Mathematical Modeling of Lithium Batteries: From Electrochemical Models to State Estimator Algorithms
Language: English
Published by Springer, 2018
- Hardcover
- New
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
AbeBooks seller since January 6, 2003
Condition: New
£ 198.89
Quantity: 2 available
Add to basketItem description from seller
228 pages. 9.25x6.10x0.80 inches. In Stock.
Seller Inventory # x-3319035266
- Title
- Mathematical Modeling of Lithium Batteries: From Electrochemical Models to State Estimator Algorithms
- Author
- Hariharan, Krishnan S. (Author)/ Tagade, Piyush (Author)/ Ramachandran, Sanoop (Author)
- Publisher
- Springer
- Publication year
- 2018
- Condition
- Brand New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3319035266
- ISBN 13
- 9783319035260
- Item weight
- 0.5 kilograms
- Series
- Book 193 of 432: Green Energy and Technology
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.
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Revaluation Books
Exeter, United Kingdom
AbeBooks seller since January 6, 2003
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Edward Bowditch Ltd
Exstowe, Exton
Exeter, United Kingdom EX3 0PP
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