Congestion patterns of electric vehicles with limited battery capacity
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.</div- Dataset
- Dataset
- Evolutionary Biology
- Developmental Biology
- Statistics
- Science Policy
- Biological Sciences not elsewhere classified
- Mathematical Sciences not elsewhere classified
- Chemical Sciences not elsewhere classified
- road congestion effect
- traffic assignment problem
- path-based SUE traffic assignment
- BEV energy consumption
- gradient projection algorithm
- path distance limit problem
- path travel time
- path choice behavior
- column generation procedure
- battery capacity