eFleetPlan: Co-optimisation tool of charging infrastructure investment and electric fleet operations

There is an urgent need to decarbonise transport systems across all modes, including light commercial vehicle (LCV) fleets. This paper introduces eFleetPlan, an open-source software designed to support decision-making on LCV fleet electrification by jointly optimising investments in charging infrastructure and fleet charging operations. Developed in Python, eFleetPlan is a modular, transparent tool that enables data-driven planning for electric LCV fleets. This tool includes two packages: fleet operation simulation and the charging co-optimisation. The co-optimisation package incorporates a mixed-integer linear programming (MILP) model that minimises infrastructure and operational costs while meeting fleet demand and energy constraints. Its flexible architecture allows adaptation to different geographical contexts, datasets, and operational assumptions, supporting applications in research, education, and practical fleet planning.

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Publication Details

Journal
SoftwareX
Published
2026-05-29
DOI
https://doi.org/10.1016/j.softx.2026.102748
Citations
1
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
7.94
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article

eFleetPlan: Co-optimisation tool of charging infrastructure investment and electric fleet operations

Carolina Gil Ribeiro, Jagruti Thakur
1 citations
SoftwareX
Electric Vehicles and Infrastructure
7.94
article

eFleetPlan: Co-optimisation tool of charging infrastructure investment and electric fleet operations

Carolina Gil Ribeiro, Jagruti Thakur
article en
1 citations

Abstract

There is an urgent need to decarbonise transport systems across all modes, including light commercial vehicle (LCV) fleets. This paper introduces eFleetPlan, an open-source software designed to support decision-making on LCV fleet electrification by jointly optimising investments in charging infrastructure and fleet charging operations. Developed in Python, eFleetPlan is a modular, transparent tool that enables data-driven planning for electric LCV fleets. This tool includes two packages: fleet operation simulation and the charging co-optimisation. The co-optimisation package incorporates a mixed-integer linear programming (MILP) model that minimises infrastructure and operational costs while meeting fleet demand and energy constraints. Its flexible architecture allows adaptation to different geographical contexts, datasets, and operational assumptions, supporting applications in research, education, and practical fleet planning.

SoftwareXVol. 35
KTH Royal Institute of Technology (SE)
Industry, innovation and infrastructure
Openalex Percentile: Top 2%
Electric Vehicles and Infrastructure
7.94
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