iHorizon Enabled Energy Management for Electrified Vehicles

Download or Read online iHorizon Enabled Energy Management for Electrified Vehicles full in PDF, ePub and kindle. This book written by Clara Marina Martinez and published by Butterworth-Heinemann which was released on 11 September 2018 with total pages 431. We cannot guarantee that iHorizon Enabled Energy Management for Electrified Vehicles book is available in the library, click Get Book button to download or read online books. Join over 650.000 happy Readers and READ as many books as you like.

iHorizon Enabled Energy Management for Electrified Vehicles
Author :
Publisher : Butterworth-Heinemann
Release Date :
ISBN : 9780128150115
Pages : 431 pages
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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. Addresses the level of integration of electrified powertrains Presents the state-of-the-art of electrified vehicle energy control Offers a novel concept able to perform dynamic speed profile and energy demand prediction

iHorizon Enabled Energy Management for Electrified Vehicles

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

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