01593880

Component

This paper concentrates on the impacts of stochastic driving distance limits on equilibrium flows of networks serving electric vehicles suffering from “range anxiety” issue derived from limited battery capacity, insufficient coverage of charging infrastructure and varying driving conditions. The authors proposed two network equilibrium models that respectively embrace discrete and continuous stochastic distance limits on trip chains consisting of activity nodes and travel links. The two models are both written in the convex programming form with finite number of constraints. Though Model II is more reasonable due to the continuous nature of stochastic distance limits, Model I has a relatively simple structure compared to Model II. Both models are then solved by the Frank-Wolfe algorithm, where efficient network loading processes are schemed for the two models based on the solving of the distance-constrained, node-sequenced shortest path subproblem. Furthermore, the numerical results reveal that as the increase of the number of discrete constraint classes in a given type and range, the network equilibrium results derived from the discrete model converge to the equilibrium results from the continuous model with its constraint distributed in the same type and range. It is also proved that Model II has a better computational performance than Model I with the proposed solution methods.

This paper was sponsored by TRB committee ADC80 Standing Committee on Alternative Transportation Fuels and Technologies.

01584066

16-5510

English

20p

2016

Transportation Research Board 95th Annual Meeting

Digital/other

Figures; References; Tables

Distance; Driving; Electric vehicles; Equilibrium (Systems); Trip chaining; Vehicle range

Highways; Planning and Forecasting

Transportation Research Board Annual Meeting 2016 Paper #16-5510

TRIS, TRB, ATRI

Jan 12 2016 6:24PM