Temperature drift dynamic compensation system and method of Hall current sensor

Abstract

The invention discloses a temperature drift dynamic compensation system and method for a Hall current sensor. The system comprises a thermistor assembly, a power supply module, an analog-to-digital conversion module, a processor module and a compensation algorithm module. The thermistor is directly coupled to the surface of the Hall element, and an improved Kalman filtering algorithm is combined, so that dynamic compensation in a wide temperature range is realized. According to the invention, the measurement precision and stability can be significantly improved, the hardware complexity and cost are reduced, the temperature drift and nonlinearity influence of other elements is reduced, and the method is suitable for a high-precision current detection scene.

Description

Technical Field

[0001] This invention belongs to the field of sensor technology, and in particular relates to a temperature drift dynamic compensation system and method for a Hall current sensor. Background Technology

[0002] Hall effect current sensors, as widely used current sensing devices, are susceptible to temperature variations in measurement accuracy. Currently, commercially available Hall effect current sensors typically lack temperature compensation. To minimize the drift of current measurements with temperature, manufacturers often choose Hall elements with low temperature drift coefficients. However, these sensors are more expensive, increasing the overall system cost.

[0003] Some measurement systems attempt to improve this problem by adding external temperature compensation circuitry. Specifically, this method measures the ambient temperature around the Hall sensor and outputs a compensation signal to compensate for the sensor signal. However, this approach has certain limitations. For example, the measured temperature cannot accurately reflect the true temperature of the Hall element, and the hardware circuit design is relatively complex and lacks software optimization, making the final measurement value susceptible to environmental interference.

[0004] Among the known technical solutions, some studies have proposed improvement measures. For example, by measuring the ambient temperature of the Hall sensor and compensating for the sensor signal with an output voltage signal based on the temperature and the sensor's temperature drift coefficient. However, these existing technologies still have the following shortcomings: (1) When the Hall sensor signal is compensated by outputting a voltage signal through a hardware compensation circuit, the additional hardware circuit will increase the complexity of the system. At the same time, the temperature drift and nonlinear characteristics of other components may reduce the compensation effect, which will lead to increased cost and decreased stability.

[0005] (2) The temperature drift coefficient of Hall elements has a large dispersion. Hall elements of the same model but different batches may have significant differences in temperature drift coefficient, and the temperature drift coefficient of Hall elements is also different in different temperature ranges. Although some studies have attempted to perform multi-segment linear fitting of temperature drift coefficient in different temperature ranges through experimental data, they have not fully considered the differences between different batches of Hall elements, resulting in inconsistent results when directly using temperature coefficient for compensation.

[0006] (3) When using an external temperature sensor to measure temperature, since only the ambient temperature can be obtained and the actual temperature of the Hall element cannot be directly measured, the temperature tracking performance is poor and the final compensation effect is difficult to reach the ideal level.

[0007] Therefore, how to design a Hall current sensor system that can achieve high-precision temperature drift compensation over a wide temperature range has become a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0008] This invention aims to at least partially solve one of the technical problems in related technologies. The temperature drift error compensation system and signal optimization method for Hall current sensors significantly improves measurement accuracy and stability over a wide temperature range by directly coupling the thermistor to the surface of the Hall element and combining it with an improved Kalman filter algorithm, while reducing hardware complexity and cost.

[0009] To achieve the above objectives, the first aspect of this invention proposes a method for compensating the temperature drift of a Hall current sensor, which includes the following steps: S1. A thermistor is attached to the surface of the Hall element, and a voltage divider resistor is connected in series with the thermistor to form a voltage divider circuit. The Hall element is used to sense the change in the magnetic field generated by the coil. S2. Power-on calibration process: Power on the Hall element and the voltage divider circuit for the first time, collect the temperature signal Temp after voltage division by the thermistor and the current sensing signal Out from the output side of the coil, read their voltage values, convert them from analog to digital and record them as the initial temperature signal voltage. Offset voltage ; S3. Collect the temperature signal Temp after voltage division by the thermistor and the current sensing signal Out on the output side of the coil according to the set frequency, and record their voltage values ​​as the current temperature signal voltage Vtemp_real and the current current sensing signal voltage Vout_real respectively after analog-to-digital conversion. S4. Calculate the current measurement value. ,in, The current conversion coefficient of the Hall element; S5. Calculate the temperature change value after offset calibration. ,in, This is the conversion factor between the voltage value and temperature value after voltage division by the thermistor; S6. Transfer the current measurement value Temperature change value The input is fed into the Kalman filter optimization algorithm to obtain the optimal current estimate. .

[0010] Furthermore, the Kalman filter optimization algorithm includes: S61. Based on the temperature change value Tchg and the voltage temperature drift coefficient α of the Hall element... T Calculate voltage and temperature compensation values ; S62, Based on voltage and temperature compensation values Calculate the predicted current value ; S63. Based on filter parameters Q, R, and P... k-1 Calculate the error covariance P k : S631. Calculate the prediction error covariance. Where Q is the process noise covariance, This represents the error covariance from the previous measurement. S632, Calculate the Kalman filter gain Where R is the measurement noise covariance; S633, Update Error Covariance ; S64. Based on the measured current value Current prediction value Kalman filter gain Calculate the optimal estimate of the current .

[0011] Another object of the present invention is to provide a temperature drift dynamic compensation system for a Hall current sensor, comprising: A thermistor is attached to the surface of a Hall element to collect the temperature of the Hall element, which senses changes in the magnetic field generated by a coil. A voltage divider resistor is connected in series with the thermistor to form a voltage divider circuit. The voltage divider circuit outputs the voltage value after voltage division by the thermistor, which is denoted as the temperature signal Temp. The signal acquisition module acquires the voltage value at the output side of the coil and outputs a current sensing signal Out. The power supply module provides a stable power supply for the Hall element and thermistor assembly; The analog-to-digital conversion module samples the temperature signal Temp and the current sensing signal Out and converts them into digital signals; The processor module reads the digital signal output from the analog-to-digital converter module via the communication bus and runs a compensation algorithm to calculate the final current estimate. ; The compensation algorithm module is configured to execute the compensation algorithm, which dynamically corrects the current signal using an improved Kalman filter algorithm based on the temperature drift coefficient of the Hall element, real-time temperature changes, and the current measurement value.

[0012] Furthermore, the compensation algorithm module includes a power-on calibration process and a dynamic compensation process; during the power-on calibration process, the processor module reads the current sensing signal and temperature signal output by the analog-to-digital conversion module, and records them as offset voltages respectively. Initial temperature signal voltage During the dynamic compensation process, the current current sensing signal voltage Vout_real and the offset voltage output by the analog-to-digital conversion module are used as the basis for the compensation. Calculate the current measured current value Imea; based on the current temperature signal voltage Vtemp_real and the initial temperature signal voltage... Calculate the temperature change value Tchg.

[0013] Furthermore, the formula for calculating the real-time current measurement value Imea is as follows: ; in, is the current conversion coefficient of the Hall element.

[0014] Furthermore, the formula for calculating the temperature change value Tchg is as follows: ; in, This is the conversion factor between the voltage value and temperature value after voltage division by the thermistor.

[0015] Furthermore, the compensation algorithm module also includes a Kalman filter optimization algorithm, which is based on the temperature change value Tchg and the voltage temperature drift coefficient α of the Hall element. T Calculate the voltage-temperature compensation value Vtc; calculate the current prediction value Ipred based on the voltage-temperature compensation value Vtc; calculate the current prediction value Ipred based on the Kalman filter parameters Q, R, ... Calculate the error covariance P k and Kalman filter gain According to the Kalman filter gain The final current estimate Iopt is obtained by calculating the real-time current measurement value Imea and the current prediction value Ipred.

[0016] Furthermore, the formula for calculating the voltage-temperature compensation value Vtc is as follows: .

[0017] Furthermore, the formula for calculating the predicted current value Ipred is as follows: .

[0018] Furthermore, the error covariance Pk is calculated through the following steps: S001, Calculate the prediction error covariance Where Q is the process noise covariance, This represents the error covariance from the previous measurement. S002, Calculate the Kalman filter gain Where R is the measurement noise covariance; S003, Update Error Covariance .

[0019] Furthermore, the final current estimate Iopt is calculated using the following formula: .

[0020] Compared with existing technologies, the beneficial effects of the temperature drift dynamic compensation system and method for a Hall current sensor of the present invention are as follows: By directly coupling the thermistor to the surface of the Hall element, the thermal resistance between the thermistor and the Hall element is significantly reduced, enabling the thermistor to respond quickly to temperature changes in the Hall element, thereby improving the accuracy of temperature tracking. Through an improved Kalman filter algorithm, combined with the temperature drift coefficient of the Hall element and real-time temperature changes, synchronous correction of zero-point drift and temperature drift is achieved, significantly improving measurement accuracy over a wide temperature range. Furthermore, the present invention eliminates the need for complex hardware compensation circuits, reducing the hardware complexity and cost of the system, while also minimizing the impact of temperature drift and nonlinearity of other components on the compensation effect. The optimized Kalman filter algorithm only needs to record the error covariance of the previous measurement, eliminating the need to store large amounts of historical data, greatly reducing the storage space requirements of the hardware processor and improving computational efficiency. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the temperature drift dynamic compensation system for the Hall current sensor in an embodiment of the present invention. Figure 2 This is a flowchart of the temperature drift shift state compensation method for the Hall current sensor in an embodiment of the present invention; Figure 3 This is a flowchart of the Kalman filter optimization algorithm in the compensation algorithm of this invention embodiment. Detailed Implementation

[0022] Example 1: This invention provides a temperature drift dynamic compensation system and method for a Hall current sensor. Figure 1 The system's structural block diagram illustrates its main components and their connections. The system includes a thermistor assembly, a power supply module, an analog-to-digital converter module, a processor module, and a compensation algorithm module. The following detailed explanation, in conjunction with the accompanying drawings, outlines the composition, connections, and operating principles of each component.

[0023] The thermistor assembly consists of a thermistor 1 and a voltage divider resistor 2. Thermistor 1 is directly bonded to the surface of Hall element 4 via thermally conductive adhesive 3. Hall element 4 senses changes in the magnetic field generated by coil 5. One end of coil 5 receives a primary current Ip, and the other end outputs a secondary current Is. Figure 1As shown. The thickness of the thermally conductive adhesive 3 is controlled between 0.1mm and 0.3mm to reduce thermal resistance and achieve temperature synchronization between the thermistor 1 and the Hall element 4. Using thermally conductive adhesive can significantly reduce the thermal resistance between the Hall element and the thermistor, making the temperature of the thermistor as close as possible to that of the Hall element.

[0024] Voltage divider resistor 2 is fixed on the circuit board and connected in series with thermistor 1 to form a voltage divider circuit. The voltage divider circuit outputs the voltage value after the thermistor 1 is divided, denoted as the temperature signal Temp, which reflects the temperature value of thermistor 1. The temperature signal Temp is connected to the input terminal of the analog-to-digital converter module via a wire.

[0025] The power supply module generates a constant voltage VDD and connects it to Hall element 4 and voltage divider circuit through wires. At the same time, the ground terminal GND is also connected to Hall element 4 and the negative terminal of voltage divider circuit through wires.

[0026] The analog-to-digital converter (ADC) module includes a multi-channel ADC module. Its input terminals acquire the current sensing signal Out from the secondary side of the output terminal of coil 5 and the temperature signal Temp after voltage division by the thermistor 1 via wires. It then converts the analog voltage signals Out and Temp into digital signals. The sampling frequency of the ADC module is set to 1kHz to 10kHz to meet real-time requirements.

[0027] The processor module communicates with the analog-to-digital converter (ADC) module via a digital bus to read the digital values ​​of the current sensing signal (Out voltage) and the temperature signal (Temp voltage). The processor module includes an embedded microcontroller, which integrates a storage unit and an arithmetic unit. The storage unit stores the initial parameters and historical data required for the compensation algorithm, while the arithmetic unit executes the compensation algorithm. The embedded microcontroller communicates with the ADC module via an SPI interface to read the digital signals output by the ADC module.

[0028] The compensation algorithm module includes a power-on calibration process and a dynamic compensation process. During the power-on calibration process, the processor module reads the current sensing signal and temperature signal output from the analog-to-digital converter module, and records them as offset voltages, respectively. Initial temperature signal voltage During dynamic compensation, the processor module calculates the current current sensing signal voltage Vout_real and the offset voltage output by the analog-to-digital conversion module. Calculate the current measured current value Imea; based on the current temperature signal voltage Vtemp_real and the initial temperature signal voltage... Calculate the temperature change value Tchg.

[0029] The formula for calculating the real-time current measurement value Imea is: ; in, The current conversion coefficient of the Hall element is obtained through experimental calibration.

[0030] The formula for calculating the temperature change value Tchg is: ; in, The conversion coefficient between the voltage value and temperature value after voltage division by the thermistor is obtained by table lookup or multi-segment linear fitting.

[0031] The compensation algorithm module also includes a Kalman filter optimization algorithm, the process of which is as follows: Figure 3 As shown. The Kalman filter optimization algorithm is based on the real-time current measurement value Imea, the temperature change value Tchg, and the voltage temperature drift coefficient α of Hall element 4. T Calculate the voltage-temperature compensation value Vtc and the current prediction value Ipred.

[0032] The formula for calculating the voltage-temperature compensation value Vtc is: .

[0033] The formula for calculating the predicted current value Ipred is: .

[0034] The Kalman filter optimization algorithm further considers the error covariance P k and Kalman filter gain Calculate the final current estimate Iopt.

[0035] Error covariance P k Calculate using the following steps: (1) First, calculate the prediction error covariance. : ; Where Q is the process noise covariance, representing the uncertainty of the current prediction value, obtained through experimental modeling. This represents the error covariance from the previous measurement.

[0036] (2) Then calculate the Kalman filter gain. : ; Where R is the measurement noise covariance, representing the uncertainty of the current measurement value, which is obtained through experimental modeling.

[0037] (3) Last update error covariance P k : .

[0038] The final current estimate Iopt is calculated using the following formula: .

[0039] The voltage temperature drift coefficient α of Hall element 4 T The temperature drift coefficient was obtained through experimental measurement. Specifically, the output voltage change of Hall element 4 was recorded every 5°C within the temperature range of -40°C to +85°C, and the temperature drift coefficient within different temperature ranges was obtained through linear fitting.

[0040] The conversion factor between the voltage value and temperature value after voltage division of the thermistor 1 The voltage is obtained by looking up a table or by multi-segment linear fitting. Specifically, within the temperature range of -40℃ to +85℃, the output voltage of the thermistor voltage divider circuit is recorded every 5℃, and a voltage-temperature curve is plotted.

[0041] The initial error covariance P0 of the Kalman filter optimization algorithm is set to an empirical value between 0.1 and 2. As the algorithm iterates, the error covariance P0... k It gradually converges to a stable value.

[0042] like Figure 2 As shown, in a practical application scenario, when the system starts up, Hall element 4 and thermistor 1 are powered on for the first time. The processor module first reads the initial current sensing signal Out and the initial temperature signal Temp output by the analog-to-digital converter module, which are recorded as offset voltages respectively. and initial temperature signal voltage The system then enters a dynamic compensation process, where the processor module uses the current current sensing signal voltage Vout_real and offset voltage acquired by the analog-to-digital converter module. Calculate the real-time current measurement value Imea; based on the current temperature signal voltage Vtemp_real and the initial temperature signal voltage acquired by the analog-to-digital conversion module... The temperature change value Tchg is calculated. The real-time current measurement value Imea and the temperature change value Tchg are input into the Kalman filter optimization algorithm to calculate the final current estimate Iopt. Throughout the process, thermistor 1 maintains close contact with the surface of Hall element 4 through thermally conductive adhesive 3, enabling rapid response to temperature changes in Hall element 4 and thus improving the accuracy of temperature tracking. The improved Kalman filter algorithm, combining the temperature drift coefficient of Hall element 4 and real-time temperature changes, achieves synchronous correction of zero-point drift and temperature drift, significantly improving measurement accuracy over a wide temperature range.

[0043] To enable those skilled in the art to fully understand and implement this invention, the specific implementation principle of this invention is further explained below in conjunction with a specific application scenario.

[0044] In practical applications, upon system startup, the processor module first reads the initial current sensing signal Out from Hall element 4 and the initial temperature signal Temp from the voltage divider circuit of thermistor 1 via the analog-to-digital converter module. These two signals are then recorded as offset voltages. and initial temperature signal voltage This serves as the baseline value for the subsequent dynamic compensation process. Subsequently, the system enters the real-time compensation phase. The processor module continuously obtains the current sensing signal voltage Vout_real and the current temperature signal voltage Vtemp_real from the analog-to-digital conversion module, and calculates the real-time current measurement value Imea and the temperature change value Tchg based on these signals. During this process, the thermistor 1 is tightly bonded to the surface of the Hall element 4 using thermally conductive adhesive 3, with its thickness controlled between 0.1mm and 0.3mm to ensure that the thermistor 1 can quickly respond to temperature changes in the Hall element 4, thereby improving the accuracy of temperature tracking.

[0045] During the dynamic compensation process, the processor module follows the formula: ; Calculate the real-time current measurement value Imea, where, is the current conversion coefficient of Hall element 4, which was obtained through experimental calibration.

[0046] Meanwhile, the processor module follows the formula: ;

[0047] Calculate the temperature change value Tchg. The conversion coefficient between the voltage value and temperature value after voltage division by the thermistor is obtained by table lookup or multi-segment linear fitting. These calculation results are input into the Kalman filter optimization algorithm to further correct the current measurement value.

[0048] The core of the Kalman filter optimization algorithm lies in utilizing the voltage temperature drift coefficient α of Hall element 4. T The real-time temperature change value Tchg and the current measurement value Imea are used to calculate the voltage temperature compensation value Vtc and the current prediction value Ipred.

[0049] Specifically, the voltage-temperature compensation value Vtc is obtained through the formula: , The current prediction value Ipred is obtained through the formula. Calculation. Based on this, the Kalman filter optimization algorithm further incorporates the error covariance P. k and Kalman gain K k Calculate the final current estimate Iopt. Error covariance P k The update process includes prediction error covariance Calculation of Kalman filter gain Determination of error covariance The update, specifically the formulas are as follows: ; ; .

[0050] The final current estimate Iopt is obtained using the following formula: .

[0051] During the above process, the power supply module provides a stable power supply to Hall element 4 and the thermistor voltage divider circuit, ensuring that the system's measurement accuracy is not affected by power fluctuations. The multi-channel analog-to-digital converter module samples the current sensing signal Out of Hall element 4 and the temperature signal Temp of the thermistor voltage divider circuit at a sampling frequency of 1kHz to 10kHz, ensuring the real-time performance and accuracy of data acquisition. The processor module communicates with the analog-to-digital converter module via the SPI interface, reads the digitized signal, and executes a compensation algorithm to achieve dynamic correction of the current measurement value.

[0052] Through the above steps, the system achieves high-precision dynamic compensation of the Hall current sensor output signal. Thermistor 1 is directly coupled to the surface of Hall element 4 via thermally conductive adhesive 3, significantly reducing thermal resistance and enabling thermistor 1 to respond quickly to temperature changes in Hall element 4, thereby improving the accuracy of temperature tracking. The improved Kalman filter algorithm, combined with the temperature drift coefficient of Hall element 4 and real-time temperature changes, achieves synchronous correction of zero-point drift and temperature drift, significantly improving measurement accuracy over a wide temperature range. Furthermore, since complex hardware compensation circuits are unnecessary, the overall system complexity and cost are reduced, while also minimizing the impact of temperature drift and nonlinear characteristics of other components on the compensation effect.

[0053] In practical applications, such as current monitoring in industrial automation equipment, this system can effectively cope with drastic changes in ambient temperature, ensuring the stability and reliability of current measurements. The Kalman filter optimization algorithm only needs to record the error covariance of the previous measurement, eliminating the need to store large amounts of historical data. This significantly reduces the storage space requirements of the processor module while improving computational efficiency, enabling the system to operate efficiently in resource-constrained embedded environments.

[0054] For those skilled in the art, various modifications and improvements can be made without departing from the inventive concept of this invention, and these all fall within the protection scope of this invention.

Claims

1. A method for compensating the temperature drift of a Hall current sensor, characterized in that, It includes the following steps: S1. A thermistor is attached to the surface of the Hall element, and a voltage divider resistor is connected in series with the thermistor to form a voltage divider circuit. The Hall element is used to sense the change in the magnetic field generated by the coil. S2. Power-on calibration process: Power on the Hall element and the voltage divider circuit for the first time, collect the temperature signal Temp after the thermistor voltage divider and the current sensing signal Out on the output side of the coil, read their voltage values ​​and record them as the initial temperature signal voltage Vtemp_init and the offset voltage Vout_init respectively after analog-to-digital conversion. S3. Collect the temperature signal Temp after voltage division by the thermistor and the current sensing signal Out on the output side of the coil according to the set frequency, and record their voltage values ​​as the current temperature signal voltage Vtemp_real and the current current sensing signal voltage Vout_real respectively after analog-to-digital conversion. S4. Calculate the current measurement value. ,in, The current conversion coefficient of the Hall element; S5. Calculate the temperature change value after offset calibration. ,in, This is the conversion factor between the voltage value and temperature value after voltage division by the thermistor; S6. Input the current measurement value Imea and the temperature change value Tchg into the Kalman filter optimization algorithm to obtain the optimal current estimate value Iopt.

2. The temperature drift dynamic compensation method for a Hall current sensor as described in claim 1, characterized in that, The Kalman filter optimization algorithm includes: S61. Based on the temperature change value Tchg and the voltage temperature drift coefficient α of the Hall element... T Calculate voltage and temperature compensation values ; S62, Based on voltage and temperature compensation values Calculate the predicted current value ; S63. Based on filter parameters Q, R, and P... k-1 Calculate the error covariance P k : S631. Calculate the prediction error covariance. Where Q is the process noise covariance, This represents the error covariance from the previous measurement. S632, Calculate the Kalman filter gain Where R is the measurement noise covariance; S633, Update Error Covariance ; S64. Based on the measured current value Current prediction value Kalman filter gain Calculate the optimal estimate of the current .

3. A temperature drift dynamic compensation system for a Hall current sensor, characterized in that, include: A thermistor is attached to the surface of a Hall element to collect the temperature of the Hall element, which senses changes in the magnetic field generated by a coil. A voltage divider resistor is connected in series with the thermistor to form a voltage divider circuit. The voltage divider circuit outputs the voltage value after voltage division by the thermistor, which is denoted as the temperature signal Temp. The signal acquisition module acquires the voltage value at the output side of the coil and outputs a current sensing signal Out. The power supply module provides a stable power supply for the Hall element and thermistor assembly; The analog-to-digital conversion module samples the temperature signal Temp and the current sensing signal Out and converts them into digital signals; The processor module reads the digital signal output from the analog-to-digital converter module via the communication bus and runs a compensation algorithm to calculate the final current estimate. ; The compensation algorithm module is configured to execute the compensation algorithm, which dynamically corrects the current signal using an improved Kalman filter algorithm based on the temperature drift coefficient of the Hall element, real-time temperature changes, and the current measurement value.

4. The temperature drift dynamic compensation system for the Hall current sensor as described in claim 3, characterized in that, The compensation algorithm module includes a power-on calibration process and a dynamic compensation process; during the power-on calibration process, the processor module reads the current sensing signal and temperature signal output by the analog-to-digital conversion module, and records them as offset voltages respectively. Initial temperature signal voltage During the dynamic compensation process, the current current sensing signal voltage Vout_real and the offset voltage output by the analog-to-digital conversion module are used as the basis for the compensation. Calculate the current measured current value Imea; based on the current temperature signal voltage Vtemp_real and the initial temperature signal voltage... Calculate the temperature change value Tchg.

5. The temperature drift dynamic compensation system for the Hall current sensor as described in claim 4, characterized in that, The formula for calculating the real-time current measurement value Imea is as follows: ； in, is the current conversion coefficient of the Hall element.

6. The temperature drift dynamic compensation system for the Hall current sensor as described in claim 5, characterized in that, The formula for calculating the temperature change value Tchg is: ； in, This is the conversion factor between the voltage value and temperature value after voltage division by the thermistor.

7. The temperature drift dynamic compensation system for the Hall current sensor as described in claim 5 or 6, characterized in that, The compensation algorithm module also includes a Kalman filter optimization algorithm, which is based on the temperature change value Tchg and the voltage temperature drift coefficient α of the Hall element. T Calculate the voltage-temperature compensation value Vtc; calculate the current prediction value Ipred based on the voltage-temperature compensation value Vtc; calculate the current prediction value Ipred based on the Kalman filter parameters Q, R, P. k-1 Calculate the error covariance P k and Kalman filter gain K k According to the Kalman filter gain K k The final current estimate Iopt is obtained by calculating the real-time current measurement value Imea and the current prediction value Ipred.

8. The temperature drift dynamic compensation system for the Hall current sensor as described in claim 7, characterized in that, The formula for calculating the voltage-temperature compensation value Vtc is as follows: 。 9. The temperature drift dynamic compensation system for the Hall current sensor as described in claim 7, characterized in that, The formula for calculating the predicted current value Ipred is as follows: 。 10. The temperature drift dynamic compensation system for the Hall current sensor as described in claim 7, characterized in that, The error covariance P k Calculate using the following steps: S001, Calculate the prediction error covariance Where Q is the process noise covariance, This represents the error covariance from the previous measurement. S002, Calculate the Kalman filter gain Where R is the measurement noise covariance; S003, Update Error Covariance .

11. The temperature drift dynamic compensation system for the Hall current sensor as described in claim 7, characterized in that, The final current estimate Iopt is calculated using the following formula: 。

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