Dongpu Cao – författare

Modelling, Dynamics and Control of Electrified Vehicles provides a systematic overview of EV-related key components, including batteries, electric motors, ultracapacitors and system-level approaches, such as energy management systems, multi-source energy optimization, transmission design and control, braking system control and vehicle dynamics control. In addition, the book covers selected advanced topics, including Smart Grid and connected vehicles. This book shows how EV work, how to design them, how to save energy with them, and how to maintain their safety.

The book aims to be an all-in-one reference for readers who are interested in EVs, or those trying to understand its state-of-the-art technologies and future trends.

Offers a comprehensive knowledge of the multidisciplinary research related to EVs and a system-level understanding of technologies Provides the state-of-the-art technologies and future trends Covers the fundamentals of EVs and their methodologies Written by successful researchers that show the deep understanding of EVs

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

Advanced Driver Intention Inference: Theory and Design describes one of the most important function for future ADAS, namely, the driver intention inference. The book contains the state-of-art knowledge on the construction of driver intention inference system, providing a better understanding on how the human driver intention mechanism will contribute to a more naturalistic on-board decision system for automated vehicles.

Features examples of using machine learning/deep learning to build industry products Depicts future trends for driver behavior detection and driver intention inference Discuss traffic context perception techniques that predict driver intentions such as Lidar and GPS