Browsing by Author "Northrop, William"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Can Automated Vehicles "See" in Minnesota? Ambient Particle Effects on LiDAR
    (Minnesota Department of Transportation, 2022-08) Northrop, William; Zhan, Lu; Haag, Shawn; Zarling, Darrick
    This project will use a combination of laboratory experimentation and road demonstrations to better understand the reduction of LiDAR signal and object detection capability under adverse weather conditions found in Minnesota. It will also lead to concepts to improve LiDAR systems to adapt to such conditions through better signal processing image recognition software.
  • Thumbnail Image
    Item
    Reducing Winter Maintenance Equipment Fuel Consumption Using Advanced Vehicle Data Analytics
    (Minnesota Department of Transportation, 2023-01) Northrop, William; Challa, Dinesh Reddy; Eagon, Matthew; Wringa, Peter
    This project analyzes the impact that idling and snowfall have on the fuel consumed by MnDOT's snowplow fleet, with the underlying objective to determine and advise MnDOT on ways to reduce fuel usage of the fleet using vehicle telematics data. This is a significant problem to solve as fuel use reduction contributes to MnDOT?s sustainability goals of achieving a 30% reduction in fossil fuel use and greenhouse gas (GHG) emissions from 2005 levels by 2025. Furthermore, rising fuel costs are a future cause for concern due to an increase in business operational costs that increases the burden on taxpayers to keep roads safe in winter. This problem is challenging because existing on-board diagnostics (OBD) data do not contain mass information for the trucks' fuel use, which can fluctuate significantly when they are applying deicing substances to the road. Taking a mean value for the vehicle mass, we observe a clear positive correlation between snowfall and average fuel use. For days with snowfall totaling 4 inches or more, fuel use rises more than 25% on average compared to days without snowfall. In addition, the results from the idling analysis indicate that the idling time associated with the fleet is about 23% of total recorded hours and constitutes about 4.3% of the total fuel used. Daily idling activity reports containing information about idling events and fuel economy are generated for the sampled vehicles and shared with MnDOT.
  • Thumbnail Image
    Item
    Waste to Energy Prime Mover Efficiencies for Commercially Available Technology
    (2020-03-27) Lasode, Aduramo; Northrop, William; lasod002@umn.edu; Lasode, Aduramo; University of Minnesota Thomas E Murphy Engine Lab
    The data provides a collected set of information on electric power rating and efficiency for commercially available prime movers in waste to energy applications. The five main technologies in focus are: steam turbines, gas turbines, microturbines, reciprocating internal combustion engines, and fuel cells (specifically solid oxide). The technology data points collected are systems that can use fuel with components from biogas (methane, hydrogen, etc) generated during anaerobic waste treatment. The data set provides a commercial preview of each technology that could guide potential use in different ranges based on desired electric output (and required power input).