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Springer - Battery Management Algorithm for Electric Vehicles

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Description

Master the technical foundations of electric vehicle technology with this comprehensive guide from Springer. This book provides a systematic introduction to the core algorithms required for effective Battery Management Systems (BMS). It is designed to help readers navigate the primary technical bottlenecks found in modern BMS applications. Readers will gain a deep understanding of battery system modeling and essential estimation techniques, including State of Charge (SOC), State of Health (SOH), and State of Power (SOP). The text also covers advanced topics like Remaining Useful Life (RUL) prediction, low-temperature heating solutions, and charging optimization strategies. Beyond theoretical algorithms, this resource discusses the necessary background, experimental data, and hardware developments that bring these systems to life. It serves as a practical reference for anyone looking to understand the mathematical and physical processes that keep electric vehicle batteries running safely and efficiently.

Key Features

Covers essential BMS algorithms including State of Charge (SOC) and State of Health (SOH) estimation for improved battery monitoring.

Provides detailed guidance on State of Power (SOP) estimation and Remaining Useful Life (RUL) prediction to extend vehicle longevity.

Addresses critical technical bottlenecks such as battery system modeling and optimization of charging processes.

Includes practical insights into low-temperature heating solutions to maintain battery performance in various climates.

Discusses the relationship between theoretical algorithms, experimental results, and recent hardware developments.

Offers a systematic approach to understanding the background and application of battery management in electric vehicles.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
08 October 2019
Listed Since
13 August 2019

Barcode

No barcode data available

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