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ICCT Spatiotemporal Analysis of Electric Truck Charging Demand in Europe (2026)

Source Updated 2026-09-27 Cited by 4 pages

Steffen Link, Daniel Speth, Patrick Plötz (Fraunhofer ISI) and Albert Alonso-Villar, Hussein Basma (ICCT), Spatiotemporal analysis of electric truck charging demand in Europe, ICCT report ID 649, September 2026. A modelling study, not measured load: its VESUVIO model estimates battery-electric truck (BET) charging energy and power for the EU-27 plus the UK, Norway and Switzerland, on a hexagonal grid of about 250 km2 (17 x 20 km), for heavy trucks above 12 tonnes (class N3) only. Buses, medium and light commercial vehicles and cars are excluded.

Scenarios

  • Moderate Electrification: road-toll exemptions for zero-emission trucks (Eurovignette Directive) in every country plus ETS2 carbon pricing; no purchase premiums or depot-charging subsidies. By 2045 the EU-27 BET stock reaches over 3.45 million vehicles, 56.5% of heavy vehicles, enough to meet the EU heavy-duty CO2 standards beyond 2040.
  • Minimum Electrification: no policy support; uptake driven only by technology development and charging prices. It covers the CO2 standards until 2032 and then falls 51% short of the required BET stock by 2040. Sweden is among the five countries with the highest relative BET penetration here (with Switzerland, Norway, Denmark and Germany).

Findings

FindingDetail
DemandAbout 100 TWh a year by 2035 and about 200 TWh by 2045 across Europe (Moderate Electrification)
Depot vs publicDepot charging is typically 70–80% or more of energy; en-route public charging is 30–50% in smaller transit countries. Sweden has one of the highest long-haul en-route shares (with Estonia, Bulgaria, Croatia, Latvia, Greece); Norway, the UK, Poland and Denmark the highest depot shares
ConcentrationThe top 1% of hexagons hold roughly 25–33% of a country’s charging energy (about 50% in some countries) and the top 10% hold 60–90%; hotspots lie along major freight corridors and industrial hubs
Peak powerIn the most heavily loaded hexagon, larger freight countries reach 20–50 MW and small ones a few MW; a few cases exceed 50 MW (UK and Luxembourg in 2045). Local grid problems are expected at hotspots, not uniformly
Load shapeRegional depot charging peaks in the evening and at night; public en-route and intermediate charging peak around midday. Larger batteries give lower, broader peaks with more overnight charging, though a bigger fleet can raise the system peak. Fast depot charging sharpens midday and evening peaks; optimised depot charging spreads load but still peaks around noon and early morning
VariationResults use a representative average week; in busy weeks, two to three times a year, traffic and electricity demand can be 30–40% higher, so peaks are likely understated though hotspots stay the same

Sweden. A case study assuming 20% of the truck stock is electric finds that the top 10% of Swedish hexagons hold about 70% of weekly charging demand and the lowest 50% only about 3%. The report’s Lund example (a hexagon between the E6 and E22 northeast of Malmö, Moderate Electrification, 2035) has 282 MWh a week, a 3.1 MW peak and a 41% public en-route share, with peaks at midday and midnight. These are modelled values for one scenario and year.

Recommendations

The authors argue against one-size-fits-all targets and recommend: focus charging and grid deployment on priority locations (informing AFIR implementation and the Commission’s Clean Transport Corridor Initiative, which covers the North Sea-Baltic and Scandinavian-Mediterranean corridors); proactive grid investment in high-demand hotspots, because grid expansion planning is reactive to customer demand and has long investment cycles; support depot charging while deploying public charging where transit demand is large; and country-specific deployment strategies. The introduction adds that without “proactive and flexible grid connections” insufficient distribution capacity may delay road-freight decarbonisation.

Limits

  • Charging profiles derive mostly from German or Central European data; long-haul trucks use the regional profile. Hexagon peaks depend on the completeness of location data, and the uptake curve comes from a US model.
  • Controlled charging (tariff-aware or grid-responsive) and vehicle-to-grid or vehicle-to-building at depots are not modelled; the authors name them as future work on the flexibility of truck charging. A follow-up is to match the demand to grid capacity per hexagon.

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