A Comparative Study of Different Objectives Functions for the Minimal Fuel Drive Cycle Optimization in Autonomous Vehicles

[+] Author and Article Information
Niket Prakash

Graduate Student Research Assistant, Lay Automotive Laboratory, University of Michigan, 1231 Beal Ave, Ann Arbor, Michigan 48109

Youngki Kim

Assistant Professor, Mechanical Engineering, University of Michigan, 4901 Evergreen Road, Dearborn, Michigan 48128

Anna G. Stefanopoulou

Professor of Mechanical Engineering, Lay Automotive Laboratory, University of Michigan, 1231 Beal Ave, Ann Arbor, Michigan 48109

1Corresponding author.

ASME doi:10.1115/1.4043189 History: Received May 05, 2018; Revised March 08, 2019


With the advent of self-driving autonomous vehicles, vehicle controllers are free to drive their own velocities. This feature can be exploited to drive an optimal velocity trajectory that minimizes fuel consumption. Two typical approaches to drive cycle optimization are velocity smoothing and tractive energy minimization. The former reduces accelerations and decelerations and hence it does not require information of vehicle parameters and resistance forces. On the other hand, the latter reduces tractive energy demand at the wheels of a vehicle. In this work, utilizing an experimentally validated full vehicle simulation software, we show that for conventional gasoline vehicles the lower energy velocity trajectory can consume as much fuel as the velocity smoothing case. This implies that the easily implementable, vehicle agnostic velocity smoothing optimization can be used for velocity optimization rather than the non-linear tractive energy minimization, which results in a pulse-and-glide trajectory.

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