T3e Webinar Overview

Energy-Efficient Adaptive Cruise Control for Electric Connected and Autonomous Vehicles

View Webinar: link to this webinar's archive materials

Date: Thursday, March 8, 2018
Time: 1:00 PM – 2:00 PM EST
Cost: All T3e webinars are free of charge
PDH: 1.0 View PDH Policy

T3e Webinars are brought to you by the Intelligent Transportation Systems (ITS) Professional Capacity Building (PCB) Program of the U.S. Department of Transportation’s (U.S. DOT) ITS Joint Program Office (JPO). The purpose of this webinar series is to provide a platform for students to share their research findings. References in this webinar to any specific commercial products, processes, or services, or the use of any trade, firm, or corporation name is for the information and convenience of the public, and does not constitute endorsement, recommendation, or favoring by the U.S. DOT.


Background

This presentation proposes an energy-efficient adaptive cruise control, called Energy-Efficient Electric Driving Model (E3DM), for electric, connected, and autonomous vehicles (e-CAVs) in a traffic stream with mixed autonomous and human-driven vehicles. E3DM is able to maintain high energy efficiency of regenerative braking by adjusting the spacing between the leading and the following vehicles. Moreover, a power-based energy consumption model is proposed to estimate the on-road energy consumption for battery electric vehicles, considering the impact of ambient temperature on auxiliary load. Using the proposed energy consumption model, the impact of E3DM on vehicle energy consumption is investigated. In particular, single-lane vehicle dynamics in a traffic stream with mixed e-CAVs and human-driven vehicles are simulated. The result shows that E3DM outperforms existing adaptive cruise control strategies based on Intelligent Driver Model (IDM-ACC) and the Nissan Model (Nissan-ACC) in terms of energy consumption. Moreover, higher market penetration of e-CAVs may not result in better energy efficiency of the entire fleet. The reason is that more e-CAVs in the traffic stream results in faster string stabilization which decreases the regenerative energy.

Learning Objectives

Upon completion of this webinar, the audience will understand:

  • What is energy-efficient adaptive cruise control for CAVs
  • The energy consumption characteristics of battery electric vehicles
  • How e-CAVs affect energy efficiency of a platoon

Target Audiences

Transportation professionals and researchers who are interested in eco-driving, electric vehicles, and connected and autonomous vehicles will find this seminar of interest.

Host

Dr. Jing Dong, Assistant Professor, Iowa State University
Jing Dong Dr. Jing Dong is an Assistant Professor of Civil Engineering in the Department of Civil, Construction, and Environmental Engineering at Iowa State University. She also is a Transportation Engineer for the Center for Transportation Research and Education at ISU’s Institute for Transportation (Intrans). Before joining ISU, she worked at the U.S. Department of Energy’s Oak Ridge National Laboratory as a research staff member from 2010 to 2012. Dr. Dong specializes in network modeling and optimization, traffic flow theory, intelligent transportation systems, and transportation energy analysis.

Presenters

Dr. Chaoru Lu, Postdoctoral Fellow, Norwegian University of Science and Technology
Chaoru Lu Dr. Chaoru Lu received a BS in Civil Engineering from Hunan University of Science and Technology, Xiangtan, China, in 2011, an MS in Civil Engineering from Texas A&M University-Kingsville, TX, in 2014, and a PhD in Civil Engineering from Iowa State University, Ames, IA, in 2017. He is currently a Postdoctoral Fellow at Norwegian University of Science and Technology. His research interests include connected and automated vehicles, traffic flow theory, and intelligent transportation systems.

Mr. Liang Hu, Ph.D. Student, Iowa State University
Liang Hu Liang Hu is a PhD student in Civil Engineering at Iowa State University. His research focuses on the transportation problems of plug-in electric vehicles, autonomous vehicles, ride-sharing, taxi operation, and eco-driving.

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