2020/02/06 by Ahad Hamednia, Nalin Kumar Sharma, Hamednia, Ahad +5
Energy · Engineering · #Energy, Environment, and Transportation Policies #FOS: Electrical engineering #Systems and Control (eess.SY) #Traffic control and management #Transportation and Mobility Innovations #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2002.02357
openalex publication_date 2020/02/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper presents a computationally efficient algorithm for eco-driving\nover long prediction horizons. The eco-driving problem is formulated as a\nbi-level program, where the bottom level is solved offline, pre-optimizing gear\nas a function of longitudinal velocity and acceleration. The top level is\nsolved online, optimizing a nonlinear dynamic program with travel time, kinetic\nenergy and acceleration as state variables. To further reduce computational\neffort, the travel time is adjoined to the objective by applying necessary\nPontryagin Maximum Principle conditions, and the nonlinear program is solved\nusing real-time iteration sequential quadratic programming scheme in a model\npredictive control framework. Compared to standard cruise control, the energy\nsavings of using the proposed algorithm is up to 15.71%.\n