Advances in battery and charging technology have made heavy-duty battery-electric vehicles (HDBEVs) a viable pathway for decarbonizing heavy-duty vehicles (HDV). Predicting electrical charging profiles for HDBEV fleets is critical to supporting Canadian energy system reliability. This study leverages high-resolution telematics from the American Transportation Research Institute for Ontario HDVs in 2019 to produce annual HDBEV fleet charging profiles under various technology and operator charging scenarios. _x000D_ _x000D_ The project has two phases: data processing and charging demand modelling. First, converting real-world HDV travel data into schedules, identifying driving and charging periods and summarizing travel statistics. Second, estimating the charging demand for randomly sampled HDBEV fleets using government-reported HDBEV battery sizes, charging rates, and selected charging strategy. Strategies include immediate charging (start charging once stationary), delayed charging (fully charge just before next departure), or minimum-power (charge at lowest constant power)._x000D_ _x000D_ Preliminary findings using August 8-14 data generated 1960 HDV schedules and highlighted the impact of charging strategy. Immediate charging increases afternoon peak electrical demand by over 30% compared to delayed and minimum-power charging, while minimum-power charging minimizes daily electrical demand variation. These results offer energy system decision makers valuable insights into HDBEV load profiles and power demand variations across operator charging behaviours.
