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In this paper results are given from single-cylinder, steady-state engine tests using the Texaco Diesel Additive (TDA) as an in-fuel emission reducing agent. The data include NOx, total unburned hydrocarbons, indicated specific fuel consumption, and heat release analysis for one engine speed (1500 RPM) with two different loads (Φ ≈ 0.3, IMEP = 0.654 MPa and Φ ≈ 0.5, IMEP = 1.006 MPa) using the baseline fuel and fuels with one percent and five percent additive by weight. The emissions were measured in the exhaust stream of a modified TACOM-LABECO single cylinder engine. This engine is a 114 mm x 114 mm (4.5″ x 4.5″) open chamber low swirl design with a 110.5 MPa (16,000 psi) peak pressure Bosch injector. The injector has 8 holes, each of 0.2 mm diameter. The intake air was slightly boosted (approximately 171 kPa (25 psia)) and slightly heated (333 K (140 °F)). In previous research on this engine the emissions, including soot, were well documented.

This study looks at the application of a titanium dioxide (TiO2) catalytic nanoparticle suspension to the surface of the combustion chamber as a coating, as well as the addition of hydrogen gas to a four-stroke spark-ignited carbureted engine as a possible technique for lowering engine-out emissions. The experiments were conducted on two identical Generac gasoline powered generators using two, four and six halogen work lamps to load the engine. One generator was used as a control and the second had key components of the combustion chamber coated with the catalytic suspension. In addition to the coating, both engines were fed a hydrogen and oxygen gas mixture and tested at low, medium and high loads. Using an unmodified engine as a control set, the following three conditions were tested and compared: addition of hydrogen only, addition of coating only, and addition of hydrogen to the coated engine.

The SAE AutoDrive Challenge II is a four-year collegiate competition dedicated to developing a Level 4 autonomous vehicle by 2025. In January 2023, the participating teams each received a Chevy Bolt EUV. Within a span of five months, the second phase of the competition took place in Ann Arbor, MI. The authors of this contribution, who participated in this event as team Wisconsin Autonomous representing the University of Wisconsin–Madison, secured second place in static events and third place in dynamic events. This has been accomplished by reducing reliance on the actual vehicle platform and instead leveraging physical analogs and simulation. This paper outlines the software and hardware infrastructure of the competing vehicle, touching on issues pertaining sensors, hardware, and the software architecture employed on the autonomous vehicle. We discuss the LiDAR-camera fusion approach for object detection and the three-tier route planning and following systems.