Computationally Efficient Algorithm for Eco-Driving Over Long Look-Ahead Horizons
Journal article, 2022
This paper presents a computationally efficient algorithm for eco-driving along horizons of over 100km. The eco-driving problem is formulated as a bi-level program, where the bottom level is solved offline, pre-optimising gear as a function of longitudinal velocity (kinetic energy) and acceleration. The top level is solved online, optimising a nonlinear dynamic program with travel time, kinetic energy and acceleration as state variables. To further reduce computational effort, the travel time is adjoined to the objective by applying necessary Pontryagin's Maximum Principle conditions, and the nonlinear program is solved using real-time iteration sequential quadratic programming scheme in a model predictive control framework. Compared to average driver's driving cycle, the energy savings of using the proposed algorithm is up to 11.60%.
velocity optimisation
Pontryagin's maximum principle
model predictive control
real-time iteration
Acceleration
sequential quadratic programming
Vehicle dynamics
Mechanical power transmission
Eco-driving
Roads
optimal control
Real-time systems
Optimization
Gears
Author
Ahad Hamednia
Chalmers, Electrical Engineering, Systems and control
Nalin Kumar Sharma
Chalmers, Electrical Engineering, Systems and control
Nikolce Murgovski
Chalmers, Electrical Engineering, Systems and control
Jonas Fredriksson
Chalmers, Electrical Engineering, Systems and control
IEEE Transactions on Intelligent Transportation Systems
1524-9050 (ISSN) 1558-0016 (eISSN)
Vol. 23 7 6556 -6570Subject Categories
Computer Engineering
Computational Mathematics
Control Engineering
DOI
10.1109/TITS.2021.3058418