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SUMMARY:Degradation of Li-­‐ion Batteries: Experiments and Mathematical
  Modeling
DTSTART:20130503T130000
DTEND:20130503T140000
DTSTAMP:20260924T175119Z
UID:da6fe0c82a9ba6920a01a29decbd309fdf1e4ca48a968c898f903d27
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr Charles Delacourt\, CNRS\, Université de Picardie\, FR\nBi
 o: Charles Delacourt received his M. Sc. degree in analytical chemistry an
 d electrochemistry from University Pierre & Marie Curie (Paris VI\, France
 ) in 2002\, and completed his PhD in materials chemistry at Laboratoire de
  Réactivité et de Chimie des Solides (Université de Picardie Jules Vern
 e\, Amiens) in 2005. After a two-year postdoc within Prof. Newman group at
  Lawrence Berkeley National Lab and University of California\, Berkeley\, 
 he has been acting as a CNRS researcher at Laboratoire de Réactivité et 
 Chimie des Solides since fall 2007. His current research interest is the d
 evelopment of physics-based mathematical models for studying lithium-ion b
 atteries\, with a focus on degradation phenomena and battery life predicti
 on. In 2012\, he returned to Lawrence Berkeley Lab for a sabbatical in the
  group of Dr. Venkat Srinivasan\, the head of the US DOE BATT program. Cha
 rles Delacourt is the author (or coauthor) of 37 peer-reviewed journal pap
 ers (among which 2 in Nature Materials)\, 2 patents\, and is the recipient
  of the 2005 Research Student Award of the Battery Division of the Electro
 chemical Society\, the 2007 Umicore Scientific Award\, the 2009 Oronzio an
 d Niccolò De Nora Foundation Prize of ISE on Applied Electrochemistry\, a
 nd the 2011 Carl Wagner Medal of Excellence in Electrochemical Engineering
  of the European Federation of Chemical Engineering.\nLi-ion batteries (Li
 Bs) are the foremost candidates for powering electric/hybrid vehicles (EV/
 HEVs). For a LiB to be suitable for electric transportation\, proper perfo
 rmance in terms of power and energy is required over long periods (i.e.\, 
 10+ and 15+ years for EV and HEV\, respectively). In practice\, unwanted a
 ging phenomena lead to a decrease of the battery performance over time\, w
 hich practically limits its lifetime. Loss of electrode active material an
 d cyclable lithium along with the increase in cell resistance are among th
 e most common outcomes of degradation phenomena encountered in LiBs. Altho
 ugh the evaluation of the battery performance under conditions typical of 
 the end-application is crucial\, an EV/HEV battery experiences a wide rang
 e of operating conditions\, and as a consequence the experimental study of
  the battery aging in all of these conditions is impractical. In practice\
 , one is left with trying to predict the battery life from aging studies o
 f limited duration and based on a limited set of operating conditions.\nIn
  this presentation\, a methodology for life prediction based on a physics-
 based model is presented and applied to commercial 2.3 Ah graphite/LiFePO4
  (LFP) batteries. First\, typical aging experiments are described\, along 
 with intermediate nonintrusive checkups and postmortem analyses. The metho
 dology does not require a specific design of experiments\, and therefore e
 xperiments consist of any type of cycling and storage condition\, where pa
 rameters such as current density (cycling)\, state of charge (storage)\, a
 nd temperature vary from one experiment to the other.\nThe aging data coll
 ected at the different checkups are then analyzed using a mathematical mod
 el that does not contain aging phenomena. This analysis allows for identif
 ying and quantifying the different aging sources in the cell at all experi
 mental conditions and all times.\nWith the information gathered from this 
 analysis\, along with the input from postmortem analyses\, it is possible 
 to include aging phenomena in the initial model and make it predictive. In
  our case study\, aging phenomena include side reactions that lead to the 
 growth of a passive film at the solid/liquid interface of both electrodes 
 as well as active-material loss at the negative electrode. Ideally\, a phy
 sical description of each aging phenomenon allows deriving meaningful gove
 rning equations. However\, empirical correlations can be implemented into 
 the model whenever a physical description is neither possible nor availabl
 e. Examples of the life-prediction capability of the aging model are provi
 ded. The advantage of this methodology is that no extrapolation in time is
  needed.\nIn the last part of the talk\, we comment on how this class of m
 odels can be further developed by resorting to “model” experiments. In
  such experiments\, the design is simplified and operating conditions are 
 well-controlled in order to focus on a single source of aging. The aim is 
 to unravel poorly understood aging mechanisms and derive a meaningful set 
 of governing equations that can be implemented in the aging model. The con
 tamination of the negative electrode by transition metal dissolving from t
 he positive electrode is taken as an example.
LOCATION:MEB1B10 http://plan.epfl.ch/?room=ME%20B1%20B10
STATUS:CONFIRMED
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