Semiconductor Switch Resistance Estimation From Noisy Harmonic Measurements
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for parameter estimation in electrical power systems, particularly for semiconductor switches and supercapacitors, are inadequate in noisy environments, leading to inaccurate measurements due to low signal-to-noise ratios, which are exacerbated by noise levels comparable to or higher than the signal amplitude, especially in condition monitoring applications requiring high accuracy.
Innovation Solution
A method involving the integration of voltage and current harmonics of a selected frequency over a period of time to enhance the signal-to-noise ratio, allowing for accurate estimation of parameters such as ON-state resistance and circuit parameters by extracting and integrating harmonic components before estimating resistance or capacitance, thereby reducing the impact of noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If noise reduction filtering is applied to voltage and current measurements, then measurement noise is reduced, but bandwidth is lowered and measurement accuracy at frequency of interest is degraded
Solution Approach 1:
The measurement signal is segmented into discrete harmonic components using Fourier transform, allowing selective processing of each frequency component. This segmentation enables noise reduction to be applied specifically to unwanted frequency components while preserving the signal at the frequency of interest, thus resolving the contradiction between noise reduction and measurement precision.
Solution Approach 2:
The harmful noise components are extracted and removed from the measurement signal through frequency domain analysis. By identifying and isolating noise frequencies from the signal of interest, the method eliminates noise without affecting the bandwidth or accuracy of measurements at the desired frequency, thereby resolving the technical contradiction.
2Device complexity
If conventional parameter estimation methods (RLS, Kalman filters) are used, then computational simplicity is maintained, but accuracy deteriorates when noise exceeds 3%
Solution Approach 1:
The method uses periodic excitation signals and synchronized detection to estimate parameters. By applying periodic action at known frequencies and detecting the response at those same frequencies, the method achieves high accuracy even in noisy environments while maintaining computational simplicity through the use of standard Fourier transform techniques.
Solution Approach 2:
The method replaces complex adaptive filtering algorithms (Kalman filters, RLS) with a simpler frequency domain analysis approach. By substituting time-domain recursive estimation with frequency-domain harmonic analysis, the method achieves superior noise immunity while reducing computational complexity, thus resolving the contradiction between algorithm simplicity and estimation accuracy.
Data Source
AI summary
A method for estimating an ON-state resistance of a semiconductor switch in an electric power converter is provided. The method comprises obtaining, from a measurement circuit, an ON-state voltage of the semiconductor switch. The method further comprises obtaining an ON-state current through the semiconductor switch. The method further comprises obtaining a selected frequency, extracting voltage harmonics of the selected frequency from the ON-state voltage, and extracting current harmonics of the selected frequency from the ON-state current. The method further comprises integrating the voltage harmonics over a period of time, to obtain an integrated voltage. The method further comprises integrating the current harmonics over the same period of time, to obtain an integrated current. The method further comprises determining an ON-state resistance estimate of the semiconductor switch based on the integrated voltage and the integrated current.