Adaptive Angle Sensor Calibration for Magnetic Field Precision
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Solution Overview
Problem
Magnetic field sensing systems face challenges in accurately measuring the angular position and speed of rotating targets due to offset adjustments, sensitivity mismatches, and orthogonality issues between sensing elements, which affect the reliability and precision of sensor outputs in safety-critical applications.
Innovation Solution
A method and system that utilize multiple magnetic field sensing elements to generate signals associated with a rotating target, processing these signals to calculate offset adjustment vectors, sensitivity mismatch coefficients, and non-orthogonality coefficients, which are then stored for adjusting the signals to correct for distortions and improve measurement accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If magnetic field sensing elements are used to measure angular position and speed of rotating targets, then motion detection capability is provided, but measurement precision deteriorates due to offset adjustments, sensitivity mismatches, and orthogonality issues between sensing elements
Solution Approach 1:
The system performs preliminary calibration by rotating the target through multiple positions and measuring signals at each position. These preliminary measurements are used to calculate offset adjustment vectors, sensitivity mismatch coefficients, and non-orthogonality coefficients before normal operation begins. This preliminary action eliminates measurement errors that would otherwise degrade precision and reliability during actual use.
Solution Approach 2:
The calibration process involves changing the angular position parameter of the rotating target through multiple discrete positions. By measuring signals at different angular positions and analyzing how the sensing elements respond to parameter changes, the system calculates correction coefficients that compensate for sensitivity mismatches and non-orthogonality, thereby improving measurement precision.
2Measurement precision
If multiple magnetic field sensing elements are used to improve measurement accuracy, then angular position measurement capability is enhanced, but device complexity increases due to the need for calibration procedures
Solution Approach 1:
The system performs self-calibration by using its own sensing elements to measure signals at multiple angular positions and automatically calculate the necessary correction coefficients. The processing circuitry within the sensor itself computes offset adjustment vectors, sensitivity mismatch coefficients, and non-orthogonality coefficients without requiring external calibration equipment, thereby reducing overall system complexity while maintaining high measurement precision.
Solution Approach 2:
The processing circuitry serves multiple functions: it processes real-time sensor signals for angular position measurement, performs calibration calculations by analyzing signals at different positions, and stores correction coefficients for ongoing compensation. This multi-functionality eliminates the need for separate calibration devices or systems, reducing device complexity while achieving high measurement precision.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the accuracy and reliability of magnetic field sensing systems by correcting for offset, sensitivity, and orthogonality issues, thereby improving the precision of angular position and speed measurements.
Implementation Method 1
Some sensors include one or magnetic field sensing elements, such as a Hall effect element or a magnetoresistive element, to sense a magnetic field associated with proximity or motion of a target object
Implementation Method 2
Some sensors include one or magnetic field sensing elements, such as a Hall effect element or a magnetoresistive element, to sense a magnetic field associated with proximity or motion of a target object
Data Source
AI summary
A method comprising: obtaining at least three sampled values m, each of the sampled values m including a respective first component that is obtained based on a first signal and a respective second component that is obtained based on a second signal and solving a system of equations to yield at least one of (i) an offset adjustment vector k, (ii) a sensitivity mismatch coefficient γ, and (iii) a non-orthogonality coefficient s, the system of equations being arranged to model each of the sampled values m as a function of: a respective one of a plurality of number arrays, a magnetic field, and the at least one of (i) the offset adjustment vector k, (ii) the sensitivity mismatch coefficient γ, and (iii) the non-orthogonality coefficient s.


