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Article
Intelligent Vehicle Fuel Saving Technologies: Comparing Three Primary Categories of Methods
American Society of Mechanical Engineers Dynamic Systems and Control Conference
  • Danielle Fredette, Cedarville University
  • Junbo Jing
  • Ümit Özguner, The Ohio State University
Document Type
Conference Presentation
Location
Columbus, OH
Event Date
10-28-2015
Keywords
  • Fuels,
  • vehicles
Abstract
In recent years, numerous control algorithms for connected and automated vehicles have emerged which focus on modifying driving strategy in order to reduce fuel usage. Referred to as “dynamic eco-driving,” these technologies have realized the possibility for additional fuel savings by utilizing information technologies rather than mechanics. The exact methodologies, however, are diverse. Three primary categories of dynamic eco-driving methodologies are identified and described: 1) ad-hoc methods, designed for the purpose of saving fuel but not considering optimality, 2) classical optimization methods, which use fuel usage modeling to solve an optimal control problem forwards in time, whether numerically or analytically, and 3) optimization by dynamic programming, in which a fuel usage-oriented cost function is minimized but solved backwards in time in discrete steps. Representatives from each of these categories are studied and implemented in simulation for comparison. Advantages and disadvantages of each relative to multiple performance measures are discussed.
Citation Information
Danielle Fredette, Junbo Jing and Ümit Özguner. "Intelligent Vehicle Fuel Saving Technologies: Comparing Three Primary Categories of Methods" American Society of Mechanical Engineers Dynamic Systems and Control Conference (2015)
Available at: http://works.bepress.com/danielle-fredette/4/