Energy-Efficient Driving of Road Vehicles

Toward Cooperative, Connected, and Automated Mobility

By: Antonio Sciarretta, Ardalan Vahidi

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Paperback | 15 August 2020

At a Glance

Paperback
316 Pages

Dimensions(cm)
23.5 x 15.5 x 1.68

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$173.32

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This book elaborates the science and engineering basis for energy-efficient driving in conventional and autonomous cars. After covering the physics of energy-efficient motion in conventional, hybrid, and electric powertrains, the book chiefly focuses on the energy-saving potential of connected and automated vehicles. It reveals how being connected to other vehicles and the infrastructure enables the anticipation of upcoming driving-relevant factors, e.g. hills, curves, slow traffic, state of traffic signals, and movements of nearby vehicles. In turn, automation allows vehicles to adjust their motion more precisely in anticipation of upcoming events, and to save energy. Lastly, the energy-efficient motion of connected and automated vehicles could have a harmonizing effect on mixed traffic, leading to additional energy savings for neighboring vehicles. Building on classical methods of powertrain modeling, optimization, and optimal control, the book further develops the theory of energy-efficient driving. In addition, it presents numerous theoretical and applied case studies that highlight the real-world implications of the theory developed. The book is chiefly intended for undergraduate and graduate engineering students and industry practitioners with a background in mechanical, electrical, or automotive engineering, computer science or robotics.

Industry Reviews

"The book's structure is very adequate. The way it is written is understandable for beginners, and the concepts are illustrated with suitable examples. Many theoretical concepts are formally formulated and explained with sufficient concreteness, making it possible to follow the book without having to use supplementary texts. ... It's an adequate text for a course on efficient energy mobility with support in robotics systems." (Jose Carlos Moreno Ubeda, Computing Reviews, November 3, 2020)

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