MEMS Sensor Linearization via Frequency-Dependent Compensation
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Solution Overview
Problem
Microelectromechanical system (MEMS) sensors, such as accelerometers and gyroscopes, face accuracy issues due to temperature and signal amplitude variations, leading to nonlinear errors that current compensation strategies, including piecewise linear approaches, are insufficient to correct, especially under extreme conditions like high vibrations and temperatures.
Innovation Solution
A method and system that associate test temperature values with input signal values to determine temperature-input signal pairs, measure output signals, and calculate compensation terms to modify the sense signal of MEMS sensors, using polynomial formulas to address both linear and nonlinear variations, enabling self-testing and self-calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fixed or static correction strategies are used to compensate MEMS sensor errors, then the compensation process is simple, but the accuracy is insufficient under high amplitude vibrations and frequency-variant conditions
Solution Approach 1:
The patent implements dynamic compensation by transitioning from fixed correction values to frequency-dependent correction values. The system measures the actual frequency of vibrations and selects appropriate correction values from a lookup table, allowing the compensation to adapt dynamically to changing vibration conditions rather than using a static correction approach
Solution Approach 2:
The patent changes the parameter used for compensation from a fixed static value to a frequency-dependent value. By using the measured vibration frequency as a selector parameter for the correction lookup table, the system adjusts the correction magnitude based on the actual operating conditions, thereby improving accuracy without requiring complex real-time calculations
2Measurement precision
If polynomial formulas are used to correct nonlinearities, then the accuracy improves, but the computational complexity increases
Solution Approach 1:
The patent performs preliminary computation by pre-calculating correction values for various frequency conditions and storing them in a lookup table during manufacturing or calibration. This eliminates the need for complex polynomial calculations during real-time operation, as the system only needs to perform a simple table lookup based on the measured frequency
Solution Approach 2:
The patent replaces complex mathematical computation (polynomial formulas) with a simpler data retrieval operation (lookup table). By substituting the computational mechanism with a memory-based approach, the system achieves the same nonlinear correction accuracy without the computational burden of real-time polynomial evaluation
3Measurement precision
If frequency-dependent correction values are implemented, then the accuracy under vibrations improves, but the device complexity increases
Solution Approach 1:
The patent segments the correction approach by creating a lookup table with discrete correction values for different frequency ranges. This segmentation allows the complex frequency-dependent correction to be broken down into manageable discrete steps, simplifying the implementation while maintaining accuracy across varying vibration frequencies
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
The solution effectively compensates for nonlinear errors in MEMS sensors, improving accuracy by modifying the output signals based on calculated compensation terms, reducing vibration-induced errors and enhancing robustness in applications like automotive systems.
Implementation Method 1
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Data Source
AI summary
Methods and systems for compensation of a microelectromechanical system (MEMS) sensor may include associating test temperature values with input test signal values, identifying temperature-input signal pairs, and applying one of the test temperature values and one of the test signal values to the MEMS sensor. Desired output signal values may be determined, with each of the desired output signal values corresponding to one of the applied temperature-input signal pairs. Measured output signal values from the MEMS sensor may be measured, with each of the measured output signal values corresponding to one of the applied temperature-input signal pairs. Compensation terms may be determined based on the plurality of temperature-input signal pairs, the corresponding plurality of measured output signal values, and the corresponding plurality of desired output signal values. Compensation terms may be used to modify a sense signal of the MEMS sensor.