Spread Spectrum Time Domain Reflectometry and Steepest Descent Inversion to Measure Complex Impedance

Journal Article · Tue Mar 16 00:00:00 EDT 2021 · ACES Journal

DOI:https://doi.org/10.47037/2020.aces.j.360211· OSTI ID:2234306

Kingston, Samuel R. ^[1]; Ellis, Hunter ^[1]; Saleh, Mashad U. ^[1]; Benoit, Evan J. ^[1]; Edun, Ayobami ^[2]; Furse, Cynthia M. ^[3]; Scarpulla, Michael A. ^[1]; Harley, Joel B. ^[2]

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1. University of Utah, Salt Lake City, UT (United States)
2. University of Florida, Gainesville, FL (United States)
3. University of Utah, Salt Lake City, UT (United States); LiveWire Innovation, Camarillo, CA (United States)

In this paper, we present a method for estimating complex impedances using reflectometry and a modified steepest descent inversion algorithm. We simulate spread spectrum time domain reflectometry (SSTDR), which can measure complex impedances on energized systems for an experimental setup with resistive and capacitive loads. A parametric function, which includes both a misfit function and stabilizer function, is created. The misfit function is a least squares estimate of how close the model data matches observed data. The stabilizer function prevents the steepest descent algorithm from becoming unstable and diverging. Steepest descent iteratively identifies the model parameters that minimize the parametric function. We validate the algorithm by correctly identifying the model parameters (capacitance and resistance) associated with simulated SSTDR data, with added 3 dB white Gaussian noise. With the stabilizer function, the steepest descent algorithm estimates of the model parameters are bounded within a specified range. Furthermore, the errors for capacitance (220pF to 820pF) and resistance (50 Ω to 270 Ω) are < 10%, corresponding to a complex impedance magnitude |R +1/jωC| of 53 Ω to 510 Ω.

• Research Organization: Univ. of Utah, Salt Lake City, UT (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
• Grant/Contract Number: EE0008169
• OSTI ID: 2234306
• Journal Information: ACES Journal, Vol. 36, Issue 2; ISSN 1054-4887
• Publisher: Applied Computational Electromagnetics Society
• Country of Publication: United States
• Language: English

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14 SOLAR ENERGY