Demonstration of Ego Vehicle and System Level Benefits of Eco-Driving on Chassis Dynamometer Southwest Research Institute

Format:

Book

Conference/Event

Author/Creator:

Bhagdikar, Piyush, author.

Contributor:

Gankov, Stanislav

Rengarajan, Sankar

Sarlashkar, Jayant

Conference Name:

WCX SAE World Congress Experience (2023-04-18 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2023

Summary:

Eco-Driving with connected and automated vehicles has shown potential to reduce energy consumption of an individual (id est, ego) vehicle by up to 15%. In a project funded by ARPA-E, a team led by Southwest Research Institute demonstrated an 8-12% reduction in energy consumption on a 2017 Prius Prime. This was demonstrated in simulation as well as chassis dynamometer testing. The authors presented a simulation study that demonstrated corridor-level energy consumption improvements by about 15%. This study was performed by modeling a six-kilometer-long urban corridor in Columbus, Ohio for traffic simulations. Five powertrain models consisting of two battery electric vehicles (BEVs), a hybrid electric vehicle (HEV), and two internal combustion engine (ICE) powered vehicles were developed. The design of experiment consisted of sweeps for various levels of traffic, penetration of smart vehicles, penetration of technology, and powertrain electrification. The large-scale simulation study consisted of doing approximately 96,000 powertrain simulations. A sophisticated clustering scheme was built and utilized to down select representative traces for each scenario from the simulation study for vehicle testing on a chassis dynamometer. This paper provides a summary of individual ego vehicle testing as well as a comprehensive overview of the method utilized for down selecting representative traces from large scale simulation studies that can be used to quantify corridor level benefits. Vehicle test results along with corresponding analyses are presented

Notes:

Vendor supplied data

Publisher Number:

2023-01-0219

Access Restriction:

Restricted for use by site license