My Account Log in

1 option

Battery Management Algorithm for Electric Vehicles / by Rui Xiong.

Springer Nature - Springer Energy eBooks 2020 English International Available online

View online
Format:
Book
Author/Creator:
Xiong, Rui, author.
Contributor:
SpringerLink (Online service)
Series:
Energy (Springer-40367)
Language:
English
Subjects (All):
Energy storage.
Automotive engineering.
Automatic control.
Electrical engineering.
Energy Storage.
Automotive Engineering.
Control and Systems Theory.
Electrical Engineering.
Local Subjects:
Energy Storage.
Automotive Engineering.
Control and Systems Theory.
Electrical Engineering.
Physical Description:
1 online resource (XVII, 297 pages) : 193 illustrations, 122 illustrations in color
Edition:
First edition 2020.
Contained In:
Springer eBooks
Place of Publication:
Singapore : Springer Singapore : Imprint: Springer, 2020.
System Details:
text file PDF
Summary:
This book systematically introduces readers to the core algorithms of battery management system (BMS) for electric vehicles. These algorithms cover most of the technical bottlenecks encountered in BMS applications, including battery system modeling, state of charge (SOC) and state of health (SOH) estimation, state of power (SOP) estimation, remaining useful life (RUL) prediction, heating at low temperature, and optimization of charging. The book not only presents these algorithms, but also discusses their background, as well as related experimental and hardware developments. The concise figures and program codes provided make the calculation process easy to follow and apply, while the results obtained are presented in a comparative way, allowing readers to intuitively grasp the characteristics of different algorithms. Given its scope, the book is intended for researchers, senior undergraduate and graduate students, as well as engineers in the fields of electric vehicles and energy storage.
Contents:
Overview of battery and its management
Battery test
Modeling theory of lithium-ion batteries
Battery SOC and SOH estimation
State estimation of battery system
Remaining useful life prediction of lithium-ion batteries
Low-temperature heating and optimal charging methods for lithium-ion batteries
Algorithm development, test and evaluation.
Other Format:
Printed edition:
ISBN:
978-981-15-0248-4
9789811502484
Access Restriction:
Restricted for use by site license.

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

Find

Home Release notes

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Find catalog Using Articles+ Using your account