Tunnel magnetoresistive current sensor self-correction measurement method, system and device based on voltage feedback and medium

Abstract

The invention discloses a tunnel reluctance current sensor self-correction measurement method, system and device based on voltage feedback and a medium, and belongs to the technical field of current measurement and sensor anti-interference, and the method comprises the steps: extracting fundamental wave complex components at the fundamental wave frequency of a power supply voltage and an initial output voltage; calculating a filter coefficient according to the fundamental wave complex component and performing phase correction on the output voltage to obtain a corrected output voltage sequence aligned with the phase of the power supply voltage signal; calculating a voltage ratio signal according to the corrected output voltage and the power supply voltage and determining a ratio signal residual error; final current estimation is obtained according to the voltage ratio signal and the ratio signal residual error in combination with the ratio signal; according to the invention, a double-closed-loop compensation structure is adopted, so that channel mismatching and non-linear interference are effectively suppressed; the digital implementation mode enables the system to have good reconfigurability and environmental adaptability, and the system is suitable for application scenes such as intelligent power grids, distributed power monitoring and industrial online detection.

Description

Technical Field

[0001] This invention relates to the field of current measurement and sensor anti-interference technology, specifically to a self-calibration measurement method, system, device, and medium for a tunnel magnetoresistive current sensor based on voltage feedback. Background Technology

[0002] In recent years, current sensors based on the magnetoresistive effect have gradually become mainstream. In particular, TMR sensors have become an important direction for the next generation of current sensors due to their advantages such as high sensitivity, low power consumption, low temperature drift, and easy integration. However, while the extremely high sensitivity of TMR sensors improves measurement resolution, it also amplifies the impact of external interference, making them more sensitive to power supply stability, electromagnetic noise, and environmental disturbances.

[0003] The errors of TMR current sensors are mainly attributed to external magnetic field interference. Therefore, research on TMR current sensors primarily focuses on anti-magnetic field interference design. However, as anti-magnetic field technology matures, interference caused by power supply voltage disturbances becomes increasingly prominent. When the sensor is powered by a battery, AC / DC power supply, or DC / DC regulated power supply, phase jitter and channel delay of the power supply voltage directly couple to the output signal, introducing non-magnetic error signals and thus reducing current measurement accuracy. This problem is particularly severe in environments with frequent power quality fluctuations. Existing voltage feedback compensation methods generally rely on simple ratio correction, but under the influence of phase disturbances, channel delays, and nonlinear residual interference, the measurement accuracy remains insufficient, making it difficult to guarantee high accuracy and long-term stability.

[0004] Therefore, to achieve phase alignment and accurate calibration of the current sensor under power supply disturbance conditions, this invention proposes a self-calibration measurement method for a tunnel magnetoresistive current sensor based on voltage feedback. By combining an adaptive calibration scheme of voltage feedback and phase compensation, stronger robustness to power supply disturbances can be achieved. The system has a compact structure, strong adaptability, and broad application prospects. Summary of the Invention

[0005] In view of the above-mentioned problems, the present invention is proposed.

[0006] Therefore, the technical problem solved by this invention is that while the extremely high sensitivity of the tunnel magnetoresistive sensor improves the measurement resolution, it also amplifies the influence of external interference, making it more sensitive to power supply stability, electromagnetic noise and environmental disturbances. Existing voltage feedback compensation methods mostly rely on simple ratio correction, but they still have obvious limitations under the influence of phase disturbance, channel delay and nonlinear residual interference, making it difficult to guarantee high accuracy and long-term stability.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a self-calibration measurement method for a tunnel magnetoresistive current sensor based on voltage feedback, comprising the following steps: The power supply voltage and initial output voltage of the sensor are obtained, and spectrum analysis is performed to extract the fundamental complex component at the fundamental frequency. The filter coefficients are calculated based on the fundamental complex components, and the output voltage is phase-corrected to obtain a corrected output voltage sequence that is phase-aligned with the supply voltage signal. Calculate the voltage ratio signal based on the corrected output voltage and the supply voltage, and determine the residual of the ratio signal; The filter output is calculated based on the voltage ratio signal and the ratio signal residual; The filter output is combined with the ratio signal to obtain the final current estimate.

[0008] In a preferred embodiment of the voltage feedback-based self-calibration measurement method for a tunnel magnetoresistive current sensor according to the present invention, the step of extracting the fundamental complex component at the fundamental frequency includes: Obtain the sensor's power supply voltage and initial output voltage; Perform spectrum analysis on the supply voltage and initial output voltage to obtain the spectrum analysis results; The fundamental complex components of the supply voltage and the initial output voltage are determined by the results of spectrum analysis.

[0009] The beneficial effects of this preferred technical solution are as follows: by extracting the complex components of the supply voltage and the initial output voltage at the fundamental frequency through spectrum analysis, the phase alignment of the sensor signal and the supply voltage signal is achieved; this provides a phase reference for subsequent calculations, and can also eliminate measurement errors caused by signal phase deviation, improve measurement accuracy, and ensure the accuracy and stability of current measurement results.

[0010] In a preferred embodiment of the self-calibration measurement method for a tunnel magnetoresistive current sensor based on voltage feedback according to the present invention, the step of calculating the filter coefficients and performing phase correction on the output voltage includes: The phase angle between the supply voltage and the initial output voltage is obtained by using the fundamental complex component; Calculate the phase difference based on the phase angle between the supply voltage and the initial output voltage; The phase compensation coefficients are calculated using the phase difference and the reference filter coefficients. The output voltage is phase-corrected based on the phase compensation coefficient to obtain a corrected output voltage sequence that is phase-aligned with the supply voltage signal.

[0011] In a preferred embodiment of the self-calibration measurement method for a tunnel magnetoresistive current sensor based on voltage feedback according to the present invention, the step of calculating the voltage ratio signal and determining the ratio signal residual includes: The voltage ratio signal is calculated by correcting the output voltage and the supply voltage. The residual of the ratio signal is obtained by subtracting the voltage ratio signal from the reference ratio signal.

[0012] In a preferred embodiment of the self-calibration measurement method for a tunnel magnetoresistive current sensor based on voltage feedback according to the present invention, the step of calculating the filter output based on the voltage ratio signal and the ratio signal residual includes: The residual compensation weight is calculated based on the ratio signal sequence and the ratio signal residual. The filter output is calculated based on the residual compensation weights combined with the voltage ratio signal.

[0013] As a preferred embodiment of the self-calibration measurement method for a tunnel magnetoresistive current sensor based on voltage feedback according to the present invention, the step of obtaining the final current estimate by combining the filter output with the ratio signal includes: Calculate the effective ratio signal based on the filter output and voltage ratio signal; The current estimate is calculated based on the effective ratio signal.

[0014] The beneficial effects of this preferred technical solution are as follows: by modeling and compensating for residual errors, the influence of complex interference factors such as temperature drift, amplifier nonlinearity, and device aging on the measurement results is suppressed; the calculation of the effective ratio signal and the derivation of the current estimate form a complete error correction and signal optimization mechanism, which improves the measurement accuracy and stability of the tunnel magnetoresistive current sensor.

[0015] In a preferred embodiment of the voltage feedback-based self-calibration measurement method for tunnel magnetoresistive current sensors according to the present invention, the formula for calculating the residual compensation weight is: ; in, As the residual compensation weight for the next period, This is the residual compensation weight for the current period. The ratio signal residual, Step size factor It is a ratio signal sequence, and L is the filter length. It is a voltage ratio signal; The formula for calculating the filter output is: ; in, For filter output, For index variables.

[0016] This invention provides a self-calibration measurement system for a tunnel magnetoresistive current sensor based on voltage feedback.

[0017] To solve the above-mentioned technical problems, the present invention further provides the following technical solution: a self-calibration measurement system for a tunnel magnetoresistive current sensor based on voltage feedback, comprising: a data acquisition module for acquiring the power supply voltage and initial output voltage of the sensor; Spectrum analysis module: Performs spectrum analysis on the supply voltage and initial output voltage, and extracts the fundamental complex component at the fundamental frequency; Phase correction module: Calculates filter coefficients based on fundamental complex components and performs phase correction on the output voltage to obtain a corrected output voltage that is phase-aligned with the supply voltage signal; First data calculation module: Calculates the voltage ratio signal based on the corrected output voltage and the supply voltage, determines the ratio signal residual and the ratio signal sequence, and calculates the filter output; The second data calculation module combines the filter output with the ratio signal to obtain the final current estimate.

[0018] The present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, characterized in that the processor, when executing the computer program, implements the steps of a self-calibration measurement method for a tunnel magnetoresistive current sensor based on voltage feedback.

[0019] The present invention provides a computer-readable storage medium having a computer program stored thereon, characterized in that the computer program, when executed by a processor, implements the steps of a self-calibration measurement method for a tunnel magnetoresistive current sensor based on voltage feedback.

[0020] The beneficial effects of this invention are as follows: By introducing a phase detection and alignment mechanism, this invention improves the measurement accuracy of the tunnel magnetoresistive current sensor under power supply disturbance conditions; the dual closed-loop compensation structure suppresses channel mismatch and nonlinear interference; the first closed loop achieves precise phase alignment between the sensor signal and the power supply voltage signal based on spectrum analysis; the second closed loop models and compensates for residual errors, suppressing complex interference factors such as temperature drift, amplifier nonlinearity, and device aging; the calculation of the effective ratio signal and the derivation of the current estimate form a complete error correction and signal optimization mechanism, improving the measurement accuracy and stability of the tunnel magnetoresistive current sensor; the digital implementation method gives the system good reconfigurability and environmental adaptability, making it suitable for applications such as smart grids, distributed power monitoring, and industrial online detection. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 The above is a flowchart of a self-calibration measurement method for a tunnel magnetoresistive current sensor based on voltage feedback, provided as an embodiment of the present invention.

[0023] Figure 2 This is a schematic diagram of the hardware structure of a self-calibration measurement method for a tunnel magnetoresistive current sensor based on voltage feedback, provided as an embodiment of the present invention.

[0024] Figure 3 The flowchart illustrates an algorithm for a self-calibration measurement method for a tunnel magnetoresistive current sensor based on voltage feedback, as provided in one embodiment of the present invention. Detailed Implementation

[0025] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0026] Example 1, referring to Figure 1 This is the first embodiment of the present invention, which provides a self-calibration measurement method for a tunnel magnetoresistive current sensor based on voltage feedback, comprising: S100: Acquire the sensor's power supply voltage and initial output voltage, perform spectrum analysis, and extract the fundamental complex component at the fundamental frequency; S200: Calculate the filter coefficients based on the fundamental complex components and perform phase correction on the output voltage to obtain a corrected output voltage that is phase-aligned with the supply voltage signal; S300: Calculates the voltage ratio signal and determines the ratio signal residual based on the corrected output voltage and the supply voltage; S400: Calculates the filter output based on the voltage ratio signal and the ratio signal residual; S500: Combines the filter output with the ratio signal to obtain the final current estimate.

[0027] It should be noted that while the extremely high sensitivity of the tunnel magnetoresistive sensor improves the measurement resolution, it also amplifies the impact of external interference, making it more sensitive to power supply stability, electromagnetic noise, and environmental disturbances. Existing voltage feedback compensation methods mostly rely on simple ratio correction, but they still have significant limitations under the influence of phase disturbances, channel delays, and nonlinear residual interference, making it difficult to guarantee high accuracy and long-term stability. Therefore, it is very important to propose a self-calibration measurement method for the tunnel magnetoresistive current sensor based on voltage feedback.

[0028] To address the aforementioned issues of sensors struggling to guarantee high accuracy and long-term stability, steps S100-S600 introduce a phase detection and alignment mechanism, significantly improving the measurement accuracy of the tunnel magnetoresistive current sensor under power supply disturbance conditions. A dual-loop compensation structure effectively suppresses channel mismatch and nonlinear interference. The first loop achieves precise phase alignment between the sensor signal and the supply voltage signal based on spectrum analysis; the second loop performs online modeling and compensation for residual errors, suppressing complex interference factors such as temperature drift, amplifier nonlinearity, and device aging. The digital implementation provides the system with excellent reconfigurability and environmental adaptability, making it suitable for applications such as smart grids, distributed power monitoring, and industrial online detection.

[0029] Example 2, refer to Figure 1 and Figure 2 This is the second embodiment of the present invention, which provides a self-calibration measurement method for a tunnel magnetoresistive current sensor based on voltage feedback.

[0030] In this embodiment of the application, the extraction of the fundamental complex component at the fundamental frequency in step S100 includes the following steps A1 to A3: A1: Obtain the sensor's power supply voltage and initial output voltage; In this embodiment of the application, obtaining the power supply voltage and initial output voltage of the sensor includes: acquiring the voltage signal at the power supply terminal of the tunnel magnetoresistive current sensor to obtain the power supply voltage; acquiring the signal output by the tunnel magnetoresistive current sensor, which is amplified by a differential amplifier circuit and acquired synchronously to obtain the initial output voltage of the tunnel magnetoresistive current sensor.

[0031] A2: Perform spectrum analysis on the supply voltage and initial output voltage to obtain the spectrum analysis results; In the embodiments of this application, the discrete data of the supply voltage and the initial output voltage are input into an analysis tool with fast Fourier transform function, such as MATLAB, Python's NumPy library, or a simple spectrum analysis software, to perform fast Fourier transform operations on the supply voltage and the initial output voltage respectively.

[0032] A3: Determine the fundamental complex components of the supply voltage and the initial output voltage through spectrum analysis results.

[0033] In this embodiment of the application, in the spectrum analysis results obtained by the analysis tool in step A2, the spectrum point corresponding to the fundamental frequency is located, and the amplitude and phase of the spectrum point are the complex components of the fundamental frequency.

[0034] In this embodiment of the application, after performing a fast Fourier transform analysis on a certain sampled data, the fundamental complex component of the supply voltage signal at a fundamental frequency of 50Hz is: The fundamental complex component of the initial output voltage is .

[0035] In one alternative implementation, the extraction of the fundamental complex component at the fundamental frequency can also be achieved through a phase-locked loop. The supply voltage and the initial output voltage are multiplied by the two reference signals respectively, and after low-pass filtering, the in-phase component and quadrature component of the fundamental are obtained. The in-phase component is used as the real part, and the quadrature component is used as the imaginary part. The combination of these components forms the complex component, and the output is the fundamental complex component.

[0036] In another alternative implementation, the fundamental complex component at the fundamental frequency can also be extracted by orthogonal wavelet transform. An orthogonal wavelet suitable for fundamental analysis is selected, and the supply voltage and initial output voltage signals are decomposed by wavelet. The wavelet coefficients corresponding to the fundamental frequency range are retained, and the fundamental time domain signal is obtained by wavelet reconstruction. The output is the fundamental complex component.

[0037] In this embodiment of the application, the calculation of filter coefficients and phase correction of the output voltage in step S200 includes the following steps B1 to B4: B1: Obtain the phase angle between the supply voltage and the initial output voltage through the fundamental complex component; In this embodiment of the application, the fundamental complex component of the power supply voltage signal is... The amplitude of the supply voltage was found to be 5.54, and the phase angle of the supply voltage was 26.57°. Based on the fundamental complex component of the initial output voltage... The initial output voltage amplitude was 0.515, and the initial output voltage phase angle was 14.04°.

[0038] B2: Calculate the phase difference based on the phase angle between the supply voltage and the initial output voltage; In this embodiment of the application, the formula for calculating the phase difference is: ; in, For phase difference, The phase angle of the supply voltage. The phase angle of the initial output voltage; In this embodiment of the application, the phase angle of the supply voltage obtained in step B1 is 26.57°, and the phase angle of the initial output voltage is 14.04°. The phase difference is calculated by substituting these values ​​into the phase difference calculation formula. =12.53°.

[0039] B3: Calculate the phase compensation coefficient using the phase difference and the reference filter coefficients; In this embodiment of the application, the formula for calculating the phase compensation coefficient is: ; in, For phase compensation coefficients, For the reference filter coefficients, Where k is the filter length and k is the filter coefficient index. ; In this embodiment, the filter length is set to 4, and the index coefficients are 0, 1, 2, and 3. Given the range [0.25, 0.5, 0.5, 0.25], the phase difference of -12.53° is converted to -0.2187 radians. Substituting these values ​​into the formula yields: ; ; ; ; The final phase compensation coefficient is: [ , , , ].

[0040] In one alternative implementation, the phase compensation coefficient can also be calculated through frequency domain amplitude-phase correction. First, the reference filter coefficients are subjected to fast Fourier transform to obtain the frequency domain response, the phase of the frequency point corresponding to the fundamental frequency is corrected, and then the time domain phase compensation coefficient is obtained through inverse fast Fourier transform.

[0041] In another alternative implementation, the phase compensation coefficient can also be calculated through adaptive filtering. The initial value of the reference filter coefficient is set and the target phase is determined. The signal to be processed is input into the reference filter to obtain the output signal. The phase error between the output signal and the target phase signal is calculated. According to the least mean square adaptive algorithm, the phase component of each filter coefficient is iterated. Through multiple iterations or when the phase error converges to a minimum value, the final phase compensation coefficient is obtained.

[0042] B4: The initial output voltage is phase-corrected according to the phase compensation coefficient to obtain a corrected output voltage sequence that is phase-aligned with the supply voltage signal.

[0043] In this embodiment, the formula for phase correction of the output voltage is: ; in, To correct the output voltage, This is the initial output voltage; In this embodiment of the application, the phase compensation coefficient obtained through step B3 is: [ , , , ], Set the initial output voltage as follows: [ , , , ]; Calculate the corrected output voltage point by point, when n=0 and k=0: ; When n=1 and k=0.

[0044] ; Similarly, the calculation yields , , ; The calculated corrected output voltages at each point are arranged in order to obtain the corrected output voltage sequence.

[0045] In this embodiment of the application, the calculation of the voltage ratio signal and the determination of the ratio signal residual in step S300 includes the following steps C1~C2: C1: Calculates the voltage ratio signal by correcting the output voltage sequence and the supply voltage; In this embodiment of the application, the formula for calculating the voltage ratio signal is: ; in, It is a voltage ratio signal. To correct the output voltage sequence, It is a sequence of supply voltages, obtained by arranging the supply voltages in order. In this embodiment of the application, the corrected output voltage sequence obtained in step B4 is: [ ]; The power supply voltage sequence is set as follows: [5.0+j0,4.9+j0,5.1+j0,5.0+j0,4.9+j0]; The voltage ratio signal is calculated using the formula for calculating the voltage ratio signal as follows: [0.025+j0.00625,0.0706+j0.0204,0.1065+j0.0294,0.128+j0.035,0.1108+j0.0306].

[0046] C2: The residual of the ratio signal is obtained by subtracting the voltage ratio signal from the reference ratio signal; In this embodiment of the application, the formula for calculating the ratio signal residual is: ; in, As a reference ratio signal, The ratio signal residual; In this embodiment of the application, the voltage ratio signal obtained through step C1 is: [0.025+j0.00625,0.0706+j0.0204,0.1065+j0.0294,0.128+j0.035,0.1108+j0.0306]; The reference ratio signal is set as follows: [0.025+j0.0,0.07+j0.0,0.105+j0.0,0.125+j0.0,0.11+j0.0]; Substituting into the formula for the ratio signal residual, the ratio signal residual is calculated as follows: [j0.00625,0.0006+j0.0204,0.0015+j0.0294,0.003+j0.035,0.0008+j0.0306].

[0047] In one alternative implementation, the ratio signal residual can also be calculated by subtracting the values ​​of a sliding window. The length of the sliding window is set and the processing rules for the signals within the window are defined. The arithmetic mean of the voltage ratio signal and the reference ratio signal within the window are calculated respectively. Then, the average value of the voltage ratio signal within the window is subtracted from the average value of the reference ratio signal to obtain the ratio signal residual at the current point.

[0048] In another alternative implementation, the residual of the ratio signal can also be calculated by subtraction using fuzzy logic. The real and imaginary parts of the voltage ratio signal and the reference ratio signal are defined as fuzzy inputs, and the fuzzy output is calculated by fuzzy rules. For example, if the real part of the voltage ratio is much larger than the real part of the reference ratio, the real part of the residual is large. The residual of the ratio signal is then obtained by defuzzification.

[0049] In this embodiment of the application, the step S400 of calculating the filter output based on the voltage ratio signal and the ratio signal residual includes the following steps D1~D2: D1: Calculate the residual compensation weight based on the ratio signal sequence and the ratio signal residual; In this embodiment of the application, the formula for calculating the residual compensation weight is: ; in, As the residual compensation weight for the next period, This is the residual compensation weight for the current period. The ratio signal residual, Step size factor It is a ratio signal sequence, and When n < 0 Set to 0, where L is the filter length. It is a voltage ratio signal; In this embodiment, the compensation factor is set to 0.01, the filter length is 3, and the initial residual compensation weight is... [0, 0, 0] T The voltage ratio signal obtained through step C1 is: [0.025+j0.00625,0.0706+j0.0204,0.1065+j0.0294,0.128+j0.035,0.1108+j0.0306]; The ratio signal residual obtained through step C2 is: [j0.00625,0.0006+j0.0204,0.0015+j0.0294,0.003+j0.035,0.0008+j0.0306]; When n=0, calculate the residual compensation weight for the next period: ; ; ; Similarly, the residual compensation weights for each period are calculated sequentially.

[0050] In one alternative implementation, the residual compensation weights can also be calculated using a genetic algorithm. With the goal of minimizing the error after residual compensation, an initial weight population is set, and the quality of each weight group is evaluated by defining a fitness function. A roulette wheel selection method is used to select high-quality parents, and a new population is generated through crossover and mutation. After multiple iterations or convergence, the weight combination with the highest fitness is selected as the final residual compensation weight.

[0051] In another alternative implementation, the residual compensation weights can also be calculated using the least squares method. The voltage ratio signal sequence is constructed into a matrix according to the filter length, and the ratio signal residuals are organized into a vector. The least squares equation system is established with the minimum sum of squared errors after residual compensation as the optimization objective. The weight vector is calculated, and the residual compensation weights are output based on the weight vector.

[0052] D2: Calculate the filter output based on the residual compensation weights and the voltage ratio signal; In this embodiment of the application, the formula for calculating the filter output is: ; in, For filter output, For index variables; In this embodiment of the application, the voltage ratio signal obtained through step C1 is: [0.025+j0.00625,0.0706+j0.0204,0.1065+j0.0294,0.128+j0.035,0.1108+j0.0306]; Calculate the residual compensation weights using a filter length of 3 and n=3 as an example. ; Substituting into the formula for filter output, the filter output is calculated as follows: .

[0053] In this embodiment of the application, step S400, which combines the filter output with the ratio signal to obtain the final current estimate, includes the following steps E1~E2: E1: Calculate the effective ratio signal based on the filter output and voltage ratio signal; In this embodiment of the application, the formula for calculating the effective ratio signal is: ; in, For effective ratio signals, It is a voltage ratio signal. For filter output; In the embodiments of this application, taking n=1 as an example, the voltage ratio signal is set to 0.128+j0.035, the filter output is 0.0523+j0.0262, and the effective ratio signal is calculated to be 0.0757+j0.0088 when n=1 by substituting into the effective ratio signal calculation formula.

[0054] E2: Calculate the current estimate based on the effective ratio signal.

[0055] In this embodiment of the application, the formula for calculating the current estimate is: ; in, This is an estimated value for the current. These are calibration coefficients, determined through offline calibration experiments; In this embodiment, the effective ratio signal is set to 0.1275+j0.0347, the calibration coefficient is 96.15−j19.23, and the current estimate is calculated by substituting into the current estimate calculation formula: 12.93+j0.89.

[0056] Example 3, referring to Figure 1 This is a third embodiment of the present invention, which provides a voltage feedback-based tunneling magnetoresistive current sensor self-calibration measurement system, comprising: Data acquisition module: acquires the sensor's power supply voltage and initial output voltage; Spectrum analysis module: Performs spectrum analysis on the supply voltage and initial output voltage, and extracts the fundamental complex component at the fundamental frequency; Phase correction module: Calculates filter coefficients based on fundamental complex components and performs phase correction on the output voltage to obtain a corrected output voltage that is phase-aligned with the supply voltage signal; First data calculation module: Calculates the voltage ratio signal based on the corrected output voltage and the supply voltage, determines the ratio signal residual and the ratio signal sequence, and calculates the filter output; The second data calculation module combines the filter output with the ratio signal to obtain the final current estimate.

[0057] Example 4, the fourth embodiment of the present invention, differs from the previous three embodiments in that: if the function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0058] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0059] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0060] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0061] Example 5, refer to Figure 3 This is the fifth embodiment of the present invention, which provides a self-calibration measurement method for a tunnel magnetoresistive current sensor based on voltage feedback, employing... Figure 2The hardware structure diagram shown comprises seven core modules: an input interface, a TMR full-bridge sensor, a differential amplifier circuit, a digital-to-analog converter module, a digital processing unit, a power supply voltage sampling module, and an output interface. The input interface is responsible for receiving the measured current information. The TMR full-bridge sensor is the core sensing element of the system, employing four TMR magnetoresistive elements to form a Wheatstone full-bridge structure. When the external measured current generates a magnetic field around the sensor, the tunneling magnetoresistive value of the TMR element changes with the magnetic field strength. The full-bridge structure converts this magnetoresistive change into a differential voltage signal output. The full-bridge configuration not only improves measurement sensitivity but also effectively suppresses temperature drift and common-mode interference, ensuring the stability and accuracy of the output signal. The differential amplifier circuit precisely amplifies the weak differential signal output from the TMR sensor. It employs a precision instrumentation amplifier with high common-mode rejection ratio and adjustable gain, while integrating low-noise, low-temperature drift, and high-frequency filtering functions to effectively suppress external electromagnetic interference and internal system noise. The power supply voltage sampling module is a key component for achieving voltage feedback self-calibration. It monitors the waveform changes of the system power supply voltage in real time through a high-precision resistor divider network and adjusts it to the acceptable input range of the ADC. The sampling accuracy of this module directly determines the effectiveness of subsequent compensation algorithms. The digital-to-analog converter module uses a high resolution of 16 bits or higher and a sampling rate of no less than 1MHz to meet the technical requirements of high-precision current measurement. The digital processing unit, based on high-performance digital signal processing or a field-programmable gate array (FPGA), is responsible for executing core signal processing algorithms such as phase detection, phase alignment compensation, and adaptive filtering. It also provides a standard digital communication interface to support data exchange with a host computer or monitoring system. The output interface provides fully calibrated current measurement results. The entire hardware system is compactly designed, and the modules are connected through optimized signal links to ensure signal transmission integrity and system reliability.

[0062] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A self-correcting measurement method for a voltage feedback based tunneling magnetoresistance current sensor, characterized in that, The method comprises: obtaining the supply voltage and the initial output voltage of the sensor, performing spectrum analysis, and extracting a fundamental wave complex component at a fundamental wave frequency; calculating filter coefficients according to the fundamental wave complex component and performing phase correction on the output voltage to obtain a corrected output voltage sequence aligned in phase with the supply voltage signal; calculating a voltage ratio signal according to the corrected output voltage and the supply voltage and determining a residual error of the voltage ratio signal; calculating a filter output according to the voltage ratio signal and the residual error of the voltage ratio signal; combining the filter output with the voltage ratio signal to obtain a final current estimation.

2. A self-calibrating measurement method for a voltage feedback based tunneling magnetoresistance current sensor as claimed in claim 1, characterized in that, The step of extracting the fundamental wave complex component at the fundamental wave frequency comprises: obtaining the supply voltage and the initial output voltage of the sensor; performing spectrum analysis on the supply voltage and the initial output voltage to obtain a spectrum analysis result; determining the fundamental wave complex component of the supply voltage and the initial output voltage through the spectrum analysis result.

3. A self-calibrating measurement method for a voltage feedback based tunneling magnetoresistance current sensor as claimed in claim 2, characterized in that, The step of calculating filter coefficients and performing phase correction on the output voltage comprises: obtaining phase angles of the supply voltage and the initial output voltage through the fundamental wave complex component; calculating a phase difference according to the phase angles of the supply voltage and the initial output voltage; calculating a phase compensation coefficient through the phase difference and a reference filter coefficient; performing phase correction on the output voltage according to the phase compensation coefficient to obtain a corrected output voltage sequence aligned in phase with the supply voltage signal.

4. A self-calibrating measurement method for a voltage feedback based tunneling magnetoresistance current sensor as claimed in claim 3, wherein, The step of calculating a voltage ratio signal and determining a residual error of the voltage ratio signal comprises: calculating the voltage ratio signal through the corrected output voltage and the supply voltage; obtaining the residual error of the voltage ratio signal by subtracting a reference voltage ratio signal from the voltage ratio signal.

5. A self-calibrating measurement method for a voltage feedback based tunneling magnetoresistance current sensor as claimed in claim 4, characterized in that, The step of calculating a filter output according to the voltage ratio signal and the residual error of the voltage ratio signal comprises: calculating a residual compensation weight according to the voltage ratio signal sequence and the residual error of the voltage ratio signal; calculating the filter output according to the residual compensation weight and the voltage ratio signal.

6. A self-calibrating measurement method for a voltage feedback based tunneling magnetoresistance current sensor as claimed in claim 5, characterized in that, The step of combining the filter output with the voltage ratio signal to obtain a final current estimation comprises: calculating an effective voltage ratio signal according to the filter output and the voltage ratio signal; calculating a current estimation value according to the effective voltage ratio signal.

7. A self-calibrating measurement method for a voltage feedback based tunneling magnetoresistance current sensor as claimed in claim 5, wherein, The formula for calculating the residual compensation weight is: ； wherein is a next cycle residual compensation weight, is a current cycle residual compensation weight, is a ratio signal residual, is a step factor, is a ratio signal sequence, and L is a filter length, is a voltage ratio signal; The formula for calculating the filter output is: ； wherein is the filter output, is the index variable.

8. A self-calibrating measurement system for a voltage feedback based tunneling magnetoresistance current sensor, applying a self-calibrating measurement method for a voltage feedback based tunneling magnetoresistance current sensor according to any one of claims 1 to 7, characterized in that, The method comprises: a data acquisition module: obtaining the supply voltage and the initial output voltage of the sensor; a spectrum analysis module: performing spectrum analysis on the supply voltage and the initial output voltage to extract a fundamental wave complex component at a fundamental wave frequency; a phase correction module: calculating filter coefficients according to the fundamental wave complex component and performing phase correction on the output voltage to obtain a corrected output voltage sequence aligned in phase with the supply voltage signal; a first data calculation module: calculating a voltage ratio signal according to the corrected output voltage and the supply voltage, determining a residual error of the voltage ratio signal and a voltage ratio signal sequence, and calculating a filter output; a second data calculation module: combining the filter output with the voltage ratio signal to obtain a final current estimation. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-8 when the computer program is executed by the processor. The processor executes the computer program to implement the steps of the tunnel magnetoresistance current sensor self-correcting measurement method based on voltage feedback according to any one of claims 1 to 7.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the tunnel magnetoresistance current sensor self-correcting measurement method based on voltage feedback according to any one of claims 1 to 7.

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