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dc.contributor.authorMerten, D.-
dc.contributor.authorSinger, J. A.-
dc.contributor.authorFiedler, H.-
dc.contributor.authorTappertzhofen, S.-
dc.description.abstractMicroscale Thermoelectric Generators (microTEGs) have a high application potential for energy harvesting for autonomous microsystems. In contrast to conventional thermoelectric generators, microTEGs can only supply small output-voltages. Therefore, voltage converters are required to provide supply-voltages that are sufficiently high to power microelectronics. However, for high conversion efficiency, voltage converters need to be optimized for the limited input voltage range and the typically high internal resistance of microTEGs. To overcome the limitations of conventional voltage converters we present an optimized self-startup voltage converter with dynamic maximum power point tracking. The performance potential of our concept is theoretically and experimentally analyzed. The voltage conversion interface demonstrates energy harvesting from open-circuit voltages as low as 30.7 mV, and enables independent and full start-up from 131 mV. No additional external power supply is required at any time during operation. It can be operated with a wide range of internal resistances from 20.6 to − 4 kΩ with a conversation efficiency between η = 68–79%.en
dc.relation.ispartofseriesSN applied sciences;4(5)-
dc.subjectBoost converteren
dc.subjectDynamic maximum power point trackingen
dc.subjectMeissner oscillatoren
dc.subjectVoltage conversion interfaceen
dc.subjectThermoelectric energy harvestingen
dc.subjectThermoelectric generatoren
dc.subjectHigh conversion efficiencyen
dc.titleConcept of an efficient self-startup voltage converter with dynamic maximum power point tracking for microscale thermoelectric generatorsen
dcterms.accessRightsopen access-
eldorado.secondarypublication.primarycitationMerten, D., Singer, J.A., Fiedler, H. et al. Concept of an efficient self-startup voltage converter with dynamic maximum power point tracking for microscale thermoelectric generators. SN Appl. Sci. 4, 154 (2022). https://doi.org/10.1007/s42452-022-05037-5de
Appears in Collections:Lehrstuhl für Mikro- und Nanoelektronik

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