Date: May 10, 2019 ǀ 14:00-15:00
Location: Auditorium, TUM Institute for Advanced Study, Lichtenbergstrasse 2 a, 85748 Garching, Tel +49.89.289.10550
Organization: TUM-IAS and Rudolf Diesel Industry Fellow Dr. Filippo Maglia (BMW Group)
Admission is free. No registration required.
Title: Determination of parameters for physics-based models of Li-ion batteries.
Speaker: Dr. Charles Delacourt, Laboratoire de Réactivité et Chimie des Solides, CNRS UMR 7314, Université de Picardie Jules Verne, 80039 Amiens Cedex, France.
Charles has been a CNRS researcher at Laboratoire de Réactivité et Chimie des Solides (France) since 2007. He completed his PhD in materials chemistry at Université de Picardie Jules Verne (Amiens, France), in 2005. He was then a Postdoctoral fellow for two years in Prof. John Newman’s group at University of California, Berkeley. Charles has authored about 57 peer-reviewed papers and 3 patents, and got awarded several distinctions, among which the "Carl Wagner Medal of Excellence in Electrochemical Engineering of the European Federation of Chemical Engineering" (2011) and the "Oronzio and Niccolò De Nora Foundation Prize of ISE on Applied Electrochemistry" (2009). Current effort is the development of physics-based mathematical models for studying lithium-ion batteries, with a focus on electrolyte transport properties and battery degradation. His research is in close collaboration with French automotive industry.
Abstract: Li-ion battery is the energy-storage technology that is used in the majority of today’s electric vehicles (EVs). This is thanks to a high energy density along with a long lifetime, compared with other battery technologies. Still, EV market penetration is made difficult both by the limited battery performance, which limits vehicle mileage, and by the battery performance decay over time, which limits vehicle service life. Physics-based modeling is quite powerful in order to understand performance limitations of an actual battery under a specified usage. It is also possible to predict the occurrence of degradation phenomena, such as Li plating during charge. This type of modeling is well-suited to aid in cell design, by readily answering a number of “what-if” questions aiming at finding an optimum for performance (energy/power) while preventing side effects from happening. In addition to making sure that the physical description of phenomena is meaningful enough, accurate determination of model parameters is crucial, and it often turns out to be the main Achille’s heel across modeling literature. During the presentation, I will provide an overview of the different experimental methods we have been working on over the past years in order to measure model parameters, would they be geometric, kinetic, or transport-related:
• Electrode tortuosity measurements using an electrochemical method.
• Intermittent electrochemical titration methods to determine insertion rate constant and diffusion coefficient of an active material
• Electrochemical-based measurements of electrolyte transport properties Next step will be to discuss how predictive a physics-based model can be, once fed with proper values of model parameters. I will exemplify my case on a set of industry-grade graphite electrodes with different designs, ranging from ca. 25 to 120 µm in terms of thickness and ca. 12 to 45% in terms of porosity.