D4.1 Analysis framework for decision-support/assessment and intervention tools at the operational level
The deliverable presents a methodology to apply new synthesized data for heavy-duty or long-haul truck (LHT) movements to allocate an alternative fuel vehicle technology, i.e., fast and slow stationary charging, infrastructure network for heavy-duty vehicles in Europe. Many recent studies reflect on long-haul battery-powered electric trucks (LBET) charging needs but are mainly limited to a small geographical scale, e.g., nationally, or do not identify significant charging station requirements, i.e., locations of charging stations, the characteristics and number of installed charging points, and the daily energy requirements, due to lack of details from LHT travel patterns. The detailed charging requirements also impact (or are constrained by) other significant systems connected to the charging stations, such as the power grid. Other studies utilize detailed datasets from the original equipment manufacturers (OEM)s, which cannot represent the whole region and ignore the impact of passing trucks from neighboring countries. Other methodologies utilize more representative data, e.g., traffic counts of all passing trucks, to identify charging needs. However, such methodologies cannot distinguish between the truck travel pattern heterogeneity, which fails to capture the charging point differences, e.g., the power rate.
In this report, we present a model that evaluates the LBET’s charging requirements in the year 2030 for the European continent. Following the EU truck driver regulations, the research converts an origin-destination (OD) matrix resulting from a four-step transport model into long-haul or heavy-duty truck (LHT) trip chains. A trip chain denotes a set of connected trips between “significant” locations (e.g., depos and shops) before a vehicle ends its journey. A complete trip chain determines the travel patterns of a higher spatial and temporal resolution table of the OD matrix. The detailed trip chain identifies each LBET’s multiple stop location and duration, energy consumption, and the amount of energy that had to be charged at each stop. This report shows that the suggested methodology could provide charging requirement infrastructure insights (i.e., charging types, station capacity, and energy supply) for all moving trucks of the EU member state to serve electrified LHTs. The identified information could also be used for emission analysis from all moving trucks.
We show that in our main case scenario of 15 % LBET share, a minimum of 28,800 slow (≤ 100 kW) and 9,800 fast (≥ 1 mW) charging points are required to meet the energy demand corresponding to the daily energy requirements of 112 GWh. On average, the ratio of slow to fast charging points is 3:1. The fast and slow charging points serve 12 and 2 LBETs daily, respectively.