Abstract
The path choice behavior of battery electric vehicle (BEV) drivers is influenced by the lack of public charging stations, limited battery capacity, range anxiety and long battery charging time. This paper investigates the congestion/flow pattern captured by stochastic user equilibrium (SUE) traffic assignment problem in transportation networks with BEVs, where the BEV paths are restricted by their battery capacities. The BEV energy consumption is assumed to be a linear function of path length and path travel time, which addresses both path distance limit problem and road congestion effect. A mathematical programming model is proposed for the path-based SUE traffic assignment where the path cost is the sum of the corresponding link costs and a path specific out-of-energy penalty. We then apply the convergent Lagrangian dual method to transform the original problem into a concave maximization problem and develop a customized gradient projection algorithm to solve it. A column generation procedure is incorporated to generate the path set. Finally, two numerical examples are presented to demonstrate the applicability of the proposed model and the solution algorithm.
Highlights
Battery electric vehicles (BEVs) have received much attention in the past few years due to their advantages in reducing greenhouse gas emissions, noise pollution, reliance on fossil oil and improving the efficiency of electricity grid by vehicle-to-grid technology [1]
This paper works on the stochastic traffic assignment models with battery capacity constraints, where new path-constrained stochastic user equilibrium (SUE) traffic assignment problem is formulated, solved and numerically analyzed
The method considers a flow-depend energy consumption assumption for battery electric vehicles (BEV), which is a generalization of flowindependent driving distance constraint
Summary
OPEN ACCESS Citation: Jing W, Ramezani M, An K, Kim I (2018) Congestion patterns of electric vehicles with limited battery capacity. The path choice behavior of battery electric vehicle (BEV) drivers is influenced by the lack of public charging stations, limited battery capacity, range anxiety and long battery charging time. This paper investigates the congestion/flow pattern captured by stochastic user equilibrium (SUE) traffic assignment problem in transportation networks with BEVs, where the BEV paths are restricted by their battery capacities. The BEV energy consumption is assumed to be a linear function of path length and path travel time, which addresses both path distance limit problem and road congestion effect. A mathematical programming model is proposed for the path-based SUE traffic assignment where the path cost is the sum of the corresponding link costs and a path specific out-of-energy penalty.
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