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Connectivity and automation are increasingly being developed for cars and trucks, aiming to provide better safety and better driving experience. As these technologies mature and reach higher adoption rates, they will also have an impact on the energy consumption: Connected and Automated Vehicles (CAVs) may drive more smoothly, stop less often, and move at faster speeds, thanks to overall improvements to traffic flows. These potential impacts are not well studied, and any existing studies tend to focus solely on conventional engine-powered cars, leaving aside electrified vehicles such as Hybrid Electric Vehicles (HEVs) and Battery Electric Vehicles (BEVs). This work intends to address this issue by analyzing the energy impact of various CAV scenarios on different types of electric vehicles using high-fidelity models. The vehicles-all midsize, one HEV, one BEV, and a conventional-are modeled in Autonomie, a high-fidelity, forward-looking vehicle simulation tool.

In Hybrid Electric Vehicles (HEV), the electrical hybridization offers different ways to reduce the fuel consumption: kinetic energy recuperation during vehicle deceleration, possibility of stopping the engine, and intelligent Energy Management System (EMS). Besides, with the future more stringent standards, there is a need to integrate the pollutant emissions in the EMS, since strictly reducing the fuel consumption can increase the emissions. The paper presents an optimal energy management strategy with constraints on pollutant emissions for gasoline-HEV, taking into account the 3-Way Catalyst Converter (3WCC). Based on a complete model of the powertrain, a mixed fuel consumption / pollutant emissions performance index is minimized with the Pontryaguin Minimum Principle (PMP) and two states, the battery State Of Charge and the 3WCC temperature.