V2X Platooning: Minimizing Travel Time and Energy Consumption in an Urban Setting
Connected and Automated Vehicles (CAVs) and vehicle platooning are popular areas of research in both systems and transportation engineering. The benefits of CAV platooning are high; linking vehicles to each other as well as urban infrastructure reduces energy consumption and travel time by decreasing aerodynamic drag, eliminating margin needed for human reaction times, and enabling optimal trajectory generation using traffic signal preview. This study focuses on the energy modeling and optimization of a CAV platoon as it traverses through an urban setting with a multitude of traffic lights. The key focus is on minimizing associated energy consumption and studying how parameters with high correlation to energy can be adjusted for further potential savings. Another point of study is quantifying the trade-off between trajectories minimizing time of travel and those minimizing energy consumption. This study focuses on battery electric vehicles (BEVs), specifically passenger cars, in single-vehicle and three-vehicle platoon scenarios. The nonlinear mathematical model of a BEV powertrain is intelligently relaxed so that convex optimization can be used to find an optimal solution which is also optimal for the original nonlinear problem. This project applies data science strategies such as mathematical modeling, optimization, and optimal control to answer the questions at hand.
CE 295: Data Science for Energy, Fall 2021
Team Project by:
- Shih-Hung Chiu
- Marge D’Auria
- Joe Koszut
- Tianhao Wu
- Jarvis Yuan
- Aoyu Zou