Wireless sensor dynamic voltage regulation method and system based on load current prediction

Abstract

The invention provides a wireless sensor dynamic voltage regulation method and system based on load current prediction, and relates to the technical field of voltage regulation. According to a load current prediction sequence output by the load current prediction model and response characteristics of output voltage of a direct current-direct current converter in the wireless sensor under different working conditions to the load current, feed-forward compensation amounts of the power supply voltage of the wireless sensor under different working conditions are determined; suppressing the output voltage ripples of the DC-DC converter to obtain the disturbance suppression degree of the output voltage ripples of the DC-DC converter; and performing closed-loop adjustment on the power supply voltage of the wireless sensor through the disturbance suppression degree and all the feedforward compensation amounts to obtain a closed-loop gain coefficient of the power supply voltage, and further generating a voltage adjustment instruction of the wireless sensor according to the closed-loop gain coefficient. According to the invention, the ripple interference of the output voltage of the DC-DC converter can be suppressed in the voltage regulation process of the wireless sensor.

Description

Technical Field

[0001] This application relates to the field of voltage regulation technology, and more specifically, to a method and system for dynamic voltage regulation of wireless sensors based on load current prediction. Background Technology

[0002] In wireless sensor systems, voltage regulation technology is a key element in ensuring stable operation and accurate measurement performance of sensors. Since wireless sensors are mostly powered by batteries or energy harvesting modules, their voltage supply is greatly affected by environmental and load changes. If the voltage regulation is unstable, it will not only reduce the energy efficiency of the sensor, but also cause sampling errors and communication distortion, affecting the overall reliability of the system. Therefore, it is of great significance to design a voltage control mechanism with adaptive adjustment capability based on the power consumption characteristics and dynamic load change patterns of wireless sensors.

[0003] Existing wireless sensor voltage regulation methods mostly rely on DC-DC converters for voltage regulation. However, under dynamic load changes or sudden changes in operating conditions, the transient response speed of the converter is limited, and its output is prone to voltage ripple. Voltage ripple will form periodic interference at the sensor power supply end, affecting sensitive analog circuits and RF modules, causing signal drift or transmission errors, and in severe cases, it may even cause module reset. In addition, traditional feedback voltage regulation methods generally have the problem of response lag, making it difficult to compensate for output disturbances caused by load current fluctuations in a timely manner, and unable to effectively suppress ripple interference. Therefore, how to suppress the output voltage ripple interference of DC-DC converters in the process of wireless sensor voltage regulation has become a difficult problem for the industry. Summary of the Invention

[0004] This application provides a method and system for dynamic voltage regulation of wireless sensors based on load current prediction, which can suppress output voltage ripple interference of DC-DC converters during the voltage regulation process of wireless sensors.

[0005] In a first aspect, this application provides a method for dynamic voltage regulation of a wireless sensor based on load current prediction, the method comprising the following steps:

[0006] Acquire historical load current data of wireless sensors under different operating conditions, and then construct a load current prediction model;

[0007] The feedforward compensation amount of the power supply voltage of the wireless sensor under different operating conditions is determined based on the load current prediction sequence output by the load current prediction model and the response characteristics of the output voltage of the DC-DC converter in the wireless sensor to the load current under different operating conditions.

[0008] The load disturbance information of the wireless sensor when the load current changes suddenly is collected, and the output voltage ripple of the DC-DC converter is suppressed according to the load disturbance information to obtain the disturbance suppression degree of the output voltage ripple of the DC-DC converter.

[0009] The power supply voltage of the wireless sensor is closed-loop regulated using the disturbance suppression degree and all feedforward compensation values ​​to obtain the closed-loop gain coefficient of the power supply voltage. Then, a voltage regulation command for the wireless sensor is generated based on the closed-loop gain coefficient.

[0010] In this embodiment, constructing the load current prediction model specifically includes:

[0011] Acquire historical load current data of wireless sensors under different operating conditions;

[0012] All historical load current data are preprocessed to obtain different preprocessed load current data.

[0013] Time series features and operating condition correlation features are extracted from each preprocessed load current data;

[0014] The load current prediction model is obtained by training the model based on all time series features and all operating condition correlation features.

[0015] In this embodiment, determining the feedforward compensation amount of the power supply voltage of the wireless sensor under different operating conditions, based on the load current prediction sequence output by the load current prediction model and the response characteristics of the output voltage of the DC-DC converter inside the wireless sensor to the load current under different operating conditions, specifically includes:

[0016] The response characteristics of the output voltage of the DC-DC converter in the wireless sensor to the load current under different operating conditions are obtained. The response characteristics represent the delay time and voltage deviation amplitude of the output voltage as the load current changes.

[0017] The rate of change of output voltage with load current under different operating conditions is determined based on the response characteristics of output voltage to load current under different operating conditions.

[0018] By analyzing the response characteristics of output voltage to load current under different operating conditions, the load current variation trend value under different operating conditions can be extracted from the load current prediction sequence output by the load current prediction model.

[0019] Based on the load current variation trend value and the voltage change rate of the output voltage with load current under different operating conditions, the power supply voltage of the wireless sensor under different operating conditions is fed forward to obtain the feedforward compensation amount of the power supply voltage of the wireless sensor under different operating conditions.

[0020] In this embodiment, the output voltage ripple of the DC-DC converter is suppressed based on the load disturbance information, and the disturbance suppression degree of the output voltage ripple of the DC-DC converter is obtained specifically includes:

[0021] Collect load disturbance information from the wireless sensor when the load current changes abruptly;

[0022] Feature extraction is performed on the load disturbance information to obtain disturbance abruptness features and disturbance time features;

[0023] The output voltage ripple of the DC-DC converter is suppressed by feedback using the disturbance change characteristics and the disturbance time characteristics, and the feedback suppression index of the output voltage ripple of the DC-DC converter is obtained.

[0024] The disturbance suppression degree of the output voltage ripple of the DC-DC converter is determined based on the feedback suppression index and the output voltage ripple amplitude of the DC-DC converter in the steady state before the load current change.

[0025] In this embodiment, the closed-loop adjustment of the power supply voltage of the wireless sensor using the disturbance suppression degree and all feedforward compensation amounts to obtain the closed-loop gain coefficient of the power supply voltage specifically includes:

[0026] Adjust the response sensitivity of the closed-loop regulation according to the disturbance suppression degree;

[0027] Determine the power supply voltage deviation of the wireless sensor;

[0028] By performing closed-loop verification on the power supply voltage of the wireless sensor using all feedforward compensation values, a closed-loop verification sequence for the power supply voltage is obtained.

[0029] The closed-loop gain coefficient of the supply voltage is determined based on the response sensitivity, the supply voltage deviation, and the closed-loop verification sequence.

[0030] In this embodiment, generating the voltage regulation command for the wireless sensor based on the closed-loop gain coefficient specifically includes:

[0031] The control gain parameter of the power supply voltage of the wireless sensor is determined based on the closed-loop gain coefficient.

[0032] The voltage regulation command for the wireless sensor is generated using the control gain parameter.

[0033] In this embodiment, the feedforward compensation amount refers to the compensation voltage applied in advance to offset the output voltage fluctuations caused by changes in load current.

[0034] In this embodiment, the disturbance suppression degree represents the reduction ratio of the output voltage ripple of the DC-DC converter compared to the steady-state ripple before the disturbance.

[0035] In this embodiment, the closed-loop gain coefficient represents the gain coefficient of the response strength to the supply voltage deviation during the closed-loop regulation process.

[0036] Secondly, this application provides a wireless sensor dynamic voltage regulation system based on load current prediction, used to execute a wireless sensor dynamic voltage regulation method based on load current prediction, the wireless sensor dynamic voltage regulation system comprising:

[0037] The model building module is used to acquire historical load current data of wireless sensors under different operating conditions, and then build a load current prediction model.

[0038] The feedforward compensation module is used to determine the feedforward compensation amount of the power supply voltage of the wireless sensor under different operating conditions based on the load current prediction sequence output by the load current prediction model and the response characteristics of the output voltage of the DC-DC converter in the wireless sensor to the load current under different operating conditions.

[0039] The disturbance suppression module is used to collect load disturbance information of the wireless sensor when the load current changes suddenly, and to suppress the output voltage ripple of the DC-DC converter according to the load disturbance information, so as to obtain the disturbance suppression degree of the output voltage ripple of the DC-DC converter.

[0040] The closed-loop adjustment module is used to perform closed-loop adjustment of the power supply voltage of the wireless sensor using the disturbance suppression degree and all feedforward compensation quantities to obtain the closed-loop gain coefficient of the power supply voltage, and then generate the voltage adjustment command of the wireless sensor based on the closed-loop gain coefficient.

[0041] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects:

[0042] Historical load current data of the wireless sensor under different operating conditions is acquired, and a load current prediction model is constructed. Based on the load current prediction sequence output by the load current prediction model and the response characteristics of the output voltage of the DC-DC converter within the wireless sensor to the load current under different operating conditions, the feedforward compensation amount of the power supply voltage of the wireless sensor under different operating conditions is determined. Load disturbance information of the wireless sensor during sudden load current changes is collected, and the output voltage ripple of the DC-DC converter is suppressed based on the load disturbance information to obtain the disturbance suppression degree of the DC-DC converter output voltage ripple. The power supply voltage of the wireless sensor is then closed-loop regulated using the disturbance suppression degree and all feedforward compensation amounts to obtain the closed-loop gain coefficient of the power supply voltage. Finally, a voltage regulation command for the wireless sensor is generated based on the closed-loop gain coefficient.

[0043] Therefore, in this application, the voltage regulation command for the wireless sensor can be generated based on the closed-loop gain coefficient. Firstly, by acquiring historical load current data of the wireless sensor under different operating conditions and constructing a load current prediction model, the load change trend can be predicted in advance, providing a scientific basis for feedforward compensation of the supply voltage. This step not only enhances the adaptability of the voltage regulation system to dynamic changes in load current but also significantly improves transient response speed, avoiding voltage deviation caused by sudden load changes. Secondly, by using the load current prediction sequence combined with the response characteristics of the DC-DC converter's output voltage to load current under different operating conditions, the feedforward compensation amount is determined, enabling voltage regulation before load fluctuations occur. This reduces voltage ripple amplitude from the source and lowers the impact on sensitive analog circuits. Furthermore, by collecting disturbance information during load changes and suppressing output voltage ripple, real-time feedback adjustment of actual disturbances can be achieved, compensating for the response lag problem in traditional closed-loop control and improving the voltage regulation system's stability and dynamic adjustment capability. Finally, by combining the feedforward compensation amount with the disturbance suppression degree, closed-loop regulation of the wireless sensor's power supply voltage is realized, and a closed-loop gain coefficient is generated accordingly, which in turn generates a voltage regulation command to complete the dynamic voltage control of the entire process. This closed-loop mechanism can adaptively optimize based on feedforward prediction and disturbance suppression, keeping the power supply voltage stable under different load conditions, while improving the voltage regulation system's response capability to sudden load disturbances, thus enhancing the overall accuracy and reliability of voltage regulation.

[0044] In summary, the technical solution adopted in this application can suppress the output voltage ripple interference of the DC-DC converter during the voltage regulation process of the wireless sensor. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, 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 for this embodiment of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 This is an exemplary flowchart of a method for dynamic voltage regulation of wireless sensors based on load current prediction provided in this application;

[0047] Figure 2 This is a flowchart illustrating the process for determining the feedforward compensation amount provided in this application;

[0048] Figure 3 This is a flowchart illustrating the determination of disturbance suppression degree provided in this application;

[0049] Figure 4 This is a module structure diagram of a wireless sensor dynamic voltage regulation system based on load current prediction, provided in this application. Detailed Implementation

[0050] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0051] This application provides a method and system for dynamic voltage regulation of a wireless sensor based on load current prediction. The core of this method is to acquire historical load current data of the wireless sensor under different operating conditions, and then construct a load current prediction model. Based on the load current prediction sequence output by the load current prediction model and the response characteristics of the output voltage of the DC-DC converter within the wireless sensor to the load current under different operating conditions, the method determines the feedforward compensation amount of the power supply voltage of the wireless sensor under different operating conditions. It collects load disturbance information of the wireless sensor when the load current changes abruptly, and suppresses the output voltage ripple of the DC-DC converter based on the load disturbance information to obtain the disturbance suppression degree of the DC-DC converter output voltage ripple. The method then performs closed-loop regulation of the power supply voltage of the wireless sensor using the disturbance suppression degree and all feedforward compensation amounts to obtain the closed-loop gain coefficient of the power supply voltage, and finally generates a voltage regulation command for the wireless sensor based on the closed-loop gain coefficient.

[0052] Example 1: To better understand the above technical solution, the following will provide a detailed description of the technical solution in conjunction with the accompanying drawings and specific implementation methods. (Refer to...) Figure 1 As shown in the figure, this is an exemplary flowchart of a wireless sensor dynamic voltage regulation method based on load current prediction according to this embodiment of the present application. The wireless sensor dynamic voltage regulation method includes the following steps:

[0053] In step S1, historical load current data of the wireless sensor under different operating conditions are obtained, and then a load current prediction model is constructed.

[0054] It should be noted that the different operating conditions mentioned in this application refer to working modes under different task states, specifically including standby operating condition, data acquisition operating condition, data processing operating condition, data transmission operating condition and abnormal operating condition; it should also be noted that the historical load current data represents an ordered sequence of load current changes over time.

[0055] In this embodiment, the load current prediction model can be constructed using the following steps:

[0056] Acquire historical load current data of wireless sensors under different operating conditions;

[0057] All historical load current data are preprocessed to obtain different preprocessed load current data.

[0058] Time series features and operating condition correlation features are extracted from each preprocessed load current data;

[0059] The load current prediction model is obtained by training the model based on all time series features and all operating condition correlation features.

[0060] It should be noted that the time series features mentioned in this application represent data features reflecting the change of load current over time; the operating condition correlation features represent feature representations of the operating status information of wireless sensors; and the load current prediction model represents a time series prediction model for predicting future load current changes.

[0061] In specific implementation, firstly, historical load current data of the wireless sensor under different operating conditions are acquired; secondly, the average value of five consecutive sampling points is calculated using the moving average method for all load current data to eliminate random noise. Outlier data points exceeding three times the standard deviation of the mean are removed using the 3σ criterion. Then, through normalization, the load current values ​​are linearly mapped to the [0, 1] interval, thus obtaining different pre-processed current data; next, time series features and operating condition correlation features are extracted from all pre-processed load current data. The time series features are obtained through statistical analysis methods, including the mean, standard deviation, maximum value, minimum value within the sliding window, and the difference between adjacent sampling points, used to reflect the fluctuation amplitude and trend of the load current. The load current correlation feature can be transformed into numerical input features by one-hot encoding of each load current label, ensuring that the model can simultaneously perceive the dynamic characteristics of the current and the load current information. Then, all the extracted time series features and load current correlation features are concatenated and input into the long short-term memory network model. The load current value at a specific future time is used as the prediction target. The model uses the Adam optimization algorithm to iteratively update the parameters, and the mean squared error is used as the loss function to measure the prediction accuracy. During the training process, the parameters of the long short-term memory network model are gradually adjusted through multiple rounds of iteration. When the prediction error of the long short-term memory network model on the validation set tends to stabilize and is lower than the preset threshold, the training is stopped, and the model obtained after stopping the training is used as the load current prediction model.

[0062] In step S2, the feedforward compensation amount of the power supply voltage of the wireless sensor under different operating conditions is determined based on the load current prediction sequence output by the load current prediction model and the response characteristics of the output voltage of the DC-DC converter in the wireless sensor to the load current under different operating conditions.

[0063] Preferably, in this embodiment, the feedforward compensation amount of the power supply voltage of the wireless sensor under different operating conditions is determined based on the load current prediction sequence output by the load current prediction model and the response characteristics of the output voltage of the DC-DC converter in the wireless sensor to the load current under different operating conditions, with reference to... Figure 2 As shown in the figure, this is a schematic flowchart of determining the feedforward compensation amount in some embodiments of this application. In this embodiment, the determination of the feedforward compensation amount can be achieved by the following steps:

[0064] In step S21, the response characteristics of the output voltage of the DC-DC converter in the wireless sensor to the load current under different operating conditions are obtained. The response characteristics represent the delay time and voltage deviation amplitude of the output voltage as the load current changes.

[0065] In step S22, the voltage change rate of the output voltage with the load current under different operating conditions is determined based on the response characteristics of the output voltage to the load current under different operating conditions.

[0066] In step S23, the load current change trend value under different operating conditions is extracted from the load current prediction sequence output by the load current prediction model based on the response characteristics of the output voltage to the load current under different operating conditions.

[0067] In step S24, the power supply voltage of the wireless sensor under different operating conditions is fed forward to compensate based on the load current change trend value under different operating conditions and the voltage change rate of the output voltage with the load current under different operating conditions, so as to obtain the feedforward compensation amount of the power supply voltage of the wireless sensor under different operating conditions.

[0068] It should be noted that the load current change trend value mentioned in this application represents the magnitude of load current change within the time window that needs to be compensated in advance, and the feedforward compensation amount represents the compensation voltage that can be applied in advance to offset the output voltage fluctuation caused by the load current change.

[0069] In specific implementation, firstly, under different operating conditions, a preset load current step signal (e.g., a sudden increase from 20μA to 300mA) is input to the DC-DC converter within the wireless sensor. An oscilloscope is used to simultaneously acquire the current step moment and the output voltage change curve. By marking the start of the current step and the start of the voltage change, the time difference between the two is taken as the delay time under the corresponding operating condition. Then, the difference between the voltage's stable value before and after the step is taken as the voltage deviation amplitude under the corresponding operating condition. The characteristics composed of the delay time and voltage deviation amplitude under the corresponding operating condition are used as the response characteristics of the DC-DC converter within the wireless sensor to the load current under the corresponding operating condition. Secondly, the voltage deviation amplitude in the response characteristics of the DC-DC converter within the wireless sensor to the load current under different operating conditions is... The degree is divided by the change in load current under the corresponding operating condition, and the resulting value is used as the voltage change rate of the output voltage with the change in load current under the corresponding operating condition. Then, from the load current prediction sequence output by the load current prediction model, the delay time in the response characteristics of the output voltage to the load current of the DC-DC converter in the wireless sensor under different operating conditions is combined to determine the advance intervention window (for example, if the delay time is 6μs, the predicted load current value within the next 6μs is taken). The difference between the initial value of the load current and the predicted end value of the load current within this window is calculated, and this difference is used as the load current change trend value under the corresponding operating condition. Finally, the load current change trend value under different operating conditions is multiplied by the voltage change rate of the corresponding operating condition, and the resulting value is used as the feedforward compensation amount of the power supply voltage of the wireless sensor under the corresponding operating condition.

[0070] In step S3, load disturbance information of the wireless sensor when the load current changes suddenly is collected, and the output voltage ripple of the DC-DC converter is suppressed according to the load disturbance information to obtain the disturbance suppression degree of the output voltage ripple of the DC-DC converter.

[0071] Preferably, in this embodiment, the output voltage ripple of the DC-DC converter is suppressed based on the load disturbance information to obtain the disturbance suppression degree of the output voltage ripple of the DC-DC converter, with reference to... Figure 3 As shown in the figure, this is a schematic flowchart of determining the disturbance suppression degree in some embodiments of this application. In this embodiment, the disturbance suppression degree can be determined by the following steps:

[0072] In step S31, the load disturbance information of the wireless sensor during sudden changes in load current is collected;

[0073] In step S32, feature extraction is performed on the load disturbance information to obtain disturbance abruptness features and disturbance time features;

[0074] In step S33, the output voltage ripple of the DC-DC converter is suppressed by the disturbance change characteristics and the disturbance time characteristics to obtain the feedback suppression index of the output voltage ripple of the DC-DC converter.

[0075] In step S34, the disturbance suppression degree of the output voltage ripple of the DC-DC converter is determined based on the feedback suppression index and the output voltage ripple amplitude of the DC-DC converter in the stable state before the load current change.

[0076] It should be noted that the load disturbance information mentioned in this application represents the disturbance to the output voltage of the DC-DC converter when the load current of the wireless sensor changes abruptly; the disturbance change feature represents the feature reflecting the severity of the load current change; the disturbance time feature represents the time feature of the load current disturbance; the feedback suppression index represents the degree of suppression of the voltage ripple change caused by the load disturbance by the feedback control loop; and the disturbance suppression degree represents the reduction ratio of the output voltage ripple of the DC-DC converter compared to the steady-state ripple before the disturbance.

[0077] In specific implementation, firstly, when the load current of the wireless sensor undergoes a sudden change (e.g., from 100μA to 500mA), the waveform (including the amplitude and duration of the change) and the corresponding output voltage ripple change waveform are recorded simultaneously at the moment of the current change. These synchronously acquired waveform data are used as load disturbance information. Secondly, the peak detection method is used on the load disturbance information (traversing the waveform data to find the maximum and minimum values ​​of the current change), and the peak difference of the current change is used as the disturbance change feature. At the same time, by marking the start time and the stable time of the current change, the time difference between the two is used as the disturbance time feature. Then, a proportional-integral feedback control algorithm is used, with the disturbance change feature as the proportional term input (proportional coefficient set to 0.01) and the disturbance time feature as the integral term input (integral coefficient set to 0.005). The ratio of the adjusted value output by the proportional-integral controller to the original ripple amplitude (e.g., adjusted value 0.08V ÷ original ripple amplitude 0.2V = 0.4) is used as the feedback suppression index for the output voltage ripple of the DC-DC converter. Finally, the feedback suppression index is multiplied by the output voltage ripple amplitude under steady-state conditions before the load current change (e.g., 0.2V) (0.4 × 0.2V = 0.08V), and then the product is subtracted from the steady-state ripple amplitude (0.2V - 0.08V = 0.12V). The percentage of the difference to the steady-state ripple amplitude (0.12V ÷ 0.2V × 100% = 60%) is used as the disturbance suppression degree for the output voltage ripple of the DC-DC converter.

[0078] In step S4, the power supply voltage of the wireless sensor is adjusted in a closed loop using the disturbance suppression degree and all feedforward compensation values ​​to obtain the closed-loop gain coefficient of the power supply voltage. Then, a voltage adjustment command for the wireless sensor is generated based on the closed-loop gain coefficient.

[0079] In this embodiment, the closed-loop adjustment of the power supply voltage of the wireless sensor using the disturbance suppression degree and all feedforward compensation amounts can be achieved through the following steps to obtain the closed-loop gain coefficient of the power supply voltage:

[0080] Adjust the response sensitivity of the closed-loop regulation according to the disturbance suppression degree;

[0081] Determine the power supply voltage deviation of the wireless sensor;

[0082] By performing closed-loop verification on the power supply voltage of the wireless sensor using all feedforward compensation values, a closed-loop verification sequence for the power supply voltage is obtained.

[0083] The closed-loop gain coefficient of the supply voltage is determined based on the response sensitivity, the supply voltage deviation, and the closed-loop verification sequence.

[0084] It should be noted that the response sensitivity described in this application characterizes the response strength of closed-loop regulation under disturbance changes; the power supply voltage deviation represents the deviation between the current power supply voltage and the target voltage; the closed-loop verification sequence represents the stability verification sequence reflecting the change of the power supply voltage of the wireless sensor over time during the closed-loop regulation process; and the closed-loop gain coefficient represents the gain coefficient for the response strength to the power supply voltage deviation during the closed-loop regulation process.

[0085] In specific implementation, firstly, the disturbance suppression degree is multiplied by the preset reference sensitivity, and the result is used as the response sensitivity of the closed-loop regulation; secondly, the actual value of the current power supply voltage of the wireless sensor is collected in real time, and differential calculation is performed with the target set voltage to obtain the voltage deviation value, which is used as the power supply voltage deviation; nextly, the feedforward compensation quantities under each operating condition are arranged in chronological order and compared with the actual voltage fluctuation values ​​collected after the compensation is implemented to calculate the actual deviation corresponding to each feedforward compensation quantity, and these deviation data are combined in chronological order to form a closed-loop verification sequence; finally, a proportional-derivative control algorithm is adopted, with the response sensitivity as the proportional term coefficient, the power supply voltage deviation as the input signal, and the mean of the closed-loop verification sequence as the derivative term input, and the closed-loop gain coefficient is calculated based on the linear superposition relationship between the proportional term output and the derivative term output.

[0086] In this embodiment, generating the voltage regulation command for the wireless sensor based on the closed-loop gain coefficient can be achieved through the following steps:

[0087] The control gain parameter of the power supply voltage of the wireless sensor is determined based on the closed-loop gain coefficient.

[0088] The voltage regulation command for the wireless sensor is generated using the control gain parameter.

[0089] It should be noted that the control gain parameter described in this application reflects the actual effect of the closed-loop gain coefficient within the range of the wireless sensor's power supply voltage adjustment; the voltage adjustment command represents an instruction to adjust the power supply voltage of the wireless sensor.

[0090] In specific implementation, firstly, the closed-loop gain coefficient is multiplied by the feedback voltage division ratio of the DC-DC converter inside the wireless sensor (calculated through circuit resistance parameters, for example, feedback resistor R1=10kΩ, R2=2kΩ, feedback voltage division ratio=R2 / (R1+R2)=2 / 12≈0.167) (0.02×0.167≈0.0033), then divided by the minimum adjustment step value of the DC-DC converter (i.e., the minimum voltage change that the hardware can recognize), and then rounded to the nearest integer. The integer obtained is then used as the power supply voltage of the wireless sensor. The control gain parameter is used; secondly, a common digital-to-analog converter output method is adopted to multiply the current supply voltage deviation by the control gain parameter to obtain the voltage to be adjusted. The current supply voltage deviation is the difference between the actual voltage and the target voltage. Then, the voltage is converted into a digital quantity. Specifically, the voltage to be adjusted is divided by the minimum voltage resolution of the digital-to-analog converter. The minimum voltage resolution of the digital-to-analog converter is obtained by dividing the output range by the total number of scales corresponding to the number of bits of the digital-to-analog converter. The calculated digital quantity is used as a voltage adjustment command and then sent to the control module of the DC-DC converter.

[0091] Therefore, in this application, the voltage regulation command for the wireless sensor can be generated based on the closed-loop gain coefficient. Firstly, by acquiring historical load current data of the wireless sensor under different operating conditions and constructing a load current prediction model, the load change trend can be predicted in advance, providing a scientific basis for feedforward compensation of the supply voltage. This step not only enhances the adaptability of the voltage regulation system to dynamic changes in load current but also significantly improves transient response speed, avoiding voltage deviation caused by sudden load changes. Secondly, by using the load current prediction sequence combined with the response characteristics of the DC-DC converter's output voltage to load current under different operating conditions, the feedforward compensation amount is determined, enabling voltage regulation before load fluctuations occur. This reduces voltage ripple amplitude from the source and lowers the impact on sensitive analog circuits. Furthermore, by collecting disturbance information during load changes and suppressing output voltage ripple, real-time feedback adjustment of actual disturbances can be achieved, compensating for the response lag problem in traditional closed-loop control and improving the voltage regulation system's stability and dynamic adjustment capability. Finally, by combining the feedforward compensation amount with the disturbance suppression degree, closed-loop regulation of the wireless sensor's power supply voltage is realized, and a closed-loop gain coefficient is generated accordingly, which in turn generates a voltage regulation command to complete the dynamic voltage control of the entire process. This closed-loop mechanism can adaptively optimize based on feedforward prediction and disturbance suppression, keeping the power supply voltage stable under different load conditions, while improving the voltage regulation system's response capability to sudden load disturbances, thus enhancing the overall accuracy and reliability of voltage regulation.

[0092] In summary, the technical solution adopted in this application can suppress the output voltage ripple interference of the DC-DC converter during the voltage regulation process of the wireless sensor.

[0093] Example 2: This application provides a wireless sensor dynamic voltage regulation system based on load current prediction, referencing... Figure 4 As shown in the figure, this is a block structure diagram of a wireless sensor dynamic voltage regulation system based on load current prediction according to this embodiment of the present application. The wireless sensor dynamic voltage regulation system includes:

[0094] The model building module 100 is used to acquire historical load current data of wireless sensors under different operating conditions, and then build a load current prediction model.

[0095] The feedforward compensation module 200 is used to determine the feedforward compensation amount of the power supply voltage of the wireless sensor under different operating conditions based on the load current prediction sequence output by the load current prediction model and the response characteristics of the output voltage of the DC-DC converter in the wireless sensor to the load current under different operating conditions.

[0096] The disturbance suppression module 300 is used to collect load disturbance information of the wireless sensor when the load current changes suddenly, and suppress the output voltage ripple of the DC-DC converter according to the load disturbance information to obtain the disturbance suppression degree of the output voltage ripple of the DC-DC converter.

[0097] The closed-loop adjustment module 400 is used to perform closed-loop adjustment of the power supply voltage of the wireless sensor through the disturbance suppression degree and all the feedforward compensation quantities to obtain the closed-loop gain coefficient of the power supply voltage, and then generate the voltage adjustment command of the wireless sensor according to the closed-loop gain coefficient.

[0098] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0099] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-Erasable Programmable Read-Only Memory (EEPROM), compactdisc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0100] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

Claims

1. A method for dynamic voltage regulation of wireless sensors based on load current prediction, characterized in that, The wireless sensor dynamic voltage regulation method includes the following steps: Acquire historical load current data of wireless sensors under different operating conditions, and then construct a load current prediction model; The feedforward compensation amount of the power supply voltage of the wireless sensor under different operating conditions is determined based on the load current prediction sequence output by the load current prediction model and the response characteristics of the output voltage of the DC-DC converter in the wireless sensor to the load current under different operating conditions. The load disturbance information of the wireless sensor when the load current changes suddenly is collected, and the output voltage ripple of the DC-DC converter is suppressed according to the load disturbance information to obtain the disturbance suppression degree of the output voltage ripple of the DC-DC converter. The power supply voltage of the wireless sensor is closed-loop regulated using the disturbance suppression degree and all feedforward compensation values ​​to obtain the closed-loop gain coefficient of the power supply voltage. Then, a voltage regulation command for the wireless sensor is generated based on the closed-loop gain coefficient.

2. The method for dynamic voltage regulation of wireless sensors based on load current prediction as described in claim 1, characterized in that, The construction of a load current prediction model specifically includes: Acquire historical load current data of wireless sensors under different operating conditions; All historical load current data are preprocessed to obtain different preprocessed load current data. Time series features and operating condition correlation features are extracted from each preprocessed load current data; The load current prediction model is obtained by training the model based on all time series features and all operating condition correlation features.

3. The method for dynamic voltage regulation of wireless sensors based on load current prediction as described in claim 1, characterized in that, Based on the load current prediction sequence output by the load current prediction model and the response characteristics of the output voltage of the DC-DC converter inside the wireless sensor to the load current under different operating conditions, the feedforward compensation amount of the power supply voltage of the wireless sensor under different operating conditions is determined, specifically including: The response characteristics of the output voltage of the DC-DC converter in the wireless sensor to the load current under different operating conditions are obtained. The response characteristics represent the delay time and voltage deviation amplitude of the output voltage as the load current changes. The rate of change of output voltage with load current under different operating conditions is determined based on the response characteristics of output voltage to load current under different operating conditions. By analyzing the response characteristics of output voltage to load current under different operating conditions, the load current variation trend value under different operating conditions can be extracted from the load current prediction sequence output by the load current prediction model. Based on the load current variation trend value and the voltage change rate of the output voltage with load current under different operating conditions, the power supply voltage of the wireless sensor under different operating conditions is fed forward to obtain the feedforward compensation amount of the power supply voltage of the wireless sensor under different operating conditions.

4. The method for dynamic voltage regulation of wireless sensors based on load current prediction as described in claim 1, characterized in that, Based on the load disturbance information, the output voltage ripple of the DC-DC converter is suppressed to obtain the disturbance suppression degree of the output voltage ripple of the DC-DC converter. Specifically, this includes: Collect load disturbance information from the wireless sensor when the load current changes abruptly; Feature extraction is performed on the load disturbance information to obtain disturbance abruptness features and disturbance time features; The output voltage ripple of the DC-DC converter is suppressed by feedback using the disturbance change characteristics and the disturbance time characteristics, and the feedback suppression index of the output voltage ripple of the DC-DC converter is obtained. The disturbance suppression degree of the output voltage ripple of the DC-DC converter is determined based on the feedback suppression index and the output voltage ripple amplitude of the DC-DC converter in the steady state before the load current change.

5. The method for dynamic voltage regulation of wireless sensors based on load current prediction as described in claim 1, characterized in that, The closed-loop gain coefficient of the power supply voltage of the wireless sensor is obtained by performing closed-loop regulation using the disturbance suppression degree and all feedforward compensation values. Adjust the response sensitivity of the closed-loop regulation according to the disturbance suppression degree; Determine the power supply voltage deviation of the wireless sensor; By performing closed-loop verification on the power supply voltage of the wireless sensor using all feedforward compensation values, a closed-loop verification sequence for the power supply voltage is obtained. The closed-loop gain coefficient of the supply voltage is determined based on the response sensitivity, the supply voltage deviation, and the closed-loop verification sequence.

6. The method for dynamic voltage regulation of wireless sensors based on load current prediction as described in claim 1, characterized in that, Generating the voltage regulation command for the wireless sensor based on the closed-loop gain coefficient specifically includes: The control gain parameter of the power supply voltage of the wireless sensor is determined based on the closed-loop gain coefficient. The voltage regulation command for the wireless sensor is generated using the control gain parameter.

7. The method for dynamic voltage regulation of wireless sensors based on load current prediction as described in claim 1, characterized in that, The feedforward compensation amount refers to the compensation voltage applied in advance to offset the output voltage fluctuations caused by changes in load current.

8. The method for dynamic voltage regulation of wireless sensors based on load current prediction as described in claim 1, characterized in that, The disturbance suppression degree represents the reduction ratio of the output voltage ripple of the DC-DC converter compared to the steady-state ripple before the disturbance.

9. The method for dynamic voltage regulation of wireless sensors based on load current prediction as described in claim 1, characterized in that, The closed-loop gain coefficient represents the gain coefficient in response to the supply voltage deviation during the closed-loop regulation process.

10. A wireless sensor dynamic voltage regulation system based on load current prediction, used to execute the wireless sensor dynamic voltage regulation method based on load current prediction as described in any one of claims 1 to 9, characterized in that, The wireless sensor dynamic voltage regulation system includes: The model building module is used to acquire historical load current data of wireless sensors under different operating conditions, and then build a load current prediction model. The feedforward compensation module is used to determine the feedforward compensation amount of the power supply voltage of the wireless sensor under different operating conditions based on the load current prediction sequence output by the load current prediction model and the response characteristics of the output voltage of the DC-DC converter in the wireless sensor to the load current under different operating conditions. The disturbance suppression module is used to collect load disturbance information of the wireless sensor when the load current changes suddenly, and to suppress the output voltage ripple of the DC-DC converter according to the load disturbance information, so as to obtain the disturbance suppression degree of the output voltage ripple of the DC-DC converter. The closed-loop adjustment module is used to perform closed-loop adjustment of the power supply voltage of the wireless sensor using the disturbance suppression degree and all feedforward compensation quantities to obtain the closed-loop gain coefficient of the power supply voltage, and then generate the voltage adjustment command of the wireless sensor based on the closed-loop gain coefficient.

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