Innis, Cody (Tennessee Technological University), Chen, Pingen (Tennessee Technological University)

A Fast Macroscopic Speed Planner for Electric Vehicle Platooning

Scheduled for presentation during the Regular Session "Highly Automated and Connected Vehicular Systems-I" (MoAT4), Monday, August 29, 2022, 12:20−12:40, Ballroom

10th IFAC International Symposium on Advances in Automotive Control, August 28-31, 2022, Columbus, Ohio, USA

This information is tentative and subject to change. Compiled on April 16, 2024

Abstract

Electric vehicles (EVs) have demonstrated significant advantages of high fuel economy and low maintenance cost over gasoline-powered vehicles and hybrid electric vehicles in moving people and goods. However, range anxiety remains as one of the main barriers in market penetration for EVs. Platooning has proven to be an effective approach to reduce aerodynamic drag resistance and thus extend EV ranges. However, taking full advantage of platooning to reduce energy consumption during a trip while satisfying the time constraint is a challenge. This paper is focused on the design and validation of the high-level speed planner of a two-level real-time platooning framework for EVs. The speed optimization problem in the high-level speed planner for the entire trip is reformulated into two speed profile optimization problems in two processes: 1) catch-up and then platooning, and 2) platooning and then break-away. Analytical solutions are derived for the optimal speed profiles in both processes. The analytical solutions capture the impacts of critical parameters such as initial and final inter-vehicle distances, and the leading vehicle speed.