Time Optimal and Eco-Driving Mission Planning under Traffic Constraints
Paper in proceeding, 2020
This paper addresses optimising a transport mission by controlling the mission start time and velocity profile of an electric vehicle (EV) driving in a hilly terrain, subject to legal and dynamic speed limits imposed by traffic congestion. To this end, a nonlinear program (NLP) is formulated, where the mission start time is allowed to vary within an interval and final time is kept free. The goal is to find the optimal trade-off between energy consumption and travel time, while allowing a flexibility in starting time and a certain variation of vehicle speed around an average. It is observed that total travel time is reduced up to 5.5% by adjusting the mission start time, when keeping an average cruising speed of about 75 km/h.
Theory and Models for Optimization and Control
Intelligent Logistics
Road Traffic Control
Author
Ahad Hamednia
Chalmers, Electrical Engineering, Systems and control
Nikolce Murgovski
Chalmers, Electrical Engineering, Systems and control
Jonas Fredriksson
Chalmers, Electrical Engineering, Systems and control
IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
9294341
9781728141497 (ISBN)
2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)
Rhodos, Greece,
Rhodos, Greece,
Multi-CORE - Multi-level COntrol for Robust integrated vehicle Energy management
Swedish Energy Agency (P43322-1), 2016-12-01 -- 2019-12-31.
Subject Categories
Computer Engineering
Transport Systems and Logistics
Vehicle Engineering
Areas of Advance
Transport
Energy
DOI
10.1109/ITSC45102.2020.9294341