Autonomous Electric Vehicle Routing Problem using Ant Colony Optimization with consideration of the Battery State-of-Health

Pierre Romet (1) , Romain Tabusse (2) , Franck Gechter , El-Hassane Aglzim (1) , Samir Jemei (2) , David Bouquain (2) , Daniela Chrenko (2)

1 DRIVE - Département de Recherche en Ingénierie des Véhicules pour l'Environnement [Nevers]
2 FEMTO-ST - Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174)

Freight transportation is evolving with the development of electric vehicle to carry out goods delivery rounds. In addition to the technological developments that make electric vehicles more and more suitable for long-distance traffic, the legislative framework also imposes these developments, such as the announced end of thermal vehicles in France in 2040. However, it is not possible to use an electric vehicle in the same way as an internal combustion vehicle. This technology impose to take into account the aging of the battery in order to define its use.

Mots clés: EVRP; ACO; autonomous vehicle; lithium-ion battery; SOE; SOH; DOD

Domaines: Sciences de l'ingénieur [physics]

Pierre Romet, Romain Tabusse, Franck Gechter, El-Hassane Aglzim, Samir Jemei, et al.. Autonomous Electric Vehicle Routing Problem using Ant Colony Optimization with consideration of the Battery State-of-Health. 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI), Nov 2021, Washington, United States. pp.475-480, ⟨10.1109/ICTAI52525.2021.00077⟩. ⟨hal-03546079⟩