Data Set: Public charging facility requirements for long-haul trucks in the EU: a trip chain approach
Abstract of the research
This research presents a trip chain-based model that evaluates the long haul electric truck (LBET)’s charging requirements in the year 2030 for the European continent. Following EU truck driver regulations, the research converts a four-step origin-destination (OD) matrix into LHT trip chains. We show that in our main case scenario of 15% LBET share, a minimum of 28800 slow (≤ 100 kW) and 9800 fast (≥ 1 mW) charging points are required to meet that energy demand, corresponding to daily energy requirements of 112 GWh. On average, the slow to fast charging points ratio is 3. Fast and slow charging points serve 12 and 2 LBETs daily, respectively. Our model suggests that it will be necessary to place charging stations every 25-35 km on highways where demand for charging is required.
Methodology
We develop a method for placement of charger locations in Europe that meets the demand of goods movements between regions while following EU driving regulations. The spatial resolution of regions is based on the Nomenclature of Territorial Units for Statistics (NUTS)-3 regions. The annual flow of goods transported by LHT is identified using the ETISplus dataset. We develop a travel pattern for the long haul truck (LHT) to convert flows into trip chains with the traversed LHT number. The traveled routes between the regions are mapped. Locations of short period stops, i.e., breaks, and long period stops, i.e., rests, are allocated/assigned along traveled routes to construct a trip chain for each moving LHT. Break and rest locations for all moving LHTs are aggregated to suggest energy requirements if assuming these LHTs are BETs. The aggregated energy to charge stopped LBETs is used to identify the number and type of chargers within each suggested charging station.
Data Set details
The presented datasets contain spatial information for generating charger stations with specifications according to charging needs. The datasets contain information about: Transport network model and edges, Transported flows, routes and flow center information data, region centers and Planned transport infrastructure.