Artificial Intelligence Applied in Smart Electric Vehicles: Towards Eco-Driving for Improved Energy Economy

Dear Colleagues,

Research on control and energy management schemes for electric vehicles (EVs) with multi-configurations has been ongoing for over 30 years, slowly moving towards intelligent EV methods underpinned by evolving advanced control methods, communication and sensing techniques, and Internet of Vehicles (IoVs). Smart EVs require resilient schemes that balance the desired control effect with the computational expense. However, many sophisticated methods are currently not suitable for application in smart EVs. As one hot spot of the research on personification decision, artificial intelligence (AI) has been broadly and meticulously studied, as it presents a huge potential in EV control and energy management implementation. Benefiting from superior ability in regression and classification analysis, AI methods pave new pathways to the state-of-art multi-scale control and energy management in EVs, e.g., AI-based battery degradation prediction, AI-based motion plans for automatic driving, etc. Moreover, AI-based schemes also have significant potential to overcome many of the barriers facing energy-saving in EVs.  

To inspire novel AI-based applications in smart EVs towards eco-driving, this Special Issue will seek fantastic solutions among high-quality submissions. The topics of interest cover AI-based control or energy management methods aiming at eco-driving for all-range configurations in EVs, including pure EVs, hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and fuel cell vehicles (FCVs).  

The suggested topics include, but are not limited to:   

• AI-based control strategies for pure EVs, HEVs, PHEVs, FCVs;
• AI-based multi-scale energy management in EVs, e.g. energy management problems in energy storage systems (battery state estimation, battery degradation prediction), powertrains, and vehicle dynamics;
• AI-based eco-driving assistant systems for pure EVs, HEVs, PHEVs, FCVs;
• AI-based control strategies in automatic driving with target to improve energy economy;
• AI-based vehicle-environment co-operation schemes for eco-driving in pure EVs, HEVs, PHEVs, FCVs;
• AI-based human-vehicle co-operation schemes for eco-driving in pure EVs, HEVs, PHEVs, FCVs;
• AI-based EV fleet control methods for eco-driving.

Dr. Yuanjian Zhang
Prof. Dr. Guodong Yin
Dr. Nan Xu
Guest Editors

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