Adapting Basic On-Road Data to the Heavy Heavy-Duty Diesel Truck Schedule for Guiding the Electrification of Long-Haul Truck Transport

<div>Heavy heavy-duty diesel truck (HHDDT) drive cycles for long-haul transport trucks were developed over 20 years ago and have a renewed relevance for performance assessment and technical forecasting for transport electrification. In this study, a model was constructed from sparse data recorded from the real-life on-road activity of a small fleet of class 8 trucks by fitting them into separate driving-type segments constituting the complete HHDDT drive cycle. Detailed 1-s resolution truck fleet raw data were also available for assessing the drive cycle model.</div> <div>Numerical simulations were conducted to assess the model for trucks powered by both 1.0 MW charging and 300 kW-level e-Highway, accounting for elevation and seasonally varying climate conditions along the Windsor–Quebec City corridor in Canada. The modeling approach was able to estimate highway cruising speeds, energy efficiencies, and battery pack lifetimes normally within 2% of values determined using the detailed high-resolution on-road raw data.</div> <div>HHDDT drive cycles derived from sparse data can be considered fully satisfactory for long-haul truck simulations for electrification planning. Further, it was shown that the virtual electric truck as specified here can perform the same duty cycle as diesel trucks are currently doing in the same amount of time on e-Hwys, and requiring less an hour per day additional time for the 1.0 MW charger modality.</div>