Please join us for our final CSS Research Forum of Fall 2017.
Whether you are brand new to CSS or a veteran, you are strongly encouraged to come join us and hear about the work other researchers are doing.
We will serve a selection of PIES.
When: Friday, December 8, 2017 - 1:00 to 2:30 PM.
Where: 1040 Dana Building
We'll hear presentations from:
Jim Gawron - MS/MBA student
Title: LCA of Connected and Automated Vehicles (CAVs): Sensing and Computing Subsystem and Vehicle Level Effects
Abstract: Although recent studies of connected and automated vehicles (CAVs) have begun to explore the potential energy and greenhouse gas (GHG) emission impacts from an operational perspective, little is known about how the full life cycle of the vehicle will be impacted. We report the results of a life cycle assessment (LCA) of Level 4 CAV sensing and computing subsystems integrated on internal combustion engine vehicle (ICEV) and battery electric vehicle (BEV) platforms. The results indicate that CAV subsystems could increase vehicle primary energy use and GHG emissions by 3-20% due to increases in power consumption, weight, drag, and data transmission. However, when potential operational effects of CAVs are included (e.g., eco-driving, platooning, and intersection connectivity) the net result is up to a 9% reduction in energy and GHG emissions in the base case. Overall, this study shows the potential of CAVs to have net positive impacts on the environment.
Krutarth Jhaveri - MS/MSE student
Title: Life Cycle Study of Thin-Wall Ductile Cast Iron for Automotive Lightweighting Applications
Abstract: Transportation is the second largest energy consumer in the U.S., only behind industrial energy consumption. Use-phase fuel consumption is responsible for the majority of an automobile’s life cycle energy and greenhouse gas (GHG) emissions. Lightweighting is an important strategy to reduce use-phase fuel consumption and potentially reduce vehicle life cycle impacts. This study, under the Lightweighting Innovations for Tomorrow (LIFT) initiative, develops a parametric life cycle model to assess the life cycle performance of Thin-Wall Ductile Cast Iron (TWDCI), a lightweighting fabrication technology. This model is used to evaluate the environmental tradeoffs and benefits of lightweighting with TWDCI and compare its life cycle energy and GHG performance to conventional cast iron and cast aluminum.