Seminars

Dr. Resmi Suresh, a postdoctoral scholar at Columbia University, New York,

DateWednesday, 05 September 2018
Time3:00 PM
VenueCHE Seminar Hall
Rechargeable Batteries: A Systems Engineering Approach
05th September 2018, Wednesday, 03:00‐04:00 pm ChE Seminar hall

Abstract:

In the present world of electric vehicles and portable electronics, high-quality rechargeable batteries are of supreme importance. Lithium-ion batteries, in particular, have been commercially viable due to their high energy densities and long lifetimes. However, they are subject to both performance and capacity degradations which impact their lifetime irreversibly. Although it is impossible to reclaim the lost capacity, periodic diagnosis, subsequent management and control can prolong their lifetime. This seminar would focus on an investigation and development of techniques for battery performance enhancement. A framework for on-line battery management system to improve performance and life of a battery is considered, focusing mainly on its three major components: model, controller and diagnostic tool. A generalized approach to model various capacity fade mechanisms and a model predictive controller implementation that aims to find an optimal balance between charging time and calendar life will be discussed. Finally, a novel technique for rapid impedance measurement based on multiple chirp signals will be presented.

 

Short-Bio:

Dr. Resmi Suresh is a post-doctoral research fellow with Prof. Venkat Venkatasubramanian in the Department of Chemical Engineering, Columbia University, New York. She completed her Ph.D from Indian Institute of Technology, Madras (IIT Madras), under the supervision of Prof. Raghunathan Rengaswamy in 2017.  She comes from a unique process systems engineering (PSE) background. During her doctoral studies, she primarily focused on applications of PSE ideas like optimization, fault diagnosis and control of rechargeable battery systems. She is currently working on solving various problems in the domain of systemic risk analysis for various industrial and business systems using PSE and data science concepts.

 

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