Modeling and Simulation in Energy Storage
| Program start date | Application deadline |
| 2022-01-03 | - |
Program Overview
Modeling and Simulation in Energy Storage
The Modeling and Simulation in Energy Storage program is a comprehensive course that focuses on the fundamentals of electrochemical and transport mechanisms in lithium-ion batteries. The program aims to provide a detailed understanding of the underlying reaction and transport processes that affect the performance, life, and safety of lithium-ion batteries.
Course Overview
Energy storage is a key enabler in the energy sustainability ecosystem, and lithium-ion batteries have transformed the modern rechargeable world. The importance of modeling and simulation in accelerating innovation and design toward improved performance, safety, and life of lithium-ion batteries is critical. This course will lay out the details of a comprehensive computational modeling framework of thermo-electrochemical interactions in lithium-ion batteries toward predicting performance life and safety.
Target Audience
The program is designed for:
- Executives, engineers, and researchers from manufacturing, service, and government organizations, including R&D laboratories
- Students at all levels (BTech/MSc/MTech/PhD) or faculty from reputed academic institutions and technical institutions
Program Details
Dates and Time
The program will take place from January 03 to January 09, 2022, from 7:30 to 9:30 PM IST (9:00 to 11:00 AM, US EST).
Organizers
The program is organized by the Department of Mechanical Engineering and Centre of Educational Technology, Indian Institute of Technology, Guwahati.
Course Schedule
The program will cover the following topics:
Day 1: Jan. 03
- Lecture 1: Introduction to the fundamentals of electrochemical and transport mechanisms in lithium-ion batteries
- Lecture 2: Basics of how the underlying transport and electrochemical mechanisms affect performance, life, and safety of lithium-ion batteries
Day 2: Jan. 04
- Lecture 3: Coupled governing differential equations that characterize the electrochemical and transport processes in Li-ion batteries
- Lecture 4: Thermo-electrochemical coupled modeling framework for Li-ion battery performance, safety, and degradation
Day 3: Jan. 05
- Lecture 5: Computational modeling and analysis for Li-ion battery performance prediction
- Lecture 6: Computational modeling and analysis of coupled thermo-electrochemical interaction
Day 4: Jan. 06
- Lecture 7: Computational modeling of Li-ion battery thermal safety
- Lecture 8: Analysis of Li-ion battery thermal safety under abuse conditions of thermal and electrochemical extremes
Day 5: Jan. 07
- Lecture 9: Computational modeling of Li-ion battery degradation due to lithium plating
- Lecture 10: Analysis of lithium plating under operational extremes for Li-ion batteries
Day 6: Jan. 08
- Tutorial 1: Modeling and analysis of Li-ion battery performance
Day 7: Jan. 09
- Tutorial 2: Modeling and analysis of Li-ion battery thermal safety
Course Fees
The program fees are as follows:
- Participants from abroad: US $100
- Industry/Research Organizations: Rs. 4000
- Academic Institutions:
- Student Participants: Rs. 200
- Faculty Participants: Rs. 2000
Faculty
The program will be taught by:
- Prof. Partha P. Mukherjee, Professor of Mechanical Engineering at Purdue University
- Prof. Amaresh Dalal, Professor of Mechanical Engineering at Indian Institute of Technology, Guwahati
Prof. Partha P. Mukherjee
Prof. Mukherjee's research interests are focused on mesoscale physics and stochastics of transport, chemistry, and materials interactions, including an emphasis on the broad spectrum of energy storage and conversion. He has received several awards, including Scialog Fellows' recognition for advanced energy storage, University Faculty Scholar, and Faculty Excellence for Early Career Research awards from Purdue University.
Prof. Amaresh Dalal
Prof. Dalal's research interests are in the area of Computational Fluid Dynamics and Heat Transfer, Finite Volume Methods and Unstructured Grid Techniques, Multiphase Flows, Natural and Mixed Convection Flows. He is currently developing a general-purpose, versatile, and robust computational fluid dynamics solver over hybrid unstructured grid, which can solve a wide range of real-life fluid flow, heat transfer, and problems involving transport phenomena over complex geometries.
