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Thermal Impedance Calibration for Rapid and Noninvasive Calorimetric Soft-Switching Loss Characterization

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Virtual prototyping, multiobjective optimization, and design automation are increasingly being used to meet the growing demands of modern power electronic applications in terms of efficiency and power density. These concepts… Click to show full abstract

Virtual prototyping, multiobjective optimization, and design automation are increasingly being used to meet the growing demands of modern power electronic applications in terms of efficiency and power density. These concepts are based on accurate loss models of the power semiconductors used. While for hard-switching, the double pulse test is an established electrical characterization method, soft-switching losses can only be determined by calorimetric measurements. Despite significant improvements in using transient approaches, calorimetric characterization of soft-switching loss energy is very time-intensive and requires complex measurement setups. This article presents a new automated calorimetric method with thermal impedance calibration that enables rapid and noninvasive switching loss measurements. Using ultrafast transient measurements and accelerated cooling phases in between, soft-switching loss maps can be determined based on hundreds of individual readings. The proposed measuring method is validated against hard-switching electrical double pulse test measurements. The method achieves a maximum error of $1.9 \,\%$ for the total loss measurement from $1-9 \,\mathrm{W}$ and an average measurement error of $16.5 \,\%$ for the soft-switching energy from $1-4 \,\mu \mathrm{J}$ of wide bandgap power semiconductors. In addition to comparing the results of different semiconductor technologies for use in a charger application, the manufacturers' simulation models are also analyzed with respect to soft-switching energy.

Keywords: soft switching; inline formula; switching loss; tex math

Journal Title: IEEE Transactions on Power Electronics
Year Published: 2023

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