Journal of Jilin University(Engineering and Technology Edition) ›› 2021, Vol. 51 ›› Issue (5): 1684-1691.doi: 10.13229/j.cnki.jdxbgxb20200421

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Mixed traffic network equilibrium with battery electric vehicles considering charging queuing time

Hao LI1,2(),Hao CHEN1,2   

  1. 1.College of Transportation Engineering，Tongji University，Shanghai 201804，China
    2.Key Laboratory of Road and Traffic Engineering of the Ministry of Education，Tongji University，Shanghai 201804，China
  • Received:2020-06-11 Online:2021-09-01 Published:2021-09-16

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Abstract:

In order to analyze the influence of charging queuing time on the path selection of electric vehicle users and network equilibrium， a mixed traffic network model was established by considering the charging queuing time in relation to charging flows and charging time in relation to the charging amount. We proved the uniqueness of the solution and derived the KKT conditions corresponding to the mixed traffic network equilibrium， which was proven to be equivalent to the Wardrop's first principle. The solution algorithm was designed based on the gradient projection method and an example network was tested to verify the effectiveness of the model and the algorithm. The research results show that the charging flow distribution among charging stations corresponding to the optimal solution under the fixed queuing time is not unique， while it is unique under the non-fixed queuing time. With the non-fixed queuing time， charging flows distribute more evenly among charging stations as travelers try to avoid excessive charging queuing time； Service capacity of charging stations has a significant impact on the balance of the utilization rates of charging stations； Total charging queuing time and total trip time gradually decrease as the service capacity of charging stations increases.

Key words: transportation planning and management, mixed traffic network equilibrium, battery electric vehicles, gradient projection method, charging queuing time, service capacity

CLC Number: 

  • U491.2

Fig.1

Hypothetical network"

Fig.2

Charging flow distribution among charging stations under the fixed queuing time"

Fig.3

Charging flow distribution among charging stations under non-fixed queuing time"

Fig.4

Charging flow at different charging stations in relation to the service capacity of node 7"

Fig.5

Indicator B in relation to service capacity of node 7"

Fig.6

Total travel time， total charging queuing time， total charging time， and total trip time in relation to service capacity of charging stations"

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