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Mathematical Modeling of Lithium Batteries: From Electrochemical Models to State Estimator Algorithms - Couverture rigide
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Synopsis
Evaluates and discusses various approaches to form one cohesive methodology for application and future development
Considers recent trends and research to explore their potential and limitations to develop technology and efficient practices
Provides a much-needed coherent framework of battery modeling techniques
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l'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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Mathematical Modeling of Lithium Batteries. From Electrochemical Models to State Estimator Algorithms.
Edité par
Cham, Springer., 2018
ISBN 10 : 3319035266
ISBN 13 : 9783319035260
Ancien ou d'occasion
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Vendeur : Universitätsbuchhandlung Herta Hold GmbH, Berlin, Allemagne
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XIV, 211 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Green Energy and Technology. Sprache: Englisch. N° de réf. du vendeur 1010LB
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Mathematical Modeling of Lithium Batteries: From Electrochemical Models to State Estimator Algorithms (Green Energy and Technology)
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Mathematical Modeling of Lithium Batteries
Edité par
Springer International Publishing AG, CH, 2018
ISBN 10 : 3319035266
ISBN 13 : 9783319035260
Neuf
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Vendeur : Rarewaves.com USA, London, LONDO, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Hardback. Etat : New. 1st ed. 2018. Evaluates and discusses various approaches to form one cohesive methodology for application and future developmentConsiders recent trends and research to explore their potential and limitations to develop technology and efficient practicesProvides a much-needed coherent framework of battery modeling techniques. N° de réf. du vendeur LU-9783319035260
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Mathematical Modeling of Lithium Batteries (eng)
impression à la demandeVendeur : Brook Bookstore On Demand, Napoli, NA, Italie
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Etat : new. Questo è un articolo print on demand. N° de réf. du vendeur f86cddddcecc22603a42030c7ec56626
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Mathematical Modeling of Lithium Batteries
Edité par
Springer International Publishing AG, CH, 2018
ISBN 10 : 3319035266
ISBN 13 : 9783319035260
Neuf
Couverture rigide
Vendeur : Rarewaves.com UK, London, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Hardback. Etat : New. 1st ed. 2018. Evaluates and discusses various approaches to form one cohesive methodology for application and future developmentConsiders recent trends and research to explore their potential and limitations to develop technology and efficient practicesProvides a much-needed coherent framework of battery modeling techniques. N° de réf. du vendeur LU-9783319035260
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Mathematical Modeling of Lithium Batteries
ISBN 10 : 3319035266
ISBN 13 : 9783319035260
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware - This book is unique to be the only one completely dedicated for battery modeling for all components of battery management system (BMS) applications. The contents of this book compliment the multitude of research publications in this domain by providing coherent fundamentals. An explosive market of Li ion batteries has led to aggressive demand for mathematical models for battery management systems (BMS). Researchers from multi-various backgrounds contribute from their respective background, leading to a lateral growth. Risk of this runaway situation is that researchers tend to use an existing method or algorithm without in depth knowledge of the cohesive fundamentals-often misinterpreting the outcome. It is worthy to note that the guiding principles are similar and the lack of clarity impedes a significant advancement. A repeat or even a synopsis of all the applications of battery modeling albeit redundant, would hence be a mammoth task, and cannot be done in a single offering. Theauthors believe that a pivotal contribution can be made by explaining the fundamentals in a coherent manner. Such an offering would enable researchers from multiple domains appreciate the bedrock principles and forward the frontier.Battery is an electrochemical system, and any level of understanding cannot ellipse this premise. The common thread that needs to run across-from detailed electrochemical models to algorithms used for real time estimation on a microchip-is that it be physics based. Build on this theme, this book has three parts. Each part starts with developing a framework-often invoking basic principles of thermodynamics or transport phenomena-and ends with certain verified real time applications. The first part deals with electrochemical modeling and the second with model order reduction. Objective of a BMS is estimation of state and health, and the third part is dedicated for that. Rules for state observers are derived from a generic Bayesian framework, and healthestimation is pursued using machine learning (ML) tools. A distinct component of this book is thorough derivations of the learning rules for the novel ML algorithms. Given the large-scale application of ML in various domains, this segment can be relevant to researchers outside BMS domain as well.The authors hope this offering would satisfy a practicing engineer with a basic perspective, and a budding researcher with essential tools on a comprehensive understanding of BMS models. 228 pp. Englisch. N° de réf. du vendeur 9783319035260
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Mathematical Modeling of Lithium Batteries
Edité par
Springer International Publishing, 2018
ISBN 10 : 3319035266
ISBN 13 : 9783319035260
Neuf
Couverture rigide
Vendeur : moluna, Greven, Allemagne
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Gebunden. Etat : New. N° de réf. du vendeur 37660852
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Mathematical Modeling of Lithium Batteries: From Electrochemical Models to State Estimator Algorithms (Green Energy and Technology)
Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
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Hardcover. Etat : New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book. N° de réf. du vendeur ERICA77333190352666
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Mathematical Modeling of Lithium Batteries: From Electrochemical Models to State Estimator Algorithms (Green Energy and Technology)
Vendeur : Books Puddle, New York, NY, Etats-Unis
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Etat : New. pp. 300. N° de réf. du vendeur 26372848686
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Mathematical Modeling of Lithium Batteries
ISBN 10 : 3319035266
ISBN 13 : 9783319035260
Neuf
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is unique to be the only one completely dedicated for battery modeling for all components of battery management system (BMS) applications. The contents of this book compliment the multitude of research publications in this domain by providing coherent fundamentals. An explosive market of Li ion batteries has led to aggressive demand for mathematical models for battery management systems (BMS). Researchers from multi-various backgrounds contribute from their respective background, leading to a lateral growth. Risk of this runaway situation is that researchers tend to use an existing method or algorithm without in depth knowledge of the cohesive fundamentals¿often misinterpreting the outcome. It is worthy to note that the guiding principles are similar and the lack of clarity impedes a significant advancement. A repeat or even a synopsis of all the applications of battery modeling albeit redundant, would hence be a mammoth task, and cannot be done in a single offering. Theauthors believe that a pivotal contribution can be made by explaining the fundamentals in a coherent manner. Such an offering would enable researchers from multiple domains appreciate the bedrock principles and forward the frontier.Battery is an electrochemical system, and any level of understanding cannot ellipse this premise. The common thread that needs to run across¿from detailed electrochemical models to algorithms used for real time estimation on a microchip¿is that it be physics based. Build on this theme, this book has three parts. Each part starts with developing a framework¿often invoking basic principles of thermodynamics or transport phenomenäand ends with certain verified real time applications. The first part deals with electrochemical modeling and the second with model order reduction. Objective of a BMS is estimation of state and health, and the third part is dedicated for that. Rules for state observers are derived from a generic Bayesian framework, and healthestimation is pursued using machine learning (ML) tools. A distinct component of this book is thorough derivations of the learning rules for the novel ML algorithms. Given the large-scale application of ML in various domains, this segment can be relevant to researchers outside BMS domain as well.The authors hope this offering would satisfy a practicing engineer with a basic perspective, and a budding researcher with essential tools on a comprehensive understanding of BMS models.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 228 pp. Englisch. N° de réf. du vendeur 9783319035260
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