Computationally Efficient Algorithm for Eco-Driving Over Long Look-Ahead Horizons

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%.

Automated summary

This paper introduces a computationally efficient algorithm for eco-driving over long distances, which combines offline and online solutions to significantly reduce computational effort and achieve energy savings.