BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:US/Mountain BEGIN:DAYLIGHT DTSTART:20160313T030000 TZOFFSETFROM:-0700 TZOFFSETTO:-0600 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:MDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20161106T010000 TZOFFSETFROM:-0600 TZOFFSETTO:-0700 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:MST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20160426T234053Z UID:22FDBAE1-FBE6-11E5-A050-0050568D2FB3 DTSTART;TZID=US/Mountain:20160503T173000 DTEND;TZID=US/Mountain:20160503T193000 DESCRIPTION:Join us at our next Power & Energy Society meeting\, Pikes Peak ! Dr. Plett\, Professor of Electrical and Computer Engineering at the Univ ersity of Colorado Colorado Springs (UCCS) will be joining us to talk abou t leading-edge research at UCCS in Battery Optimization.\n\nOptimizing the cost\, weight\, size and reliability of major hybrid and electric-vehicle (xEV) systems is critical in maximizing the value of the xEV to the end c ustomer. For example\, of the components comprising an HEV\, the costliest is the battery pack\, which may represent 30–35% of the propulsion syst em’s total cost. This is even truer for EV. The battery is among the hea viest components of a xEV's propulsion system as well. Therefore\, careful design of the battery pack and the battery management system (BMS) can dr amatically impact the lifetime affordability of a xEV.\n\nAn important tas k of the vehicle’s BMS is to provide continuous estimates of battery-pac k available energy and power to the vehicle. These estimates must be accur ate to avoid situations where the vehicle overcharges or overdischarges th e battery pack\, causing premature degradation. Historically\, the estimat es have been made based on equivalent-circuit models (ECM) of cells\; howe ver\, ECMs are unable to provide information on the internal electrochemic al processes that drive cell degradation directly. Therefore\, present-day battery packs tend to be overdesigned and conservatively operated in orde r to account for the uncertainty of how to incorporate cell aging in ECM c ontrols. This makes the battery pack larger and more expensive than it nee ds to be.\n\nIn order to provide estimates of available power and energy t hat take cell aging into account\, physics-based models (PBM) must be used instead. At UCCS\, we have been investigating computationally practical p hysics-based models (PBM) of cells\, and leveraging those models to provid e estimates of battery-pack available energy and power. A vehicle using th ese estimates can extract the maximum performance from the battery pack wh ile still maximizing battery-pack life. This can result in smaller and les s expensive battery packs.\n\nThis talk will give a background in BMS comp utational requirements\, approaches to lithium-ion cell modeling\, and opt imal controls. It will highlight some of the activities taking place at UC CS in this field.\n\nSnacks provided!\n\nSpeaker(s): Dr. Gregory Plett\, \ , Dr. Gregory Plett\, \n\nRoom: Ent Conference Center\, Bldg: Library 21c\ , 1175 Chapels Hills Drive\, Colorado Springs\, Colorado\, United States\, 80920 LOCATION:Room: Ent Conference Center\, Bldg: Library 21c\, 1175 Chapels Hil ls Drive\, Colorado Springs\, Colorado\, United States\, 80920 ORGANIZER:us.martine-denise.long@ieee.org SEQUENCE:4 SUMMARY:Battery Design & Management System Optimization: Leading-edge resea rch at UCCS URL;VALUE=URI:https://events.vtools.ieee.org/m/39321 X-ALT-DESC:Description: <br /><p><span style="font-size: 12pt\;">Join us at our next Power &amp\; Energy Society meeting\, Pikes Peak! Dr. Plett\, Pr ofessor of Electrical and Computer Engineering at the University of Colora do Colorado Springs (UCCS) will be joining us to talk about leading-edge r esearch at UCCS in Battery Optimization.</span></p>\n<p><span style="font- size: 12pt\;">&nbsp\;</span></p>\n<p><span style="font-size: 12pt\;">Optim izing the cost\, weight\, size and reliability of major&nbsp\;hybrid and e lectric-vehicle (xEV) systems is critical in maximizing the value of the&n bsp\;xEV to the end customer. For example\, of the&nbsp\;components&nbsp\; comprising an HEV\, the&nbsp\;costliest is the battery pack\, which may re present 30&ndash\;35% of the propulsion system&rsquo\;s total cost. &nbsp\ ;This is even truer for EV.&nbsp\;The&nbsp\;battery is among the heaviest components of a xEV's&nbsp\;propulsion system as well. Therefore\, careful design of&nbsp\;the&nbsp\;battery pack and the battery management system (BMS) can dramatically impact&nbsp\;the lifetime affordability of a xEV.</ span></p>\n<p><span style="font-size: 12pt\;">&nbsp\;</span></p>\n<p><span style="font-size: 12pt\;">An important task of the vehicle&rsquo\;s BMS i s to provide continuous&nbsp\;estimates of battery-pack available energy a nd power to the vehicle.&nbsp\;&nbsp\;These estimates must be accurate to avoid situations where the vehicle overcharges or overdischarges the batte ry pack\, causing premature degradation. Historically\, the estimates have been made based on equivalent-circuit models (ECM) of cells\; however\, E CMs are unable to provide&nbsp\;information on the internal&nbsp\;electroc hemical processes that drive cell&nbsp\;degradation directly.&nbsp\;Theref ore\, present-day battery packs tend to be overdesigned and conservatively operated in order to account for the uncertainty of how to incorporate ce ll aging in ECM controls. This makes the battery pack larger and more expe nsive than it needs to be.</span></p>\n<p><span style="font-size: 12pt\;"> &nbsp\;</span></p>\n<p><span style="font-size: 12pt\;">In order to provide &nbsp\;estimates of available power and energy that&nbsp\;take cell aging into account\,&nbsp\;physics-based models (PBM) must be used instead. &nbs p\;At UCCS\, we have been investigating computationally practical physics- based models (PBM) of cells\, and leveraging those models to provide estim ates of battery-pack available energy and power. &nbsp\;A vehicle using th ese estimates can extract the maximum performance from the battery pack wh ile still maximizing battery-pack life. &nbsp\;This can result in smaller and less expensive battery packs.</span></p>\n<p><span style="font-size: 1 2pt\;">&nbsp\;</span></p>\n<p><span style="font-size: 12pt\;">This talk wi ll give a background in BMS computational requirements\, approaches to lit hium-ion cell modeling\, and optimal controls. &nbsp\;It will highlight so me of the activities taking place at UCCS in this field.</span></p>\n<p>&n bsp\;</p>\n<p><span style="font-size: 12pt\;">Snacks&nbsp\;provided!</span ></p> END:VEVENT END:VCALENDAR