https://techxplore.com/news/2024-06-rap ... cells.html
by Ingrid Fadelli , Tech Xplore
The electrification of road vehicles has already begun, with most automotive companies now investing in hybrid and electric cars. While these efforts could contribute to reducing carbon emissions worldwide, they have so far been primarily focused on cars, rather than trucks and heavy-duty vehicles for transporting goods.
The primary reason for this is that electrifying larger and heavier vehicles is technically challenging, as powering them for long periods of time would require more expensive and sophisticated battery technologies. Studies exploring the potential future of zero-emission heavy-duty vehicles have so far been relatively scarce, also due to the lack of available data related to the costs of fuel cells and truck batteries.
Researchers at Fraunhofer Institute for Systems and Innovation Research ISI and Karlsruhe Institute of Technology (KIT) recently set out to fil this gap in the literature, by forecasting changes in the cost of truck batteries and fuel cells over the next decades. Their analyses, outlined in a paper published in Nature Energy, suggest that the costs of both truck batteries and fuel cells could decline over the next few years, facilitating the electrification of heavy-duty vehicles.
"Discrepancies exist regarding current cost levels of fuel cells and batteries for decarbonizing road transport, as well as the pace and extent of achievable cost reductions," Steffen Link, lead author of the paper, told Tech Xplore. "Our findings emphasize that zero-emission truck costs are primed to decline much faster than expected in previous studies, with cost-effective operations appearing feasible today. Given the short ownership times of heavy commercial trucks (typically 3-6 years), market diffusion will happen substantially quicker than for private passenger cars."
As part of their study, the researchers collectively analyzed data derived from over 200 sources published between 2010 and 2023, including peer-reviewed papers, industry announcements and analyst reports. Using various statistical methods, including normal and robust regression techniques, they derived possible cost projections for truck batteries and fuel cells, and then validated the robustness of their forecasts.
