Fraunhofer Institute for Systems and Innovation Research ISI
Fraunhofer Institute for Systems and Innovation Research ISI

Project

Spatiotemporal Analysis of Electric Truck Charging in Europe (VESUVIO)

The European Union’s climate targets – cutting greenhouse gas emissions by 55% by 2030 and reaching net zero by 2050 – require a rapid transformation of the freight transport sector. Electrifying heavy-duty vehicles is a key part of this effort, and electric truck adoption is accelerating. However, the large-scale deployment of charging infrastructure at public locations and private depots as well as its integration into existing electricity grids are expected to pose substantial challenges.

This research project aims to address these challenges by developing the VESUVIO (Vehicle Energy Systems Utilizing Visualized Infrastructure Optimization) model, which allows generating comprehensive insights into the spatial and temporal charging demand of electric trucks across Europe and evaluating the regional readiness of electricity grids to accommodate this demand. Thus, VESUVIO supports the implementation of the AFIR (Alternative Fuels Infrastructure Regulation) and the CTCI (Clean Transport Corridor Initiative) by identifying potential bottlenecks or priority regions and quantifying on-site demand to support evidence-based sizing and siting of truck charging infrastructure.

The resulting insights offer an actionable decision-support basis for policymakers, energy providers, and infrastructure operators to ensure that electrifying freight transport proceeds efficiently and reliably.

The development of VESUVIO Base Model was commissioned and supported by the International Council on Clean Transportation (ICCT) between June 2025 and June 2026. The research is structured in two phases: charging load profiles and demand estimation (Part-I) and regional grid readiness assessment (Part-II). Future iterations of the model may extend beyond heavy-duty trucks to cover other sectors or vehicle segments.

Objectives and outputs of the two project phases

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  • Part-I involves developing a high-resolution, Python-based model to estimate charging demand from electric heavy-duty trucks across the EU-27 and neighboring countries (mainly EFTA states and the UK). The model accounts for market uptake scenarios, truck fleet compositions, trip patterns, and charging behaviour for different operational types (urban, regional, and long-haul).

    The model produces charging load profiles (at 15-minute intervals for an average week) on a regional level based on a hexagonal grid, helping to identify high-demand locations such as major transport corridors and logistics hubs. It integrates data from freight transport models, agent-based simulations, national statistics, and infrastructure plans such as the AFIR.

    Expected outputs include:

    • a scenario-based simulation model to estimate charging demand over time and space
    • open datasets and key assumptions for BET deployment and charging behaviour
    • a validated, modular demand model that can be updated as new data becomes available
    • regional energy demand maps accessible via interactive dashboards
    • final report on “charging load profiles and demand estimation“

  • Part-II assesses whether regional electricity grids can meet future charging needs in selected European regions. Areas with high demand and publicly available grid data will be prioritized – such as parts of Ireland, the UK, Portugal, Spain, and Norway. The analysis aims to compare the projected charging loads with medium-voltage grid capacity on a substation level.

    Expected outputs include:

    • substation-level assessments of grid capacity and constraints
    • identification of reinforcement needs in grid-critical regions
    • regional and cross-country recommendations for infrastructure planning
    • final report on “grid readiness and planning strategies”

  • coming soon

    • Link, S.; Speth, D.; Plötz, P. (2026): Spatiotemporal Analysis of Electric Truck Charging in Europe (VESUVIO) – Parameter documentation. Version V1. Karlsruhe. Fraunhofer ISI. https://doi.org/10.24406/publica-8186
    • Link, S.; Plötz, P.; Speth, D.; Alonso-Villar, A.; Basma, H. (2026 – under review): Spatiotemporal Analysis of Electric Truck Charging in Europe – PART I: Demand-side modeling. Technical Report. International Council on Clean Transportation. Fraunhofer ISI.
    • Plötz, P.; Thoma, J.; Link, S.; Speth, D.; Alonso-Villar, A.; Basma, H. (2026 – under review): Spatiotemporal Analysis of Electric Truck Charging in Europe – PART II: Grid assessments. Technical Report. International Council on Clean Transportation. Fraunhofer ISI.