東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Battery management algorithm for ele...

Xiong, Rui.

Linked to FindBook

Google Book

Amazon

博客來

Battery management algorithm for electric vehicles

Record Type:	Electronic resources : Monograph/item
Title/Author:	Battery management algorithm for electric vehicles/ by Rui Xiong.
Author:	Xiong, Rui.
Published:	Singapore :Springer Singapore : : 2020.,
Description:	xvii, 297 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer eBooks
Subject:	Battery management systems. -
Online resource:	https://doi.org/10.1007/978-981-15-0248-4
ISBN:	9789811502484

Battery management algorithm for electric vehicles
Xiong, Rui.

Battery management algorithm for electric vehicles[electronic resource] /by Rui Xiong. - Singapore :Springer Singapore :2020. - xvii, 297 p. :ill. (some col.), digital ;24 cm.

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.

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.

ISBN: 9789811502484

Standard No.: 10.1007/978-981-15-0248-4doiSubjects--Topical Terms:

3443770
Battery management systems.

LC Class. No.: TL220 / .X56 2020

Dewey Class. No.: 621.3126

Battery management algorithm for electric vehicles
LDR:02321nmm a2200325 a 4500 001 2213852
003 DE-He213
005 20200221172737.0
006 m d
007 cr nn 008maaau
008 201118s2020 si s 0 eng d
020 $a 9789811502484 $q (electronic bk.)
020 $a 9789811502477 $q (paper)
024 7 $a 10.1007/978-981-15-0248-4 $2 doi
035 $a 978-981-15-0248-4
040 $a GP $c GP
041 0 $a eng
050 4 $a TL220 $b .X56 2020
072 7 $a THRH $2 bicssc
072 7 $a TEC031000 $2 bisacsh
072 7 $a THY $2 thema
082 0 4 $a 621.3126 $2 23
090 $a TL220 $b .X6 2020
100 1 $a Xiong, Rui. $3 3443769
245 1 0 $a Battery management algorithm for electric vehicles $h [electronic resource] / $c by Rui Xiong.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2020.
300 $a xvii, 297 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a 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.
520 $a 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.
650 0 $a Battery management systems. $3 3443770
650 0 $a Electric vehicles $x Batteries. $3 2131825
650 1 4 $a Energy Storage. $3 1532778
650 2 4 $a Automotive Engineering. $3 928032
650 2 4 $a Control and Systems Theory. $3 3381515
650 2 4 $a Electrical Engineering. $3 1001838
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
856 4 0 $u https://doi.org/10.1007/978-981-15-0248-4
950 $a Energy (Springer-40367)