Method and apparatus for constructing a hall magnetic balance current sensor

Abstract

The application provides a construction method and device of a Hall magnetic balance type current sensor, and the method comprises the following steps: obtaining known hardware parameters and target performance indexes of a Hall magnetic balance type current sensor to be constructed; based on a closed-loop zero magnetic flux principle, calculating a TMR chip parameter constraint boundary according to the known hardware parameters and the target performance indexes; selecting a target TMR chip meeting the calculated TMR chip parameter constraint boundary from current TMR chip products according to the calculated TMR chip parameter constraint boundary; and constructing the Hall magnetic balance type current sensor by using the target TMR chip and according to the hardware parameters. The traditional experience trial and error type selection is changed into a theory driven quantitative design, and the quantitative indexes of the adaptive TMR chip can be determined at one time in the design stage, so that the development cycle of the sensor is significantly shortened, and the construction efficiency of the Hall magnetic balance type current sensor is effectively improved.

Description

Technical Field

[0001] This application relates to the field of sensor design technology, and in particular to a method for constructing a Hall magnetic balance current sensor, a device for constructing a Hall magnetic balance current sensor, a computer device, a computer-readable storage medium, and a computer program product. Background Technology

[0002] With the large-scale integration of new energy sources and the deepening transformation of power systems towards power electronics, new power systems exhibit complex operating characteristics such as low power factor, high-order harmonics, and DC bias. Traditional electromagnetic induction current sensors are limited by inherent defects such as magnetic saturation of ferromagnetic materials, narrow bandwidth, and poor DC resistance, making it difficult to achieve high-precision measurement over a wide frequency and range. Magnetic sensing technology based on the tunneling magnetoresistance (TMR) effect, with its advantages of high sensitivity, wide bandwidth, and low power consumption, has become a key technological direction for solving these problems. Among them, the Hall magnetic balance current sensor based on the zero-flux principle is the mainstream architecture for high-precision measurement. The TMR chip, as the core magnetic field detection unit, directly determines the final accuracy and range of the sensor.

[0003] Currently, the design of Hall effect magnetic balance current sensors typically begins with determining the geometric dimensions of the magnetic ring and air gap based on the application scenario's requirements for range and accuracy, combined with experience. Finite element simulation analysis is then used to analyze the impact of the magnetic circuit structure on the magnetic field distribution, completing the initial structural design. Building upon this, designers begin screening from existing commercial TMR chip product libraries. Based on parameters such as sensitivity, linearity, and zero-point bias voltage provided in the product manuals, they select chip models whose values ​​are closest to the design expectations for initial adaptation. After selecting a chip, the back-end signal conditioning circuit and feedback compensation circuit are designed around the chip's input / output characteristics, including setting the amplification factor, configuring the filter network, and building the feedback coil drive circuit. If necessary, external circuits are used to compensate for inherent performance defects of the chip. After prototype assembly, the sensor undergoes testing for key indicators such as accuracy and linearity. If the test results fail to meet the preset sensor accuracy or range requirements, designers, based on experience, systematically check each step, speculate on possible causes, readjust the magnetic circuit dimensions, or replace the chip, and repeat the prototype preparation and testing. This iterative process continues until the prototype's measured performance meets the sensor's design specifications.

[0004] However, designers can only make rough selections based on typical or range values ​​of parameters given in the product manual. The quantitative correlation between parameters such as sensitivity, linearity, and zero-point bias voltage and the final accuracy of the sensor is unclear, and the design phase cannot predict whether the selected chip will meet the accuracy requirements of the final product. This uncertainty makes prototype testing the only means of verifying chip compatibility. If the test fails, the magnetic circuit, chip, and circuit components must be checked one by one, readjusted, and prototyped again. This iterative process leads to extended development cycles, increased development costs, and the need to repeat this trial-and-error process for each new product development. Design experience is difficult to reuse across different projects, severely reducing the overall development efficiency of sensor products. Summary of the Invention

[0005] The purpose of this application is to provide a method for constructing a Hall magnetic balance current sensor, a device for constructing a Hall magnetic balance current sensor, a computer device, a computer-readable storage medium, and a computer program product, so as to improve the research and development efficiency of Hall magnetic balance current sensors.

[0006] To address the aforementioned technical problems, the embodiments of this application provide the following technical solutions: The first aspect of this application provides a method for constructing a Hall magnetic balance current sensor. The method includes: obtaining known hardware parameters and target performance indicators of the Hall magnetic balance current sensor to be constructed; calculating TMR chip parameter constraint boundaries based on the closed-loop zero flux principle and the known hardware parameters and target performance indicators; selecting target TMR chips that meet the calculated TMR chip parameter constraint boundaries from current TMR chip products based on the calculated TMR chip parameter constraint boundaries; and constructing the Hall magnetic balance current sensor using the target TMR chip and according to the hardware parameters.

[0007] Compared to existing technologies, the method for constructing a Hall magnetic balance current sensor provided in the first aspect of this application obtains the known hardware parameters and target performance indicators of the sensor to be constructed, quantitatively calculates the TMR chip parameter constraint boundary based on the closed-loop zero flux principle, and accurately selects the target TMR chip from existing TMR chip products for sensor construction based on the TMR chip parameter constraint boundary. This transforms the traditional experience-based trial-and-error selection into a theory-driven quantitative design, allowing the quantitative indicators of the suitable TMR chip to be determined at the design stage in one go, eliminating the need for repeated iterative cycles of chip selection, prototype preparation, performance testing, and parameter adjustment. This significantly shortens the sensor development cycle and effectively improves the construction efficiency of the Hall magnetic balance current sensor.

[0008] In other embodiments provided in this application, the target performance index includes at least the target measurement accuracy, and the known hardware parameters include at least the operational amplifier gain, coil impedance, and TMR supply voltage. Based on the closed-loop zero flux principle, the tunneling magnetoresistive effect TMR chip parameter constraint boundary is calculated according to the known hardware parameters and the target performance index, including: determining the maximum allowable error of the Hall magnetic balance current sensor based on the target measurement accuracy; determining the first sensitivity threshold of the TMR chip based on the maximum error, operational amplifier gain, coil impedance, and TMR supply voltage, wherein the first sensitivity threshold enables the output signal of the TMR chip to drive the feedback coil to generate a reverse compensation magnetic field under the operational amplifier gain, so as to cancel the magnetic field generated by the primary current; and using the first sensitivity threshold as a constraint term in the TMR chip parameter constraint boundary.

[0009] By determining the maximum allowable error of the sensor based on the target measurement accuracy, and quantitatively calculating the first sensitivity threshold of the TMR chip in combination with the operational amplifier gain, coil impedance, and TMR supply voltage, the chip sensitivity at the circuit level can drive the feedback coil to generate a sufficient reverse compensation magnetic field to counteract the primary current magnetic field. This ensures that the output signal of the selected TMR chip matches the gain of the back-end circuit during the design phase, avoiding repeated adjustments to circuit parameters or replacement of chips due to feedback loop failure caused by insufficient sensitivity, and further improving the construction efficiency of Hall magnetic balance current sensor.

[0010] In other embodiments provided in this application, the known hardware parameters also include magnetic circuit parameters, and the target performance indicators also include the target range; the maximum allowable error of the Hall magnetic balance current sensor is determined based on the target measurement accuracy; the first sensitivity threshold of the TMR chip is determined based on the maximum error, operational amplifier gain, coil impedance, and TMR supply voltage, including: determining the maximum magnetic field generated by the full-scale current at the air gap based on the magnetic circuit parameters and the target range, where the air gap is the gap in the magnetic circuit structure of the Hall magnetic balance current sensor used to place the TMR chip; determining the correspondence between the residual magnetic field at the air gap under the maximum magnetic field and the sensitivity of the TMR chip based on the closed-loop zero flux principle, where the variables in the correspondence include the residual magnetic field and the sensitivity of the TMR chip, and the feasible region of the correspondence is constrained by the operational amplifier gain, coil impedance, and TMR supply voltage; determining the maximum allowable residual magnetic field at the air gap based on the maximum error, and substituting the maximum residual magnetic field as the extreme value constraint of the residual magnetic field into the correspondence to calculate the initial sensitivity threshold of the TMR chip; and compensating the initial sensitivity threshold based on the temperature drift rate of the TMR chip within its operating temperature range to obtain the first sensitivity threshold.

[0011] By determining the maximum magnetic field generated by the full-scale current at the air gap based on the magnetic circuit parameters and the target range, and compensating the initial sensitivity threshold with the temperature drift rate, the first sensitivity threshold is obtained. This ensures that the determination of the sensitivity threshold takes into account both the actual working conditions of the magnetic circuit and the performance degradation over the entire temperature range. As a result, a sensitivity constraint value that meets the requirements of all operating conditions can be obtained at the design stage, eliminating the need for reselection and debugging due to sensor accuracy deviations caused by temperature changes. This further improves the construction efficiency of Hall magnetic balance current sensors.

[0012] In other embodiments provided in this application, the target performance index includes at least a current detection threshold, and the known hardware parameters include at least operational amplifier noise parameters and TMR noise parameters. Based on the closed-loop zero flux principle, the tunneling magnetoresistance effect TMR chip parameter constraint boundary is calculated according to the known hardware parameters and the target performance index, including: determining a second sensitivity threshold for the TMR chip based on the current detection threshold, operational amplifier noise parameters, and TMR noise parameters. The second sensitivity threshold enables the output signal of the TMR chip to be greater than the combined noise of operational amplifier noise and TMR noise at the current detection threshold. The second sensitivity threshold is used as a constraint term in the TMR chip parameter constraint boundary.

[0013] By determining the second sensitivity threshold based on the current detection threshold and the noise parameters of the operational amplifier and TMR, the TMR chip can output a value higher than the system's synthesized noise floor when detecting weak signals. This ensures that the sensor has a theoretically achievable current detection threshold during the design phase, eliminating the need for reselection due to weak signals being overwhelmed by noise caused by insufficient sensitivity. This further improves the construction efficiency of Hall magnetic balance current sensors.

[0014] In other embodiments provided in this application, determining a second sensitivity threshold for the TMR chip based on a current detection threshold, operational amplifier noise parameters, and TMR noise parameters includes: determining the minimum magnetic field signal that the Hall magnetic balance current sensor needs to detect based on the current detection threshold; determining the operational amplifier noise voltage of the corresponding operational amplifier component within its operating bandwidth based on the operational amplifier noise parameters; determining the TMR magnetic noise of the TMR chip within its operating bandwidth based on the TMR noise parameters; determining the total noise based on the operational amplifier noise voltage and the TMR magnetic noise; and determining, based on the minimum magnetic field signal and the total noise, the minimum sensitivity value required for the TMR chip to detect the minimum magnetic field signal that its output signal is higher than the total noise, as the second sensitivity threshold.

[0015] By determining the minimum magnetic field signal based on the current detection threshold, and calculating the operational amplifier noise voltage and TMR magnetic noise separately to synthesize the total noise, the minimum sensitivity value required for the TMR output signal to be higher than the total noise is determined. This ensures that the determination of the second sensitivity threshold fully covers the combined influence of all noise sources in the system. As a result, the sensor can be guaranteed to have a true signal-to-noise ratio margin when detecting weak signals during the design phase. This eliminates the need for rework and adjustment due to insufficient noise estimation leading to substandard measured current detection thresholds, further improving the construction efficiency of Hall magnetic balance current sensors.

[0016] In other embodiments provided in this application, the target performance indicators include target measurement accuracy and current detection threshold. Known hardware parameters include operational amplifier gain, coil impedance, TMR supply voltage, operational amplifier noise parameters, and TMR noise parameters. The method further includes: determining the maximum allowable error of the Hall magnetic balance current sensor based on the target measurement accuracy; determining a first sensitivity threshold of the TMR chip based on the maximum error, operational amplifier gain, coil impedance, and TMR supply voltage, wherein the first sensitivity threshold enables the output signal of the TMR chip to drive the feedback coil to generate a reverse compensation magnetic field under the operational amplifier gain, thereby canceling the magnetic field generated by the primary current; determining a second sensitivity threshold of the TMR chip based on the current detection threshold, operational amplifier noise parameters, and TMR noise parameters, wherein the second sensitivity threshold enables the output signal of the TMR chip to be greater than the combined noise of operational amplifier noise and TMR noise under the current detection threshold; and using the higher of the first and second sensitivity thresholds as a constraint term in the TMR chip parameter constraint boundary.

[0017] By using the higher of the first and second sensitivity thresholds as a constraint term in the TMR chip parameter constraint boundary, the selected single sensitivity index can simultaneously meet the dual requirements of circuit driving capability and noise suppression, eliminating the need for separate selection and verification for different constraint conditions, and further improving the construction efficiency of Hall magnetic balance current sensor.

[0018] In other embodiments provided in this application, the target performance index includes at least the target range, and the known hardware parameters include at least the maximum output voltage of the operational amplifier, the operational amplifier gain, the coil impedance, the TMR supply voltage, and the sensitivity threshold of the TMR chip. Based on the closed-loop zero flux principle, the tunneling magnetoresistance effect TMR chip parameter constraint boundary is calculated according to the known hardware parameters and the target performance index, including: determining the maximum allowable input voltage at the input terminal of the operational amplifier component based on the maximum output voltage and operational amplifier gain; determining the correspondence between the residual magnetic field of the TMR chip at the air gap and the sensitivity of the TMR chip based on the closed-loop zero flux principle; determining the signal voltage generated by the TMR chip at the air gap based on the correspondence, the coil impedance, the TMR supply voltage, and the sensitivity threshold; determining the zero-point bias voltage threshold of the TMR chip based on the maximum input voltage and the signal voltage, such that the sum of the signal voltage and the zero-point bias voltage does not exceed the maximum input voltage; and using the zero-point bias voltage threshold as a constraint term in the TMR chip parameter constraint boundary.

[0019] By determining the maximum input voltage at the input terminal based on the maximum output voltage and gain of the operational amplifier, and combining the correspondence between the residual magnetic field and sensitivity to determine the signal voltage, the zero-point bias voltage threshold is calculated with the constraint that the sum of the signal voltage and the zero-point bias voltage does not exceed the maximum input voltage. This ensures that the selected TMR chip will not saturate and distort due to excessive bias voltage across the entire range. Thus, the complete linear operating range of the signal link can be ensured during the design phase, eliminating the need to repeatedly adjust the circuit bias or replace the chip due to saturation distortion issues, further improving the construction efficiency of the Hall magnetic balance current sensor.

[0020] In other embodiments provided in this application, the known hardware parameters also include magnetic circuit parameters; determining the zero-point bias voltage threshold of the TMR chip based on the maximum input voltage and signal voltage includes: determining the maximum magnetic field generated by the full-scale current at the air gap based on the magnetic circuit parameters and the target range; determining the signal voltage generated by the TMR chip under the residual magnetic field based on the correspondence, coil impedance, TMR supply voltage and sensitivity threshold; and subtracting the signal voltage from the maximum input voltage to obtain the zero-point bias voltage threshold.

[0021] By determining the maximum magnetic field generated by the full-scale current at the air gap based on the magnetic circuit parameters and the target range, and determining the signal voltage based on the correspondence between the residual magnetic field and the sensitivity, the zero-point bias voltage threshold is obtained by subtracting the signal voltage from the maximum input voltage. This ensures that the constraint determination of the zero-point bias voltage fully combines the actual working conditions of the magnetic circuit and the circuit gain boundary, eliminating the need for reselection and debugging due to op-amp saturation caused by inaccurate bias estimation, and further improving the construction efficiency of the Hall magnetic balance current sensor.

[0022] In other embodiments provided in this application, the target performance index includes at least the target range, and the known hardware parameters include at least the magnetic circuit parameters. Based on the closed-loop zero flux principle, the tunneling magnetoresistance effect TMR chip parameter constraint boundary is calculated according to the known hardware parameters and the target performance index. This includes: determining the air gap magnetic field generated by the primary current at the air gap and the compensation magnetic field generated by the feedback current at the air gap according to the magnetic circuit parameters and the target range; determining the linear range threshold of the TMR chip according to the higher magnetic field in the air gap magnetic field and the compensation magnetic field and the preset safety factor, so that the TMR chip does not saturate due to the instantaneous magnetic field impact during current change; and using the linear range threshold as a constraint term in the TMR chip parameter constraint boundary.

[0023] By determining the air gap magnetic field and compensation magnetic field based on the magnetic circuit parameters and target range, and combining the larger of the two with a preset safety factor to determine the linear range threshold, the selected TMR chip can remain in the linear operating region without saturation under transient conditions such as current surges. This ensures the dynamic response reliability of the sensor during the design phase, eliminating the need for re-selection and testing due to output distortion caused by transient saturation, and further improving the construction efficiency of Hall magnetic balance current sensors.

[0024] In other embodiments provided in this application, the linear range threshold of the TMR chip is determined based on the higher magnetic field in the air gap magnetic field and the compensation magnetic field and a preset safety factor, including: amplifying the higher magnetic field in the air gap magnetic field and the compensation magnetic field according to the safety factor to obtain the peak magnetic field that may appear at the air gap when the current changes abruptly; and using the peak magnetic field as the linear range threshold of the TMR chip.

[0025] By using the high magnetic field in the air gap magnetic field and the compensation magnetic field with a safety factor as the linear range threshold, the linear range of the selected TMR chip can cover the peak magnetic field impact that may occur during current change. This ensures that the chip remains unsaturated under extreme transient conditions during the design phase, eliminating the need for repeated verification and adjustment due to system oscillation or response distortion caused by dynamic saturation, and further improving the construction efficiency of Hall magnetic balance current sensor.

[0026] In other embodiments provided in this application, the target performance index includes at least the target measurement accuracy, and the known hardware parameters include at least the operational amplifier gain, coil impedance, TMR supply voltage, magnetic circuit parameters, and the sensitivity threshold of the TMR chip. Based on the closed-loop zero flux principle, the tunneling magnetoresistive effect TMR chip parameter constraint boundary is calculated according to the known hardware parameters and the target performance index, including: determining the loop gain of the Hall magnetic balance current sensor based on the operational amplifier gain, sensitivity threshold, proportionality coefficient between the air gap magnetic field and the feedback current, coil impedance, and TMR supply voltage; determining the allowable nonlinearity threshold of the TMR chip based on the target measurement accuracy and loop gain, so that the nonlinearity error of the TMR chip meets the target measurement accuracy after being suppressed by the loop gain; and using the nonlinearity threshold as a constraint term in the TMR chip parameter constraint boundary.

[0027] By determining the loop gain based on the operational amplifier gain, sensitivity threshold, proportional coefficient, coil impedance, and supply voltage, and then deriving the allowable nonlinearity threshold of the TMR chip in conjunction with the target measurement accuracy, the determination of the nonlinearity constraint fully considers the closed-loop system's ability to suppress nonlinear errors. This eliminates the need for repeated trial and error due to difficulties in selection or exceeding accuracy limits caused by overly strict or lenient nonlinearity specifications, further improving the construction efficiency of Hall magnetic balance current sensors.

[0028] In other embodiments provided in this application, determining the permissible nonlinearity threshold of the TMR chip based on the target measurement accuracy and loop gain includes: establishing an error propagation relationship based on the closed-loop zero flux principle, whereby the nonlinearity error of the TMR chip is transmitted to the output of the Hall magnetic balance current sensor after being suppressed by the loop gain; determining the maximum permissible total error of the Hall magnetic balance current sensor based on the target measurement accuracy; substituting the maximum total error as a boundary condition into the error propagation relationship to calculate the maximum permissible nonlinearity error of the TMR chip; and determining the nonlinearity threshold based on the ratio of the maximum nonlinearity error to the full-scale output signal of the TMR chip.

[0029] By establishing the error propagation relationship from nonlinear error to sensor output after being suppressed by loop gain, and determining the nonlinearity threshold by back-calculating the maximum nonlinear error using the maximum total error as the boundary, the determination of nonlinearity constraints accurately quantifies the actual suppression capability of the closed-loop system for nonlinear error. This eliminates the need for repeated adjustments to the selection due to prototype accuracy exceeding the limit caused by nonlinearity index mismatch, further improving the construction efficiency of Hall magnetic balance current sensor.

[0030] In other embodiments provided in this application, before calculating the parameter constraint boundary of the tunneling magnetoresistive effect (TMR) chip based on the closed-loop zero flux principle and according to known hardware parameters and target performance indicators, the method further includes: obtaining the magnetic circuit parameters of the Hall magnetic balance current sensor; performing finite element simulation based on the magnetic circuit parameters to obtain a first proportionality coefficient characterizing the ratio of the magnetic field generated by the primary current at the air gap to the primary current, and a second proportionality coefficient characterizing the ratio of the feedback current to the air gap magnetic induction intensity; calculating the parameter constraint boundary of the tunneling magnetoresistive effect (TMR) chip based on the closed-loop zero flux principle and according to known hardware parameters and target performance indicators, including: calculating the parameter constraint boundary of the tunneling magnetoresistive effect (TMR) chip based on the closed-loop zero flux principle and according to known hardware parameters, target performance indicators, the first proportionality coefficient, and the second proportionality coefficient.

[0031] By acquiring magnetic circuit parameters and performing finite element simulation to obtain the first and second proportional coefficients, the range requirement is converted into the air gap magnetic field value, and the chip output signal is converted into the reverse compensation magnetic field. This allows the calculation of parameter constraint boundaries to be based on the actual magnetic circuit characteristics rather than empirical estimation. As a result, the actual working magnetic field range of the TMR chip can be accurately obtained in the design stage, eliminating the need for repeated simulation iterations due to selection deviations caused by inaccurate matching of magnetic circuit and circuit parameters. This further improves the construction efficiency of the Hall magnetic balance current sensor.

[0032] A second aspect of this application provides a device for constructing a Hall magnetic balance current sensor. The device includes: an acquisition module for acquiring known hardware parameters and target performance indicators of the Hall magnetic balance current sensor to be constructed; a calculation module for calculating the tunneling magnetoresistance effect (TMR) chip parameter constraint boundaries based on the closed-loop zero flux principle and the known hardware parameters and target performance indicators; a screening module for selecting target TMR chips that meet the calculated TMR chip parameter constraint boundaries from current TMR chip products; and a construction module for constructing the Hall magnetic balance current sensor using the target TMR chip according to the hardware parameters.

[0033] A third aspect of this application provides a computer device including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the method of the first aspect.

[0034] A fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method of the first aspect.

[0035] The fifth aspect of this application provides a computer program product, including a computer program that, when executed by a processor, implements the method of the first aspect.

[0036] The apparatus for constructing a Hall magnetic balance current sensor provided in the second aspect of this application, the computer device provided in the third aspect, the computer-readable storage medium provided in the fourth aspect, and the computer program product provided in the fifth aspect have the same or similar beneficial effects as the method for constructing a Hall magnetic balance current sensor provided in the first aspect. Attached Figure Description

[0037] The above and other objects, features, and advantages of exemplary embodiments of this application will become readily understood by reading the following detailed description with reference to the accompanying drawings. In the drawings, several embodiments of this application are illustrated by way of example and not limitation, with the same or corresponding reference numerals denoteing the same or corresponding parts, wherein: Figure 1 This is a flowchart illustrating the construction method of the Hall magnetic balance current sensor in the embodiments of this application. Figure 1 ; Figure 2 This is a flowchart illustrating the construction method of the Hall magnetic balance current sensor in the embodiments of this application. Figure 2 ; Figure 3 This is a schematic diagram of the structure of the Hall magnetic balance current sensor construction device in the embodiments of this application. Figure 1 ; Figure 4 This is a schematic diagram of the structure of the Hall magnetic balance current sensor construction device in the embodiments of this application. Figure 2 ; Figure 5 This is a schematic diagram of the structure of the computer device in the embodiments of this application. Detailed Implementation

[0038] Exemplary embodiments of this application will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of this application are shown in the drawings, it should be understood that this application may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of this application and to fully convey the scope of this application to those skilled in the art.

[0039] It should be noted that, unless otherwise stated, the technical or scientific terms used in this application shall have the ordinary meaning as understood by one of ordinary skill in the art to which this application pertains.

[0040] It should be noted that the user data, data acquisition, and / or use involved in the embodiments of this application strictly comply with the laws, regulations, and industry standards of relevant countries and regions. The collection and acquisition of data involved in the embodiments of this application are all done in advance by actively prompting or prominently displaying information to inform users and obtaining authorization, or by obtaining full authorization from all parties. The processing, manipulation, forwarding, and use of data involved in the embodiments of this application are all carried out on the premise that the user or relevant party is fully informed and authorized. In implementing the various embodiments of this application, the types of data or information, scope of use, and usage scenarios that may be involved are informed to users or relevant parties and authorization is obtained through appropriate means. The specific methods of notification and authorization may vary according to the actual situation, and this application is not limited in this regard. The processing of personal information involved in the embodiments of this application is carried out under the premise of having a legal basis (such as obtaining the consent of the personal information subject or being necessary for the performance of a contract), and is only processed within the prescribed or agreed scope. Sensitive personal information such as biometric information, medical and health information, financial account information, and precise location information involved in the embodiments of this application are all processed under the premise of having a specific purpose and sufficient necessity, and with the separate authorization and consent of the user or relevant party. In some embodiments of this application, if the user or related party refuses to process personal information other than the information necessary for the basic functions, it will not affect the use of the basic functions of the embodiments of this application.

[0041] Currently, the construction of Hall magnetic balance current sensors relies on a trial-and-error process involving structural design, experience-based selection, prototype testing, and iterative troubleshooting. This results in a lack of quantitative basis for chip selection, which involves deriving parameter constraints from the system accuracy target. The matching can only be verified by repeatedly preparing prototypes, leading to problems such as long R&D cycles, high development costs, and difficulty in reusing design experience.

[0042] In view of this, embodiments of this application provide a method for constructing a Hall magnetic balance current sensor, a device for constructing a Hall magnetic balance current sensor, a computer device, a computer-readable storage medium, and a computer program product. By using the known hardware parameters of the sensor and the target performance indicators as input, the multi-dimensional parameter constraint boundaries of the TMR chip are quantitatively calculated using the closed-loop zero flux principle. This transforms the traditional trial-and-error selection into a quantitative screening based on a mathematical model, allowing chip selection to be completed once at the design stage based on the quantitative boundaries. This eliminates the need for repeated prototype preparation to verify matching, thereby shortening the R&D cycle, reducing development costs, and making design experience reusable, effectively improving the construction efficiency of the Hall magnetic balance current sensor.

[0043] First, the construction method of the Hall magnetic balance current sensor provided in the embodiments of this application will be described.

[0044] Figure 1 This is a flowchart illustrating the construction method of the Hall magnetic balance current sensor in the embodiments of this application. Figure 1 See Figure 1 As shown, the method may include: S11: Obtain the known hardware parameters and target performance indicators of the Hall magnetic balance current sensor to be constructed.

[0045] The Hall effect magnetic balance current sensor to be constructed refers to a closed-loop magnetic balance current detection device that has not yet been finalized and requires determination of the parameter constraints of the core component, the TMR chip, based on given hardware conditions (such as known hardware parameters like magnetic ring structure, operational amplifier gain, coil impedance, and TMR supply voltage) and target performance indicators (such as target measurement accuracy, range, and current detection threshold). This involves selecting or customizing the chip to achieve the overall design. For example, the sensor to be constructed might have a rated primary current of 100A, an accuracy of 0.1 class, uses a TMR chip as the magnetic sensing element, has an operational amplifier gain of 2500, and a coil impedance of 70Ω. Another example is a closed-loop magnetic balance leakage current sensor with a rated primary current of 50A, an accuracy of 0.2 class, uses a TMR chip as the magnetic sensing element, has an operational amplifier gain of 2000, and a coil impedance of 50Ω.

[0046] Known hardware parameters refer to the inherent hardware conditions of the Hall magnetic balance current sensor to be constructed that have been determined during the design phase and are independent of the TMR chip selection. These include, but are not limited to, magnetic circuit parameters such as the geometry and number of turns of the magnetic ring and air gap, operational amplifier gain, coil impedance, TMR supply voltage, maximum output voltage of the operational amplifier, and operational amplifier noise parameters.

[0047] The target performance indicators refer to the expected performance requirements that the Hall magnetic balance current sensor to be constructed needs to achieve, including but not limited to target measurement accuracy, target range, and current detection threshold. The current detection threshold refers to the minimum primary current value that the Hall magnetic balance current sensor can effectively distinguish and measure. When the primary current is lower than this value, the sensor's output signal will be overwhelmed by system noise and cannot be accurately measured.

[0048] S12: Based on the closed-loop zero flux principle, calculate the parameter constraint boundary of the tunneling magnetoresistive effect TMR chip according to the known hardware parameters and target performance indicators.

[0049] The so-called closed-loop zero flux principle refers to the phenomenon in a Hall effect magnetic balance current sensor where a primary current flowing through a conductor generates magnetic flux in the core. A TMR chip located in the air gap of the core senses this magnetic field strength in real time. The closed-loop feedback circuit drives a feedback coil to generate a secondary feedback current based on the output signal of the TMR chip. The magnetic flux generated by this feedback current in the core is opposite in direction to the primary current flux. Through negative feedback control, the resultant magnetic field (i.e., the residual magnetic field) at the air gap dynamically approaches zero, ensuring the core always operates in an ideal zero flux state. At this point, according to the ampere-turn balance principle, the primary current and the feedback current satisfy the relationship of equal ampere-turns. Therefore, by measuring the feedback current, the value of the primary current can be accurately deduced.

[0050] In specific calculations, the overall performance target of the sensor can be started from, and the constraint boundaries of each core parameter of the TMR chip can be solved in reverse. Specifically, firstly, magnetic circuit parameters (such as the proportionality coefficient between the air gap magnetic field and the primary current) are obtained using magnetic circuit simulation, establishing a quantitative relationship between the primary current, feedback current, and air gap magnetic field. Based on the closed-loop zero flux principle, a mathematical expression between the residual magnetic field and the sensitivity and circuit parameters of the TMR chip is derived. Secondly, using target performance indicators (such as target measurement accuracy, target range, current detection threshold, etc.) as boundary conditions, constraint equations are established for each core parameter of the TMR chip, and the critical values ​​that each parameter must satisfy are solved in reverse for each parameter. Finally, considering all constraints comprehensively, a complete TMR chip parameter constraint boundary system is formed. This system includes the threshold or threshold requirements of each parameter, serving as a quantitative basis for subsequent chip selection or custom design.

[0051] The TMR chip parameter constraint boundaries refer to the quantized range or limit values ​​that the core performance parameters (including sensitivity, zero-point bias voltage, linear range, nonlinearity, etc.) of the TMR chip must meet in order for the Hall magnetic balance current sensor to be constructed to achieve the preset target performance indicators. For example, the TMR chip parameter constraint boundaries include: sensitivity threshold greater than 1.55mV / V / Oe, zero-point bias voltage threshold less than 2.44mV, linear range threshold greater than 1.12Oe, and nonlinearity threshold better than 146.5%.

[0052] S13: Based on the calculated TMR chip parameter constraint boundary, select target TMR chips from the current TMR chip products that meet the calculated TMR chip parameter constraint boundary.

[0053] When screening target TMR chips, firstly, obtain the product manuals or specifications of existing commercial TMR chips on the market, and extract the core performance parameters of each candidate chip from the manuals, including sensitivity, zero-point bias voltage, linear range, and nonlinearity. Then, compare the parameters of each candidate chip one by one with the constraints calculated above. For parameters with threshold requirements (such as sensitivity), select chip models whose parameter values ​​are greater than or equal to the threshold. For parameters with threshold requirements (such as zero-point bias voltage and nonlinearity), select chip models whose parameter values ​​are less than or equal to the threshold. For parameters that require simultaneously meeting the upper threshold (such as linear range), select chip models whose parameter values ​​fall within that range. Finally, from all candidate chips, screen out the chip model that can simultaneously meet all constraint boundary conditions, and determine it as the target TMR chip.

[0054] If multiple chip models simultaneously meet all the constraints, a comprehensive evaluation will be conducted based on actual application requirements (such as cost, delivery cycle, package size, etc.), and the optimal one will be selected as the target TMR chip.

[0055] For example, suppose the calculated TMR chip parameter constraints are: sensitivity threshold greater than 1.55mV / V / Oe, zero-point bias voltage threshold less than 2.44mV, linear range threshold greater than 1.12Oe, and nonlinearity threshold better than 146.5%. The key parameters in the datasheets of three existing commercial TMR chips are as follows: Chip A: Sensitivity is 2.0mV / V / Oe, zero-point bias voltage is 1.8mV, linear range is ±3Oe, and nonlinearity is 0.1%; Chip B: Sensitivity is 1.2mV / V / Oe, zero-point bias voltage is 1.5mV, linear range is ±2Oe, and nonlinearity is 0.2%; Chip C: Sensitivity is 2.5mV / V / Oe, zero-point bias voltage is 3.0mV, linear range is ±5Oe, and nonlinearity is 0.15%.

[0056] As can be seen, chip A meets all constraints: sensitivity 2.0 > 1.55, zero-point bias voltage 1.8 < 2.44, linear range 3 > 1.12, and nonlinearity 0.1% < 146.5%. Chip B's sensitivity 1.2 < 1.55 does not meet the sensitivity threshold requirement and is therefore excluded. Chip C's zero-point bias voltage 3.0 > 2.44 does not meet the zero-point bias voltage threshold requirement and is also excluded. Therefore, chip A is selected as the target TMR chip.

[0057] S14: Using the target TMR chip, construct a Hall magnetic balance current sensor according to the hardware parameters.

[0058] In the specific construction, firstly, the magnetic ring and air gap are mechanically assembled according to the pre-designed magnetic circuit parameters. The target TMR chip is precisely installed at the center of the air gap of the magnetic ring, ensuring that the magnetic sensitivity direction of the chip is consistent with the direction of the air gap magnetic field to obtain the maximum magnetic field coupling efficiency. Then, the signal conditioning and feedback compensation circuit is built according to the determined circuit parameters. The output terminal of the TMR chip is connected to the input terminal of the operational amplifier, and the amplification factor is configured according to the operational amplifier gain setting value. After the amplified signal is filtered to remove high-frequency noise, one path is used as the sensor voltage signal output, and the other path is sent to the power amplifier stage to drive the feedback coil. The feedback coil is wound on the magnetic ring, and the direction of the compensation magnetic field it generates is opposite to the direction of the magnetic field generated by the primary current, forming a closed-loop negative feedback control. Finally, after the overall assembly is completed, the basic functions of the sensor are debugged. The connection polarity of the feedback coil is checked to ensure that the supply voltage of the TMR chip is stable at the set value, and the operating points of the operational amplifier are normal, ensuring that the sensor can establish a zero-flux closed-loop working state normally.

[0059] As can be seen from the above, the method for constructing a Hall magnetic balance current sensor provided in this application obtains the known hardware parameters and target performance indicators of the sensor to be constructed, quantitatively calculates the TMR chip parameter constraint boundary based on the closed-loop zero flux principle, and accurately selects the target TMR chip from existing TMR chip products for sensor construction based on the TMR chip parameter constraint boundary. This transforms the traditional experience-based trial-and-error selection into a theory-driven quantitative design, allowing the quantitative indicators of the suitable TMR chip to be determined at the design stage, eliminating the need for repeated iterative cycles of chip selection, prototype preparation, performance testing, and parameter adjustment. This significantly shortens the sensor development cycle and effectively improves the construction efficiency of the Hall magnetic balance current sensor.

[0060] Furthermore, as a response to Figure 1 As a refinement and extension of the method shown, this application embodiment also provides a method for constructing a Hall magnetic balance current sensor.

[0061] Figure 2 This is a flowchart illustrating the construction method of the Hall magnetic balance current sensor in the embodiments of this application. Figure 2 See Figure 2 As shown, the method may include: S21: Obtain the known hardware parameters and target performance indicators of the Hall magnetic balance current sensor to be constructed.

[0062] Step S21 here is implemented in the same way as step S11 in the previous embodiment. Please refer to the relevant description in the previous embodiment. It will not be repeated here.

[0063] S22: Perform finite element simulation based on the magnetic circuit parameters to obtain a first proportionality coefficient to characterize the ratio of the magnetic field generated by the primary current in the air gap to the primary current, and a second proportionality coefficient to characterize the ratio of the feedback current to the air gap magnetic induction intensity.

[0064] The known hardware parameters include magnetic circuit parameters. Magnetic circuit parameters refer to the geometric structure parameters and winding parameters of the magnetic core and air gap in the Hall magnetic balance current sensor to be constructed, including the magnetic ring size, air gap width, primary conductor core-passing method, and number of turns of the feedback coil.

[0065] When the magnetic flux is zero, according to the ampere-turn balance principle, the primary current and the feedback current satisfy I p N=I f N1, therefore the feedback current can be expressed as I f =I p N / N1 means that the current flows through the feedback coil, generating a corresponding compensating magnetic field at the air gap of the magnetic core. Where I p I f N, N1, and N2 are the feedback current, the feedback magnetic field at the air gap, the number of turns of the primary coil, and the number of turns of the feedback coil, respectively.

[0066] During the simulation, the magnetic circuit parameters of the Hall magnetic balance current sensor are obtained. A three-dimensional geometric model of the magnetic ring and air gap is established in the finite element simulation software. The magnetic permeability of the magnetic ring material and the air gap medium are set to air. The air gap region is meshed to ensure the accuracy of the magnetic field calculation at the air gap.

[0067] To obtain the first proportional coefficient, the primary current I is set respectively. p Static magnetic field simulations were performed for 0.04A, 0.1A, 1A, and 10A, and the magnetic induction intensity value B at the center of the air gap was extracted under each current condition. p By fitting different current values ​​with their corresponding air gap magnetic induction values, the fitting results show that B p with I p It exhibits a good linear relationship, with a proportionality constant k1=B p / I p =0.82mT / A, meaning that for every 1A change in the primary current, the magnetic induction intensity at the air gap changes by 0.82mT.

[0068] To obtain the second proportional coefficient, a feedback current I is similarly applied. f Static magnetic field simulation was performed to extract the air gap magnetic induction intensity B. f According to the equivalence relationship between magnetic circuits and electrical circuits, the magnetic flux density at the air gap of the magnetic core is proportional to the ampere-turns that generate the magnetic field. Therefore, combined with the number of turns N of the feedback coil... f The ratio of the feedback current to the number of turns N in the primary coil can be used to obtain the proportionality coefficient k2=B between the feedback current and the air gap magnetic field. f / I f =k1·(N f / N). Substituting the specific turns ratio, we get k2 = 2.05T / A, which means that for every 1A change in the feedback current, the compensating magnetic induction intensity at the air gap changes by 2.05T accordingly.

[0069] The first proportionality coefficient establishes a quantitative bridge between the measured quantity (primary current) and the magnetic field actually sensed by the TMR chip, enabling designers to convert the target range into a specific magnetic field value at the air gap, thereby determining the magnetic field range that the TMR chip needs to detect under that range, and providing boundary conditions for the magnetic field dimension for subsequent calculations of parameters such as sensitivity threshold and linear range.

[0070] The second proportional coefficient quantifies and converts the reverse compensation magnetic field generated after the TMR chip's output signal is amplified by the operational amplifier and driven by the feedback coil. This allows designers to establish a complete signal chain transmission relationship between the TMR chip's output voltage, feedback current, and air gap compensation magnetic field. Consequently, in residual magnetic field analysis, zero-point bias voltage constraints, and loop gain calculations, circuit parameters and magnetic circuit parameters can be quantitatively calculated under the same mathematical framework.

[0071] Of course, the first and second proportionality coefficients can also be obtained directly through analytical calculation of the magnetic circuit without finite element simulation. Specifically, based on Ohm's law of the magnetic circuit (magnetomotive force equals magnetic reluctance multiplied by magnetic flux), combined with the geometric dimensions of the magnetic ring (magnetic circuit length, air gap width, core cross-sectional area) and the material's permeability, the relationship between the air gap magnetic induction intensity and the primary current can be directly calculated analytically, thus obtaining the first proportionality coefficient. Similarly, based on the number of turns of the feedback coil and the magnetic circuit parameters, the second proportionality coefficient can be analytically obtained.

[0072] In this way, the calculation process does not need to rely on finite element simulation software. Only basic parameters such as the geometric dimensions of the magnetic ring and the magnetic permeability of the material are needed to quickly obtain the scaling factor, which reduces the design threshold and the initial investment cost. It also facilitates rapid parameter sensitivity analysis and iterative optimization in the early stages of design.

[0073] At this point, it is also possible to establish TMR chip parameter constraint boundaries without obtaining the first and second proportionality coefficients. The core idea is to switch the expression of the constraint boundaries from using the magnetic field as a parameter to using the current as a unified parameter. All constraint boundaries are directly derived and expressed based on the current dimension, while the air gap magnetic field is only used as an intermediate variable and obtained from the current through Ampere's circuital law of the magnetic circuit, without the need to extract the proportionality coefficient separately.

[0074] For example, regarding the sensitivity threshold, using the target measurement accuracy and range as boundary conditions, the minimum detectable current deviation corresponding to the sensor accuracy requirement is directly converted into the equivalent magnetic field at the air gap through magnetic circuit geometric parameters (air gap width, magnetic ring circuit length, and material permeability), thereby determining the sensitivity threshold. In this process, the magnetic field quantity is naturally derived from the current quantity through the analytical relationship of the magnetic circuit, without the need to obtain the specific value of the proportionality coefficient in advance; it can be directly calculated by substituting the magnetic ring geometric dimensions.

[0075] For example, the zero-point bias voltage threshold is determined using direct constraints at the circuit level. Based on the op-amp's maximum output voltage and gain, the maximum voltage that the op-amp's input can withstand is deduced. Subtracting this from the signal voltage output by the TMR chip at full-scale current gives the zero-point bias voltage threshold. The TMR output signal voltage corresponding to the full-scale current is determined by both the magnetic circuit geometry and the TMR chip's sensitivity; therefore, it can be obtained directly through analytical calculations of the magnetic circuit without the need for proportionality coefficient extraction.

[0076] This method of using current as a unified parameter eliminates the need to obtain the specific values ​​of the first and second proportional coefficients during the entire constraint boundary calculation process. Only basic physical parameters such as the geometric dimensions of the magnetic ring and the permeability of the material are required to establish a complete TMR chip parameter constraint boundary system, which greatly reduces the preconditions for method implementation. Furthermore, the physical meaning of all constraint boundaries directly corresponds to the measured quantity, making it easy for designers to understand intuitively and apply quickly.

[0077] S23: Based on the closed-loop zero flux principle, calculate the parameter constraint boundary of the tunneling magnetoresistive effect TMR chip according to the known hardware parameters, target performance indicators, first proportional coefficient and second proportional coefficient.

[0078] In addition to sensitivity threshold, zero-point bias voltage threshold, linear range threshold, and nonlinearity threshold, TMR chip parameter constraint boundaries can also include sensitivity threshold, operating temperature range constraint, long-term aging drift constraint, and power supply voltage fluctuation constraint.

[0079] The sensitivity threshold is established based on the ratio of the maximum allowable input voltage of the operational amplifier to the output signal of the TMR chip at full-scale current, preventing excessive sensitivity from causing operational amplifier saturation. The operating temperature range constraint is established based on the sensor's operating ambient temperature range and the temperature drift coefficient of the TMR chip, ensuring that the limiting parameters still meet the various constraint boundaries after temperature drift. The long-term aging drift constraint is established based on the sensor's design lifespan and the aging drift rate of the TMR chip, ensuring that the target measurement accuracy is maintained even after parameter drift within the lifespan. The power supply voltage fluctuation constraint is established based on the fluctuation range of the power supply and the dependence of the TMR chip's output voltage on the supply voltage, incorporating the error introduced by voltage fluctuations into the sensitivity threshold calculation for compensation. These constraints expand the TMR chip parameter constraint boundary system from basic constraints applicable only to normal temperature and ideal power supply conditions to comprehensive constraints covering wide temperature ranges, long lifespans, and non-ideal power supply scenarios in practical engineering applications, significantly improving the adaptability and reliability of the constraint boundary system under different application scenarios.

[0080] The sensitivity threshold, zero-point bias voltage threshold, linear range threshold, and nonlinearity threshold, respectively, correspond to the signal detection capability, signal fidelity starting point, dynamic operating range, and global accuracy determinants of the TMR chip. They constitute the complete performance guarantee chain of the Hall magnetic balance current sensor, from whether it can detect weak signals to whether it can maintain accuracy across the entire range. Therefore, they can be the main components of the parameter constraint boundary of the TMR chip.

[0081] In order to unify the above four parameter constraints under the same physical framework for correlation analysis, the residual magnetic field B is first introduced. net As an intermediate variable, it enables all parameter constraints to establish a quantitative mapping relationship with the circuit parameters and magnetic circuit parameters in the closed-loop zero flux principle, with the residual magnetic field as the link.

[0082] Residual magnetic field: B net =B p -B f In ideal circumstances, B net The value is 0. In practice, the feedback circuit requires TMR drive, so the TMR will experience a very small residual magnetic field. Ideally, the output voltage of the TMR is V. a =S TMR ·B net Therefore, S is required TMR It needs to be large enough to be detected.

[0083] After sorting, the remaining magnetic field B is obtained. net and TMR chip sensitivity S TMR Relationship:

[0084] Among them, B net For the residual magnetic field, B p and B f Let I represent the magnetic fields generated in the air gap by the primary current and the feedback current, respectively. k2 is the second proportionality coefficient between the air gap magnetic field and the feedback current. f For feedback current, S TMR For the sensitivity of the TMR chip, A apm V is the gain factor of the op-amp. TMR For the TMR supply voltage, Z coil The impedance is the same as that of the coil.

[0085] Further processing yielded B net and S TMR Relationship:

[0086] This relationship is used to substitute the maximum permissible residual magnetic field corresponding to the sensor target measurement accuracy as a boundary condition, and then deduce the TMR chip sensitivity threshold required to meet the accuracy requirements, thereby establishing a quantitative mapping between accuracy indicators and chip sensitivity.

[0087] 1. Sensitivity threshold The target performance indicators include at least the target measurement accuracy, and the known hardware parameters include at least the operational amplifier gain, coil impedance, and TMR supply voltage.

[0088] Step S23 above may include: Step A11: Determine the maximum allowable error of the Hall magnetic balance current sensor based on the target measurement accuracy.

[0089] Specifically, the maximum allowable error of the Hall magnetic balance current sensor can be obtained by multiplying the target measurement accuracy of the Hall magnetic balance current sensor by the full-scale current value.

[0090] Step A12: Based on the maximum error, operational amplifier gain, coil impedance and TMR supply voltage, determine the first sensitivity threshold of the TMR chip. The first sensitivity threshold enables the output signal of the TMR chip to drive the feedback coil to generate a reverse compensation magnetic field under the operational amplifier gain, so as to counteract the magnetic field generated by the primary current.

[0091] The first sensitivity threshold, also known as the first lower sensitivity limit, is the minimum sensitivity that the TMR chip must achieve to meet the circuit's driving capability requirements for the target measurement accuracy.

[0092] Specifically, the maximum allowable residual magnetic field at the air gap is determined based on the maximum error, and the maximum residual magnetic field is used as the extreme value constraint of the residual magnetic field. Substituting this into the analytical relationship between the residual magnetic field and the sensitivity of the TMR chip derived from the closed-loop zero flux principle, the minimum sensitivity value required to meet the accuracy requirements is obtained by solving the inverse relationship, thus obtaining the first sensitivity threshold. This allows the minimum detectable signal output by the TMR chip at this sensitivity to be amplified by the operational amplifier gain and drive the feedback coil to generate a sufficient reverse compensation magnetic field to counteract the magnetic field generated by the primary current.

[0093] To reliably maintain the required detection sensitivity across the entire temperature range, the initial sensitivity threshold can be compensated for using the temperature drift rate to mitigate the risk of performance degradation caused by temperature drift.

[0094] Specifically, step A12 above may include: Step A121: Based on the magnetic circuit parameters and the target range in the target performance indicators, determine the maximum magnetic field generated by the full-scale current at the air gap. The air gap is the gap in the magnetic circuit structure of the Hall magnetic balance current sensor used to place the TMR chip.

[0095] For example, based on the magnetic circuit parameters, a finite element simulation is performed, and the primary current is set to 0.04A, 0.1A, 1A and 10A respectively. The air gap magnetic induction intensity is extracted and fitted to obtain the first proportional coefficient k1=0.82mT / A. Then, this proportional coefficient is multiplied by the target range of 100A to obtain the maximum magnetic field generated by the full-scale current at the air gap as 82mT.

[0096] Step A122: Based on the closed-loop zero flux principle, determine the correspondence between the residual magnetic field at the air gap under the maximum magnetic field and the sensitivity of the TMR chip. The variables in the correspondence include the residual magnetic field and the sensitivity of the TMR chip, and the feasible region of the correspondence is constrained by the operational amplifier gain, coil impedance and TMR supply voltage.

[0097] That is, based on the closed-loop zero flux principle, the residual magnetic field is defined by the difference between the magnetic field generated by the primary current in the air gap and the compensation magnetic field generated by the feedback current in the air gap. Based on the complete signal chain transmission relationship that the output voltage of the TMR chip is equal to the product of the sensitivity, the residual magnetic field and the supply voltage, and that the voltage is amplified by the operational amplifier to drive the feedback coil to generate the compensation magnetic field, the analytical relationship between the residual magnetic field and the sensitivity of the TMR chip is derived. This relationship includes parameters such as the operational amplifier gain, the coil impedance and the TMR supply voltage.

[0098] Step A123: Determine the maximum allowable residual magnetic field at the air gap based on the maximum error, and substitute the maximum residual magnetic field as the extreme value constraint of the residual magnetic field into the corresponding relationship to calculate the initial sensitivity threshold of the TMR chip.

[0099] The initial sensitivity threshold, also known as the initial sensitivity lower limit, is the minimum critical value of the TMR chip sensitivity calculated by substituting the maximum residual magnetic field as a boundary condition into the correspondence between the residual magnetic field and the sensitivity.

[0100] The maximum error corresponding to the target measurement accuracy is used as the boundary condition for the residual magnetic field (i.e., B). net Substituting the maximum allowable value into the analytical relationship between the residual magnetic field and sensitivity derived in step A122, we can solve for the sensitivity value required to satisfy the boundary condition and obtain the initial sensitivity threshold.

[0101] Step A124: Based on the temperature drift rate of the TMR chip within its operating temperature range, compensate for the initial sensitivity threshold to obtain the first sensitivity threshold.

[0102] The maximum sensitivity attenuation can be calculated based on the temperature drift rate and maximum operating temperature difference of the TMR chip within its operating temperature range. The initial sensitivity threshold is then multiplied by a temperature compensation coefficient greater than 1 (i.e., 1 plus the product of the temperature drift rate and the maximum temperature difference) to perform upward compensation, thus obtaining the first sensitivity threshold.

[0103] For example, assuming precision = That is, the sensitivity S of the TMR chip TMR Must meet:

[0104] Assume op-amp gain A apm The impedance Z is 2500, and the coil has the same impedance. coil 70Ω, TMR supply voltage V TMR Given 1V, substituting it into the calculation and considering temperature drift (1000ppm / ℃), we obtain S. TMR-min It must be greater than 1.55mV / V / Oe.

[0105] It should be noted that the above formula is derived based on ideal conditions. In practical engineering applications, factors such as nonlinearity, zero-point bias voltage, temperature drift, aging drift, and safety factor must also be considered. Among these, the error caused by nonlinearity is significantly suppressed by the loop gain, and therefore is usually not a major limiting factor in determining the sensitivity threshold.

[0106] In addition to determining the first sensitivity threshold using the methods described above, the first sensitivity threshold can also be determined based on the sensor's rated operating frequency range and the frequency response characteristics of the TMR chip. That is, when the sensor's operating frequency increases, causing the amplitude of the TMR chip's output signal to decrease with the increase in frequency, the minimum output amplitude required to drive the feedback coil after the decrease in effective sensitivity is taken as the boundary condition. The minimum sensitivity value that can maintain closed-loop control throughout the entire operating frequency range is then derived as the first sensitivity threshold.

[0107] Step A13: Use the first sensitivity threshold as a constraint term in the TMR chip parameter constraint boundary.

[0108] In addition to the first sensitivity threshold determined based on the target measurement accuracy, a second sensitivity threshold can be determined based on the current detection threshold and in combination with the operational amplifier noise and TMR noise to ensure that the sensor can effectively distinguish between valid signals and noise under weak signal detection conditions.

[0109] The target performance indicators include at least the current detection threshold, and the known hardware parameters include at least the op-amp noise parameters and the TMR noise parameters.

[0110] Specifically, step S23 above may include: Step A21: Determine the second sensitivity threshold of the TMR chip based on the current detection threshold, the operational amplifier noise parameters, and the TMR noise parameters. The second sensitivity threshold ensures that the output signal of the TMR chip is greater than the combined noise of the operational amplifier noise and the TMR noise at the current detection threshold.

[0111] The current detection threshold, also known as the lower limit of current detection, is the smallest primary current value that a closed-loop magnetic balance sensor can effectively distinguish and measure.

[0112] The minimum magnetic field signal that the Hall magnetic balance current sensor needs to detect is determined based on the current detection threshold. At the same time, the operational amplifier noise voltage is determined based on the operational amplifier noise power spectral density and bandwidth, and the TMR magnetic noise is determined based on the TMR detection accuracy and bandwidth. The two are combined into a total noise. Then, the sensitivity value required to meet the signal-to-noise ratio requirement is derived by using the minimum magnetic field signal being greater than the total noise as the boundary condition. This value is then used as the second sensitivity threshold.

[0113] To enable the sensor to effectively distinguish between signal and noise under weak signal detection conditions, the current detection threshold can be converted into the minimum magnetic field signal. Then, the operational amplifier noise voltage and TMR magnetic noise are determined separately and synthesized into the total noise. Finally, the minimum sensitivity value that ensures the signal-to-noise ratio meets the requirements is derived by using the TMR output signal amplitude being greater than the total noise as the boundary condition. This value serves as the second sensitivity threshold.

[0114] Specifically, step A21 above may include: Step A211: Determine the minimum magnetic field signal that the Hall magnetic balance current sensor needs to detect based on the current detection threshold.

[0115] Based on the minimum measurable current value corresponding to the current detection threshold, and combined with the proportional relationship between the primary current and the air gap magnetic field determined by the magnetic circuit parameters (the first proportional coefficient), the minimum current value is multiplied by the first proportional coefficient to obtain the minimum magnetic field signal corresponding to the air gap. This magnetic field signal is the minimum physical quantity that the TMR chip needs to sense and convert into a voltage signal under the current detection threshold condition.

[0116] Step A212: Determine the op-amp noise voltage within the operating bandwidth of the corresponding op-amp component based on the op-amp noise parameters.

[0117] Based on the noise power spectral density parameter given in the op-amp datasheet, and combined with the op-amp's actual operating bandwidth, the noise power spectral density is multiplied by the square root of the bandwidth to obtain the total effective value of the op-amp component's noise voltage within the operating bandwidth. This value reflects the degree of interference of the electrical noise generated by the op-amp itself on the detection of weak signals.

[0118] Step A213: Determine the TMR magnetic noise of the TMR chip within its operating bandwidth based on the TMR noise parameters.

[0119] Based on the equivalent magnetic noise value (i.e., detection accuracy) given in the TMR chip datasheet, and combined with the actual operating bandwidth of the TMR chip, the effective magnetic noise value of the TMR chip within its operating bandwidth is obtained by multiplying the equivalent magnetic noise value by the square root of the bandwidth. This value reflects the limitation of the detection resolution caused by the magnetic noise generated by the TMR chip itself when sensing a magnetic field.

[0120] Step A214: Determine the total noise based on the op-amp noise voltage and TMR magnetic noise.

[0121] The RMS value of the operational amplifier noise voltage obtained in step A212 and the RMS value of the TMR magnetic noise obtained in step A213 are synthesized by taking the square root of the sum of their squares (i.e., the total noise is equal to the square root of the sum of the squares of the operational amplifier noise voltage and the TMR magnetic noise), to obtain the total RMS value of the system noise. This total noise represents the total noise floor level encountered by the sensor when detecting weak signals.

[0122] Step A215: Based on the minimum magnetic field signal and the total noise, determine the minimum sensitivity value required for the TMR chip to output a signal higher than the total noise when detecting the minimum magnetic field signal, and use this as the second sensitivity threshold.

[0123] The second sensitivity threshold, also known as the second lower sensitivity limit, is the minimum sensitivity that the TMR chip must achieve in order to meet the signal-to-noise ratio requirements of the current detection threshold.

[0124] The product of the minimum magnetic field signal obtained in step A211 and the TMR chip sensitivity and supply voltage is taken as the output voltage amplitude of the TMR chip under this magnetic field. Using the condition that this output voltage amplitude must be greater than the total effective noise value obtained in step A214 (i.e., signal-to-noise ratio greater than 1), the minimum sensitivity value required to satisfy this condition is derived and used as the second sensitivity threshold. This threshold ensures that, under the current detection threshold condition, the effective signal output by the TMR chip can be effectively distinguished from the background noise.

[0125] Specifically, the boundary condition is: the current detection threshold requirement of the sensor needs to consider the noise of the operational amplifier and TMR. The operational amplifier noise is:

[0126] TMR noise is:

[0127] The total noise is:

[0128] Therefore, the sensitivity S of the TMR chip TMR Must meet:

[0129] Among them, S min e is the second sensitivity threshold. n W is the noise power spectral density of the operational amplifier. apm For the op-amp bandwidth, B noise For the detection accuracy of TMR, W TMR For TMR bandwidth.

[0130] In addition to determining the second sensitivity threshold based on operational amplifier noise and TMR noise, the second sensitivity threshold can also be determined based on the sensor's rated operating frequency range and the frequency response characteristics of the TMR chip. That is, obtain the sensor's highest operating frequency and the attenuation curve of the TMR chip's sensitivity as the frequency increases at that frequency. With the attenuated effective sensitivity still allowing the TMR chip to output a signal amplitude higher than the total system noise under the minimum magnetic field signal corresponding to the current detection threshold as the boundary condition, the minimum sensitivity value that can meet the signal-to-noise ratio requirement across the entire operating frequency range can be deduced and used as the second sensitivity threshold.

[0131] Step A22: Use the second sensitivity threshold as a constraint term in the TMR chip parameter constraint boundary.

[0132] It should be noted that the first sensitivity threshold can be calculated based on the target measurement accuracy and its associated circuit parameters (including op-amp gain, coil impedance, and TMR supply voltage), or the second sensitivity threshold can be calculated based on the current detection threshold and its associated noise parameters (including op-amp noise and TMR noise). One of these can be selected as the final sensitivity threshold. Alternatively, both the first and second sensitivity thresholds can be calculated simultaneously, and the larger of the two can be used as the final sensitivity threshold, in order to balance the requirements of both circuit driving capability and weak signal detection capability.

[0133] Step A3: Take the higher sensitivity threshold between the first sensitivity threshold and the second sensitivity threshold as a constraint term in the TMR chip parameter constraint boundary.

[0134] The sensitivity threshold, also known as the lower limit of sensitivity, is the higher of the first sensitivity threshold and the second sensitivity threshold, and serves as the minimum value that the TMR chip's sensitivity must ultimately reach.

[0135] 2. Zero-point bias voltage threshold The target performance indicators include at least the target range, and the known hardware parameters include at least the maximum output voltage of the op-amp, the op-amp gain, the coil impedance, the TMR supply voltage, and the sensitivity threshold of the TMR chip.

[0136] Step S23 above may include: Step B1: Determine the maximum allowable input voltage at the input terminal of the op-amp component based on the op-amp's maximum output voltage and op-amp gain.

[0137] Specifically, you can determine the maximum input voltage that the op-amp's output can withstand by dividing the maximum output voltage swing (i.e., the maximum voltage value that the op-amp's output can reach) by the op-amp's gain setting. If the input voltage exceeds this value, the op-amp will enter the saturation region, and the output signal will be clipped and distorted, failing to drive the feedback coil correctly.

[0138] Step B2: Based on the closed-loop zero flux principle, determine the correspondence between the residual magnetic field of the TMR chip at the air gap and the sensitivity of the TMR chip.

[0139] Specifically, based on the closed-loop zero flux principle, a primary current generates a magnetic field at the air gap. The TMR chip detects this magnetic field and outputs a voltage signal. This voltage signal is amplified by an operational amplifier and drives the feedback coil to generate a reverse compensation magnetic field. Through the transmission relationship of the above complete signal chain, an analytical correspondence between the residual magnetic field at the air gap and the sensitivity of the TMR chip is established. This relationship includes parameters such as operational amplifier gain, coil impedance, TMR supply voltage, and the proportionality coefficient between the air gap magnetic field and the feedback current.

[0140] Step B3: Determine the signal voltage generated by the TMR chip at the air gap based on the correspondence, coil impedance, TMR power supply voltage, and sensitivity threshold.

[0141] Substitute the sensitivity threshold (the lowest sensitivity value determined according to accuracy or signal-to-noise ratio requirements), coil impedance, TMR supply voltage, and the proportional coefficient between the air gap magnetic field and the feedback current into the correspondence established in step B2 to calculate the signal voltage amplitude generated by the TMR chip when it is actually working at the air gap.

[0142] Step B4: Determine the zero-point bias voltage threshold of the TMR chip based on the maximum input voltage and the signal voltage, so that the sum of the signal voltage and the zero-point bias voltage does not exceed the maximum input voltage.

[0143] Zero-point bias voltage threshold, also known as the upper limit of zero-point bias voltage, is the maximum allowable zero-point bias voltage of the TMR chip to prevent the op-amp components from saturating due to excessive input signals.

[0144] Subtracting the TMR chip signal voltage obtained in step B3 from the maximum allowable input voltage at the op-amp input obtained in step B1 gives the difference, which is the maximum allowable zero-point bias voltage. This constraint ensures that the sum of the signal voltage output by the TMR chip at full-scale current and the chip's inherent zero-point bias voltage does not exceed the maximum allowable input voltage at the op-amp input, thereby preventing the op-amp from saturating due to excessive input signal.

[0145] To ensure that the sensor output signal does not saturate and distort within the full range, the target range can be converted into an air gap magnetic field based on the magnetic circuit parameters, and the full-scale signal voltage can be calculated accordingly. Then, the maximum allowable input voltage at the op-amp input terminal is subtracted from the signal voltage to obtain the strict threshold of the zero-point bias voltage.

[0146] Specifically, step B4 above may include: Step B41: Determine the maximum magnetic field generated by the full-scale current at the air gap based on the magnetic circuit parameters and the target range.

[0147] Specifically, the proportionality coefficient (first proportionality coefficient) between the primary current and the air gap magnetic field can be obtained from the magnetic circuit parameters. This proportionality coefficient is then multiplied by the target range to obtain the maximum magnetic field generated by the full-scale current at the air gap.

[0148] Step B42: Determine the signal voltage generated by the TMR chip under the residual magnetic field based on the correspondence, coil impedance, TMR power supply voltage, and sensitivity threshold.

[0149] Specifically, the maximum magnetic field can be used as the boundary value of the residual magnetic field. This value can be substituted into the correspondence between the residual magnetic field and the sensitivity of the TMR chip derived from the closed-loop zero flux principle. Combined with the coil impedance, the TMR supply voltage, and the determined sensitivity threshold, the signal voltage amplitude output by the TMR chip under the full-scale residual magnetic field can be calculated.

[0150] Step B43: Subtract the signal voltage from the maximum input voltage to obtain the zero-point bias voltage threshold.

[0151] Specifically, the maximum allowable input voltage at the op-amp input terminal can be subtracted from the signal voltage amplitude output by the TMR chip under the full-scale residual magnetic field, and the difference is used as the zero-point bias voltage threshold of the TMR chip.

[0152] In addition to using the steps described above to determine the zero-point bias voltage threshold, the zero-point bias voltage threshold can also be determined based on the reference voltage and quantization input range of the analog-to-digital converter. This involves subtracting the signal voltage amplitude of the TMR chip at full-scale current from the maximum allowable input voltage of the analog-to-digital converter, and using the difference as the zero-point bias voltage threshold. This ensures that the output signal of the TMR chip, after being amplified by the operational amplifier, falls within the effective quantization input range of the analog-to-digital converter without being truncated.

[0153] Step B5: Use the zero-point bias voltage threshold as a constraint term in the TMR chip parameter constraint boundary.

[0154] Specifically, the boundary condition is: the maximum output voltage of the op-amp:

[0155] The zero-point bias voltage V is derived. offset for:

[0156] In practical applications, assume the op-amp gain A apm The impedance Z is 2500, and the coil has the same impedance. coil 70Ω, TMR supply voltage V TMR The op-amp voltage is 1V. apm-max The voltage is 3.3V, and the sensitivity is S. TMR Given 2mV / V / Oe and k2 = 2.05T / A, the V value is calculated at 100A. offset ≤2.44mV.

[0157] 3. Linear range threshold The target performance indicators should include at least the target range, and the known hardware parameters should include at least the magnetic circuit parameters.

[0158] Step S23 above may include: Step C1: Based on the magnetic circuit parameters and the target range, determine the air gap magnetic field generated by the primary current in the air gap, and the compensation magnetic field generated by the feedback current in the air gap.

[0159] Specifically, the proportionality coefficient (first proportionality coefficient) between the primary current and the air gap magnetic field can be obtained based on the magnetic circuit parameters. This proportionality coefficient is then multiplied by the target range to obtain the air gap magnetic field value generated by the rated primary current at the air gap. Simultaneously, the proportionality coefficient (second proportionality coefficient) between the feedback current and the air gap magnetic field can be obtained based on the magnetic circuit parameters. This proportionality coefficient is then multiplied by the rated feedback current to obtain the compensation magnetic field value generated by the feedback current at the air gap.

[0160] Step C2: Based on the high magnetic field in the air gap magnetic field and the compensation magnetic field and the preset safety factor, determine the linear range threshold of the TMR chip so that the TMR chip will not saturate due to the instantaneous magnetic field impact when the current changes suddenly.

[0161] The linear range threshold, also known as the lower limit of the linear range, is the minimum value that the linear range of the TMR chip must reach in order to prevent the TMR chip from saturating due to the instantaneous magnetic field impact when the current changes abruptly.

[0162] Specifically, the magnitudes of the air gap magnetic field and the compensation magnetic field can be compared, and the larger value can be taken. Then, the larger value is multiplied by a preset safety factor, and the product is used as the threshold of the linear range of the TMR chip. This ensures that the instantaneous peak magnetic field at the air gap does not exceed the linear operating range of the TMR chip when there is a sudden change in current or overload, thus preventing the chip from entering the saturation region.

[0163] To ensure that the chip does not saturate due to instantaneous strong magnetic field impact during sudden current changes or overloads, a safety factor can be used to amplify the high magnetic field in the air gap magnetic field and the compensation magnetic field, and the resulting peak value can be used as the linear range threshold.

[0164] Specifically, step C2 above may include: Step C21: Amplify the high magnetic field in the air gap magnetic field and the compensation magnetic field according to the safety factor to obtain the peak magnetic field that may appear at the air gap when the current changes abruptly.

[0165] Compare the magnitudes of the air gap magnetic field and the compensation magnetic field, and take the larger of the two. Considering that the primary current may experience a momentary overshoot of several times (such as twice the rated current) when the current changes suddenly or is overloaded, and that the feedback current has not yet been established or cannot be tracked in time, the actual magnetic field at the air gap is the larger of the two multiplied by the preset safety factor, thus obtaining the peak magnetic field that may occur at the air gap when the current changes suddenly.

[0166] Step C22: Use the peak magnetic field as the linear range threshold of the TMR chip.

[0167] The peak magnetic field value obtained after amplification is determined as the threshold of the linear range of the TMR chip. That is, the linear operating range of the TMR chip is required to cover at least the range from zero to the peak magnetic field, ensuring that the chip still works in the linear region under transient shocks, and avoiding closed-loop system oscillation or response distortion due to saturation.

[0168] In addition to determining the linear range threshold using the steps described above, it can also be determined based on the maximum fault current multiple the sensor may withstand and a safety factor. This involves multiplying the rated range by the maximum fault current multiple, converting this to an equivalent air gap magnetic field, and then multiplying the result by the safety factor. The product is then used as the linear range threshold. This ensures that the TMR chip remains unsaturated even under the most severe fault current impact, making it particularly suitable for applications requiring high transient overload capacity, such as short-circuit protection.

[0169] Step C3: Use the linear range threshold as a constraint term in the TMR chip parameter constraint boundary.

[0170] Specifically, the boundary condition is: above the maximum value of the residual magnetic field, i.e.

[0171] Assume op-amp gain A apm The impedance Z is 2500, and the coil has the same impedance. coil 70Ω, TMR supply voltage V TMR 1V, sensitivity S TMR Given 2mV / V / Oe, k2 is 2.05T / A, and the safety factor is 2, then X is obtained. TMR >1.12Oe.

[0172] To ensure that the TMR does not enter the saturation region under any circumstances, its linear range should at least cover the absolute value of the maximum possible residual magnetic field:

[0173] Among them, B p,max and B f,max These represent the maximum magnetic fields generated by the primary current and the feedback current in the air gap, respectively. The worst-case scenario is the magnetic field generated by the primary current (open-loop magnetic field) multiplied by the safety factor. Therefore, a linear range ≥ 2.84 mT = 164 mT is generally recommended.

[0174] 4. Nonlinearity threshold The target performance indicators include at least the target measurement accuracy, and the known hardware parameters include at least the operational amplifier gain, coil impedance, TMR supply voltage, magnetic circuit parameters, and the sensitivity threshold of the TMR chip.

[0175] Step S23 above may include: Step D1: Determine the loop gain of the Hall magnetic balance current sensor based on the operational amplifier gain, sensitivity threshold, proportionality coefficient between the air gap magnetic field and the feedback current, coil impedance, and TMR supply voltage.

[0176] Specifically, based on the closed-loop zero flux principle, the loop gain of the Hall magnetic balance current sensor can be calculated using the mathematical relationships between the operational amplifier gain, sensitivity threshold, the proportionality coefficient between the air gap magnetic field and the feedback current, the TMR supply voltage, and the coil impedance. This loop gain reflects the sensor's ability to suppress TMR chip errors (including nonlinear errors); the larger the loop gain, the stronger the suppression effect on nonlinear errors.

[0177] Step D2: Based on the target measurement accuracy and loop gain, determine the allowable nonlinearity threshold of the TMR chip so that the nonlinearity error of the TMR chip meets the target measurement accuracy after being suppressed by the loop gain.

[0178] The nonlinearity threshold, also known as the upper limit of nonlinearity, is the maximum allowable nonlinearity of the TMR chip so that the nonlinearity error of the TMR chip can meet the target measurement accuracy after being suppressed by the loop gain.

[0179] Based on the target measurement accuracy and the determined loop gain, the maximum nonlinear error allowed by the TMR chip is calculated by considering the error propagation relationship from the nonlinear error to the sensor output after being suppressed by the loop gain. Then, this maximum nonlinear error is divided by the full-scale output signal of the TMR chip to obtain the nonlinearity threshold allowed by the TMR chip. Under this nonlinearity threshold condition, the nonlinear error of the TMR chip can still meet the target measurement accuracy requirements of the sensor after being suppressed by the loop gain.

[0180] To ensure that the nonlinear error of the TMR chip itself does not exceed the target measurement accuracy requirements of the sensor after being suppressed by closed-loop feedback, a nonlinear error propagation relationship can be established based on the closed-loop zero flux principle. The maximum total error corresponding to the target measurement accuracy is used as a boundary condition and substituted into this relationship to deduce the maximum nonlinear error allowed by the chip. The ratio of this error to the full-scale output signal is then used as the nonlinearity threshold.

[0181] Specifically, step D2 above may include: Step D21: Based on the closed-loop zero flux principle, establish the error propagation relationship between the nonlinear error of the TMR chip and the output of the Hall magnetic balance current sensor after being suppressed by the loop gain.

[0182] Specifically, based on the closed-loop zero flux principle, the nonlinear error of the TMR chip can be regarded as an error voltage superimposed on the ideal output voltage. This error voltage is transmitted to the final output of the sensor after being suppressed by the negative feedback of the loop gain, thereby establishing the transmission relationship of nonlinear error from the TMR chip to the sensor output. In this transmission relationship, the larger the loop gain, the smaller the nonlinear error transmitted to the output.

[0183] Step D22: Determine the maximum allowable total error of the Hall magnetic balance current sensor based on the target measurement accuracy.

[0184] That is, the product of the target measurement accuracy level and the full-scale output value of the sensor is taken as the maximum allowable total error of the Hall magnetic balance current sensor.

[0185] Step D23: Substitute the maximum total error as a boundary condition into the error propagation relationship to calculate the maximum nonlinear error allowed by the TMR chip.

[0186] That is, the maximum total error is taken as the maximum allowable nonlinear error contribution at the sensor output, and substituted into the error propagation relationship established in step D21 to solve for the maximum allowable nonlinear error voltage value of the TMR chip itself.

[0187] Step D24: Determine the nonlinearity threshold based on the ratio of the maximum nonlinearity error to the full-scale output signal of the TMR chip.

[0188] Specifically, the maximum permissible nonlinear error voltage of the TMR chip obtained by reverse calculation is divided by the full-scale output signal voltage of the TMR chip, and the resulting ratio is the permissible nonlinearity threshold of the TMR chip.

[0189] In addition to determining the nonlinearity threshold using the steps described above, it can also be determined based on the sensor's total harmonic distortion (THD) index. Specifically, the maximum allowable THD value of the sensor is determined according to the target measurement accuracy requirements. Then, based on the analytical mapping relationship between the TMR chip's nonlinearity and the sensor's THD, the maximum allowable THD of the TMR chip required to meet the THD requirement is deduced, and this value is used as the nonlinearity threshold. This directly ensures the sensor's measurement accuracy in non-sinusoidal waveform measurements (such as harmonic analysis and variable frequency drive current detection, which contain rich harmonic components), rather than constraining only the fundamental or DC components. This improves the sensor's harmonic measurement accuracy under nonlinear loads or complex waveform conditions.

[0190] Step D3: Use the nonlinearity threshold as a constraint term in the TMR chip parameter constraint boundary.

[0191] Specifically, the boundary condition is: meeting the accuracy requirements. The theoretical derivations of sensitivity, zero-point bias voltage, etc., above are all based on ideal conditions. Next, introducing a nonlinearity factor, we obtain:

[0192] Among them, V t (B) is the output voltage of the TMR, and ε(B) is the nonlinear error voltage, satisfying |ε(B)|≤L TMR S TMR B max V TMR B max =k p I p,max B is the air gap magnetic field corresponding to the full-scale current, and B is the magnetic field actually felt by the TMR chip at the air gap.

[0193] Further defining the loop gain G yields:

[0194] Where G is the loop gain of the Hall magnetic balance current sensor, and V a V is the output voltage of the TMR. t B is the output voltage of the TMR after being amplified by the operational amplifier. p and B f Let A represent the magnetic fields generated in the air gap by the primary current and the feedback current, respectively. Let k2 be the second proportionality coefficient between the air gap magnetic field and the feedback current. apm V is the gain factor of the op-amp. TMR For the TMR supply voltage, Z coil The impedance is the same as that of the coil.

[0195] The nonlinear error propagation process will be derived in detail below: First, the basic equations for the closed loop are given:

[0196] Formula V t (B) Substituting the sum G into equation B net The result was:

[0197] The results were:

[0198] Further, the expression for the output voltage is obtained:

[0199] The ideal voltage output V, which does not contain nonlinearity 0,ideal for:

[0200] Therefore, the relative error is:

[0201] in,

[0202]

[0203] Substituting into the equation for relative error, we get:

[0204] Further derivation yields the requirement for nonlinearity:

[0205] Among them, L TMR V represents the nonlinearity of TMR, G is the loop gain of the Hall magnetic balance current sensor, and V... a V is the output voltage of the TMR. t R is the output voltage of the TMR after being amplified by the operational amplifier. s V0 is the sampling resistor, ε(B) is the output voltage of the Hall magnetic balance current sensor, and ε(B) is the sampling resistor. net ) represents the nonlinear error voltage, B p and B f Let A represent the magnetic fields generated in the air gap by the primary current and the feedback current, respectively. Let k2 be the second proportionality coefficient between the air gap magnetic field and the feedback current. apm V is the gain factor of the op-amp. TMR For the TMR supply voltage, Z coil For coils with equal impedance, B n That is, B net ΔV o This refers to the output voltage deviation caused by nonlinear error.

[0206] Here, we can assume that the op-amp gain A apm The impedance Z is 2500, and the coil has the same impedance. coil 70Ω, TMR supply voltage V TMR 1V, sensitivity S TMR Substituting 2mV / V / Oe into the derived formula, we obtain the allowable nonlinearity L of TMR. TMR ≤146.5%.

[0207] At this point, the TMR chip parameter constraint boundaries include at least the sensitivity threshold, zero-point bias voltage threshold, linear range threshold, and nonlinearity threshold. Next, based on this set of constraint boundaries, the corresponding parameters in the candidate TMR chip product manual are compared item by item to select the chip models that simultaneously meet all their respective constraint boundaries, and these are taken as the target TMR chips.

[0208] S24: Based on the calculated TMR chip parameter constraint boundary, select target TMR chips from the current TMR chip products that meet the calculated TMR chip parameter constraint boundary.

[0209] S25: Using the target TMR chip, a Hall magnetic balance current sensor is constructed according to the hardware parameters.

[0210] Steps S24 and S25 here are implemented in the same way as steps S13 and S14 in the previous embodiments. Please refer to the relevant descriptions in the previous embodiments, which will not be repeated here.

[0211] This concludes the description of the construction method for the Hall magnetic balance current sensor provided in this application embodiment.

[0212] Based on the same inventive concept, this application also provides a device for constructing a Hall magnetic balance current sensor.

[0213] Figure 3 This is a schematic diagram of the structure of the Hall magnetic balance current sensor construction device in the embodiments of this application. Figure 1 See Figure 3 As shown, the device may include: The acquisition module 31 is used to acquire the known hardware parameters and target performance indicators of the Hall magnetic balance current sensor to be constructed.

[0214] The calculation module 32 is used to calculate the parameter constraint boundary of the tunneling magnetoresistive effect TMR chip based on the closed-loop zero flux principle, according to the known hardware parameters and target performance indicators.

[0215] The filtering module 33 is used to filter target TMR chips that meet the calculated TMR chip parameter constraint boundaries from the current TMR chip products based on the calculated TMR chip parameter constraint boundaries.

[0216] Module 34 is used to construct a Hall magnetic balance current sensor using the target TMR chip according to the hardware parameters.

[0217] Furthermore, as a response to Figure 3 In a refinement and extension of the illustrated device, this application embodiment also provides a construction apparatus for a Hall magnetic balance current sensor.

[0218] Figure 4 This is a schematic diagram of the structure of the Hall magnetic balance current sensor construction device in the embodiments of this application. Figure 2 See Figure 4 As shown, the device may include: The acquisition module 41 is used to acquire the known hardware parameters and target performance indicators of the Hall magnetic balance current sensor to be constructed.

[0219] Given known hardware parameters, including magnetic circuit parameters, simulation module 42 is used to acquire the magnetic circuit parameters of the Hall magnetic balance current sensor; finite element simulation is performed based on the magnetic circuit parameters to acquire a first proportionality coefficient characterizing the ratio of the magnetic field generated by the primary current at the air gap to the primary current, and a second proportionality coefficient characterizing the ratio of the feedback current to the magnetic induction intensity of the air gap; wherein, the first proportionality coefficient is used to convert the range requirement in the target performance index into the magnetic field value at the air gap, so as to determine the working magnetic field range of the TMR chip at the air gap based on the known hardware parameters, and the second proportionality coefficient is used to convert the output signal of the TMR chip into the reverse compensation magnetic field at the air gap through the known hardware parameters, so as to participate in the calculation of the parameter constraint boundary of the TMR chip.

[0220] The calculation module 43 is used to calculate the parameter constraint boundary of the tunneling magnetoresistive effect TMR chip based on the closed-loop zero flux principle, according to the known hardware parameters, target performance indicators, first proportional coefficient and second proportional coefficient.

[0221] The calculation module 43 includes a first calculation unit 431, a second calculation unit 32, a third calculation unit 433, and a fourth calculation unit 434.

[0222] Given that the target performance indicators include at least the target measurement accuracy, and the known hardware parameters include at least the operational amplifier gain, coil impedance, and TMR supply voltage, the first calculation unit 431 is used to determine the maximum allowable error of the Hall magnetic balance current sensor based on the target measurement accuracy; and to determine the first sensitivity threshold of the TMR chip based on the maximum error, operational amplifier gain, coil impedance, and TMR supply voltage. The first sensitivity threshold enables the output signal of the TMR chip to drive the feedback coil to generate a reverse compensation magnetic field under the operational amplifier gain, so as to cancel the magnetic field generated by the primary current; and to use the first sensitivity threshold as a constraint term in the parameter constraint boundary of the TMR chip.

[0223] Given that the known hardware parameters also include magnetic circuit parameters, and the target performance indicators also include the target range, the first calculation unit 431 is specifically used to determine the maximum magnetic field generated by the full-scale current at the air gap based on the magnetic circuit parameters and the target range. The air gap is the gap in the magnetic circuit structure of the Hall magnetic balance current sensor used to place the TMR chip. Based on the closed-loop zero flux principle, the corresponding relationship between the residual magnetic field at the air gap under the maximum magnetic field and the sensitivity of the TMR chip is determined. The variables in the corresponding relationship include the residual magnetic field and the sensitivity of the TMR chip, and the feasible region of the corresponding relationship is constrained by the operational amplifier gain, coil impedance, and TMR supply voltage. Based on the maximum error, the maximum allowable residual magnetic field at the air gap is determined, and the maximum residual magnetic field is used as the extreme value constraint of the residual magnetic field and substituted into the corresponding relationship to calculate the initial sensitivity threshold of the TMR chip. Based on the temperature drift rate of the TMR chip within the operating temperature range, the initial sensitivity threshold is compensated to obtain the first sensitivity threshold.

[0224] Given that the target performance indicators include at least the current detection threshold and the known hardware parameters include at least the operational amplifier noise parameters and the TMR noise parameters, the first calculation unit 431 is used to determine a second sensitivity threshold for the TMR chip based on the current detection threshold, the operational amplifier noise parameters, and the TMR noise parameters. The second sensitivity threshold enables the output signal of the TMR chip to be greater than the combined noise of the operational amplifier noise and the TMR noise at the current detection threshold. The second sensitivity threshold is used as a constraint term in the parameter constraint boundary of the TMR chip.

[0225] The first calculation unit 431 is specifically used to determine the minimum magnetic field signal that the Hall magnetic balance current sensor needs to detect based on the current detection threshold; determine the operational amplifier noise voltage of the corresponding operational amplifier component within the operating bandwidth based on the operational amplifier noise parameters; determine the TMR magnetic noise of the TMR chip within the operating bandwidth based on the TMR noise parameters; determine the total noise based on the operational amplifier noise voltage and the TMR magnetic noise; and determine the minimum sensitivity value required for the TMR chip to detect the minimum magnetic field signal when its output signal is higher than the total noise based on the minimum magnetic field signal and the total noise, which is used as the second sensitivity threshold.

[0226] The first calculation unit 431 is also used to take the higher sensitivity threshold between the first sensitivity threshold and the second sensitivity threshold as a constraint term in the TMR chip parameter constraint boundary.

[0227] Given that the target performance indicators include at least the target range, and the known hardware parameters include at least the operational amplifier's maximum output voltage, operational amplifier gain, coil impedance, TMR supply voltage, and the TMR chip's sensitivity threshold, the second calculation unit 432 is used to determine the maximum allowable input voltage at the operational amplifier component's input terminal based on the operational amplifier's maximum output voltage and operational amplifier gain; determine the correspondence between the residual magnetic field of the TMR chip at the air gap and the TMR chip's sensitivity based on the closed-loop zero flux principle; determine the signal voltage generated by the TMR chip at the air gap based on the correspondence, coil impedance, TMR supply voltage, and sensitivity threshold; determine the zero-point bias voltage threshold of the TMR chip based on the maximum input voltage and signal voltage, such that the sum of the signal voltage and the zero-point bias voltage does not exceed the maximum input voltage; and use the zero-point bias voltage threshold as a constraint term in the TMR chip parameter constraint boundary.

[0228] Given that the hardware parameters also include magnetic circuit parameters, the second calculation unit 432 is specifically used to determine the maximum magnetic field generated by the full-scale current at the air gap based on the magnetic circuit parameters and the target range; to determine the signal voltage generated by the TMR chip under the residual magnetic field based on the correspondence, coil impedance, TMR power supply voltage and sensitivity threshold; and to obtain the zero-point bias voltage threshold by subtracting the signal voltage from the maximum input voltage.

[0229] Given that the target performance indicators include at least the target range and the known hardware parameters include at least the magnetic circuit parameters, the third calculation unit 433 is used to determine the air gap magnetic field generated by the primary current at the air gap and the compensation magnetic field generated by the feedback current at the air gap based on the magnetic circuit parameters and the target range; based on the higher magnetic field in the air gap magnetic field and the compensation magnetic field and the preset safety factor, the linear range threshold of the TMR chip is determined so that the TMR chip does not saturate due to the instantaneous magnetic field impact when the current changes abruptly; the linear range threshold is used as a constraint term in the parameter constraint boundary of the TMR chip.

[0230] The third calculation unit 433 is specifically used to amplify the high magnetic field in the air gap magnetic field and the compensation magnetic field according to the safety factor, so as to obtain the peak magnetic field that may appear at the air gap when the current changes suddenly; and to use the peak magnetic field as the linear range threshold of the TMR chip.

[0231] Given that the target performance indicators include at least the target measurement accuracy, and the known hardware parameters include at least the operational amplifier gain, coil impedance, TMR supply voltage, magnetic circuit parameters, and the sensitivity threshold of the TMR chip, the fourth calculation unit 434 is used to determine the loop gain of the Hall magnetic balance current sensor based on the operational amplifier gain, sensitivity threshold, proportionality coefficient between the air gap magnetic field and the feedback current, coil impedance, and TMR supply voltage; determine the allowable nonlinearity threshold of the TMR chip based on the target measurement accuracy and loop gain, so that the nonlinearity error of the TMR chip meets the target measurement accuracy after being suppressed by the loop gain; and use the nonlinearity threshold as a constraint term in the parameter constraint boundary of the TMR chip.

[0232] The fourth calculation unit 434 is specifically used to establish the error propagation relationship of the nonlinear error of the TMR chip after being suppressed by the loop gain and then transmitted to the output of the Hall magnetic balance current sensor, based on the closed-loop zero flux principle; determine the maximum allowable total error of the Hall magnetic balance current sensor according to the target measurement accuracy; substitute the maximum total error as a boundary condition into the error propagation relationship to calculate the maximum allowable nonlinear error of the TMR chip; and determine the nonlinearity threshold according to the ratio of the maximum nonlinear error to the full-scale output signal of the TMR chip.

[0233] The filtering module 44 is used to filter target TMR chips that meet the calculated TMR chip parameter constraint boundaries from the current TMR chip products based on the calculated TMR chip parameter constraint boundaries. Module 45 is used to construct a Hall magnetic balance current sensor according to the hardware parameters using the target TMR chip.

[0234] It should be noted that the descriptions of the above device embodiments are similar to those of the above method embodiments, and have similar beneficial effects. For technical details not disclosed in the device embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0235] Based on the same inventive concept, this application also provides a computer device.

[0236] Figure 5 This is a schematic diagram of the structure of the computer device in an embodiment of this application. See also... Figure 5 As shown, the computer device may include: a memory 51, a processor 52, and a computer program stored on the memory 51, wherein the processor 52 executes the computer program to implement the methods described in the foregoing embodiments.

[0237] It should be noted that the description of the above computer device embodiments is similar to the description of the above method embodiments, and has similar beneficial effects. For technical details not disclosed in the computer device embodiments of this application, please refer to the description of the method embodiments of this application for understanding.

[0238] Based on the same inventive concept, embodiments of this application also provide a computer-readable storage medium. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the methods described in the foregoing embodiments.

[0239] It should be noted that the description of the above computer-readable storage medium embodiments is similar to the description of the above method embodiments, and has similar beneficial effects. For technical details not disclosed in the computer-readable storage medium embodiments of this application, please refer to the description of the method embodiments of this application for understanding.

[0240] Based on the same inventive concept, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the methods described in the foregoing embodiments.

[0241] It should be noted that the descriptions of the above computer program product embodiments are similar to those of the above method embodiments, and have similar beneficial effects. For technical details not disclosed in the computer program product embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0242] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for constructing a Hall magnetic balance current sensor, characterized in that, The method includes: Obtain the known hardware parameters and target performance indicators of the Hall magnetic balance current sensor to be constructed; Based on the closed-loop zero flux principle, the parameter constraint boundary of the tunneling magnetoresistance effect (TMR) chip is calculated according to the known hardware parameters and the target performance index. Based on the calculated TMR chip parameter constraint boundaries, target TMR chips that meet the calculated TMR chip parameter constraint boundaries are selected from the current TMR chip products. Using the target TMR chip, the Hall magnetic balance current sensor is constructed according to the hardware parameters.

2. The method according to claim 1, characterized in that, The target performance indicators include at least the target measurement accuracy, and the known hardware parameters include at least the operational amplifier gain, coil impedance, and TMR supply voltage; the calculation of the tunneling magnetoresistance effect TMR chip parameter constraint boundaries based on the closed-loop zero flux principle, according to the known hardware parameters and the target performance indicators, includes: The maximum allowable error of the Hall magnetic balance current sensor is determined based on the target measurement accuracy. Based on the maximum error, the operational amplifier gain, the coil impedance, and the TMR supply voltage, a first sensitivity threshold for the TMR chip is determined. The first sensitivity threshold enables the output signal of the TMR chip to drive the feedback coil to generate a reverse compensation magnetic field under the operational amplifier gain, so as to counteract the magnetic field generated by the primary current. The first sensitivity threshold is used as a constraint term in the parameter constraint boundary of the TMR chip.

3. The method according to claim 2, characterized in that, The known hardware parameters also include magnetic circuit parameters, and the target performance indicators also include the target range; the maximum allowable error of the Hall magnetic balance current sensor is determined based on the target measurement accuracy. Based on the maximum error, the operational amplifier gain, the coil impedance, and the TMR supply voltage, a first sensitivity threshold for the TMR chip is determined, including: Based on the magnetic circuit parameters and the target range, the maximum magnetic field generated by the full-scale current at the air gap is determined. The air gap is the gap in the magnetic circuit structure of the Hall magnetic balance current sensor used to place the TMR chip. Based on the closed-loop zero flux principle, the correspondence between the residual magnetic field at the air gap under the maximum magnetic field and the sensitivity of the TMR chip is determined. The variables in the correspondence include the residual magnetic field and the sensitivity of the TMR chip, and the feasible region of the correspondence is constrained by the operational amplifier gain, the coil impedance and the TMR supply voltage. The maximum allowable residual magnetic field at the air gap is determined based on the maximum error, and the maximum residual magnetic field is used as the extreme value constraint of the residual magnetic field and substituted into the corresponding relationship to calculate the initial sensitivity threshold of the TMR chip. The initial sensitivity threshold is compensated based on the temperature drift rate of the TMR chip within its operating temperature range to obtain the first sensitivity threshold.

4. The method according to claim 1, characterized in that, The target performance index includes at least a current detection threshold, and the known hardware parameters include at least operational amplifier noise parameters and TMR noise parameters; The calculation of the parameter constraint boundary of the tunneling magnetoresistance effect (TMR) chip based on the closed-loop zero flux principle, according to the known hardware parameters and the target performance indicators, includes: Based on the current detection threshold, the operational amplifier noise parameter, and the TMR noise parameter, a second sensitivity threshold for the TMR chip is determined. The second sensitivity threshold enables the output signal of the TMR chip to be greater than the combined noise of the operational amplifier noise and the TMR noise at the current detection threshold. The second sensitivity threshold is used as a constraint term in the constraint boundary of the TMR chip parameters.

5. The method according to claim 4, characterized in that, The step of determining the second sensitivity threshold of the TMR chip based on the current detection threshold, the operational amplifier noise parameters, and the TMR noise parameters includes: Based on the current detection threshold, determine the minimum magnetic field signal that the Hall magnetic balance current sensor needs to detect; Based on the operational amplifier noise parameters, determine the operational amplifier noise voltage of the corresponding operational amplifier component within the operating bandwidth; Based on the TMR noise parameters, determine the TMR magnetic noise of the TMR chip within its operating bandwidth; The total noise is determined based on the operational amplifier noise voltage and the TMR magnetic noise; Based on the minimum magnetic field signal and the total noise, the minimum sensitivity value required for the TMR chip to output a signal higher than the total noise when detecting the minimum magnetic field signal is determined, which is used as the second sensitivity threshold.

6. The method according to claim 1, characterized in that, The target performance indicators include target measurement accuracy and current detection threshold; the known hardware parameters include operational amplifier gain, coil impedance, TMR supply voltage, operational amplifier noise parameters, and TMR noise parameters; the method further includes: The maximum allowable error of the Hall magnetic balance current sensor is determined based on the target measurement accuracy. Based on the maximum error, the operational amplifier gain, the coil impedance, and the TMR supply voltage, a first sensitivity threshold for the TMR chip is determined. The first sensitivity threshold enables the output signal of the TMR chip to drive the feedback coil to generate a reverse compensation magnetic field under the operational amplifier gain, so as to counteract the magnetic field generated by the primary current. Based on the current detection threshold, the operational amplifier noise parameter, and the TMR noise parameter, a second sensitivity threshold for the TMR chip is determined. The second sensitivity threshold enables the output signal of the TMR chip to be greater than the combined noise of the operational amplifier noise and the TMR noise at the current detection threshold. The higher sensitivity threshold between the first sensitivity threshold and the second sensitivity threshold is used as a constraint term in the TMR chip parameter constraint boundary.

7. The method according to claim 1, characterized in that, The target performance indicators include at least the target range, and the known hardware parameters include at least the operational amplifier maximum output voltage, operational amplifier gain, coil impedance, TMR supply voltage, and the sensitivity threshold of the TMR chip. The calculation of the parameter constraint boundary of the tunneling magnetoresistance effect (TMR) chip based on the closed-loop zero flux principle, according to the known hardware parameters and the target performance indicators, includes: The maximum allowable input voltage at the input terminal of the operational amplifier component is determined based on the maximum output voltage and the gain of the operational amplifier. Based on the closed-loop zero flux principle, the correspondence between the residual magnetic field of the TMR chip at the air gap and the sensitivity of the TMR chip is determined. Based on the correspondence, the coil impedance, the TMR power supply voltage, and the sensitivity threshold, the signal voltage generated by the TMR chip at the air gap is determined. Based on the maximum input voltage and the signal voltage, determine the zero-point bias voltage threshold of the TMR chip, such that the sum of the signal voltage and the zero-point bias voltage does not exceed the maximum input voltage; The zero-point bias voltage threshold is used as a constraint term in the parameter constraint boundary of the TMR chip.

8. The method according to claim 7, characterized in that, The known hardware parameters also include magnetic circuit parameters; determining the zero-point bias voltage threshold of the TMR chip based on the maximum input voltage and the signal voltage includes: Based on the magnetic circuit parameters and the target range, determine the maximum magnetic field generated by the full-scale current at the air gap; Based on the correspondence, the coil impedance, the TMR power supply voltage, and the sensitivity threshold, the signal voltage generated by the TMR chip under the residual magnetic field is determined. The zero-point bias voltage threshold is obtained by subtracting the signal voltage from the maximum input voltage.

9. The method according to claim 1, characterized in that, The target performance index includes at least the target range, and the known hardware parameters include at least the magnetic circuit parameters; the calculation of the tunneling magnetoresistance effect (TMR) chip parameter constraint boundaries based on the closed-loop zero flux principle, according to the known hardware parameters and the target performance index, includes: Based on the magnetic circuit parameters and the target range, determine the air gap magnetic field generated by the primary current in the air gap, and the compensation magnetic field generated by the feedback current in the air gap. Based on the high magnetic field in the air gap magnetic field and the compensation magnetic field and the preset safety factor, the linear range threshold of the TMR chip is determined so that the TMR chip does not saturate due to the instantaneous magnetic field impact when the current changes suddenly. The linear range threshold is used as a constraint term in the TMR chip parameter constraint boundary.

10. The method according to claim 9, characterized in that, The step of determining the linear range threshold of the TMR chip based on the higher magnetic field in the air gap magnetic field and the compensation magnetic field and a preset safety factor includes: Based on the safety factor, the higher magnetic field in the air gap magnetic field and the compensation magnetic field is amplified to obtain the peak magnetic field that may appear at the air gap when the current changes abruptly. The peak magnetic field is used as the linear range threshold of the TMR chip.

11. The method according to claim 1, characterized in that, The target performance index includes at least the target measurement accuracy, and the known hardware parameters include at least the operational amplifier gain, coil impedance, TMR supply voltage, magnetic circuit parameters, and the sensitivity threshold of the TMR chip; the calculation of the tunneling magnetoresistance effect TMR chip parameter constraint boundaries based on the closed-loop zero flux principle, according to the known hardware parameters and the target performance index, includes: The loop gain of the Hall magnetic balance current sensor is determined based on the operational amplifier gain, the sensitivity threshold, the proportionality coefficient between the air gap magnetic field and the feedback current, the coil impedance, and the TMR supply voltage. Based on the target measurement accuracy and the loop gain, the allowable nonlinearity threshold of the TMR chip is determined, so that the nonlinearity error of the TMR chip, after being suppressed by the loop gain, meets the target measurement accuracy. The nonlinearity threshold is used as a constraint term in the parameter constraint boundary of the TMR chip.

12. The method according to claim 11, characterized in that, The step of determining the permissible nonlinearity threshold of the TMR chip based on the target measurement accuracy and the loop gain includes: Based on the closed-loop zero flux principle, an error propagation relationship is established between the nonlinear error of the TMR chip and the output of the Hall magnetic balance current sensor after the loop gain is suppressed. The maximum allowable total error of the Hall magnetic balance current sensor is determined based on the target measurement accuracy. Substitute the maximum total error as a boundary condition into the error propagation relationship to calculate the maximum nonlinear error allowed by the TMR chip. The nonlinearity threshold is determined based on the ratio of the maximum nonlinearity error to the full-scale output signal of the TMR chip.

13. The method according to any one of claims 1 to 12, characterized in that, The known hardware parameters include magnetic circuit parameters; before calculating the constraint boundary of the tunneling magnetoresistance effect (TMR) chip parameters based on the closed-loop zero flux principle, according to the known hardware parameters and the target performance index, the method further includes: Obtain the magnetic circuit parameters of the Hall magnetic balance current sensor; Finite element simulation is performed based on the magnetic circuit parameters to obtain a first proportionality coefficient to characterize the ratio of the magnetic field generated by the primary current in the air gap to the primary current, and a second proportionality coefficient to characterize the ratio of the feedback current to the air gap magnetic induction intensity. The calculation of the parameter constraint boundary of the tunneling magnetoresistance effect (TMR) chip based on the closed-loop zero flux principle, according to the known hardware parameters and the target performance indicators, includes: Based on the closed-loop zero flux principle, the parameter constraint boundary of the tunneling magnetoresistive effect (TMR) chip is calculated according to the known hardware parameters, the target performance index, the first proportional coefficient, and the second proportional coefficient.

14. A device for constructing a Hall magnetic balance current sensor, characterized in that, The device includes: The acquisition module is used to acquire the known hardware parameters and target performance indicators of the Hall magnetic balance current sensor to be constructed. The calculation module is used to calculate the parameter constraint boundary of the tunneling magnetoresistance effect (TMR) chip based on the closed-loop zero flux principle, according to the known hardware parameters and the target performance index. The filtering module is used to filter target TMR chips that meet the calculated TMR chip parameter constraint boundaries from the current TMR chip products based on the calculated TMR chip parameter constraint boundaries. A construction module is used to construct the Hall magnetic balance current sensor according to the target TMR chip and the hardware parameters.

15. A computer device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 13.

16. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 13.

17. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 13.

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