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Mathematical Modeling of Lithium Batteries

From Electrochemical Models to State Estimator Algorithms
LivreCartonné
Classement des ventes 7589dans
CHF153.00

Description

This book is unique to be the only one completely dedicated for battery modeling for all components of battery management system (BMS) applications.

Détails

ISBN/GTIN978-3-319-79138-8
Type de produitLivre
ReliureCartonné
ÉditeurSpringer
Date de parution06.06.2019
EditionSoftcover reprint of the original 1st ed. 2018
SérieGreen Energy and Technology
Pages211 pages
LangueAnglais
DimensionsLargeur 155 mm, Hauteur 235 mm
Poids355 g
IllustrationsXIV, 211 p. 73 illus., 34 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen
N° article6885645
CataloguesBuchzentrum
Source des données n°31771761
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Série

Auteur

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 electric vehicle (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&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, Republic 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 BSc degree (2001) from the University of Calicut, Kerala, India. He obtained a Masters degree (2003) and PhD (2009) in Physics from the Indian Institute of Technology Madras, India. This was followed by two postdoctoral stints at the Tokyo Metropolitan University (2011), 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, Bangalore, India. 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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Mot-clé

VLB objectif lecture principal