Quantitative Performance Comparison of Thermal Structure Function Computations

Nils J. Ziegeler, Peter W. Nolte and Stefan Schweizer
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Nils J. Ziegeler: Faculty of Electrical Engineering, South Westphalia University of Applied Sciences, 59494 Soest, Germany
Peter W. Nolte: Fraunhofer Application Center for Inorganic Phosphors, Branch Lab of Fraunhofer Institute for Microstructure of Materials IMWS, 59494 Soest, Germany
Stefan Schweizer: Faculty of Electrical Engineering, South Westphalia University of Applied Sciences, 59494 Soest, Germany

Energies, 2021, vol. 14, issue 21, 1-16

Abstract: The determination of thermal structure functions from transient thermal measurements using network identification by deconvolution is a delicate process as it is sensitive to noise in the measured data. Great care must be taken not only during the measurement process but also to ensure a stable implementation of the algorithm. In this paper, a method is presented that quantifies the absolute accuracy of network identification on the basis of different test structures. For this purpose, three measures of accuracy are defined. By these metrics, several variants of network identification are optimized and compared against each other. Performance in the presence of noise is analyzed by adding Gaussian noise to the input data. In the cases tested, the use of a Bayesian deconvolution provided the best results.

Keywords: compact thermal models; thermal impedance; transient thermal measurement; time constant spectrum; thermal structure function; network identification by deconvolution (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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