scholarly journals En-Route Battery Management and a Mixed Network Equilibrium Problem Based on Electric Vehicle Drivers’ En-Route Recharging Behaviors

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4061
Author(s):  
Kai Liu ◽  
Sijia Luo ◽  
Jing Zhou

With the rapidly increasing number of electric vehicle users, in many urbans transport networks, there are mixed traffic flows (i.e., electric vehicles and gasoline vehicles). However, limited by driving ranges and long battery recharging, the battery electric vehicle (BEV) drivers’ route choice behaviors are inevitably affected. This paper assumes that in a transportation network, when BEV drivers are traveling between their original location and destinations, they tend to select the path with the minimal driving times and recharging time, and ensure that the remaining charge is not less than their battery safety margin. In contrast, gasoline vehicle drivers tend to select the path with the minimal driving time. Thus, by considering BEV drivers’ battery management strategies, e.g., battery safety margins and en-route recharging behaviors, this paper developed a mixed user equilibrium model to describe the resulting network equilibrium flow distributions. Finally, a numerical example is presented to demonstrate the mixed user equilibrium model. The results show that BEV drivers’ en-route recharging choice behaviors are significantly influenced by their battery safety margins, and under the equilibrium, the travel routes selected by some BEV drivers may not be optimal, but the total travel time may be more optimal.

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Chenming Jiang ◽  
Linjun Lu ◽  
Junliang He ◽  
Caimao Tan

Adverse weather condition is one of the inducements that lead to supply uncertainty of an urban transportation system, while travelers’ multiple route choice criteria are the nonignorable reason resulting in demand uncertainty. This paper proposes a novel stochastic traffic network equilibrium model considering impacts of adverse weather conditions on roadway capacity and route choice criteria of two-class mixed roadway travellers on demand modes, in which the two-class route choice criteria root in travelers’ different network information levels (NILs). The actual route travel time (ARTT) and perceived route travel time (PRTT) are considered as the route choice criteria of travelers with perfect information (TPI) and travelers with bounded information (TBI) under adverse weather conditions, respectively. We then formulate the user equilibrium (UE) traffic assignment model in a variational inequality problem and propose a solution algorithm. Numerical examples including a small triangle network and the Sioux Falls network are presented to testify the validity of the model and to clarify the inner mechanism of the two-class UE model under adverse weather conditions. Managerial implications and applications are also proposed based on our findings to improve the operation efficiency of urban roadway network under adverse weather conditions.


1970 ◽  
Vol 25 (2) ◽  
pp. 119-125 ◽  
Author(s):  
Xin Wang ◽  
Hai-Jun Huang

For an elastic demand transportation network with continuously distributed value of time, the system disutility can be measured either in time units or in cost units. The user equilibrium model and the system optimization model are each formulated in two different criteria. The conditions required for making the system optimum link flow pattern equivalent to the user equilibrium link flow pattern are derived. Furthermore, a bi-objective model has been developed which minimizes simultaneously the system travel time and the system travel cost. The existence of a pricing scheme with anonymous link tolls which can decentralize a Pareto system optimum into the user equilibrium has been investigated.


Author(s):  
Shengxue He ◽  
Bingquan Fan

Regional transportation can be regarded as a complex system consisting of many subsystems. If it is assumed that the decisions of others are known, one of the subsystems, such as a manufacturer, will make decisions from the viewpoint of individual optimal. But among these subsystems, there are noncooperative interactions. The first Wardrop principle can be used to explain the interplay between the subsystems and the second Wardrop principle to explain the internal decision making of one subsystem. To capture the feature of hierarchical behavior, classical Wardrop principles need to be generalized. The new behavior principle is named the generalized Wardrop principle. With the substitution of actual path sets for the simple links in a spatial price equilibrium network and constructing the generalized transportation cost functions, the regional transportation network equilibrium model is formulated. The new model combines the spatial price equilibrium model with the network optimization model. It can be explained by the generalized Wardrop principle and reflects the multicommodity, multimodal characteristics of regional transportation. The modified projection algorithm is used to solve the model. One numerical example is given to show the efficiency of the algorithm.


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