國立虎尾科技大學 |

Battery Management Algorithm for Electric Vehicles

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Battery Management Algorithm for Electric Vehicles / by Rui Xiong.
Author:	Xiong, Rui.
Description:	XVII, 297 p. 193 illus., 122 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Energy storage. -
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. - 1st ed. 2020. - XVII, 297 p. 193 illus., 122 illus. in color.online resource.

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:

677971
Energy storage.

LC Class. No.: TJ165

Dewey Class. No.: 621.3126

Battery Management Algorithm for Electric Vehicles
LDR:02671nam a22003975i 4500 001 1025042
003 DE-He213
005 20200703140434.0
007 cr nn 008mamaa
008 210318s2020 si | s |||| 0|eng d
020 $a 9789811502484 $9 978-981-15-0248-4
024 7 $a 10.1007/978-981-15-0248-4 $2 doi
035 $a 978-981-15-0248-4
050 4 $a TJ165
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
100 1 $a Xiong, Rui. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1225116
245 1 0 $a Battery Management Algorithm for Electric Vehicles $h [electronic resource] / $c by Rui Xiong.
250 $a 1st ed. 2020.
264 1 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2020.
300 $a XVII, 297 p. 193 illus., 122 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
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 Energy storage. $3 677971
650 0 $a Automotive engineering. $3 1104081
650 0 $a Control engineering. $3 1249728
650 0 $a Electrical engineering. $3 596380
650 1 4 $a Energy Storage. $3 784791
650 2 4 $a Automotive Engineering. $3 683772
650 2 4 $a Control and Systems Theory. $3 1211358
650 2 4 $a Electrical Engineering. $3 768742
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9789811502477
776 0 8 $i Printed edition: $z 9789811502491
776 0 8 $i Printed edition: $z 9789811502507
856 4 0 $u https://doi.org/10.1007/978-981-15-0248-4
912 $a ZDB-2-ENE
912 $a ZDB-2-SXEN
950 $a Energy (SpringerNature-40367)
950 $a Energy (R0) (SpringerNature-43717)