An energy control method for a vibration energy self-powered wireless sensor

Abstract

The application discloses a kind of energy control methods for vibration energy self-powered wireless sensor, comprising the following steps: step 1, setting sensor working time slot;Step 2, according to the vibration frequency of the vibration source collected by sensor in the past, the average vibration frequency of the vibration source in current time slot is predicted using exponential weighted moving average algorithm;Step 3, according to the vibration acceleration of the vibration source and the average vibration frequency predicted in current time slot, the vibration energy collection power of current time slot is predicted;Step 4, according to the vibration energy collection power predicted in current time slot, the duty cycle of sensor working is adaptively calculated;Step 5, sensor works using the calculated duty cycle in current time slot, and the wireless sensor system can have higher energy utilization efficiency and longer life cycle by the energy management algorithm.

Description

Technical Field

[0001] The present invention relates to the technical field of energy management of wireless sensor systems, and in particular to an energy control method for a vibration energy self-powered wireless sensor. Background Art

[0002] With the rapid development of information technology, wireless sensor systems have been widely used in many fields, including industrial monitoring, structural health assessment, and environmental monitoring. Wireless sensor systems sense the state of the external environment and convert it into valid data information. After local information processing, it is transmitted to the network via single-hop or multi-hop wireless communication for user use. However, traditional wireless sensor systems have limited available energy and are generally powered by batteries. If they are deployed in areas with complex terrain, batteries are difficult to replace. When the battery energy is exhausted, the sensor node will be unable to continue its mission. Therefore, the introduction of energy harvesting (EH) technology is of great significance for achieving sustainable unattended operation of wireless sensor systems.

[0003] Traditional environmental energy harvesting primarily involves solar energy and wind energy. However, most industrial equipment is located indoors, such as in manufacturing workshops and wind turbine rooms, making it difficult to harvest solar and wind energy. Vibration energy, as a novel energy harvesting source, is unaffected by factors such as location and weather. Furthermore, the electromagnetic vibration energy harvester used in vibration-powered wireless sensors boasts a simple structure, low cost, and relatively high power density. The electromagnetic vibration energy harvester is designed based on Faraday's law of electromagnetic induction. Its most basic structure consists of a permanent magnet, a spring, and an induction coil. When external vibration is present, the spring causes relative motion between the magnet and the induction coil, resulting in a change in the magnetic flux passing through the coil. This in turn generates an induced electromotive force in the induction coil, converting vibration energy into electrical energy.

[0004] Energy harvesting technology significantly extends the operational lifecycle of wireless sensor systems, but it also introduces new challenges. Wireless sensor systems require energy management to achieve a balance between energy collection and consumption, avoiding two extreme scenarios: on the one hand, if energy consumption is too low and energy harvesting is excessive, the energy storage device may become saturated and unable to fully utilize the available energy, resulting in waste. On the other hand, if energy consumption is too high and energy harvesting is insufficient, the sensor may become depleted and unable to operate normally, ultimately affecting the long-term reliability of the system and the integrity of the data collected.

[0005] Existing energy management methods for wireless sensor systems primarily include simple power management techniques such as fixed threshold control, rule-based scheduling strategies, and predictable energy arrival models. These methods have demonstrated some effectiveness in scenarios where the energy supply is relatively stable and periodic. However, because they typically rely on preset energy consumption models and static parameter configurations, they are less adaptable to vibration energy, an energy source with significant uncertainty. This can lead to system energy exhaustion and performance degradation. Therefore, it is necessary to develop more adaptive energy management algorithms tailored to the unique characteristics of vibration energy harvesting. Summary of the Invention

[0006] In view of the shortcomings of the existing technology, the present invention proposes an energy control method for a vibration energy self-powered wireless sensor. Through the energy management algorithm, the wireless sensor system can have higher energy utilization efficiency and longer life cycle.

[0007] In order to solve the above technical problems, the technical solution of the present invention is:

[0008] A method for controlling energy of a vibration-powered wireless sensor, comprising the following steps:

[0009] Step 1: Set the sensor working time slot;

[0010] Step 2: Based on the vibration frequencies of the previous vibration sources collected by the sensor, an exponentially weighted moving average algorithm is used to predict the average vibration frequency of the vibration source in the current time slot;

[0011] Step 3: predicting the vibration energy collection power of the current time slot based on the vibration acceleration of the vibration source and the average vibration frequency predicted in the current time slot;

[0012] Step 4: adaptively calculate the duty cycle of the sensor based on the vibration energy collection power predicted in the current time slot;

[0013] Step 5: The sensor operates using the calculated duty cycle in the current time slot.

[0014] Preferably, the working method of the sensor is: the sensor senses whether the vibration source is vibrating, and if the vibration source is in a non-vibrating state, the sensor maintains a low power consumption mode; if the sensor senses that the vibration source is in a vibrating state, the sensor switches to a working mode.

[0015] Preferably, the working time slot of the sensor is set to 10 minutes.

[0016] Preferably, the sensor includes a vibration pickup system and an energy conversion system, the vibration pickup system includes a moving mass block and a spring, and the moving mass block and the spring cooperate to convert the mechanical vibration of the vibration source into the vibration of the moving mass block; the energy conversion system includes an induction coil and a permanent magnet, and the induction coil and the permanent magnet convert the vibration energy of the moving mass block into electrical energy through Faraday's electromagnetic induction theorem.

[0017] Preferably, in step 4, the method for predicting the vibration energy collection power in the current time slot is:

[0018] First, according to the Laplace transform, when the vibration acceleration of the vibration source is a, the relative displacement of the moving mass block can be derived as z(t);

[0019] The magnetic flux and magnetic induction intensity are both related to the displacement of the moving mass block. According to the finite element method, the magnetic field is simulated using Ansoft Maxwell simulation software to obtain the magnetic flux of the moving mass block under different displacement conditions;

[0020] Secondly, a model was established and simulated using Simulink based on Laplace transform, dynamics, and Faraday's law of electromagnetic induction. The output power P(a, ω) of the vibration generator when the load resistance is R was obtained. The output power P(a, ω) of the vibration generator corresponding to the vibration acceleration a and vibration frequency ω of different vibration sources was recorded and interpolated to obtain the function F(a, ω) of the vibration generator output power with respect to the vibration acceleration a and vibration frequency ω.

[0021] Finally, at the beginning of each time slot, according to the vibration acceleration a of the vibration source and the predicted average vibration frequency ω of the vibration source in the current time slot, t , the predicted value of the vibration energy collection power in the current time slot is obtained through the function F(a,ω).

[0022] Preferably, in step 4, the calculation method of the duty cycle of the sensor is:

[0023] Step 4-1: Calculate the duty cycle d of the current time slot based on the predicted vibration energy harvesting power and the power of the sensor in working mode and sleep mode. predict ;

[0024] Step 4-2: Based on the difference between the remaining power percentage of the energy storage module in the sensor and the target power percentage, use the PID control algorithm to calculate the duty cycle d of the energy storage module. pid ;

[0025] Step 4-3, use weight β to predict and d pid Combined into the final duty cycle d final .

[0026] As an advantage, in step 4-1, the duty cycle d of the current time slot is predict The calculation method is:

[0027]

[0028] Among them, P collect is the predicted vibration energy harvesting power, P sleep is the power of the sensor in sleep mode, P active is the power of the sensor in working mode;

[0029] When P collect >P active When d predict The value of is limited to 1, that is, the sensor can maintain the working mode throughout the current time slot, and there is still excess harvested energy not used in the time slot; in this case, the PID control algorithm is used to dynamically increase d in subsequent time slots. predict value so that the overall energy consumed is still equal to the energy collected.

[0030] In addition, when there is a deviation between the predicted vibration energy harvesting power and the actual vibration energy harvesting power, or when the vibration source fails to maintain vibration in the entire time slot due to changes in the external environment, the PID control algorithm dynamically adjusts the d predict value so that the overall energy consumed is still equal to the energy collected.

[0031] Preferably, the weight β is the difference between the current remaining power percentage of the energy storage module and the target power percentage.

[0032] As an example, the working method of the sensor is as follows: the sensor is in the first d of the current time slot. final ×100% of the time is in working mode, collecting vibration data of the vibration source; and switches to sleep mode during the remaining time of the current time slot.

[0033] The present invention has the following characteristics and beneficial effects:

[0034] Adopting the above technical solution, the present invention uses the EWMA algorithm to predict the collected power of the current time slot based on the collected vibration signal, defines the duty cycle in combination with the power consumption of the sensor to achieve energy neutrality (Energy Neutrality), and combines the PID control algorithm to further adjust the duty cycle to achieve precise and dynamic energy regulation, thereby achieving the effect of not requiring regular battery replacement, supporting unattended operation, and reducing system maintenance costs. Compared with energy management algorithms that process solar energy, wind energy, and other energy sources with certain periodic characteristics, the algorithm proposed in the present invention shows more superior adaptability when dealing with vibration energy, an energy source with significant uncertainty: the algorithm can dynamically adjust the energy consumption strategy according to real-time conditions, thereby optimizing energy utilization efficiency and improving the overall reliability of the system. In addition, the algorithm has low computing cost and data storage cost, and can be well applied to the problem of limited hardware resources of sensing equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0036] Figure 1 The present invention is a method flow chart of a method for energy control of a vibration self-powered wireless sensor according to an embodiment of the present invention.

[0037] Figure 2 This is the trend of the remaining power of the energy storage module changing over time in the embodiment of the present invention. DETAILED DESCRIPTION

[0038] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0039] In the description of the present application, it needs to be understood that the terms "center", "longitudinal", "transverse", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, which is only for the convenience of describing the present application and simplifying the description, and does not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application. In addition, the terms "first", "second" and the like are only for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined with "first", "second" and the like can be explicitly or implicitly included one or more. In the description of the present application, unless otherwise specified, the meaning of "a plurality of" is two or more.

[0040] In the description of the present application, it needs to be understood that unless otherwise explicitly specified and limited, the terms "mounting", "connection", "connection" should be understood in a broad sense, for example, it can be fixed connection, or detachable connection, or integral connection; it can be mechanical connection, or electrical connection; it can be directly connected, or indirectly connected through intermediate medium, or it can be the communication inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood through specific circumstances.

[0041] The present application provides an energy control method for a vibration energy self-powered wireless sensor, comprising the following steps:

[0042] Step 1, setting the sensor working time slot.

[0043] It should be noted that the time slot can be selected to have different spans, such as 1 minute, 10 minutes, 30 minutes, 1 hour, etc. The smaller the span, the more accurate the energy prediction, but it will increase the calculation cost and the switching frequency of the working mode, thereby increasing the energy consumption. In this example, the energy prediction and energy consumption are balanced while facilitating data analysis and illustration, and the span of the selected time slot is 10 minutes.

[0044] In addition, for the working setting of the sensor operation, if the vibration source is in a non-vibration state, the sensor remains in a low-power mode; if the vibration source is in a vibration state, the sensor switches to a working mode.

[0045] Specifically, the sensor in low-power mode will reduce the sampling frequency to reduce power consumption, because the function of low-power mode is to detect the vibration of the vibration source when the vibration source is in a non-vibration state, rather than to collect specific vibration signals.

[0046] If the sensor senses that the vibration source is in a vibrating state, the sensor will collect the vibration signal, otherwise it will remain in low power consumption mode.

[0047] Step 2: Based on the vibration frequencies of the previous vibration sources collected by the sensor, an exponentially weighted moving average algorithm is used to predict the average vibration frequency of the vibration source in the current time slot.

[0048] Specifically, the Exponential Weighted Moving Average (EWMA) algorithm is used to predict the average vibration frequency ω of the vibration source at the current time slot t t ,Right now where ω t-1 is the EWMA value of the previous time slot, is the mean value of the vibration frequency of the previous time slot, and α is the smoothing coefficient.

[0049] The smoothing coefficient α in this algorithm adjusts the weighting of the predicted value between the data in the previous time slot and the data in the previous time slot. When α is large, the EWMA predicted value is more biased towards the mean frequency of the previous time slot, allowing it to quickly respond to drastic frequency changes. Conversely, when α is small, the EWMA predicted value tends to follow the past frequency trend, effectively smoothing short-term fluctuations and maintaining tracking of long-term trends.

[0050] The selection of α needs to be adjusted appropriately based on the actual characteristics of the vibration source. If the vibration source's frequency changes rapidly and is unstable, a larger α value is generally required to ensure the system's rapid response to the latest vibration frequency. For a vibration source that changes slowly and steadily, a smaller α value can be used. In this example, an α value of 0.6 is selected.

[0051] Step 3: The vibration energy collection power of the current time slot is predicted based on the vibration acceleration of the vibration source and the average vibration frequency predicted for the current time slot.

[0052] It should be noted that the energy supply of the sensor is based on the built-in vibration generator, and its basic components can be divided into the following according to their functions:

[0053] A vibration pickup system consisting of a moving mass and a spring that converts the mechanical vibration of the vibration source into vibration of the moving mass;

[0054] An energy conversion system consisting of an induction coil and a permanent magnet that converts the vibration energy of a moving mass block into electrical energy through Faraday's electromagnetic induction theorem.

[0055] Specifically, first, according to Laplace transform, when the vibration acceleration of the vibration source is a, the relative displacement of the moving mass block can be derived as z(t);

[0056] The magnetic flux and magnetic induction intensity are both related to the displacement of the moving mass block. According to the finite element method, the magnetic field is simulated using Ansoft Maxwell simulation software to obtain the magnetic flux of the moving mass block under different displacement conditions;

[0057] Secondly, based on Laplace transform, dynamics and Faraday's law of electromagnetic induction, a model was established using Simulink for simulation, and the output power P(a, ω) of the vibration generator when the load resistance is R was obtained. The output power P(a, ω) of the vibration generator corresponding to the vibration acceleration a and vibration frequency ω of different vibration sources was recorded, and combined with interpolation, the function F(a, ω) of the vibration generator output power with respect to the vibration acceleration a and vibration frequency ω was obtained.

[0058] It should be noted that the function F(a, ω) is obtained by combining the data obtained from the previous simulation with interpolation. Different models of vibration generators obtain different functions. The general steps are given here. Therefore, in this embodiment, no specific explanation is given.

[0059] Finally, at the beginning of each time slot, according to the vibration acceleration a of the vibration source and the predicted average vibration frequency ω of the vibration source in the current time slot, t , the predicted value of the vibration energy collection power in the current time slot is obtained through the function F(a,ω).

[0060] Step 4: Adaptively calculate the duty cycle of the sensor based on the vibration energy harvesting power predicted in the current time slot:

[0061] Step 4-1: Calculate the duty cycle d of the current time slot based on the predicted vibration energy harvesting power and the power of the sensor in working mode and sleep mode. predict ;

[0062] Specifically, after obtaining the predicted vibration energy harvesting power, the duty cycle d can be calculated in combination with the predicted vibration energy harvesting power. predict The calculation rule is to make the energy consumed in the current time slot equal to the collected energy, thereby avoiding the occurrence of two extreme situations: on the one hand, if the energy consumption is too low and the energy collection is excessive, the energy storage device may be saturated and unable to fully utilize the collectible energy, resulting in waste; on the other hand, if the energy consumption is too high and the energy collection is insufficient, the sensor may not be able to operate normally due to energy depletion, ultimately affecting the long-term reliability of the system and the integrity of data acquisition.

[0063] The duty cycle d of the current time slot predict The calculation method is:

[0064]

[0065] Among them, P collectis the predicted vibration energy harvesting power, P sleep is the power of the sensor in sleep mode, P active is the power of the sensor in working mode;

[0066] When P collect >P active When d predict The value of is limited to 1, that is, the sensor can maintain the working mode throughout the current time slot, and there is still excess harvested energy not used in the time slot; in this case, the PID control algorithm is used to dynamically increase d in subsequent time slots. predict value so that the overall energy consumed is still equal to the energy collected.

[0067] In addition, when there is a deviation between the predicted vibration energy harvesting power and the actual vibration energy harvesting power, or when the vibration source fails to maintain vibration in the entire time slot due to changes in the external environment, the PID control algorithm dynamically adjusts the d predict value so that the overall energy consumed is still equal to the energy collected.

[0068] Step 4-2: Based on the difference between the remaining power percentage of the energy storage module in the sensor and the target power percentage, use the PID control algorithm to calculate the duty cycle d of the energy storage module. pid .

[0069] Specifically, based on the difference between the current remaining power percentage of the energy storage module (e.g., rechargeable battery, capacitor, etc.) and the target power percentage, the PID control algorithm is used to calculate d pid The target power percentage refers to the power level that the energy storage module is expected to maintain. The specific value can be set during the system initialization phase. In this example, the target power percentage value selected is 80%.

[0070] It should be noted that the PID control algorithm has significant advantages in this scenario. Its proportional (P) control can directly adjust the duty cycle according to the current deviation, thereby quickly responding to changes in the power level; the integral (I) control corrects the long-term steady-state error by accumulating historical deviations to ensure that the system eventually converges to the target power level; the differential (D) control predicts the trend in advance by monitoring the rate of change of the deviation, thereby improving the system's response speed to sudden changes. The parameters of the PID control algorithm (proportional coefficient, integral coefficient, differential coefficient) can be determined by methods such as the Ziegler-Nichols method or the empirical trial and error method. The parameters selected in this example are K p =72,K i =5,K d =3.

[0071] Step 4-3, use weight β to predictand d pid Combined into the final duty cycle d final .

[0072] Specifically, in order to calculate the final duty cycle d final , by introducing the weight parameter β, the predicted duty cycle d predict The duty cycle d calculated by the PID control algorithm pid Combine them in a weighted summation manner, i.e. d final =(1-β)·d predict +β·d pid The value of the weight parameter β depends on the difference between the current remaining power percentage of the energy storage module and the target power percentage. When the remaining power of the energy storage module is close to the target power, it means that the prediction algorithm works well, d final It is more inclined to increase the proportion of the predicted value; when the remaining power of the energy storage module is significantly different from the target power, d final It is more inclined to increase the proportion of PID control algorithm output, thereby enhancing the dynamic response capability of the system.

[0073] Step 5: The sensor operates using the calculated duty cycle in the current time slot.

[0074] Specifically, the sensor uses a duty cycle d in the current time slot final To work, the sensor is in the first d of the current time slot final The system is in the non-mode for ×100% of the time, collecting data such as the vibration frequency and amplitude of the vibration source; it switches to the sleep mode for the remaining time of the current time slot, and returns to step 1 in the next time slot.

[0075] The following results were obtained based on the technical solution provided in the above example.

[0076] In this example, the maximum capacity of the energy storage module is 1000mWh. Figure 1 This graph shows how the remaining charge in the energy storage module changes over time in this energy management method. Analyzing the data in the graph clearly shows that the remaining charge remains relatively stable near the target value, demonstrating good energy balance. Quantitatively, the absolute error in the remaining charge remains within 10mWh, and the relative error is less than 1%, demonstrating that the system is capable of maintaining relatively accurate energy management over a long period of time.

[0077] This result demonstrates that the proposed energy management method can achieve efficient and stable energy control in vibration-powered wireless sensors, fully meeting the wireless sensor's requirements for low power consumption and long-term operation. More importantly, the method demonstrates excellent dynamic adjustment capabilities in the face of complex factors such as environmental changes and fluctuations in the vibration energy source. It can flexibly cope with energy supply uncertainties and ensure the system maintains stable operation in dynamic environments.

[0078] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited to the described embodiments. It will be apparent to those skilled in the art that various changes, modifications, substitutions, and variations of these embodiments, including components, without departing from the principles and spirit of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for energy control of a vibration self-powered wireless sensor, characterized in that: The steps include: Step 1: Set the sensor working time slot; Step 2: Based on the vibration frequencies of the previous vibration sources collected by the sensor, an exponentially weighted moving average algorithm is used to predict the average vibration frequency of the vibration source in the current time slot; Step 3: predicting the vibration energy collection power of the current time slot based on the vibration acceleration of the vibration source and the average vibration frequency predicted in the current time slot; Step 4: adaptively calculate the duty cycle of the sensor based on the vibration energy collection power predicted in the current time slot; The calculation method of the duty cycle of the sensor is: Step 4-1: Calculate the duty cycle d of the current time slot based on the predicted vibration energy harvesting power and the power of the sensor in working mode and sleep mode. predict ; Step 4-2: Based on the difference between the remaining power percentage of the energy storage module in the sensor and the target power percentage, use the PID control algorithm to calculate the duty cycle d of the energy storage module. pid ; Step 4-3, use weight β to predict and d pid Combined into the final duty cycle d final ; Step 5: The sensor operates using the calculated duty cycle in the current time slot.

2. The energy control method for a vibration energy self-powered wireless sensor according to claim 1, characterized in that: The working method of the sensor is as follows: the sensor senses whether the vibration source is vibrating, and if the vibration source is in a non-vibrating state, the sensor maintains a low power consumption mode; if the sensor senses that the vibration source is in a vibrating state, the sensor switches to a working mode.

3. The energy control method for a vibration energy self-powered wireless sensor according to claim 1, characterized in that: The working time slot of the sensor is set to 10 minutes.

4. The energy control method for a vibration energy self-powered wireless sensor according to claim 1, characterized in that: The sensor includes a vibration pickup system and an energy conversion system. The vibration pickup system includes a moving mass block and a spring. The moving mass block and the spring cooperate to convert the mechanical vibration of the vibration source into the vibration of the moving mass block; the energy conversion system includes an induction coil and a permanent magnet. The induction coil and the permanent magnet convert the vibration energy of the moving mass block into electrical energy through Faraday's electromagnetic induction theorem.

5. The energy control method for a vibration energy self-powered wireless sensor according to claim 4, characterized in that: In step 3, the method for predicting the vibration energy collection power in the current time slot is: First, according to the Laplace transform, when the vibration acceleration of the vibration source is a, the relative displacement of the moving mass block can be derived as z(t); The magnetic flux and magnetic induction intensity are both related to the displacement of the moving mass block. According to the finite element method, the magnetic field is simulated using Ansoft Maxwell simulation software to obtain the magnetic flux of the moving mass block under different displacement conditions; Secondly, a model was established and simulated using Simulink based on Laplace transform, dynamics, and Faraday's law of electromagnetic induction. The output power P(a, ω) of the vibration generator when the load resistance is R was obtained. The output power P(a, ω) of the vibration generator corresponding to the vibration acceleration a and vibration frequency ω of different vibration sources was recorded and interpolated to obtain the function F(a, ω) of the vibration generator output power with respect to the vibration acceleration a and vibration frequency ω. Finally, at the beginning of each time slot, according to the vibration acceleration a of the vibration source and the predicted average vibration frequency ω of the vibration source in the current time slot, t , the predicted value of the vibration energy collection power in the current time slot is obtained through the function F(a,ω).

6. The energy control method for a vibration energy self-powered wireless sensor according to claim 1, characterized in that: In step 4-1, the duty cycle d of the current time slot predict The calculation method is: Among them, P collect is the predicted vibration energy harvesting power, P sleep is the power of the sensor in sleep mode, P active is the power of the sensor in working mode; By adjusting the duty cycle d of the current time slot predict Dynamic adjustments are made so that the overall energy consumed still equals the energy collected.

7. The energy control method for a vibration energy self-powered wireless sensor according to claim 6, characterized in that: The duty cycle d of the current time slot predict The dynamic adjustment method is: when P collect >P active When d predict The value of is limited to 1, that is, the sensor can maintain the working mode throughout the current time slot, and there is still excess harvested energy not used in the time slot; in this case, the PID control algorithm is used to dynamically increase d in subsequent time slots. predict value so that the overall energy consumed is still equal to the energy collected; In addition, when there is a deviation between the predicted vibration energy harvesting power and the actual vibration energy harvesting power, or when the vibration source fails to maintain vibration in the entire time slot due to changes in the external environment, the PID control algorithm dynamically adjusts the d predict value so that the overall energy consumed is still equal to the energy collected.

8. The energy control method for a vibration energy self-powered wireless sensor according to claim 1, characterized in that: The weight β is the difference between the current remaining power percentage of the energy storage module and the target power percentage.

9. The energy control method for a vibration energy self-powered wireless sensor according to claim 1, characterized in that: The working method of the sensor is: the sensor is in the front d of the current time slot final ×100% of the time is in working mode, collecting vibration data of the vibration source; and switches to sleep mode during the remaining time of the current time slot.

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