BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Europe/London BEGIN:DAYLIGHT DTSTART:20260329T020000 TZOFFSETFROM:+0000 TZOFFSETTO:+0100 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:BST END:DAYLIGHT BEGIN:STANDARD DTSTART:20251026T010000 TZOFFSETFROM:+0100 TZOFFSETTO:+0000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:GMT END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260213T115621Z UID:DE6D0D01-DBD3-48B5-9496-9267B070FC3D DTSTART;TZID=Europe/London:20260218T133000 DTEND;TZID=Europe/London:20260218T143000 DESCRIPTION:The global economy will be greatly shaped by the transformed en ergy landscapes. Battery storage systems play an important role in decarbo nizing the whole energy chain from accepting renewable generations to elec trification of transport and other sectors. The talk presents some recent studies in the data-driven state estimation of Li-ion battery systems assi sted with machine learning and novel fibre optical sensors.\n\nCo-sponsore d by: Ulster University\n\nSpeaker(s): Kang\, \n\nVirtual: https://events. vtools.ieee.org/m/539139 LOCATION:Virtual: https://events.vtools.ieee.org/m/539139 ORGANIZER:h.zheng@ulster.ac.uk SEQUENCE:16 SUMMARY:Data-Driven State Estimation of Li-ion Batteries Assisted with Mach ine Learning and FBG Sensors URL;VALUE=URI:https://events.vtools.ieee.org/m/539139 X-ALT-DESC:Description: <br /><p style="text-align: justify\;"><span class= "content">The global economy will be greatly shaped by the transformed ene rgy landscapes. Battery storage systems play an important role in decarbon izing the whole energy chain from accepting renewable generations to elect rification of transport and other sectors. The talk presents some recent s tudies in the data-driven state estimation of Li-ion battery systems assis ted with machine learning and novel fibre optical sensors. </span></p> END:VEVENT END:VCALENDAR