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iHorizon-enabled energy management f...

Martinez, Clara Marina.

iHorizon-enabled energy management for electrified vehicles

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	iHorizon-enabled energy management for electrified vehicles/ Clara Marina Martinez, Dongpu Cao.
作者:	Martinez, Clara Marina.
其他作者:	Cao, Dongpu,
出版者:	Oxford, UK :Elsevier Ltd. : : 2019.,
面頁冊數:	1 online resource :ill. :
標題:	Electric vehicles. -
電子資源:	https://www.sciencedirect.com/science/book/9780128150108
ISBN:	9780128150115 (electronic bk.)

iHorizon-enabled energy management for electrified vehicles
Martinez, Clara Marina.

iHorizon-enabled energy management for electrified vehicles[electronic resource] /Clara Marina Martinez, Dongpu Cao. - Oxford, UK :Elsevier Ltd. :2019. - 1 online resource :ill.

Includes bibliographical references and index.

iHorizon-Enabled Energy Management for Electrified Vehicles proposes a realistic solution that assumes only scarce information is available prior to the start of a journey and that limited computational capability can be allocated for energy management. This type of framework exploits the available resources and closely emulates optimal results that are generated with an offline global optimal algorithm. In addition, the authors consider the present and future of the automotive industry and the move towards increasing levels of automation. Driver vehicle-infrastructure is integrated to address the high level of interdependence of hybrid powertrains and to comply with connected vehicle infrastructure. This book targets upper-division undergraduate students and graduate students interested in control applied to the automotive sector, including electrified powertrains, ADAS features, and vehicle automation.

ISBN: 9780128150115 (electronic bk.)Subjects--Topical Terms:

639235
Electric vehicles.
Index Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: TL220

Dewey Class. No.: 629.22/93

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520 $a iHorizon-Enabled Energy Management for Electrified Vehicles proposes a realistic solution that assumes only scarce information is available prior to the start of a journey and that limited computational capability can be allocated for energy management. This type of framework exploits the available resources and closely emulates optimal results that are generated with an offline global optimal algorithm. In addition, the authors consider the present and future of the automotive industry and the move towards increasing levels of automation. Driver vehicle-infrastructure is integrated to address the high level of interdependence of hybrid powertrains and to comply with connected vehicle infrastructure. This book targets upper-division undergraduate students and graduate students interested in control applied to the automotive sector, including electrified powertrains, ADAS features, and vehicle automation.
588 0 $a Online resource; title from PDF title page (EBSCO, viewed September 18, 2018).
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