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Institute
We present a fast and accurate measurement technique for quasi-static magnetic fields by employing a progressive sampling method in an unconfined input space. The proposed machine learning algorithm is tested against uniform sampling on printed circuit board test structures and a buck converter. We prove allocation of multiple, separated regions with predefined lateral field limits at MHz frequencies. The feasibility of equivalent magnetic dipole source modeling based on a small number of samples is demonstrated. Compared to uniform testing, progressive expansion sampling identifies contours of given field limits in less than 3% of the reference measurement time.
Reliability analysis of power MOSFET’s with the help of compact models and circuit simulation
(2002)
High temperature reliability on automotive power modules verified by power cycling tests up to 150°C
(2003)
Power cycling and temperature endurance test of a GaN switching cell with substrate integrated chips
(2019)
We present a reliability study of a half-bridge switching cell with substrate integrated 650 V GaN HEMTs. Power Cycling Testing with a ΔTj of 100 K has revealed thermo-mechanically induced failures of contact vias after more than 220 kcycles. The via failure mode of contact opening is confirmed by reverse-bias pulsed IV-measurements to be primarily triggered by a ΔTj imposed thermal gradient and not by a high Tj. The chip electrical characteristics, however, remained unaffected during Power Cycling. Furthermore, a High Temperature Storage test at 125 °C for 5000 h has shown no changes in the electrical performance of substrate integrated GaN HEMTs.