Optimal Real-Time Velocity Planner of a Battery Electric Vehicle in V2V Driving

Autonomous driving systems are among the most interesting technologies in the transportation field nowadays, ensuring a high level of safety and comfort while also enhancing energy saving. For the following case study, a Battery Electric Vehicle (BEV) is considered able to communicate with other vehicles through vehicle-to-vehicle (V2V) technology by exchanging information on position and velocity. In this framework, an innovative real-time velocity planner has been developed aiming at maximizing the battery energy savings while improving the passenger comfort as well. This controller uses the principles of the equivalent consumption minimization strategy (ECMS) when the preceding vehicle is accelerating. Simulation results demonstrate improvements in comfort ranging from 26% to 42% ca. and in energy consumption (from 0.4% to 1.3%) when performing different drive cycles in V2V automated driving mode thanks to the proposed controller.

Automated summary

An innovative real-time velocity planner has been developed in this study to maximize energy savings and improve passenger comfort in V2V automated driving mode for Battery Electric Vehicles (BEVs). Simulation results show significant improvements in comfort and energy consumption when using the proposed controller.