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Battery Management Systems: Physics-Based Methods (3)

Battery Management Systems: Physics-Based Methods (3)

Battery Management Systems: Physics-Based Methods (3)
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Battery Management Systems: Physics-Based Methods (3) Hardback - 2026

by Plett, Gregory L.; Trimboli, M. Scottus

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  • Title Battery Management Systems: Physics-Based Methods (3)
  • Author Plett, Gregory L.; Trimboli, M. Scottus
  • Binding Hardback
  • Condition New
  • Volumes 1
  • Language ENG
  • Publisher Artech House Publishers
  • Publication date 2026-03-19
  • Bookseller's Inventory # 46869526-n
  • ISBN 9781630819040 / 1630819042
  • Weight 2.89 lbs (1.31 kg)
  • Dimensions 11.15 x 8.67 x 1.02 in (28.32 x 22.02 x 2.59 cm)
  • Category Technology & Industrial Arts
  • Quantity available 1

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Reader reviews for Battery Management Systems: Physics-Based Methods (3)

From the publisher

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 extend 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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