D5.1 Well tested and robust analytical tools and insights for optimal placement and roll out of charging infrastructure for heavy-duty trucks for a supply chain or retail customer


Heavy-duty vehicles account for less than 2-5% of the vehicles on the road in Europe but contribute to 15-22% of CO2 emissions from road transport. Battery electric trucks (BETs) could be deployed on a large scale to reduce greenhouse gas emissions, but they require charging infrastructure that supports long-haul operations. Therefore, assessing the required charging locations, energy, and power requirements is critical. This deliverable reports a case study to estimate the charging infrastructure for BETs in long-haul operations in Europe by the year 2030. We use a trip-chain-based model to derive charging requirements for BETs in long-haul operations (defined as travel times over 4.5 hours or distances over 360 km) for Europe in 2030. We convert an origin-destination (OD) matrix into trip chains combined with European truck driving regulations to derive break and rest stops. We show that an average charging area (defined as a 25´25 km square areas, where each square can include multiple charging stations and parking lots with multiple charging points) needs to have four to five times more overnight (CCS) than megawatt (MCS) charging points: We estimate that about 40,000 CCS (50-100 kW) and about 9,000 MCS (0.7 – 1.2 MW) points are required to support a BET share of long-haul operations of 15%. On average, eight CCS and two  MCS chargers are required per charging area. On average each CCS serves two, and MCS 11 BETs daily, respectively. The daily electricity demand for public charging of BET in each charging area would be around 110 GWh. The model can be applied to any region with similar data. Future work can consider improving the queuing model, assumptions regarding regional differences of BET penetration, and heterogeneity of truck sizes and utilization.