Transportation

Hyper Tech Research Inc., aims to design and demonstrate a multi-MW, high-efficiency, and high-power density integrated electric propulsion motor, drive, and thermal management system that meets the performance requirements of future hybrid electric, single-aisle passenger aircraft.

General Electric Global Research will develop a 2 MW fully integrated all-electric aircraft powertrain and demonstrate a 350-kW lab-scale prototype to enable zero carbon emission narrow-body commercial aircraft with all-electric propulsion.

Wright Electric will design a high-efficiency and torque-dense electric powertrain that combines innovations in integrated cooling, power electronics, and rotor design. Co-developing these critical elements will enable Wright to achieve the target efficiency and weight metric and lead to a scalable solution. The design will create a high-performance motor without sacrificing safety or the use of existing manufacturing techniques. The team plans to use an aggressive in-slot cooling strategy coupled with a high-frequency inverter whose efficiency may exceed 99.5%.

Marquette University and its partners are developing the next generation of electric drivetrains for aerospace propulsion. The proposed system consists of a high-power density motor enabled by (1) an additively manufactured winding and heat pipe based thermal management scheme, (2) a modular power electronics topology, and (3) tight system integration and shared thermal management between the motor and power electronics to meet or exceed system-level targets.

Advanced Magnet Lab (AML) seeks to develop high-power density permanent magnet motors. When coupled to an integrated SiC (silicon carbide) drive, these motors will enable an overall specific power beyond 12 kW/kg. The proposed concept relies on (1) the tight integration of a high-power density dual-rotor permanent magnet rotor based on "continuous flux directed" magnets (PM-360TM) currently under development at AML, (2) high-power density SiC power converters, and (3) a shared closed-loop cooling system rejecting the heat in the propulsion ducted fan air stream.

Argonne National Laboratory is developing a low-temperature catalytic upcycling process for converting post-consumer plastic wastes made of polyethylene or polypropylene polymers to premium synthetic lubricants. Argonne’s hydrogenolysis (decomposition of a compound resulting from its interaction with hydrogen) catalyst technology converts these polymers to the desired lubricant product with high selective and near-quantitative yields, and with negligible formation of light gases.

Western Research Institute will explore technologies based on pyrolysis (thermal conversion) and hydrocracking (a chemical process that upgrades low-quality, heavy gas oils) to convert waste, low-value plastic, and paper polymers into high-energy liquid products suitable as fuel, refinery feedstock, or feed for chemicals manufacturing. The pyrolysis technologies involve heating the polymers in oil media to a temperature high enough to break the chemical bonds to produce a liquid product.

The University of Utah aims to develop and deploy a distributed carbon sensor system that is buried into the soil, capable of locally stimulating a surrounding volume of soils at multiple depths, and sensing carbon and carbon flux at ultra-low operational cost. The sensors will enable high-accuracy and real-time decision data for cost-effective carbon removal, storage, and management to promote climate change mitigation via agriculture and managed land systems.

Texas A&M will focus on the design, fabrication, and testing of a lightweight and ultra-efficient electric powertrain for aircraft propulsion to reduce the energy costs and emissions of aviation.

The Lawrence Berkeley National Lab (LBNL) CARBON STANDARD team will develop advanced machine learning tools for a cross-scale quantification of carbon intensity (CI) during biofuel feedstock production. LBL will act as the integrator across all SMARTFARM teams to analyze complex, multi-physics, and multi-scale datasets, and develop scaling approaches across the variety of CI monitoring fields.