Mathematical Modeling of Lithium Batteries: From Electrochemical Models to State Estimator Algorithms (Green Energy and Technology)

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9783319035260: Mathematical Modeling of Lithium Batteries: From Electrochemical Models to State Estimator Algorithms (Green Energy and Technology)

Compiling state of the art approaches in mathematical modeling of lithium batteries, this monograph develops a theoretical framework of various modeling approaches, and discusses recent trends in research and their applications and limitations. It draws together the plethora of existing published research, and provides a much-needed coherent framework of battery modeling techniques. The book explores electrochemical models (EM), electrochemical impedance spectroscopy models (EIS), equivalent circuit models (ECM) and reduced order models (ROM), as well as fundamental theory, equations, model development and solution methodology to algorithms. Providing an invaluable resource to industrial R & D departments and electric vehicle manufacturers, this book is also intended for battery consortiums and academic research groups involved in battery modelling.

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About the Author:

Dr. Hariharan’s research focuses on mathematical modeling of lithium batteries for industrial applications. During his research career, he has had the opportunity to develop electrochemical, impedance spectroscopy as well as equivalent circuit models for lithium batteries. In addition, Dr. Hariharan was also involved in developing battery state estimator algorithms and thermal analysis of cells as well as battery packs. During his tenure with General Motors R&D, he collaborated with algorithm engineers responsible for implementing on-board state estimators for EV programs. His research experience with various approaches in battery modeling would enable a successful monograph on state of the art in this emerging area.

Piyush Tagade is a Research Staff Member at Samsung Advanced Institute of Technology, Samsung R and D Institute Bangalore, India. He holds a PhD degree in Aerospace Engineering from Indian Institute of Technology Bombay, India. Before joining Samsung, he was a postdoctoral research associate at Korea Advanced Institute of Science and Technology, Rep. of Korea and Massachusetts Institute of Technology, USA. In his scientific research work he is mostly concerned with developing efficient Bayesian framework for large scale system simulators. His areas of interest include Bayesian inference, uncertainty propagation, data assimilation, optimization and machine learning.

Sanoop Ramachandran was born in Kerala, India in 1981. He got his B. Sc. degree (2001) from the University of Calicut. He obtained a Masters degree (2003) and Ph. D. (2009) in Physics from the Indian Institute of Technology Madras, India.  This was followed by two postdoctoral stints at the Tokyo Metropolitan University (2011)  in Tokyo, Japan and the Universite Libre de Bruxelles (2012), Brussels, Belgium.  From late 2012 till date, he has been working as a Staff research scientist at the Samsung R&D Institute India - Bangalore. He is an author of over 20 journal publications, several patents

ideas and book chapters. His general research interests are in the field of soft-matter, electrochemistry as well as the use of mathematical modelling and computational tools for applied industrial research.

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