Objectives of the service
E-Spacement is an advanced location intelligence tool designed to help Charge Point Operators (CPOs), municipalities, and other stakeholders identify the best locations for new EV charging stations. By leveraging data-driven insights, E-Spacement ensures optimal charger placement to maximize usage, reduce investment risks, and support the expansion of sustainable e-mobility networks.
As electric vehicles (EVs) become increasingly popular, the expansion of charging infrastructure is critical to support this growing market, while the lack of progress on charging infrastructure can act as a bottleneck on future growth of e-mobility. Finding the best locations for new charger locations is a major challenge and a key parameter in ensuring that the expansion of charging infrastructure is done in a financially sustainable manner. Poorly placed chargers can suffer from low utilization, resulting in wasted resources and longer payback periods. E-Spacement solves this by analysing multiple key factors—such as traffic patterns, customer demand, accessibility, and grid capacity—to identify the most profitable and effective locations in a variety of environments - rural areas, urban streets, and along highways.
Users and their needs
E-Spacement is an AI-powered decision support platform that helps Charge Point Operators (CPOs) and infrastructure developers identify the most strategic, high-performing locations for electric vehicle (EV) charging stations. By combining spatial data with advanced machine learning, E-Spacement offers an end-to-end site scoring and prioritization service designed for precision, speed, and return on investment.
Why E-Spacement?
As the EV market expands across Europe, choosing the right charging site can mean the difference between profitability and sunk cost. E-Spacement empowers decision-makers with data-rich, explainable analytics to:
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Maximize charger utilization rates
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Accelerate planning and permitting
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De-risk capital allocation
Benefits for charge point operators
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Cut site planning time from weeks to days
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Increase ROI by focusing only on viable locations
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Visualize market coverage, competition, and expansion paths
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Win more tenders with data-backed rollout strategies
Service/ system concept
E-Spacement’s core is a predictive AI model trained on multi-layer spatial data to determine the viability of a given location. The data used includes layers such as:
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Copernicus EO datasets (land cover, elevation, solar potential)
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Road network data and real world mobility patterns
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Socio economics and demographics
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Points of interest and grid proximity
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Distances from sector specific POIs
Space Added Value
The project uses EO data from Sentinel mission as well as GNSS data.
The data significantly increases the precision of our models, by adding layers that help to characterize a given location being considered for an EV charging point
Current Status
Technical
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Functional prototype of the AI-based site selection engine built, integrating algorithmic learning modules.
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A core spatial database covering Hungary and Slovenia was established (100×100 m grid), integrating EO (Sentinel-2), mobility (GNSS), demographic, and grid data.
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▪️ Successful ingestion of AFIR-mandated DATEX II data
Market
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Engagements and interviews held with stakeholders from across the EU confirming willingness to use.
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Validation of market need for standardized, spatially-informed site-selection tools aligned with AFIR and national EV rollout strategies.
Business
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Refined subscription-based SaaS model with tiered pricing.
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Positive cost–benefit indicators: 25 % + expected improvement in charger utilization
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Clear route-to-market
Prime Contractor(s)
