume. After determining the wind range, the cantilever beam length position corresponding to the wind range is determined as the initial cantilever beam position. This ensures that when the energy harvester is deployed, the length of the energy harvester is adjusted to the length position corresponding to the wind speed range where the wind speed occurs most frequently, thereby reducing the probability of gear adjustment.

[0098] Reference Figure 6 The steps for determining the dynamic suspension beam position by analyzing the preceding stable waveform, sliding energy waveform, average energy amplitude, and suspension beam length position include: Step S600: Determine whether the average energy amplitude is greater than the preset effective power generation threshold.

[0099] The effective power generation threshold refers to the lower limit of the average energy amplitude corresponding to the effective power generation wind. It is determined by the operator through offline multi-scenario iterative pre-experiment by setting the directional wind with the corresponding wind speed based on the effective acquisition threshold. After controlling the directional wind to blow in the forward direction of the energy harvester, the power generation waveform of the energy harvester is analyzed to determine the average amplitude corresponding to the directional wind. The average amplitude is then verified by long-term operation, and the average amplitude is fine-tuned based on the verification results.

[0100] By processing the terminal to determine whether the energy amplitude is greater than the effective power generation threshold, it is possible to determine whether there is an effective Karman vortex street excitation frequency, and then to determine whether to initiate the Karman vortex street frequency consistency verification step, thereby avoiding ineffective adjustment of the cantilever beam length setting and improving energy harvesting efficiency.

[0101] Step S601: If it is not greater than, then continuously obtain the average energy amplitude and perform cyclic judgment.

[0102] If the processing terminal determines that the average energy amplitude is not greater than the effective power generation threshold, it indicates that the Karman vortex street excitation frequency is invalid at this time. Therefore, the average energy amplitude is continuously acquired for cyclic judgment, thereby monitoring the power generation waveform of the energy harvester in real time and improving the energy harvesting efficiency.

[0103] Step S602: If it is greater than, perform Fourier transform on the preceding stable waveform and the sliding energy waveform to determine the preceding vortex street main frequency and the real-time vortex street main frequency.

[0104] Among them, the dominant frequency of the preceding vortex street refers to the dominant frequency of the Karman vortex street corresponding to the preceding stable waveform. It is determined by the processing terminal by first performing a Fourier transform on the preceding stable waveform and then extracting the dominant frequency of the Fourier transform data.

[0105] The real-time vortex street master frequency refers to the Karman vortex street master frequency corresponding to the sliding energy waveform. It is determined by the processing terminal by performing a Fourier transform on the sliding energy waveform and then extracting the master frequency from the Fourier transform data.

[0106] Step S603: Calculate the relative deviation between the preceding vortex street frequency and the real-time vortex street frequency to determine the real-time vortex street deviation.

[0107] Among them, the real-time vortex street deviation refers to the Karman vortex street frequency deviation between the real-time vortex street main frequency and the preceding vortex street main frequency, which is determined by the processing terminal by calculating the relative deviation between the preceding vortex street main frequency and the real-time vortex street main frequency.

[0108] Step S604: Analyze the real-time vortex street main frequency, real-time vortex street deviation, and cantilever length setting to determine the dynamic cantilever setting.

[0109] The dynamic cantilever beam setting is consistent with the dynamic cantilever beam setting in step S104, and is determined by the processing terminal through analysis of the real-time vortex street main frequency, real-time vortex street deviation, and cantilever beam length setting. Specific analysis steps are detailed below. Figure 7 The steps in the process.

[0110] Reference Figure 7 The steps for determining the dynamic suspension beam setting by analyzing the real-time vortex street main frequency, real-time vortex street deviation, and suspension beam length setting include: Step S700: Determine whether the real-time vortex shear deviation is greater than the preset gear shift deviation threshold.

[0111] Among them, the adjustment deviation threshold refers to the lower limit threshold of the vortex street deviation that needs to be changed at the length setting of the vibrating cantilever beam. The operator determines the resonant bandwidth corresponding to each length setting of the vibrating cantilever beam through offline pre-experiments. After determining the frequency matching range corresponding to the wind direction for efficient energy harvesting, the initial cantilever beam length is initially determined by combining the Karman vortex street frequency variation characteristics measured throughout the year in the energy harvester installation area and the frequency interval between the cantilever beam length settings. Then, the power generation efficiency of the energy harvester corresponding to different frequency deviations is determined. The initial cantilever beam length is fine-tuned based on the adjustment response speed of the vibrating cantilever beam, thereby avoiding frequent adjustments to the length setting of the vibrating cantilever beam and improving the energy harvesting efficiency of the energy harvester.

[0112] By processing the terminal to determine whether the real-time vortex shedding deviation is greater than the adjustment deviation threshold, it can be determined whether the length setting of the vibrating cantilever beam needs to be changed, thereby monitoring the energy output of the energy harvester in real time, adjusting the cantilever beam length in a timely manner, and improving energy harvesting efficiency.

[0113] Step S701: If it is not greater than, then continuously acquire the previous stable waveform, the sliding energy waveform and the average energy amplitude, calculate the real-time vortex shedding deviation and perform cyclic judgment.

[0114] If the processing terminal determines that the real-time vortex shedding deviation is not greater than the gear shifting deviation threshold, it indicates that there is no need to change the length gear of the cantilever beam at this time. Therefore, the preceding stable waveform, sliding energy waveform and energy amplitude mean are continuously acquired, and the real-time vortex shedding deviation is calculated for iterative judgment.

[0115] Step S702: If it is greater than, then obtain the frequency of the suspension beam corresponding to the suspension beam length position.

[0116] If the processing terminal determines that the real-time vortex shedding deviation is greater than the gear adjustment deviation threshold, it indicates that the cantilever beam length gear needs to be adjusted. Therefore, the cantilever beam gear frequency corresponding to each cantilever beam length gear is obtained.

[0117] The cantilever beam length range frequency refers to the natural vibration frequency of the vibrating cantilever beam corresponding to each cantilever beam length range. After determining the cantilever beam length range, the operator adjusts the vibrating cantilever beam to the cantilever beam length range and conducts an offline vibration experiment to measure and determine the natural vibration frequency of the cantilever beam length at different length ranges.

[0118] Step S703: Calculate the absolute deviation between the cantilever beam gear frequency and the real-time vortex street main frequency to determine the gear vortex street deviation.

[0119] Among them, the gear vortex street deviation refers to the deviation between the frequency of each cantilever gear and the real-time vortex street main frequency, which is determined by the processing terminal by calculating the absolute deviation between the cantilever gear frequency and the real-time vortex street main frequency.

[0120] Step S704: Perform numerical analysis on the gear vortex deviation to determine the minimum vortex deviation.

[0121] Among them, the minimum vortex street deviation refers to the minimum gear vortex street deviation. The minimum value of the gear vortex street deviation is determined by the processing terminal through numerical analysis of the gear vortex street deviation.

[0122] Step S705: Determine the cantilever length position corresponding to the minimum vortex shedding deviation as the dynamic cantilever position.

[0123] The dynamic suspension beam position is consistent with the dynamic suspension beam position in step S604. The processing terminal determines the suspension beam length position corresponding to the minimum vortex street deviation as the dynamic suspension beam position after determining the minimum vortex street deviation.

[0124] Based on the same inventive concept, embodiments of this application provide a Karman vortex street energy harvester control system, including: The acquisition module is used to acquire historical wind speed data, historical wind direction data, preceding stable waveform, sliding energy waveform, average energy amplitude, and cantilever beam frequency. A memory for storing a program for a Karman vortex street energy harvester control method; The processor can load and execute programs in memory to implement a Karman vortex street energy harvester control method.

[0125] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0126] This application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed as a Karman vortex street energy harvester control method.

[0127] Computer storage media include, for example, USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media that can store program code.

[0128] The above are all preferred embodiments of this application and are not intended to limit the scope of protection of this application. Any feature disclosed in this specification (including the abstract and drawings) may be replaced by other equivalent or similar features unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is only one example of a series of equivalent or similar features.

Claims

1. A control method for a Karman vortex street energy harvester, characterized in that, include: Obtain historical wind speed and historical wind direction data; Historical wind speed and direction data are analyzed to determine the fixed direction of the data logger, the minimum cantilever length, the cantilever length setting, and the initial cantilever setting. The preset energy collectors are deployed according to the fixed direction of the collectors, the preset maximum cantilever length, the preset minimum cantilever length, and the initial cantilever position. Obtain the preceding stable waveform, the sliding energy waveform, and the average energy amplitude; The dynamic suspension beam position is determined by analyzing the preceding stable waveform, sliding energy waveform, average energy amplitude, and suspension beam length position. Adjust the length of the pre-set vibrating cantilever beam on the energy harvester according to the dynamic cantilever beam setting to control the energy harvester's energy collection.

2. The control method for a Karman vortex street energy harvester according to claim 1, characterized in that, The steps for analyzing historical wind speed and direction data to determine the fixed direction of the data logger, minimum cantilever length, cantilever length setting, and initial cantilever setting include: Historical wind direction data corresponding to historical wind speed data are filtered according to a preset effective collection threshold to determine effective wind direction data; Analyze the effective wind direction data to determine the probability of effective wind direction and the effective wind direction for data collection; Data analysis is performed on the effective wind direction probability to determine the maximum wind direction probability; The effective wind direction corresponding to the maximum wind direction probability is determined as the fixed direction of the data collector. Historical wind speed data is extracted based on the fixed direction of the data collector to determine the effective wind speed; The effective wind speed is analyzed to determine the minimum cantilever length; The effective wind speed is analyzed to determine the suspension beam length setting and the initial suspension beam setting.

3. The control method for a Karman vortex street energy harvester according to claim 2, characterized in that, The steps for analyzing the effective wind speed to determine the minimum cantilever length include: Numerical analysis of effective wind speed is performed to determine the maximum effective wind speed; Input the maximum effective wind speed and the preset mass block diameter into the preset vortex shedding frequency model to determine the maximum vortex shedding frequency; Input the maximum vortex shedding frequency, the preset cantilever section constant, the preset cantilever elastic modulus, and the preset mass weight into the preset cantilever frequency model to determine the minimum cantilever length.

4. The control method for a Karman vortex street energy harvester according to claim 2, characterized in that, The steps for analyzing the effective wind speed to determine the cantilever length setting and the initial cantilever setting include: Cluster analysis was performed on the effective wind speed to determine the interval wind speed data and the amount of data in each interval. Data processing is performed on the interval data volume to determine the decreasing data volume; Based on the preset number of gear settings, the interval wind speed data corresponding to the decreasing data volume is extracted to determine the gear wind speed data. Data analysis is performed on the gear wind speed data to determine the gear wind range, gear wind speed probability, and gear wind speed. The decreasing data volume, wind speed range, wind speed probability, and wind speed at each gear are analyzed to determine the beam length gear and the initial beam gear.

5. The control method for a Karman vortex street energy harvester according to claim 4, characterized in that, The steps for analyzing decreasing data volume, wind speed range, wind speed probability, and wind speed at each gear to determine the cantilever length gear and the initial cantilever gear include: The expected value of the wind speed at each gear is calculated based on the probability of wind speed at each gear, in order to determine the base wind speed at each gear. Input the gear reference wind speed into the preset vortex shedding frequency model to determine the gear vortex shedding frequency. Input the vortex shedding frequency of the gear, the preset cantilever section constant, the preset cantilever elastic modulus, and the preset mass weight into the preset cantilever frequency model to determine the cantilever length gear. Extract data from the decreasing data volume to determine the maximum data volume; Data is extracted from the cantilever length range corresponding to the maximum data volume to determine the initial cantilever range.

6. The control method for a Karman vortex street energy harvester according to claim 1, characterized in that, The steps for determining the dynamic suspension beam position by analyzing the preceding stable waveform, sliding energy waveform, average energy amplitude, and suspension beam length position include: Determine whether the average energy amplitude is greater than the preset effective power generation threshold; If it is not greater than, the average energy amplitude will be continuously obtained for iterative judgment; If it is greater than 1, then perform Fourier transform on the preceding stable waveform and the sliding energy waveform to determine the preceding vortex street main frequency and the real-time vortex street main frequency. Calculate the relative deviation between the preceding vortex street frequency and the real-time vortex street frequency to determine the real-time vortex street deviation; The dynamic suspension beam setting is determined by analyzing the real-time vortex street main frequency, real-time vortex street deviation, and suspension beam length setting.

7. The control method for a Karman vortex street energy harvester according to claim 6, characterized in that, The steps for determining the dynamic cantilever beam setting by analyzing the real-time vortex street main frequency, real-time vortex street deviation, and cantilever beam length setting include: Determine whether the real-time vortex shear deviation is greater than the preset gear shift deviation threshold; If it is not greater than, then continuously acquire the preceding stable waveform, sliding energy waveform and average energy amplitude, calculate the real-time vortex shedding deviation and perform cyclic judgment; If it is greater than, then obtain the frequency of the cantilever beam corresponding to the cantilever beam length position; Calculate the absolute deviation between the cantilever beam gear frequency and the real-time vortex street main frequency to determine the gear vortex street deviation; Numerical analysis was performed on the gear shift vortex deviation to determine the minimum vortex deviation. The cantilever length range corresponding to the minimum vortex shedding deviation is determined as the dynamic cantilever range.

8. A control system for a Karman vortex street energy harvester, characterized in that, include: The acquisition module is used to acquire historical wind speed data, historical wind direction data, preceding stable waveforms, sliding energy waveforms, and average energy amplitude. A memory for storing a program for a Karman vortex street energy harvester control method as described in any one of claims 1 to 7; The processor and the program in the memory can be loaded and executed by the processor to implement the Karman vortex street energy harvester control method as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, The computer program is stored and can be loaded by a processor and executed as described in any one of claims 1 to 7 for controlling a Karman vortex street energy harvester.

Images