نظرة عامة على البرنامج

Modeling and Simulation in Energy Storage

The Modeling and Simulation in Energy Storage program is designed to provide a comprehensive understanding of the fundamentals of electrochemical and transport mechanisms in lithium-ion batteries. This program aims to equip participants with the knowledge and skills necessary to model and simulate the performance, safety, and life of lithium-ion batteries.

Program Overview

Energy storage is a critical component of 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 cannot be overstated. This program 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 (B.Tech, M.Sc, M.Tech, Ph.D.) or faculty from reputed academic institutions and technical institutions

Program Details

Dates and Time

The program will take place from January 03 to 09, 2022, with sessions scheduled 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 the Centre of Educational Technology, Indian Institute of Technology, Guwahati.

Program Schedule

The program schedule includes the following lectures and tutorials:

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 course 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 led 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 and the 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, and 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.