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Solicitation on Topics Informing New Program Areas - Models to Optimize Train Infrastructure, Vehicles, and Energy Storage (LOCOMOTIVES)
NOTE: The Solicitations and topics listed on this site are copies from the various SBIR agency solicitations and are not necessarily the latest and most up-to-date. For this reason, you should use the agency link listed below which will take you directly to the appropriate agency server where you can read the official version of this solicitation and download the appropriate forms and rules.
The official link for this solicitation is: https://arpa-e-foa.energy.gov/
Application Due Date:
Available Funding Topics
Through this LOCOMOTIVES Topic, ARPA-E seeks the development of validated planning and simulation tools that are able to model the deployment of a wide range of ES technologies in the Class 1 Rail Freight sector and that determine associated lifecycle GHG emissions and levelized cost of Mt-km (LCOTKM) values over various time scales (e.g., 10, 20, 30 years). ARPA-E seeks the development of these tools via two categories: i) a comprehensive, route-by-route model (“Full Roll-out Model (FRM)”), and ii) a reduced-scope model (“Bounding Model (BM)”), which is a solution to the required validated physical and economic core model. Please note that although Class 1 freight is the primary focus, proposals that additionally consider commuter railroads and/or shorter haul freight routes that intersect with Class 1 operations, such as sharing a section of track along one or more Class 1 freight route(s), for example, are also responsive to this Topic. At the conclusion of work sponsored under this Targeted Topic, ARPA-E envisions one or more models will be publically available for use by third-parties to study and support the cost-benefit analysis of fleet GHG emission decarbonization. The models would also be available to applicants and awardees under a future ARPA-E program, if any, to assist with concept development and optimization. ARPA-E may use these models, combined with information from other sources, to inform potential future program development, including a prioritization of ES technologies to pursue.