BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT DTSTART:20230312T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20231105T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20231104T191403Z UID:902515B3-D37C-46E0-B535-EA5365AF92F1 DTSTART;TZID=America/New_York:20231102T170000 DTEND;TZID=America/New_York:20231102T180000 DESCRIPTION:Component degradation in power electronic converters severely t hreatens the system's reliability. These components degrade over long oper ation time due to electrical\, thermal\, and mechanical stress. This calls for accurate monitoring of component health considering cost\, accuracy\, and adaptability. This paper develops and validates a real-time Digital T win (DT)-based condition monitoring for Multi-Phase Interleaved Boost Conv erters (IBCs). The DT model employs state-space modeling to twin the real- physical hardware attributes and performance. Subsequently\, outputs from both the physical hardware and the DT model undergo comparison to determin e the least squared error in a multi-objective optimization setting. Techn iques such as particle swarm optimization and the genetic algorithm are em ployed for assessing the health of the converter's components. Furthermore \, this suggested approach can be adapted for various inductor coupling me thods\, functioning under both continuous-conduction-mode (CCM) and discon tinuous-conduction-mode (DCM). The paper proposes decoupling and hybrid ap proaches to improve estimation accuracy by 9.4% and reduce embedded comput ational requirements by 22%\, respectively. A 75 kW\, 60 kHz SiC IBC hardw are prototype is built and tested for concept validation.\n\nSpeaker(s): K ushan Choksi\n\nHauppauge Radisson\, 110 Motor Parkway\, Hauppauge\, New Y ork\, United States\, 11788 LOCATION:Hauppauge Radisson\, 110 Motor Parkway\, Hauppauge\, New York\, Un ited States\, 11788 ORGANIZER:colotti@ieee.org SEQUENCE:4 SUMMARY:Self-Evolving Digital Twin-based Online Health Monitoring of Multi- Phase Boost Converters URL;VALUE=URI:https://events.vtools.ieee.org/m/382178 X-ALT-DESC:Description: <br /><p>Component degradation in power electronic converters severely threatens the system's reliability. These components d egrade over long operation time due to electrical\, thermal\, and mechanic al stress. This calls for accurate monitoring of component health consider ing cost\, accuracy\, and adaptability. This paper develops and validates a real-time Digital Twin (DT)-based condition monitoring for Multi-Phase I nterleaved Boost Converters (IBCs). The DT model employs state-space model ing to twin the real-physical hardware attributes and performance. Subsequ ently\, outputs from both the physical hardware and the DT model undergo c omparison to determine the least squared error in a multi-objective optimi zation setting. Techniques such as particle swarm optimization and the gen etic algorithm are employed for assessing the health of the converter's co mponents. Furthermore\, this suggested approach can be adapted for various inductor coupling methods\, functioning under both continuous-conduction- mode (CCM) and discontinuous-conduction-mode (DCM). The paper proposes dec oupling and hybrid approaches to improve estimation accuracy by 9.4% and r educe embedded computational requirements by 22%\, respectively. A 75 kW\, 60 kHz SiC IBC hardware prototype is built and tested for concept validat ion.</p> END:VEVENT END:VCALENDAR