Modeling, implementation and experimental verification of eco-driving on a battery-electric heavy-duty vehicle

Y.J.J. Heuts, J.J.F. Wouters, O.F. Hulsebos and M.C.F. Donkers

Applied Energy, 2025, vol. 390, issue C, No S0306261925005124

Abstract: In this paper, an Eco-Driving Assistance System (EDAS) has been implemented on a fully electric heavy-duty vehicle and its performance has been validated using real-world experiments. The objective of the EDAS is to provide the driver with a recommendation on the vehicle’s optimal speed trajectory that minimizes its energy consumption over the entire trip. This requires solving a receding horizon optimal control problem, which, in this case, consists of a convex optimization problem and can be solved as a second-order cone program. Simulations were used to explore different prediction horizon lengths and move-blocking strategies of the underlying receding horizon optimal control problem, aiming to strike a balance between numerical complexity and energy savings. Finally, the method is implemented on an electric heavy-duty vehicle where an augmented speedometer is presented to the driver. Multiple tests with and without an EDAS have been performed, which resulted in a reduction of 6.5 %–12 % in energy consumption compared to when the vehicle was driven without the EDAS active.

Keywords: Eco-driving; Experimental validation; Optimal control problem; Convex optimization (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261925005124
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:390:y:2025:i:c:s0306261925005124

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2025.125782

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().