01558340

Component

This study investigates the routing aspects of electric vehicle (EV) users and their effects on the overall traffic network performance. EVs are classified as battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). This study focuses on BEVs. BEVs have some unique characteristics such as long battery recharging time, and recuperation of energy lost during the deceleration phase if equipped with regenerative braking systems. This raises two interesting questions: (i) whether the energy recuperation characteristics of BEVs will lead to different route selection compared to conventional internal combustion engine vehicles (ICEVs), and (ii) whether such route selection implications of BEVs will affect the network performance. With the increasing market penetration of BEVs, these questions are becoming increasingly important. The study formulates a multi-class dynamic user equilibrium (DUE) model to determine the equilibrium flows for a traffic system consisting of a mix of BEVs and ICEVs. A simulation- based framework is used to obtain the solution of the DUE problem. Results from computational experiments on a test network illustrate that the dominantly selected routes by BEV drivers are different from ICEV drivers as BEV drivers may select congested routes to recuperate battery charge while ICEV drivers focus on routes minimizing their travel time. Hence, BEV drivers may select routes with more congestion characteristics so that the start-and-stop phenomena associated with such routes can recuperate the energy at a better rate, implying increased energy efficiency for the chosen route. This has implications for the overall network performance, in that it can synergistically move the traffic system towards optimal performance as the congestion and energy imperatives of ICEVs and BEVs, respectively, are traded off.

This paper was sponsored by TRB committee ADB30 Transportation Network Modeling.

01550057

15-5426

English

0000-0002-3454-0799

17p

2015

Transportation Research Board 94th Annual Meeting

Digital/other

Figures; References; Tables

Electric vehicle charging; Electric vehicles; Energy consumption; Internal combustion engines; Optimization; Regenerative braking; Route choice; Traffic congestion; Traffic equilibrium

Dynamic user equilibrium; Traffic network performance

Energy; Highways; Planning and Forecasting; Vehicles and Equipment; I72: Traffic and Transport Planning; I90: Vehicles

Transportation Research Board Annual Meeting 2015 Paper #15-5426

TRIS, TRB, ATRI

Dec 30 2014 1:49PM