Capacitive ADC Calibration by Excluding Noise-Driven Extreme Values
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Solution Overview
Problem
Existing analog to digital converters face challenges in accurately calibrating correction values due to unexpected external noise, leading to errors in conversion results, especially when noise is random or periodically generated, as current methods require extensive averaging and are ineffective in noisy environments.
Innovation Solution
Incorporating an averaging circuit that removes the maximum and minimum values from elemental correction values to calculate a correction value, allowing for accurate calibration even in the presence of external noise, thereby improving calibration accuracy and reducing the time required for calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional averaging methods are used to calculate correction values, then calibration accuracy can be improved by extensive averaging, but calibration time increases significantly
Solution Approach 1:
The patent extracts and removes the maximum and minimum values from the set of correction values before averaging. This eliminates the influence of outlier data points caused by noise, allowing accurate calibration to be achieved with fewer sampling operations, thus reducing calibration time while maintaining high accuracy.
Solution Approach 2:
By skipping the extreme values (maximum and minimum) in the correction value set, the patent rushes through the calibration process more efficiently. Instead of requiring extensive averaging of all values, the method quickly identifies and excludes outliers, enabling faster convergence to an accurate correction value.
2Measurement precision
If extensive averaging is performed to remove noise effects, then calibration accuracy improves, but the complexity of the calibration process increases
Solution Approach 1:
The patent simplifies the calibration process by extracting only the essential operation: removing maximum and minimum values. This straightforward approach avoids the complexity of sophisticated noise filtering algorithms while still achieving effective noise removal and accurate calibration.
Solution Approach 2:
Instead of trying to preserve all correction values and filter out noise through complex averaging, the patent inverts the approach by explicitly removing the problematic extreme values first, then averaging the remaining values. This simpler inverse approach reduces process complexity while maintaining accuracy.
3Ease of operation
If conventional averaging includes all correction values, then the process is simple, but noise effects significantly degrade calibration accuracy
Solution Approach 1:
The patent maintains operational simplicity while improving accuracy by extracting and removing only the maximum and minimum values before averaging. This minimal modification to the conventional approach preserves ease of operation while effectively eliminating noise-induced outliers that would otherwise degrade calibration accuracy.
Solution Approach 2:
The patent changes the parameter set used for averaging by excluding the extreme values (maximum and minimum). This parameter modification simplely adjusts the input data range, maintaining procedural simplicity while significantly improving the quality and accuracy of the calibration result.
4Measurement precision
If multiple correction values are averaged to reduce noise, then accuracy improves, but the time required for multiple operations increases
Solution Approach 1:
By extracting and removing the maximum and minimum values from the correction value set, the patent reduces the number of values that need to be processed in the averaging operation. This decreases the computational workload and time required, thereby improving calibration speed while maintaining accuracy through the exclusion of noisy outlier values.
Solution Approach 2:
The patent rushes through the calibration process by skipping the time-consuming operation of averaging all correction values including outliers. Instead, it quickly excludes the extreme values and performs averaging on a reduced set, achieving both speed and accuracy improvements.
Data Source
AI summary
An analog-to-digital (AD) convertor includes: a capacitance digital-to-analog (DA) convertor circuit; a comparator circuit coupled to the capacitance DA convertor circuit; and a calibration circuit that calculates a correction value for the AD convertor, wherein the capacitance DA convertor circuit includes a first capacitor, a second capacitor, n number of capacitors (n being integer equal to or larger than 3), each of the capacitors from first to n-th to be activated based on input digital data, wherein each of the first and second capacitors is designed for having a first capacitance value, wherein the n-th capacitor is designed for having twice the capacitance value of the (n−1)-th capacitor, wherein the calibration circuit calculates the correction value based on first and second results of the AD convertor, and wherein the first result is generated using the n-th capacitor and the second result is generated using the capacitors from first to (n−1)-th.