9781630819040 - battery management systems, volume iii: physics-based methods: 3 de plett, gregory l.; trimboli, m. scott (26 resultados)
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Hardcover. Condición: 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 cov…ers 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.
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Hardback. Condición: New. 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 fo…undations 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.
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Hardback. Condición: New. 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 fo…undations 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.
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Hardback. Condición: New. 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 fo…undations 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.
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Buch. Condición: Neu. Neuware - Battery Management Systems, Volume III: Physics-Based Methods is the third and final volume in a celebrated series, which 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 e…xtend life. It reviews the foundations of electrochemical models of lithium-ion cells and explains how to incorporate these models in state-of-the-art physics-based methods for battery management. Building upon the content in Volumes I and II, this reference helps identify parameter values for physics-based models of a commercial lithium-ion battery cell without requiring cell teardown; demonstrates how to estimate the internal electrochemical state of all cells in a battery pack in a computationally efficient manner during operation using these models; showcases 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 a step-by-step approach of reviewing the use of these models to compute the available power that can be demanded from the battery pack while also maximizing battery service life. The approaches presented in this guide overcome the primary roadblocks to implementing physics-based methods for battery management: the computational complexity roadblock, the parameter-identification roadblock, and the control optimization roadblock. By uncovering the internal physical variables of lithium-ion cells, the operation of the battery up to its fundamental performance limits is enabled, instead of requiring the over-conservative design assumptions used in all present state-of-the art methods based on equivalent-circuit models. This is a strong resource for battery engineers, chemists, researchers, and educators who are interested in advanced battery management.
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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Hardcover. Condición: Brand New. 380 pages. 11.50x8.75x1.00 inches. In Stock.
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Hardback. Condición: New. 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 fo…undations 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.
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Hardcover. Condición: 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 cov…ers 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 our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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Hardcover. Condición: Brand New. 380 pages. 11.50x8.75x1.00 inches. In Stock. This item is printed on demand.
