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Connected and automated vehicles (CAV) are marketed for their increased safety, driving comfort, and time saving potential. With much easier access to information, increased processing power, and precision control, they also offer unprecedented opportunities for energy efficient driving. This paper is an attempt to highlight the energy saving potential of connected and automated vehicles based on first principles of motion, optimal control theory, and a review of the vast but scattered eco-driving literature. We explain that connectivity to other vehicles and infrastructure allows better anticipation of upcoming events, such as hills, curves, slow traffic, state of traffic signals, and movement of neighboring vehicles. Automation allows vehicles to adjust their motion more precisely in anticipation of upcoming events, and save energy. Opportunities for cooperative driving could further increase energy efficiency of a group of vehicles by allowing them to move in a coordinated manner. Energy efficient motion of connected and automated vehicles could have a harmonizing effect on mixed traffic, leading to additional energy savings for neighboring vehicles.

The paper presents a methodology to account for battery aging in the energy management strategy for a hybrid electric vehicle. An optimal control problem is formulated to minimize fuel consumption as well as battery aging, using recently developed methods for battery lifetime modeling. The approach relies on the concept of severity factor map, a tool used to quantify the aging effects of a battery due to its different on-vehicle operating conditions. The optimal control problem is solved using Pontryagin's Minimum Principle, showing with simulations the effect of the new control approach compared to the standard energy management strategies.