A Modelling Framework for Energy-Management and Eco-Driving Problems using Convex Relaxations

This paper presents a convex optimization framework for eco-driving and vehicle energy management problems. We will first show that several types of eco-driving and vehicle energy management problems can be modelled using the same notions of energy storage buffers and energy storage converters that are connected to a power network. It will be shown that these problems can be formulated as optimization problems with linear cost functions and linear dynamics, and nonlinear constraints representing the power converters. We will show that under some mild conditions, the (non-convex) optimization problem has the same (globally) optimal solution as a convex relaxation. This means that the problems can be solved efficiently and that the solution is guaranteed to be globally optimal. Finally, a numerical example of the eco-driving problem is used to illustrate this claim.

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Publication Details

Published
2024-08-21
DOI
https://doi.org/10.1109/ccta60707.2024.10666655
Citations
1
Primary Topic
Traffic control and management
Type
article
Field-Weighted Citation Impact
0.33
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article

A Modelling Framework for Energy-Management and Eco-Driving Problems using Convex Relaxations

M.C.F. Donkers, Y.J.J. Heuts
1 citations
Traffic control and management
0.33
article

A Modelling Framework for Energy-Management and Eco-Driving Problems using Convex Relaxations

M.C.F. Donkers, Y.J.J. Heuts
article en
1 citations

Abstract

This paper presents a convex optimization framework for eco-driving and vehicle energy management problems. We will first show that several types of eco-driving and vehicle energy management problems can be modelled using the same notions of energy storage buffers and energy storage converters that are connected to a power network. It will be shown that these problems can be formulated as optimization problems with linear cost functions and linear dynamics, and nonlinear constraints representing the power converters. We will show that under some mild conditions, the (non-convex) optimization problem has the same (globally) optimal solution as a convex relaxation. This means that the problems can be solved efficiently and that the solution is guaranteed to be globally optimal. Finally, a numerical example of the eco-driving problem is used to illustrate this claim.

Eindhoven University of Technology (NL)
Affordable and clean energy
Openalex Percentile: Top 42%
Traffic control and management
0.33
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