A metamaterial energy transmission tuning method based on resonance shift detection

Abstract

The application is suitable for the field of wireless power transmission technology, and particularly relates to a metamaterial energy transmission tuning method based on resonance shift detection, which comprises the following steps: obtaining resonance information of a metamaterial unit; when it is judged that the resonance state of the metamaterial unit does not appear significant shift based on multiple resonance information mapped based on multiple time stamps adjacent to a current time stamp, then determining a resonance parameter in a current tuning parameter as a transmission parameter of the current time stamp; and generating a tuning control instruction to drive the metamaterial unit to adjust resonance characteristics based on the transmission parameter of the current time stamp. The metamaterial energy transmission tuning method based on resonance shift detection provided in the application can solve the problem of reduced energy transmission efficiency caused by fixed frequency or transmission based on instantaneous data calculation in the traditional metamaterial energy transmission process.

Description

Technical Field

[0001] This application belongs to the field of wireless power transfer technology, and in particular relates to a metamaterial power transfer tuning method based on resonance offset detection. Background Technology

[0002] Wireless power transfer is a method of transmitting electromagnetic fields or radio waves from a power source to a load via wireless means (e.g., electromagnetic field coupling), that is, transferring electrical energy from one place to another.

[0003] In the actual operating environment of metamaterial energy transfer systems, the resonant state of metamaterial units may shift due to environmental factors such as electromagnetic interference and temperature changes, leading to a decrease in energy coupling efficiency between the transmitter and receiver. In existing technologies, some solutions detect the deviation between the current resonant frequency and a preset target frequency, triggering frequency rescanning or parameter adjustment when the deviation exceeds a threshold. However, these solutions determine the need for tuning based solely on the frequency deviation at a single moment, which can easily lead to unnecessary parameter readjustment triggered by transient interference, causing unnecessary jumps in tuning parameters and resulting in a temporary decrease in transmission efficiency. For permanent environmental changes, the tuning parameters in existing solutions are calculated based on instantaneous data, making them susceptible to noise and unable to accurately reflect the true steady-state resonant state of the system, thus failing to maintain optimal transmission efficiency in complex electromagnetic environments. Both of these situations contribute to a reduction in the transmission efficiency of metamaterial energy transfer systems. Summary of the Invention

[0004] This application provides a metamaterial energy transfer tuning method based on resonance offset detection, which can solve the problem of reduced energy transfer efficiency caused by using fixed frequency or instantaneous data calculation in traditional metamaterial energy transfer processes.

[0005] In a first aspect, embodiments of this application provide a metamaterial energy transfer tuning method based on resonance offset detection, including: Obtain the resonance information of the metamaterial unit; wherein the resonance information is used to reflect the electromagnetic field strength, resonant frequency, or transmission efficiency; When it is determined that the resonant state of the metamaterial unit has not significantly shifted based on multiple resonant information mapped from multiple timestamps adjacent to the current timestamp, the resonant parameter in the current tuning parameters is determined as the transmission parameter of the current timestamp; wherein, the multiple timestamps are consecutive time nodes before the current timestamp; the current tuning parameters are calculated based on the multiple resonant information; when the metamaterial unit is operating in a stable environment mode, it is determined that the resonant state of the metamaterial unit has not significantly shifted. When a significant shift in the resonance state of the metamaterial unit is determined based on multiple resonance information, resonance trend data corresponding to the timestamp sequence within a preset time window is obtained, and the transmission parameters of the current timestamp are determined based on the resonance trend data. Based on the transmission parameters of the current timestamp, a tuning control command is generated to drive the metamaterial unit to adjust its resonance characteristics.

[0006] The technical solutions described in this application embodiment have at least the following technical effects: The metamaterial energy transfer tuning method based on resonance offset detection provided in this application determines that the resonance state of the metamaterial unit has not significantly shifted based on multiple resonance information mapped from multiple timestamps adjacent to the current timestamp. This indicates that the current system is in a stable transmission state with high energy coupling efficiency between the transmitter and receiver. The tuning parameters in the current configuration are used as the transmission parameters for the current timestamp. When a significant shift in the resonance state of the metamaterial unit is determined based on multiple resonance information, it indicates that the energy coupling efficiency between the transmitter and receiver is affected, and the tuning parameters in the current configuration are not meaningful for efficient transmission. The transmission parameters of the previous timestamps adjacent to the current timestamp are determined as the transmission parameters for the current timestamp. In this way, the resonance state of the metamaterial unit determined based on multiple resonance information can comprehensively reflect the changes in the resonance state of the metamaterial unit at multiple consecutive time nodes, rather than relying on the instantaneous data of a single timestamp. This helps to reduce the possibility of transient interference causing a jump in the tuning parameters. Then, the resonance trend data within a preset time window can reflect the direction and amplitude of resonance information changes at multiple consecutive time points. Determining transmission parameters based on the resonance trend data helps distinguish between resonance offsets caused by instantaneous interference and those caused by environmental changes. This allows for the determination of corresponding transmission parameters for resonance offsets of different natures, reducing the impact of resonance offsets on transmission efficiency. Finally, based on the transmission parameters at the current timestamp, tuning control commands are generated to drive the metamaterial unit to adjust its resonance characteristics. Determining the transmission parameters at the current timestamp by judging multiple resonance information avoids the problem of reduced energy transfer efficiency caused by using fixed frequencies or transmission based on instantaneous data calculations.

[0007] In a second aspect, embodiments of this application provide a metamaterial energy transfer tuning device for implementing the metamaterial energy transfer tuning method based on resonance offset detection as described in any of the first aspects above, applied to a metamaterial energy transfer system including tunable metamaterial units, the device comprising: An acquisition unit is used to acquire the resonance information of the metamaterial unit; wherein the resonance information is used to reflect the electromagnetic field strength, resonant frequency, or transmission efficiency. A determining unit is configured to, when determining, based on multiple resonance information mapped from multiple timestamps adjacent to the current timestamp, that the resonance state of the metamaterial unit has not significantly shifted, determine the resonance parameter in the current tuning parameters as the transmission parameter of the current timestamp; wherein, the multiple timestamps are consecutive time nodes prior to the current timestamp; the current tuning parameter is calculated based on the multiple resonance information; and when the metamaterial unit operates in a stable environment mode, it is determined that the resonance state of the metamaterial unit has not significantly shifted. The setting unit is used to obtain the resonance trend data corresponding to the timestamp sequence within a preset time window when it is determined that the resonance state of the metamaterial unit has significantly shifted based on multiple resonance information, and to determine the transmission parameters of the current timestamp based on the resonance trend data. The generation unit is used to generate tuning control commands based on the transmission parameters of the current timestamp to drive the metamaterial unit to adjust the resonance characteristics.

[0008] Thirdly, embodiments of this application provide a metamaterial energy transfer system, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the metamaterial energy transfer tuning method based on resonance offset detection as described in any of the first aspects above.

[0009] It is understood that the beneficial effects of the second and third aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a flowchart illustrating a metamaterial energy transfer tuning method based on resonance offset detection provided in an embodiment of this application. Figure 2 This is a schematic diagram of the implementation process for determining the resonance state of a metamaterial unit in a metamaterial energy transfer tuning method based on resonance offset detection provided in an embodiment of this application; Figure 3 This is a schematic diagram of the implementation process for determining the transmission parameters to be set for the current timestamp in a metamaterial energy transfer tuning method based on resonance offset detection provided in an embodiment of this application; Figure 4 This is a schematic diagram of the metamaterial energy transfer tuning device provided in the embodiments of this application; Figure 5 This is a schematic diagram of the metamaterial energy transfer system provided in the embodiments of this application. Detailed Implementation

[0012] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0013] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0014] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0015] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if the described condition or event is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once the described condition or event is detected," or "in response to the detection of the described condition or event."

[0016] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0017] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0018] In related technologies, wireless power transfer is a method of transmitting electromagnetic fields or radio waves from the power source to the load via wireless means (e.g., electromagnetic field coupling), that is, transferring electrical energy from one place to another.

[0019] Traditional methods rely on the resonant frequency deviation at a single moment for tuning decisions, resulting in a singular basis for judgment. In real-world operating environments, metamaterial energy transfer systems face diverse types of interference: one type is transient interference (e.g., occasional electromagnetic pulses, transient electromagnetic disturbances caused by equipment start-up and shutdown), characterized by short duration and limited impact, allowing the metamaterial unit's resonant state to recover spontaneously after the interference disappears; the other type is permanent environmental changes (e.g., continuously rising ambient temperature, new persistent electromagnetic interference sources), characterized by long duration and gradually increasing impact, preventing the metamaterial unit's resonant state from recovering spontaneously. Existing solutions employ the same triggering mechanism to respond to both types of interference, i.e., even when a transient interference causes the resonant frequency to briefly exceed a threshold, parameter readjustment is triggered, leading to unnecessary jumps in tuning parameters. These parameter jumps themselves cause a momentary shift in the metamaterial unit's resonant operating point, resulting in a temporary decrease in transmission efficiency. Furthermore, frequent parameter adjustments increase the computational burden on the control device and the adjustment frequency of hardware tuning components, accelerating hardware fatigue.

[0020] Furthermore, in existing schemes, after the trigger parameters are adjusted, the calculation of tuning parameters usually only relies on the instantaneous resonance data at the trigger moment. However, instantaneous resonance data is easily affected by random noise and instantaneous interference, causing the calculated tuning parameters to deviate from the true steady-state resonance state of the system. Based on such tuning parameters, the operating point of the metamaterial unit is not the optimal resonance point, and the transmission efficiency is difficult to achieve optimal.

[0021] To address the aforementioned issues, this application provides a metamaterial energy transfer tuning method based on resonance offset detection.

[0022] In this method, the resonance state of the metamaterial unit is determined to be stable without significant shift based on multiple resonance information mapped from multiple timestamps adjacent to the current timestamp. This indicates that the current system is in a stable transmission state and the energy coupling efficiency between the transmitter and receiver is high. The tuning parameters in the current configuration are used as the transmission parameters for the current timestamp. When the resonance state of the metamaterial unit is determined to be significantly shifted based on multiple resonance information, it indicates that the energy coupling efficiency between the transmitter and receiver is affected, and the tuning parameters in the current configuration are not meaningful for efficient transmission. The transmission parameters of the previous timestamps adjacent to the current timestamp are determined as the transmission parameters for the current timestamp. In this way, the resonance state of the metamaterial unit determined based on multiple resonance information can comprehensively reflect the changes in the resonance state of the metamaterial unit at multiple consecutive time nodes, rather than relying on the instantaneous data of a single timestamp. This helps to reduce the possibility of transient interference causing the tuning parameters to jump. Then, the resonance trend data within a preset time window can reflect the direction and amplitude of resonance information changes at multiple consecutive time points. Determining transmission parameters based on the resonance trend data helps distinguish between resonance offsets caused by instantaneous interference and those caused by environmental changes. This allows for the determination of corresponding transmission parameters for resonance offsets of different natures, reducing the impact of resonance offsets on transmission efficiency. Finally, based on the transmission parameters at the current timestamp, tuning control commands are generated to drive the metamaterial unit to adjust its resonance characteristics. Determining the transmission parameters at the current timestamp by judging multiple resonance information avoids the problem of reduced energy transfer efficiency caused by using fixed frequencies or transmission based on instantaneous data calculations.

[0023] The metamaterial energy transfer tuning method based on resonance offset detection provided in this application embodiment can be applied to metamaterial energy transfer systems. In this case, the metamaterial energy transfer system is the execution subject of the metamaterial energy transfer tuning method based on resonance offset detection provided in this application embodiment. This application embodiment does not impose any restrictions on the specific type of metamaterial energy transfer system.

[0024] For example, a metamaterial energy transfer system may include a transmitter (e.g., a transmitting coil, which generates an electromagnetic field through metamaterial units and converts electrical energy from a power source into electromagnetic waves for transmission), a receiver (e.g., a receiving coil, whose metamaterial units receive the electromagnetic waves transmitted by the transmitter and convert them into electrical energy), a power source (to provide a stable power source for the transmitter), and a control device. The metamaterial units may be composed of structural units with specific geometric shapes (such as small metal sheets, conductor coils, periodic arrays, etc.). The control device can determine the changes in the resonant state based on resonant information from multiple timestamps and thus determine the current transmission parameters.

[0025] In this embodiment, the specific structure of the metamaterial unit can be as follows: the metamaterial unit adopts an open resonant ring structure, for example, it can be an array composed of several basic resonant units arranged periodically. Each basic resonant unit can include: an outer ring conductor and an inner ring conductor, both of which are rectangular ring structures made of copper, and the openings of the outer ring conductor and the inner ring conductor are symmetrical. The outer ring conductor and the inner ring conductor are printed on the same side of the dielectric substrate, and the dielectric substrate is made of FR-4 material. The spacing between adjacent basic resonant units is a preset distance, for example, it can be 2 mm.

[0026] A variable capacitor element is placed at the opening of the inner conductor of each basic resonant unit. The capacitance value of the varactor diode changes with the reverse bias voltage, and the adjustment range can be from 2pF to 20pF. By changing the DC bias voltage applied across the varactor diode, the equivalent capacitance value of the basic resonant unit can be continuously adjusted, thereby changing the resonant frequency of the metamaterial unit.

[0027] The control interface of the metamaterial unit may include: a DC bias voltage input port, which is connected to the digital-to-analog converter output pin of the control device via a flexible printed circuit. The control device outputs an analog voltage signal through a DAC (digital-to-analog converter), which, after ripple is filtered out by a filter capacitor, is applied across the varactor diode to control the resonant frequency.

[0028] For example, the control device can be a microcontroller, tablet computer, laptop computer, ultra-mobile personal computer (UMPC), netbook, desktop computer, computing device, or computer, laptop computer, handheld communication device, handheld computing device, etc. connected to a wireless modem.

[0029] To better understand the metamaterial energy transfer tuning method based on resonance offset detection provided in the embodiments of this application, the specific implementation process of the metamaterial energy transfer tuning method based on resonance offset detection provided in the embodiments of this application will be described by way of example below.

[0030] Figure 1 A schematic flowchart of a metamaterial energy transfer tuning method based on resonance offset detection provided in this application is shown. The metamaterial energy transfer tuning method based on resonance offset detection includes: S100 acquires the resonance information of the metamaterial unit. This resonance information reflects the electromagnetic field strength, resonant frequency, or transmission efficiency.

[0031] It is understood that the metamaterial unit integrates an electromagnetic sensor array for real-time acquisition of electromagnetic field strength. These electromagnetic sensors include magnetic field strength sensors and electric field strength sensors, capable of measuring changes in the electromagnetic environment surrounding the metamaterial unit. By sampling and performing spectral analysis on the electromagnetic signal generated when the metamaterial unit resonates, the actual resonant frequency of the metamaterial unit can be obtained and compared with a preset ideal resonant frequency, thus yielding data reflecting the deviation from the resonant frequency. The efficiency of wireless power transmission can be calculated based on the input power of the transmitter and the output power of the receiver.

[0032] In this embodiment, the resonance information exists in the form of a structured data set, specifically including: timestamp identifier, resonant frequency value (unit: MHz), electromagnetic field strength value (unit: dBμV / m), and transmission efficiency value (unit: %). The resonance information can be acquired by the control device in each timestamp period T (e.g., T=100ms) by using a frequency counter to collect the actual resonant frequency f of the metamaterial unit, using an electromagnetic sensor array to collect the electromagnetic field strength E around the metamaterial unit, and using a power detection circuit to obtain the transmitter input power Pin and receiver output power Pout, and then calculating the transmission efficiency η = Pout ÷ Pin × 100%. In the tuning method of this application, the resonant frequency f is used as the core parameter reflecting the resonance state for offset judgment and tuning calculation, the electromagnetic field strength E is used as an auxiliary parameter for environmental noise assessment, and the transmission efficiency η is used for final tuning effect verification.

[0033] With this setup, the acquired resonance information can be used as the basis for generating tuning control commands, enabling the system to automatically adjust the resonance characteristics of the metamaterial unit according to changes in the environment or working state, thereby achieving intelligent and automated wireless power transmission.

[0034] S200, when it is determined that the resonant state of the metamaterial unit has not significantly shifted based on multiple resonance information mapped from multiple timestamps adjacent to the current timestamp, the resonance parameter in the current tuning parameters is determined as the transmission parameter of the current timestamp. Here, multiple timestamps are consecutive time nodes preceding the current timestamp. The current tuning parameters are calculated based on multiple resonance information. When the metamaterial unit operates in a stable environment mode, it is determined that the resonant state of the metamaterial unit has not significantly shifted.

[0035] It can be understood that the resonant state is used to reflect the operating state of the metamaterial unit. Resonance parameters indicate various characteristics and performance indicators of the metamaterial unit in the resonant state, such as resonant frequency and matching impedance. Transmission parameters indicate the parameters that should be set in the metamaterial energy transfer system; for example, transmission parameters include the resonant frequency. When the environmental noise data received by the metamaterial unit within a preset continuous time period does not exceed a preset environmental interference threshold, it is determined that the metamaterial unit is operating in a stable environmental mode. In this stable environmental mode, it is determined that the resonant state of the metamaterial unit does not show a significant shift. The transmission parameters can be the final set values ​​used to generate tuning control commands.

[0036] Key parameters (such as resonant frequency, electromagnetic field strength, and transmission efficiency) in the resonant information mapped from multiple timestamps are assigned different weights. More recent resonant information, being closer to the current state, can be assigned higher weights, while information from more distant times has relatively lower weights. For example, when calculating the current resonant frequency tuning parameters, the resonant frequencies of the past five timestamps are assigned weights of 0.1, 0.15, 0.2, 0.25, and 0.3 respectively. The resonant frequency value in the current tuning parameters is then calculated using the formula f = 0.1 × f1 + 0.15 × f2 + 0.2 × f3 + 0.25 × f4 + 0.3 × f5. In other words, the current tuning parameters are calculated based on multiple resonant information between the current and previous timestamps adjacent to the current timestamp. Similarly, the tuning parameters of previous timestamps can be calculated based on multiple resonant information between previous timestamps adjacent to previous timestamps.

[0037] For example, when calculating the resonant frequency value in the current tuning parameters, a weighted moving average method based on a time decay model can be used. Specifically, the resonant frequency data of the five consecutive timestamps before the current timestamp (f1 is the earliest, f5 is the most recent) are selected and assigned weights w1, w2, w3, w4, and w5. The weights are determined using an exponentially weighted moving average method, meaning that data closer to the current timestamp has a higher weight, to better reflect the real-time state of the system. The specific calculation method for the weights is as follows: First, set the basic decay coefficient α = 0.5, then the weight corresponding to the i-th timestamp is: wi = α^(ni) ÷ Σ(α^(nj)), where i = 1, 2, ..., 5, j = 1, 2, ..., 5. When the window number n = 5 and α = 0.5, the normalized weight values ​​are approximately w1 = 0.033, w2 = 0.067, w3 = 0.133, w4 = 0.267, w5 = 0.5. To facilitate hardware implementation, the above weights are linearly simplified and approximated, resulting in simplified weight values ​​of 0.1, 0.15, 0.2, 0.25, and 0.3. The simplified weights maintain an increasing trend and their sum is 1.

[0038] Compared with the traditional Kalman filter algorithm, the weighted moving average method adopted in this scheme has the following advantages: (1) low computational complexity, requiring only multiplication and addition operations; (2) no need to pre-establish accurate system state equations and noise covariance matrices, reducing the difficulty of system modeling; (3) through adjustable window number and weight distribution, it can flexibly adapt to the needs of different application scenarios (for example, by using the statistical smoothing effect of multi-point data to reduce the influence of noise components in a single instantaneous data point, so that the tuning parameters are closer to the steady-state resonance state of the system, so that the random noise components at a single timestamp are partially canceled in the weighted averaging process). In the wireless power transmission scenario of this application, the system mainly faces slow drift and occasional instantaneous interference caused by the external environment, and the weighted moving average method can effectively deal with such interference modes.

[0039] The frequency data is obtained by subtracting the resonant parameter from the tuning parameters determined by multiple resonant information of the current timestamp from the transmission parameters of the previous timestamp adjacent to the current timestamp. The frequency data is then judged to determine whether it meets the first requirement, which indicates that the value of the frequency data is within a set range.

[0040] When the value of the frequency data is within the set range, it means that the resonance state of the metamaterial unit at the previous timestamp is basically the same as or has not changed much from the resonance state of the current metamaterial unit. In this case, the resonance parameter in the current tuning parameters can be determined as the transmission parameter of the current timestamp.

[0041] When the frequency data value is not within the set range, it can be determined whether the current interference is transient (for example, the values ​​corresponding to the first few resonance information are greater than the maximum value of the set range (e.g., the first 2 or 3), but the next or subsequent two resonance information quickly return to normal (e.g., the values ​​corresponding to the last two resonance information are within the set range), indicating that it may be transient interference). If so, S300 is executed. If not, the resonance parameter in the current tuning parameters is determined as the transmission parameter of the current timestamp.

[0042] In this embodiment, the current tuning parameters may include: the resonant frequency parameter fx and the matching impedance parameter Zx. The resonant frequency parameter fx is calculated using a weighted moving average method, as shown in the previous embodiment. The matching impedance parameter is calculated based on the resonant frequency parameter fx using the impedance matching formula, specifically, Zx = Z0 × (f0 ÷ fx)^(1 ÷ 2), where Z0 is the standard impedance value (e.g., 50Ω) and f0 is the standard resonant frequency.

[0043] This setup allows for continuous monitoring of the metamaterial unit's operating state by comparing resonance information from multiple timestamps. If there is no significant shift between the current and previous timestamps' resonance states, it indicates that the metamaterial unit's operating state is relatively stable. In this case, using the current tuning parameter as the transmission parameter ensures stable system operation and avoids instability caused by over-adjustment.

[0044] S300: When it is determined that the resonance state of the metamaterial unit has shifted significantly based on multiple resonance information, the resonance trend data corresponding to the timestamp sequence within the preset time window is obtained, and the transmission parameters of the current timestamp are determined based on the resonance trend data.

[0045] In one possible implementation, when a significant shift in the resonant state of a metamaterial unit is determined based on multiple resonance information, the method further includes the following differentiation processing logic: S301, acquire the resonance trend data corresponding to the timestamp sequence within a preset duration window. Specifically, the length of the preset duration window can be set according to the system response characteristics, for example, a time span of 5 to 10 consecutive timestamps. Record the resonance frequencies corresponding to each timestamp within the window to form a time-frequency trend sequence.

[0046] S302, calculate the slope of frequency change between adjacent time stamps in the trend sequence. When the absolute value of the slope of frequency change between adjacent time stamps shows a decreasing trend time-by-time within a preset observation window (e.g., at least 3 consecutive time stamps), it indicates that the frequency offset is decaying. Furthermore, before the end of the preset duration window, if the resonant frequency returns to the set tolerance range of the resonant frequency corresponding to the current tuning parameter (e.g., tolerance range of ±2%), the recovery condition is met, and the significant offset is determined to be transient interference. The selection of the set tolerance range can be based on the typical bandwidth characteristics of the resonant curve (e.g., half-power point bandwidth) and transmission efficiency (e.g., efficiency drop does not exceed a preset threshold, such as 1%), or it can be determined through pre-simulation or experimental testing.

[0047] Specifically, the criterion for judging whether the absolute value of the slope shows a decreasing trend with respect to each time stamp can be as follows: within a preset duration window, select at least 3 adjacent time stamp pairs consecutively, calculate the absolute value of the frequency change slope between each pair of adjacent time stamps, and when the absolute values ​​of these at least 3 slopes decrease sequentially (i.e., the absolute value of the later slope is strictly less than the absolute value of the previous slope), it is determined that the absolute value of the slope satisfies the decreasing trend with respect to each time stamp.

[0048] In this embodiment, the method for determining whether a significant shift has occurred in the resonant state may include: subtracting the resonant frequency fa in the tuning parameters of the current timestamp from the resonant frequency fb in the transmission parameters of the previous timestamp to obtain the frequency data Δf = |fb-fa|. When Δf is within a set interval [Δfmin, Δfmax] (e.g., [0.5, 5.0] MHz), it is determined that no significant shift has occurred; when Δf exceeds the set interval, a secondary judgment is made by combining the resonant information trends of multiple historical timestamps.

[0049] S302a, when a significant offset is determined to be a transient interference, the resonant dataset of the previous timestamp adjacent to the current timestamp is obtained, and the transmission parameters of the previous timestamp are read from it; wherein, the transmission parameters of the previous timestamp include the resonant frequency and the matching impedance.

[0050] S302b directly determines the transmission parameters of the previous timestamp as the transmission parameters of the current timestamp, that is, the resonant frequency of the current timestamp is equal to the resonant frequency of the previous timestamp, and the matching impedance of the current timestamp is equal to the matching impedance of the previous timestamp.

[0051] S302c uses the transmission parameters determined by the current timestamp as the key node of the data stream, overwrites the resonant dataset of the previous timestamp with data, and generates the resonant dataset of the current timestamp, which is used to indicate the transmission parameters of the subsequent timestamps adjacent to the current timestamp.

[0052] With this setup, when the interference is determined to be transient, since transient interference is brief and sporadic, the actual resonant state of the system does not change substantially. Therefore, the stable transmission parameters before the interference occurred are directly used to avoid the tuning parameter jump caused by transient interference, thus ensuring that the system maintains stable transmission efficiency during the interference period.

[0053] S303. When the recovery condition is not met, i.e., the resonant frequency has not returned to the set tolerance range by the end of the preset time window, or the slope of the frequency change does not show a decaying trend (e.g., the absolute value of the slope continues to increase or remains constant), the significant offset is determined to be a permanent environmental change. At this time, the system triggers the resonant point re-search process.

[0054] Specifically, before performing a frequency scan, the current frequency offset is first evaluated to determine whether it is worthwhile to initiate a re-search process. Specifically, the resonant frequency at the current timestamp is compared with the resonant frequency in the current tuning parameters, and the frequency offset percentage δ = |fcurrent - ftun| ÷ ftun × 100%. When δ is less than a preset minimum search threshold δmin (e.g., 1%), it is determined that the current offset is small, and the efficiency loss from initiating a frequency scan may exceed the efficiency loss from using the current parameters. In this case, the system does not initiate a re-search and directly uses the resonant parameters in the current tuning parameters as the transmission parameters for the current timestamp, avoiding unnecessary efficiency loss. When δ is greater than or equal to δmin, the system initiates a re-search process. The selection of δmin can be determined based on the system's tolerance for efficiency degradation. For example, it can be determined through pre-simulation experiments. For instance, at different offsets, the transmission efficiency using the old parameters is compared with the average transmission efficiency during the frequency scan, and the offset corresponding to the zero efficiency difference between the two is taken as δmin.

[0055] Once it is determined that a re-search needs to be initiated, a frequency scan is performed with the resonant frequency of the current timestamp as the center, within a preset search bandwidth range (e.g., ±10% of the frequency range) and a preset step size (e.g., 0.5% of the frequency step size); at each scan frequency point, the transmission efficiency data of the metamaterial unit is collected.

[0056] In order to control efficiency loss during the frequency scanning process and shorten the time the system is in a suboptimal state, this embodiment adopts the following optimization strategy: (1) Hierarchical scanning strategy: A hierarchical scanning method of coarse first and fine later is adopted. The first coarse scan quickly covers the entire search bandwidth with a large step size (e.g., 2%) to initially determine the frequency band range with high transmission efficiency; the second fine scan only performs fine scanning within this high-efficiency frequency band range with a small step size (e.g., 0.5%), thereby reducing the number of scan points required for full-band scanning from most to a few while ensuring search accuracy, so as to shorten the scanning time.

[0057] (2) Early termination strategy: During the scanning process, the highest transmission efficiency value among the currently scanned frequency points is recorded in real time. When it is found that the transmission efficiency of a certain frequency point has reached the preset efficiency target value (for example, not less than 102% of the transmission efficiency before scanning, that is, it is better than the original parameter), the scanning is terminated immediately, and the frequency point is determined as the new resonant point, thereby avoiding unnecessary scanning of the remaining frequency points.

[0058] (3) Transmission guarantee during scanning: During scanning, the dwell time of the system at each scanning frequency point is controlled within a single timestamp period (e.g., 100ms) to limit the duration of the system in a non-optimal transmission state. At the same time, when switching between adjacent scanning frequency points during scanning, a smooth transition method is adopted (i.e., the bias voltage of the varactor diode is gradually adjusted by the DAC, rather than a step-like switching) to reduce the efficiency drop at the moment of frequency switching.

[0059] Through the aforementioned pre-search evaluation and hierarchical scanning optimization strategies, the system can control the efficiency loss and scanning time during frequency scanning within an acceptable range while ensuring search accuracy. The frequency point with the highest transmission efficiency is selected as the new resonant point, and the frequency corresponding to the new resonant point is determined as the transmission parameter for the current timestamp.

[0060] With this setup, when a significant offset is detected, the system can first determine whether the offset is a transient disturbance through trend analysis. For transient disturbances, the stable parameters from the previous timestamp are used to avoid erroneous adjustments; for permanent environmental changes, the system actively performs a re-search for the resonant point to find a new optimal operating point, achieving true adaptive optimization rather than simply reverting to old parameters.

[0061] S400 generates tuning control commands based on the transmission parameters of the current timestamp to drive the metamaterial unit to adjust its resonant characteristics.

[0062] It can be understood that the transmission parameters of the current timestamp information are mapped to specific hardware tuning parameter adjustment amounts, that is, control commands are generated to adjust the variable capacitance or inductance values ​​in the metamaterial unit.

[0063] This configuration allows for adjustments to transmission parameters based on actual conditions, thereby avoiding the problem of reduced energy transmission efficiency caused by transmission at fixed frequencies or with fixed signals.

[0064] In one possible implementation, please refer to Figure 2 Metamaterial energy transfer tuning methods based on resonance offset detection also include: S201, when the frequency data meets the first requirement, it is determined that the resonant state of the metamaterial unit has not shifted significantly. The frequency data is obtained based on the resonant parameters in the current tuning parameters and the transmission parameters of the previous timestamp adjacent to the current timestamp.

[0065] It is understandable that frequency data is used to reflect the degree of difference between the transmission parameters of the previous timestamp adjacent to the current timestamp and the resonant parameters in the tuning parameters determined by multiple resonant information of the current timestamp. The frequency data is obtained by subtracting the resonant parameters in the tuning parameters determined by multiple resonant information of the current timestamp from the transmission parameters of the previous timestamp adjacent to the current timestamp. It is then determined whether the frequency data meets the first requirement, which can be a set interval, for example, [2,10].

[0066] When the frequency data meets the first requirement (for example, the frequency data is 3, which is within the threshold region [2,10]), it means that the resonance state of the metamaterial unit at the previous timestamp is basically consistent with or has not changed much from the resonance state of the current metamaterial unit, that is, the resonance state of the metamaterial unit has not shifted significantly.

[0067] This setup indicates that the metamaterial unit is in a stable resonant state, eliminating the need for tuning commands and reducing resource waste and hardware fatigue caused by frequent system adjustments.

[0068] S202, when the frequency data does not meet the first requirement, and it is determined based on multiple resonance information that the resonance state of the metamaterial unit has not shifted significantly, it is determined that the resonance state of the metamaterial unit has not shifted significantly.

[0069] It is understandable that when the frequency data does not meet the first requirement (for example, the frequency data is 15, which is outside the threshold region [2,10]), it is possible to determine whether the resonance state of the metamaterial unit has significantly shifted based on multiple resonance information. For example, if multiple resonance information are all normal values ​​and it is determined that the resonance state of the metamaterial unit has not significantly shifted, then the resonance parameter in the current tuning parameter calculated based on multiple resonance information can be determined as the transmission parameter of the current timestamp.

[0070] With this setup, by analyzing the trends of multiple resonance information (such as some resonance information showing abnormalities but then recovering quickly), it is possible to identify anomalies caused by transient noise or interference, and avoid misjudging them as the true offset of the metamaterial unit resonance.

[0071] S203, when the frequency data does not meet the first requirement, and the resonance state of the metamaterial unit is significantly shifted based on multiple resonance information, the resonance state of the metamaterial unit is significantly shifted.

[0072] It is understandable that when the frequency data does not meet the first requirement (for example, the frequency data is 15, which is outside the threshold region [2,10]), it is possible to determine whether the resonance state of the metamaterial unit has shifted significantly based on multiple resonance information. For example, if the current resonance information is greater than the historical value (for example, the first 2 or 3), but the next or subsequent two resonance information quickly returns to normal, it indicates that there may be instantaneous interference, that is, it is determined that the resonance state of the metamaterial unit has shifted significantly. At this time, the current tuning parameters calculated based on multiple resonance information cannot be adapted to the metamaterial energy transfer system, that is, the current tuning parameters calculated based on multiple resonance information are meaningless. Then, the transmission parameters of the previous timestamp adjacent to the current timestamp can be determined as the transmission parameters of the current timestamp.

[0073] This setup, by analyzing the trends of multiple resonance information (such as some resonance information showing anomalies but then quickly recovering), can identify anomalies caused by transient noise or interference, rather than long-term changes in the system itself. This helps to identify these disturbances in a timely manner and avoid misjudgments, ensuring that the system is not subjected to meaningless or excessive adjustments.

[0074] In one possible implementation, please refer to Figure 3 Before generating tuning control commands to drive the metamaterial unit to adjust its resonance characteristics based on the transmission parameters of the current timestamp in step S400, the metamaterial energy transfer tuning method based on resonance offset detection further includes: S410 measures environmental noise data in a metamaterial energy transfer system. This environmental noise data reflects the impact of environmental factors on wireless power transmission.

[0075] Understandably, a spectrum analyzer or integrated spectrum analysis module is used to scan the operating frequency band and surrounding frequency bands to identify interference signal peaks and broadband noise levels, such as electromagnetic interference intensity. Real-time temperature is obtained through a temperature sensor, and environmental noise data is determined based on the electromagnetic interference intensity and temperature. For example, the environmental interference value K = wE × +wT× Where, wE=0.6, wT=0.4, wE is the weighting coefficient of the electromagnetic interference component, and wT is the weighting coefficient of the temperature component. E is the electromagnetic interference intensity. E0 is the ambient background noise baseline value, such as 30dBμV / m. Emax is the system's anti-interference design threshold, such as 80dBμV / m. T is the acquired real-time temperature. T0 is the standard operating temperature, such as 25°C. Tmax is the critical temperature for metamaterial performance stability, such as 60°C.

[0076] Specifically, the weighting coefficients K can be determined through orthogonal experiments: An L25(5²) orthogonal experimental table was designed, and the transmission efficiency change Δη of the metamaterial energy transfer system was measured under 25 combinations of 5 electromagnetic interference intensity levels (30, 40, 50, 60, 70 dBμV / m) and 5 temperature levels (25, 30, 40, 50, 55°C). Using the normalized electromagnetic interference component XE=(E-E0)÷(Emax-E0) and temperature component XT=(T-T0)÷(Tmax-T0) as independent variables, and the transmission efficiency change Δη as the dependent variable, a multiple linear regression analysis was performed: Δη=a1·XE+a2·XT+ζ. The regression coefficients a1 and a2, after normalization, become the weighting coefficients wE and wT.

[0077] It should be noted that the linear weighted model of the above environmental interference values ​​can accurately reflect the comprehensive impact of environmental factors when both electromagnetic interference intensity and temperature are at a moderate level. When the electromagnetic interference intensity or temperature is at an extreme value (such as electromagnetic interference intensity close to Emax or temperature close to Tmax), there may be a nonlinear interaction effect between electromagnetic interference and temperature, and the linear model may produce a certain deviation. In another embodiment, the accuracy of the model can be improved by: (1) adding interaction terms to correct according to the actual application scenario, such as K'=K+wET×XE×XT; (2) fitting a nonlinear correction function through experimental data.

[0078] This configuration, using the aforementioned linear weighted environmental interference value model, offers an advantage over schemes that set separate thresholds for electromagnetic interference and temperature to trigger judgments. It allows for a unified quantitative index K to comprehensively reflect the coupled effects of the two factors, avoiding missed detections when a single factor does not exceed its threshold but the combined effect of the two factors produces a significant impact. The weighting coefficients were determined through orthogonal experiments and regression analysis, ensuring the objectivity of the model's predictions regarding changes in transmission efficiency.

[0079] When the environmental interference value K of the environmental noise data is greater than the interference threshold (e.g., 0.7), it is determined that environmental factors have an impact on wireless power transmission. When the environmental interference value K of the environmental noise data is less than or equal to the interference threshold (e.g., 0.7), it is determined that environmental factors have no impact on wireless power transmission.

[0080] With this setup, by scanning the frequency band using a spectrum analyzer or integrated spectrum analysis module and combining it with temperature sensor data, the environmental interference value can be calculated. This objectively and quantitatively reflects the degree of influence of environmental factors (such as electromagnetic interference and temperature) on wireless power transmission, which helps the system make reasonable tuning decisions under different environmental conditions.

[0081] S420, when environmental noise data indicates that environmental factors affect wireless power transmission, generates a composite tuning command based on the transmission parameters at the current timestamp and the environmental noise data. The composite tuning command carries the transmission parameters that should be set at the current timestamp.

[0082] It is understandable that when environmental noise data reflects that environmental factors have an impact on wireless power transmission, it means that the transmission parameters of the current timestamp need to be corrected. Therefore, a composite tuning command can be generated based on the transmission parameters of the current timestamp and the environmental noise data.

[0083] When environmental noise data reflects the impact of environmental factors on wireless power transmission, a correction frequency is generated based on the electromagnetic interference intensity. For example, Δf = 0.1 × (E - 50), and the correction frequency f = f0 + Δf, where E is the electromagnetic interference intensity in the environmental noise data, and f0 is the resonant frequency in the transmission parameters at the current timestamp. An impedance correction coefficient is calculated based on temperature, and the corrected matching impedance is obtained from this coefficient. For example, the impedance correction coefficient Kt = 1 + 0.002 × (T - 25), and the corrected matching impedance Z1 = Z0 × Kt, where Kt is the impedance correction coefficient, T is the temperature data in the environmental noise data, and Z0 is the impedance in the transmission parameters at the current timestamp.

[0084] Furthermore, E=50dBμV / m is the correction zero point, indicating that no frequency correction is needed under this electromagnetic interference intensity. This value corresponds to the typical interference level of a general indoor electromagnetic environment. When the electromagnetic interference intensity E<50dBμV / m, Δf is negative, indicating that the resonant frequency is slightly adjusted towards lower frequencies to compensate for the slight positive bias of the resonant characteristics due to the ambient background noise. When the temperature exceeds the applicable range of linear correction (e.g., >55°C), the impedance correction coefficient can adopt a quadratic correction model: Kt=1+0.002×(T-25)+0.00005×(T-25)^2. E=50dBμV / m corresponds to the electromagnetic interference intensity measurement value when the resonant frequency offset of the metamaterial unit is less than 0.1% under standard test conditions (no additional electromagnetic interference source, temperature 25°C), which can be determined by averaging multiple experimental measurements.

[0085] The frequency correction and matching impedance correction are mapped to specific hardware tuning parameter adjustments, i.e., a composite tuning command is generated to adjust the frequency and tuning capacitor. Once the composite tuning command is generated, it replaces the tuning control command.

[0086] This setup allows for an objective and quantitative reflection of the impact of environmental factors (such as electromagnetic interference and temperature) on wireless power transmission, which helps the system make reasonable tuning decisions under different environmental conditions.

[0087] S430, when the environmental noise data indicates that environmental factors have no impact on wireless power transmission, the transmission parameters of the current timestamp are determined as the transmission parameters that should be set for the current timestamp.

[0088] It is understandable that when environmental noise data reflects that environmental factors have no impact on wireless power transmission, it means that the transmission parameters of the current timestamp do not need to be corrected, and the transmission parameters of the current timestamp can be directly determined as the transmission parameters that should be set for the current timestamp.

[0089] This configuration avoids frequent and unnecessary parameter adjustments when environmental interference is minimal, reduces calculation and adjustment time during tuning, and improves system response speed and transmission efficiency.

[0090] In one possible implementation, the environmental noise data carries the intensity of environmental electromagnetic interference and temperature parameters. The metamaterial energy transfer tuning method based on resonance offset detection also includes: S411, determine the environmental interference value based on the intensity and temperature of the environmental electromagnetic interference.

[0091] It is understandable that the intensity of environmental electromagnetic interference and temperature can be substituted into the formula for calculating the environmental interference value to obtain the environmental interference value. For example, the environmental interference value K = wE × +wT× Where wE=0.6, wT=0.4, wE is the weighting coefficient of the electromagnetic interference component, and wT is the weighting coefficient of the temperature component. E is the electromagnetic interference intensity. E0 is the ambient background noise baseline value, such as 30 dBμV / m (e.g., it can be obtained by consulting the standard electromagnetic environment value under external electromagnetic interference). Emax is the system's anti-interference design threshold, such as 80 dBμV / m (e.g., it can be determined by gradually increasing the intensity of the interference source and monitoring the resonant frequency shift in an experiment). T is the acquired real-time temperature. T0 is the standard operating temperature, such as 25°C. Tmax is the critical temperature for metamaterial performance stability, such as 60°C.

[0092] For example, the specific weights of the electromagnetic interference (EMI) and temperature components can be determined by conducting orthogonal experiments, measuring the change in transmission efficiency of the wireless power transmission system under combined conditions of five EMI intensity levels (e.g., 30, 40, 50, 60, 70 dBμV / m) and five temperature levels (e.g., 25, 30, 40, 50, 55°C). Multiple linear regression analysis is then performed on the experimental data, with the efficiency change as the dependent variable and the normalized EMI and temperature components as independent variables, yielding regression coefficients. For ease of engineering implementation, the regression coefficients are rounded and normalized; these rounded and normalized regression coefficients represent the weights of the EMI and temperature components.

[0093] This setup allows for a unified numerical indicator to objectively reflect the impact of environmental factors on wireless power transmission, helping the system avoid subjective judgment and improve the accuracy of the assessment.

[0094] S412, when the environmental interference value is greater than the interference threshold, it is determined that the environmental noise data reflects the influence of environmental factors on wireless power transmission.

[0095] It is understandable that when the environmental interference value K of the environmental noise data is greater than the interference threshold (such as 0.7), it is determined that environmental factors have an impact on wireless power transmission.

[0096] This setting allows for accurate identification of interference conditions, avoiding ambiguity or misjudgment.

[0097] S413, when the environmental interference value is less than or equal to the interference threshold, it is determined that the environmental noise data reflects that environmental factors have no impact on wireless power transmission.

[0098] It is understandable that when the environmental interference value K of the environmental noise data is less than or equal to the interference threshold (such as 0.7), it is determined that environmental factors have no impact on wireless power transmission.

[0099] This setting allows for accurate identification of interference conditions, avoiding ambiguity or misjudgment.

[0100] In one possible implementation, the resonance information carries magnetic field strength data. Before detecting the environmental noise data in the metamaterial energy transfer system in step S410, the metamaterial energy transfer tuning method based on resonance offset detection further includes: S414: Based on the resonance information mapped from multiple timestamps adjacent to the current timestamp, operational data is obtained. This operational data reflects the relationship between the resonant frequency and the timestamp. One timestamp corresponds to one resonant frequency.

[0101] It can be understood that obtaining resonance information over a certain period of time is possible, as this information is composed of resonant frequencies corresponding to multiple timestamps. A time series is then established using these multiple timestamps and resonant frequencies to reflect the relationship between the resonant frequencies and the timestamps.

[0102] With this setup, by analyzing the resonance information mapped from multiple timestamps adjacent to the current timestamp, operational data reflecting the relationship between the resonant frequency and the timestamp can be generated, providing a basis for subsequent tuning calculations.

[0103] S415, based on the running data, obtain the tuning amount of the current timestamp. The tuning amount of the current timestamp indicates the amount of resonant frequency tuning at the current timestamp.

[0104] It is understandable that the tuning value can be obtained by calculating the frequency change between a certain timestamp and its adjacent previous timestamps, and then averaging the frequency changes between multiple timestamps. For example, the tuning value = (fn - fn-1) ÷ 5; where fn is the resonant frequency mapped to the nth timestamp.

[0105] With this setup, the tuning value at the current timestamp can be obtained based on the running data, which can provide a basis for subsequent tuning value calculations.

[0106] S416, based on the tuning amount at the current timestamp and the duration between the current timestamp and the adjacent previous timestamp, first data is obtained. The first data indicates the amount of resonant frequency tuning per unit time.

[0107] It's understandable that the tuning amount at the current timestamp can be divided by the duration between the current timestamp and the adjacent previous timestamp to obtain the amount of resonant frequency tuning per unit time. For example, the first data = Where fn-fn-1 is the frequency difference between the current timestamp and the previous timestamp, i.e. the tuning amount of the current timestamp, and tn-tn-1 is the time interval between the current timestamp and the previous timestamp.

[0108] This setup provides a foundation for subsequent adjustments.

[0109] S417, based on the phase, the tuning amount of the current timestamp, and the first data, obtains the transmission parameters of the current timestamp.

[0110] It is understandable that phase is used to indicate the trend of the resonant frequency tuning at the current timestamp. For example, phase is used to indicate whether the resonant frequency at the current timestamp is in positive tuning or in negative tuning.

[0111] By observing the relationship between multiple resonant frequencies and the timestamp, it can be determined whether the resonant frequency of the current timestamp is positively tuned or negatively tuned. For example, if the trend of multiple resonant frequencies relative to the timestamp is increasing, then the resonant frequency of the current timestamp is positively tuned; conversely, the resonant frequency of the current timestamp is negatively tuned.

[0112] Based on the tuning amount of the current timestamp, we can determine how many resonant frequencies should be tuned. Based on the phase, we can determine whether the tuning is in the positive or negative direction. Based on the first data, we can determine how many resonant frequencies should be tuned per unit time. In summary, based on the previous transmission parameters, we can obtain the transmission parameters for the current timestamp.

[0113] Specifically, it is assumed that the resonant frequency in the transmission parameter at the previous timestamp is f(n-1), the tuning amount at the current timestamp is Δfn=(fn-f(n-1)), the time interval between the current timestamp and the previous timestamp is Δt=tn-t(n-1), and the first data is the frequency change rate Rn=Δfn÷Δt. The tuning direction identifier Dn: if fn>f(n-1), Dn=+1; if fn<f(n-1), Dn=-1. Then the resonant frequency in the transmission parameter at the current timestamp is: ftrans(n)=f(n-1)+Dn×|Δfn| With such arrangement, the transmission parameter at the current timestamp is obtained based on the phase, the tuning amount at the current timestamp and the first data, which can improve the accuracy of resonant frequency tuning.

[0114] In a possible implementation, after detecting the environmental noise data in the metamaterial energy transmission system in step S410, the metamaterial energy transmission tuning method based on resonance offset detection further comprises: Taking the transmission parameter set at the current timestamp as a key node of the data stream, performing data overwriting on the resonance data set of the metamaterial unit at the previous timestamp, and generating the resonance data set at the current timestamp. The resonance data set at the current timestamp carries the transmission parameter at the current timestamp. The resonance data set at the current timestamp is used to indicate the transmission parameter at the subsequent timestamp adjacent to the current timestamp.

[0115] It can be understood that the frequency tuning amount (for example, the tuning amount and the first data) and the phase change (indicating the tuning direction: positive tuning or negative tuning) are taken as key nodes of the data stream, and the resonance data set at the previous timestamp is corrected based on the tuning direction and the tuning amount of the current transmission parameter, for example, the transmission parameter at the current timestamp is applied to the previous resonance data set, and the data set at the previous timestamp is adjusted based on the transmission parameter at the current timestamp. The resonance data set at the current timestamp carries the transmission parameter at the current timestamp, and the resonance data set at the current timestamp is used to indicate the transmission parameter at the subsequent timestamp adjacent to the current timestamp, that is, the tuning in the time period from the current timestamp to the subsequent timestamp adjacent to the current timestamp is guided based on the resonance data set at the current timestamp.

[0116] With such arrangement, by taking the transmission parameter at the current timestamp as a reference and applying it to the previous resonance data set, the consistency of time series data is ensured, so that the adjustment of the resonance data set is no longer isolated, but forms a continuous and progressive dynamic process.

[0117] In a possible implementation, the metamaterial energy transmission tuning method based on resonance offset detection further comprises: S500, based on multiple startup resonance information after the metamaterial unit is activated, determines the startup tuning parameters. These startup tuning parameters are used to indicate the transmission parameters of the startup timestamp, and the multiple startup resonance information mapped to the startup timestamp includes at least one of the multiple resonance information.

[0118] It is understandable that key parameters (such as resonant frequency, electromagnetic field strength, transmission efficiency, etc.) in the startup resonance information mapped from multiple timestamps during the period from the initial startup to the subsequent startup are assigned different weights. Recent resonance information, being closer to the current state, can be assigned higher weights, while information from more distant times has relatively lower weights. For example, when calculating the startup tuning parameters, the resonant frequencies of the past five timestamps are assigned weights of 0.1, 0.15, 0.2, 0.25, and 0.3 respectively. The resonant frequency value in the startup tuning parameters is calculated using the formula f = 0.1 × f1 + 0.15 × f2 + 0.2 × f3 + 0.25 × f4 + 0.3 × f5. That is, the startup tuning parameters are calculated based on multiple resonance information from the initial startup to the subsequent startup. Subsequently, the transmission parameters at startup are subtracted from the resonant parameters determined by the multiple resonance information after startup to obtain the startup frequency data. It is then determined whether the startup frequency data meets the first requirement, and thus, which resonant parameter to use.

[0119] This setup allows for continuous monitoring of the metamaterial unit's operating state by comparing the initial resonance information. If there is no significant shift between the current and previous timestamps' resonance states, it indicates that the metamaterial unit's operating state is relatively stable. Using the initial tuning parameters as transmission parameters ensures stable system operation and avoids instability caused by over-adjustment.

[0120] S600 overwrites the resonant dataset of the metamaterial unit with the transmission parameters determined by the start timestamp to obtain the resonant dataset of the start timestamp.

[0121] It can be understood that frequency tuning values ​​(e.g., tuning values ​​and initial data) and phase changes (indicating tuning direction: positive or negative tuning) are used as key nodes in the data stream. Based on the tuning direction and tuning value of the transmission parameters determined by the start timestamp, the resonant dataset is corrected. For example, the transmission parameters determined by the start timestamp are applied to the resonant dataset, and the dataset is adjusted based on the transmission parameters at the start timestamp. The resonant dataset at the start timestamp is used to indicate the transmission parameters after startup, i.e., it guides tuning from the initial startup to a period of time after startup, based on the startup tuning parameters.

[0122] This setting helps improve transmission efficiency.

[0123] In one possible implementation, S420, when the ambient noise data reflects that environmental factors have an impact on wireless power transmission, generates a composite tuning command based on the transmission parameters at the current timestamp and the ambient noise data, including: S421, when the environmental noise data reflects that environmental factors have an impact on wireless power transmission, determines the correction frequency and correction matching impedance based on the environmental noise data and the transmission parameters of the current timestamp.

[0124] It is understandable that the corrected frequency is used to indicate the frequency at which the metamaterial energy transfer system is tuned. The corrected matching impedance is used to indicate the capacitance at which the metamaterial energy transfer system is tuned.

[0125] For example, when environmental noise data reflects the impact of environmental factors on wireless power transmission, a correction frequency is generated based on the electromagnetic interference intensity. For instance, Δf = 0.1 × (E - 50), and the correction frequency f = f0 + Δf, where E is the electromagnetic interference intensity in the environmental noise data, and f0 is the resonant frequency in the transmission parameters at the current timestamp. An impedance correction coefficient is calculated based on the temperature, and the corrected matching impedance is obtained from this coefficient. For example, the impedance correction coefficient Kt = 1 + 0.002 × (T - 25), and the corrected matching impedance Z1 = Z0 × Kt, where Kt is the impedance correction coefficient, T is the temperature data in the environmental noise data, and Z0 is the impedance in the transmission parameters at the current timestamp.

[0126] This setup allows for an objective and quantitative reflection of the impact of environmental factors (such as electromagnetic interference and temperature) on wireless power transmission, which helps the system make reasonable tuning decisions under different environmental conditions.

[0127] S422 generates a composite tuning command based on the corrected frequency and the corrected matching impedance.

[0128] It can be understood that mapping the corrected frequency and corrected matching impedance to specific hardware tuning parameter adjustments generates composite tuning commands to adjust the frequency and tuning capacitors.

[0129] This configuration helps the system make reasonable tuning decisions under different environmental conditions, thereby improving transmission efficiency.

[0130] In one possible implementation, the frequency data meets the first requirement when the metamaterial unit operates in a stable environmental mode.

[0131] It is understandable that when the metamaterial unit is working in a stable environment mode, the resonance parameter in the tuning parameters determined by the transmission parameters of the previous timestamp adjacent to the current timestamp minus the resonance information of the current timestamp may be zero, that is, the frequency data is zero. Therefore, it is determined that the frequency data is zero and is outside the threshold region [2,10]. In order to avoid misjudging that the frequency data does not meet the first requirement, it can be directly set that the frequency data meets the first requirement when the metamaterial unit is working in a stable environment mode, thereby omitting the subsequent judgment steps when the frequency data does not meet the first requirement, and directly determining that the resonance state of the metamaterial unit has not shifted significantly.

[0132] This setting can prevent misjudgment that the frequency data does not meet the first requirement.

[0133] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0134] Corresponding to the metamaterial energy transfer tuning method based on resonance offset detection described in the above embodiments, this application also provides a metamaterial energy transfer tuning device, wherein each unit block of the device can realize each step of the metamaterial energy transfer tuning method based on resonance offset detection. Figure 4 A structural block diagram of the metamaterial energy transfer tuning device provided in the embodiments of this application is shown. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0135] Reference Figure 4 The metamaterial energy transfer tuning device includes: The acquisition unit is used to acquire the resonance information of the metamaterial unit. This resonance information reflects the electromagnetic field strength, resonant frequency, or transmission efficiency.

[0136] A determining element is used to identify the resonant parameters in the current tuning parameters as the transmission parameters for the current timestamp when, based on multiple resonant information mapped from multiple timestamps adjacent to the current timestamp, no significant shift in the resonant state of the metamaterial element is determined. Here, multiple timestamps refer to consecutive time nodes preceding the current timestamp. The current tuning parameters are calculated based on multiple resonant information. This ensures that the resonant state of the metamaterial element does not exhibit a significant shift when operating in a stable environment mode.

[0137] The setting unit is used to acquire the resonance trend data corresponding to the timestamp sequence within a preset time window when a significant shift in the resonance state of the metamaterial unit is determined based on multiple resonance information, and to determine the transmission parameters of the current timestamp based on the resonance trend data.

[0138] The generation unit is used to generate tuning control commands based on the transmission parameters of the current timestamp to drive the metamaterial unit to adjust the resonance characteristics.

[0139] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0140] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units is used as an example. In practical applications, the above functions can be assigned to different functional units as needed, that is, the internal structure of the device can be divided into different functional units to complete all or part of the functions described above. The functional units in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0141] This application also provides a metamaterial energy transfer system. Figure 5 This is a schematic diagram of a metamaterial energy transfer system provided in an embodiment of this application. Figure 5 As shown, the metamaterial energy transfer system 6 of this embodiment includes: at least one processor 60 ( Figure 5 Only one is shown in the image), at least one memory 61 ( Figure 5 (Only one is shown in the image) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60, wherein when the processor 60 executes the computer program 62, it causes the metamaterial energy transfer system 6 to implement the steps in any of the above embodiments of the metamaterial energy transfer tuning method based on resonance offset detection, or causes the metamaterial energy transfer system 6 to implement the functions of each unit in the above embodiments of the device.

[0142] For example, the computer program 62 may be divided into one or more units, which are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 62 in the metamaterial energy transfer system 6.

[0143] The metamaterial energy transfer system 6 may include a transmitter (e.g., a transmitting coil, which generates an electromagnetic field through metamaterial units and converts electrical energy from the power source into electromagnetic waves for transmission), a receiver (e.g., a receiving coil, whose metamaterial units receive the electromagnetic waves transmitted by the transmitter and convert them into electrical energy), a power source (for providing stable electrical energy to the transmitter), and a control device. The metamaterial units may be composed of structural units with specific geometric shapes (e.g., small metal sheets, conductor coils, periodic arrays, etc.). The control device can determine the changes in the resonance state based on resonance information from multiple timestamps and decide the current transmission parameters. The metamaterial energy transfer system 6 may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that… Figure 5 This is merely an example of the metamaterial energy transfer system 6 and does not constitute a limitation on the metamaterial energy transfer system 6. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0144] The processor 60 can be a Central Processing Unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0145] In some embodiments, the memory 61 may be an internal storage unit of the metamaterial energy transfer system 6, such as a hard disk or memory of the metamaterial energy transfer system 6. In other embodiments, the memory 61 may be an external storage device of the metamaterial energy transfer system 6, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the metamaterial energy transfer system 6. Furthermore, the memory 61 may include both internal storage units and external storage devices of the metamaterial energy transfer system 6. The memory 61 is used to store operating systems, applications, bootloaders, data, and other programs, such as the program code of the computer program. The memory 61 can also be used to temporarily store data that has been output or will be output.

[0146] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0147] This application provides a computer program product that, when run on a metamaterial energy transfer system, enables the metamaterial energy transfer system to perform the steps described in any of the above method embodiments.

[0148] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to the metamaterial energy transfer system, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0149] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0150] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0151] In the embodiments provided in this application, it should be understood that the disclosed metamaterial energy transfer tuning device / system and the metamaterial energy transfer tuning method based on resonance offset detection can be implemented in other ways. For example, the embodiments of the metamaterial energy transfer tuning device / system described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0152] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0153] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A metamaterial energy transfer tuning method based on resonance offset detection, characterized in that, The method, applied to a metamaterial energy transfer system comprising tunable metamaterial units deployed at a transmitter or receiver, includes: Obtain the resonance information of the metamaterial unit; wherein the resonance information is used to reflect the electromagnetic field strength, resonant frequency, or transmission efficiency; When it is determined that the resonant state of the metamaterial unit has not significantly shifted based on multiple resonant information mapped from multiple timestamps adjacent to the current timestamp, the resonant parameter in the current tuning parameters is determined as the transmission parameter of the current timestamp; wherein, the multiple timestamps are consecutive time nodes before the current timestamp; the current tuning parameters are calculated based on the multiple resonant information; when the metamaterial unit is operating in a stable environment mode, it is determined that the resonant state of the metamaterial unit has not significantly shifted. When a significant shift in the resonance state of the metamaterial unit is determined based on multiple resonance information, resonance trend data corresponding to the timestamp sequence within a preset time window is obtained, and the transmission parameters of the current timestamp are determined based on the resonance trend data. Based on the transmission parameters of the current timestamp, a tuning control command is generated to drive the metamaterial unit to adjust its resonance characteristics.

2. The metamaterial energy transfer tuning method based on resonance offset detection as described in claim 1, characterized in that, The method further includes: When the frequency data meets the first requirement, it is determined that the resonant state of the metamaterial unit has not shifted significantly; wherein, the frequency data is obtained based on the resonant parameter in the current tuning parameters and the transmission parameter of the previous time stamp adjacent to the current time stamp; When the frequency data does not meet the first requirement, and it is determined based on multiple resonance information that the resonance state of the metamaterial unit has not shifted significantly, it is determined that the resonance state of the metamaterial unit has not shifted significantly. When the frequency data does not meet the first requirement, and it is determined that the resonance state of the metamaterial unit has significantly shifted based on multiple resonance information, it is determined that the resonance state of the metamaterial unit has significantly shifted.

3. The metamaterial energy transfer tuning method based on resonance offset detection as described in claim 1, characterized in that, Before generating tuning control commands to drive the metamaterial unit to adjust its resonant characteristics based on the transmission parameters of the current timestamp, the method further includes: Detecting environmental noise data in a metamaterial energy transfer system; wherein the environmental noise data is used to reflect the impact of environmental factors on wireless power transmission; When the environmental noise data reflects that environmental factors have an impact on wireless power transmission, a composite tuning command is generated based on the transmission parameters of the current timestamp and the environmental noise data; wherein, the composite tuning command carries the transmission parameters that should be set at the current timestamp; When the environmental noise data indicates that environmental factors have no impact on wireless power transmission, the transmission parameters of the current timestamp are determined as the transmission parameters that should be set for the current timestamp.

4. The metamaterial energy transfer tuning method based on resonance offset detection as described in claim 3, characterized in that, The environmental noise data carries environmental electromagnetic interference intensity and temperature parameters, and the method further includes: The environmental interference value is determined based on the environmental electromagnetic interference intensity and the temperature. If the environmental interference value is greater than the interference threshold, it is determined that the environmental noise data reflects the impact of environmental factors on wireless power transmission. If the environmental interference value is less than or equal to the interference threshold, the environmental noise data is determined to reflect that environmental factors have no impact on wireless power transmission.

5. The metamaterial energy transfer tuning method based on resonance offset detection as described in claim 3, characterized in that, Before detecting environmental noise data in the metamaterial energy transfer system, the method further includes: Based on the resonance information mapped from multiple timestamps adjacent to the current timestamp, running data is obtained; wherein, the running data is used to reflect the relationship between the resonant frequency and the timestamp; one timestamp corresponds to one resonant frequency; Based on the operational data, the tuning amount of the current timestamp is obtained; wherein, the tuning amount of the current timestamp is used to indicate the amount of resonant frequency tuning at the current timestamp. Based on the tuning amount of the current timestamp and the duration between the current timestamp and the adjacent previous timestamp, first data is obtained; wherein, the first data is used to indicate the amount of resonant frequency tuning per unit time. Based on the phase, the tuning amount of the current timestamp, and the first data, the transmission parameters of the current timestamp are obtained; wherein, the phase is used to indicate the trend of the resonant frequency tuning of the current timestamp.

6. The metamaterial energy transfer tuning method based on resonance offset detection as described in claim 3, characterized in that, After detecting environmental noise data in the metamaterial energy transfer system, the method further includes: Using the transmission parameters set at the current timestamp as key nodes in the data stream, the resonant datasets of the metamaterial units at previous timestamps are overwritten to generate the resonant dataset at the current timestamp; wherein, the resonant dataset at the current timestamp carries the transmission parameters of the current timestamp; the resonant dataset at the current timestamp is used to indicate the transmission parameters of subsequent timestamps adjacent to the current timestamp.

7. The metamaterial energy transfer tuning method based on resonance offset detection as described in claim 6, characterized in that, The method further includes: Based on multiple activation resonance information after the metamaterial unit is activated, activation tuning parameters are determined; wherein, the activation tuning parameters are used to indicate the transmission parameters of the activation timestamp, and the multiple activation resonance information mapped by the activation timestamp includes at least one of the multiple resonance information; The transmission parameters determined by the start timestamp are overwritten with the resonant dataset of the metamaterial unit to obtain the resonant dataset of the start timestamp.

8. The metamaterial energy transfer tuning method based on resonance offset detection as described in claim 5, characterized in that, When the environmental noise data reflects that environmental factors have an impact on wireless power transmission, a composite tuning command is generated based on the transmission parameters of the current timestamp and the environmental noise data, including: When the environmental noise data reflects that environmental factors have an impact on wireless power transmission, the correction frequency and correction matching impedance are determined based on the environmental noise data and the transmission parameters of the current timestamp. The composite tuning command is obtained based on the corrected frequency and the corrected matching impedance.

9. The metamaterial energy transfer tuning method based on resonance offset detection as described in claim 2, characterized in that, When the metamaterial unit operates in a stable environment mode, the frequency data meets the first requirement.

10. A metamaterial energy transfer system, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method as claimed in any one of claims 1 to 9.

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