This book shows you how to use physics-based models of battery cells in a computationally efficient way for optimal battery-pack management and control to maximize battery-pack performance and extend life. You’ll understand the state of the art in physics-based methods for battery management and know where improvements beyond present state-of-art can still be made. With a strong emphasis on software and control aspects, the book also shows you how to overcome the primary roadblocks to implementing physics-based method for battery management: the computational-complexity roadblock, the parameter-identification roadblock, and the control-optimization roadblock.
"synopsis" may belong to another edition of this title.
Gregory L. Plett received his B.Eng. degree in Computer Systems Engineering from Carleton University and his M.S. and Ph.D. degrees in Electrical Engineering from Stanford University. He is currently a professor for the Department of Electrical and Computer Engineering at the University of Colorado, Colorado Springs and a senior member of the IEEE and life member of the Electrochemical Society.
M. Scott Trimboli received his B.S in Engineering Science from the United States Air Force Academy in 1980, his M.S in Engineering Mechanics from Columbia University in 1981 and his Ph.D. in Control Engineering from the University of Oxford. He previously served as an exchange scientist with the German Aerospace Research Establishment (DLR) in Göttingen, Germany. He is an Associate Professor of Electrical and Computer Engineering at the University of Colorado Colorado Springs.
"About this title" may belong to another edition of this title.
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # GB-9781630819040
Quantity: 4 available
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: New. Seller Inventory # 46869526-n
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: New. Seller Inventory # 46869526-n
Quantity: Over 20 available
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition. Seller Inventory # 46869526
Seller: Chiron Media, Wallingford, United Kingdom
Hardcover. Condition: New. Seller Inventory # 6666-GRD-9781630819040
Quantity: 4 available
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Condition: New. In. Seller Inventory # ria9781630819040_new
Quantity: Over 20 available
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New. Seller Inventory # 396553956
Quantity: 3 available
Seller: Brook Bookstore On Demand, Napoli, NA, Italy
Condition: new. Seller Inventory # N0JD5S7P7G
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: As New. Unread book in perfect condition. Seller Inventory # 46869526
Quantity: Over 20 available
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condition: new. Hardcover. This book -- the third and final volume in a series describing battery-management systems shows you how to use physics-based models of battery cells in a computationally efficient way for optimal battery-pack management and control to maximize battery-pack performance and extend life. It covers the foundations of electrochemical model-based battery management system while introducing and teaching the state of the art in physics-based methods for battery management. Building upon the content in volumes I and II, the book helps you identify parameter values for physics-based models of a commercial lithium-ion battery cell without requiring cell teardown; shows you how to estimate the internal electrochemical state of all cells in a battery pack in a computationally efficient way during operation using these physics-based models; demonstrates the use the models plus state estimates in a battery management system to optimize fast-charge of battery packs to minimize charge time while also maximizing battery service life; and takes you step-by-step through the use models to optimize the instantaneous power that can be demanded from the battery pack while also maximizing battery service life. The book also demonstrates how to overcome the primary roadblocks to implementing physics-based method for battery management: the computational-complexity roadblock, the parameter-identification roadblock, and the control-optimization roadblock. It also uncovers the fundamental flaw in all present state of art methods and shows you why all BMS based on equivalent-circuit models must be designed with over-conservative assumptions. This is a strong resource for battery engineers, chemists, researchers, and educators who are interested in advanced battery management systems and strategies based on the best available understanding of how battery cells operate. Demonstrates how to use physics-based models of battery cells in a computationally efficient framework for optimal battery-pack management to maximize battery performance and extend life. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781630819040