Predictive Energy Consumption Reduction for EV Adaptive Cruise Controllers with Uncertain Speed Information

Since the early days of research on autonomous vehicles, besides safety, the energy consumption of vehicles has played a crucial role in the study of their design. While many tried to optimize the vehicles' design, others researched path planning and estimating the energy consumed in a trajectory. As internal combustion engines use gas to power the vehicle, in electric vehicles, there is an electric motor connected to a battery that produces the power. Nowadays, with the increase in the utilization of electric vehicles capable of being more intelligent than their previous models, such as V2V communication, one can use this information to optimize the energy consumption of these vehicles. The focus of this paper is to study the effect of speed information forecasting on the energy consumption of an electric vehicle using an adaptive cruise controller to follow a leading vehicle moving on a longitudinal trajectory. We use an electric vehicle power loss model for our energy consumption calculation and a V2V communication system with uncertainty and packet loss to receive the speed information of the lead vehicle. Three different drive cycles are introduced to replicate scenarios such as urban areas, highways, or a mixture of them. Finally, we show our analysis of the energy consumption optimization on these drive cycles.